Multi-population GWAS and enrichment analyses reveal novel genomic regions and promising candidate genes underlying bovine milk fatty acid composition

G Gebreyesus,D Sun,H J F Van Valenberg,A J Buitenhuis,N A Poulsen,M H P W Visker,H Bovenhuis,Q Zhang

doi:10.1186/s12864-019-5573-9

G Gebreyesus, D Sun + Show 6 more

Open Access

https://doi.org/10.1186/s12864-019-5573-9

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Abstract

BackgroundThe power of genome-wide association studies (GWAS) is often limited by the sample size available for the analysis. Milk fatty acid (FA) traits are scarcely recorded due to expensive and time-consuming analytical techniques. Combining multi-population datasets can enhance the power of GWAS enabling detection of genomic region explaining medium to low proportions of the genetic variation. GWAS often detect broader genomic regions containing several positional candidate genes making it difficult to untangle the causative candidates. Post-GWAS analyses with data on pathways, ontology and tissue-specific gene expression status might allow prioritization among positional candidate genes.ResultsMulti-population GWAS for 16 FA traits quantified using gas chromatography (GC) in sample populations of the Chinese, Danish and Dutch Holstein with high-density (HD) genotypes detects 56 genomic regions significantly associated to at least one of the studied FAs; some of which have not been previously reported. Pathways and gene ontology (GO) analyses suggest promising candidate genes on the novel regions including OSBPL6 and AGPS on Bos taurus autosome (BTA) 2, PRLH on BTA 3, SLC51B on BTA 10, ABCG5/8 on BTA 11 and ALG5 on BTA 12. Novel genes in previously known regions, such as FABP4 on BTA 14, APOA1/5/7 on BTA 15 and MGST2 on BTA 17, are also linked to important FA metabolic processes.ConclusionIntegration of multi-population GWAS and enrichment analyses enabled detection of several novel genomic regions, explaining relatively smaller fractions of the genetic variation, and revealed highly likely candidate genes underlying the effects. Detection of such regions and candidate genes will be crucial in understanding the complex genetic control of FA metabolism. The findings can also be used to augment genomic prediction models with regions collectively capturing most of the genetic variation in the milk FA traits.

Highlights

The power of genome-wide association studies (GWAS) is often limited by the sample size available for the analysis
Of the studied fatty acid (FA), C18:3n3 and CLA occurred at concentrations less than 1% of total fat in the milk samples
Multi-population GWAS for gas chromatography (GC)-quantified FA traits resulted in the detection of 56 genomic regions significantly associated to at least one of the studied FAs, including novel regions explaining relatively smaller fractions of the genetic variation

Summary

Introduction

The power of genome-wide association studies (GWAS) is often limited by the sample size available for the analysis. FAs in milk can originate either through direct transport from the rumen to the mammary gland via the blood, or Gebreyesus et al BMC Genomics (2019) 20:178 reported for the fat composition of milk [5, 6]. Part of this genetic variation is attributed to polymorphisms in genes with major effects such as DGAT1 and SCD1 [7]. Detection of additional genomic regions requires availability of larger sample size and high-density markers. GC analysis, the current method of choice to quantify milk FA, requires expensive equipment and is time-consuming, limiting measurement of the traits to experimental scale

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