Evidence map›Paper›PMID 30841852›Full record

ArticleBMC genomics2019

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

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

Abstract read
In one paragraph

Article in BMC genomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

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0cells of the map it votes in
21citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

21 citing papers in PubMed.

  1. Article
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  11. Genetic polymorphisms ofFrontiers in genetics · 2022
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  13. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

G GebreyesusCenter for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Blichers Allé 20, P.O. Box 50, DK-8830, Tjele, Denmark. grum.gebreyesus@mbg.au.dk.ORCID http://orcid.org/0000-0003-4757-3060
A J BuitenhuisCenter for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Blichers Allé 20, P.O. Box 50, DK-8830, Tjele, Denmark.
N A PoulsenDepartment of Food Science, Aarhus University, Blichers Allé 20, P.O. Box 50, DK-8830, Tjele, Denmark.
M H P W ViskerAnimal Breeding and Genomics, Wageningen University and Research, P.O. Box 338, 6700 AH, Wageningen, the Netherlands.
Q ZhangLaboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
H J F van ValenbergDairy Science and Technology Group, Wageningen University and Research, P.O. Box 17, 6700 AA, Wageningen, the Netherlands.
D SunLaboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
H BovenhuisAnimal Breeding and Genomics, Wageningen University and Research, P.O. Box 338, 6700 AH, Wageningen, the Netherlands.

Funding

Innovationsfonden 0603-00519B
6 · The paper itself

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.

Indexed as

Genome-Wide Association StudyGenomicsAnimalsCattleFatty AcidsGenetic VariationMilkFatty AcidsCandidate genesMilk fatty acidsMulti-population GWASPathway analysis

Identifiers

PMID30841852
PMCPMC6404302

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.