Location: Reproduction Research
2008 Annual Report
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.
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.
The assessment of imprinted genes has also been quite successful as well as linking the genetic linkage map with the porcine physical maps (BAC map and genome sequence). Members of this CRIS project have also actively participated in international consortiums to sequence the pig genome and develop a high density SNP genotyping platform for pig genomic research.
The achievement of future milestones of this CRIS are dependent on the integration of markers on the swine genetic linkage map with the BAC physical map. The swine linkage map contains 3,418 markers primarily generated at the USMARC and spans the complete pig genome. The BAC physical map was assembled by the Swine Genome Sequencing Consortium and consists of over 260,000 genomic clone fingerprints assembled in 172 large fragments or contigs covering 98% of the pig genome. Several computational methods, some incorporating additional information such as the Harvard Gene Index and the swine-human comparative map, were utilized to create tens of thousands of links between the maps. A graph of linkage vs physical map position shows the expected sigmoidal relationship that is consistent with higher recombination at the telomeres and lower at the centromeres. There were no major discrepancies found between the physical and genetic maps. This integrated map will facilitate directed marker development as well as assist in genome sequence assembly. This project is aligned with Performance Measure 1.2.3, Component 1 of the National Program 101 Action Plan, “Understanding, Improving, and Effectively Using Animal Genetic and Genomic Resources”, specifically Problem Statement 1A: Develop Genome-Enabling Tools and Reagents.2. Identification and validation of SNPs in pig calpastatin that are predictive of pork tenderness.
The quality and palatability of fresh retail pork is variable and tenderness is a key factor guiding consumer choices for pork. The ability to genetically select for animals that are superior and consistent for meat quality traits would improve consumer acceptance and benefit the pork industry. A quantitative trait locus (QTL) region has been identified on SSC2 for pork tenderness over the calpastatin gene. Several markers in the calpastatin gene were genotyped and analyzed for association with slice shear force in Duroc-Landrace and Duroc-Landrace-Large White populations and three were highly significantly associated with slice shear force. These results provide publicly available genetic markers associated with slice shear force that may be useful to the swine industry for marker assisted selection of animals with superior tenderness.
This accomplishment is aligned with Performance Measure 1.2.3, Component 1 of the National Program Action Plan, “Understanding, Improving, and Effectively Using Animal Genetic and Genomic Resources”, specifically Problem Statement 1D: Develop and Implement Genome-Enabled Genetic Improvement Programs.3. Development of an integrated physical map of the pig genome.
We have constructed a comprehensive physical map of the pig genome using large segments of DNA from the pig genome in the form of bacterial artificial chromosomes (BACs). The physical map integrates previous landmark maps with a fingerprint map developed from these large segments of DNA. Because of the close relationship between human and pig sequence, we used sequence information from over 260,000 BACs compared to the human genome to improve the continuity and local ordering of the BAC segments. We estimate that approximately 98% of the pig genome is represented in 172 contigs or overlapping groups of BACs. Some chromosomes are well mapped and the entire chromosome is represented by only one or a few contigs, while other chromosomes are represented by many contigs. The map is publicly accessible on the internet (http://pre.ensembl.org/Sus_scrofa/index.html). This physical map is providing a framework for the generation and assembly of the pig genome sequence. Furthermore, the map is immediately useful to the pig research community to identify genes and fine mapping of quantitative trait loci.
This accomplishment is aligned with Performance Measure 1.2.3, Component 1 of the National Program Action Plan, “Understanding, Improving, and Effectively Using Animal Genetic and Genomic Resources”, specifically Problem Statement 1A: Develop Genome-Enabling Tools and Reagents.
Freking, B.A., Leymaster, K.A., Vallet, J.L., Christenson, R. 2007. Number of fetuses and conceptus growth throughout gestation in lines of pigs selected for either ovulation rate or uterine capacity. Journal of Animal Science. 85(9):2093-2103.
Humphray, S.J., Scott, C.E., Clark, R., Marron, B., Bender, C., Camm, N., Davis, J., Jenks, A., Noon, A., Patel, M., Sehra, H., Yang, F., Rogatcheva, M.B., Milan, D., Chardon, P., Rohrer, G., Nonneman, D., de Jong, P., Meyers, S.N., Archibald, A., Beever, J.E., Schook, L.B., Rogers, J. 2007. A high utility integrated map of the pig genome. Genome Biology. 8(7):R139.
Alexander, L.J., Juneja, B., Shiroma, D., Nonneman, D.J., Snelling, W.M., Fahrenkrug, S.C. 2007. Comparative and physical mapping of 112 previously reported and 105 new porcine microsatellites. Animal Genetics 38:584-594.
Chitko Mckown, C.G., Leonard, J.C., Moscatello, D., Miller, L.C., Freking, B.A. 2008. Development of cell lines from the sheep used to construct the CHORI-243 ovine BAC library. Animal Biotechnology. 19(2):84-88.
Bischoff, S.R., Tsai, S., Hardison, N.E., York, A.M., Freking, B.A., Nonneman, D.J., Rohrer, G.A., Piedrahita, J.A. 2008. Identification of SNPs and INDELS in swine transcribed sequences using short oligonucleotide microarrays. Biomed Central (BMC) Genomics 9:252.
Jacobs, K., Van Poucke, M., Mattheeuws, M., Chardon, P., Yerle, M., Rohrer, G.A., Van Zeveren, A., Peelman, L.J. 2002. Characterization of the porcine melanocortin 2 receptor gene (MC2R). Animal Genetics 33:415-421.