Reference # 30644110 Details

Authors:Duarte D A S, Newbold C J, Detmann E, Silva F F, Freitas P H F, Veroneze R, Duarte M S (Contact:
Affiliation:Department of Animal Science, Universidade Federal de Viçosa, Viçosa, 36570-000, Minas Gerais, Brazil
Title:Genome-wide association studies pathway-based meta-analysis for residual feed intake in beef cattle
Journal:Animal Genetics, 2019, 50(2):2 DOI: 10.1111/age.12761
Genome-wide association studies (GWASes) have been performed to search for genomic regions associated with residual feed intake (RFI); however inconsistent results have been obtained. A meta-analysis may improve these results by decreasing the false-positive rate. Additionally, pathway analysis is a powerful tool that complements GWASes, as it enables identification of gene sets involved in the same pathway that explain the studied phenotype. Because there are no reports on GWAS pathways-based meta-analyses for RFI in beef cattle, we used several GWAS results to search for significant pathways that may explain the genetic mechanism underlying this trait. We used an efficient permutation hypothesis test that takes into account the linkage disequilibrium patterns between SNPs and the functional feasibility of the identified genes over the whole genome. One significant pathway (valine, leucine and isoleucine degradation) related to RFI was found. The three genes in this pathway-methylcrotonoyl-CoA carboxylase 1 (MCCC1), aldehyde oxidase 1 (AOX1) and propionyl-CoA carboxylase alpha subunit (PCCA)-were found in three different studies. This same pathway was also reported in a transcriptome analysis from two cattle populations divergently selected for high and low RFI. We conclude that a GWAS pathway-based meta-analysis can be an appropriate method to uncover biological insights into RFI by combining useful information from different studies.
Links:   PubMed | List QTL |Data locator:  RbEq9K9LtC 
Combined analysis: PMID:18791150 // Combined analysis: PMID:18318789 // Combined analysis: PMID:24476087 // Combined analysis: PMID:22497295 // Combined analysis: PMID:22479267 // Combined analysis: PMID:17709790 // Combined analysis: PMID:22497335 // Combined analysis: PMID:23736061 // Combined analysis: PMID:19749024 // Combined analysis: PMID:24517472 //

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