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Brief Summary of Minutes

NRSP-8 Business Meeting
Date January 12, 2014

1. Call to order by Milt Thomas (roughly 5:15pm), with Stephen White serving as the secretary.

2. Coordinator Reports

Milt Thomas called on each species coordinators to give their report. The allotted time for each report was shortened due to the need to use the room to prepare for the opening session of PAG. Thus, below is a list of the species reports. The specifics of each report were submitted in their annual report. Notable highlights of these 7 reports follows the list.

a. Equine – Ernie Bailey

b. Swine – Chris Tuggle and Cathy Ernst

c. Aquaculture – Caird Rexroad (in place of John Liu)

d. Cattle – Juan Medrano, Alison Van Eenennaam, Jerry Taylor

e. Sheep/Goat – Stephen White

f. Poultry – Mary Delany

g. Bioinformatics – James Reecy

Notable highlights: Many of the species groups have included or expanded the number of Co-Coordinators. The complete list of coordinators and co-coordinators now includes: Equine – Ernest Bailey, Molly McCue, Samantha Brooks; Swine – Chris Tuggle, Cathy Ernst; Aquaculture – John Liu, Caird Rexroad III; Cattle – Juan Medrano, Jerry Taylor, Alison Van Eennaam; Sheep/Goat – Noelle Cockett, Stephen White; Poultry – Mary Delany, Hans Cheng; Bioinformatics – James Reecy, Max Rothschild, Susan Lamont, Chris Tuggle, Fiona McCarthy. Multiple genome assembly improvement and high density genotyping projects are under way, and the sheep reference genome assembly paper has been submitted for publication. Multiple species groups also expressed enthusiasm for AgENCODE projects amid discussion following the white paper meeting that preceded the weekend meeting.

3. Administrator reports

a. Eric Young

Eric stated that the renewal of NRSP8 had gone extremely well, with no edits or changes recommended. The budget has also been approved. There will now be a 5 year approval process with a mid-term review in year 3. This review will be dependent on the success documented in the annual reports. Thanks to Tom Porter, Milt Thomas and the writing committee. Finally, Eric reminded everyone that the current report will be the project-end report for the terminating NRSP8 project (2008-2013), so project reports need to include accomplishment summaries over the whole project period.

b. Lakshmi Matukumalli

Due to funding restrictions, Lakshmi did not attend but sent his apologies.

4. Call for old business: no items requested or presented.

5. Call for new business: Noelle Cockett spoke about AgENCODE and steps that will contribute to its success.

a. Steve Ellis had mentioned an NSF call for comments from the community about next funding priorities. Jim Reecy will provide notice on AngenMap. Community feedback on the importance of regulatory element identification across taxa will be important, but those that respond need to keep in mind the scientific priorities of NSF do not explicitly include agricultural production.

b. Also, NRSP8 is planning to host a meeting year in the Washington, DC area in the first half of 2014 to help coordinate international efforts and funding sources for AgENCODE. A committee including Chris Tuggle, Joan Lunney, and Stephen White will be advancing this effort.

6. Nominations for next business meeting: no items requested or presented. Location confirmed as San Diego for next year.

7. Nominations for Secretary/Chair-elect:

Joan Lunney nominated Daniel Ciobanu of University of Nebraska for the Secretary in 2015 and Chair in 2016. Second was obtained from Susan Lamont and the motion passed unanimously. Daniel had been notified of the intention to nominate and had agreed to accept the nomination prior to the business meeting.

8. "pass the gavel" to Stephen White:

After passing the gavel, the NRSP8 community thanked Milt Thomas for his leadership in the last year during a time of transition for the NRSP8 projects.

9. Meeting adjourned



Minutes prepared by Stephen White, 02/05/2014.

Accomplishments

OBJECTIVES<br /> Objective 1: Create shared genomic tools and reagents and sequence information to enhance the understanding and discovery of genetic mechanisms affecting traits of interest.<br /> Objective 2: Facilitate the development and sharing of animal populations and the collection and analysis of new, unique and interesting phenotypes.<br /> Objective 3: Develop, integrate and implement bioinformatics resources to support the discovery of genetic mechanisms that underlie traits of interest.<br /> <br /> Aquaculture Technical Report<br /> <br /> Objective 1:<br /> Catfish: The channel catfish genome assembly has been improved by changing the assembly algorithm from ABySS to MaSuRCA. The current version of the catfish genome assembly (v1.1) has 95% of the channel catfish genome sequences spanning 780.7Mb in 46,936 contigs and 8,597 scaffolds. We are continuing to work with the developers of Celera Assembler to optimize assembly of long PacBio and Illumina reads. The catfish genome was annotated using transcriptome sequencing. Through transcriptome analysis of various tissues, a total of over 23,000 complete cDNAs have been assembled and annotated. Gene families and gene duplications were analyzed. A draft genetic linkage map from 3-generation families has been produced and is currently analyzed and will be used to assist genome assembly. A 250K SNP array based on Affymetrix Axiom technology has been constructed.<br /> <br /> Oyster: The transcriptome of an adult Eastern oyster (Crassostrea virginica) was sequenced with short Illumina reads and assembled into 66,229 contigs. The de novo assembly covers 90% of published ESTs and a set of ~40K contigs have been annotated using public databases. 657 genes related to innate immunity have been identified. RNA sequencing of C. virginica samples collected before and after the Deep Water Horizon oil spill resulted in a de novo transcriptome assembly where 9,469 transcripts were homologous to Pacific oyster transcripts. RNA seq data are being used to identify potential effects of oiled water and sediments on the Eastern oyster. A Crassostrea gigas fosmid library was constructed that contains 459,936 clones representing 22.34-fold haploid genome equivalents. End sequencing revealed over 6000 sequences with open reading frames e 300 bp, 1 million SNPs, and 3200 SSRs. Fifty-six SNPs were identified in C. gigas sequences mined from the EST database. Forty-two SNPs conform to Hardy-Weinberg Equilibrium and 28 are polymorphic in a full-sib family, suggesting these SNPs will be useful for pedigree analysis, association studies and marker assisted selection.<br /> <br /> Salmonids: To identify genes and gene products that are essential in the regulation of embryonic development in rainbow trout, RNA-Seq analysis was performed on eight RNA samples isolated from developing embryos. There are 2,020 transcripts that are only expressed in embryos before cell division, and 34 genes that start to express in 3d embryos, the onset of maternal zygotic transition in rainbow trout. In addition, a total of 50,351 novel transcripts were identified from the dataset, and 3,329 to 17,312 splice variants were observed at different stages of embryonic development. The first rainbow trout high density 57K SNP chip was developed and characterized. Approximately 50K of the SNPs were validated in a panel of 18 rainbow trout populations at the standard 97% call rate of the Affymetrix SNP polisher software.<br /> <br /> Striped Bass: Genomic DNA (30.52 Gb) sequenced from 4 domesticated striped bass was assembled into ~517 Mb comprised of 71,500 contigs averaging 7 Kb, with several over 80Mb and one >100 Mb. Contig coverage is generally 30X, with fewer than 10 contigs >400X, suggesting the genome is near 600 Mb, similar to the confamilial European sea bass. Over 200 million unique sequences of small RNAs from ovarian tissues were obtained, with most representing piRNAs expressed in early oogenesis, including ~400 miRNAs known to regulate transcript translation and degradation. Striped bass and white bass are the parental species of the hybrid striped bass (white bass,Morone chrysops X striped bass, M. saxatilis). Major tissues and organs (brain, liver, spleen, kidney, ovary, testes, etc) from 10 individuals from each species (5 male and 5 female) were harvested and RNA sequenced in a lane of Illumina HiSeq2000. A total of 262 x 106 high quality reads were obtained with 135 x 106 reads from striped bass and 127 x 106 reads from white bass. Reads were assembled into 203,587 striped bass contigs and 185,531 white bass contigs. Annotation was carried out by BLAST against the UniProt and nr databases for both species. Again, similar results were obtained from both species, with 18,630 UniProt and 23,605 nr annotated unigenes in striped bass and 18,584 UniProt and 22,354 nr annotated unigenes in white bass. <br /> <br /> Objective 2:<br /> Catfish:Bulked segregant RNA-seq (BSR-Seq) was used to analyze differentially expressed genes and associated SNPs with disease resistance against enteric septicemia of catfish (ESC). A total of 1,255 differentially expressed genes were found between resistant and susceptible fish. In addition, 56,419 SNPs were identified as significant SNPs between susceptible and resistant fish located on 4,304 unique genes. Detailed analysis of these significant SNPs allowed differentiation of significant SNPs caused by genetic segregation and those caused by allele-specific expression. Mapping of the significant SNPs, along with analysis of differentially expressed genes, allowed identification of candidate genes underlying disease resistance against ESC. Genotyping-by-sequencing was conducted on individuals from populations of wild and aquacultured blue catfish. Markers were validated and extended using multiplex Sequenom MassArray assays and should be useful in follow up studies of the diversity of cultured blue catfish populations and in parentage studies. In-depth transcriptome sequencing of channel catfish resistant and susceptible to Flavobacterium columnare as well as microbiome sequencing of channel, blue, and hybrid catfish mucosal tissues. <br /> <br /> Oyster: Sequence polymorphisms and differential gene expression patterns were identified that can distinguish among two C. gigas lines exhibiting either high or low survival with respect to summer mortality.<br /> <br /> Salmonids: Several studies were completed to investigate genetic variation of multiple salmonid species including Chinook salmon, steelhead/rainbow trout, and cutthroat trout. Studies included investigation into the genetic basis for traits such as thermal adaptation and migration. QTL mapping families for stress response and bacterial cold water resistance in rainbow trout that were previously genotyped with microsatellites, were re-genotyped with ~5,000 restriction-site associated DNA (RAD) SNPs. The major microsatellite QTL were validated by the new RAD SNPs linkage maps. Sequence information from the RAD SNPs is useful for aligning the QTL with sequence contigs from the rainbow trout draft genome assembly in an effort to identify positional candidate genes.<br /> <br /> Striped Bass: Novel supervised machine learning analyses identified networks of expressed ovarian genes and proteins that collectively function to determine a complex phenotype, egg quality. Artificial neural networks (ANNs) were used to reveal a powerful relationship (R2 >90%) between profiles of maternal ovary gene expression and subsequent egg fertility in wild and domestic striped bass. RNAseq data from the same fish is being mined for single nucleotide polymorphisms (SNPs) to determine if there is a genetic basis for egg quality. K-means clustering and support vector machines (SVMs) were applied to quantitative tandem mass spectrometry data to reveal a strong relationship (R2 >83%) between ovarian stage and protein profiles during the annual reproductive cycle. <br /> Objective 3:The aquaculture community works with the Bioinformatics Coordinator to develop species-specific resources, such as those included in the Animal QTLdb. Large sequence databases are also publicly available at www.animalgenome.org/aquaculture/database/. <br /> <br /> Oyster: SQLShare has been used to store, distribute, and query large genomic datasets from the Pacific oyster. Details of this project, including tutorials for the freely available resource are available at: github.com/sr320/qdod/wiki.<br /> <br /> Salmonids: The working draft of the rainbow trout genome assembly reported in 2012 was placed on the animalgenome.org web site hosted by the NRSP-8 Bioinformatics Coordinators. It is now available for downloading by the general public. In addition, an excel file with the genome location of the 145K RAD SNPs dataset reported in 2012 is available from the same web site and as an appendix file from the journal of Molecular Ecology Resources.<br /> <br /> Striped Bass: A new high performance computing cluster dedicated to NGS analysis in studies of striped bass. This new cyberinfrastructure, built around the open source scientific computing platform  Galaxy, was used successfully to assemble an ovarian transcriptome from RNA-seq data. <br /> <br /> Cattle Technical Report<br /> <br /> Objective 1:<br /> Bovine Genome sequence: An important focus of the community has been towards improving the bovine genome assembly. There are several actively funded efforts in this directions and the expectation is to have new updates on the assembly in 2014. The Bovine Genome Improvement Consortium was formed, which is a group of scientists working to improve the bovine reference genome assembly and its annotation. Multiple data types have been or are in the process of being generated, such as an optical map, Illumina paired-end and mate-pair sequence, PacBio sequence, and improved gene predictions based on RNA-seq data. All of the data will be derived from tissue samples from L1 Dominette 01449, the reference animal. The goal of the group is a single reference genome sequence with fewer gaps, misassemblies, and missing genes. The consortium held a conference call November 21, 2013 to coordinate efforts between various projects and will be meeting at PAG in January 2014. <br /> <br /> The specific efforts currently underway and supported by NIFA grants are: 1) David Schwartz and Shigou Zhou (University of Wisconsin, Madison): Currently the optical map has 76 contigs. It covers 97% of the genome (based on UMD3.1 and Btau 4.6. reference genomes), with a genome coverage of 447x. It has 8.9 kb average fragment size, with an average contig size of 34 Mb. The optical map can be compared to any assembly of the Dominette reference genome and will report back any discordances (likely misassemblies) of any kind and can also place unmapped contigs. Overall both assemblies are in reasonable shape, but the optical map will contribute significantly to their improvement. 2) Chris Elsik (University of Missouri) will create a dedicated page at www.bovinegenome.org to direct people towards the efforts of improving the bovine genome reference. Jim Reecy will mirror the information from the Animal Genome website. 3) Kim Worley (Baylor College of Medicine, Houston, TX) is using long PacBio reads to improve the assembly. The target is to develop a 10X PacBio coverage for both the sheep and cattle genomes and use PBJelly software (developed in-house at Baylor) to fill gaps and improve scaffolds. 4) Jared Decker (University of Missouri, Columbia): Aleksey Zimin and others will generate the new genome assembly of Dominette data (not currently NIFA supported). 5) Chris Elsik (University of Missouri, Columbia) will improve gene annotation using RNA-seq data, new software and visualization applications and community annotation. <br /> <br /> Objective 2: n/a<br /> <br /> Objective 3:<br /> Bioinformatics and database resources: Dr. Harvey Blackburn at USDA-ARS National Animal Germplasm Program (NAGP) and the Colorado State University Agricultural Experimental Station have joined efforts to begin the development of genomic databases that will serve as a repository for DNA data from the large animal genomics projects funded by AFRI, the dairy and beef industry, and other large projects that may have valuable data that need permanent archiving for future research. This effort, coupled with the existing capacities to store phenotypic and production system data in Animal-GRIN as well as germplasm/tissue samples, will facilitate the communities efforts to maintain valuable data for future use. Database and bioinformatics activities are also coordinated by Jim Reecy (NRSP8 Bioinformatics Coordinator) at the NAGRP site (http://www.genome.iastate.edu/cattle/). <br /> <br /> Swine Technical Report<br /> <br /> Objective 1:<br /> Genome Map Development Update: New gene markers continue to be identified with the development of the 60K SNP chip and GWAS and sequencing efforts. The 60KSNP chip information can be integrated with the development of Build 10.2 as maps now are based on the pig sequencing efforts.<br /> <br /> Shared Materials and Funding:The Pig Genome Coordinator has recently supported community activities to find associations with many different traits. In FY 2013, several projects including those for disease resistance, reproduction and meat quality were supported. This brings the total to well over 3,000 chips/genotyping for those several projects from 2009-2013.<br /> <br /> Porcine SNP chip update: Illumina and the International Porcine SNP Chip Consortium developed a porcine 60K+ SNP and has shipped it to many researchers worldwide. The original publication was Ramos et al. 2009. Prices for the chip have been dropping and are reasonable. A new custom low density chip is now available for imputation work. GeneSeek, a supplier of genotyping services has announced the GeneSeek Genomic Profiler for Porcine LD (GGP-Porcine). This custom low density BeadChip utilizes Illumina Infinium chemistry and features approximately 8,500 SNPs for high density chip imputation. The GGP - Porcine BeadChip also includes gene markers from several well-known reproduction, growth, feed efficiency, and meat quality traits at no added expense. These include the following markers: EPOR, MC4R, HMGA, CCKAR, PRKAG,ESR, and CAST. Details on these markers will be available from GeneSeek. In addition, researchers can request additional markers including the HAL, Rendement Napole (RN), resistance marker to E.coli (F4 ab/ac), a SNP parentage panel, which impacts litter size in Large White or Yorkshire by paying additional royalty fees for these optional licensed tests. The chip was developed as a result of a collaborative effort involving leading academic, USDA, and GeneSeek researchers. The price (per sample) is about 40% of the cost of the 60K chip.<br /> <br /> Objective 2: n/a<br /> <br /> Objective 3:<br /> Database Activities: The Pig Genome Database continues to receive considerable updating. The <br /> Animal QTLdb included 1468 new pig QTL in during 2013(release #21), making the total number of pig QTL in the database 8,919., Throughout 2013, the NAGRP bioinformatics team has continued their efforts to make improvements to the Animal QTLdb, which includes a new mirror site in China, facilitate <br /> the addition of gene network analysis data, improved search tools and data analysis tools. Users are encouraged to register an account to enter new QTL data. Find out more from http://www.animalgenome.org/QTLdb . In addition, the pig genome build 10.2 annotations are continuing to be updated in the BioMart (http://www.animalgenome.org:8181) and for the Animal QTLdb.<br /> <br /> Poultry Technical Report<br /> <br /> Objective 1:<br /> Reference linkage map. Linkage mapping is now primarily via high throughput SNP assays. Very high density SNP mapping (ca. 600,000 SNP) panels have been developed and are being employed in genome-wide association studies and genome-wide marker-assisted selection (GMAS). Last year, 192 Affymetrix 600K genotypes were obtained from DNA Landmarks for various committee members using coordination funding.<br /> <br /> Physical and comparative maps. Physical mapping of the turkey genome is complete, involving construction of a detailed comparative chicken-turkey BAC contig comparative map. <br /> <br /> Chicken genome sequence. A new build, Galgal4.0, of the chicken genome sequence which combines the original reads, next generation sequencing (NGS) reads (Roche and Illumina) and the near-finished quality of the Z sequence done by Bellott et al. (Nature 466:612-616, 2010) was released late in 2011 and is now on browser sites. This still has not captured the roughly 5% of missing sequence (believed to be predominantly on the microchromosomes). Methods to fill gaps and obtain the missing sequence are being pursued (e.g., optical mapping, PacBio and Moleculo sequence methods, new assembly algorithms). Optical mapping and Moleculo sequencing of the reference genome was supported this year through coordination funds. In addition, Cobb-Vantress Inc. made a ~$150,000 commitment to this effort being led by The Genome Institute at Washington U., and additional support has been obtained this year from a USDA-NIFA-AFRI grant submission. A number of additional chicken genomes have been sequenced via NGS. This year coordination funds supported a project to sequence 19 different chicken lines of interest to NRSP-8 members. That project is currently in progress with data availability anticipated by the end of 2013. <br /> <br /> Turkey genome sequence. The Turkey Genome Sequencing Consortium generated a draft sequence of the turkey genome (Dalloul et al., PLoS Biology 8(9):e1000475, 2010) using a combination of NGS reads, along with the turkey BAC contig map noted above. Coordination funds were committed to aid in this effort which also enjoyed support from VaTech, BARC and U. of Minn., among others. Efforts are on-going to improve the annotation of genes and fill gaps in the turkey sequence, as funded by a subsequent AFRI grant.<br /> <br /> Chicken microarrays. Previously, coordination funds provided microarrays for transcriptional profiling and comparative genome hybridization. Some coordination support also was committed to Illumina RNA-sequencing and Agilent chip-based transcriptional profiling, partly in hopes of filling in missing sequences<br /> <br /> Objective 2: <br /> DNA from the East Lansing international reference mapping population has been sent to many laboratories throughout the world. Similarly, DNA from the junglefowl used to generate the reference sequence assembly has been widely distributed, especially for copy number variant studies.<br /> <br /> Objective 3:<br /> Database activities are led by the NRSP-8 Bioinformatics Coordinator, Jim Reecy, and Susan Lamont, along with Shane Burgess, represent poultry interests on the advisory committee for this group. Poultry bioinformatics has also benefitted from support at several other locations. We maintain a homepage for the NRSP-8 U.S. Poultry Genome project (http://poultry.mph.msu.edu) that provides a variety of genome mapping resources, including our newsletter archive. The Poultry Genome Newsletter is published quarterly and is distributed through our Homepage and on the angenmap email discussion group. <br /> <br /> Equine Technical Report<br /> <br /> Objective 1:<br /> Two major goals for the horse genome workshop have been improvement of the reference genome and development of a new assay tool for SNP analysis. Gene discovery is one of the main research areas for scientists in this section and problems with the current assembly were discussed at the previous PAG meetings and at a horse genome Workshop held during the July 2014 under the auspices of the Dorothy Russell Havemeyer Foundation. REFSEQ data helped to identify genes which had not been included in the assembly; REFSEQ data identified numerous differences between the genome annotation for the horse and the actual situation for the horse with regard to intron-exon structure and sequence; a gene for one trait was identified among sequences which had not been included in the assembly and relegated to chromosome UN. Toward the goal of improving the reference sequence, additional NEXTGEN DNA sequence was obtained for the reference horse, TWILIGHT, and compared to the annotated reference genome. Discrepancies between the assemblies suggested novel approaches that will be part of research grant designed to create a new assembly of the reference genome. Scientists at NCBI were contacted and stated that they have created and are continuing to develop processes to annotate a new assembly. A new assembly for the horse would be readily handled by these programs. The studies described above are subject of publications during the last year or will be published in the near future. <br /> <br /> Illumina SNP chips have been used extensively by workshop participants to make gene discoveries. The current tool (Illumina Equine SNP70) is about to expire and the workshop participants are collaborating to develop a new SNP assay tool using a format developed by Affymetrix, Inc. The earlier tools were based on SNPs discovered during the initial production of the reference sequence and are heavily biased towards SNPs found in Thoroughbred horses. The new chip is being designed based on SNPs detected in connection with NEXTGEN sequencing of more than 150 horses of diverse breeds. A set of 200 horses of diverse breeds will be tested with 2 million SNPs and a set of 670,000 SNPs will be selected for the final assay tool. The work began on this in 2013 and the tool will be available in the middle of 2014.<br /> <br /> Objective 2: <br /> The extent of variation among horses was assayed using the Illumina SNP50 chip by testing 814 horses of 36 different breeds. Workshop participants collaborated in a consortium to assemble DNA samples from horses of diverse breeds from around the world. SNPs were evaluated for information content they provided and a set of 10,536 used to construct trees reflecting the relationships among breeds as well as the efficacy of the set of SNPs to identify individual horses with their stated breed. The work was published in 2013. A second published study extended that work to investigate signatures of selection. <br /> <br /> Objective 3: <br /> During 2013 a committee was established to standardize and database nomenclature for horse genomics.<br /> <br /> Sheep/Goat Technical Report<br /> <br /> Objective 1:<br /> Develop high resolution genome maps for sheep: An ongoing project of the ISGC (international sheep genome consortium) is development of a whole genome reference assembly. In 2010, sequence data were generated at two sequencing facilities (Beijing Genomics Institute and the Roslin Institute) from DNA of a Texel ewe and a Texel ram, respectively. The first step of the reference sequence assembly involved de novo assembly of 75X reads from the Texel ewe into contigs and scaffolds. Once that was completed, sequences from both animals were used for gap filling. Version 2.0 of the ovine whole-genome reference sequence (Oar v2.0) was publicly released in February, 2011 and Oar v3.1 was released in October, 2012 through NCBI GenBank. For chromosome assemblies go to<br /> http://www.ncbi.nlm.nih.gov/assembly/GCA_000298735.1/ and for the full assembly, including scaffolds and contigs not assigned to chromosomes, go to<br /> http://www.livestockgenomics.csiro.au/cgi-bin/gbrowse/oarv3.1/<br /> <br /> To allow annotation by Ensembl, the ISGC has agreed not to release a new version of the assembly until late 2015, although update patches for some regions will likely be released before then. The RNA dataset produced by Roslin Institute and submitted to Ensembl is the largest transcriptome analysis of any species in Ensembl, including man. <br /> <br /> A manuscript describing the whole genome assembly (Oar v3.1), the RH map, and the linkage map is in preparation. Highlights of differences between the genome structure of sheep, cattle and goats are included in the manuscript. The analysis of about a terabite of data on the transcriptome is also included. Variation of alleles, allelic imbalance and copy number variation have been included in the manuscript as points of interest. Biological stories include reproduction, digestive tract enzymes, evolution of the rumen, lipid metabolism and evolution of wool.<br /> <br /> Kim Worley (BCM-HGSC) received funding from a 2013 USDA/AFRI grant to fill gaps in the sheep assembly using PacBio data with PBJelly (scaffolding and gap filling) and Honey (structural variation identification and assembly QC). For sheep, this approach has produced 19x long read data (40 kb max, 8.5 kb N50, and 6 kb mean). Using three rounds of PBJelly 2, analysis has moved the assembly contig N50 from 41.7 kb to over 500 kb and closed 89% of gaps. However, there was only a minor shift in scaffold N50 (from 100.1Mb to 101.2Mb). Improvement of the Y chromosome, which is full of repetitive sequence, will not be possible with this method. The PacBio work will be in Oar v4.<br /> <br /> Develop high resolution genome maps for goats: The sequencing of the goat genome and development of a more refined genome assembly has continued over the past year. The San Clemente Island goat, Papadum, sequencing and assembly by the USDA and VSU has been evolving as the sequencing technologies evolve. Currently, we have about 67X coverage of Illumina HiSeq sequence data and more than 13X coverage with PacBio sequences. The PacBio technology has been rapidly improving and collaboration with Tim Smith at USDA-ARS Clay Center has allowed us to put more of our sequencing focus on PacBio technologies. Currently we have over 8X coverage of PacBio sequences that are >5 kb. Currently, we are utilizing the next generation of PacBio chemistry for improve read lengths and are pushing the coverage of Papadum to 70X on PacBio and increasing our Illumina sequence coverage. The Illumina 50K SNP chip characterization and development paper has been accepted for publication by PLoS One led by Gwenola Tosser at INRA. The SNP chip is still available and was used heavily over the last year by many groups. Additionally, the first non-IGGC publication using the SNP chip is out and we expect to have more publications coming out over the next year. <br /> <br /> Gwenola Tosser-Klopp, Philippe Bardou, Olivier Bouchez, Cédric Cabau, Richard Crooijmans, Yang Dong, Cécile Donnadieu-Tonon, André Eggen, Henri C. M. Heuven, Saadiah Jamli, Abdullah Johari Jiken, Christophe Klopp, Cynthia T. Lawley, John McEwan, Patrice Martin, Carole R. Moreno, Philippe Mulsant, Ibouniyamine Nabihoudine, Eric Pailhoux, Isabelle Palhière, Rachel Rupp, Julien Sarry, Brian L. Sayre, Aurélie Tircazes, Jun Wang, Wen Wang, Wenguang Zhang, and the International Goat Genome Consortium. 2014. Design and Characterization of a 52K SNP Chip for Goats. PLOS ONE 10.1371/journal.pone.0086227<br /> <br /> Objective 2<br /> <br /> Provide genome mapping resources for sheep: An ovine HD (600K) SNP chip was released by Illumina in 2013. Parameters for inclusion of SNPs on the chip were equal spacing (80% of the SNPs), functional, GBS (genotyping by sequencing), literature and 50K chip SNPs (that were not already included under equal spacing). There is still 6K head room which can be added by users. The final design provides about 12 SNPs every 50K. There should be little ascertainment bias across breeds; however, there will be bias within breeds. There are a lot of low MAF SNPs on the HD chip so users should not create a cluster file, and instead use the cluster file created with ~3,500 animals and available from Illumina. The SNPs will be deposited in dbSNP by March, 2014. The chip should be useful for GWAS and evolutionary studies, and be moderately useful for imputation.<br /> <br /> A USDA/AFRI project, funded in 2013, is focused on a resequencing database that will include extensive annotation of variants. To date, 75 animals from the HapMap project that were included in the sequencing project for SNP identification were chosen and represent 40 breeds and 2 wild sheep species (thin tail and big horn). BCM-HGSC did the sequencing and then aligned the sequences using Oar v3.1. Over 24M SNPs were detected and some selection sweeps across breeds were identified such as pigmentation, horns and shape of ears. As expected, no breed-specific selection sweeps were found.<br /> <br /> Provide genome mapping resources and unique goat populations: We are continuing collaboration with the USDA-ARS Beltsville faculty and research groups from ILRI, ICARDI, ASARECA working in Africa and international collaborators from Brazil, Austria, UK, China, New Zealand and Australia, on a project to improve management of goat genetic resources and the goat production value chain in Africa. The project has collected >2400 samples from ~55 sites in 12 African countries. The extractions of DNA are complete for most of those samples and are currently working on genotyping these samples with the Illumina 50K SNP panel. We have utilized the Illumina 50K SNP panel to begin characterization of U.S. meat goat breeds. We have genotyped samples from the Boer, Myotonic, Kiko and Spanish breed populations. We are using the panel to analyze the breed relationships and origins as well as inbreeding levels.<br /> <br /> Objective 3:<br /> Bioinformatics and genetic mechanisms in goats: We are continuing to develop our bioinformatics tools and activities. This past year we have begun the development of a novel mathematical model for candidate gene finding utilizing bioinformatics and model systems analysis approach. We have developed methods for identifying protein-protein interactions, transcription factor binding sites and epigenetic factors from multiple species and are working on methods to combine these data types for an improved prediction of candidate genes in a cross-species analysis.<br /> <br /> Bioinformatics Technical Report<br /> <br /> Objective 1: n/a<br /> <br /> Objective 2:<br /> Over the past year, partnered with researchers at Kansas State University, Michigan State University, Iowa State University, and U.S. Department of Agriculture, we have further developed and improved the web-interfaced relational databases to store and disseminate phenotypic and genotypic information from large genomic studies in farm animals and better serve the needs of researchers. For example, we are working with the PRRS CAP Host <br /> Genome consortium to develop a relational database to house individual animal genotype and phenotype data (http://www.animalgenome.org/lunney/index.php). This will help the consortium, whose individual research labs lack expertise with relational databases, share information among consortium members, thereby facilitating data analysis.<br /> <br /> Objective 3:<br /> Poultry: A total of 477 new QTL were curated into the Animal QTLdb (http://www.animalgenome.org/QTLdb/chicken.html). Chicken QTL can be <br /> visualized against the genome at http://www.animalgenome.org/cgi-bin/gbrowse/chicken/ and aligned with chicken 60K SNPs along with NCBI-annotated gene information (http://www.animalgenome.org/cgi-bin/gbrowse/chicken/) on genome build GG_4.0. In addition, we continue to mirror Dr. Carl Schmidt's Gallus genome browser while the original site is undergoing restructuring (http://www.animalgenome.org/cgi-bin/gbrowse/gallus/). The Chicken Gene Nomenclature Committee (CGNC) database was initiated with NRSP-8 funds to provide standardized gene nomenclature for chicken genes. As of 30 December 2013, we have assigned nomenclature for 14,800 genes using orthology to HGNC assigned gene names and a further 1,684 genes have been manually assigned nomenclature by biocurators supported by Arizona state funds. We also responded to 11 community requests to provide chicken gene nomenclature. The standardized chicken gene names are publically displayed at the NCBI Entrez Gene database and we are working with Ensembl to ensure they are able to also access this data.<br /> <br /> Cattle: In the past year, 2000 new cattle QTL were added to the Animal QTLdb <br /> (http://www.animalgenome.org/QTLdb/cattle). In addition, cattle QTL can now be viewed relative to both the UMD3.1 assembly (http://www.animalgenome.org/cgi-bin/gbrowse/bovine/) and Btau4.2 assembly (http://www.animalgenome.org/cgi-bin/gbrowse/cattle). Cattle 770K high-density SNPs and 4.1M dbSNP data are now available in GBrowse to align with QTL and in SNPlotz for genome analysis (http://www.animalgenome.org/tools/snplotz/). We have also updated the initial cattle gene nomenclature provided by the Bovine Genome Database, providing standardized gene nomenclature for 9,910 Bos taurus genes based upon homology to assigned human gene nomenclature. This data is available at http://www.animalgenome.org/genetics_glossaries/bovgene. <br /> <br /> Swine: The pig genome sequencing information has been updated at http://www.animalgenome.org/pigs/genome/ and a new pig genome database has been under active development (http://www.animalgenome.org/pig/genome/db/). In the past year, a total of 1,547 new QTL were added to the AnimalQTLdb (http://www.animalgenome.org/QTLdb/pig). The pig gene Wishlist (http://www.animalgenome.org/cgi-bin/host/ssc/gene2bacs) has continued to support the pig genome annotation activities.<br /> <br /> Sheep: In 2013, 36 new sheep QTL were added to the Animal QTLdb (http://www.animalgenome.org/QTLdb/sheep). Active updates have been continued for the NRSP-8 web site for activities in the sheep genome community (http://www.animalgenome.org/sheep/). GBrowse alignments for sheep 54K SNP and BAC clones were set up on OAR Build 3.1.<br /> <br /> Aquaculture: Many useful links for aquaculture can be found at http://www.animalgenome.org/aquaculture/. Thanks to collaborative efforts by researchers from the USDA National Center for Cool and Cold Water Aquaculture, new QTL continue to be entered into the QTLdb. In 2013, 39 new QTL data for rainbow trout were curated into the Animal QTLdb (http://www.animalgenome.org/cgi-bin/QTLdb/OM/index). <br /> <br /> Multi-species: A local copy of Biomart software has been kept up-to-date on the AnimalGenome.ORG server to serve the cattle, chicken, pig, and horse communities (http://www.animalgenome.org:8181/). New data sources and species continue to be updated. <br /> <br /> Ontology development: This past year we continued to focus on the integration of the Animal Trait Ontology into the Vertebrate Trait Ontology (http://bioportal.bioontology.org/ontologies/1659). We have continued working with the Rat Genome Database to integrate ATO terms that are not applicable to the Vertebrate Trait Ontology into the Clinical Measurement Ontology (http://bioportal.bioontology.org/ontologies/1583). Traits specific to livestock products continue to be incorporated into a Livestock Product Trait Ontology (PT; http://animalgenome.org/cgi-bin/amido/browse.cgi). We have also continued mapping the cattle, pig, chicken, and sheep QTL traits to Vertebrate Trait Ontology (VT), Product Trait Ontology (PT) and Clinical Measurement Ontology (CMO) to help standardize the trait nomenclature used in the QTLdb. A new web page is set up to reflect this development (http://www.animalgenome.org/bioinfo/projects/ato/alt), with new sites at http://www.animalgenome.org/bioinfo/projects/vt/, http://www.animalgenome.org/bioinfo/projects/pt/, and http://www.animalgenome.org/bioinfo/projects/cmo/ respectively. Anyone interested in helping to improve the ATO/VT is encouraged to contact James Reecy (jreecy@iastate.edu), Cari Park (caripark@iastate.edu) or Zhiliang Hu (zhu@iastate.edu). The new VT/PT/CMO cross-mapping has been well employed by the Animal QTLdb and VCMap tools. Finally, we have made plans to expand the livestock breed ontology with updated data from Oklahoma State University, <br /> Food and Agriculture Organization, and from China. The chicken adult anatomy is complete, and consists of 2,284 ontology terms cross referenced with the Vertebrate and Uberon Ontologies. The information for these terms includes relationships, synonyms, definitions, and comments (homologies to mammalian structures, species differences). In January 2013, Drs Frances Wong (Roslin Institute) and Fiona McCarthy (University of Arizona) collaborated to begin integration of adult and embryological anatomy terms for the chicken ontology. Dr Wong's visit to the UA was partially supported by a Collaborative Exchange award from the Phenotype Ontology Research Coordination Network (NSF-DEB-0956049). Continuation of this work awaits further funding opportunity.<br /> <br /> Software development: The NRSP-8 Bioinformatics Online Tool Box has been actively updated (http://www.animalgenome.org/bioinfo/tools/). Software upgrades were made continually to SNPlotz, Gene Ontology CateGOrizer, BEAP, and the Expeditor. As a result of collaborations between Iowa State University, the Medical College of Wisconsin, and University of Iowa, the Virtual Comparative Map (VCMap; http://www.animalgenome.org/VCmap/) tool has passed its initial development stage and is at a stable working status serving the community. <br /> Application development, improvement, and testing has continued. Online help materials have been added, including a written user manual and a video tutorial. To improve links between AgBase and the NRSP-8 website, AgBase now also provides a link to the Virtual Comparative Map (VCMap). Please feel free to try things out and send any feedback to vcmap@animalgenome.org.<br /> <br /> Mailing lists and user forums: We have been hosting a couple dozen mailing lists / web sites for various research groups in the NAGRP community. The most active groups include the AnGenMap (www.animalgenome.org/community/angenmap/), The "CRI-MAP users" (http://www.animalgenome.org/tools/share/crimap/) for user interactions to improve CRI-MAP software), "Sheep Models" (www.animalgenome.org/sheep/community/SheepModels), etc. Upon request from Hasan Khatib (hkhatib@wisc.edu), a new mailing list "EPIgroup" (www.animalgenome.org/community/epigroup/) was set up to promote epigenetics research in livestock species. It currently has 198 members. Upon request from Frank Nicholas (frank.nicholas@sydney.edu.au), a new mailing list "OMIA-Support Group" (www.animalgenome.org/community/omia-support/) was set up to facilitate OMIA development activities. It currently has 80 members.<br /> <br /> Minimal standards development: We have continued to work on the MIBBI project <br /> http://www.mibbi.org/index.php/Main_Page to help define minimal standards for publication of QTL and gene association data (http://miqas.sourceforge.net/). See Taylor et al. (2008) for additional information.<br /> <br /> Expanded Animal QTLdb functionality: In 2013, a total of 4099 new QTL have been added to the database. Currently, there are 9862 curated porcine QTL, 6305 curated bovine QTL, 3919 curated chicken QTL, 789 curated sheep QTL, and 127 curated rainbow trout QTL in the database (http://www.animalgenome.org/QTLdb/). We are adding Horse QTLdb to the Animal QTLdb family to collect horse QTL/association data. All included livestock QTL data have been ported to NCBI. In 2013, we have worked with UCSC and Ensembl to port the livestock animal QTL data to UCSC Golden tracks and to Ensembl databases. Now users can fully utilize the tools at NCBI, Ensembl, and UCSC to mine animal QTL data. The January 2013 Nucleic Acids Research Database Issue contains a paper describing the latest developments we made on the Animal QTLdb.<br /> <br /> Facilitating research: The Data Repository for the aquaculture, cattle, chicken, and pig communities to share their genome analysis data has proven to be very useful (http://www.animalgenome.org/repository). New data is continually being added. Frequent data downloads include over 140 data files in 6 different animal species. The newly added data includes rainbow trout genome assembly draft, chicken 60K SNP information, etc. In parallel to the public data repository, the online data file-sharing tool has also been actively used to facilitate data sharing among collaborators and/or groups. Our helpdesk is here to assist community members. Throughout the year, we have helped more than 50 research groups/individuals with their research projects and questions. Our involvement has ranged from data transfer, data assembly, and data analysis, to software applications, code development, etc. Please continue to contact us as you need help with bioinformatic issues.<br /> <br />

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The NRSP-8 business meeting was preceded by two days of species workshops, area subcommittees, and the combined Animal Genome Workshop presented on Sunday afternoon. The combined workshop included four plenary presentations as follows: Dr. Kim Worley, Baylor College of Medicine, “Improving the Reference – Better Genomes for the Sheep and the Cow”; Dr. John Hickey, The Roslin Institiute, University of Edinburgh, “Genomic Selection 2.0”; Dr. Hans Cheng, USDA-ARS-ADOL, delivered the NRSP8 Distinguished Lecture entitled “Integrative Genomics to Provide Basic and Applied Knowledge to Control Marek’s Disease in Chicken”; Dr. Elisabetta Giuffra, INRA, UMR de Genetique Animale et Biologie Integrative, “The Functional Annotation of Animal Genomes (FAANG) Initiative”. Dr. Giuffra’s presentation was followed by a 30 minute FAANG Roundtable Discussion by members of the international FAANG consortium. Topics of discussion included current pilot projects as well as plans for future large-scale collaborative work on annotation of regulatory elements across many animal clades. The business meeting was called to order by the Chair, Dr. Stephen White (USDA-ARS-ADRU, Pullman, WA), and was recorded by the Secretary, Dr. Daniel Ciobanu (University of Nebraska-Lincoln) with approximately 40 members in attendance. Coordinator reports were presented for the species/topic groups of Cattle, Poultry, Swine, Sheep and Small Ruminants, Equine, Aquaculture, and Bioinformatics. Dr. Eric Young (North Carolina State University) provided the administrative report. Dr. Lakshmi Matukumalli (contact for the Tools and Resources – Animal Breeding, Genetics and Genomics, USDA-NIFA-AFRI) provided a brief update. It was stated and confirmed that the 2015 NRSP8 meeting will again be held in conjunction with the Plant and Animal Genome conference in San Diego. Dr. Daniel Ciobanu assumed the NRSP-8 Chair for 2015-2016, and Dr. Huaijun Zhou (University of California-Davis) was elected Secretary for 2016-2017. The meeting was adjourned

Accomplishments

Objective 1:Catfish<br /> <br /> A) Cooperative research between USDA-ARS Warmwater Aquaculture Research Unit and the School of Fisheries, Aquaculture and Aquatic Sciences at Auburn University has resulted in the first generation catfish genome sequence assembly. Next generation sequences from a doubled haploid channel catfish were error-corrected and assembled using the MaSuRCA/Whole Genome Shotgun Assembler pipeline. Mate pair reads from 3kb and 8kb length fragments, and paired end sequences from 34.4 kb fosmid clones were used to link contigs into scaffolds. Illumina and Pac Bio sequences were used to fill scaffold gaps, which improved the average contig lengths from 7.2 kb to 17.1 kb. Half the assembled bases were contained in 2,861 contigs of 76.7 kb or longer (up to 607 kb) and in 113 scaffolds of 1.88 Mb or longer (up to 11.5 Mb). 99% of the assembled bases were contained in 5,299 scaffolds of 1kb or longer. The kmer-based genome size estimate was 948 Mb, and the combined lengths of contigs and degenerates (sequences deemed as genomic repeats) was 934 Mb. 93.7% of assembled bases could be placed on the high density genetic map, and 95.6% could be placed on the BAC physical map. The catfish genome was annotated using transcriptome sequencing. Through transcriptome analysis of various tissues, a total of almost 28,000 genes were identified, and 23,000 complete cDNAs have been assembled and annotated. Gene families and gene duplication were analyzed. B) The catfish genome was annotated using transcriptome sequencing. Through transcriptome analysis of various tissues, a total of almost 28,000 genes were identified, and 23,000 complete cDNAs have been assembled and annotated. Gene families and gene duplication were analyzed. C) Development and validation of SNP resources in different lines of blue catfish <br /> <br /> Oyster<br /> <br /> A) Proposal to sequence and assemble the Eastern Oyster Genome was funded by the USDA NIFA Animal Breeding, Genetics, and Genomics program. PI: Marta Gómez-Chiarri. B) Draft genome of Pearl oyster (Pinctada fucata) is in progress (NCBI BioProject ID PRJDB2628). C) Mantle transcriptome of pearl oyster (Pinctada maxima) was sequenced, assembled and annotated. In addition, 1764 SSRs were identified. D) The Pacific Oyster methylome was characterized. Genes that are regulated by CpG methylation largely originate within the eukaryotic lineage suggesting that alternate methylation patterns contiribute to the radiation of eukaryotic taxa.<br /> <br /> Salmonids<br /> <br /> A) The first rainbow trout reference genome was published (Berthelot et al., 2014) and the genome assembly was posted at the NCBI genome database. B) Thousands of SNP markers from RAD tags were identified and genotyped for various populations of O. mykiss (Matala et al. 2014), O. tshawytscha, O. nerka, and O. kisutch. C) An effective method for custom amplicon sequencing (GT-seq) that allows thousands of fish to be genotyped for panels of 100-1000 SNPs was developed (Campbell et al. 2014, E-published).<br /> <br /> Shrimp<br /> <br /> A high quality draft assembly of the Litopenaeus vannamei remains elusive. Several groups are working on this, including a teams led by Mike Criscitiello at Texas A&M and Rogerio Sotelo-Mundo at CIAD in Hermosillo Mexico, and one led by Jianguo He from Sun Yat-sen University in China. Efforts are currently focused upon assembly methods and inclusion of more PacBio data.<br /> <br /> Striped bass<br /> <br /> The 585 Mb hybrid Illumina-PacBio striped bass genome sequence assembly was annotated and an jBrowse website is being designed for presenting access to it online with availability via the the NRSP8 website, URL: http://stripedbass.animalgenome.org/ anticipated in 2016. A dedicated virtual machine platform has been setup to develop cyber resources for the Striped Bass Genome Database project at NC State University. Female and male white bass genomes also have been sequenced using Illumina and assembled using the striped bass genome as a reference. The female and male white bass genome assemblies consist of 57,533 contigs (643 Mb) and 56,818 contigs (644 Mb), respectively and partial Cegma scores indicate that both assemblies are 97.98% complete."<br /> <br /> Objective 2: Catfish<br /> <br /> A) Bulked segregant RNA-seq (BSR-Seq) was used to analyze differentially expressed genes and associated SNPs with disease resistance against enteric septicemia of catfish (ESC). A total of 1,255 differentially expressed genes were found between resistant and susceptible fish. In addition, 56,419 SNPs were identified as significant SNPs between susceptible and resistant fish located on 4,304 unique genes. Detailed analysis of these significant SNPs allowed differentiation of significant SNPs caused by genetic segregation and those caused by allele-specific expression. Mapping of the significant SNPs, along with analysis of differentially expressed genes, allowed identification of candidate genes underlining disease resistance against ESC disease. Genomic sequencing of multiple individuals allowed identification of 8.4 millons of SNPs and analysis between the domestic and wild catfish allowed identification of selection sweeps. B) Continued characterization of immune responses and underlying gene actors in innate and specific immune responses in catfish<br /> <br /> Oyster<br /> <br /> A) The transcriptomes of wild juvenile oysters from high and low salinity regimes were sequenced and compared to identify candidate genes for osmoregulation. High nucleotide sequence divergence between the Eastern Oyster and Pacific Oyster limits the extent to which the C. gigas genome can serve as a reference genome for C. virginica; however, purifying selection on protein sequences in this genus allowed for accurate functional annotation of C. virginica predicted protein sequences. B) The transcriptomes of juvenile Eastern Oysters from ROD (Roseovarius Oyster Disease) resistant and susceptible families were sequenced and compared to characterize the responses of different families to the disease as well as provide insight to mechanisms of disease resistance. Transcripts involved in immune recognition, signaling, protease inhibition, detoxification, and apoptosis were differentially expressed among the two families. C) Two Illumina GoldenGate genotyping arrays containing 384 SNP markers were designed for Crassostrea gigas and Ostrea edulis respectively and used to genotype 1000 individuals from wild and selected populations as well as families bred for commercially important traits. Overall success rate was 60%. These arrays provide adequate power for parentage assignment. D) Transcriptomes of Pacific Oysters from three wild populations were sequenced and aligned to the Pacific Oyster genome. 5.8 × 105 SNPs were identified and non-synonymous SNPs were enriched in genes involved in apoptosis and responses to biological stimuli. HRM genotyping assays have been developed for approximately 1300 SNP markers.<br /> <br /> Salmonids<br /> <br /> A) The rainbow trout 57K SNP array is now commercially available from Affymetrix in two formats; for samples in 96-well plates and for samples in 384-well plates (more economical). For the 96 format the minimum order is 192 samples and for the 384 format the minimum order 1,920 samples. More ordering information on the array and a data sheet with technical information are available on the Affymetrix web site: http://www.affymetrix.com/estore/catalog/prod900010/AFFY/Axiom%26%23174%3B+Trout+Genotyping+Array#1_1. B) GWAS studies were conducted for disease resistance in rainbow trout (Campbell et al. 2014, E-published), and tested natural populations of steelhead for genomic association with variable environments and landscapes (Matala et al. 2014). C) SNP markers were used to identify specific stocks of Chinook salmon and to identify run-timing, straying, and delayed mortality in natural populations (Hess et al. 2014; Rechisky et al. 2014). D) <br /> A total of 76 differentially expressed miRNAs including 10 miRNAs novel to rainbow trout were identified in skeletal muscle under the influence of estrogen. The known miRNAs include important myogenic miRNAs, such as miR-1, miR-133a, miR-126, miR-145, miR-499 and miR-206. E) A stringent set of 9,674 large intergenic noncoding RNAs (lncRNAs) were identified by RNA-Seq analysis of rainbow trout transcriptome. These lincRNAs in general are less conserved than protein-coding genes, and typically co-expressed with their neighboring genes. Many of them are tissue-specific and functionally associated with important biological processes.<br /> <br /> Shrimp<br /> <br /> Several RNAseq projects have been completed in this species, including a refined transcriptome annotation from the Texas A&M/CIAD team late this year (Scientific Reports 4:7081 2014).<br /> <br /> Striped bass<br /> <br /> Artificial neural networks and supervised machine learning were employed to further evaluate relationships between ovary transcriptome profiles and egg quality (fertility) in striped bass. Expression levels of as few as 250-1,000 ovary genes proved to be a robust predictor of egg quality (R2 always > 0.80) in separate studies involving analyses of gene expression by microarray or RNA-Seq in different groups of domesticated and wild striped bass. Egg transcriptome profiles were nearly as informative as ovary profiles from the same females, implicating maternal transcripts deposited in eggs in control of egg quality. <br /> <br /> Objective 3: Oyster<br /> <br /> Proposal to hold resource coordination workshops focused on oysters and other shellfish funded through NRSP8 Aquaculture Program. PI: Steven Roberts.<br /> <br /> Salmonids<br /> <br /> A bioinformatics pipeline was developed for genotyping SNPs from raw sequence data for the GT-seq method (Campbell et al. 2014, E-published).<br /> <br /> Shrimp<br /> <br /> The shrimp community is slowly making data more accessible. Acacia Alcivar-Warren’s Environmental Genomics is moving on shrimp projects internationally in epigenomics and environmental toxicology, and had set up a One Health Genomics website that was unfortunately hacked. Most groups are still sharing data via small institution repositories (e.g. http://repository.tamu.edu/handle/1969.1/152151).<br /> <br /> <br /> Cattle Technical Report<br /> <br /> Objective 1:<br /> <br /> Bovine Genome sequence: An important focus of the community has been towards improving the bovine genome assembly. In 2014, there was limited success in expanding these efforts to the desired level with NIFA funding. A group of collaborating scientists are working toward improving the bovine reference genome assembly and its annotation. Multiple data types have been generated, such as an optical map, Illumina paired-end and mate-pair sequence, PacBio sequence, and improved gene predictions based on RNA-seq data. All of the data were derived from tissue samples from L1 Dominette 01449, the reference animal. The goal of the group has been to generate improved reference genome assemblies with fewer gaps, miss-assemblies, and missing genes. <br /> <br /> Efforts currently underway and supported by NIFA grants: 1) David Schwartz, Shigou Zhou (University of Wisconsin, Madison) and collaborators: Have generated a whole genome optical map (BtOM1.0) of Dominette 01449. BtOM1.0 is a high-resolution physical map that has been used to compare the structure of both bovine assemblies, UMD3.1 and Btau4.6, revealing that Btau4.6 has double the number of discordances than UMD3.1. BtOM1.0, when used as an independent guide, will greatly advance future improvements of existing sequence builds and will also serve as an accurate physical scaffold for comparative genomic studies. 2) Kim Worley (Baylor College of Medicine, Houston, TX) is using long PacBio reads to improve the assembly and has generated 20x PacBio data for both Dominette 01449 and a Texel sheep. She will use PBJelly software (developed in-house at Baylor) to fill gaps and improve scaffolds and is working with David Schwartz to get the optical map data in a form that will allow identifying regions of Btau4.6 and UMD3.1 that are consistent and inconsistent with the optical map. 3) Chris Elsik (University of Missouri, Columbia) is working on improving gene annotation using RNA-seq data from strand-specific cDNA libraries, new software and visualization applications with community annotation. 4) Huaijun Zhou and collaborators (University of California, Davis) are following the blue print of the human and mouse ENCODE projects for identifying the functional roles of regulatory elements in the genome, this group has implemented a similar effort in cattle, pig and chicken, initiating the AGENCODE project. The goals are to identify promoter, enhancer, and silencer region specific chromatin marks, and to determine functional roles of regulatory regions in relevant tissues in each species.<br /> <br /> Efforts currently underway, not supported by NIFA grants: Tim Smith (Meat Animal Research Center, Nebraska) and Juan Medrano (University of California, Davis): Genomic DNA from Dominette 01449 is being used to produce PacBio libraries to generate >50x of coverage of the genome for an independent assembly, which will be merged with the current assembly UMD3.1 to leverage the advantages of both. Funding for this project comes from $55k from NRSP8 Cattle coordinator funds, $15k from USMARC and $10K from Zoetis. Part of the funds will also be used to generate IsoSeq PacBio RNA full-length cDNA sequences from Dominette tissues to supplement fat, muscle and lung tissues already performed at USMARC. Data from these efforts will be made publically available as the data are being generated using public funding. <br /> <br /> Objective 2: n/a<br /> <br /> Objective 3:<br /> <br /> Harvey Blackburn at USDA-ARS National Animal Germplasm Program (NAGP), Colorado State University Experimental Station and EMBRAPA have joined efforts to develop a genomic database that will serve as a repository for DNA data from the large animal genomics projects which have valuable data that needing permanent archiving for future research. This effort, coupled with the existing capacities to store phenotypic and production system data in the Animal-GRIN database as well as germplasm/tissue samples, will facilitate the communities’ efforts to maintain valuable data for future use. Database and bioinformatics activities are also coordinated by Jim Reecy (NRSP8 Bioinformatics Coordinator) at the NAGRP site (http://www.genome.iastate.edu/cattle/). Coordination funds supported students, post-docs and workshop speakers travel awards for PAG-XXI in January 2014, and will do the same for PAG XXII in January 2015. A future priority is to support efforts towards the improvement of the bovine genome reference sequence assembly in 2015, and to support data sharing and the creation of sample and data repositories that will benefit other cattle research investigators. We will expand our efforts to include international collaborators and the cattle industry, and expect to keep the Cattle Genome Community informed of developments and activities of the Cattle Genome Coordinators through a periodic newsletter. If you have any informational items you would like distributed via this newsletter please contact Alison Van Eenennaam (alvaneenennaam@ucdavis.edu) or either of the two other co-coordinators. Constructive suggestions from researchers on areas to support in bovine genomics are also welcomed.<br /> <br /> <br /> Swine Technical Report<br /> <br /> Objective 1:<br /> <br /> Porcine SNP chips update: Illumina and the International Porcine SNP Chip Consortium developed a porcine 60K BeadChip that has been used worldwide for numerous genome wide association studies (GWAS) studies. GeneSeek, a supplier of genotyping services, has a low density chip, the GeneSeek Genomic Profiler for Porcine LD (GGP-Porcine LD) that utilizes Illumina Infinium chemistry and features approximately 8,500 SNPs for high density chip imputation. GeneSeek also released a new chip in 2014, the GGP - Porcine HD that features nearly 70,000 SNPs that span the pig genome, as well as several markers that directly impact disease and performance traits. Details on these chips can be obtained from GeneSeek (geneseekinfo@neogen.com). A new high density SNP chip is being developed by Affymetrix, and will be announced in 2015.<br /> <br /> Objective 2: <br /> <br /> Shared Materials and Funding: NRSP8 funds are available to support community activities to find associations with many different traits. In 2014, a policy was developed and approved by the Advisory Committee that for swine genomics projects to be eligible for NRSP8 Coordination support, the project must materially involve two or more NRSP8 member groups (university or ARS research locations) and that substantial funding will only be provided for projects that have matching funding from another agency. In FY 2014 one project was approved to work toward a genetic analysis of PEDV resistance. Any questions on this policy, please contact the Coordinators.<br /> <br /> Objective 3:<br /> <br /> International Efforts: Communication with all international groups and individuals is excellent. The Swine Genome coordinators have been working with a large number of individuals in many countries to develop a new initiative, called Functional Annotation of ANimal Genomes (FAANG). This group proposes a project to identify all functional elements in animal genomes, and has presented their plans on a website organized by the Swine Coordination effort (see www.faang.org). <br /> Policy Updates: We have developed an Advisory Committee, who will provide guidance on policy as well as help evaluate requests for funding. The members of this Advisory Committee represent the swine industry, swine genomics and biotechnology researchers, NRSP-8 Stations and participating USDA labs. The members are: Jack Dekkers (ISU), Chris Hostetler (National Pork Board), Joan Lunney (USDA-BARC), Randy Prather (U. Missouri), and Juan P. Steibel (MSU). Thanks to this group for volunteering for this important role!<br /> Communication: The Pig Genome Update has now published 120 issues and has been distributed electronically to over 2,300 people worldwide. PGU will be electronically published three times a year, and in addition to general updates, the issues will be published to coincide with major events of interest to the genome community in February, June, and October.<br /> Travel and Meeting Support: Travel of some scientists was partially funded to attend important pig genomics meetings. These included: Chris Eisley 2014 Neal Jorgenson Travel Award, Joan Lunney 2014 Distinguished Lecturer NRSP-8 Workshop, 2015 commitments:<br /> Melanie Trenhaile, 2015 Neal Jorgenson Travel Award winner, Elisabetta Giuffra, 2015 NRSP-8 special speaker on FAANG, Huaijun Zhou, Midwest ASAS Functional Genomics Workshop.<br /> 2014 Research Support Activities: The goals are to help support all of the objectives of this project. Major activities included helping facilitate collection of phenotypes and sharing use of SNP chips in the future. New bioinformatic tools relevant to the swine genomics community will also be developed with help of the bioinformatics team. Constructive suggestions from researchers to help this coordination and facilitation program grow and succeed are appreciated. <br /> Projects approved for funding during period: <br /> 1. FAANG project led by Huaijun Zhou, University of California-Davis. This project also had funding promised by the NRSP8 Bovine and Poultry Coordinators, as well as funding by the National Pork Board.<br /> 2. PEDV genetics resistance project led by Max Rothschild with collaborators Daniel Ciobanu and Canadian swine genetics companies.<br /> <br /> Poultry Technical Report<br /> <br /> Objective 1:<br /> <br /> Reference linkage map. Linkage mapping is now primarily via high throughput SNP assays. Very high density SNP mapping (ca. 600,000 SNP) panels have been developed and are being employed in genome-wide association studies (GWAS) and genomic selection (GS). Plans will begin soon to help resolute unmapped sequence contigs through genetic mapping of selected SNPs on the East Lansing reference panel.<br /> <br /> Chicken genome sequence. Efforts are ongoing to improve the chicken genome sequence, which is being led by Wes Warren, The Genome Institute at Washington U. The latest build, Galgal5.0, will incorporate information from 30x PacBio coverage from a 10 Kb library (funded by Cobb-Vantress), which has improved the N50 contig size from 250 Kb to 1.79 Mb and cut about half of the number of unplaced scaffold gaps (1722 to 965). Unfortunately, even with these efforts and the use of 6x Moleculo sequence, the new build has still not captured the roughly 5% of missing sequence (believed to be predominantly on the microchromosomes). Future planned efforts include PacBio sequencing of a 20 Kb library and, as discussed above, integration with an improved genetic map.<br /> <br /> Objective 2: <br /> <br /> DNA from the East Lansing international reference mapping population has been sent to many laboratories throughout the world. Similarly, DNA from the junglefowl used to generate the reference sequence assembly has been widely distributed, especially for copy number variant studies.<br /> <br /> Objective 3:<br /> <br /> Database activities are led by the NRSP-8 Bioinformatics Coordinator, Jim Reecy, and Susan Lamont, along with Shane Burgess, represent poultry interests on the advisory committee for this group. Poultry bioinformatics has also benefitted from support at several other locations. We maintain a homepage for the NRSP-8 U.S. Poultry Genome project (http://poultry.mph.msu.edu) that provides a variety of genome mapping resources, including our newsletter archive. The Poultry Genome Newsletter is published quarterly and is distributed through our Homepage and on the angenmap email discussion group. <br /> Meetings: Over 3,000 scientists attended the joint Plant and Animal Genome XXII meeting last January, held jointly with the annual NAGRP meeting. Coordination funds helped support attendance at PAG-XXII: Travel support for John Hsieh, Iowa State U. graduate student (Lamont, PI); Melissa Monson, Recipient of Neal Jorgenson Genome Travel Award, U. Minnesota graduate student (Reed, PI); Dr. Michael Romanov, U. Kent, UK. Dr. Rachel Hawken, Cobb-Vantress, NRSP-8 workshop speaker.<br /> Impact: This project is generating tools through which the genome sequence can be used to locate inherited production trait alleles and apply the DNA sequence to ascertain the physiological basis for those traits. It has resulted, among other things, in the generation of the complete sequence of the chicken and now the turkey genome. Commercial breeders are using the sequence and SNP we generated to characterize and improve production lines using GS. In simpler terms, we are now moving closer to understanding the cause of phenotypic variation that is relevant to the agricultural use of poultry.<br /> <br /> Equine Technical Report<br /> <br /> Objective 1:<br /> <br /> New Reference Genome Assembly: Ted Kalbfleisch announced that the Morris Animal Foundation had selected for funding a proposal crafted by Ted, Jamie MacLeod and Ludovic Orlando for creating a new assembly of the reference sequence, the putative Ecab 3.0. Partial support for a postdoctoral student will come from USDA-NRSP8 coordinators’ funds. The grant proposal and work is underpinned by data provided by workshop participants including whole genome sequence information from TWILIGHT (reference horse) and from horses of other breeds. <br /> Whole Genome Sequences: In connection with research projects, many of which are cited in the reference section, over 200 horses have had their whole genomes sequenced. Many of those sequences are being used for the new assembly described in the previous paragraph and were used to identify SNPs for construction of the 670K SNP assay tool described below.<br /> Access to reference DNA: The Cornell laboratory (Doug Antczak and Don Miller) have continued to provide samples to other scientists from TWILIGHT, the horse providing DNA for the reference sequence and from BRAVO, the horse that provided DNA for the CHORI 241 BAC library. <br /> <br /> Objective 2: <br /> <br /> New SNP assay tool: The 670K SNP chip is now available for research use on horses. This was an initiative proposed and driven by Dr. Molly McCue of the University of Minnesota with support of students, co-workers and funding from several agencies including the USD-NRSP8 coordinators‘ fund. Bob Schaefer (UMN) gave a presentation describing the considerations in designing the tool. Geneseek (NE) is a commercial laboratory offering testing and has agreed to coordinate testing among laboratories to help reduce costs. Workshop scientists contributed data from whole genome sequencing of more than 200 horses to discover SNPs for use on this assay tool.<br /> <br /> Objective 3: <br /> <br /> A consortium was established to annotate functional elements in the genome responsible for regulating phenotypic traits for all animal species. The group is called Functional Annotation of Animal Genomes (FAANG) and is patterned after the ENCODE program that has been successful for studying functional genomics in humans. Dr. Jamie MacLeod (University of Kentucky) has been invited to serve on the guiding committee to represent the interests of horse genomics. Dr. MacLeod has invited participation in a subgroup focusing on horses, called E-FAANG, for Equine – FAANG.<br /> Database Activities: Two databases compile published genetic data for horses: http://locus.jouy.inra.fr/cgi-bin/lgbc/mapping/common/intro2.pl?BASE=horse; http://www.thearkdb.org/. Several genome browsers have been developed at the University of California, Santa Cruz, ENSEMBL and NCBI: http://www.genome.ucsc.edu/cgi-bin/hgGateway?hgsid=95987985&clade=vertebrate&org=Horse&db=0; http://www.ncbi.nlm.nih.gov/mapview/map_search.cgi?taxid=9796; http://www.equinegenome.org/Equinegenome.org.htmlhttp://pre.ensembl.org/Equus_caballus/index.html. A SNP database is available: http://www.broad.mit.edu/mammals/horse/. <br /> A RNAseq database: http://macleod.uky.edu/equinebrowser/ A major entry point for databases and other relevant information about the horse genome workshop and participants is the workshop website: http://www.uky.ledu/AG/Horsemap.<br /> International Efforts: The horse genome technical committee is an international activity with approximately half of the participants coming from Europe, Africa and AustralAsia while the other half come from North America.<br /> Communication: Communication within the horse genome workshop is facilitated by an email list for sharing information by the Horse Genome Coordinator and through the website: http://www.uky.edu/AG/Horsemap. One of the major aspects of the website is to increase its value for informing members of the horse industry about the scientists using horse genomics to solve important problems and to explain the value of horse genomics<br /> Travel and Meeting Support: During 2014, travel awards were provided to 10 students, including one Jorgenson award, and travel support for two invited speakers to the Horse Genome Workshop and to the NRSP8 general meeting.<br /> Future Activities: During 2015 a workshop on Horse Genomics will be conducted under the auspices of the Dorothy Russell Havemyer Foundation in conjunction with the USDA-NRSP8. The workshop will include discussions of applications of the horse genome tools to address issues of performance and health in horses. In addition, one session will be devoted to discussion of FAANG and activities to promote this program. Coordinator funding will be used for partial support of a postdoctoral fellow to work on the Morris Animal Foundation funded project to create a new assembly for the horse genome (Ecab 3.0).<br /> <br /> Sheep/Goat Technical Report<br /> <br /> Objective 1:<br /> <br /> An ongoing project of the ISGC is development of a whole genome reference assembly. In 2010, sequence data were generated at two sequencing facilities (Beijing Genomics Institute and the Roslin Institute) from DNA of a Texel ewe and a Texel ram, respectively. A paper was published in Science in June, 2014 describing the whole genome assembly (Oar v3.1), the RH map, and the linkage map. Highlights of differences between the genome structure of sheep, cattle and goats are included in the paper. The analysis of about a terabite of data on the transcriptome is also included. Variation of alleles, allelic imbalance and copy number variation have been included in the manuscript as points of interest. Biological stories include digestive tract enzymes, evolution of the rumen, lipid metabolism and evolution of wool.<br /> Kim Worley (BCM-HGSC) received funding from a 2013 USDA/AFRI grant to fill in gaps and improve the sheep assembly using PacBio sequence data with PBJelly (scaffolding and gap filling). Around XX whole genome shotgun sequence using the PacBio technology has been generated from the Texel ram used in the sheep assembly. The sequence reads were long (up to 10 kb average) and therefore useful for spanning gaps in a draft genome. For sequences mapped to specific sheep chromosomes, the PBJelly method closed 70% of the gaps, reducing the number of contigs from 117,293 to 35,267. The assembly is more contiguous, with the contig N50 increased from 41.7 kb to 165.2 kb and almost ¼ of the contigs larger than 100kb (8,527; increased from 2,355). The PacBio data appears to improve the GC representation, increasing the G+C content slightly (0.1% of the contig bases). The fraction of the ambiguous bases (Ns) in the scaffolds decreased from 3.12% to 0.87% of the genome. The PacBio work will be in Oar v4.<br /> <br /> Objective 2<br /> <br /> A USDA/AFRI project, funded in 2013, is focused on a resequencing database that will include extensive annotation of variants. The overall objective of this proposal is to build a comprehensive database of genomic variation for sheep, based on whole genome analysis, and to make the database available to the research community. This resource, referred to as the SheepGenomes DB, will speed discovery and innovation for scientists working in the area of livestock genomics. <br /> Four elements essential to the design, construction and delivery of the SheepGenomes DB have been completed to date. The first element is the finalized design of the database and how it interacts with external public data archives. Importantly, the workflow integrates NCBI, dbSNP and the European Variation Archive (EVA), which delivers key advantages concerning public access of genome information, data storage and variant accessioning. Secondly, a standardized bioinformatic pipeline has been completed for raw sequence read filtering and mapping to create reference guided assemblies of each individual. This is essential, as a standardized pipeline ensures that the variants detected within every animal in SheepGenomesDB can be confidently compared against each other. Thirdly, a mission statement was distributed to the community, resulting in agreements to submit over 400 sheep genomes into the analysis by early 2015 (see table below). Another 1000+ genomes in Run 2 are expected by late 2015. Finally, a web portal has been created to house project information and to support user downloads of SNP and indel information. <br /> <br /> Objective 3: n/a<br /> <br /> Bioinformatics Technical Report<br /> <br /> Objective 1: n/a<br /> <br /> Objective 2:<br /> <br /> Over the past year, partnered with researchers at Kansas State University, Michigan State University, Iowa State University, and U.S. Department of Agriculture, we continued to further develop and improve the web-interfaced relational databases to store and disseminate phenotypic and genotypic information from large genomic studies in farm animals and better serve the needs of researchers. For example, we are working with the PRRS CAP Host Genome consortium to develop a relational database to house individual animal genotype and phenotype data (http://www.animalgenome.org/lunney). This will help the consortium, whose individual research labs lack expertise with relational databases, share information among consortium members, thereby facilitating data analysis. <br /> PLANS FOR THE FUTURE: Facilitate the development and sharing of animal populations and the collection and analysis of new, unique, and interesting phenotypes. We will seek to partner with any NRSP-8 members wishing to warehouse phenotypic and genotypic data in customized relational databases. This will help consortia/researchers whose individual research labs lack expertise with relational databases to warehouse and share information. <br /> <br /> Objective 3:<br /> <br /> The following describes the project's activities over this past year. The NAGRP data repository has been actively used by the horse community to share the Variant Call Format (VCF) files in their collaborative research.<br /> Multi-species support: The Animal QTLdb and the NAGRP data repository have been actively serving multiple species research activities. A state-of-the-art online alignment tool (Jbrowse) has been set up on the AnimalGenome.ORG server to serve the cattle, chicken, pig, sheep, and horse communities for QTL/association data alignment with annotated genes and other genome features (http://i.animalgenome.org/jbrowse). The advantage of Jbrowse is that it easily allows user quantitative data- XYPlot/Density, in BAM or VCF format-to be loaded directly to a user's browser for comparisons in the local environment. New data sources and species continue to be updated. This complements GBrowse, which features multiple HD SNP chip, OMIA genes, and STS marker alignments against QTL/association data for cattle, chicken, pig, sheep, and horse. Recently a dedicated virtual machine platform was set up to develop cyber resources for the Striped Bass Genome Database activity, a project led by Benjamin Reading and Charles Opperman at North Carolina State University (http://stripedbass.animalgenome.org/).<br /> Ontology development : This past year we continued to focus on the integration of the Animal Trait Ontology into the Vertebrate Trait Ontology (http://bioportal.bioontology.org/ontologies/VT). We have continued working with the Rat Genome Database to integrate ATO terms that are not applicable to the Vertebrate Trait Ontology into the Clinical Measurement Ontology (http://bioportal.bioontology.org/ontologies/CMO). Traits specific to livestock products continue to be incorporated into a Livestock Product Trait Ontology (PT; http://animalgenome.org/cgi-bin/amido/browse.cgi). We have also continued mapping the cattle, pig, chicken, sheep, and horse QTL traits to Vertebrate Trait Ontology (VT), Product Trait Ontology (PT) and Clinical Measurement Ontology (CMO) to help standardize the trait nomenclature used in the QTLdb. A new web page is set up to reflect this development (http://www.animalgenome.org/bioinfo/projects/ato/alt), with links to the three new sites for VT, PT, and CMO respectively. At the request of community members, at least 45 new terms were added to the VT in 2014. Anyone interested in helping to improve the ATO/VT is encouraged to contact James Reecy (jreecy@iastate.edu), Cari Park (caripark@iastate.edu), or Zhiliang Hu (zhu@iastate.edu). The new VT/PT/CMO cross-mapping has been well employed by the Animal QTLdb and VCMap tools. Annotation to the VT is now also available for rat QTL data in the Rat Genome Database and for mouse strain measurements in the Mouse Phenome Database. Finally, we have made plans to expand the livestock breed ontology with updated data from Oklahoma State University, Food and Agriculture Organization, and from China. <br /> Continuing work on the chicken anatomy ontology is based upon UA biocurator funds, with work focusing on (1) linking adult chicken anatomy terms with the Uberon ontology (of generic anatomical terms) and (2) adding developmental terms provided by Prof Burt's group at the Roslin Institute. Currently the chicken anatomy ontology contains 14,627 terms, cross-referenced with the Uberon ontology (and other related anatomy ontologies). Since this ontology will be required for the Functional Annotation of Animal Genomes (FAANG) Project, during 2015 we will seek competitive funding for a full-time biocurator to complete this ontology.<br /> Software development : The NRSP-8 Bioinformatics Online Tool Box has been actively updated (http://www.animalgenome.org/bioinfo/tools/). Software upgrades were made continually to SNPlotz, Gene Ontology CateGOrizer, and the Expeditor. The CateGOrizer is now bundled with a new external tool, ReviGO, for the convenience of users to take CateGOrizer outputs directly to ReviGO for a semantic representative subset analysis.<br /> In collaboration with Dr. Shengsong Xie and Yuhua Fu from Shanghai, China, a sRNAPrimer designing tool has been made available through AnimalGemome.ORG (http://www.animalgenome.org/cgi-bin/host/sRNAPrimer/d).<br /> As a result of collaborations between Iowa State University, the Medical College of Wisconsin, and University of Iowa, the Virtual Comparative Map<br /> (http://www.animalgenome.org/VCmap/) tool has passed its initial development stage and is at a stable working status serving the community. Application development, improvement, and testing have continued. Online help materials have been added, including a written user manual and a video tutorial. AgBase and the NRSP-8 websites provide multiple reciprocal reference links to facilitate resource sharing. Please feel free to try things out and send any feedback to vcmap@animalgenome.org. <br /> Gene nomenclature standard: <br /> During 2014 the Chicken Gene Nomenclature Committee (CGNC) updated nomenclature to support new annotations from both NCBI and Ensembl. We currently provide standardized nomenclature for 16,422 genes and this data is now routinely distributed to both NCBI Entrez and Ensembl. During 2014 funding to support chicken gene nomenclature was provided by NIH NIGMS Project number 5R24GM079326-02 and during 2015 we will be seeking continued competitive funds for this project.<br /> The initial cattle gene nomenclature is provided by the Bovine Genome Database.<br /> Currently we have standardized gene nomenclature for 9,910 Bos taurus genes based upon homology to assigned human gene nomenclature (http://www.animalgenome.org/genetics_glossaries/bovgene). We are also working with HGNC to support the development and use of standardized gene nomenclature for livestock species.<br /> Minimal standards development : We have continued to work on the MIQAS project to help define minimal standards for publication of QTL and gene association data (http://miqas.sourceforge.net/). The most recent works were to develop documentations how this was done in Animal QTLdb. <br /> Expanded Animal QTLdb functionality: In 2014, a total of 9,063 new QTL have been added to the database. Currently, there are 12,618 curated porcine QTL, 13,415 curated bovine QTL, 4,379 curated chicken QTL, 1,005 curated horse QTL, 791 curated sheep QTL, and 127 curated rainbow trout QTL in the database (http://www.animalgenome.org/QTLdb/). All included livestock QTL data have been ported to NCBI, Ensembl, and UCSC genome browser. Now users can fully utilize the browser and data mining tools at NCBI, Ensembl, and UCSC to explore animal QTL/association data. In addition we have continued to improve existing and add new QTLdb curation tools and user portal tools. The new additions include a batch data loading tool to speed up the curation process and a new API tool set to facilitate programming access to the database (see our poster #1157 for details).<br /> Facilitating research: The Data Repository for the aquaculture, cattle, chicken, and pig communities to share their genome analysis data has proven to be very useful (http://www.animalgenome.org/repository). New data is continually being added.<br /> A total of 1,126 data files on different animal genomes, supplementary data files to publications, and other sharing purpose have been made available to community users. More than 50 data files were shared/transmitted through the online data file-sharing tool by collaborators and/or groups in the community.<br /> Our helpdesk is here to assist community members. Throughout 2014, we have helped more than 60 research groups/individuals with their research projects and questions. Our involvement has ranged from data transfer, data assembly, and data analysis, to software applications, code development, etc. Please continue to contact us as you need help with bioinformatic issues. <br /> Community support and user services at AnimalGenome.ORG : We have been maintaining and actively updating the NRSP-8 species web pages for each of the six species. We have been hosting a couple dozen mailing lists/web sites for various research groups in the NAGRP community (http://www.animalgenome.org/community/). This includes groups like AnGenMap, "CRI-MAP users", "Sheep Models", etc. The most recent addition is a new web site for the Functional Annotation of ANimal Genomes (FAANG) project, with list mailing, user forum, wiki pages, and online publishing capabilities to support coordinated international action to accelerate Genome to Phenome. An increasing number of web hits and data downloads continued in 2014. For example, AnimalGenome.ORG received over 3.7 million web hits from 237,000 individual sites (visitors), which made 970,000 data downloads that generated almost 2 TB internet traffic.<br /> Reaching out: We have been sending periodic updates to over 2,500 users worldwide to inform them of the news and updated information we develop or host at AnimalGenome.ORG.<br /> More than 38 new items were updated to the community in 2014.<br /> PLANS FOR THE FUTURE: Develop, integrate, and implement bioinformatic resources to support the discovery of genetic mechanisms that underlie traits of interest. <br /> We will continue to work with bovine, mouse, rat, and human QTL database curators to develop minimal information for publication standards. We will also work with these same database groups to improve phenotype and measurement ontologies, which will facilitate transfer of QTL information across species. We will continue working with U.S. and European colleagues to develop a Bioinformatics Blueprint, similar to the Animal Genomics Blueprint recently published by USDA-NIFA, to help direct future livestock-oriented bioinformatic/database efforts. <br />

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Participants

Aquaculture - 84 attendees representing 18 Countries (US, Canada, Mexico, Norway, Australia, China, Netherlands, Thailand, Malaysia, Germany, Chile, UK, France, New Zeeland, Turkey, Columbia, Taiwan, Japan) and 53 institutes.

Cattle and Sheep/Goat (joint) - 200 people attending each one of the scientific sessions. Out of these attendees, ~ 44% were international attendees from at least 29 countries, including Australia, Belgium, Brazil, Canada, Chile, China, Denmark, Egypt, Ethiopia, France, Germany, Ireland, Italy, Japan, Kenya, Mexico, Netherlands, New Zealand, Norway, South Africa, South Korea, Spain, Sweden, Switzerland, Taiwan, Thailand, Uganda, UK, Uruguay. Approximately 25 people attended the station reports session.

Horse - Approximately 80 people attended the sessions with participants from at least 10 countries (USA, Brazil, China, Japan, Korea, Denmark, United Kingdom, Italy, Argentina, Ireland).

Poultry - not available

Swine - 33 people signed in, although it is estimated that at least 75 were present for the invited talks. Among those signing in, 12 attendees represented 7 countries outside the US, and the 21 US attendees were from 10 universities, 3 industry companies and 2 government agencies.

Brief Summary of Minutes

Accomplishments

<p>See Summary of Minutes attachment.</p>

Publications

<p>See Summary of Minutes attachment and document attached here.</p>

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Participation in NRSP 8 Workshops -
Aquaculture – 85 attendees, representing 47 institutions and 16 countries
Equine – 78 attendees
Pig – 58 attendees, representing 40 institutions and 8 companies
Poultry – 120 attendees, representing 6 countries
Cattle and small ruminants - ~300 attendees

Brief Summary of Minutes

Accomplishments

<p>See summary of minutes for accomplishments from the various species groups.</p>

Publications

<p>See summary of minutes for publication list from each species group.</p>

Impact Statements

1. See summary of minutes for impacts from the various species groups.

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Participants

120 participants from 20 countries attended the combined species workshop.

50+ participants from 42 institutions attended the Aquaculture workshop.

90+ participants from 20+ institutions attended the Equine workshop.

75+ participants from 16 institutions attended the Poultry workshop

16 participants from 14 institutions attended the Sheep & Goats workshop.

68 participants from 10 institutions attended the Swine workshop.

Brief Summary of Minutes

Accomplishments

<p><strong><span style="text-decoration: underline;">SUMMARY OF NRSP-8 ACCOMPLISHMENTS </span></strong><strong><span style="text-decoration: underline;">(2013-2017)</span></strong></p><br /> <p><strong>Overview of accomplishments for all NRSP-8 technical committees</strong></p><br /> <p>The most important accomplishment of the NRSP-8 has been the formation of a large community of scientists working worldwide to advance animal genomics through the sharing of resources, development of open-access multi-species bioinformatic tools, sequencing and assembly of genomes, organization of workshops and conferences, communication of results, support for travel for students and invited speakers, preparation of multi-institutional grant proposals, and formation of large collaborative research groups. The communication and sharing of information among the different species technical committees fostered by NRSP-8 has led to significant achievements under each of the three objectives outlined for 2013-2017. Across committees, the experience of one group has often informed and influenced the directions and approaches taken by other groups and this shared knowledge has accelerated tool development and discovery for all supported species. A summary of the important accomplishments and impacts for each of the technical committees (aquaculture, cattle, horse, poultry, sheep/goat, swine and bioinformatics) are included below. Here we highlight a few of the accomplishments shared across multiple species for each of the three objectives.</p><br /> <p><strong>Objective 1: Advance the status of reference genomes for all species, including basic annotation of worldwide genetic variation, by broad sequencing among different lines and breeds of animals. </strong>Between 2013 and 2017, reference genomes were assembled for the pig, turkey, sheep, goat, catfish pacific oyster, rainbow trout and striped bass. In addition, genome reference assemblies were improved for the chicken, cow, horse, pig and rainbow trout with researchers capitalizing on short-read sequencing technologies, optical mapping, Pacific Biosciences sequencing and other technologies. Across all species, these improved assembles reached high-quality chromosome levels, eliminated most of the regions with ambiguous sequences, and in some cases provided sequence for previously unsequenced autosomes. Genome annotation and gene predictions were enhanced in several species using a variety of methods including RNA sequencing (RNA-Seq) of protein coding RNA, micro RNA (miRNA), and long non-coding RNA (lncRNA), full-length transcript sequencing using Iso-seq, and coordinated efforts to manually annotate genes.</p><br /> <p>Efforts were initiated in the cow, pig, chicken, horse, sheep, rainbow trout and pacific oyster to annotate additional functional elements of the genome as part of a new initiative, the Functional Annotation of ANimal Genomes (FAANG) consortium. The FAANG consortium was formed in 2014 with the goal of accelerating genome-to-phenome discovery in NRSP-8 species. In the first phases of this effort, a number of investigations have been proposed or initiated across 80-105 tissues, depending on the species. These include whole genome sequencing; whole genome bisulfite sequencing; RNA sequencing (mRNA, miRNA, ncRNA) and transcriptome assembly; ATAC-seq; ChIP-seq with DNAse I, histone modification marks, insulator-binding protein CCCTC-binding factor, and important transcription factors; and the study of the genome-wide chromatin interactome using Hi-C. Is it worth noting that this is the first time some of these technologies have been applied to some of these species.&nbsp; Work is ongoing among members of the FAANG project to standardize collection techniques, experimental protocols, and data analysis pipelines to maximize the utility of the data produced by this effort.</p><br /> <p><strong>Objective 2:</strong> <strong>Develop strategies to identify and exploit genes and allelic variation that contribute to economically relevant phenotypes and traits, in part through improving functional annotation of the genomes of our species. &nbsp;</strong>From 2013 to 2017, single nucleotide polymorphism (SNP) high-throughput genotyping arrays were developed for several species including Equine (54K, 65K, 670K and 2M arrays), chicken (670K), cattle (250K functional allele array), sheep (600K), goat (52K), swine (670K) and rainbow trout (57K, 50K functional allele arrays). For all species, the impacts of these SNP genotyping arrays include: permitting genome-wide analyses such as genome-wide association studies (GWAS) and genomic signatures of selection for identification of genomic regions harboring alleles for traits of interest; allowing for, and improving the accuracy of predicted breeding values; enabling genomic selection; and permitting estimation of genetic diversity in breeds and populations of interest. Across species tools developed under this objective have allowed for identification of alleles responsible for important economic and disease traits, including alleles important in infectious diseases such as GBP5 associated with resistance/susceptibility to primary PRRS virus infection in pigs. In addition, the dairy industry has used SNP-chips to genotype nearly over one million dairy cattle allowing application of genomic selection which has reduced animal selection generation interval (from 5 years to less than one year) and has increased genetic merit prediction accuracy by more than 30 percent with an estimated annual benefits of $100 million per year.</p><br /> <p><strong>Objective 3:</strong> <strong>Facilitate analysis, curation, storage, distribution and application of the enormous datasets now being generated by next-generation sequencing and related "omics" technologies with regard to animal species of agricultural interest. </strong>Successful efforts have been made to develop platforms to facilitate collaborative research for collection and analysis of new, unique, and interesting phenotypes, and to develop, integrate, and implement bioinformatic resources to support the discovery of genetic mechanisms underlying agriculturally important traits. For example, the Animal Quantitative Trait Loci database (Animal QTLdb) was updated with 104,272 new quantitative trait loci (QTL). To date, the database contains 95,332 cattle, 6,633 chicken, 1,245 horse, 16,516 pig, 1,412 sheep and 127 rainbow trout loci that have been associated with many traits of interest. Further, the data repository for the aquaculture, cattle, chicken, horse, pig, and sheep communities to share their genome analysis data has proven to be very useful for the community with 1,140 data files, totaling 140 GBGb, shared through this platform. Finally, a collaborative VCF information-mining platform was developed to allow for sharing discovered genetic variants between researchers.</p><br /> <p>In addition to direct contributions to each of the three objectives, NRSP-8 participants have leveraged the NRSP-8 investment in tools and infrastructure into at least $94.5 million dollars in funding to study diverse animal models to investigate fundamental mechanisms of genome biology and physiology and pathophysiology affecting production efficiency, product quality, animal health, disease resistance and food safety and to develop additional bioinformatics resources (see <strong>Table 1</strong>). Finally, the annual NRSP-8 workshops have become an essential component for the development of collaborations, training and dissemination of new information to government, academic, and industry stakeholders in animal agriculture. NRSP-8 species coordinators&rsquo; funds have been used to support travel for 146 postdoctoral and graduate students to the NRSP-8 meetings that are held in conjunction with the annual Plant and Animal Genome (PAG) meeting.&nbsp;</p><br /> <p>&nbsp;</p><br /> <table width="0"><br /> <tbody><br /> <tr><br /> <td width="199"><br /> <p>&nbsp;</p><br /> </td><br /> <td width="120"><br /> <p><strong>Federal </strong></p><br /> </td><br /> <td width="120"><br /> <p><strong>Private/Industry</strong></p><br /> </td><br /> <td width="90"><br /> <p><strong>Intramural</strong></p><br /> </td><br /> <td width="144"><br /> <p><strong>Total</strong></p><br /> </td><br /> </tr><br /> <tr><br /> <td width="199"><br /> <p><strong>Horse</strong></p><br /> </td><br /> <td width="120"><br /> <p>$14,605,017</p><br /> </td><br /> <td width="120"><br /> <p>$4,799,843</p><br /> </td><br /> <td width="90"><br /> <p>$3,440,344</p><br /> </td><br /> <td width="144"><br /> <p><strong>$22,845,204</strong></p><br /> </td><br /> </tr><br /> <tr><br /> <td width="199"><br /> <p><strong>Poultry</strong></p><br /> </td><br /> <td width="120"><br /> <p>$18,675,963</p><br /> </td><br /> <td width="120"><br /> <p>$150,000</p><br /> </td><br /> <td width="90">&nbsp;</td><br /> <td width="144"><br /> <p><strong>$18,825,963</strong></p><br /> </td><br /> </tr><br /> <tr><br /> <td width="199"><br /> <p><strong>Cattle</strong></p><br /> </td><br /> <td width="120"><br /> <p>$27,831,461</p><br /> </td><br /> <td width="120"><br /> <p>$73,000</p><br /> </td><br /> <td width="90">&nbsp;</td><br /> <td width="144"><br /> <p><strong>$27,904,461</strong></p><br /> </td><br /> </tr><br /> <tr><br /> <td width="199"><br /> <p><strong>Swine</strong></p><br /> </td><br /> <td width="120"><br /> <p>$8,229,905</p><br /> </td><br /> <td width="120"><br /> <p>$621,591</p><br /> </td><br /> <td width="90"><br /> <p>$533,500</p><br /> </td><br /> <td width="144"><br /> <p><strong>$9,384,996</strong></p><br /> </td><br /> </tr><br /> <tr><br /> <td width="199"><br /> <p><strong>Aquaculture</strong></p><br /> </td><br /> <td width="120"><br /> <p>$5,553,103</p><br /> </td><br /> <td width="120">&nbsp;</td><br /> <td width="90">&nbsp;</td><br /> <td width="144"><br /> <p><strong>$5,553,103</strong></p><br /> </td><br /> </tr><br /> <tr><br /> <td width="199"><br /> <p><strong>Sheep/goat</strong></p><br /> </td><br /> <td width="120"><br /> <p>$3,644,000</p><br /> </td><br /> <td width="120"><br /> <p>$109,000</p><br /> </td><br /> <td width="90"><br /> <p>$467,000</p><br /> </td><br /> <td width="144"><br /> <p><strong>$4,220,000</strong></p><br /> </td><br /> </tr><br /> <tr><br /> <td width="199"><br /> <p><strong>Bioinformatics /multispecies</strong></p><br /> </td><br /> <td width="120"><br /> <p>$5,753,033</p><br /> </td><br /> <td width="120"><br /> <p>&nbsp;</p><br /> </td><br /> <td width="90"><br /> <p>&nbsp;</p><br /> </td><br /> <td width="144"><br /> <p><strong>$5,753,033</strong></p><br /> </td><br /> </tr><br /> <tr><br /> <td width="199"><br /> <p><strong>Total</strong></p><br /> </td><br /> <td width="120"><br /> <p><strong>$84,292,482</strong></p><br /> </td><br /> <td width="120"><br /> <p><strong>$5,753,434</strong></p><br /> </td><br /> <td width="90"><br /> <p><strong>$4,440,844</strong></p><br /> </td><br /> <td width="144"><br /> <p><strong>$94,486,760</strong></p><br /> </td><br /> </tr><br /> </tbody><br /> </table><br /> <p>&nbsp;</p><br /> <p><strong><span style="text-decoration: underline;">AQUACULTURE</span></strong></p><br /> <p><a href="http://www.animalgenome.org/aquaculture/">http://www.animalgenome.org/aquaculture/</a></p><br /> <p><strong><span style="text-decoration: underline;">Direct contributions to Objective 1</span></strong><strong>:</strong></p><br /> <ul><br /> <li>Reference genome for catfish (2016). <strong>Impact(s): </strong>The genome reference will allow understanding the genes controlling performance traits. Technologies can be developed based on this information allowing superior catfish breeds that will help farmers increase profits.</li><br /> <li>Rainbow trout high-density 57K SNP chip was developed and characterized (2013). Approximately 50K of the SNPs were validated in a panel of 18 rainbow trout populations at the standard 97% call rate of the Affymetrix SNP polisher software. <strong>Impact(s): </strong>The SNP chip allowed improved accuracy of predicting breeding values for bacterial cold water disease resistance compared to a traditional pedigree-based model in rainbow trout aquaculture.</li><br /> <li>Reference genome for the Pacific oyster (2012). <strong>Impact(s): </strong>This genome provides a basis for numerous phenotype studies and provides insight into performance under changing environmental conditions.</li><br /> <li>Striped Bass Genetic Map (2012). The first genetic map of the genome of the striped bass was developed and published. <strong>Impact(s): </strong>This medium-density linkage map was based on 298 microsatellite markers and is enabling detection of QTL affecting production traits.</li><br /> <li>Rainbow Trout Reference Genome sequence (2012): A pooling and tagging scheme was used for sequencing of ~15,000 clones from the BAC fingerprinted physical map minimal tiling path (MTP). <strong>Impact(s): </strong>The map helped in assembling the trout genome.</li><br /> <li>Improved Rainbow Trout Reference Genome sequence (2017): The longest available read length of the Illumina technology was used to improve the genome sequence producing longer and better anchored scaffolds to chromosomes. <strong>Impact(s): </strong>The genome assembly led to SNP genotyping tools that are being used to accelerate genetic improvement.</li><br /> <li>Striped bass genome sequence assembly containing ~35 K scaffolds was produced (2015). <strong>Impact(s): </strong>The assembly should accelerate analysis of the striped bass genome, to identify and characterize genes affecting important production traits.</li><br /> </ul><br /> <p><strong><span style="text-decoration: underline;">Direct contributions to Objective 2</span></strong><strong>:</strong></p><br /> <ul><br /> <li>A 675K SNPs array was developed for catfish (2017). <strong>Impact(s): </strong>This array allowed for genetic mapping and validation of the reference genome sequence assembly as well as for identification of a genetic markers associated with aquaculture production traits in catfish.</li><br /> <li>A 57K SNPs array was developed for rainbow trout (2014). <strong>Impact(s): </strong>This array allowed for genetic mapping and improving assembly of the reference genome and evaluation genomic selection in rainbow trout.</li><br /> <li>A 50K cSNPs array was developed for rainbow trout (2016). <strong>Impact(s): </strong>This array allowed for allelic-imbalance analysis of genes that are associated with muscle yield and fillet quality traits and also with bacterial cold-water disease survivability.</li><br /> <li>Bulked segregant RNA-seq (BSR-Seq) was used to analyze differentially expressed genes and associated SNPs with disease resistance against enteric septicemia of catfish (ESC) (2013). A total of 1,255 differentially expressed genes were found between resistant and susceptible fish. <strong>Impact(s): </strong>These genes are candidates for further functional genomics work to validate their role in providing catfish with susceptibility to ESC.</li><br /> <li>QTL mapping families for stress response and bacterial cold-water resistance (BCWD) in rainbow trout (2013). <strong>Impact(s): </strong>The families are being used to study genes responsible for stress response and BCWD.</li><br /> <li>Illumina GoldenGate genotyping arrays were designed for <em>Crassostrea gigas</em> and <em>Ostrea edulis</em> (2014). <strong>Impact(s): </strong>These assays were used to genotype 1,000 individuals from wild and selected populations as well as families bred for commercially important traits.</li><br /> <li>Large intergenic noncoding RNAs (lncRNAs) were identified by RNA-Seq analysis of rainbow trout transcriptome (2016). <strong>Impact(s): </strong>Many of the lncRNAs are tissue-specific and functionally associated with important biological processes including resistance to the rainbow trout BCWD and muscle growth.</li><br /> <li>RNA-Seq analysis of miRNAs associated with different production quality traits in trout (2015 and 2017). <strong>Impact(s): </strong>Several miRNAs with epigenetic role associated with egg quality and muscle quality traits were identified.</li><br /> </ul><br /> <p><strong><span style="text-decoration: underline;">Direct contributions to Objective 3</span></strong><strong>:</strong></p><br /> <ul><br /> <li>Rainbow trout QTL database (2012) available through the Animal Genome website of the NRSP-8 bioinformatics group (http://www.animalgenome.org/cgi-bin/QTLdb/index) and is being continually updated. <strong>Impact(s): </strong>QTLs are available for industry to improve aquaculture production traits in rainbow trout.</li><br /> <li>Bioinformatics pipeline was developed for genotyping SNPs from raw sequence data for the GT-seq method (2014). <strong>Impact(s): </strong>The pipeline provides significant cost reduction for genotyping.</li><br /> <li><em> gigas</em> transcriptome information derived from 2.2 billion sequences from 114 RNA-seq datasets has been organized and deposited into a publicly available database: GigaTON (2015). <strong>Impact(s): </strong>The user interface provides powerful and user-friendly tools to search and retrieve annotation, expression, and polymorphism information of important genes related to aquaculture traits.</li><br /> </ul><br /> <p><strong><span style="text-decoration: underline;">Communication:</span></strong></p><br /> <ul><br /> <li>A strategic planning workshop for aquaculture genomics, genetics and breeding was held at Auburn University (2016). <strong>Impact(s): </strong>The workshop led to a white paper published in BMC Genomics that placed goals and priorities for future research in the aquaculture genomics, genetics and breeding in the US.</li><br /> <li>NRSP-8 Aquaculture leaders participated in establishing the FAASG (Functional Annotation of All Salmonid Genomes) consortium. <strong>Impact(s):</strong> The consortium will allow coordinating data sharing and establish an infrastructure for providing high quality functional annotation of salmonid genomes.</li><br /> </ul><br /> <p><strong><span style="text-decoration: underline;">Research support mini-grants (coordinator grants):</span></strong></p><br /> <ul><br /> <li>Approximately 25 mini-grants (~$10,000/each) supported projects that fall under all three primary objectives and include a variety of species.</li><br /> </ul><br /> <p><strong><span style="text-decoration: underline;">Travel support and opportunities for trainings:</span></strong></p><br /> <ul><br /> <li>Travel of 25 students/postdocs was funded to attend the Aquaculture workshop at PAG meetings (2012-2016). The purpose of the travel award program is to help graduate students and postdocs to travel to the annual PAG meeting to present their research.</li><br /> </ul><br /> <h1>Leveraged funds and stakeholders&rsquo; use of project outputs</h1><br /> <p>Leveraged funds from diverse projects totaling more than $5,553,103 from federal sources. Selected grants are highlighted below.</p><br /> <ul><br /> <li>Whole genome mapping of disease resistance/susceptibility-associated SNPs in catfish. USDA National Institute of Food and Agriculture Competitive Grant no. 2015-67015-22975. <strong>$500,000</strong>. John Liu (PD).</li><br /> </ul><br /> <p>This project is designed to address the following two objectives: 1). Genome wide scan of QTLs conferring resistance to ESC and columnaris using F2 and F4 fish using the 250K catfish SNP array; and 2). Fine QTL analysis by genotyping a large number of F2 and F4 individuals using evenly-spaced markers from mapped QTL regions. <strong>Impact(s): </strong>The impact of this grant will be to determine genes that will be used to select for fish resistant catfish</p><br /> <ul><br /> <li>Closing the tilapia genome assembly. USDA National Institute of Food and Agriculture Competitive Grant no. 67015-23088. <strong>$270,000</strong>. Tom Kocher (PD).</li><br /> </ul><br /> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; This project aims to improve the platform for genetic improvement of tilapia by developing a definitive sequence of the tilapia genome. <strong>Impact(s): </strong>The ultimate goal of the project is to improve the health and production of tilapia and related aquaculture species.</p><br /> <ul><br /> <li>Sequencing the Genome of the Eastern Oyster. USDA National Institute of Food and Agriculture Competitive Grant no. 2015-67016-22942. <strong>$242,051</strong> Marta Gonez-Chiarri (PD).</li><br /> </ul><br /> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; This project propose to develop these key resources and tools by performing the sequencing, assembly, and annotation of a reference genome and transcriptome for the Eastern oyster C. virginica. Genome researchers and bioinformatics experts, in collaboration with the Eastern Oyster Genome Consortium, will use state-of-the-art sequencing and assembly strategies to achieve these aims. <strong>Impact(s):</strong> The reference genome and transcriptomes for the Eastern oysters will aid the research community in the discovery of candidate genes and markers associated with traits of commercial, biological, and ecological importance in oysters.</p><br /> <ul><br /> <li>Development of 675K SNP arrays for whole genome mapping and genetic studies in catfish. USDA National Institute of Food and Agriculture Competitive Grant no. 2015-67015-22907. <strong>$485,000</strong> John Liu (PD).</li><br /> </ul><br /> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; This project addresses major limitations to adopting genome technologies in aquaculture that currently are the lack of a high- throughput technology for the analysis of genomic variations in relation to phenotypic variations. We need a high-density SNP array technology that allows high- efficiency, cost-effective, whole-genome coverage, analysis of genetics of important performance traits such as disease resistance. This project is poised to resolve these challenges, with three specific objectives: 1) Developing the catfish 675K SNP arrays; 2). Genetic mapping of whole genomic sequence scaffolds; 3). Enhancing and validating the catfish whole genome assembly. <strong>Impact(s):</strong> This project will address the most significant problem currently existing in catfish genomics. This project will develop a technology for the most efficient analysis of performance traits, and will literally transform the isolated whole genome sequence tags into a well-assembled reference genome assembly, thereby enabling its application in breeding and selection programs.</p><br /> <ul><br /> <li>Homozygous clonal rainbow trout lines as genomic resources. USDA National Institute of Food and Agriculture Competitive Grant no. 2016-67015-24472. <strong>$485,000</strong>. Gary Thorgaard (PD).</li><br /> </ul><br /> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Doubled haploid lines have unique value as genomic tools because they have minimal heterozygosity and allow full chromosomal haplotypes to be identified. These lines have been used for the rainbow trout genome sequencing project and for QTL studies. The experimental objectives will include: (1) Establish at least 12 lines within the USDA. (2) Transfer cryopreserved semen from each line as an ongoing repository. (3) Generate a repository of frozen tissues and genomic DNA. (4) Conduct baseline karyotype analysis and SNP typing by re-sequencing of two of the lines. (5) Attempt to induce sex reversal to females in the YY lines and test their fertility. <strong>Impact(s):</strong> The project will assure continued availability of the lines to the trout research community, develop sperm, tissue and DNA repositories and improve propagation methods.</p><br /> <ul><br /> <li>SNP markers for muscle, growth and fillet quality traits in rainbow trout. USDA National Institute of Food and Agriculture Competitive Grant no. 2014-67015-21602. <strong>$500,000</strong>. Mohamed Salem (PD).</li><br /> </ul><br /> <p>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; The project aims to find genes and to develop genetic markers that would be used in USDA marker-assisted selection programs to develop food fish strains with superior muscle growth and fillet quality in rainbow trout. This project is expected to produce a large number of true genetic markers that provide a valuable resource for determination of genetic merit of growth and carcass traits in rainbow trout. Project outcomes including, knowledge, expertise, methods, tools, and technologies, will be disseminated to the US aquaculture industry/stakeholders including the US largest producers of rainbow trout food fish and eggs. <strong>Impact(s):</strong> These genetic markers may be quickly adapted to other species and give the US aquaculture industry a competitive advantage.</p><br /> <p><strong><span style="text-decoration: underline;">Major impact products (could be potential impact):&nbsp;&nbsp; </span></strong></p><br /> <p>Recently, the first genome-wide SNP arrays have been developed and applications of the SNP-chip technology in genomic selection have just begun to be adapted by commercial breeders of some aquaculture species including catfish (600K), salmon (286K), rainbow trout (57K) and oyster (190K).</p><br /> <p>&nbsp;</p><br /> <p><strong><span style="text-decoration: underline;">CATTLE</span></strong></p><br /> <p><a href="http://www.animalgenome.org/cattle/">http://www.animalgenome.org/cattle/</a></p><br /> <p><strong><span style="text-decoration: underline;">Direct contributions to Objective 1</span></strong><strong>:</strong></p><br /> <ul><br /> <li>An improved bovine genome reference sequence assembly of Dominette (the reference animal) based on multiple data types developed by the bovine community (optical map, Illumina paired-end, PacBio sequence, and improved gene predictions based on RNA-Seq and Iso-Seq data) will be released in Fall of 2017. <strong>Impact(s): </strong>This improved assembly will help with the identification of genetic markers associated with economically important traits in cattle.</li><br /> </ul><br /> <p><strong><span style="text-decoration: underline;">Direct contributions to Objective 2</span></strong><strong>:</strong></p><br /> <ul><br /> <li>A 250K functional variant assay was made available to cattle researchers. The assay was designed using various sources of sequence data derived from AFRI-funding and is focused on the detection of genic variants likely to be functional in taurine cattle. <strong>Impact(s): </strong>This tool will assist researchers to identify genetic identifying causative SNPs that are associated with economically important traits and which are likely to be useful in marker-assisted selection across multiple breeds.</li><br /> </ul><br /> <p><strong><span style="text-decoration: underline;">Direct contributions to Objective 3</span></strong><strong>:</strong></p><br /> <ul><br /> <li>A database (Animal-GRIN) has been developed to serve as a permanent archive for DNA data, germplasm/tissue samples, and phenotypic and production system data from large animal genomics projects. <strong>Impact(s): </strong>This database will allow for future data mining and value capture from the data and samples collected by publicly funded research.</li><br /> </ul><br /> <p><strong><span style="text-decoration: underline;">Communication:</span></strong><span style="text-decoration: underline;">&nbsp; </span></p><br /> <ul><br /> <li>A bovine genome newsletter was prepared by the bovine coordinators and distributed to the AnGenMap listserve. <strong>Impact(s): </strong>This helped inform the bovine research community of ongoing developments with the bovine genome.</li><br /> <li>Two industry conferences were held, the &ldquo;2015 Applied Reproductive Strategies in Beef Cattle (ARSBC) Conference Grant&rdquo;, and &ldquo;New Approaches to Bovine Respiratory Disease Prevention, Management, and Diagnosis&rdquo; with support from USDA, National Institute of Food and Agriculture Conference Grants (2014-67015-21562; 2015-67015-23693). Proceedings were produced from both conferences, and the latter was published in Animal Health Reviews.</li><br /> </ul><br /> <p><strong><span style="text-decoration: underline;">Research support mini-grants (coordinator grants):</span></strong></p><br /> <ul><br /> <li>Livestock FAANG project (lead by H. Zhou, P. Ross and I Korf) Coordinator funds ($30,000)]. [The project allowed for sample collection from 4 individuals (2 males and 2 females). These funds were used as leverage that resulted in ~$500,000 grant from the USDA NIFA and another ~$100,000 from National Pork Board, Aviagen etc. for FAANG data collection on these samples.</li><br /> </ul><br /> <p><strong><span style="text-decoration: underline;">Leveraged funds and stakeholders&rsquo; use of project outputs:</span></strong></p><br /> <p>From 2013-2017, the investigators and stakeholders leveraged the tools and resources generated through NRSP-8 to obtain at least $27,904,461 additional funding from federal sources, in funding from private foundations and industry sources. Selected grants are highlighted below.</p><br /> <ul><br /> <li>Integrated program for reducing bovine respiratory disease complex in beef and dairy cattle. USDA National Institute of Food and Agriculture Competitive Grant no. 2011-68004-30367. <strong>$9,750,000</strong>. Jim Womack (PD). The objective of this Coordinated Agricultural Project was to use genomic tools to identify genetic markers associated decreased susceptibility to bovine respiratory disease. This is the most important disease in both the beef and dairy cattle industry with estimated losses of more than one billion dollars annually. This project used genome sequences to fine map genetic variants associated with respiratory disease, with the aim of delivering a tool that the industry can use to select for cattle that are less susceptible to respiratory disease. <strong>Impact(s): </strong>The impact of this grant will be decreased morbidity and antibiotic use in cattle production, and improved animal health and welfare.</li><br /> <li>2015-2017: USDA NIFA 2015-67015-23183. &ldquo;Application of a functional variant assay and sequence imputation to identify large-effect QTL underlying feed efficiency and component traits in beef cattle.&rdquo; Taylor JF, RD Schnabel, JE Decker, CS Seabury and HL Neibergs. 4/1/15-03/31/17. <strong>$500,000</strong>. This grant supported the development of the GGP-F250 functional assay. The accomplishment is that we successfully designed an assay for which 173,609 variants can be assayed with a marker call rate of at least 90%. These variants are highly enriched for rare functional variation within the bovine genome and include 82,979 variants that alter amino acids within gene products, 665 Indels that either alter frame or add/delete amino acids, 2017 splice site variants and 44,358 variants within untranslated regions. The assay is currently publicly available through GeneSeek. <strong>Impact(s): </strong>Impacts of this grant include 23,541 variants within QTL regions detected in the BRD and Feed Efficiency grant that were identified and included on the assay and 1978 BRD case-control and 4609 Feed Efficiency project animals have been genotyped with the assay to fine-map QTL. The assay also contains 2,224 variants for which no homozygotes were detected. These are currently being mapped to genes known to be essential for life to identify candidates for lethal alleles segregating in cattle. Finally, the assay is expected to aid in the process of imputing genotypes to whole genome sequence, because, contrary to the currently used assays which are strongly enriched for common variants, the GGP-F250 is enriched for rare variants and the linkage disequilibrium that exists among rare variants will aid in the imputation of genotypes for this class of variant.</li><br /> <li>2013-2017: USDA-NIFA-AFRI. 2013-68004-20364. &ldquo;Identification and management of alleles impairing heifer fertility while optimizing genetic gain in Angus cattle.&rdquo; Patterson DJ, JF Taylor, A Van Eenennaam, S Brown and M Smith. <strong>$2,997,040</strong>. This grant supported the whole genome sequencing of the 100 registered Angus bulls that have had the greatest impact on the breed as determined by the number of registered descendants. These animals, along with sequences obtained on 162 additional animals from 12 other taurine breeds, were used to identify variants genome wide. With support from the three other USDA grants (Bovine Respiratory Disease, Feed Efficiency and Functional Variant), we designed the GGP-F250 assay for which 173,609 variants can be assayed with a marker call rate of at least 90%. These variants are highly enriched for rare functional variation within the bovine genome and include 82,979 variants that alter amino acids within gene products, 665 Indels that either alter frame or add/delete amino acids, 2017 splice site variants and 44,358 variants within untranslated regions. <strong>Impact(s): </strong>The assay is currently publicly available through GeneSeek allowing genetic gain assessment for important production phenotypes in Angus cattle.</li><br /> <li>2016-2019: NIH 1R01HD084353. &ldquo;Linking Fertility-Associated Gene Polymorphisms to Aberrant Sperm Phenotypes.&rdquo; Sutovsky P, RD Schnabel, JF Taylor. 7/1/2016-6/30/21. <strong>$2,149,000</strong>. This grant has just started but plans to sequence 100 bulls with either sperm abnormalities or with extreme differences for conception rate to identify mutations in genes known to be expressed in sperm that are responsible for the defects and variants that are candidates for genetic variation in male fertility. We have begun the collection of sperm samples from US and Canadian AI companies. <strong>Impact(s):</strong> The project is expected to identify and validate sperm phenotype biomarkers encoded by fertility associated polymorphic genes, and to improve sire management by genetic selection and automated semen evaluation. This project will also yield new methods and potentially new treatments for human male and idiopathic infertility.</li><br /> <li>Gene Seek and Zoetis provided industry funds and support to leverage the cost of developing the new bovine genome assembly, <strong>$73,000</strong>.</li><br /> </ul><br /> <p><strong><span style="text-decoration: underline;">Travel support and opportunities for trainings:</span></strong></p><br /> <ul><br /> <li>Funding was used to bring students to the annual PAG meeting based on a competitive travel award. Coordinator funds were also used on several occasions to help support the NRSP8 speaker at PAG.</li><br /> </ul><br /> <p><strong><span style="text-decoration: underline;">Major impact products (could be potential impact):</span></strong></p><br /> <ul><br /> <li>Genomic selection has dramatically improved the rate of genetic progress within the US dairy industry. The dairy industry has used SNP-chips to genotype over 1 million dairy cattle. Application of GS reduced animal selection generation interval (from 5 years to less than one year) and has increased prediction accuracy by more than 30 percent for an estimated annual benefits of $100 million per year.</li><br /> <li>Genomic selection is starting to be implemented in the US beef industry.</li><br /> <li>Development of a 173,609 SNP functional variant assay containing variants highly enriched for rare functional variation within the bovine genome and including 82,979 variants that alter amino acids within gene products, 665 Indels that either alter frame or add/delete amino acids, and 2017 splice site variants. The assay is currently publicly available through GeneSeek.</li><br /> </ul><br /> <p>&nbsp;</p><br /> <p><strong><span style="text-decoration: underline;">HORSE</span></strong></p><br /> <p>http://www.uky.edu/Ag/Horsemap/</p><br /> <p><strong><span style="text-decoration: underline;">Direct contributions to Objective 1</span></strong><strong>:</strong></p><br /> <ul><br /> <li>A new reference genome build (EqCab 3.0) was created for the horse and shared among workshop participants. Public release and publication is expected in late 2017. Morris Animal Foundation, NRSP-8 coordinator and other federal funds supported this work. <strong>Impact(s): </strong>The new assembly improved gene annotation, increased contig N50 from 112 Kb to 1.4 Mb, and eliminated most of the regions with ambiguous sequence (&ldquo;Ns&rdquo;). The improved reference will increase the power and efficacy of genomics research to discover the genes and alleles underlying disease and economically important performance traits in the horse.</li><br /> <li>The annotation of the horse genome was improved through investigations of gene expression and splice variation that occurs among diverse tissues. Data supporting wide- scale annotations of the horse genome were published in several reports (2013-2016). <strong>Impact(s): </strong>Improved annotation provides context for the discoveries by making it possible to identify the functional aspects of genetic variation.</li><br /> <li>SNP and insertion-deletion polymorphism discovery was performed using whole genome sequence from 153 horses as part of an effort to design 2M and 670K SNP Affymetrix SNP arrays. <strong>Impact(s):</strong> This work documents the extent of variation that exists among 24 horse breeds and made genotypes from 485 horses across 2M SNPs publically available providing raw material for use in developing research tools. (Schaefer RJ, <em>et al</em>. Developing a 670k genotyping array to tag~ 2M SNPs across 24 horse breeds. <em>BMC Genomics 18.1 (2017): 565</em>).</li><br /> </ul><br /> <p><strong><span style="text-decoration: underline;">Direct contributions to Objective 2</span></strong><strong>:</strong></p><br /> <ul><br /> <li>An assay tool to assay ~65K SNPs (SNP70) was developed to replace the ~54K SNP (SNP50) tool in 2013. The development of this tool was a collaborative activity of the NRSP-8 community and made publicly available. An imputation pipeline between these two moderate-density arrays was developed. (McCoy AM, McCue ME. Validation of imputation between equine genotyping arrays. <em>Animal Genetics </em>45:153, 2014. PMCID: PMC4000747.) <strong>Impact(s): </strong>Developing this tool and imputation pipeline made it possible to continue to perform genome-wide analyses that impact the health and welfare of horses.</li><br /> <li>SNP discovery based on whole genome sequence from 153 horses was used to construct the next generation 2M and 670K SNP Affymetrix SNP arrays for equine whole genome analyses. The 670K array is designed for imputation and enables data from prior lower density SNP arrays to be imputed up to ~1.8M SNPs. The equine 670K SNP chip was made available in 2015. (Schaefer RJ, <em>et al</em>. Developing a 670K genotyping array to tag~ 2M SNPs across 24 horse breeds. <em>BMC Genomics 18.1 (2017): 565.</em>). <strong>Impact(s): </strong>This 670K array and imputation resource improves genome coverage more than 30-fold over the medium density (54K and 65K) SNP arrays. More than 20,000 670K genotyping arrays have been used to date. This increase in SNP density will allow for GWAS in genetic diverse breeds of economic importance such as the American Quarter Horse (~4 million registered individuals).</li><br /> <li>Because of the closing of the commercial operation of the BAC library, the primary CHORI 241 BAC library was moved from the Children&rsquo;s' Hospital of Oakland to the laboratory of Samantha Brooks (co-coordinator) at the University of Florida. <strong>Impact(s): </strong>This will ensure continued access to the library for equine researchers. This resource is key for investigating the broader aspects of structure and organization of the horse genome.</li><br /> </ul><br /> <p><strong><span style="text-decoration: underline;">Direct contributions to Objective 3</span></strong><strong>:</strong></p><br /> <ul><br /> <li>Horse technical committee members joined the FAANG initiative to generate gene expression data for 38 of tissues from two horses. In connection, competitive, extramural industry funding was obtained to further develop this dataset. <strong>Impact(s): </strong>This resource will empower research in the area of functional genomics.</li><br /> <li>The horse genomics community actively utilized the collaborative resources provided in the AnimalGenome.org Data Repository. The site hosts large shared files, prepublication works and polymorphism data.</li><br /> <li>Horse specific transcriptome assemblies not yet curated by NCBI were made available at AnimalGenome.org and through GitHub (<a href="https://github.com/drtamermansour/horse_trans">https://github.com/drtamermansour/horse_trans</a>). <strong>Impact(s):</strong> This resource increases the publically availability of equine transcriptional data and will improve genome annotation.</li><br /> <li>With the assistance of horse genome researchers, the AnimalQTL database added horse to the species list. <strong>Impact(s): </strong>This resource provides rapid access to 1,245 equine QTL and associated metadata.</li><br /> <li>Horse genome workshop members deposited 1,524 genomic SRA archives for the horse. These accessions contain many fully re-sequenced genomes, as well as targeted datasets generated by diverse NGS platforms. <strong>Impact(s): </strong>This resource increases the publically availability of equine whole genome sequence and transcriptomic data.</li><br /> </ul><br /> <p><strong><span style="text-decoration: underline;">Communication:</span></strong><span style="text-decoration: underline;">&nbsp; </span></p><br /> <ul><br /> <li>Additional workshops were conducted for NRSP-8 participants in connection with the International Society of Animal Genetics ([ISAG] 2016 [Salt Lake City], ISAG 2014 [Xian, China], ISAG 2012 [Cairns, Australia], and ISAG 2017 [Dublin, Ireland]). <strong>Impact(s): </strong>These meetings facilitated communication and collaborations among international scientists working on all species and extended discussions conducted at the annual NRSP-8 workshops.</li><br /> <li>Additional workshops were conducted with support of the Dorothy Russell Havemeyer Foundation that focused on issues related to horse genomics (2013 [Azores, Portugal], 2015 [Hannover, Germany], 2018 [planned, Pavia, Italy]). <strong>Impact(s): </strong>These workshops include the entire international horse genomics research community and facilitate exchange of information and collaboration between scientists.</li><br /> <li>Following the identification of critical needs in coordinating collaborations across institutions for new and evolving projects, an initiative to provide a database of ongoing work is now hosted thorough collaboration with the Interbull.org service. <strong>Impact(s):</strong> This database currently provides a listing of projects recruiting samples, but may eventually expand to include file sharing for exchange of SNP and NGS datasets.</li><br /> </ul><br /> <p><strong><span style="text-decoration: underline;">Research support mini-grants (coordinator grants):</span></strong></p><br /> <ul><br /> <li>Matching funds provided to support development of the SNP70 SNP genotyping array (~65K SNPs) for discovery research on the genomics of horses.</li><br /> <li>Matching Funds provided to support development of the 670K SNP genotyping array. Primary funding from USDA-NIFA ( Molly McCue PI) along with coordinator funds were used to develop a 2M test array. 670K SNPs were selected to tag ~1.8M SNPs across 24 horse breeds.</li><br /> <li>Matching funds provided for EqCab 3.0. Primary funding from the Morris Animal Foundation. Improved predictions from assembly.</li><br /> <li>Matching funds provided to develop FAANG resources for horse; primary funding came from Grayson-Jockey Club Research foundation project Developing resource for functional genomics research.</li><br /> </ul><br /> <p><strong><span style="text-decoration: underline;">Leveraged funds and stakeholders&rsquo; use of project outputs:</span></strong></p><br /> <p>From 2012-2017, the equine investigators leveraged the tools and resources generated through NRSP-8 to obtain <strong>$22,845,204</strong> in additional funding. This included <strong>$</strong><strong>14,605,017</strong> in funding from federal sources, <strong>$</strong><strong>4,799,843</strong> in funding from private foundations and industry sources and <strong>$</strong><strong>3,440,344</strong> in intramural funding. Selected grants are highlighted below.</p><br /> <ul><br /> <li>&ldquo;<strong>Genetic diversity and selection in the domestic horse</strong>.&rdquo; Dr. Molly McCue PI, Dr. James Mickelson Co-I, and others<strong> $499,481</strong> USDA-AFRI. <strong>Impact(s):</strong> This proposal quantified genetic diversity and to identify functional alleles that cause variation in size, locomotion and athletic phenotypes among 36 domestic horse breeds.</li><br /> <li>&ldquo;<strong>Tools to Link Genotype to Phenotype in the Horse</strong>.&rdquo; Dr. Molly McCue PI, Dr. James Mickelson Co-I, and others. <strong>$499,727 </strong>USDA-NIFA. In this proposal builds upon the recent development of high-density SNP arrays to develop tools that further facilitate GWAS in the horse by: <strong>1)</strong> enabling complementary GWAS approaches including gene, haplotype, and pathway-based analyses through SNP-to-gene mapping and the construction of a haplotype map; <strong>2)</strong> increasing marker density by developing an imputation resource; and <strong>3)</strong> constructing context-specific co-expression networks for integrated network-based association analysis.&nbsp; Prioritization of candidate genes is assisted by: <strong>4)</strong> refining the physical annotation of mRNAs, lncRNAs, and miRNAs; and <strong>5)</strong> improving functional annotation of these loci through tissue-specific gene expression and gene co-expression networks. Finally, the identification of functional alleles will be accelerated by <strong>6)</strong> developing a comprehensive catalog of genetic variants from WGS of &gt;450 horses.</li><br /> <li>&ldquo;<strong>Functional Prioritization of Candidate Genes and Alleles for Equine Metabolic Syndrome</strong>.&rdquo; Dr. Molly McCue PI, Dr. James Mickelson Co-I. <strong>$499,815 </strong>USDA-NIFA. Genome wide association in Welsh Ponies (WP) and Morgan horses has identified &gt;180 chromosomal regions of interest (ROI) harboring &gt;3,000 positional candidate genes associated with Equine Metabolic Syndrome (EMS) phenotypes. The objectives of this proposal are to <strong>1)</strong> prioritize candidate genes using skeletal muscle and/or adipose tissue gene expression or alterations in serum metabolite abundance to support their role in EMS pathophysiology; and <strong>2)</strong> identify the functional alleles underlying EMS phenotypes.</li><br /> <li>&ldquo;<strong>Discovering Causal Variants for Complex Disease Using Functional Networks in the Horse</strong>.&rdquo; Dr. Rob Schaefer PI, Dr. Molly McCue mentor. <strong>$150,000</strong> USDA-NIFA. The goals of this grant are to develop software tools to integrate available sources of genomic data and functional data (WGS, SNP, RNA-sequencing, proteomics and metabolomics) in agricultural species to better understand complex phenotypic traits using metabolic syndrome in the domestic horse as a test case.</li><br /> <li>&ldquo;<strong>Protein Networks Mediating Airway Hyper-Responsiveness In Equine Airways</strong>.&rdquo; Dr. Chipper Swiderski <strong>$438,153</strong> USDA-AFRI. This grant seeks to better understand the etiopathogenesis of Recurrent Airway Obstruction in the horse through proteomic studies and improved annotation of genes expressed during disease exacerbation.</li><br /> <li>&ldquo;<strong>Comparative Genomics in Qatar</strong>.&rdquo; Dr. Doug Antczak and Dr. Samantha Brooks, <strong>$1,030,000</strong> Qatar National Research Foundation- National Priorities Research Program. This project will document variation and signatures of selection in desert breeds of horse, as part of a larger effort to improve genomic resources in desert adapted hoof stock.</li><br /> <li>&ldquo;<strong>Identification of Genetic Factors Responsible for Establishment of Equine Arteritis Virus Carrier State in Stallions</strong>.&rdquo; Dr. Uri Balasuriya PI, Dr. Ernie Bailey Co-PI and others. <strong>$2,930,000</strong> USDA-AFRI.</li><br /> </ul><br /> <p><strong><span style="text-decoration: underline;">Travel support and opportunities for training:</span></strong></p><br /> <ul><br /> <li>Travel of 64 students/postdocs was funded to attend the Equine workshop at PAG meetings (2012-2016). The purpose of the travel award program is to help graduate students and postdocs to travel to the meeting to present their research.</li><br /> <li>Support for five NRSP-8 members to attend GO-FAANG workshop in Washington DC to provide leadership horse group in connection with this initiative.</li><br /> <li>Member sent to participate in Hack-a-thon in Europe 2016 in support of FAANG activities. Integration with international efforts to develop functional genomics databases for animal genomics.</li><br /> </ul><br /> <p><strong><span style="text-decoration: underline;">Major impact products (could be potential impact):</span></strong></p><br /> <ul><br /> <li>Development of 4 SNP genotyping arrays (54K, 65K, 670K and 2M). <strong>Impact(s):</strong> These arrays allow for efficient and economic performance of dozens of genome-wide analyses in the horse.</li><br /> <li>Genomic diagnostics in the horse have now expanded to include commercially available tests over 100 markers contributing to more than 40 diverse traits. <strong>Impact(s): </strong>Costs per test are falling, and as adoption of genomic selection and mandatory genetic testing increases across the industry, translating in to reduced economic losses due to genetic disease.</li><br /> <li>Diagnostic tests created for markers related to performance, disease and color, including <em>DMRT3</em> and gait, <em>TBX3</em> and dun color, <em>SHOX</em> and dwarfism, <em>B4GALT7</em> and dwarfism, <em>ACAN</em> and dwarfism, <em>RFWD3</em> and Appaloosa color pattern, <em>SERPINB11</em> and hoof quality, <em>KIT</em> and spotting in donkeys, <em>HOXD3</em> and occipitoalantoaxial malformation, <em>CXCL16</em> and susceptibility to equine arteritis virus.</li><br /> <li>Additional targets for investigation were identified through genome-wide analyses including signatures of selection in 38 horse breeds, genomic loci contributing to osteochondrosis, recurrent laryngeal neuropathy and others.</li><br /> <li>Molecular tests to identify chromosome abnormalities were reported and additional test are being developed. <strong>Impact(s): </strong>Chromosome abnormalities are the most common genetic cause of infertility and disease amongst horses and molecular tests are much less expensive than conventional karyotyping.</li><br /> <li>The major histocompatibility complex plays a major role in the occurrence and consequences of allergic and infectious diseases. Determinants playing a role in specific diseases were identified and methods were developed to improve our ability to identify yet other MHC determinants. <strong>Impact(s):</strong> MHC is a genetically complex region but plays a major role in immune responses.&nbsp; Knowledge of the MHC remains incomplete for all species and but research is turning up applications, especially with respect to vaccine design and immune therapy.</li><br /> </ul><br /> <p><strong><span style="text-decoration: underline;">&nbsp;</span></strong></p><br /> <p><strong><span style="text-decoration: underline;">POULTRY</span></strong></p><br /> <p><a href="https://www.animalgenome.org/poultry/">https://www.animalgenome.org/poultry/</a></p><br /> <p><strong><span style="text-decoration: underline;">Direct contributions to Objective 1</span></strong><strong>:</strong></p><br /> <ul><br /> <li>The chicken genome build (Galllus_gallus-5.0) was released to the public in 2015. <strong>Impact(s): </strong>This improved build, which was aided by long single molecular sequencing and finished BACs, yielded a gain of 180 Mb in assembled bases and provided coverage to 3 previously missing autosomes. As the reference genome, this invaluable resource greatly enhances the ability to identify genes and genetic variations associated with traits of agronomic interest.</li><br /> <li>A turkey draft genome was generated from next generation sequencing and a turkey BAC contig (physical) map.</li><br /> <li>Guidelines for standardized gene nomenclature for chicken genes were developed to assign nomenclature to (1) MHC genes; (2) genes highly expressed in egg white, yolk and eggshell; (3) histone; and (4) myosin genes. <strong>Impact(s): </strong>This nomenclature was shared with NCBI and Ensembl.</li><br /> </ul><br /> <p><strong><span style="text-decoration: underline;">Direct contributions to Objective 2</span></strong><strong>:</strong></p><br /> <ul><br /> <li>Very high-density SNP mapping (ca. 600K SNP) panels have been developed and along with 60K SNP chips. <strong>Impact(s): </strong>These genotyping arrays are being employed in genome-wide association studies (GWAS) and genomic selection (GS).</li><br /> <li>Efforts have been initiated to annotate the chicken genome, especially with respect to regulatory elements. In brief, datasets for transcripts, histone marks, methylation and more have been integrated to identify promoters, enhancers, and silencers. <strong>Impact(s): </strong>This information is vital to help connect genotypic variation to phenotypic variation.</li><br /> <li>Transcript and comparative genome hybridization arrays were developed and distributed.</li><br /> </ul><br /> <p><strong><span style="text-decoration: underline;">Direct contributions to Objective 3</span></strong><strong>:</strong></p><br /> <ul><br /> <li>Over 40 unique chicken research lines and their derived materials have been shared with amongst investigators to expand studies on the chicken genome.</li><br /> <li>DNA from the East Lansing international reference mapping population has been sent to many laboratories throughout the world. Similarly, DNA from the junglefowl used to generate the reference sequence assembly has been widely distributed.</li><br /> </ul><br /> <p><strong><span style="text-decoration: underline;">Communication:</span></strong><span style="text-decoration: underline;">&nbsp; </span></p><br /> <ul><br /> <li>Provided support for members to attend GO-FAANG meeting and/or other multi-state research project meetings to enhance communications of activities, communicate about resources.</li><br /> </ul><br /> <p><strong><span style="text-decoration: underline;">Research support mini-grants (coordinator grants):</span></strong></p><br /> <ul><br /> <li>Provided $30,000 in funds towards the USDA AFRI Animal ENCODE proposal; Huaijun Zhou, UC Davis &ndash; PI.</li><br /> <li>Financial support provided to W. Warren, Washington U., St Louis, for sequencing of microchromosomes, which has aided to fill in gaps in the genome assembly.</li><br /> <li>Financial support provided to M. Delany, UC Davis, to create a capture arrays and sequence the wg-2 mutation in the Wingless-2.331 congenic inbred line.</li><br /> <li>Financial support provided to H. Zhou, UC Davis, for challenge experiments involving highly pathogenic Newcastle Disease Virus (NDV) and the Fayoumi and Leghorn strains in order to characterize genetic resistance.</li><br /> <li>Financial support provided to B. Muir, Purdue U. to create a synthetic resource population using 8 diverse genetic lines to fine map genetic resistance to Marek&rsquo;s disease.</li><br /> <li>Financial support provided to M. Miller, City of Hope, for further sequencing of microchromosome 16 BAC clones to improve understanding of the MHC/Rfp-Y complex.</li><br /> </ul><br /> <p><strong><span style="text-decoration: underline;">Leveraged funds and stakeholders&rsquo; use of project outputs:</span></strong></p><br /> <p>From 2013-2017, the investigators and stakeholders leveraged the tools and resources generated through NRSP-8 to obtain at least $18,675,963 additional funding from federal sources and $150,000 in funding from industry sources (Cobb Vantress supported efforts towards the improvement of the chicken genome assembly). Selected grants are highlighted below:</p><br /> <ul><br /> <li>2013-2017: USDA NIFA 2013-67015-21357. &ldquo;Improving the chicken genome assembly and annotation.&rdquo; Warren W, CT Brown, H Cheng H, and J Dodgson. <strong>$485,690</strong>. This grant supported the improvement of the chicken genome assembly and annotation by filling in known gaps within and between existing scaffolds, and refining microchromosome linkage maps for localization of unplaced sequences. <strong>Impacts(s):</strong> With the biology becoming reliant on a genome assembly, the higher quality chicken assembly aided all efforts especially with respect to identifying genes and pathways of agronomic importance. Furthermore, other avian genomes were improved as they also rely on the chicken genome assembly as their reference as well.</li><br /> <li>2012-2017. USDA NIFA 2012-67015-19419. &ldquo;Enhancing genetic resistance to Marek&rsquo;s disease in chicken via allele-specific expression screens and genome-wide selection.&rdquo; This grant supported the identification of genes and genetic markers associated with resistance to Marek&rsquo;s disease (MD), a herpesvirus-induced lymphoma of chickens. Hypothesizing that differences in gene expression (when, where, and how much) are the major contributors of phenotypic variation for complex traits such as disease resistance, SNPs that exhibit allele-specific expression (ASE) in response to Marek&rsquo;s disease virus infection were identified. These ASE SNPs were found to account for over 83% of the genetic variance and were 125% more accurate in genomic selection compared to pedigree evaluation (i.e., BLUP). <strong>Impact(s):</strong> These results support the hypothesis that phenotypic variation in traits is primarily due to changes in regulation of gene expression rather than other sources such as differences in protein composition. Furthermore, we have identified most of the genes that confer MD genetic resistance, which should help reduce the ~$1-2 billion in annual losses associated with MD.</li><br /> <li>2013-2018. USAID AID-OAA-A-13-00080 &ldquo;Improving food security in Africa by enhancing resistance to disease and heat in chickens; Feed the future innovation lab for genomics to improve poultry&rdquo; Zhou H. Bunn D, Gallardo G, Lamont S. Dekkers J. et al. <strong>$6,000,000</strong>. This grant uses contemporary high-throughput genetic technologies of SNP chips and functional genomics, along with targeted genome resequencing and extensive statistical and bioinformatic analyses to dissect and identify the genetic factors of the chicken that enhance its resistance against NDV and heat stress by assessing diverse populations of chickens, including well- characterized research lines and highly relevant local African ecotypes. <strong>Impact</strong>: The project has significantly improved institute capacity (infrastructure has developed in Africa) and human capacity building, including by training of students and scientists both on-site in Africa and in the US in essential skills that enable the African partners to sustain and disseminate the results of this project. Project outcomes are expected to reduce poverty, hunger, and malnutrition, and empower women through increased agricultural productivity achieved by decreasing the major losses that currently occur as a result of Newcastle disease and heat stress in African chickens.</li><br /> <li>2015-2017. USDA NIFA 2015-67015-22940 &ldquo;Genome wide identification and annotation of functional regulatory regions in livestock species&rdquo; H. Zhou, P. Ross, I. Korf. <strong>$500,000</strong>. This grant supported research effort in functionally annotating regulatory elements in the three major farm animal species by integrative bioinformatic analysis of RNA-seq, DNase-seq and ChIP-seq data from the eight most important tissues. <strong>Impact</strong>: This will generate first line of re-annotation of gene structure and landscape of functional regulatory elements in chicken, bovine, and swine genomes, and will develop a framework to continue a more in-depth functional annotation of these genomes and other agricultural animals.</li><br /> <li>2011-2016. USDA NIFA &ldquo;System Biology Analysis &amp; Modeling Of Complex &ldquo;Omic&rdquo; Data: A Service Center Approach&rdquo;. Zhou H. Drake K. <strong>$750,000</strong>. This grant has supported an effort in collaboration with Seralogix, to provide sophisticated systems biology and modeling analysis with visualization for a total of 12 projects generating more than 100 data analysis module reports. These projects include microarray and RNA-seq data from cattle, sheep, chicken and mice in the areas of nutrition, reproduction, growth and disease. <strong>Impacts</strong>: Results have contributed greatly to our understanding and formulation of new hypotheses that are advancing the fields of animal infection, nutrition, reproduction, and physiology.</li><br /> <li>2015-2018. USDA NIFA 2015-67015-23093 and BBSRC BB/M028208/1. &ldquo;US-UK Collaborative Research: Host Resistance to Avian Pathogenic E. coli&rdquo; Lamont, S.J. (PD), Wolc, A; Kaiser, P. (dec.), Stevens, M., Vervelde, L. <strong>$499,999</strong> (USDA). This grant supported the genomic, molecular and cellular characterization of the host-pathogen interactions between chickens and avian pathogenic E. coli (APEC), through the use of unique inbred chicken lines in both countries that differ in resistance to avian pathogenic E. coli (APEC), analysis of transgenic chickens in which all cells of the myeloid lineage express a fluorescent protein to aid the phenotyping of APEC-infected cells, definition of the transcriptome of infected cells, association of resistance with bird genetic variation (in structure and expression) through GWAS and RNA-seq analysis, and validation of selected research findings for translation into industry application. <strong>Impact(s):</strong> The impacts of this grant will be a reduction of the negative impact of respiratory APEC on the poultry industry, improved poultry health and vaccine strategies, and decreased use of antibiotics in food animals.</li><br /> </ul><br /> <p><strong><span style="text-decoration: underline;">Travel support and opportunities for trainings:</span></strong></p><br /> <ul><br /> <li>Provided financial support for over 40 students, postdocs, members, and speakers to attend the PAG Poultry Workshop (2013-2017).</li><br /> </ul><br /> <p><strong><span style="text-decoration: underline;">Major impact products (could be potential impact):</span></strong></p><br /> <ul><br /> <li>Genomic selection is now routinely implemented in both the meat (broiler) and egg (layer) breeding companies. This has greatly accelerated the genetic progress required by the industry to meet the growing consumer demand. Furthermore, poultry health and welfare have been enhanced.</li><br /> <li>The chicken genome assembly reached the stage that scientists can confidently identify genes and genetic variations associated with biological traits, many of which are highly relevant to the poultry industry.</li><br /> <li>The draft assembly of the turkey genome has been released, which affords the opportunity for efforts similar to those in the poultry industry, e.g., biological characterization, genomic selection.</li><br /> </ul><br /> <p><strong><span style="text-decoration: underline;">&nbsp;</span></strong></p><br /> <p><strong><span style="text-decoration: underline;">SHEEP/GOAT</span></strong></p><br /> <p><a href="http://www.animalgenome.org/sheep/">http://www.animalgenome.org/sheep/</a></p><br /> <p><strong><span style="text-decoration: underline;">Direct contributions to Objective 1</span></strong><strong>:</strong></p><br /> <ul><br /> <li>Reference genomes were published for goat in Nature Biotechnology in 2013 and for sheep in Science in 2014. An improved reference genome for the goat was published in Nature Genetics in 2017 that leveraged single molecule sequencing plus chromatin conformation capture to create a genome assembly with chromosome length scaffolds. <strong>Impact(s): </strong>The reference genomes advanced the status of mammal genome assembly and annotation technology at the time of publication. They also enabled comparative genomic insight into rumen biology, and expanded understanding of genes underlying numerous economically important traits. The improved goat genome reference elevated the standard for quality of mammal reference genome assemblies. Together, these results will underpin all future efforts to improve genetics of productive efficiency in sheep and goats.</li><br /> </ul><br /> <p><strong><span style="text-decoration: underline;">Direct contributions to Objective 2</span></strong><strong>:</strong></p><br /> <ul><br /> <li>A sheep 600K SNP chip and a goat 52K SNP chip were both released for research in 2014. <strong>Impact(s): </strong>This dramatic increase in SNP density for sheep and the first genome-wide medium density panel for goat have enabled powerful new tools including genome-wide association and genomic selection to dissect and improve numerous traits in sheep and goats.</li><br /> </ul><br /> <p><strong><span style="text-decoration: underline;">Direct contributions to Objective 3</span></strong><strong>:</strong></p><br /> <ul><br /> <li>A sheep genomes database has been assembled to provide a public, large-scale warehouse for global sheep genetic diversity. The database now includes re-sequencing data from almost 1,000 sheep genomes with an overall total of nearly 100 million identified sequence variants. <strong>Impact(s): </strong>This resource will accelerate the identification of causal variants for numerous traits and enable previously inconceivable analyses.</li><br /> </ul><br /> <p><strong><span style="text-decoration: underline;">Communication:</span></strong><span style="text-decoration: underline;">&nbsp; </span></p><br /> <ul><br /> <li>Strategic planning conference calls with international attendance were held in 2015 and 2016, in addition to annual meetings at PAG and biennial meetings at International Society for Animal Genetics (ISAG). <strong>Impact(s): </strong>These contributed to the development and implementation of the Ovine FAANG Project tissue collection in the U.S. and recent successful leveraged grant funding.</li><br /> </ul><br /> <p><strong><span style="text-decoration: underline;">Research support mini-grants (coordinator grants):</span></strong></p><br /> <ul><br /> <li>Ovine FAANG (Functional Annotation of ANimal Genomes) Project tissue collection ($15,000 Coordinator funds). Sample collection of 100 tissues from a new reference genome sheep was conducted in 2016. <strong>Impact(s): </strong>Use of the reference genome anim

Publications

<p><strong>Aquaculture Publications -</strong></p><br /> <p>Jin Y, Zhou T, Li N, Liu S, Xu X, Tan S, Shi H, Yang Y, Yuan Z, Wang W, Pan Y, Gao D, Dunham R, Liu ZJ. 2018. JAK and STAT members in channel catfish: Identification, phylogenetic analysis and expression profiling after bacterial infection. Developmental and Comparative Immunology, in press.</p><br /> <p>Yuan Z, Huang W, Liu S, Xu P, Dunham R, Liu ZJ. 2018. Historical demography of common carp estimated from individuals collected from various parts of the world using the pairwise sequentially Markovian coalescent approach. Genetica, in press.</p><br /> <p>Yang Y, Fu Q, Liu Y, Wang X, Dunham R, Liu S, Bao L, Zeng Q, Zhou T, Li N, Qin Z, Jiang C, Gao D, Liu ZJ. 2018. Comparative transcriptome analysis reveals conserved branching morphogenesis related genes involved in chamber formation of catfish swimbladder. Physiological Genomics, in press.</p><br /> <p>Fu Q, Yang Y, Li C, Zeng Q, Zhou T, Li N, Liu Y, Liu S, Li D, Liu ZJ. 2017. The CC and CXC chemokine receptors in channel catfish (Ictalurus punctatus) and their involvement in disease and hypoxia responses. Developmental and Comparative Immunology 77: 241-251.</p><br /> <p>Fu Q, Yang Y, Li C, Zeng Q, Zhou T, Li N, Liu Y, Li Y, Wang X, Liu S, Li D, Liu ZJ. 2017. The chemokinome superfamily: II. The 64 CC chemokines in channel catfish and their involvement in disease and hypoxia responses. Developmental and Comparative Immunology 73: 97-108.</p><br /> <p>Geng X, Liu S, Yuan Z, Jiang Y, Zhi D, and Liu ZJ. 2017. A genome wide association study reveals that genes with functions for bone development are associated with body conformation in catfish. Marine Biotechnology 19: 570-578.</p><br /> <p>Wang X, Liu S, Dunham R, Liu ZJ. 2017. Effects of strain and body weight on low-oxygen tolerance of channel catfish. Aquaculture International 25: 1645-1652. DOI: 10.1007/s10499-017-0125-2</p><br /> <p>The Aquaculture Genomics, Genetics and Breeding Workshop, Abdelrahman H, ElHady M, Alcivar-Warren A, Allen S, Al-Tobasei R, Bao L, Beck B, Blackburn H, Bosworth B, Buchanan J, Chappell J, Daniels W, Dong S, Dunham R, Durland E, Elaswad A, Gomez-Chiarri M, Gosh K, Guo X, Hackett P, Hanson T, Hedgecock D, Howard T, Holland L, Jackson M, Jin Y, Kahlil K, Kocher T, Leeds T, Li N, Lindsey L, Liu S, Liu ZJ*, Martin K, Novriadi R, Odin R, Palti Y, Peatman E, Proestou D, Qin G, Reading B, Rexroad C, Roberts S, Salem M, Severin A, Shi H, Shoemaker C, Stiles S, Tan S, Tang KFJ, Thongda W, Tiersch T, Tomasso J, Tri Prabowo W, Vallejo R, van der Steen H, Vo K, Waldbieser G, Wang H, Wang X, Xiang J, Yang Y, Yant R, Yuan Z, Zeng Q, and Zhou T. 2017. Aquaculture genomics, genetics and breeding in the United States: current status, challenges, and priorities for future research. BMC Genomics 18: 191. DOI 10.1186/s12864-017-3557-1</p><br /> <p>Wang X, Liu S, Yang Y, Fu Q, Abebe A, Liu ZJ. 2017. Identification of NF-&kappa;B related genes in channel catfish and their expression profiles in mucosal tissues after columnaris bacterial infection. Developmental and Comparative Immunology 70: 27-38.</p><br /> <p>Li N, Zhou T, Geng X, Jin Y, Wang X, Liu S, Xu X, Gao D, Li Q, Liu ZJ. 2017. Identification of novel genes significantly affecting growth in catfish through GWAS analysis. Molecular Genetics and Genomics, in press. doi.org/10.1007/s00438-017-1406-1</p><br /> <p>Yuan Z, Liu S, Bao L, Zhou T, Liu ZJ. 2017. Comparative genome analysis of 52 fish species suggests differential associations of repetitive elements with their living aquatic environments. BMC Genomics, in press.</p><br /> <p>Zhong X, Wang X, Zhou T, Jin Y, Tan S, Jiang C, Geng X, Li N, Shi H, Zeng Q, Yang Y, Yuan Z, Bao L, Tian C, Liu S, Li Q, Liu ZJ. 2017. Genome-wide association study reveals multiple novel QTL associated with low-oxygen tolerance in hybrid catfish. Marine Biotechnology 19: 379-390. DOI: 10.1007/s10126-017-9757-5.</p><br /> <p>Li Y, Geng X, Bao L, Elaswad A, Huggins KW, Dunham R, Liu ZJ. 2017. A deletion in the Hermansky-Pudlak syndrome 4 (Hps4) gene appears to be responsible for albinism in channel catfish. Molecular Genetics and Genomics, in press. DOI 10.1007/s00438-017-1302-8</p><br /> <p>Nunes, Jos&eacute; de Ribamar da Silva, Liu S, P&eacute;rtille F, Perazza C, Vera Maria Fonseca de Almeida Val, Hilsdorf AWS, Liu ZJ, &amp; Coutinho LL. 2017. Large-scale SNP discovery and construction of a high-density genetic map of tambaqui (Colossoma macropomum) through genotyping-by-sequencing. Scientific Report 7: 46112.</p><br /> <p>Zhou T, Liu S, Geng X, Jin Y, Jiang C, Bao L, Yao J, Zhang Y, Zhang J, Sun L, Wang X, Li N, Tan S, Liu ZJ. 2017. GWAS analysis of QTL for enteric septicemia of catfish and their involved genes suggest evolutionary conservation of a molecular mechanism of disease resistance. Molecular Genetics and Genomics 292: 231-242. DOI 10.1007/s00438-016-1269-x</p><br /> <p>Gao S, and Liu ZJ. 2017. Taste receptors and gustatory associated G proteins in channel catfish, Ictalurus punctatus. Comparative Biochemistry and Physiology, part D, Genomics and Proteomics 21: 1-9. doi.org/10.1016/j.cbd.2016.10.002.</p><br /> <p>Gao S, Liu S, Yao J, Li N, Yuan Z, Zhou T, Li Q, and Liu ZJ. 2017. Genomic organization and evolution of olfactory receptors and trace amine-associated receptors in channel catfish, Ictalurus punctatus. Biochimica et Biophysica Acta - General Subjects 1861 (2017): 644-651. Doi 10.1016/j.bbagen.2016.10.017.</p><br /> <p>Zeng Q, Fu Q, Li Y, Waldbieser G, Bosworth B, Liu S, Yang Y, Bao L, Yuan Z, Li N, and Liu ZJ. 2017. Development of a 690K SNP array in catfish and its application for genetic mapping of 250,000 markers and validation of the reference genome sequence.&nbsp; Scientific Report 7: 40347 DOI:10.1038/srep40347.</p><br /> <p>Zhou T, Li N, Liu S, Jin Y, Fu Q, Gao S, Wang X, Liu ZJ. 2017. The NCK and ABI adaptor genes in catfish and their involvement in ESC disease responses. Developmental and Comparative Immunology 73: 119-123.</p><br /> <p>Tian C, Tan S, Bao L, Zeng Q, Liu S, Yang Y, Zhong X, Liu ZJ. 2017. DExD/H-box RNA helicase genes are differentially expressed between males and females during the critical period of male sex differentiation in channel catfish. Comparative Biochemistry and Physiology part D 22: 109-119.</p><br /> <p>Fu Q, Zeng Q, Li Y, Yang Y, Li C, Zhou T, Li N, Liu S, Yao J, Jiang C, Li D, Liu ZJ. 2017. The chemokinome superfamily in channel catfish: I. CXC subfamily and their involvement in disease defense and hypoxia responses. Fish and Shellfish Immunology 60: 380-390.</p><br /> <p>Puritz, J. B., &amp; Lotterhos, K. E. (2017). Expressed Exome Capture Sequencing (EecSeq): a method for cost-effective exome sequencing for all organisms with or without genomic resources. bioRxiv, 223735.</p><br /> <p>Qi, H., Song, K., Li, C., Wang, W., Li, B., Li, L., Zhang, G. (2017) Construction and evaluation of a high-density SNP array for the Pacific oyster (Crassostrea gigas). PLoS One, 12(3), e0174007.</p><br /> <p>Bach&egrave;re, E., Barranger, A., Bruno, R., Rouxel, J., Menard, D., Piquemal, D., &amp; Akcha, F. (2017). Parental diuron-exposure alters offspring transcriptome and fitness in Pacific oyster Crassostrea gigas. Ecotoxicology and Environmental Safety, 142, 51-58.</p><br /> <p>Gutierrez, A. P., Turner, F., Gharbi, K., Talbot, R., Lowe, N. R., Pe&ntilde;aloza, C., ... &amp; Houston, R. D. (2017). Development of a medium density combined-species SNP Array for Pacific and European oysters (Crassostrea gigas and Ostrea edulis). G3: Genes, Genomes, Genetics, 7(7), 2209-2218.</p><br /> <p>Gutierrez, A., Bean, T. P., Hooper, C., Stenton, C. A., Sanders, M. B., Paley, R. K., &amp; Houston, R. D. (2017). A genome-wide association study for host resistance to Asteroid Herpesvirus in Pacific oysters (Crassostrea gigas). bioRxiv, 223032.</p><br /> <p>Song, K., Li, L., &amp; Zhang, G. (2017). The association between DNA methylation and exon expression in the Pacific oyster Crassostrea gigas. PloS one, 12(9), e0185224.</p><br /> <p>Gonzalez-Romero, R., Suarez-Ulloa, V., Rodriguez-Casariego, J., Garcia-Souto, D., Diaz, G., Smith, A., ... &amp; Eirin-Lopez, J. M. (2017). Effects of Florida Red Tides on histone variant expression and DNA methylation in the Eastern oyster Crassostrea virginica. Aquatic Toxicology, 186, 196-204.</p><br /> <p>Li, B., Song, K., Meng, J., Li, L., &amp; Zhang, G. (2017). Integrated application of transcriptomics and metabolomics provides insights into glycogen content regulation in the Pacific oyster Crassostrea gigas. BMC genomics, 18(1), 713.</p><br /> <p>Gavery MR, Roberts SB. (2017) Epigenetic considerations in aquaculture PeerJ 5:e4147 doi: 10.7717/peerj.4147</p><br /> <p>Samuel J. White, Brent Vadopalas, Katherine Silliman &amp; Steven B. Roberts (2017) Genotoype-by-sequencing of three geographically distinct populations of Olympia oysters, Ostrea lurida Scientific Data 4, Article number: 170130 doi: 10.1038/sdata.2017.130</p><br /> <p>Heare JE, White SJ, Vadopalas B, Roberts SB. (2018) Differential response to stress in Ostrea lurida as measured by gene expression PeerJ 6:e4261.</p><br /> <p>Emma B. Timmins-Schiffman, Grace A Crandall, Brent Vadopalas, Michael E. Riffle, Brook L. Nunn and Steven Roberts (2017) Integrating discovery-driven proteomics and selected reaction monitoring to develop a non-invasive assay for geoduck reproductive maturation Journal of Proteome Research doi: 10.1021/acs.jproteome.7b00288</p><br /> <p>Al-Tobasei, R., Ali, A., Leeds, T.D., Liu, S., Palti, Y., Kenney, B. &amp; Salem, M. (2017). Identification of SNPs associated with muscle yield and quality traits using allelic-imbalance analyses of pooled RNA-Seq samples in rainbow trout. BMC Genomics, 18: 582</p><br /> <p>Campbell, N.R., C. Kamphaus, K. Murdoch, and S.R. Narum.&nbsp; 2017. Patterns of genomic variation in Coho salmon following reintroduction to the interior Columbia River. Ecology and Evolution 7:10350-10360.</p><br /> <p>Cleveland, B.M., Leeds, T.D., Rexroad III, C.E., Summerfelt, S., Good, C., Davidson, J., May, T., Wolters, W.R., Plemmons, B., Kenney, P. 2017. Genetic line by environment interaction on rainbow trout growth and processing traits. North American Journal of Aquaculture. 79:140-154.</p><br /> <p>Koganti, P., Wang, J., Cleveland, B., Ma, H., Weber, G., and Yao, J. 2017. Estradiol regulates expression of miRNAs associated with myogenesis in rainbow trout. Molecular and Cellular Endocrinology, 443, 1-14.</p><br /> <p>Koganti, P., Wang, J., Cleveland, B.M., and Yao, J. 2017. 17&beta;-Estradiol increases non-CpG methylation in exon 1 of the rainbow trout (Oncorhynchus mykiss) MyoD gene.&nbsp; Marine Biotechnology 19(4):321-327.</p><br /> <p>Leeds, T. D., R. L. Vallejo, G. M. Weber, D. Gonzalez-Pena, J. T. Silverstein. 2016. Response to five generations of selection for growth performance traits in rainbow trout (Oncorhynchus mykiss). Aquaculture 465:341-351.</p><br /> <p>Liu, S., Palti, Y., Martin, K.E., Parsons, J.E., Rexroad, III, C.E. 2017. Assessment of genetic differentiation and genetic assignment of commercial rainbow trout strains using a SNP panel. Aquaculture. 468(1): 120-125.</p><br /> <p>Ma, H., G. M. Weber, H. Wei, J. Yao. 2016. Identification of mitochondrial genome-encoded small RNAs related to egg deterioration caused by postovulatory aging in rainbow trout. Mar. Biotechnol. 18:584-597.</p><br /> <p>Macqueen, D.J., Primmer, C.R., Houston, R.D., Nowak, B.F., Bernatchez, L., Bergseth, S., Davidson, W.S., Gallardo-Esc&aacute;rate, C., Goldammer, T., Guiguen, Y., Iturra, P., Kijas, J.W., Koop, B.F., Lien, S., Maass, A., Martin, S.a.M., Mcginnity, P., Montecino, M., Naish, K.A., Nichols, K.M., &Oacute;lafsson, K., Omholt, S.W., Palti, Y., Plastow, G.S., Rexroad, C.E., Rise, M.L., Ritchie, R.J., Sandve, S.R., Schulte, P.M., Tello, A., Vidal, R., Vik, J.O., Wargelius, A. &amp; Y&aacute;&ntilde;ez, J.M. (2017). Functional Annotation of All Salmonid Genomes (FAASG): an international initiative supporting future salmonid research, conservation and aquaculture. BMC Genomics, 18: 484.</p><br /> <p>Matala, A.P., B. Allen, S.R. Narum, and E. Harvey. 2017. Restricted gene flow between resident Oncorhynchus mykiss and an admixed population of anadromous steelhead. Ecology and Evolution 7:8349-8362.</p><br /> <p>Narum, S.R., P. Gallardo, C. Correa, A. Matala, D. Hasselman, B.J.G. Sutherland, and L. Bernatchez. 2017. Genomic patterns of diversity and divergence of two introduced species in Patagonia, South America. Evolutionary Applications 10:402-416.</p><br /> <p>Paneru, B.D., Al-Tobasei, R., Kenney, B., Leeds, T.D. &amp; Salem, M. (2017). RNA-Seq reveals MicroRNA expression signature and genetic polymorphism associated with growth and muscle quality traits in rainbow trout. Scientific Reports, 7: 9078.</p><br /> <p>Vallejo, R.L., Leeds, T.D., Gao, G., Parsons, J.E., Martin, K.E., Evenhuis, J., Fragomeni, B.O., Wiens, G.D., Palti, Y. 2017. Genomic selection models double the accuracy of predicted breeding values for bacterial cold water disease resistance compared to a traditional pedigree-based model in rainbow trout aquaculture. Genetics Selection Evolution. 49(17):1-33.</p><br /> <p>Vallejo, R.L., Leeds, T.D., Gao, G., Parsons, J.E., Martin, K.E., Evenhuis, J.P., Fragomeni, B.O., Wiens, G.D. &amp; Palti, Y. (2017). Genomic selection models double the accuracy of predicted breeding values for bacterial cold water disease resistance compared to a traditional pedigree-based model in rainbow trout aquaculture. Genetics Selection Evolution, 49: 17.</p><br /> <p>Salger, S.A., Reading, B.J., and Noga, E.J. 2017. Tissue Localization of Piscidin Host-Defense Peptides during Striped Bass (Morone saxatilis) Development. Fish and Shellfish Immunology 61: 173-180.</p><br /> <p>Fuller, S.A., Rawles, S.D., McEntire, M.E., Bader, T.J., Riche, M, Beck, B.H., and Webster, C.D. 2017. White bass (Morone chrysops) preferentially retain n‑3 PUFA in ova when fed prepared diets with varying FA content. Lipids 52: 823-836.</p><br /> <p>Fuller, S.A., Beck, B.H., Rawles, S.D., Green, B.W., Li, C., Peatman, E. Childress, C.J., Gaylord, T.G., Barrows, F.T., McEntire, M.E. 2017. Hybrid striped bass National Breeding Program:&nbsp; Research towards genetic improvement of a non-model species. Bulletin of Japan Fisheries Research and Education Agency 45: 89-100.</p><br /> <p><strong>Horse Publications - </strong></p><br /> <p>Al Abri, M.A., K&ouml;nig von Borstel, U., Strecker, V. and Brooks, S.A. (2017) 'Application of Genomic Estimation Methods of Inbreeding and Population Structure in an Arabian Horse Herd', <em>Journal of Heredity</em>, 108(4), 361-368, available: http://dx.doi.org/10.1093/jhered/esx025.</p><br /> <p>Aleman M, Finno CJ, Weich K, Penedo MCT. Investigation of known genetic mutations of Arabian horses in Egyptian Arabian foals with Juvenile Idiopathic Epilepsy. J Vet Intern Med 2017; doi: 10.1111/jvim.14873. [Epub ahead of print].</p><br /> <p>Balmer P, Bauer A, Pujar S, McGarvey KM, Welle M, Galichet A, M&uuml;ller EJ, Pruitt KD, Leeb T, Jagannathan V. A curated catalog of canine and equine keratin genes. PLoS One. 2017 Aug 28;12(8):e0180359. doi: 10.1371/journal.pone.0180359. eCollection 2017. PMID: 28846680</p><br /> <p>Bauer A, Hiemesch T, Jagannathan V, Neuditschko M, Bachmann I, Rieder S, Mikko S, Penedo MC, Tarasova N, Vitkov&aacute; M, Sirtori N, Roccabianca P, Leeb T, Welle MM. A Nonsense Variant in the ST14 Gene in Akhal-Teke Horses with Naked Foal Syndrome.&nbsp; G3 (Bethesda). 2017 Apr 3;7(4):1315-1321. doi: 10.1534/g3.117.039511.</p><br /> <p>Bellone, R.R., Liu, J., Petersen, J.L. Mack, M., Singer-Berk, M., Dr&ouml;gem&uuml;ller, C., Malvick, J., Wallner, B., Brem, G., Penedo, M.C., &amp; Lassaline, M. (2017) A missense mutation in damage-specific DNA binding protein 2 is a genetic risk factor for limbal squamous cell carcinoma in horses.&nbsp;<em>International Journal of Cancer&nbsp;</em>141(2):342-353.</p><br /> <p>Bergmann T, Lindvall M, Moore E, Moore E, Sidney J, Miller D, Tallmadge RL, Myers PT, Malaker SA, Shabanowitz J, Osterrieder N, Peters B, Hunt DF, Antczak DF, Sette A. Peptide-binding motifs of two common equine class I MHC molecules in Thoroughbred horses. Immunogenetics. 2017 69 351-358.</p><br /> <p>Bordbari MH, Penedo MC, Aleman M, Mickelson JR, Valberg SJ, Finno CJ. Deletion of 2.7kb near HOX3 in an Arabian horse with occipitoatlantoaxial malformation. Anim Genet. 2017 Jun;48(3):287-294.</p><br /> <p>Brown J, Valberg SJ, Hogg M, Finno CJ. Effect of feeding two RRR-alpha-tocopherol formulations on serum, cerebrospinal fluid and muscle alpha-tocopherol concentrations in horses with subclinical vitamin E deficiency. <em>Equine Vet J</em>, 2017 Apr 22. doi: 10.1111/evj.12692. [Epub ahead of print]</p><br /> <p>Brunner MAT, Jagannathan V, Waluk DP, Roosje P, Linek M, Panakova L, Leeb T, Wiener DJ, Welle MM. Novel insights into the pathways regulating the canine hair cycle and their deregulation in alopecia X. PLoS One. 2017 Oct 24;12(10): e0186469. doi: 10.1371/journal.pone.0186469. eCollection 2017. PMID: 29065140</p><br /> <p>Bryan K, McGivney BA, Farries G, McGettigan PA, McGivney CL, Gough KF, MacHugh DE, Katz LM, Hill EW. Equine skeletal muscle adaptations to exercise and training: evidence of differential regulation of autophagosomal and mitochondrial components. BMC Genomics. 2017 Aug 9;18(1):595. doi: 10.1186/s12864-017-4007-9.</p><br /> <p>Burger D, Thomas S, Aepli H, Dreyer M, Fabre G, Marti E, Sieme H, Robinson MR, Wedekind C.Major histocompatibility complex-linked social signaling affects female fertility. Proc Biol Sci. 2017 Dec 6;284(1868). pii: 20171824. doi: 10.1098/rspb.2017.1824.PMID: 29212724</p><br /> <p>Canisso IF, Ball BA, Esteller-Vico A, Williams NM, Squires EL, Troedsson MH.&nbsp; (2017) Changes in maternal androgens and oestrogens in mares with experimentally-induced ascending placentitis.&nbsp; <em>Equine Vet J.&nbsp; </em>49(2):244-249.&nbsp;</p><br /> <p>Carossino M, Loynachan AT, Canisso IF, Cook RF, Campos JR, Nam B, Go YY, Squires EL, Troedsson MHT, Swerczek T, Del Piero F, Bailey E, Timoney PJ, Balasuriya UBR. (2017) Equine Arteritis Virus Has Specific Tropism for Stromal Cells and CD8(+) T and CD21(+) B Lymphocytes but Not for Glandular Epithelium at the Primary Site of Persistent Infection in the Stallion Reproductive Tract. J Virol.&nbsp; 91e00418-17.</p><br /> <p>Claes A, Ball BA, Scoggin KE, Roser JF, Woodward EM, Davolli GM, Squires EL, Ball BA.&nbsp; (2017) The influence of age, antral follicle count and diestrous ovulations on estrous cycle characteristics of mares.&nbsp; <em>Theriogenology.&nbsp; </em>97:34-40.<em>&nbsp; </em></p><br /> <p>Dorado J., Anaya G., Bugno-Poniewierska M., Molina A., Mendez-Sanchez A., Ortiz I., Moreno-Mill&aacute;n M., Hidalgo M., Peral Garc&iacute;a P., Demyda-Peyr&aacute;s S. 2017. First case of sterility associated with sex chromosomal abnormalities in a jenny. Reprod. Domest Anim. .52 (2) :227-234.</p><br /> <p>D&uuml;rig N, Jude R, Holl H, Brooks SA, Lafayette C, Jagannathan V, Leeb T. Whole genome sequencing reveals a novel deletion variant in the KIT gene in horses with white spotted coat colour phenotypes. Anim Genet. 2017 Aug;48(4):483-485. doi: 10.1111/age.12556. Epub 2017 Apr 26.PMID: 28444912</p><br /> <p>D&uuml;rig N, Jude R, Jagannathan V, Leeb T. A novel MITF variant in a white American Standardbred foal. Anim Genet. 2017 Feb;48(1):123-124. doi: 10.1111/age.12484. Epub 2016 Sep 5.</p><br /> <p>Durward-Akhurst S, Valberg SJ. Review of immune-mediated muscle diseases in the horse. Vet Path 2017 Jan 1:300985816688755. doi: 10.1177/0300985816688755</p><br /> <p>Esteller-Vico A, Ball BA, Troedsson MHT, Squires EL.&nbsp; (2017) Endocrine changes, fetal growth, and uterine artery hemodynamics after chronic estrogen suppression during the last trimester of equine pregnancy.&nbsp; <em>Biol Reprod.&nbsp; </em>96(2): 197-210.</p><br /> <p>Farries G, McGettigan PA, Gough KF, McGivney BA, MacHugh DE, Katz LM, Hill EW. Genetic contributions to precocity traits in racing Thoroughbreds. Anim Genet.2017 Dec 12. doi: 10.1111/age.12622. [Epub ahead of print] PubMed PMID: 29230835.</p><br /> <p>Fedorka CE, Scoggin KE, Squires EL, Ball BA, Troedsson MHT.&nbsp; (2017) Expression and localization of cysteine-rich secretory protein-3 (CRISP-3) in the prepubertal and postpubertal male horse.&nbsp; <em>Theriogenology.&nbsp; </em>87:187-192.&nbsp;</p><br /> <p>Fedorka CE, Scoggin KE, Woodward EM, Squires EL, Ball BA, Troedsson M.&nbsp; (2017) The effect of select seminal plasma proteins on endometrial mRNA cytokine expression in mares susceptible to persistent mating-induced endometritis.&nbsp; <em>Reprod Domest Anim.&nbsp; </em>52(1):89-96.</p><br /> <p>Fenn, DJ, T. Raudsepp, E. G. Cothran, N.A. Hamilton and B. Haase (2017) Validation of a candidate causative mutation for white spotting in donkeys. Anim Genet 48 (1): 124 &ndash; 125&nbsp;</p><br /> <p>Fernandes CB, Loux SC, Scoggin KE, Squires EL, Troedsson MHT, Esteller-Vico A, Ball BA.&nbsp; Sex Steroid Receptors, Prostaglandin E2 Receptors, and Cyclooxygenase in the Equine Cervix During Estrus, Diestrus and Pregnancy:&nbsp; Gene Expression and Cellular Localization.&nbsp; <em>Animal Reproduction Science</em>. 187:141-151.</p><br /> <p>Hamilton NA (2017). Gene doping detection: The past, present and future. Proc 21st Int Conf Racing Analysts Vets. (Accepted in press)</p><br /> <p>Hoban, R., K. Castle, N.A. Hamilton and B. Haase&nbsp;&nbsp;(2017)&nbsp;&nbsp;Novel KIT variants for Dominant White in the Australian horse population. Anim Genet&nbsp;doi: 10.1111/age.12627</p><br /> <p>Holl, H., Isaza, R., Mohamoud, Y., Ahmed, A., Almathen, F., Youcef, C., Gaouar, S., Antczak, D.F. and Brooks, S. (2017) 'A Frameshift Mutation in KIT is Associated with White Spotting in the Arabian Camel', <em>Genes</em>, 8(3), 102.</p><br /> <p>Holl, H., Vanhnasy, J., Everts, R., Hoefs-Martin, K., Cook, D., Brooks, S., Carpenter, M., Bustamante, C. and Lafayette, C. (2017) 'Single nucleotide polymorphisms for DNA typing in the domestic horse', <em>Animal Genetics</em>, 48(6), 669-676, available: http://dx.doi.org/10.1111/age.12608. (JIF= 1.973)</p><br /> <p>Holl, H.M., Brooks, S.A., Carpenter, M.L., Bustamante, C.D. and Lafayette, C. (2017) 'A novel splice mutation within equine KIT and the W15 allele in the homozygous state lead to all white coat color phenotypes', <em>Animal Genetics</em>, 48(4), 497-498, available: http://dx.doi.org/10.1111/age.12554.</p><br /> <p>Ishikawa S, Horinouchi C, Mizoguchi R, Senokuchi A, Kamikakimoto R, Murata D, Hatazoe T, Tozaki T, Misumi K, Hobo S. (2017) Isolation of equine peripheral blood stem cells from a Japanese native horse. J. Equine Sci. &nbsp;28:153-158.</p><br /> <p>Jacob SI, Geor RJ, Weber PSD, Harris PA,&nbsp;McCue ME.&nbsp; <a href="https://www.ncbi.nlm.nih.gov/pubmed/29195115">Effect of dietary carbohydrates and time of year on ACTH and cortisol concentrations in adult and aged horses.</a>&nbsp; Domest Anim Endocrinol. 2017 Nov 1;63:15-22. doi: 10.1016/j.domaniend.2017.10.005. [Epub ahead of print]</p><br /> <p>Jacob SI, Geor RJ, Weber PSD, Harris PA, McCue ME. Effect of age and dietary carbohydrate profiles on glucose and insulin dynamics in horses. Equine Veterinary Journal,&nbsp;manuscript online:&nbsp;18 August 2017 DOI:&nbsp;10.1111/evj.12745.</p><br /> <p>Klaudia Pawlina-Tyszko, Artur Gurgul, Tomasz Szmatoła, Katarzyna Ropka-Molik, Ewelina Semik-Gurgul, Jolanta Klukowska-Rotzler, Christoph Koch, Kathrin Mahlmann, Monika Bugno-Poniewierska. 2017. Genomic landscape of copy number variation and copy neutral loss of heterozygosity events in equine sarcoids reveals increased instability of the sarcoid genome. BIOCHIMIE, 140: 122-132.</p><br /> <p>Lewis SS, Nicholson AM, Williams Z, Valberg SJ. Warmblood horses with polysaccharide storage myopathy: Clinical characteristics and muscle glycogen concentrations. Am J Vet Res 2017: 78(11):1305-1312.</p><br /> <p>Lewis, S.L., Holl, H., Streeter, C., Posbergh, C., Schanbacher, B., Place, N., Mallicote, M., Long, M. and Brooks, S. (2017) 'Genomewide association study reveals a risk locus for equine metabolic syndrome in the Arabian horse', <em>Journal of Animal Science</em>, 95(3), 1071-1079.</p><br /> <p>Librado P, Gamba C, Gaunitz C, Der Sarkissian C, Pruvost M, Albrechtsen A, Fages A, Khan N, Schubert M, Jagannathan V, Serres-Armero A, Kuderna LFK, Povolotskaya IS, Seguin-Orlando A, Lepetz S, Neuditschko M, Th&egrave;ves C, Alquraishi S, Alfarhan AH, Al-Rasheid K, Rieder S, Samashev Z, Francfort HP, Benecke N, Hofreiter M, Ludwig A, Keyser C, Marques-Bonet T, Ludes B, Crub&eacute;zy E, Leeb T, Willerslev E, Orlando L. Ancient genomic changes associated with domestication of the horse. Science. 2017 Apr 28;356(6336):442-445. doi: 10.1126/science.aam5298. PMID: 28450643</p><br /> <p>Loux SC, Scoggin KE, Bruemmer J, Canisso I, Troedsson MHT, Squires EL, Ball BA. (2017) Evaluation of Circulating miRNAs During Late Pregnancy in the Mare.&nbsp; <em>PLOS ONE </em>12(4):e0175045.&nbsp;</p><br /> <p>Loux SC, Scoggin KE, Troedsson MHT, Squires EL, Ball BA. (2017) Characterization of the Cervical Mucus Plug in Mares. <em>Reproduction. </em>153(2): 197-210.&nbsp;&nbsp;</p><br /> <p>Mack, M., Kowalski, E., Grahn, R., Bras, D., Penedo, M.C.T., &amp;&nbsp;<strong>Bellone, R.</strong>&nbsp;(2017) Two variants in&nbsp;<em>SLC24A5</em>&nbsp;are associated with &ldquo;Tiger-Eye&rdquo; iris pigmentation in Puerto Rican Paso Fino horses.&nbsp;<em>G3: Genes|Genomes|Genetics</em>&nbsp;7(8):2799-2806. DOI:10.1534/g3.117.043786.</p><br /> <p>Maile CA, Hingst JR, Mahalingan KK, O'Reilly AO, Cleasby ME, Mickelson JR, McCue ME, Anderson SM, Hurley TD, Wojtaszewski JF, Piercy RJ.A highly prevalent equine glycogen storage disease is explained by constitutive activation of a mutant glycogen synthase. Biochimica et Biophysica Acta General Subjects, January 2017 Volume: 1861&nbsp;&nbsp; Issue: 1&nbsp;&nbsp; Pages: 3388-3398.</p><br /> <p>Mansour, T.A., Scott, E.Y.,&nbsp; Finno,&nbsp; C.J.,&nbsp; Bellone,&nbsp; R.R., Mienaltowski, M.J.,&nbsp; Penedo, M.C., Ross, P.J., Valberg,&nbsp; S.J., Murray, J.D., &amp;&nbsp; Brown, C.T.&nbsp; (2017) Tissue resolved, gene structure refined equine transcriptome.&nbsp;<em>BMC Genomics</em>&nbsp;18: 103. DOI: 10.1186/s12864-016-3451-2</p><br /> <p>McCue ME, McCoy AM.&nbsp; <a href="https://www.ncbi.nlm.nih.gov/pubmed/29201868">The Scope of Big Data in One Medicine: Unprecedented Opportunities and Challenges.</a>&nbsp; Front Vet Sci. 2017 Nov 16;4:194. doi:&nbsp; 10.3389/fvets.2017.00194. eCollection 2017.</p><br /> <p>McGivney BA, Griffin ME, Gough KF, McGivney CL, Browne JA, Hill EW, Katz LM. Evaluation of microRNA expression in plasma and skeletal muscle of thoroughbred racehorses in training. BMC Vet Res. 2017 Nov 22;13(1):347. doi: 10.1186/s12917-017-1277-z. PubMed PMID: 29166903; PubMed Central PMCID:</p><br /> <p>McGivney CL, Sweeney J, David F, O'Leary JM, Hill EW, Katz LM. Intra- and interobserver reliability estimates for identification and grading of upper respiratory tract abnormalities recorded in horses at rest and during overground&nbsp; endoscopy. Equine Vet J. 2017 Jul;49(4):433-437. doi: 10.1111/evj.12653.</p><br /> <p>Miller, D., Tallmadge, R.L., Binns, M., Zhu, B., Mohamoud, Y.A., Ahmed, A., Brooks, S.A. and Antczak, D.F. (2017) 'Polymorphism at expressed DQ and DR loci in five common equine MHC haplotypes', <em>Immunogenetics</em>, 69(3), 145-156, available: http://dx.doi.org/10.1007/s00251-016-0964-4.</p><br /> <p>Miyata H, Itoh R, Sato F, Takebe N, Hada T, Tozaki T. (2017) Effect of Myostatin SNP on muscle fiber properties in male Thoroughbred horses during training period. J. Physiol. Sci. doi: 10.1007/s12576-017-0575-3. [Epub ahead of print]</p><br /> <p>Pacholewska A, Kraft MF, Gerber V, Jagannathan V. Differential Expression of Serum MicroRNAs Supports CD4⁺ T Cell Differentiation into Th2/Th17 Cells in Severe Equine Asthma. Genes (Basel). 2017 Dec 12;8(12). pii: E383. doi: 10.3390/genes8120383.PMID: 29231896</p><br /> <p>Pacholewska A, Marti E, Leeb T, Jagannathan V, Gerber V. LPS-induced modules of co-expressed genes in equine peripheral blood mononuclear cells. BMC Genomics. 2017 Jan 5;18(1):34. doi: 10.1186/s12864-016-3390-y.&nbsp; PMID: 28056766</p><br /> <p>Pawlina K., Gurgul A., Szmatoła T., Koch C., Mahlmann K, Witkowski M., Bugno-Poniewierska M. 2017. Comprehensive characteristics of microRNA expression profile of equine sarcoids. BIOCHIMI 137; 20-28.<br /> Ropka-Molik K., Stefaniuk-Szmukier M., Żukowski K., Pi&oacute;rkowska K., GurgulA., Bugno-Poniewierska M. 2017. Transcriptome profiling of Arabian horse blood during training regimens. 2017. BMC Genetics. DOI 10.1186/s12863-017-0499-1</p><br /> <p>Pedersen PJ, Thomsen KB, Flak JB, Tejada MA, Hauser F, Trachsel D, Buhl R, Kalbfleisch T, DePriest MS, MacLeod JN, Calloe K, Klaerke DA,&nbsp; Molecular cloning and functional expression of the K+ channel KV7.1 and the regulatory subunit KCNE1 from equine myocardium. Res Vet Sci. 2017;113:79-86. doi: 10.1016/j.rvsc.2017.09.010. PubMed PMID: 28917093.</p><br /> <p>Rooney MF, Porter RK, Katz LM, Hill EW. Skeletal muscle mitochondrial bioenergetics and associations with myostatin genotypes in the Thoroughbred horse. PLoS One. 2017 Nov 30;12(11):e0186247. doi: 10.1371/journal.pone.0186247.&nbsp;</p><br /> <p>Ropka-Molik K., Stefaniuk-Szmukier M., Żukowski K., Pi&oacute;rkowska K., Bugno-Poniewierska M. Exercise-induced modification of the skeletal muscle transcriptome in Arabian horses. 2017. Physiol Genomics. doi: 10.1152/physiolgenomics.00130.2016.</p><br /> <p>Sadeghi R, Moradi-Shahrbabak M, Miraei Ashtiani SR, Miller DC, Antczak DF. MHC haplotype diversity in Persian Arabian horses determined using polymorphic microsatellites. Immunogenetics. 2017 Nov 23.</p><br /> <p>Schaefer RJ, Schubert M, Bailey E, Bannasch DL, Barrey E, Bar-Gal GK, Brem G, Brooks SA, Distl O, Fries R, Finno CJ, Gerber V, Haase B, Jagannathan V, Kalbfleisch T, Leeb T, Lindgren G, Lopes MS, Mach N, da C&acirc;mara Machado A, MacLeod JN, McCoy A, Metzger J, Penedo C, Polani S, Rieder S, Tammen I, Tetens J, Thaller G, Verini-Supplizi A, Wade CM, Wallner B, Orlando L, Mickelson JR, McCue ME. Developing a 670k genotyping array to tag ~2M SNPs across 24 horse breeds. BMC Genomics. 2017 Jul 27;18(1):565. doi: 10.1186/s12864-017-3943-8. PMID: 28750625</p><br /> <p>Schnider D, Rieder S, Leeb T, Gerber V, Neuditschko M. A genome-wide association study for equine recurrent airway obstruction in European Warmblood horses reveals a suggestive new quantitative trait locus on chromosome 13. Anim Genet. 2017 Dec;48(6):691-693. doi: 10.1111/age.12583. Epub 2017 Jul 24.PMID: 28737212</p><br /> <p>Scott, E.Y., Mansour, T., Bellone, R.R., Brown, C.T., Mienaltowski, M.J., Penedo, M.C., Ross, P.J., Valberg, S.J., Murray, J.D., &amp; Finno, C.J. Identification of long non-coding RNA in the horse transcriptome.&nbsp;<em>BMC Genomics&nbsp;</em>18:511<em>&nbsp;</em>DOI 10.1186/s12864-017-3884-2.</p><br /> <p>.1186/s12864-017-3884-2</p><br /> <p>Semik E., Ząbek T., Gurgul A., Fornal A., Szmatoła T., Pawlina K., Wnuk M., Klukowska-R&ouml;tzler J., Koch C., M&auml;hlmann K., Bugno-Poniewierska M. 2017. Comparative analysis of DNA methylation patterns of equine sarcoid and healthy skin samples. Veterinary and Comparative Oncology DOI 10.1111/vco.12308</p><br /> <p>Senju N, Tozaki T, Kakoi H, Almunia J, Maeda M, Matsuyama R, Takasu M. (2017) Genetic characterization of the Miyako horse based on polymorphisms of microsatellites and mitochondrial DNA. J. Vet. Med. Sci. 79:218-223.</p><br /> <p>Senju N, Tozaki T, Kakoi H, Shinjo A, Matsuyama R, Almunia J, Takasu M. (2017) Genetic diversity of the Yonaguni horse based on polymorphisms in microsatellites and mitochondrial DNA. J. Vet. Med. Sci. 79:425-431.</p><br /> <p>Staiger EA, Alm&eacute;n MS, Promerov&aacute; M, Brooks S, Cothran EG, Imsland F, J&auml;derkvist Fegraeus K, Lindgren G, Mehrabani Yeganeh H, Mikko S, Vega-Pla JL, Tozaki T, Rubin CJ, Andersson L. (2017) The evolutionary history of the DMRT3 'Gait keeper' haplotype. Anim. Genet. 48:551-559.</p><br /> <p>Swiderski CE, Bowser JE, Costa LRR. Pasture associated asthma. Proceedings of the American College of Veterinary Internal Medicine, National Harbor, Maryland, USA, June 8-10, 2017.</p><br /> <p>Swiderski CE, Hunter CE, Bowser JE, Costa LR, Cooley JA, Claude AD, Eddy AL, Bright LA. Deciphering the role of airway hyper-responsiveness in equine pasture asthma. <em>Journal of Equine Veterinary Science. </em>52:29-35, 2017.</p><br /> <p>Tamer TA, Erica Y Scott ET,&nbsp; Finno CJ, Bellone RR, Mienaltowski MJ, Penedo MC, Ross PJ, Valberg SJ, Murray JD, Brown CT. Tissue Resolved, Gene Structure Refined Equine Transcriptome. BMC Genomics. BMC Genomics. 2017 Jan 20;18(1):103.</p><br /> <p>Tozaki T, Kikuchi M, Kakoi H, Hirota KI, Nagata SI. (2017) A genome-wide association study for body weight in Japanese Thoroughbred racehorses clarifies candidate regions on chromosomes 3, 9, 15, and 18. J. Equine Sci. 28:127-134.</p><br /> <p>Valberg SJ, Nicholson AM, Lewis SS, Reardon RA, Finno CJ. Clinical and histopathological features of myofibrillar myopathy in Warmblood horses. <em>Equine Vet J</em> 2017 May 22. doi: 10.1111/evj.12702. [Epub ahead of print].</p><br /> <p>Viluma A, Mikko S, Hahn D, Skow L, Andersson G, Bergstr&ouml;m TF. Genomic structure of the horse major histocompatibility complex class II region resolved using PacBio long-read sequencing technology. Scientific Reports, 7:45518, doi:10.1038/srep45518, 2017</p><br /> <p>Wallner B, Palmieri N, Vogl C, Rigler D, Bozlak E, Druml T, Jagannathan V, Leeb T, Fries R, Tetens J, Thaller G, Metzger J, Distl O, Lindgren G, Rubin CJ, Andersson L, Schaefer RJ, McCue ME, Neuditschko M, Rieder S, Schl&ouml;tterer C and Brem G. Y Chromosome Uncovers the Recent Oriental Origin of Modern Stallions. Current Biology, Volume 27, Issue 13,&nbsp;10 July 2017, Pages 2029-2035.e5</p><br /> <p>Wilkin, T. A. Baoutina and N.A. Hamilton (2017) Equine performance genes and the future of doping in horse racing.&nbsp;&nbsp;Drug Test Analysis&nbsp;&nbsp;DOI 10.1002/dta.2198</p><br /> <p><strong>Poultry Publications - </strong></p><br /> <p>Baldwin, C.L et. al. (11 authors on committee) National Academies of Sciences, Engineering, and Medicine. 2017. Revisiting Brucellosis in the Greater Yellowstone Area. The National Academies Press: Washington, DC. 209 pgs; ISBN 978-0-309-45831-3 | DOI 10.17226/24750 [<a href="https://www.nap.edu/download/24750">https://www.nap.edu/download/24750</a>]</p><br /> <p>Cinar, M.U., Schneider, D.A., Waldron, D.F., O&rsquo;Rourke, K.I., White, S.N. Goats singly heterozygous for PRNP S146 or K222 orally inoculated with classical scrapie at birth show no disease at ages well beyond six years. The Veterinary Journal. (in press)</p><br /> <p>Dechow, C.D., Liu, W.-S. (2017) Genome-wide DNA methylation patterns and differential methylation in leukocytes from Holstein cattle with variable milk yield. BMC Genomics (manuscript under revision).</p><br /> <p>Dechow, C., Liu, W.-S., Idun, J., Maness, W. (2017) Two dominant paternal lineages for North American Jersey artificial insemination sires. J. Dairy Sci. (In Press). Ghadikolaei, A.N., Yeganeh, H.M., Miarei-Aashtiani, S.R., Staiger, E.A., Huson, H.J., Genome-wide association studies identify candidate genes for coat color and mohair traits in the Iranian Markhoz goat, <em>Frontiers in Genetics</em> (under revision Jan 2018)</p><br /> <p>Kiser, J.N., Neupane, M., White, S.N., Neibergs, H.L. Identification of genes associated with susceptibility to <em>Mycobacterium avium</em> ssp. <em>paratuberculosis</em> (Map) tissue infection in Holstein cattle using gene set enrichment analysis-SNP. Mammalian Genome. (in press)</p><br /> <p>Kiser, J.N., White, S.N., Johnson, K.A., Hoff, J., Taylor, J.F., Neibergs, H.L. Identification of loci associated with susceptibility to <em>Mycobacterium avium</em> subspecies <em>paratuberculosis</em> (Map) tissue infection in cattle. Journal of Animal Science. 95(3):1080-1091. 2017.</p><br /> <p>Liu, W.-S., Zhao, Y.Q., Lu, C., Ning, G., Ma, Y., Diaz, F., O'Connor, M. (2017) A novel testis-specific protein, PRAMEY, is involved in spermatogenesis in cattle. Reproduction 153, 847&ndash;863.</p><br /> <p>Mason, K.L., Gonzalez, M.V., Chung, C., Mousel, M.R., White, S.N., Taylor, J.B., Scoles, G.A. Detection of <em>Anaplasma ovis</em> and validation of improved A. marginale cELISA kit for diagnostic use in domestic sheep. Journal of Veterinary Diagnostic Investigation. 29(5):763-766. 2017.</p><br /> <p>Noelle E. Cockett, Brian Dalrymple, James Kijas, Brenda Murdoch, Kim C. Worley. Mapping the sheep genome, Chapter 5, <em>Achieving sustainable production of sheep </em>Burleigh Dodds Series in Agricultural Science (Book 22), Edited by Prof J.P.C. Greyling, Burleigh Dodds Science Publishing September 15, 2017</p><br /> <p>Notter, D. R., Mousel, M. R., Lewis, G. S., Leymaster, K. A., and Taylor, J. B. Evaluation of Rambouillet, Polypay, and Romanove-White Dorper x Rambouillet ewes mated to terminal sires in an extensive rangeland production system: lamb production. J. Anim. Sci. 95:3851-3862. 2017.</p><br /> <p>Oliveira, R.D., Mousel, M.R., Pabilonia, K.L., Highland, M.A., Taylor, J.B., Knowles, D.P., White, S.N. Domestic sheep show average <em>Coxiella burnetii</em> seropositivity generations after a sheep-associated human Q fever outbreak but lack detectable shedding by placental, vaginal, and fecal routes. PLoS One 12(11): e0188054. 2017.</p><br /> <p>Posbergh, C.J. &amp; Huson, H.J., (2018) Making Moorit: Mutations in TYRP1 are responsible for brown coat color in different United States sheep breeds, <em>Proceedings 11^th World Congress of Genetics Applied to Livestock Production</em>, (accepted, under revision Nov 2017).</p><br /> <p>Posbergh, C.J., Kalla, S.E., Sutter, N.B., Tennant, B.C., Huson, H.J., A mutation responsible for hyperbilirubinemia and photosensitivity in Southdown sheep similar to Rotor Syndrome <em>American Journal of Veterinary Research </em>(accepted July 2017, In Press</p><br /> <p>Posbergh, C.J., Thonney M.L., Huson H.J., The eyes have it: genomic approaches identify novel gene associations with aseasonality in sheep, <em>BMC Genomics</em> (submitted Jan 2018)</p><br /> <p>PrabhuDas M, Baldwin CL, Bollyky PL, Bowdish DME, Drickamer K, Febbraio M, Herz J, Kobzik L, Krieger M, Loike J, McVicker B, Means TK, Moestrup S, Post SR, Tatsuya Sawamura T, Silverstein S, Speth RC, Telfer JC, Thiele GM, Wang X-Y, Wright SD, El Khoury J. A Consensus Definitive Classification of Scavenger receptors. <em>Journal of Immunology</em> 2017; 198(10):3775-3789. doi: 10.4049/jimmunol.1700373. PMID: 28483986</p><br /> <p>Tezgel A&Ouml;, Jacobs PT*, Backlund CM, Telfer JC, Tew GN Synthetic Protein Mimics for Functional Protein Delivery. <em>Biomacromolecules</em> 2017; 18(3):819-825. doi: 10.1021/acs.biomac.6b01685. Epub 2017 Feb 27. PMID: 28165726.</p><br /> <p>White, S.N., Oliveira, R.D., Mousel, M.R., Gonzalez, M.V., Highland, M.A., Herndon, M.K., Taylor, J.B., Knowles, D.P. Underdominant KCC3b R31I association with blood sodium concentration in domestic sheep suggests role in oligomer function. Animal Genetics 48(5):626-627. 2017.</p><br /> <p>Zhang, Y.Y., Deng, X.G., Liu, W.-S., Deng, X.M. (2017) Estimation of recombination rate and effective population size with ovine genome-wide SNP-chip. Sciencepaper Online 201704-232&nbsp;</p><br /> <p><strong>Swine Publications - </strong></p><br /> <p>Bertolini F., J.C.S. Harding, B. Mote, A. Ladinig, G.S. Plastow and M.F. Rothschild. 2017. Genomic investigation of piglet resilience following porcine epidemic diarrhea outbreaks. Animal Genetics. 48(2):228-232. doi: 10.1111/age.12522.</p><br /> <p>Casir&oacute; S, D. Velez-Irizarry, C.W. Ernst, N.E. Raney, R.O. Bates, M.G. Charles and J.P. Steibel. 2017. Genome-wide association study in an F2 Duroc x Pietrain resource population for economically important meat quality and carcass traits. J. Anim. Sci. 95:545-558.</p><br /> <p>Choi, I., R.O. Bates, N.E. Raney and C.W. Ernst. 2017. Association of a corticotropin-releasing hormone receptor 2 (CRHR2) polymorphism with carcass merit, meat quality and stress response traits in pigs. Canadian J. Anim. Sci. 97:536-540.</p><br /> <p>Cole JB, Bormann JM, Gill CA, Khatib H, Koltes JE, Maltecca C, Miglior F. 2017. BREEDING AND GENETICS SYMPOSIUM: Resilience of livestock to changing environments. J Anim Sci. 95(4):1777-1779.</p><br /> <p>Daza, K.R., J.P. Steibel, D. Velez-Irizarry, N.E. Raney, R.O. Bates and C.W. Ernst. 2017. Profiling and characterization of a longissimus dorsi muscle microRNA dataset from an F2 Duroc x Pietrain pig resource population. Genom. Data. 13:50-53.</p><br /> <p>Funkhouser, S.A., R.O. Bates, C.W. Ernst, D. Newcom and J.P. Steibel. 2017. Estimation of genome-wide and locus-specific breed composition in pigs. Translational Anim. Sci. 1:36-44.</p><br /> <p>
Funkhouser, S.A., J.P. Steibel, R.O. Bates, N.E. Raney and C.W. Ernst. 2017. Evidence for transcriptome-wide RNA editing among Sus scrofa PRE-1 SINE elements. BMC Genomics.18:360.
Garcia-Baccino, C.A., S. Munilla, A. Legarra, Z.G. Vitezica, N.S. Forneris, R.O. Bates, C.W. Ernst, N.E. Raney, J.P. Steibel and R.J. Cantet. 2017. Estimates of the actual relationship between half-sibs in a pig population. J. Anim. Breed. Genet. 134:109- 118.</p><br /> <p>
Howard JT, Pryce JE, Baes C, Maltecca C. Invited review: Inbreeding in the genomics era: Inbreeding, inbreeding depression, and management of genomic variability. J Dairy Sci. 2017;100(8):6009-6024</p><br /> <p>Howard JT, Tiezzi F, Huang Y, Gray KA, Maltecca C. 2016. Characterization and management of long runs of homozygosity in parental nucleus lines and their associated crossbred progeny. Genet Sel Evol. 24;48(1):91.</p><br /> <p>Kommadath, A., H. Bao, I. Choi, J.M. Reecy, J.E. Koltes, E. Fritz-Waters, C. J. Eisley, J. R. Grant, R.R.R. Rowland, <span style="text-decoration: underline;">C. K. Tuggle</span>, J.C.M. Dekkers, J.K. Lunney, L.L. Guan, P. Stothard, and G.S. Plastow. 2017. Genetic architecture of gene expression underlying variation in host response to porcine reproductive and respiratory syndrome virus infection. Scientific Reports 7:46203. doi: 10.1038/srep46203.</p><br /> <p>Liu, H., T.P.L. Smith, D.J. Nonneman, J.C.M. Dekkers, C.K. Tuggle&nbsp;&nbsp; 2017. A high-quality annotated transcriptome of swine peripheral blood. BMC Genomics 18:479. doi: 10.1186/s12864-017-3863-7.</p><br /> <p>Tiezzi F, de Los Campos G, Parker Gaddis KL, Maltecca C. 2017. Genotype by environment (climate) interaction improves genomic prediction for production traits in US Holstein cattle. J Dairy Sci. 100(3):2042-2056</p><br /> <p>Waide, E., C.K. Tuggle, N.V.L. Ser&atilde;o, M. Schroyen, A. Hess, R.R.R. Rowland, J.K. Lunney, G. Plastow, and J.C.M. Dekkers. 2017. Genome-wide Association of Piglet Responses to one of two Porcine Reproductive and Respiratory Syndrome Virus isolates. J. Animal Science. 95:16-38.</p><br /> <p>Wijesena HR, CA Lents, J-J. Riethoven, MD Trenhaile-Grannemann, JF Thorson, BN Keel, PS Miller, ML Spangler, SD Kachman, DC Ciobanu, 2017. Integration of Genomic Approaches to Uncover Sources of Variation in Age at Puberty and Reproductive Longevity in Sows, J Anim Sci. 95(9):4196-4205. doi: 10.2527/jas2016.1334.</p><br /> <p>Wurtz K.E., J.M. Siegford, R.O. Bates, C.W. Ernst and J.P. Steibel. 2017. Estimation of genetic parameters for lesion scores and growth traits in group-housed pigs. J Anim Sci. 95:4310-4317.&nbsp;</p><br /> <p>&nbsp;</p>

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1. Bioinformatics Impact Statement - The Bioinformatics helpdesk annually helps more than 60 research groups. Involvement has ranged from data transfer, data assembly, and data analysis, to software applications, code development, information resources, etc.

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