Abstract
BackgroundThe availability of whole-genome sequence data from key ancestors in bovine populations provides an exhaustive catalogue of polymorphic sites that segregate within and across cattle breeds. Sequence variants identified from the sequenced genome of key ancestors can be imputed into animals that have been genotyped using medium- and high-density genotyping arrays. Association analysis with imputed sequences, particularly when applied to multiple traits simultaneously, is a very powerful approach to detect candidate causal variants that underlie complex phenotypes.ResultsWe used whole-genome sequence data from 157 key ancestors of the German Fleckvieh cattle population to impute 20,561,798 sequence variants into 10,363 animals that had (partly imputed) genotypes based on 634,109 single nucleotide polymorphisms (SNPs). Rare variants were more frequent among the sequence-derived than the array-derived genotypes. Association studies with imputed sequence variants were performed using seven correlated udder conformation traits as response variables. The calculation of an approximate multi-trait test statistic enabled us to detect 12 quantitative trait loci (QTL) (P < 2.97 × 10−9) that affect different morphological features of the mammary gland. Among the tested variants, the most significant associations were found for imputed sequence variants at 11 QTL, whereas the top association signal was observed for an array-derived variant at a QTL on bovine chromosome 14. Seven QTL were associated with multiple phenotypes. Most QTL were located in non-coding regions of the genome but in close proximity of candidate genes that could be involved in mammary gland morphology (SP5, GC, NPFFR2, CRIM1, RXFP2, TBX5, RBM19 and ADAM12).ConclusionsUsing imputed sequence variants in association analyses allows the detection of QTL at maximum resolution. Multi-trait approaches can reveal QTL that are not detected in single-trait association studies. Most QTL for udder conformation traits were located in non-coding regions of the genome, which suggests that mutations in regulatory sequences are the major determinants of variation in mammary gland morphology in cattle.Electronic supplementary materialThe online version of this article (doi:10.1186/s12711-016-0190-4) contains supplementary material, which is available to authorized users.
Highlights
The availability of whole-genome sequence data from key ancestors in bovine populations provides an exhaustive catalogue of polymorphic sites that segregate within and across cattle breeds
Variants from medium- (50 K) and high-density (700 K) single nucleotide polymorphisms (SNPs) arrays were almost uniformly distributed across different minor allele frequency (MAF) classes, whereas the imputed sequence variants were enriched for low-frequency MAF classes (Fig. 1b)
Genes located in the 12 quantitative trait loci (QTL) regions detected in the meta‐analysis To detect positional and functional candidate genes that could be involved in mammary gland morphology, we examined the gene content of 12 QTL regions that were identified in the meta-analysis [See Additional file 3: Figure S3]
Summary
The availability of whole-genome sequence data from key ancestors in bovine populations provides an exhaustive catalogue of polymorphic sites that segregate within and across cattle breeds. Association analysis with imputed sequences, when applied to multiple traits simultaneously, is a very powerful approach to detect candidate causal variants that underlie complex phenotypes. Efficient algorithms have been developed to perform association studies on thousands of individuals that are genotyped at millions of polymorphic sites (e.g., [7, 8]). In cattle, such association studies are generally performed within breeds on a trait-by-trait basis and by testing one variant at a time. An approximate multi-trait test statistic allows to efficiently combine the results of multiple association studies that were performed separately and thereby increases the power to identify trait-associated variants [10]
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