Sequence-based genome-wide association study of individual milk mid-infrared wavenumbers in mixed-breed dairy cattle

Fourier-transform mid-infrared (FT-MIR) spectroscopy provides a
high-throughput and inexpensive method for predicting milk composition and
other novel traits from milk samples. Whilst there have been many
genome-wide association studies (GWAS) conducted on FT-MIR predicted
traits, there have been few GWAS for individual FT-MIR wavenumbers. Here
we examine associations between genomic regions and individual FT-MIR
wavenumber phenotypes within a population of 38,085 mixed-breed New
Zealand dairy cattle with imputed whole-genome sequence. GWAS were
conducted for each of 895 individual FT-MIR wavenumber phenotypes and
three FT-MIR predicted milk composition traits, and gene annotation and
mammary tissue gene expression datasets were employed to identify
candidate causative genes and variants. This resulted in the
identification of 38 co-locating, co-segregating expression QTL (eQTL),
and 31 protein-sequence mutations for FT-MIR wavenumber phenotypes, the
latter including a null mutation in ABO that has a potential role in
changing milk oligosaccharide profiles. For the candidate causative genes
implicated in these analyses, the strength of association between relevant
loci and each wavenumber across the mid-infrared spectrum revealed shared
association patterns for groups of genomically-distant loci, highlighting
clusters of loci linked through their biological roles in lactation and
their presumed impacts on the chemical composition of milk.