La Trobe
1177237_Tiplady,KM_2021.pdf (2.8 MB)

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

Download (2.8 MB)
journal contribution
posted on 17.08.2021, 22:17 by KM Tiplady, TJ Lopdell, E Reynolds, RG Sherlock, M Keehan, TJ Johnson, Jennie PryceJennie Pryce, SR Davis, RJ Spelman, BL Harris, DJ Garrick, MD Littlejohn
Background: 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. While 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. Using imputed whole-genome sequence for 38,085 mixed-breed New Zealand dairy cattle, we conducted GWAS on 895 individual FT-MIR wavenumber phenotypes, and assessed the value of these direct phenotypes for identifying candidate causal genes and variants, and improving our understanding of the physico-chemical properties of milk. Results: Separate GWAS conducted for each of 895 individual FT-MIR wavenumber phenotypes, identified 450 1-Mbp genomic regions with significant FT-MIR wavenumber QTL, compared to 246 1-Mbp genomic regions with QTL identified for FT-MIR predicted milk composition traits. Use of mammary RNA-seq data and gene annotation information identified 38 co-localized and co-segregating expression QTL (eQTL), and 31 protein-sequence mutations for FT-MIR wavenumber phenotypes, the latter including a null mutation in the ABO gene that has a potential role in changing milk oligosaccharide profiles. For the candidate causative genes implicated in these analyses, we examined the strength of association between relevant loci and each wavenumber across the mid-infrared spectrum. This 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. Conclusions: This study demonstrates the utility of FT-MIR wavenumber phenotypes for improving our understanding of milk composition, presenting a larger number of QTL and putative causative genes and variants than found from FT-MIR predicted composition traits. Examining patterns of significance across the mid-infrared spectrum for loci of interest further highlighted commonalities of association, which likely reflects the physico-chemical properties of milk constituents.

Funding

This research was co-funded by Livestock Improvement Corporation (LIC; Hamilton, New Zealand) and the New Zealand Ministry for Primary Industries, within the Resilient Dairy Programme through Sustainable Food & Fibre Futures (Funding No: PGP06-17006). External funders had no role in the analysis or interpretation of the data, or in writing the manuscript.

History

Publication Date

20/07/2021

Journal

Genetics Selection Evolution

Volume

53

Issue

1

Article Number

62

Pagination

(p.1-24)

Publisher

BioMed Central

ISSN

0999-193X

Rights Statement

The Author reserves all moral rights over the deposited text and must be credited if any re-use occurs. Documents deposited in OPAL are the Open Access versions of outputs published elsewhere. Changes resulting from the publishing process may therefore not be reflected in this document. The final published version may be obtained via the publisher’s DOI. Please note that additional copyright and access restrictions may apply to the published version.