Using whole genome sequence to compare variant callers and breed differences of US sheep

Morgan R Stegemiller; Reid R Redden; David R Notter; Todd Taylor; J Bret Taylor; Noelle E Cockett; Michael P Heaton; Theodore S Kalbfleisch; Brenda M Murdoch

doi:10.3389/fgene.2022.1060882

Using whole genome sequence to compare variant callers and breed differences of US sheep

Front Genet. 2023 Jan 4:13:1060882. doi: 10.3389/fgene.2022.1060882. eCollection 2022.

Authors

Morgan R Stegemiller¹, Reid R Redden², David R Notter³, Todd Taylor⁴, J Bret Taylor⁵, Noelle E Cockett⁶, Michael P Heaton⁷, Theodore S Kalbfleisch⁸, Brenda M Murdoch¹

Affiliations

¹ Department of Animal, Veterinary and Food Sciences, University of Idaho, Moscow, ID, United States.
² Texas A&M AgriLife Research and Extension, Texas A&M University, San Angelo, TX, United States.
³ School of Animal Sciences, Virginia Tech, Blacksburg, VA, United States.
⁴ Department of Animal and Dairy Sciences, University of Wisconsin-Madison, Madison, WI, United States.
⁵ United States Sheep Experiment Station, United States Department of Agriculture, Agricultural Research Service, Dubois, ID, United States.
⁶ Department of Animal, Dairy and Veterinary Sciences, Utah State University, Logan, UT, United States.
⁷ USDA, ARS, U.S. Meat Animal Research Center, Clay Center, NE, United States.
⁸ Gluck Equine Research Center, College of Agriculture, Food, and Environment, University of Kentucky, Lexington, KY, United States.

Abstract

As whole genome sequence (WGS) data sets have become abundant and widely available, so has the need for variant detection and scoring. The aim of this study was to compare the accuracy of commonly used variant calling programs, Freebayes and GATK HaplotypeCaller (GATK-HC), and to use U.S. sheep WGS data sets to identify novel breed-associated SNPs. Sequence data from 145 sheep consisting of 14 U.S. breeds were filtered and biallelic single nucleotide polymorphisms (SNPs) were retained for genotyping analyses. Genotypes from both programs were compared to each other and to genotypes from bead arrays. The SNPs from WGS were compared to the bead array data with breed heterozygosity, principal component analysis and identifying breed associated SNPs to analyze genetic diversity. The average sequence read depth was 2.78 reads greater with 6.11% more SNPs being identified in Freebayes compared to GATK-HC. The genotype concordance of the variant callers to bead array data was 96.0% and 95.5% for Freebayes and GATK-HC, respectively. Genotyping with WGS identified 10.5 million SNPs from all 145 sheep. This resulted in an 8% increase in measured heterozygosity and greater breed separation in the principal component analysis compared to the bead array analysis. There were 1,849 SNPs identified in only the Romanov sheep where all 10 rams were homozygous for one allele and the remaining 135 sheep from 13 breeds were homozygous for the opposite allele. Both variant calling programs had greater than 95% concordance of SNPs with bead array data, and either was suitably accurate for ovine WGS data sets. The use of WGS SNPs improved the resolution of PCA analysis and was critical for identifying Romanov breed-associated SNPs. Subsets of such SNPs could be used to estimate germplasm composition in animals without pedigree information.

Keywords: GATK HaplotypeCaller (HC); freebayes; sheep; variant callers; whole genome sequence.