Duration: 10/01/2002 to 09/30/2007

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. 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.

Improved disease resistance will enhance production efficiency, animal welfare, and producer 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.

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/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 decade, NC-210 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 of NC-220 have developed expertise to integrate quantitative and molecular genetics for genetic improvement. Researchers in both groups have active collaborations with scientists with expertise in the biological and physiological aspects of disease resistance, meat quality, and production efficiency. Jointly, researchers from NC-210 and 220 are in an ideal position 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. Therefore, a coordinated and integrated effort among experiment stations, 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. The NC-210 Project was renewed in 1997 to identify and evaluate the expression of candidate genes controlling economically important traits. The proposed project represents a merger of NC-220 and NC-210 to better address the multi-disciplinary nature of the research questions and to eliminate overlap.

Swine genetics research in the 1970s emphasized selection and crossbreeding experiments. The efficacy of procedures to genetically change rates and efficiencies of lean and fat deposition were documented and breed and heterosis effects were established for many traits. The research focus in the 1980s was on use of Best Linear Unbiased Prediction procedures to estimate breeding values, on simulation of life-cycle pork production, and on selection experiments to enhance reproductive traits (Gama and Johnson 1993). Indexes of breeding values for improvement of lines for specific roles in crossbreeding systems are now used throughout the industry.

Quantitative genetic research conducted in the 1990s aimed to improve the accuracy of predictors of progeny performance in different breed and environmental combinations. Furthermore, 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 (Bennett and Leymaster 1989; Johnson et al. 1999; Leymaster and Christenson 1999). Ruiz-Flores and Johnson (2002) showed that two-stage selection for ovulation rate and litter size is an effective procedure to improve litter size. 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, 2000) have mapped chromosomal regions involved in general immune traits and responses to stress.

Research conducted in NC 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 USDA-ARS, the Nordic group, and the international PiGMaP group, including contributions from NC-210 members, have developed 3 linkage maps (Ellegren et al. 1994; Archibald et al. 1995; Rohrer et al. 1996). The pig database now contains 2,133 loci, of which 653 are designated genes (http://www.genome.iastate.edu/pig.html).

An objective of NC-220 has been to use the genetic maps to identify important genes and to evaluate the potential of their use for genetic improvement. The main approaches used were the candidate gene approach and the genome scan approach. Several important genes were identified using the candidate gene approach, including the estrogen receptor locus for litter size (Rothschild et al. 1996) and the MC4R gene for production efficiency (Kim et al. 2000). For the genome scan approach, several F2 resource families were developed through breed or line crosses and chromosomal regions that contain quantitative trait loci (QTL) were identified. For example, Cassady et al. (2001) identified putative QTL at 10 positions for 6 reproductive traits in a genome scan in lines selected for litter size. Surprisingly, several candidate genes that were associated with litter size in other populations accounted for very little of the response in these selection lines (Linville et al. 2001). In another genome scan to detect genes for growth and meat quality, over 100 QTL were identified at the chromosome-wise level for the 40 traits studied, of which 19 were significant at the genome-wise level (Malek et al. 2001a, b).

Current objectives of the NC-210 project (1997-2002) include developing and applying technology for positional cloning of genes that regulate important traits, and for analysis of their function and expression. Members have mapped and evaluated numerous candidate genes, constructed more than a dozen tissue-specific expressed sequence tag (EST) libraries, identified genes that are expressed differentially under various physiological states, and evaluated physiological functions of several gene products. Several NC-210 researchers use state-of-the-art high-throughput technologies such as cDNA microarrays for expression profiling experiments.

These research efforts are examples of the growing body of information on the location of genes affecting economic traits in the pig, the comparative maps that provide candidates in the search for the exact identity of those genes, and on the biological role of these genes. However, much additional work is needed before this information can be implemented through marker-assisted selection. Most QTL are not mapped precisely enough for accurate selection and variation in their effects exists across populations. Possible causes of this variation are: 1) polymorphisms in candidate genes are markers for QTL and not causal mutations, 2) populations differ in QTL allele frequencies, and 3) regulator genes or interactions with the background genome or environment cause genes to be expressed differently in one population versus another. These issues can be addressed through joint analyses of QTL mapping populations, as was conducted by Walling et al. (2000) for SSC4 using six resource populations. Furthermore, the integration of gene expression information with efforts to identify QTL regions will greatly facilitate the identification of the specific genes that are involved, as well as their function.

Whereas initial swine breeding research focused on production traits (growth, backfat, reproduction), pork quality and feed efficiency have only now begun to receive sufficient attention. Knowledge on the genetic aspects of animal health related to pork production is also very limited. Thus, in addition to further elucidating the genetic nature of production traits, more work is needed in these other research areas.

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. However, additional improvement from direct selection on feed efficiency can occur, independent of improvements in growth and backfat thickness (Kuhlers et al. 2000). 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. While heritability of most meat quality traits is moderate to high (Sellier 1998), phenotypic measurement of these traits can only be done on the carcass and is difficult, especially at line speeds in commercial packing plants. Therefore, identification of genes controlling pork quality is of critical importance for making genetic improvement in these traits.

Disease costs the swine industry more than 1.5 billion dollars a year and is the most difficult problem facing pig producers. Approaches used today are costly and relatively ineffective as long-term solutions, including the use of diagnostics, drugs, vaccines, and management practices. 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.

Evidence for the genetic control of susceptibility to diseases is substantial (Wilkie and Mallard 2000). For example, there is clear evidence for genetic variation in susceptibility to neonatal diarrhea caused by E. Coli carrying K88 fimbriae. 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, 2000; Wilkie and Mallard 2000), e.g., for resistance to K88 E. Coli (Meijerink et al. 2000), knowledge of the genetic basis of resistance or susceptibility to infectious diseases remains limited.

Research that is related to work proposed herein is conducted by NCR-21 (now NCT-189), which focuses on statistical methods to elucidate the genetic nature of quantitative traits, and by NRSP-8, which is a multi-species project to develop and share integrated genome maps and comparative maps, and to maintain animal genome data bases. The proposed project complements the NCT-89 and NRSP-8 projects by applying methods and technologies to dissect genetic variation of important traits in swine. Direct experimentation with swine is required for results to be applicable to the swine industry. Membership of this project overlaps those of NCT-89 and NRSP-8, ensuring transfer of knowledge and expertise.

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.
   
3. 
   

Methods

Resources required to conduct this research include 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.

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, feed intake and efficiency, growth, composition, and pork quality.

The basic approaches are to develop animal resource populations, quantitative methods, and genomic tools, and to apply these to evaluate and dissect the genetic basis of important traits in an integrated manner. Specifics are detailed below.

Resource Populations. Animal resources 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 two- or three-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.

QTL and candidate gene analyses: The IA, IL, MARC, MI, MN, and NE stations have or are in the process of completing F₂ resource populations for QTL mapping that overlap in foundation breeds. Multiple phenotypes related to reproduction, growth, composition, and meat quality will be measured and DNA samples will be collected and stored for sharing. Animals will be genotyped for a large number of genetic markers across the genome, including microsatellites from the USDA Pig Genome Coordination Project (IA) and markers from an integrated SNP (single nucleotide polymorphism) map that will be developed at MN. Each station will complete a primary genomic scan to identify putative QTL regions. Markers for significant QTL regions will be shared and a joint analysis will be done to validate QTL across populations.

Concurrently with QTL studies, the IL, IA, MARC, 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 AL, IA, IN, NC, NCAT, NE, and OH stations have in development or will initiate selection lines related to reproduction, growth, 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 data bases from the selection lines will be shared with IL, IA, MARC, MI, MN, and TN 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.

Field data analysis. 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.

Development of cDNA libraries. In some organisms (including human and mouse), functional genomics is built upon the framework of knowing the near-complete sequence of the genome, and geared towards narrowing the gap between sequence and function. In livestock species, including the pig, data are limited to fairly extensive collections of partially sequenced regions of expressed genes. Normalized, subtracted cDNA libraries will be constructed to develop extensive catalogs of expressed sequence tags (ESTs) from a variety of relevant pig tissues, providing broad coverage of the porcine transcriptome. Efforts include:

1. Three cDNA libraries constructed from pooled tissues (MARC): i) embryos (10 to 30 d); ii) testes, ovary, pituitary, hypothalamus, placenta, endometrium; iii) brain, liver, muscle, placenta/endometrium, ovary, testes, and immune tissues.
2. Twenty-one libraries from individual reproductive tissues at various developmental stages, including embryo, term placenta, anterior pituitary, hypothalamus, ovary, and uterus (IA, NE).
3. A library constructed from pooled tissues including adipose, brain, cartilage, heart, immune tissues, intestine, kidney, liver, lung, mammary gland, reproductive tissues and skin (MI).
4. Ovarian follicles at various stages of folliculogenesis (NE).
5. Skeletal muscle at various developmental ages from mid-gestation to adult (IL, MI).
6. Normal and diseased lung (IA).
7. Prenatal brain (IL).
8. Testis (NC).

Libraries will be extensively sequence characterized and bioinformatic tools will be used to identify clusters of genes. Sharing of this material has already begun (IA, NE, MI).

Development of maps of expressed genes and comparative maps. Large numbers of ESTs will be physically localized using somatic cell hybrid and radiation hybrid mapping (IA, IL, MARC, MI, MN, NE) to improve the density of genes in the pig map and to facilitate comparative mapping. In addition, SNPs within expressed genes will be identified and used in linkage analysis (IA, MARC, MI, MN). Resulting comparative maps will be critical to capitalize on the massive power of functional genomics in humans and mutational analysis in mice. Identification of the map locations of genes that are expressed at critical times and in important tissues (e.g., ovary for ovulation rate, brain for appetite) is vital for elucidating the identity of QTL. Expressed loci that are mapped to QTL regions for related traits become candidates for further study. Together, these expression and comparative maps will be valuable tools for positional cloning within the various QTL resource populations and will be shared among stations.

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. Identified genes will be screened within the DNA and data banks of the resource populations to validate their effects. Several approaches will be used to identify differentially expressed genes:

a)Genome-wide scans for expression changes: Differential display-PCR (DD-PCR) can detect gene expression changes on a global scale without the prerequisites of large amounts of sequence data or knowledge of the underlying physiological factors. Several stations use DD-PCR and real time PCR to discover genes that regulate muscle growth during embryonic development (IN, MI), disease resistance (BARC, MN, OK), and reproduction (NC, NE).

b) Arrays of Genes. Microarray technology expands the scope of biological investigation from studying expression of single genes to studying potentially all genes at once in a systematic fashion, thereby offering the potential to uncover new biological connections between genes and biochemical pathways. DNA microarrays will be constructed using EST libraries developed within the project (IA, IL, IN, MARC, MI, MN, NE, OK). Microarrays will be shared across stations for use in unique genetic and physiological models and screened with RNA from pigs in resource populations and selection lines to ascertain new candidate genes.

c) Specific Individual Genes. Once a candidate gene is identified or mapped in close proximity to QTL, it must be determined whether it represents the causative gene. Sequence comparisons between pigs with divergent phenotypes and gene expression differences will be used for this purpose (IA, IL, MI, MN). Individual genes can be evaluated for quantitative expression using several methods, including northern blots, competitive PCR and RT-PCR.

Bio-informatics 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 data bases for phenotypic and genetic marker data, cDNA library (EST) sequence data, and for expression data from micro-arrays. Data bases will be extensively characterized and bio-informatic tools will be used to identify clusters of genes and metabolic pathways. Data bases will be integrated across stations and across data types, including integration of phenotypic, QTL, sequence, and expression data. This will enable more effective data mining through analysis of all available data. In addition, comparative genomics methods and bio-informatic tools will be used to integrate the swine genomic data bases with those of species that are rich in genome information, such as the mouse and human. 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, IN, MARC, MI, MN, NC, NCAT, NE, TN) have initiatives in these areas, including collaborations with faculty in statistics, computer science, and mathematics, and resulting experimental designs, data management, and analysis tools will be shared among stations. Data bases and bio-informatics tools will also be made publicly available, to maximize the utility of the information that will be generated.

Marker Assisted Selection. Once QTL and candidate genes are discovered, quantitative methods will be developed to apply them in complex pig breeding programs. The IL, IA, MI, and TN stations will develop methods to incorporate marker assisted selection tools into traditional genetic improvement methodologies. The AL, IL, and OH stations will implement marker-assisted selection programs in experimental herds based on candidate genes and identified QTL regions.

Objective 2) Discover genetic mechanisms controlling animal health in pork production.

The specific aims of research done under this objective are to develop a comprehensive database with information on animal genetics, immune traits, disease symptoms, and environmental parameters that 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.

Diseases: Many diseases affect pigs and new ones are identified each year. Mutations in both viruses and microbes alter the effectiveness of disease treatment regimens. Porcine Reproductive and Respiratory Syndrome (PRRS), Salmonellosis, Mycoplasma hyopneumonia, and scours caused by E. coli are widespread and cause severe economic losses. Other important diseases are Actinobacillus pleuropneumoniae (APP), swine influenza virus, ileitis, Circovirus PMWS, Porcine Respiratory Disease Complex, and Porcine Parvovirus. We will also monitor pathogens that are associated with food safety concerns that prevent some consumers from choosing pork products, including Toxoplasma gondii, Camplylobacter spp., Salmonella spp., and E. coli.

Some important diseases (e.g. PRRS) do not exist in all sentinel herds that will be used and every effort will be made to prevent their introduction. Organisms that exist in most herds and that will be studied are Circovirus, APP, M.hyopneumonia, Salmonellosis, E. coli, and Parvovirus. Other diseases that may be included if identified are Rotavirus, Porcine Respiratory Coronavirus, Haemophilus parasuis, Pneumonic Pasteurellosis and Streptococcal diseases, and PRRS.

Populations: Collectively, the IA, NC, NCAT, 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, IA selection lines for residual feed intake, NC selection lines for nutrient utilization, and NCAT Yorkshire and Duroc populations and their crosses, which are maintained in indoor/outdoor facilities. BARC and OK will assist with immunological measurements and development of immunological profiles. Genetically defined populations will be developed for more detailed studies, including populations that segregate for genes for resistance/susceptibility to PRRS (IL), spirochetes (NE), toxoplasmosis (BARC), 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.

Immunological responses: Responses of animals to pathogens will be studied at the molecular, cellular, animal, and population levels. BARC and OK 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 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, IL, NE, OK).

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.

Measurement of Progress and Results:

Outputs

Obj. 1	Identified genes or markers that are associated with functional differences in reproduction, growth, feed efficiency, composition, and pork quality.
	Documented methodologies to enhance genetic improvement of economic traits using quantitative, molecular, and genomic information.
	Multi-station research publication on results from selection experiments.
	Public domain cDNA libraries for use by the scientists and industry.
	Standardized sets of genes for micro-array analyses.
	Public domain statistical and bio-informatics methodologies for genomics research.
	Unique genetic resources for future research and industry application.
Obj. 2	Health profile checklist.
	Characterized disease resistant/susceptible populations.
	Decision support models to assist producers to prevent disease.
	Genetic parameters of production diseases.
	Identified genes or chromosomal regions associated with disease resistance/susceptibility.
	Transcriptional profiles of host responses to specific pathogen challenge.

Measurement of Progress and Results

Outputs

Outcomes or Projected Impacts

• New methodology and technology for genetic improvement of pigs that can lead to substantial advances in production efficiency and product quality, including increased litter size, improved growth rate and feed efficiency, and improved product quality. 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 data bases, data base systems, and bioinformatics tools, which allow other researchers and industry to capitalize on developed information and methods.
• New opportunities for the improvement of pork production by non-genetic means (e.g. management and feeding) through a greater understanding of biological aspects of pork production. This will improve efficiency and profitability of U.S pork production.
• 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

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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) meetings to develop scientific symposia dedicated to project results and featuring NC committee members as speakers.
2) Work with the organizing committee of the Conference of Research Workers in Animal Disease (CRWAD) to present information to animal disease researchers.
3) Work with organizing committees of industry groups such as National Swine Improvement Federation, National Pork Board-sponsored World Pork Expo, National Swine Registry, and other organizations to develop workshops/symposia/conferences to present information to producers. This outreach will be in a less-technical format and presented in both oral and written format for industry application.
4) Specific efforts will be made to reach under-served communities, for example through the Southern Ag-Biotech Consortium for Under-served Communities (SACUC). This is a joint effort of eleven 1890 institutions, industrial partners, governmental agencies, and farm organizations to promote agbiotech outreach to farmers and consumers and to strengthen K-Life science (biotech) education. NCAT, with M. Worku as campus coordinator, is a member of SACUC and will disseminate information from this NC project to under-served communities through educational outreach workshops, community outreach, and socio-economic studies in ag-biotechnology.

See additional Outreach Plan (attached).

Organization/Governance

The membership of the regional Technical Committee includes the regional administrative adviser (non-voting), a representative from CREES (non-voting), a technical representative from each participating State Agricultural Experiment Station, North Carolina A&T State University, the USDA-ARS Beltsville Agricultural Research Center, and the USDA-ARS, Roman L. Hruska U.S. Meat Animal Research Center. Each participating station may have more than one representative on the Technical Committee, but each participating station is limited to one vote.

The Technical Committee shall elect three of its members annually to serve as Chairperson, Vice-Chairperson, and Secretary. The three officers, along with the Administrative Adviser, will serve as an executive committee. The Chairperson of the Technical Committee will also serve as chairperson of the Executive Committee. When necessary, the Executive Committee shall have the authority to act on behalf of the Technical Committee.

With authorization of the Administrative Adviser, the Technical Committee, its Executive Committee, and its subcommittees will meet when necessary to coordinate, review, plan, and discuss research progress. Generally, the full Technical Committee will meet annually to summarize and evaluate progress, analyze results, and plan future activities and publications.

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 Executive Committee (generally the Chairperson) to compile a consolidated report of the regional project. This consolidated report will be approved by the Chairperson and by the Administrative Adviser and an appropriate number of copies shall be transmitted to the CREES, USDA, and to each cooperating agency.

Literature Cited

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Attachments

Land Grant Participating States/Institutions

AL, GA, IA, IL, IN, MD, MI, MN, NC, NE, OH, OK, SD

Non Land Grant Participating States/Institutions

Beltsville Area, USDA, USDA-ARS Beltsville Agricultural Resarch Center, USDA-ARS Roman L. Hruska US Meat Animal Research Center