ExAgBov: A public database of annotated variations from hundreds of bovine whole-exome sequencing samples.

Large reference datasets of annotated genetic variations from genome-scale sequencing are essential for interpreting identified variants, their functional impact, and their possible contribution to diseases and traits. However, to date, no such database of annotated variation from broad cattle populations is publicly available. To overcome this gap and advance bovine NGS-driven variant discovery and interpretation, we obtained and analyzed raw data deposited in the SRA public repository. Short reads from 262 whole-exome sequencing samples of Bos Taurus were mapped to the Bos Taurus ARS-UCD1.2 reference genome. The GATK best practice workflow was applied for variant calling. Comprehensive annotation of all recorded variants was done using the Ensembl Variant Effect Predictor (VEP). An in-depth analysis of the population structure revealed the breeds comprising the database. The Exomes Aggregate of Bovine- ExAgBov is a comprehensively annotated dataset of more than 20 million short variants, of which ~2% are located within open reading frames, splice regions, and UTRs, and more than 60,000 variants are predicted to be deleterious.

Comparing BeadChip and WGS Genotyping: Non-Technical Failed Calling Is Attributable to Additional Variation within the Probe Target Sequence.

Microarray-based genomic selection is a central tool to increase the genetic gain of economically significant traits in dairy cattle. Yet, the effectivity of this tool is slightly limited, as estimates based on genotype data only partially explain the observed heritability. In the analysis of the genomes of 17 Israeli Holstein bulls, we compared genotyping accuracy between whole-genome sequencing (WGS) and microarray-based techniques. Using the standard GATK pipeline, the short-variant discovery within sequence reads mapped to the reference genome (ARS-UCD1.2) was compared to the genotypes from Illumina BovineSNP50 BeadChip and to an alternative method, which computationally mimics the hybridization procedure by mapping reads to 50 bp spanning the BeadChip source sequences. The number of mismatches between the BeadChip and WGS genotypes was low (0.2%). However, 17,197 (40% of the informative SNPs) had extra variation within 50 bp of the targeted SNP site, which might interfere with hybridization-based genotyping. Consequently, with respect to genotyping errors, BeadChip varied significantly and systematically from WGS genotyping, introducing null allele-like effects and Mendelian errors (<0.5%), whereas the GATK algorithm of local de novo assembly of haplotypes successfully resolved the genotypes in the extra-variable regions. These findings suggest that the microarray design should avoid polymorphic genomic regions that are prone to extra variation and that WGS data may be used to resolve erroneous genotyping, which may partially explain missing heritability.