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

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Multi-population GWAS and enrichment analyses reveal novel genomic regions and promising candidate genes underlying bovine milk fatty acid composition. / Gebreyesus, G; Buitenhuis, A J; Poulsen, N A; Visker, M H P W; Zhang, Q; van Valenberg, H J F; Sun, D; Bovenhuis, H.

I: BMC Genomics, Bind 20, 178, 03.2019.

Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avisTidsskriftartikelForskningpeer review

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@article{2f70a7d3a2434a02a704e3bb4eca327e,
title = "Multi-population GWAS and enrichment analyses reveal novel genomic regions and promising candidate genes underlying bovine milk fatty acid composition",
abstract = "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.",
keywords = "Candidate genes, Milk fatty acids, Multi-population GWAS, Pathway analysis, LIPID-METABOLISM, PROLACTIN REGULATION, PROTEIN, DANISH HOLSTEIN, DIETARY-CHOLESTEROL, QUANTITATIVE TRAIT LOCI, STEAROYL-COA DESATURASE, WIDE ASSOCIATION, DAIRY-CATTLE, MAMMARY-GLAND",
author = "G Gebreyesus and Buitenhuis, {A J} and Poulsen, {N A} and Visker, {M H P W} and Q Zhang and {van Valenberg}, {H J F} and D Sun and H Bovenhuis",
year = "2019",
month = "3",
doi = "10.1186/s12864-019-5573-9",
language = "English",
volume = "20",
journal = "B M C Genomics",
issn = "1471-2164",
publisher = "BioMed Central Ltd.",

}

RIS

TY - JOUR

T1 - Multi-population GWAS and enrichment analyses reveal novel genomic regions and promising candidate genes underlying bovine milk fatty acid composition

AU - Gebreyesus, G

AU - Buitenhuis, A J

AU - Poulsen, N A

AU - Visker, M H P W

AU - Zhang, Q

AU - van Valenberg, H J F

AU - Sun, D

AU - Bovenhuis, H

PY - 2019/3

Y1 - 2019/3

N2 - 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.

AB - 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.

KW - Candidate genes

KW - Milk fatty acids

KW - Multi-population GWAS

KW - Pathway analysis

KW - LIPID-METABOLISM

KW - PROLACTIN REGULATION

KW - PROTEIN

KW - DANISH HOLSTEIN

KW - DIETARY-CHOLESTEROL

KW - QUANTITATIVE TRAIT LOCI

KW - STEAROYL-COA DESATURASE

KW - WIDE ASSOCIATION

KW - DAIRY-CATTLE

KW - MAMMARY-GLAND

UR - http://www.scopus.com/inward/record.url?scp=85062562348&partnerID=8YFLogxK

U2 - 10.1186/s12864-019-5573-9

DO - 10.1186/s12864-019-5573-9

M3 - Journal article

VL - 20

JO - B M C Genomics

JF - B M C Genomics

SN - 1471-2164

M1 - 178

ER -