Duration: 10/01/2007 to 09/30/2012

Administrative Advisor(s):

NIFA Reps:

Non-Technical Summary

Statement of Issues and Justification

US swine producers have made tremendous improvements in the efficiency of converting feed and other inputs into pork products and genetic selection has played and will continue to play a key role in this success. Whereas production efficiency continues to be important for the U.S. swine industry, product quality and animal health are of growing importance and form the basis of the research proposed herein. Genetic improvement in these factors is required for US producers to remain competitive in an increasingly global market place and to compete with other meat industries and sources of protein. To this end, the National Pork Board, which represents U.S. pork producers and is one the largest U.S. livestock commodity organizations, has adopted the following mission: "to enhance opportunities for the success of U.S. pork producers and other industry stakeholders by establishing the U.S. pork industry as a consistent and responsible supplier of high quality pork to the domestic and world market, making U.S. pork the consumers meat of choice". Additionally, the mission statement of the National Swine Improvement Federation, which represents independent and company swine seedstock producers is "to advance and stimulate efforts of swine breeding stock suppliers, academic personnel, and pork industry affiliates in the research, development, and utilization of scientifically-based genetic improvement programs and associated practices for the economically efficient production of high quality, nutritious pork". The research outlined in this proposal addresses the missions of these industry organizations by elucidating the genetic control of product quality, animal health, and environmental sustainability. Furthermore, The American Society of Animal Sciences mission statement "to discover, disseminate and apply knowledge for sustainable use of animals for food and other human needs" and the Federation of Animal Science Societies stated purpose "to promote education and research." would be well served by the scientific work, publication, and outreach activities of the proposed project.

Pork quality comprises a set of key fresh meat qualities and processing characteristics that are important for the future profitability and competitiveness of the swine industry. These include intramuscular fat, cholesterol, pH, color, water holding capacity, cooking loss, tenderness, and sensory traits. Because most aspects of pork quality can only be measured on the carcass or by consumer panels, they have been difficult to improve by conventional means. However, most are at least moderately heritable and several quality-related genes have been identified. Great opportunities, therefore, exist for the use of marker-assisted selection to improve pork quality. Recent collaborative research by NC-1004 members has identified genomic regions and individual genes controlling many of these attributes. During the last five-year period, this information has been presented to the pig genetics industry, although further work on genetic markers and technology needs to continue to fully move the information into the industry sector.

Improved disease resistance will enhance production efficiency, animal welfare, and producer and consumer acceptance of the pork production system. In addition, improved resistance to disease will reduce the need for antibiotics to prevent or cure disease and the potential for pork products to harbor pathogens that are of potential danger to consumers. Knowledge about the genetic aspects of resistance to disease in swine is limited, although collaborative work by NC-1004 members has recently begun to identify the genes responding to infection by bacteria and by porcine reproductive and respiratory syndrome virus (PRRSV).

Pork quality and disease resistance involve complex systems that require a multi-disciplinary approach to develop an understanding of the underlying genetic factors and to develop strategies for their genetic advancement. Whereas traditional approaches have concentrated on population and quantitative genetics, it is clear that a concerted effort in molecular and population or quantitative genetics is required to address these emerging issues. Although these factors are of prime importance for the future of the U.S. swine industry, they must be accompanied by simultaneous improvement in production efficiency. Consumers expect food to be safe, of high quality and reasonably priced. This can only be achieved through a concerted effort to improve efficiency along with quality and animal health. Over the past 5-year period, NC-1004 researchers have made substantial advances in the development and utilization of molecular and genomic technologies to map genes in the pig genome and to study their function. Researchers have developed expertise to integrate quantitative and molecular genetics for genetic improvement. Researchers have active collaborations with scientists with expertise in the biological and physiological aspects of meat quality, disease resistance, and production efficiency. Jointly, researchers from NC-1004 are in an ideal position to continue to successfully address the objectives of this project. Because of the complex and multi-faceted nature of the proposed research, no single institution has sufficient resources and facilities to address the wide range and interdependent sets of research questions that must be answered. The financial and personnel cost of performing modern research on large numbers of pigs required for statistically valid conclusions is very high, especially for the areas of research described above. Therefore, a coordinated and integrated effort among experiment stations to share these costs among multiple researchers, as outlined in this proposal, is crucial for the success and relevance of any research effort on these aspects of pork production.

Related, Current and Previous Work

Most swine breeding research in the US has been conducted as part of NC Regional Projects. The Regional Swine Breeding Laboratory was initiated in 1937 and replaced by the NCR-1 Project in 1970. The NC-103 Project replaced NCR-1 in 1971, which in turn was replaced by NC-206 in 1990, and then NC-220 in 1996. With the advent of genome mapping technologies, NC-210 was initiated in 1992 to help develop the swine genome map. In 2001, NC-220 and NC-210 were merged into NC1004 to better address the multi-disciplinary nature of the research questions and to eliminate overlap. The present proposal represents a renewal of this merged project.

Swine genetics research in the 1970s emphasized selection and crossbreeding experiments, while research in the 1980s focused on use of Best Linear Unbiased Prediction procedures to estimate breeding values, on simulation of life-cycle pork production, and on selection experiments. Quantitative genetic research conducted in the 1990s aimed to improve the accuracy of predictors of progeny performance in different breed and environmental combinations. Selection experiments on component traits for reproduction, including ovulation rate and uterine capacity, produced important results that improved the understanding of the biology and genetics of male and female reproduction (Johnson et al. 1999; Ruiz-Flores and Johnson, 2002). Rothschild et al. (1996) published the first validated candidate gene (ESR) for litter size in pigs. Substantial knowledge was also developed on genes that control immune, disease, and vaccine responses, such as the major histocompatibility complex and immunoglobulin genes (Lunney and Butler, 1998). Edfors-Lilja et al. (1998) and Wattrang et al. (2005) have mapped chromosomal regions involved in general immune traits and responses to stress.

Research conducted in NC regional projects and elsewhere has established that most performance traits are under polygenic control. Estimates of population parameters such as heritability, heterosis, and genetic correlations have been used to develop effective selection and crossbreeding systems, but provide little information on the underlying genes. In 1989 less than 50 genes were mapped in the pig. Since then, efforts by several groups, including contributions from NC-210 members, have developed linkage maps. The pig database now contains 2,133 loci, of which 653 are designated genes (http://www.genome.iastate.edu/pig.html). In 2006, the public swine genome sequencing began (http://www.sanger.ac.uk/Projects/S_scrofa/).

Whereas initial swine breeding research focused on production traits (growth, backfat, and reproduction), pork quality and feed efficiency have only now begun to receive sufficient attention. Improved feed conversion has several economic and environmental advantages but direct evaluation of food intake is expensive. Thus, producers have relied on desirable genetic correlations of feed efficiency with rate and composition of growth to improve feed efficiency. Independent improvement from direct selection on feed efficiency can occur, thus, research is needed to identify genes involved in the regulation of appetite and feed utilization.

Consumers of pork demand high quality at the lowest possible price. Thus, improving the consistency and quality of pork is of growing importance. Conventional methods of selection for rapid lean growth rate in swine have frequently resulted in animals that yield inferior quality meat (Sosnicki et al. 1996). Thus, it is important to consider meat quality in selection programs. Heritability of meat quality traits is moderate to high, but phenotypic measurement of these traits is expensive and difficult. Identification of markers controlling pork quality will be of critical importance for making genetic improvement in these traits.

Knowledge on the genetic aspects of animal health related to pork production is also very limited. Disease costs the swine industry more than 1.5 billion dollars a year and is the most difficult problem facing pig producers; PRRS alone costs $560 million a year (Neumann et al., 2005). Approaches used today are costly and relatively ineffective as long-term solutions. Disease management will become even more difficult as producers are forced to use fewer antibiotics. A better understanding of the epidemiology of diseases, genetic mechanisms involved in responses to pathogens, methods of transmission, and effects of the environment and its interaction with the genome on severity of responses to pathogens is needed. Host genes and proteins that are critical to animal health and disease resistance must be identified and improved methods to manage disease and to select for greater disease resistance must be developed. New methods to identify such genes have been reported (Dawson et al., 2005; Zhao et al. 2006).

Evidence for the genetic control of susceptibility to diseases is substantial (Rothschild 1985; Wilkie and Mallard 2000). However, selection for disease resistance using quantitative methods is difficult and can be more effective once genes that confer resistance or susceptibility have been identified. Although some genomic regions and genes have been shown to affect disease traits (Lunney and Butler 1998; Edfors-Lilja et al. 1998; Wilkie and Mallard 2000; Wattrang et al. 2005), knowledge of the genetic basis of resistance or susceptibility to infectious diseases remains limited. A recent study attempted to correlate early immune traits with growth during the entire productive life of the pig (Galina-Pantoja et al. 2005).

Future advances in swine genetic research will require the use of diverse tools including both molecular and quantitative approaches The NC1004 project was established with this in mind. Identifying the exact biological pathways, genes, and gene regulators that ultimately determine phenotype will require molecular tools. Ultimately, quantitative methods will be used to incorporate the genotypic information from these markers into swine improvement programs.
The NC1004 members have made significant discoveries in these areas since the project began.

Using F2 resource populations developed within their stations, work at IA and MI have resulted in identification of multiple QTL associated with meat quality (Malek et al 2001a,b; Edwards et al., 2006 a,b). Michigan has identified QTL for growth, carcass merit and meat quality traits in their Duroc x Pietrain resource population. Iowa has continued its analysis of the Berkshire x Yorkshire population and joint analyses of the ISU Berkshire x Yorkshire and the Univ. of Illinois Berkshire x Duroc populations. These data were also used to detect several QTL with unique modes of genomic imprinting. Associations of MC4R with fat deposition (Kim et al. 2000), PRKAG3 with pH (Ciobanu et al 2001) and CAST with tenderness (Ciobanu et al 2004) were identified. The NE station has furthered its search for QTL affecting reproduction and applied new statistical models to existing data. Data from an F2 resource population created from the NE selection lines were reanalyzed with models that allowed composite interval mapping and search for chromosomal regions with imprinted effects. Based on these findings, software was developed to simulate the pedigree structure and selection background from generation 0 to 23 in the NE lines. Regions on chromosomes 6, 11, 12, and 13 were chosen for further study as they were previously shown to harbor QTL (Cassady et al. 2001).

The IA, NE, OH, and NC stations continue to create and maintain selection lines of pigs. This work is especially important because the number of experiment stations maintaining swine populations that can be utilized for research has declined dramatically in recent years. At Iowa after four generations of selection for intramuscular fat (IMF), the average EBV for select line pigs is 1.03% greater than for control line pigs. Three generations of selection for residual feed intake has resulted in a 160 g/d reduction in feed intake, with limited reductions in growth and backfat. These lines are currently used to investigate the effect of selection, feeding regime, hormonal treatment, and MC4R genotype on global gene expression profiles using microarray technology. At NE, selection for litter size and its component traits ovulation rate, embryonic survival, and uterine capacity was initiated. Five lines were developed including 1) Line I: Index selection line, selected 11 generations for ovulation rate and embryonic survival, and an additional 13 generations for increased litter size; 2) C1, randomly selected control line contemporary to I, 3) Line IOL; derived from Line I at Generation 8 and subsequently selected 8 generations for ovulation rate and uterine capacity followed by 7 generations of litter size selection; 4) Line COL: derived from Line C1 at Generation 8 and subsequently selected 8 generations for ovulation rate and uterine capacity followed by 7 generations of litter size selection; and 5) Line C2: a line contemporary with Lines IOL and COL, derived from Line C1 at Generation 8 and subsequently selected randomly. At OH, data collected from random mated populations of Landrace and Berkshire purebred swine were used to estimate genetic (co)variance parameters for use in establishing within and across breed heritability, as well as genetic correlation estimates for use in selection programs for improved pork quality. Heritability estimates were as follows: Days to 113.4 kg (0.22), Backfat (0.62), Loin Muscle Area (0.57), Minolta Color (0.36), Visual Marbling Score (0.26), Intramuscular Fat Percentage (0.35), Warner-Bratzler Shear Force (0.35), and 24 Hour pH (0.25). Notable genetic correlations were Backfat and pH (r = 0.17), Minolta Color and pH (r = -0.50), Marbling Score and Warner-Bratzler Shear (r = -0.40), Intramuscular Fat Percentage and Warner-Bratzler Shear (r = -0.45). Analyses also showed significant breed effects for most production, carcass, and pork quality traits. These data are being used to initiate a long-term Landrace selection project to improve pork quality. At NC, relationships between indirect measures of behavior and performance were measured, to evaluate the phenotypic relationships among the back test, resident-intruder test scores (RIS), growth, Loin Muscle area, and backfat in pigs. It was concluded that phenotypic associations do exist among measures of behavior and performance traits, and increased lean gain was associated with increased aggression.

Researchers at IA, NE, and WA have also developed bioinformatic tools and experience. IA and NE have developed computer modeling and simulation programs to develop, optimize, and evaluate strategies for marker-assisted selection. Researchers at WA have focused on developing comparative reagents and tools for facilitating analyses of gene sequences, map locations, expressions and functions in pigs. Using human genes as references, WA has compiled full-length cDNA sequences of 3,881 genes and partial cDNA sequences of 10,358 genes in pigs by mining the EST database at NCBI. The same comparative approach was also used to determine genes expressed in embryos and reproductive tissues, providing a panel of transcripts that can be used to study pig embryo development and reproduction (Jiang et al., 2003). A comprehensive RH map of SSC3 was constructed at WA with a total of 116 genes/markers (Jiang et al., 2005). Alignment of this pig map to orthologous regions in human, dog, mouse and rat led to the identification of 31 provisional conserved ancestral blocks (CABs). All these tools and reagents provide a foundation to further determine conserved syntenies, narrow down QTL regions and explore candidate genes for economically important traits in pigs.

Researchers at NE and BARC continue to collaborate on pig disease research. At NE a PRRSV challenge experiment with a total of 400 pigs was conducted. Challenged pigs were infected with the PRRSV RFLP-Iowa strain, and blood was withdrawn and body temperature recorded at 4, 7, and 14 d post-challenge. All pigs were sacrificed at d-14 for tissues collection. Blood, lymph tissue, and lung tissue were analyzed for presence of virus. Principal component analyses were used to identify pigs with high and low phenotypic response to PRRSV. Traits included in analyses were weight gain, change in body temperature, viremia, lymph and spleen PRRSV titer, ELISA antibody ratio, and lung lesion score (Petry et al. 2005). Variation in the first principal component described overall phenotypic response to PRRSV. Pigs that had been infected with PRRSV, but recovered quickly from disease and showed few associated production losses were categorized as resistant, whereas pigs that were infected and had clinical and production losses associated with PRRS were categorized as susceptible. Differences in immunity were evaluated using RNA extracted from lung and bronchial lymph node (BLN) tissue from 28 pigs and their uninfected littermates. Expression differences in of 12 specific immune function genes were performed for both tissues in each pig followed by serum testing for 6 cytokine proteins. Results indicated intereukin-8 (IL8) and interferon-gamma (IFNG) as relevant for PRRSV resistance.

BARC has also focused on PRRS. They utilized real-time expression assays for panels of immune markers known to control vaccine and disease immunity (see database www.ba.ars.usda.gov/nrfl/nutri-immun-db/nrfl_query1new.html). Their infectious disease work has been aimed at determining effector mechanisms that lead to innate resistance or promote protective responses against infection. They have used real time gene expression assays to monitor immune gene activation during innate and adaptive [T helper 1 (Th1) and Th2] immune responses. They tested samples, collected as part of the national PRRS CAP grant, from swine infected with, or vaccinated for PRRS virus. Their data indicated that the slow and weak development of innate immunity as evidenced by interferon-alpha (IFNA), IL1, IL6, IL8 responses results in a weak interferon-gamma (IFNG) response, thus preventing protective responses and enabling PRRSV to persist in infected pigs.

In summary, significant progress has been made toward accomplishing the outcomes and outputs defined for the NC1004 multi-state project. Numerous collaborative linkages were developed between NC1004 member stations (examples include IA/IL, IA/BARC/OK, MI/OK, NE/BARC, NC/MARC, VT/MARC) and many of these partnerships resulted in successful grant funding, which allowed research efforts to move forward. Shared resources and public availability of data has been a cornerstone of the project and these continue to be developed and distributed. Integration of quantitative and molecular information facilitates rapid discovery of genetic variation influencing pig health, production efficiency and pork quality. In addition, outreach activities and interaction with industry scientists and producers allow transfer of knowledge to the industry.

Objectives

1. Further understand the dynamic genetic mechanisms that influence production efficiency and quality of pork.
   
2. Discover genetic mechanisms controlling animal health in pork production.
   

Methods

Resources required to conduct the collaborative research proposed for this project include phenotyped animal populations, tissue, DNA and RNA samples, and quantitative and molecular data and methods. No station has all resources to complete a given objective and resources will be exchanged and shared where possible. A complete overview of contributions from each station to each objective is in Appendix I. The basic approaches are to develop phenotyped animal resource populations, quantitative methods, assay reagents and genomic tools to measure gene and protein expression, and to apply these to evaluate and dissect the genetic basis of important traits in an integrated manner. Specifics are detailed below. Objective 1) Further understand the dynamic genetic mechanisms that influence production efficiency and quality of pork. Specific aims are to a) identify and confirm putative QTL regions, b) identify and confirm the roles of candidate genes, c) further evaluate the role of genes using expression technology, d) evaluate direct and correlated responses to selection, and e) develop strategies for the use of this information in breeding programs. Emphasis will be on traits related to male and female reproduction, sow longevity and productive life, feed intake and efficiency, growth, composition, and pork quality. Resource Populations. Animal resources that are well phenotyped are central to all investigations in animal genetics. Pig populations have been developed and maintained at collaborating stations and will be used and shared within this project. Populations consist of multiple generation resource populations developed for QTL discovery, or of closed lines within selection experiments. Substantial field data will also be available for a number of traits and these will be used where applicable. As an additional resource, IA maintains Meishan animals which are a unique model for reproduction traits, as the Meishan is known to have higher litter size. Research at IA with collaborating NC-1004 members (BARC) focuses on understanding the gene expression differences in the developing conceptus and endometrium during implantation. Finally, extensive field data are available for a number of traits related to reproduction, growth, and composition through the National Swine Registry. More detailed data on pork quality characteristics are available on a smaller scale through the National Pork Board. These data sets will be used to estimate genetic parameters and as a resource for the field evaluation of findings from experimental populations. QTL analyses. The IA, MI, and NE stations have or are in the process of completing F2 and later crosses for QTL mapping that overlap in foundation breeds. Multiple phenotypes related to reproduction, growth, composition, and meat quality are measured and DNA samples are collected and stored for sharing. Animals are genotyped for a large number of genetic markers across the genome, including microsatellites and single nucleotide polymorphisms (SNPs). Each station has completed a primary genomic scan to identify putative QTL regions. Markers for significant QTL regions will be shared and joint analyses will be done where possible to increase power to detect QTL and to validate QTL across populations. Candidate gene analyses. Concurrently with QTL studies, the IA, MI, NC, NE, and OH stations will continue to identify and evaluate candidate genes for reproduction, growth, composition, and pork quality traits. In addition to physiological candidate genes, positional candidate genes will be identified within QTL regions by comparative mapping based on genome maps from other species. Selection experiments. Selection experiments allow quantitative study of the genetic control of traits under selection and of relevant correlated traits. Data from these populations will be used to estimate trait genetic parameters, including heritabilities and genetic correlations. The IA, NC, NE, and OH stations have in development or will initiate selection lines related to reproduction, growth, feed efficiency, composition, and pork quality. In an effort to share data and population materials, selection objectives with common features across stations will be implemented. In addition, different stations will monitor alternate sets of traits to better determine the spectrum of correlated responses. Results from selection experiments will be compared and genetic responses of traits measured across experiments will be summarized. DNA and phenotypic databases from the selection lines will be shared among stations to further validate QTL and candidate genes that are identified in F2 resource populations. Where possible, divergent lines will be crossed within or across stations to create new QTL mapping resource populations. Assay Reagents. Specific novel reagents developed within the group include Q-PCR primers and conditions to measure the level of RNA for specific candidate genes (BARC, IA, MI) as well as specific antibodies for porcine proteins (BARC). Such reagents and/or experimental assay details will be shared amongst the NC-1004 members to decrease costs for such measurements as well as standardize results. Detection of differentially expressed genes. Identification of genes that are differentially expressed in alternate genotypes or physiological states provides further insight into the genetic control of traits and provides an important source of new candidate genes. Several approaches will be used to identify differentially expressed genes: a) Arrays of Genes. Broad-coverage commercial microarray tools such as the Qiagen-NRSP-8 13K oligonucleotide array, the 18K second NRSP-8 oligonucleotide array, and the Affymetrix 23K Genechip®, will be used by several members of NC-1004 to determine expression patterns of genes across treatments and populations to identify genes and physiological pathways underlying variation in seasonal infertility (GA/RARC); in feed intake, (IA, GA/RARC), in reproduction (IA, GA/RARC, BARC) and growth, carcass merit and meat quality traits (MI). b) Specific Individual Genes. Sequence comparisons and gene expression differences between pigs with divergent phenotypes will be used to test if a candidate gene represents a causative gene (IA, BARC, MI). Individual genes can be evaluated for quantitative expression using several methods, including northern blots, competitive PCR and RT-PCR (IA, BARC, NE, MI). As discussed above, within the NC-1004 research group, the expensive reagents and precise experimental conditions for gene expression will be shared across Stations (IA, BARC, NE, MI). Bioinformatics and statistics. Bio-informatics and statistical methods are needed to enable the collation, organization, analysis, and interpretation of the large amounts and types of data that will be generated. This includes development of databases for phenotypic and genetic marker data, cDNA library (EST) sequence data, and for expression data from microarrays. The NRSP-8 Swine Sub-committee/Coordinator and the Database Coordinator are heavily involved in genome maps and the databases required to store and visualize mapping information. The databases created and maintained by NC-1004 members will be non-overlapping and complementary, as they will be used primarily to hold and analyze QTL data within research groups as well as microarray data and analysis produced by NC-1004 members. Databases will be integrated across stations and across data types, including integration of phenotypic, QTL, sequence, and expression data. Publicly available software will be used but, where needed, methods will be adapted to the problems at hand or new methods will be developed. Several stations (IA, GA/RARC, MI, NC, NE) have initiatives in these areas, and resulting experimental designs, data management, and analysis tools will be shared among stations. Databases and bio-informatics tools will also be made publicly available. The MI station will conduct an expression QTL (eQTL) experiment to integrate gene expression information into QTL analysis for their F2 resource population. Experimental designs and statistical methods for detection of eQTL will be developed by both the MI and IA stations and these tools will be shared among stations. The WA station will continue to work on compilation and annotation of full-length cDNA sequences in pigs. Integration of current linkage and RH maps of pigs by assigning genes/markers to their human orthologs will build up a comparative frame map of the porcine genome, which will be further used in construction of mammalian concordant QTL maps for growth, fat deposition and fertility. All these will enable more effective data mining through analysis of all available data. In addition, NC-1004 groups will collaborate with the NRSP-8 Database Coordinator to integrate expression data for large numbers of genes with the physical and genetic location of such genes on the porcine genome map. Such integration cannot be done by the NRSP-8 Database Coordinator alone, and this integration will be invaluable for selecting expression candidate genes for analysis as discussed above. Marker Assisted Selection. Once QTL and candidate genes are discovered, quantitative methods will be developed to apply them in complex pig breeding programs. The IA and MI stations will develop methods to incorporate marker assisted selection tools into traditional genetic improvement methodologies. Objective 2) Discover genetic mechanisms controlling animal health in pork production. The specific aims of research done under this objective are to determine genetic parameters for variation in responses to specific pathogens affecting pigs, to identify genes responsible for variation in resistance/susceptibility to certain pathogens, and to develop a comprehensive database with information on animal genetics, immune traits, disease symptoms, and environmental parameters. An important component of this project is to have a central database. The database will be used to a) determine the degree of genetic, environmental, and genetic by environmental variation on pig health and responses to infectious organisms, b) identify host genes and proteins that are critical to pig health and disease resistance, and c) develop improved methods to prevent or manage disease and to select for greater disease resistance. Phenotypic, immunological, and genotypic data will be used to i) describe disease intensity, symptoms, duration, pathology, and morbidity/mortality, ii) assess responses to routine vaccinations; iii) define factors associated with disease resistance/susceptibility, iv) identify specific pathogenic variants by utilizing rapid detection methods, v) develop models to predict disease incidence and disease loads from genetic and environmental information, vi) estimate heritabilities of susceptibility to diseases and genetic relationships with production traits, and vii) identify specific genes involved in disease resistance and determine how they function. Diseases and Sampling: Porcine Reproductive and Respiratory Syndrome (PRRS) and Porcine Circovirus Associated Disease (PCVAD), the disease complex caused by PCV2 in conjunction with other pathogens, are the most serious diseases affecting US pig producers. Other diseases such as those caused by Salmonella spp., Mycoplasma hyopneumoniae (MHYO), Actinobacillus pleuropneumoniae (APP), and swine influenza virus (SIV), as well as ileitis, and scours caused by E. coli, are also widespread and cause economic losses. Several of these pathogens appear to interact, especially PRRSV, MHYO, and APP, in altering the severity of PCVAD, and the related post-weaning multisystemic wasting syndrome (PMWS). PRRS challenge experiments have been conducted at NE and IA as part of the NC1004 project. Tissues from infected and uninfected pigs have been used to identify specific immune function genes differentially expressed between more resistant and more susceptible pigs. BARC, IA, and NE will collaborate on experiments with stored tissue and DNA from these experiments to map genes for PRRS resistance and to validate QTL. A finding of the NE experiment was that levels of the IL8 cytokines and expression of IFNG in blood RNA and serum were correlated with resistance to PRRS. A new PRRS Coordinated Agricultural Project (CAP), referred to as PRRS CAP2, grant is being submitted to USDA CSREES grants in Oct. 2006. It has five research aims, one of which is aimed at determining the genetics of host resistance to PRRS. If funded, this project will support internal grant applications for as much as $400,000 on the genetics research aim. A letter of intent of NC1004 researchers to apply for these funds has been sent by Dr. Chris Tuggle, NC1004 Chair, to PRRS CAP2 PI Dr. Bob Rowland at Kansas State. Stations collaborating on this objective will coordinate and collaborate on use of field data (samples of blood and scores for severity of disease) and DNA samples for PRRS infected pigs. They will have the opportunity to coordinate an application for PRRS CAP2 genetics funds and have access to tissue/DNA samples that may become available from those experiments, if funded. These data will also be used to validate QTL and cytokine levels as predictors of response to PRRSV. PCVAD, caused by PCV2, is emerging as a serious economic disease in the US. The NE Station monitored PCVAD in NE populations as part of NC1004. They showed that expression of PCVAD is influenced by genetics (heritability of approximately 0.20) and common environmental effects associated with litters. It also differed significantly between lines selected for reproduction and respective controls. Other work (P. Halbur, personal communication) indicates that severity depends on the level of viremia and on interactions with other pathogens present. For PCVAD studies, blood samples will be drawn serially at 30-40 day intervals from weaning through 150 days of age from all pigs in NE selection lines. Pigs also will be scored for PCVAD; some tissue samples will be collected at kill for pathology and immune studies.. PCV2 viremia and other pathogens will be determined in all pigs exhibiting signs of PCVAD and in unaffected littermates and penmates. DNA and sera from these pigs will be used to determine effects of candidate genes in resistant and susceptible pigs. Data will be used to estimate quantitative genetic parameters. Other pathogens that may be monitored include MHYO, APP, SIV, Haemophilus parasuis, Pneumonic Pasteurellosis, Streptococcal diseases, and PRRSV. Populations: The NC, and NE stations will collect data on environment, performance, disease symptoms, immunological profiles, pathology, and pedigree within specific populations. These include the NE litter size selection lines and their crosses to industry lines and the NC selection lines for nutrient utilization. BARC will assist with immunological measurements and development of immunological profiles. Genetically defined populations may be developed for more detailed studies, including populations that segregate for genes for resistance/susceptibility to PRRSV (BARC), PCV2 (NE), , and Mycoplasma spp. and Salmonella spp. (IA). Database: Data will be entered into a central database that can be accessed by all participants. Disease symptoms will be monitored daily by scoring pens for presence/absence of coughing and diarrhea. Sentinel pigs will be regularly assessed for presence of a number of infectious organisms (see below) by serum, nasal, and fecal sampling. Pigs at selected ages will be sampled to monitor immune status. Blood and tissue from both diseased and healthy pigs will be collected and assayed or stored for immunological, gene mapping, and expression work at collaborating stations. Protocols for immunizations and to monitor responses to immunizations will be developed. In cases of severe disease outbreaks, pairs of age-matched affected and non-affected pigs will be killed and tissue collected for pathology, gene mapping/expression work, and in-vivo experiments. Necropsy reports will be regularly obtained on pigs that die after 10 d of age. Incidence of genetic abnormalities (e.g., hernia, cryptorchid, arthritis), disease symptoms (cough, diarrhea, temperature, etc.), and duration of symptoms and treatments imposed will be recorded. Routine performance data recording will include data on reproduction, growth and efficiency, composition of growth, disease symptoms, vaccine responses, survival to different ages, and age at death, along with genetic line and pedigree. Data on housing and flow of pigs will be recorded also and physical descriptions of each building will be maintained. At some stations (NE), environmental monitoring equipment (e.g., Dicam) will be used to monitor parameters such as temperature, humidity, air velocity, particulate levels, ammonia, and possibly other compounds such as phenols. Dicam is a unique system that controls the environment with sensors and switches that regulate fans and heaters and records real-time data on environmental parameters. The database will be relational for easy access and common formats will be used across stations. The database will be used to identify factors associated with animal health and to create profiles to distinguish healthy from diseased pigs. The database will be accessible via a secure web link and managed by Dr. Rodger Johnson, NE. Immunological responses: Responses of animals to pathogens will be studied at the molecular, cellular, animal, and population levels. BARC will assist with immunological measurements and development of immunological profiles of susceptible and resistant pigs from blood and tissue samples. Immunological tools to be used include antibody response, macrophage/neutrophil function, cytokine and chemokine levels, and analysis of organ-specific immune cell subsets. Cell- and tissue-specific gene expression profiles of host response to pathogen challenge will be developed using functional genomic approaches such as real time PCR and microarrays (BARC, IA, IL, NE). NC1004 stations (IA, BARC) may also monitor host response to pathogens that are associated with food safety concerns that prevent some consumers from choosing pork products, including Toxoplasma gondii, Campylobacter spp., Salmonella spp., and E. coli. The IA station will work with BARC and USDA-ARS collaborators at NADC (Ames) to identify host genes that respond to Salmonella inoculation in functional genomics and quantitative PCR methods for both in vivo and in vitro inoculations.

Measurement of Progress and Results

Outputs

• 1. Deposit of gene expression profiling data into public databases
• 2. Multi-station research publications on results from selection experiments, structural genomics, or functional genomics projects.
• 3. Public domain statistics and bioinformatics methodologies for applying genomics to quantitative genetics.
• 4. Identified genes, markers or chromosomal regions that are associated with improved traits in reproduction, growth, feed efficiency, composition, pork quality, and disease resistance/susceptibility, and transfer of information to the industry.
• 5. Documented methodologies to enhance genetic improvement of economic traits using quantitative, molecular, and genomic information.
• 6. Genetic characterization of unique resources for future research and industry applications.
• 7. Genetic parameters of production diseases.
• 8. Database cataloging animal genetic relationships to immune traits, disease symptoms and environmental parameters.

Outcomes or Projected Impacts

• New information of important genetic variation useful in marker-assisted genetic improvement of US swine herds. This genetic improvement can lead to substantial advances in production efficiency and product quality, including increased litter size, improved growth rate and feed efficiency, improved product quality, and improved resistance to disease. These will result in the availability of pork of high quality at the lowest possible price to the U.S. consumer and for international trade.
• Publicly available genomic databases, database systems, and bioinformatics tools, which allow other researchers and industry to capitalize on developed information and methods
• New opportunities for alternate uses of swine (e.g. pharmaceuticals, xenotransplantation) through a greater understanding of the biological aspects of swine. These opportunities could create new businesses within the U.S. pork sector and increase profit potential for those participating in this unique industry.
• Opportunities to reduce the use of antibiotics in swine production through improved resistance or reduced susceptibility to diseases and a greater understanding of the genetic basis of resistance to disease, allowing for more effective use of antibiotics. This would likely lead to greater consumer acceptance of pork and improve U.S. pork profit potential by increasing the demand for pork and decreasing expenses associated with unhealthy pigs.
• Opportunities to enhance pork safety to the consumer through reduced transmission of pathogens. This could lead to greater consumer confidence in U.S. pork products, increased consumer demand for pork, and ultimately improved profitability for U.S. pork producers.

Milestones

(2008): - Submit gene expression data for 5 or more tissues relevant to reproduction and feed efficiency - Submit a whole-genome comparative frame map of pigs - New QTL and candidate genes identified - Estimates of genetic parameters for feed intake and efficiency - Expression QTL analysis of loin muscle and backfat genes completed - Submit lymph node gene expression data for pig response to Salmonella challenge

(2009): " Complete integrated database on gene expression in pig and other species for tissues relevant to improving feed intake - New QTL and candidate genes identified - Gene expression profiling related to feed intake and efficiency completed - Submit data on genes associated with improved disease resistance

(2010): - New QTL and candidate genes identified - Methodology developed for QTL detection and marker-assisted selection using field data - Complete porcine orthologous genes (PORG database) - Complete database on integrated health and genetic trait data

(2011): - New QTL and candidate genes identified

(2012): - Complete database on mammalian concordant QTL maps - New QTL and candidate genes identified - Joint analysis of QTL resource populations completed

Projected Participation

View Appendix E: Participation

Outreach Plan

Results will be widely disseminated through scientific publications, articles in industry magazines, through presentations at scientific and industry meetings, and through one-on-one contacts. This will be accomplished by designating committee members to organize or coordinate the following outreach activities:


1) Work with organizing committees of American Society of Animal Science (Midwest Section and National), American Association of Swine Veterinarians, Allen D. Leman Swine Conference and other meeting venues to develop scientific symposia dedicated to project results and featuring NC committee members as speakers.


2) Work with industry groups such as National Swine Improvement Federation, National Pork Board-sponsored World Pork Expo, National Swine Registry, American Association of Swine Veterinarians and other organizations to develop workshops, symposia, or conferences to present information to producers, veterinarians, nutritionists, consultants, and other allied industry members. This outreach will be in a less-technical format and presented in both oral and written format for industry application.


3) Multi-state scientific papers, industry articles, and fact sheets (for example the Pork Industry Gateway [formerly the Pork Industry Handbook]).


4) Publications, both scientific and non-technical, genomic data bases, and bio-informatics tools will be further disseminated by internet (e.g. through the US Swine Genome Coordinator newsletter, Pig Genome Update, and various web sites). Links to these sites from other sites commonly accessed by scientists and producers, e.g., National Swine Improvement Federation, National Pork Board, and Pork Industry Gateway will be developed. A committee member will be appointed to gather electronic files of appropriate publications or data and to work with web-site managers to keep postings current and accessible.


5) Most participants are involved in outreach programs, either through formal extension responsibilities or as speakers at industry field days and conferences. Much of the data generated in this project will require testing and validation in industry herds. As it becomes apparent which technologies have potential for application, members will work with stakeholders to develop testing, validation and implementation projects. Opportunities for this outreach component will be reviewed annually at committee meetings and coordinated outreach projects will be developed.


6) In an effort to facilitate and enhance cooperation between the NC1004 group and other industry groups like the National Swine Improvement Federation (NSIF), development of "Workshops" or "Roundtables" for pig breeders at the NSIF Annual Meeting or other similar meetings. These could be events patterned after the British Pig Breeders Roundtable or the U.S. Poultry Breeders Roundtable. These workshops would appeal to breeders from the industry and the academic community. This group roundtable would have broad appeal from the swine breeding industry throughout North America and worldwide as groups like NSIF have broadened their appeal throughout these areas.

Organization/Governance

The membership of the regional Technical Committee (TC) includes the regional administrative adviser (AA, non-voting), a CREES representative (non-voting), a representative from each participating State Agricultural Experiment Station, and the USDA-ARS-BARC and USDA-ARS-RARC. Each participating station may have more than one representative on the TC, but each participating station is limited to one vote. The TC shall elect three of its members annually to serve as Chair, Vice-Chair, and Secretary. The three officers, along with the AA, will serve as an executive committee (EC). The TC Chair will serve as chair of the EC. When necessary, the EC shall have the authority to act on behalf of the TC. With authorization of the AA, the TC, its EC, and its subcommittees will meet when necessary to coordinate, review, plan, and discuss research progress. Generally, the full TC will meet annually to summarize and evaluate progress, analyze results, and plan future activities. An annual report of the results of the research of each contributing project shall be transmitted by each cooperating station to a person designated by the EC (generally the Chair) to compile a regional project report. This consolidated report will be approved by the Chair and by the AA and an appropriate number of copies shall be transmitted to the CREES, USDA, and to each cooperating agency.

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Attachments

Land Grant Participating States/Institutions

GA, IA, IL, MI, NC, NE, OH, PA, SD, WA

Non Land Grant Participating States/Institutions

Beltsville Area, USDA, USDA-ARS Beltsville Agricultural Resarch Center, USDA/ARS/U.S. Meat Animal Research Center