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Analysis of polygenic selection in purebred and crossbred pig genomes using Generation Proxy Selection Mapping

Presenter:

Caleb Grohmann

Date:

04-28-2022

Time:

3:30PM-4:30PM

Location:

Zoom

Background

Artificial selection on quantitative traits using selection indices in commercial livestock breeding populations causes changes in allele frequency over time, termed selection signatures, at causal loci and other surrounding genomic regions.  Researchers and managers of pig breeding programs are motivated to understand the genetic basis of phenotypic diversity across genetic lines, breeds, and populations using selection signature analyses.  Here, we applied Generation Proxy Selection Mapping (GPSM), a genome-wide association analysis of SNP genotype (38,294 to 46,458 SNPs) on birth date, in four pig populations (15,457, 15,772, 16,595 and 8,447 pigs per population) to identify loci responding to artificial selection over a span of five to ten years.  Gene-drop simulation analyses were conducted to validate GPSM results.  Selection signatures within and across each population of pigs were compared in the context of commercial pork production.

Results

Forty-nine to 854 loci were identified by GPSM as under selection (Q-values less than 0.10) across 15 subsets of pigs based on population combinations.  The number of significant associations increased as populations of pigs were pooled.  In addition, several significant associations were identified in more than one population.  These results indicate concurrent selection objectives, similar genetic architectures, and shared causal variants responding to selection across populations.  Negligible error rates (less than or equal to 0.02%) of false-positive associations were identified when testing GPSM on gene-drop simulated genotypes, suggesting that GPSM is robust to detection of random genetic drift in actual pig populations.

Conclusions

This work confirms the efficacy and accuracy of the GPSM method in detecting selection signatures in commercial pig populations.  Our results suggest shared selection objectives and genetic architectures across swine populations. Identified polygenic selection highlights loci important to swine production.

For Zoom information, please contact Robert Sanders (sandersrl@missouri.edu).