Page Banner

United States Department of Agriculture

Agricultural Research Service

Related Topics


Location: Reproduction Research

2013 Annual Report

1a. Objectives (from AD-416):
Objective 1: Develop genetic tests which can be used as tools to improve selection in commercial swine populations for important production traits. Objective 2: Determine interactions among traits, parental origin of alleles, loci and/or environment to better understand the basis of genetic correlations, inheritance of complex traits and to more accurately formulate selection plans in swine. Objective 3: Utilize the knowledge gained from objective 2 and from USMARC collaborators in conjunction with the swine genome sequence to identify the causative genes underlying QTL.

1b. Approach (from AD-416):
The goal of this research is to ensure US swine producers are a competitive source of pork products by providing the genetic information necessary to maintain superior production levels. The approach will use genetic markers and genomic technologies to understand how the genome regulates animal performance and determine the molecular basis behind non-additive genetic effects. Availability of the draft swine genome sequence will allow continuation of research on genomic regions affecting components of reproductive performance, growth, and carcass quality to move faster and more efficiently. Future studies will include a broader list of phenotypes including metabolic parameters to understand nutrient utilization, animal disposition and incidence of disease during natural outbreaks in the population. This project will use genomic approaches in combination with extensively phenotyped swine populations to identify genetic markers associated with production traits and understand these complex biological processes. Our approach will be to conduct genome-wide QTL scans and then fine map these QTL and develop SNP markers in tight linkage with the causative polymorphisms. QTL scans will be conducted in subsets of the USMARC BX swine population that have been extensively phenotyped for a wide variety of traits. This will permit a more complete biological understanding of each QTL region. Follow-up studies on QTL will be conducted in the BX population on larger groups of animals that may be phenotyped for a specific set of traits. Standard QTL analyses will first be conducted followed by statistical models to identify components to nonadditive genetic variation affecting performance such as intra-locus (dominance and imprinting) and inter-locus (epistatic) interactions. These analyses will also yield valuable information about pleiotropic effects to understand the molecular bases of genetic correlations. A high density SNP map (5-20 SNP/cM) will be developed for the studied regions and genotyped across additional generations of BX animals to fine map QTL. Significant SNP markers developed from these approaches will be evaluated in additional commercially relevant lines of pig to ensure their applicability in commercial pigs. Markers that exhibit useful predictive genetic information will be disseminated to the swine industry. Finally with all of the genetic and phenotypic knowledge in hand, we should be well-equipped to determine the causative gene for some QTL and greatly improve our understanding of the physiological effects of these QTL. A precise location of the causative gene as predicted from fine mapping studies, knowledge about different biological pathways affected from the extensively phenotyped population and knowledge about the genes located in the region from the swine genome sequence should allow selection of positional candidate gene to study for causative variation. These studies will be supplemented with functional genomic and marker-assisted animal experimentation.

3. Progress Report:
This report is for bridging project 5438-31000-083 with new project expected to go through peer review in December 2013. Considerable progress has been made in the past year to identify QTL for swine production traits. We have completed our analyses on genetic markers associated with failure to reach puberty and are now evaluating candidate genes to identify the genetic variation responsible. In addition, we have completed the genome-wide association analyses of birth intervals and other factors contributing to death losses in the newborn piglet. Also the preliminary analyses from pooled DNAs on genomic regions controlling a piglet’s ability to absorb colostrum have been verified with genotypic information from over 1,500 piglets. These analyses have identified a potential mechanism to improve piglet viability as three associations are located near genes known to control appetite. To facilitate selection of genetic markers within our research population, we sequenced the genomes of founding animals. Data were collected on the 24 founding males representing an estimated fourfold coverage of each boar’s genome and twofold coverage was obtained for 48 of the most influential females. Analyses of data have identified millions of genetic markers (SNP) that can be used for fine-mapping studies. In addition, the SNP are being evaluated for their potential impact on proteins that are necessary for normal development and function. By using the same sequencing technology, we have collected data to determine if the gene inherited from the mother is expressed at the same level as the gene inherited from the father. Progeny receive one copy of each gene from their mother and a second copy of the gene from their father. Determining the balance of gene expression from different parental origin is important to understanding how quantitative traits are inherited. Finally, as part of a National Pork Board funded collaboration with Michigan State University scientists, we have collected detailed genotypic data on nearly 2,000 industry pigs. These animals have phenotypic data collected on tenderness, color and eating quality attributes. We will be conducting analyses to determine associations between genetic markers and traits associated with pork quality.

4. Accomplishments

Review Publications
Runcie, D.E., Wiedmann, R.T., Archie, E.A., Altmann, J., Wray, G.A., Alberts, S.C., Tung, J. 2013. Social environment influences the relationship between genotype and gene expression in wild baboons. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences. 368(1618):20120345.

Nonneman, D.J., Brown-Brandl, T., Jones, S.A., Wiedmann, R.T., Rohrer, G.A. 2012. A defect in dystrophin causes a novel porcine stress syndrome. Biomed Central (BMC) Genomics. 13:233.

Rohrer, G.A., Nonneman, D.J., Miller, R.K., Zerby, H., Moeller, S.J. 2012. Association of single nucleotide polymorphism (SNP) markers in candidate genes and QTL regions with pork quality traits in commercial pigs. Meat Science. 92(4):511-518.

Schneider, J.F., Rempel, L.A., Rohrer, G.A. 2012. Genome-wide association study of swine farrowing traits. Part I: Genetic and genomic parameter estimates. Journal of Animal Science. 90(10):3353-3359.

Schneider, J.F., Rempel, L.A., Snelling, W.M., Wiedmann, R.T., Nonneman, D.J., Rohrer, G.A. 2012. Genome-wide association study of swine farrowing traits. Part II: Bayesian analysis of marker data. Journal of Animal Science. 90(10):3360-3367.

Tortereau, F., Servin, B., Frantz, L., Megens, H.-J., Milan, D., Rohrer, G., Wiedmann, R., Beever, J., Archibald, A.L., Schook, L.B., Groenen, M.A.M. 2012. A high density recombination map of the pig reveals a correlation between sex-specific recombination and GC content. BMC Genomics. 13:586.

Bischoff, S.R., Tsai, S.Q., Hardison, N.E., Motsinger-Reif, A.A., Freking, B.A., Nonneman, D.J., Rohrer, G.A., Piedrahita, J.A. 2013. Differences in X-chromosome transcriptional activity and cholesterol metabolism between placentae from swine breeds from Asian and Western origins. PLoS One. 8(1):e55345.

McDaneld, T.G., Smith, T.P.L., Harhay, G.P., and Wiedmann, R.T. 2012. Next-generation sequencing of the porcine skeletal muscle transcriptome for computational prediction of microRNA gene targets. PLoS One. 7(7):e42039. doi:10.1371/journal.pone.0042039.

Groenen, M.A., Archibald, A.L., Uenishi, H., Tuggle, C., Takeuchi, Y., Rothschild, M.F., Rogel-Gaillard, C., Park, C., Milan, D., Hendrik-Jan, M., Li, S., Larkin, D., Kim, H., Franz, L.A., Caccamo, M., Hyeonju, A., Aken, B.L., Anselmo, A., Anthon, C., Auvil, L., Bouabid, B., Beattie, C.W., Bendixen, C., Berman, D.J., Blecha, F., Blomberg, J., Bolund, L., Bosse, M., Botti, S., Zhan, B., Bystrom, M., Capitanu, B., Silva, D.C., Chardon, P., Chen, C.T., Cheng, R., Choi, S., Chow, W., Clark, R.C., Clee, C., Crooijmans, R.P., Dawson, H.D., Dehais, P., De Sapio, F., Dibbits, B., Drou, N., Du, Z., Eversole, K., Fadista, J., Fairley, S., Faraut, T., Faulkner, G.J., Fowler, K.E., Fredholm, M., Fritz, E., Gilbert, J.G., Giuffra, E., Gorodkin, J., Griffin, D., Harrow, J.L., Hayward, A., Howe, K., Zhi-Liang, H., Humphray, S.J., Hunt, T., Hornshoj, H., Jeon, J., Jern, P., Jones, M., Jurka, J., Kanamori, H., Kapetanovic, R., Jaebum, K., Kim, J., Kim, K., Kim, T., Larson, G., Lee, K., Lee, K., Leggett, R., Lewin, H.A., Li, Y., Liu, W., Loveland, J.E., Lu, Y., Lunney, J.K., Ma, J., Madsen, O., Mann, K., Mathews, L., Mclaren, S., Morozumi, T., Murtaug, M.P., Narayan, J., Nguyen, D., Ni, P., Oh, S., Onteru, S., Rohrer, G.A., et al. 2012. Analysis of pig genomes provide insight into porcine demography and evolution. Nature. 491(7424):393-8.

Last Modified: 10/16/2017
Footer Content Back to Top of Page