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Using expression data to fine map QTL associated with fertility in dairy cattle.
van den Berg, Irene; Chamberlain, Amanda J; MacLeod, Iona M; Nguyen, Tuan V; Goddard, Mike E; Xiang, Ruidong; Mason, Brett; Meier, Susanne; Phyn, Claire V C; Burke, Chris R; Pryce, Jennie E.
Affiliation
  • van den Berg I; Agriculture Victoria, AgriBio, Centre of AgriBioscience, 5 Ring Road, Bundoora, VIC, 3082, Australia. irene.vandenberg@agriculture.vic.gov.au.
  • Chamberlain AJ; Agriculture Victoria, AgriBio, Centre of AgriBioscience, 5 Ring Road, Bundoora, VIC, 3082, Australia.
  • MacLeod IM; School of Applied Systems Biology, La Trobe University, Bundoora, VIC, 3083, Australia.
  • Nguyen TV; Agriculture Victoria, AgriBio, Centre of AgriBioscience, 5 Ring Road, Bundoora, VIC, 3082, Australia.
  • Goddard ME; Agriculture Victoria, AgriBio, Centre of AgriBioscience, 5 Ring Road, Bundoora, VIC, 3082, Australia.
  • Xiang R; Agriculture Victoria, AgriBio, Centre of AgriBioscience, 5 Ring Road, Bundoora, VIC, 3082, Australia.
  • Mason B; Faculty of Veterinary & Agricultural Science, University of Melbourne, Parkville, VIC, 3010, Australia.
  • Meier S; Agriculture Victoria, AgriBio, Centre of AgriBioscience, 5 Ring Road, Bundoora, VIC, 3082, Australia.
  • Phyn CVC; Faculty of Veterinary & Agricultural Science, University of Melbourne, Parkville, VIC, 3010, Australia.
  • Burke CR; Agriculture Victoria, AgriBio, Centre of AgriBioscience, 5 Ring Road, Bundoora, VIC, 3082, Australia.
  • Pryce JE; DairyNZ Limited, Hamilton, 3240, New Zealand.
Genet Sel Evol ; 56(1): 42, 2024 Jun 06.
Article in En | MEDLINE | ID: mdl-38844868
ABSTRACT

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.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Quantitative Trait Loci / Genome-Wide Association Study / Fertility Limits: Animals Language: En Journal: Genet Sel Evol Journal subject: BIOLOGIA / GENETICA Year: 2024 Type: Article Affiliation country: Australia

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Quantitative Trait Loci / Genome-Wide Association Study / Fertility Limits: Animals Language: En Journal: Genet Sel Evol Journal subject: BIOLOGIA / GENETICA Year: 2024 Type: Article Affiliation country: Australia