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Background  The 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.    Results  Multi-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.    Conclusion  Integration 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.    Electronic supplementary material  The online version of this article (10.1186/s12864-019-5573-9) contains supplementary material, which is available to authorized users.

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