Data from: Genomic loci involved in sensing environmental cues and metabolism affect seasonal coat shedding in Bos taurus and Bos indicus cattle
Data files
Jan 13, 2023 version files 3.18 GB
Abstract
Seasonal shedding of winter hair at the start of summer is well-studied in wild and domesticated populations. However, the genetic influences on this trait and their interactions are poorly understood. We use data from 13,364 cattle with 36,899 repeated phenotypes to investigate the relationship between hair shedding and environmental variables, single nucleotide polymorphisms, and their interactions to understand quantitative differences in seasonal shedding. Using de-regressed estimated breeding values from a repeated records model in a genome-wide association analysis (GWAA) and meta-analysis of year-specific GWAA gave remarkably similar results. These GWAA identified hundreds of variants associated with seasonal hair shedding. There were especially strong associations on chromosomes 5 and 23. Genotype-by-environment interaction GWAA identified 1,040 day-length-by-genotype interaction associations and 17 apparent temperature-by-genotype interaction associations with hair shedding, highlighting the importance of day length on hair shedding. Accurate genomic predictions of hair shedding were created for the entire dataset, Angus, Hereford, Brangus, and multi-breed datasets. Loci related to metabolism and light-sensing have a large influence on seasonal hair shedding. This is one of the largest genetic analyses of a phenological trait and provides insight for both agriculture production and basic science.
Methods
Hair-shedding phenotypes were collected by farmers and ranchers across the United States, but mainly within the Southeast and Midwest. Hair shedding is a 1 to 5 scoring system, reflecting the amount of winter hair that has been shed in the late spring and early summer. Data also includes meta-data used for additional analyses.
Genotypes were generated on various Neogen SNP arrays. These were imputed to a set of 846,153 SNPs.
Usage notes
Phenotypes and meta-data are in CSV format, and can be opened with various software.
Genotypes are in VCF format and can be opened/processed in VCFtools, PLINK, and other genotype analysis software.