2009 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.
For pork quality, we have obtained approximately 1,500 samples from commercial pigs with detailed pork palatability data. These samples are being used in conjunction with our 1,200 sampled animals from previous studies to develop genetic markers for tenderness suitable for industry use. Our primary focus has been on measures of tenderness. These samples have been genotyped for approximately 100 SNP markers located in QTL regions. The most intriguing results are for markers within the calpastatin gene. These markers have been consistently associated with tenderness in all populations.
Eighteen genes and a few other regions of the genome have been investigated for associations with female reproductive performance in over 1,000 BX sows. Markers were selected from regions previously reported to influence female reproduction with either genome scans or candidate gene approaches. Published markers along with novel markers were developed within previously reported genes and evaluated for significant associations with female reproductive performance. While genes involved in signaling or synthesis of reproductive hormones were frequently tested in the literature, our results indicate that genes affecting energy metabolism are also quite important, especially for rebreeding performance traits.
In an attempt to conduct genome-wide association analyses, we collected data necessary to develop a high throughput SNP genotyping platform for commercial swine. A total of 115,572 markers were discovered and location in the swine genome determined. These markers were discovered by comparing over 5 million sequences with an average length of 232 bases. The sequences represented 421,060 segments of the pig genome. The location of each marker was predicted by comparing the segment to the sequence of the entire pig genome.
The novel markers were combined with other publicly available markers to select the best set of markers for a commercial genotyping chip. These efforts resulted in approximately 60,000 genetic markers evenly spaced across the genome simultaneously assayed in a single reaction. After the genotyping platform was developed, in cooperation with Illumina, Inc. (see project report for 5438-31000-083-06S), we began genotyping 2,976 animals in the BX population with a broad range of phenotypic data for genome-wide association analyses.
Kuehn, L.A., Nonneman, D.J., Klindt, J.M., Wise, T.H. 2009. Genetic relationships of body composition, serum leptin, and age at puberty in gilts. Journal of Animal Science. 87(2):477-483.
Wiedmann, R.T., Smith, T.P., Nonneman, D.J. 2008. SNP discovery in swine by reduced representation and high throughput pyrosequencing. BioMed Central (BMC) Genetics. 9:81.
Germerodt, M., Beuermann, C., Rohrer, G.A., Snelling, W.M., Brenig, B., Knorr, C. 2008. Characterization and linkage mapping of 15 porcine STS markers to fine-map chromosomal regions associated with hernia inguinalis/scrotalis. Animal Genetics 39:671-672.
Campbell, E.M., Nonneman, D.J., Kuehn, L.A., Rohrer, G.A. 2008. Genetic variation in the mannosidase 2B2 gene and its association with ovulation rate in pigs. Animal Genetics. 39:515-519.
Holl, J.W., Rohrer, G.A., Shackelford, S.D., Wheeler, T.L., Koohmaraie, M. 2008. Estimates of genetic parameters for kyphosis in two crossbred swine populations. Journal of Animal Science. 86:1765-1769.