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ARS Home » Plains Area » Clay Center, Nebraska » U.S. Meat Animal Research Center » Livestock Bio-Systems » Research » Research Project #426415

Research Project: Genetic and Genomic Approaches to Improve Swine Reproductive Efficiency

Location: Livestock Bio-Systems

2018 Annual Report


Objectives
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.


Approach
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 Report
This is the final report for project 3040-31000-094-00D that terminated on 11/20/2017. The new project number is project 3040-31000-099-00D-"Identifying Genomic Solutions to Improve Efficiency of Swine Production." Significant progress was made during the duration of this project towards its two general goals of assessing genetic variation in commercial pigs and associating genetic variation with enhanced performance. Achievements of this project include producing an improved build of the swine genome using long-read sequencing technologies on a crossbred pig born at USMARC. The new build is considerably improved from the previous Sus scrofa 10.2 build as it corrects several misalignments and fills numerous gaps. The new build was used to assess genomic variation in commercial pigs with re-sequence data from nearly 150 animals from the USMARC BX swine population and 30 artificially inseminated (AI) sires from commercial suppliers. Analyses of these data identified 22 million variants, approximately 130,000 predicted to alter protein quantity or quality, and 569 classified as high-impact loss of function variants. These data are also being used to identify copy number variation segregating in these animals. Genome-wide association studies were conducted for age at puberty, failure to attain puberty, changes in feeding behavior during heat stress, teat number and number of vertebrae. While these studies confirmed some previously identified quantitative trait loci (QTL), they also discovered several novel pathways that merit further investigation. For instance, QTL associated with pubertal development co-localized with olfactory genes, feeding behavior during heat stress QTL tended to overlap regions containing sensory perception genes, QTL for vertebrae number tended to reside near homeobox genes (as expected) while QTL for teat number were not associated with homeobox genes (an unexpected result). Discovery of these novel biological pathways expands our understanding of these complex phenotypes and facilitates experimental designs to study these novel paths.


Accomplishments