Location: Livestock Bio-Systems2017 Annual Report
Objective 1: Identify genetic markers associated with reproductive performance suitable for use in commercial pigs. -Subobjective 1.A. Identify QTL for novel phenotypic traits associated with female reproductive performance. -1.B. Develop genetic markers in QTL regions that are predictive of phenotype in commercial populations. Objective 2: Identify genetic variation associated with genes affecting female reproductive traits in swine. -Subobjective 2.A. Create a database of genetic variants segregating in the USMARC BX population that are expected to affect gene function. -Subobjective 2.B. Determine if genetic variants from Sub-objective 2A residing in positional candidate genes for validated QTL from Objective 1 are associated with phenotypic variation. Objective 3: Provide the swine industry with the necessary information and tools to implement marker assisted selection for sow reproductive and lifetime performance.
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.
Progress continued on our efforts to identify genetic markers that can be utilized in selection programs (Objective 1). In addition, sequence variation predicted to alter protein structure and function for candidate genes residing in quantitative trait locus (QTL) regions for age at puberty and heat tolerance were tested in commercial-sired U.S. Meat Animal Research Center (USMARC) animals contributing to Objective 2. Several single nucleotide polymorphisms (SNPs) tested for age at puberty look quite promising. A genome-wide association study (GWAS) for behavioral anestrus in gilts (animals that had ovulatory cycles but did not show estrus) identified several candidate genes associated with puberty in humans. Potential functional variants in these genes were identified for further testing. All females that have completed 4 parities have been genotyped with the Illumina BeadChip technology such that we have in excess of 1,600 females for analyses of productive longevity and lifetime production. These analyses have been completed and results will be validated in other commercial populations supporting Objective 1. Additional animals from our Landrace-Duroc-Yorkshire population were sequenced to 10X or more to evaluate copy number variations (CNVs) that were identified from whole genome sequence of the 72 founders of our BX population. These animals include trios of animals (sire, dam and progeny) as well as 4 generations of father-son relationships. These data will enable imputation of CNV inheritance through generations. This will allow us to identify CNVs that correlate with phenotypes in our population, with the long-term goal of associating CNV to economic traits of interest and incorporating them into genomic selection systems (Objective 2). Work on improving the swine genome build continues based on the sequence data obtained using the next generation long-read sequencer. Genetic markers genotyped across the USMARC populations were mapped to the new build. Comparison of marker locations between the two builds identified several major discrepancies. To determine which build was more accurate, linkage disequilibrium values between adjacent markers from each position were compared. Linkage disequilibrium results indicated that for approximately 90% of the discrepancies, the new build was more accurate than the current build. As the new genome build (Sus Scrofa 11.1) was recently released, we are comparing build 11.1 to our new build and assessing accuracy and coverage. RNA sequence data using the long-read are being collected from 10 tissues of the animal sequenced to facilitate gene model prediction, as well as from neural centers that control social, sexual and feeding behavior from phenotypically different gilts (Objective 2). A study evaluating changes in an animal’s feeding behavior due to temperature deviations was conducted. Differences in how animals behave during increased temperatures were detected due to breed of sire and sex of the animal. A genome wide association study (GWAS) revealed several QTL reside within regions containing genes responsible for responses to stimuli (Objective 1). SNP that alter these proteins are currently being tested for association with response to heat stress. In an attempt to understand pork color and factors that contribute to the ‘Halo effect’ in pork ham muscles, GWAS for myoglobin content and RNA-Seq expression experiments in biceps femoris muscle were conducted. The GWAS study found a few important QTL that will be further investigated and the RNA-Seq and pathway analysis identified several genes involved in muscle fiber-type determination that were differentially expressed in light versus normal colored muscle tissues (Objective 1). Along with the University of Nebraska -Lincoln, Nebraska genetic markers associated with regions containing QTL for reproductive traits as well as 565 loss of function mutations detected in our population are being added to a genotyping product that will be commercially released in the fall of 2017 (Objective 3).
1. Genetic factors associated with changes in feeding behavior during heat stress were identified. Annual production losses due to extreme heat in the U.S. swine industry are approximately $300 million, with $200 million incurred in the finishing phase of production. Knowledge of genetic factors associated with tolerance to extreme temperatures in swine is devoid. Therefore, ARS scientists at Clay Center, Nebraska, conducted studies to monitor feeding behavior in growing pigs and evaluate how each pig altered their feeding pattern in response to increased ambient temperatures. Results indicate that gilts are less tolerant to high temperatures than barrows, while Duroc-sired pigs are the most resilient to warm temperatures and Landrace-sired pigs the most severely affected. A genome-wide association study identified several regions associated with changes in feeding behavior and indicate that genes known to detect stimuli (chemical, taste, etc.) may be causing these genetic differences. These results indicate that selection for pigs resilient to heat stress is possible and the genetic markers identified may be useful to the swine industry.
2. Genetic sequence variants have been used to identify causal variation and map complex traits. One of the key aims of livestock genetics and genomics research is to discover the genetic variants underlying economically important traits such as reproductive performance, feed efficiency, disease resistance/susceptibility, and product quality. ARS scientists at Clay Center, Nebraska sequenced the genomes of 72 influential sires and dams of the U.S. Meat Animal Research Center swine herd. They identified approximately 22 million variants and have submitted them to public databases. By utilizing the swine genome annotation, researchers found that only ~139,000 of these variants were expected to alter or disrupt the protein coded by a gene and or to regulate protein production. These variants are most likely to have a significant effect on phenotypic variation. Five hundred sixty-five variants were classified as high-impact loss-of-function (LOF) mutations. The LOF variants as well as functional variants within reproductive quantitative trait locus regions were submitted for inclusion in a commercially-available genotyping microarray.
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