Using expression data to fine map QTL associated with fertility in dairy cattle

van den Berg, Irene; Chamberlain, Amanda; MacLeod, Iona; Nguyen, Tuan V; Goddard, Mike E; Xiang, Ruidong; Mason, Brett; Meier, Susanne; Phyn, Claire VC; Burke, Chris R; Pryce, Jennie

doi:10.26181/26779363.v1

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Using expression data to fine map QTL associated with fertility in dairy cattle

journal contribution

posted on 2024-08-19, 06:40 authored by Irene van den Berg, Amanda ChamberlainAmanda Chamberlain, Iona MacLeodIona MacLeod, Tuan V Nguyen, Mike E Goddard, Ruidong XiangRuidong Xiang, Brett Mason, Susanne Meier, Claire VC Phyn, Chris R Burke, Jennie PryceJennie Pryce

Background: Female fertility is an important trait in dairy cattle. Identifying putative causal variants associated with fertility may help to improve the accuracy of genomic prediction of fertility. Combining expression data (eQTL) of genes, exons, gene splicing and allele specific expression is a promising approach to fine map QTL to get closer to the causal mutations. Another approach is to identify genomic differences between cows selected for high and low fertility and a selection experiment in New Zealand has created exactly this resource. Our objective was to combine multiple types of expression data, fertility traits and allele frequency in high- (POS) and low-fertility (NEG) cows with a genome-wide association study (GWAS) on calving interval in Australian cows to fine-map QTL associated with fertility in both Australia and New Zealand dairy cattle populations. Results: Variants that were significantly associated with calving interval (CI) were strongly enriched for variants associated with gene, exon, gene splicing and allele-specific expression, indicating that there is substantial overlap between QTL associated with CI and eQTL. We identified 671 genes with significant differential expression between POS and NEG cows, with the largest fold change detected for the CCDC196 gene on chromosome 10. Our results provide numerous candidate genes associated with female fertility in dairy cattle, including GYS2 and TIGAR on chromosome 5 and SYT3 and HSD17B14 on chromosome 18. Multiple QTL regions were located in regions with large numbers of copy number variants (CNV). To identify the causal mutations for these variants, long read sequencing may be useful. Conclusions: Variants that were significantly associated with CI were highly enriched for eQTL. We detected 671 genes that were differentially expressed between POS and NEG cows. Several QTL detected for CI overlapped with eQTL, providing candidate genes for fertility in dairy cattle.

Funding

This research was part of DairyBio, which is jointly funded by Dairy Australia (Melbourne, Australia), Agriculture Victoria (Melbourne, Australia) and The Gardiner Foundation (Melbourne Australia). The NZ study was funded by New Zealand dairy farmers through DairyNZ Inc. (Hamilton, New Zealand) and by the NZ Ministry of Business, Innovation and Employment (Wellington, New Zealand, contract number DRCX1302), and included AgResearch SIFF funding (Hamilton, New Zealand).

History

Publication Date

2024-06-06

Journal

Genetics Selection Evolution

Volume

56

Article Number

42

Pagination

18p.

Publisher

Springer Nature

ISSN

0999-193X

Rights Statement

© Crown 2024. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.