Meta-analysis of sequence-based association studies across three cattle breeds reveals 25 QTL for fat and protein percentages in milk at nucleotide resolution

Abstract

Background: Genotyping and whole-genome sequencing data have been generated for hundreds of thousands of cattle. International consortia used these data to compile imputation reference panels that facilitate the imputation of sequence variant genotypes for animals that have been genotyped using dense microarrays. Association studies with imputed sequence variant genotypes allow for the characterization of quantitative trait loci (QTL) at nucleotide resolution particularly when individuals from several breeds are included in the mapping populations.

Results: We imputed genotypes for 28 million sequence variants in 17,229 cattle of the Braunvieh, Fleckvieh and Holstein breeds in order to compile large mapping populations that provide high power to identify QTL for milk production traits. Association tests between imputed sequence variant genotypes and fat and protein percentages in milk uncovered between six and thirteen QTL (P < 1e-8) per breed. Eight of the detected QTL were significant in more than one breed. We combined the results across breeds using meta-analysis and identified a total of 25 QTL including six that were not significant in the within-breed association studies. Two missense mutations in the ABCG2 (p.Y581S, rs43702337, P = 4.3e-34) and GHR (p.F279Y, rs385640152, P = 1.6e-74) genes were the top variants at QTL on chromosomes 6 and 20. Another known causal missense mutation in the DGAT1 gene (p.A232K, rs109326954, P = 8.4e-1436) was the second top variant at a QTL on chromosome 14 but its allelic substitution effects were inconsistent across breeds. It turned out that the conflicting allelic substitution effects resulted from flaws in the imputed genotypes due to the use of a multi-breed reference population for genotype imputation.

Conclusions: Many QTL for milk production traits segregate across breeds and across-breed meta-analysis has greater power to detect such QTL than within-breed association testing. Association testing between imputed sequence variant genotypes and phenotypes of interest facilitates identifying causal mutations provided the accuracy of imputation is high. However, true causal mutations may remain undetected when the imputed sequence variant genotypes contain flaws. It is highly recommended to validate the effect of known causal variants in order to assess the ability to detect true causal mutations in association studies with imputed sequence variants.

Keywords: Cattle; Dairy traits; Meta-analysis; Qtl; Sequence imputation.

Fig. 1

Detection of QTL for dairy traits in three cattle breeds. (a-f) Composite manhattan and corresponding quantile-quantile (QQ) plots showing the association of 17,318,499, 19,021,606 and 18,063,587 imputed sequence variants, respectively, with FP and PP in HOL (a, d), FV (b, e) and BV (c, f). The composite manhattan plots summarize the results for FP and PP, i.e., each dot shows the more significant P value that was observed across both traits. Red colours represent sequence variants with P values less than 1e-8. The y-axis of the manhattan and QQ plots is truncated at –log10(1e-40) and –log10(1e-10), respectively

Fig. 2

Effect of 31 QTL on fat and protein percentages in milk. Allelic substitution effects of six, thirteen and twelve QTL, respectively, that were detected in HOL (grey), FV (green) and BV (blue) cattle. The allelic substitution effects of the top variants were divided by phenotypic standard deviations to standardize QTL effects across breeds

Fig. 3

Meta-analysis of fat and protein percentages in milk across three cattle breeds. (a) Composite manhattan plot that shows the association of 26,473,121 imputed sequence variants with FP and PP in the meta-analysis. The composite manhattan plot summarizes the results of the meta-analyses, i.e., each dot shows the more significant P value that was observed across both traits. Red colours represent sequence variants with P values less than 1e-8. The y-axis is truncated at –log10(1e-40). (b) Quantile-quantile plot of the meta-analyses. Grey and cyan colour represent P values of 26,473,121 imputed sequence variants for FP and PP, respectively. The y-axis is truncated at –log10(1e-10). (c) Overview of 25 QTL that were significant at P < 1e-8 in the meta-analysis and within-breed association studies. Filled squares indicate that QTL were significant in the respective analysis. The labels at the x-axis represent the positon of the top variant at each QTL. (d) Allelic substitution effects of 25 OTL on FP and PP. The QTL effects are given in phenotypic standard deviations. Bold type indicates three causal missense mutations in the ABCG2, DGAT1 and GHR genes