Dataset Information

Genetic support for a quantitative trait nucleotide in the ABCG2 gene affecting milk composition of dairy cattle.

ABSTRACT: Our group has previously identified a quantitative trait locus (QTL) affecting fat and protein percentages on bovine chromosome 6, and refined the QTL position to a 420-kb interval containing six genes. Studies performed in other cattle populations have proposed polymorphisms in two different genes (ABCG2 and OPN) as the underlying functional QTL nucleotide. Due to these conflicting results, we have included these QTNs, together with a large collection of new SNPs produced from PCR sequencing, in a dense marker map spanning the QTL region, and reanalyzed the data using a combined linkage and linkage disequilibrium approach.Our results clearly exclude the OPN SNP (OPN_3907) as causal site for the QTL. Among 91 SNPs included in the study, the ABCG2 SNP (ABCG2_49) is clearly the best QTN candidate. The analyses revealed the presence of only one QTL for the percentage traits in the tested region. This QTL was completely removed by correcting the analysis for ABCG2_49. Concordance between the sires' marker genotypes and segregation status for the QTL was found for ABCG2_49 only. The C allele of ABCG2_49 is found in a marker haplotype that has an extremely negative effect on fat and protein percentages and positive effect on milk yield. Of the 91 SNPs, ABCG2_49 was the only marker in perfect linkage disequilibrium with the QTL.Based on our results, OPN_3907 can be excluded as the polymorphism underlying the QTL. The results of this and other papers strongly suggest the [A/C] mutation in ABCG2_49 as the causal mutation, although the possibility that ABCG2_49 is only a marker in perfect LD with the true mutation can not be completely ruled out.

SUBMITTER: Olsen HG

PROVIDER: S-EPMC1924865 | biostudies-literature | 2007 Jun

REPOSITORIES: biostudies-literature

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Genetic support for a quantitative trait nucleotide in the ABCG2 gene affecting milk composition of dairy cattle.

Olsen Hanne Gro HG Nilsen Heidi H Hayes Ben B Berg Paul R PR Svendsen Morten M Lien Sigbjørn S Meuwissen Theo T

BMC genetics 20070621

<h4>Background</h4>Our group has previously identified a quantitative trait locus (QTL) affecting fat and protein percentages on bovine chromosome 6, and refined the QTL position to a 420-kb interval containing six genes. Studies performed in other cattle populations have proposed polymorphisms in two different genes (ABCG2 and OPN) as the underlying functional QTL nucleotide. Due to these conflicting results, we have included these QTNs, together with a large collection of new SNPs produced fro ...[more]

PMID: 17584938

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Project description:BackgroundGenome-wide association studies (GWAS) were performed at the sequence level to identify candidate mutations that affect the expression of six major milk proteins in Montbéliarde (MON), Normande (NOR), and Holstein (HOL) dairy cattle. Whey protein (α-lactalbumin and β-lactoglobulin) and casein (αs1, αs2, β, and κ) contents were estimated by mid-infrared (MIR) spectrometry, with medium to high accuracy (0.59 ≤ R2 ≤ 0.92), for 848,068 test-day milk samples from 156,660 cows in the first three lactations. Milk composition was evaluated as average test-day measurements adjusted for environmental effects. Next, we genotyped a subset of 8080 cows (2967 MON, 2737 NOR, and 2306 HOL) with the BovineSNP50 Beadchip. For each breed, genotypes were first imputed to high-density (HD) using HD single nucleotide polymorphisms (SNPs) genotypes of 522 MON, 546 NOR, and 776 HOL bulls. The resulting HD SNP genotypes were subsequently imputed to the sequence level using 27 million high-quality sequence variants selected from Run4 of the 1000 Bull Genomes consortium (1147 bulls). Within-breed, multi-breed, and conditional GWAS were performed.ResultsThirty-four distinct genomic regions were identified. Three regions on chromosomes 6, 11, and 20 had very significant effects on milk composition and were shared across the three breeds. Other significant effects, which partially overlapped across breeds, were found on almost all the autosomes. Multi-breed analyses provided a larger number of significant genomic regions with smaller confidence intervals than within-breed analyses. Combinations of within-breed, multi-breed, and conditional analyses led to the identification of putative causative variants in several candidate genes that presented significant protein-protein interactions enrichment, including those with previously described effects on milk composition (SLC37A1, MGST1, ABCG2, CSN1S1, CSN2, CSN1S2, CSN3, PAEP, DGAT1, AGPAT6) and those with effects reported for the first time here (ALPL, ANKH, PICALM).ConclusionsGWAS applied to fine-scale phenotypes, multiple breeds, and whole-genome sequences seems to be effective to identify candidate gene variants. However, although we identified functional links between some candidate genes and milk phenotypes, the causality between candidate variants and milk protein composition remains to be demonstrated. Nevertheless, the identification of potential causative mutations that underlie milk protein composition may have immediate applications for improvements in cheese-making.

Dataset Information

Genetic support for a quantitative trait nucleotide in the ABCG2 gene affecting milk composition of dairy cattle.

Publications

Genetic support for a quantitative trait nucleotide in the ABCG2 gene affecting milk composition of dairy cattle.

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