2010 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.
Due to a critical vacancy in the previous year, we were unable to complete an intra-locus quantitative trait loci (QTL) scan in FY2010. In addition, based on rapid developments in technology, we have switched our genotyping approach from a low-marker density approach relying on linkage between markers and segregation analysis to a high-marker density approach that utilizes association analyses across the entire genome. This change in direction dramatically affects statistical approaches and is computationally demanding.
We have made significant progress in all of our research objectives. We completed 3 studies using Illumina Porcine 60K BeadChip. 2,980 animals in the U.S. Meat Animal Research Center (USMARC) commercial swine population were genotyped resulting in over 177 million genotypes from 59,895 unique single nucleotide polymorphisms (SNP) (call rate 99.6%). Analyses on these data have been initiated for marker associations with measures of female reproduction, growth rate, body composition, skeletal measures, and two categorical traits (kyphosis and stress syndrome). 700 boars used in commercial populations were genotyped and association analyses conducted for first parity reproductive traits using daughter deviations as phenotypes for each boar. Results indicate 13 putative QTL regions were detected (2 for number born dead, 9 for number born alive and 2 for weaning-to-estrus interval). Finally, 92 animals challenged with Porcine circovirus 2 (PCV2) at the National Animal Disease Center (USDA-ARS) were genotyped. Analyses will be conducted for association with various response measures.
We completed an evaluation of candidate genes and QTL (over 200 markers) reported in literature for measures of pork quality and palatability in 905 samples that were collected and characterized in a National Pork Board funded grant to Ohio State University.
Test matings have been made to support a study to identify the causative genetic variation for a stress syndrome recently detected in the USMARC commercial swine population. These progeny have been extensively evaluated to better understand the physiology behind this form of stress-related death. We have replicated the stress-induced death and are in the process of acquiring enough affected animals to permit a comprehensive genetic evaluation.
Sequence analysis within Lim-domain and actin binding1 (LIMA1) and transmembrane protein 138(TMEM138) generated 46 SNP markers that were evaluated for their role in placental gene expression differences between pigs selected for uterine capacity and controls. The SNP markers genotyped displayed significant allele frequency differences between the two lines. Association analyses of the markers indicated significant effects on number of live embryos, fetal and placental development. However, these markers did not display significant effects in within-line analyses. Animals outside the selected populations are needed to evaluate the potential utility of these markers and their role in uterine capacity.
Validation of markers and quantitative trait loci (QTL) regions for pork quality and palatability. Numerous marker associations for measures of pork eating qualities have been reported, but few have been independently evaluated in commercial pork products. The National Pork Board funded the Ohio State University to collect detailed pork quality data on over 900 pork loins collected at commercial abattoirs. ARS scientists at the U.S. Meat Animal Research Center in Clay Center, NE genotyped each pork loin for over 200 single nucleotide polymorphisms (SNP) markers. SNP markers utilized were either located in QTL regions, candidate genes, or were previously associated with measures of pork quality. Several associations between SNP markers and pork quality were validated. These results will aid producers in determining which genetic markers they may wish to test in their herds to improve pork eating quality.
Identification of 13 quantitative trait loci (QTL) affecting first parity female reproductive performance in commercial swine. Currently, a large number (over 20%) of females retained for breeding in commercial production fail to produce two litters largely due to poor reproductive performance. The identification of genetic markers capable of predicting a gilt’s future reproductive performance in commercial herds would help eliminate these poor performing animals before they are transferred to the breeding herd. Genotypic data were collected by the U.S. Meat Animal Research Center (USMARC) on 700 boars contributed by industry partners using the Illumina Porcine 60K BeadChip. Phenotypic data on each of the boars’ daughters were available and their deviations from contemporary group means were used as phenotypes for each boar. In addition, similar data were available for 123 boars used in the USMARC commercial population. Two significant QTL were detected for number born dead, nine suggestive QTL were detected for number born alive, and two suggestive QTL were detected for weaning-to-estrus interval by ARS scientists at the U.S. Meat Animal Research Center in Clay Center, NE. These findings can have immediate impact in commercial populations.
Erkens, T., Rohrer, G.A., Van Zeveren, A., Peelman, L.J. 2009. SNP Detection in the Porcine PPARGC1A Promoter Region and 3'UTR, and an Association Analysis in a Landrace-Duroc-Yorkshire Population. Czech Journal of Animal Science. 54(9):408-416.
Holl, J.W., Rohrer, G.A., Brown Brandl, T.M. 2010. Estimates of Genetic Parameters Among Scale Activity Scores, Growth, and Fatness in Pigs. Journal of Animal Science. 88:455-459.
Lindholm-Perry, A.K., Rohrer, G.A., Holl, J.W., Shackelford, S.D., Wheeler, T.L., Koohmaraie, M., Nonneman, D.J. 2009. Relationships among calpastatin single nucleotide polymorphisms, calpastatin expression and tenderness in pork longissimus. Animal Genetics. 40(5):713-721.
Rempel, L.A., Nonneman, D.J., Wise, T.H., Erkens, T., Peelman, L.J., Rohrer, G.A. 2010. Association Analyses of Candidate Single Nucleotide Polymorphisms on Reproductive Traits in Swine. Journal of Animal Science. 88:1-15.
Ramos, A.M., Crooijmans, R.P.M.A., Affara, N.A., Amaral, A.J., Archibald, A.L., Beever, J.E., Bendixen, C., Churcher, C., Clark, R., Dehais, P., Hansen, M.S., Hedegaard, J., Hu, Z.L., Kerstens, H.H., Law, A.S., Megens, H.J., Milan, D., Nonneman, D.J., Rohrer, G.A., Rothschild, M.F., Smith, T.P.L., Schnabel, R.D., Van Tassell, C.P., Taylor, J.F., Wiedmann, R.T., Schook, L.B., Groenen, M.A.M. 2009. Design of a High Density SNP Genotyping Assay in the Pig Using SNPs Identified and Characterized by Next Generation Sequencing Technology. PLoS One 4(8):E6524. p. 1-13.
Liu, G., Hou, Y., Zhu, B., Cardone, M.F., Jiang, L., Cellamare, A., Mitra, A., Alexander, L.J., Coutinho, L.L., Gasbarre, L.C., Heaton, M.P., Li, R.W., Matukumalli, L.K., Nonneman, D.J., De A Regitano, L.C., Smith, T.P., Song, J., Sonstegard, T.S., Van Tassell, C.P., Eichler, E.E., Mcdaneld, T.G., Keele, J.W. 2010. Analysis of copy number variations among cattle breeds. Genome Research. 20:693-703.
Sanchez Castano, C., Smith, T.P., Wiedmann, R.T., Vallejo, R.L., Salem, M., Yao, J., Rexroad Iii, C.E. 2009. Single nucleotide polymorphism discovery in rainbow trout by deep sequencing of a reduced representation library. Biomed Central (BMC) Genomics. 10:559.
Bischoff, S.R., Tsai, S., Hardison, N., Motsinger-Reif, A.A., Freking, B.A., Nonneman, D.J., Rohrer, G.A., Piedrahita, J.A. 2009. Characterization of Conserved and Non-conserved Imprinted Genes in Swine. Biology of Reproduction. 81(5):906-920.
Heaton, M.P., Leymaster, K.A., Kalbfleisch, T.S., Freking, B.A., Smith, T.P., Clawson, M.L., Laegreid, W.W. 2010. Ovine Reference Materials and Assays for Prion Genetic Testing. BioMed Central (BMC) Veterinary Research [serial online]. 6:23. Available: http://www.biomedcentral.com/1746-6148/6/23.