2019
DOI: 10.3389/fgene.2019.00036
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Integrative Analysis of Transcriptome and GWAS Data to Identify the Hub Genes Associated With Milk Yield Trait in Buffalo

Abstract: The mammary gland is the production organ in mammals that is of great importance for milk production and quality. However, characterization of the buffalo mammary gland transcriptome and identification of the valuable candidate genes that affect milk production is limited. Here, we performed the differential expressed genes (DEGs) analysis of mammary gland tissue on day 7, 50, 140, and 280 after calving and conducted gene-based genome-wide association studies (GWAS) of milk yield in 935 Mediterranean buffaloes… Show more

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Cited by 61 publications
(47 citation statements)
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“…Integrative multi-omics approaches to data integration are now widely used to explore and dissect the genomic architecture and physiological basis of complex traits in domestic livestock, including network-based methods to integrate functional genomics and GWAS data (Canovas et al 2014;Fang et al 2017;Cai et al 2018;Fang et al 2018;Deng et al 2019;Yan et al 2020). However, to the best of our knowledge, this study is the first that uses network biology to systematically combine transcriptomics data from M. bovis-infected macrophages with GWAS data for M. bovis infection resistance in cattle.…”
Section: Discussionmentioning
confidence: 99%
“…Integrative multi-omics approaches to data integration are now widely used to explore and dissect the genomic architecture and physiological basis of complex traits in domestic livestock, including network-based methods to integrate functional genomics and GWAS data (Canovas et al 2014;Fang et al 2017;Cai et al 2018;Fang et al 2018;Deng et al 2019;Yan et al 2020). However, to the best of our knowledge, this study is the first that uses network biology to systematically combine transcriptomics data from M. bovis-infected macrophages with GWAS data for M. bovis infection resistance in cattle.…”
Section: Discussionmentioning
confidence: 99%
“…Comparative transcriptome analyses facilitate the discovery of differentially expressed genes and microRNAs. For example, Deng et al () performed an integrated analysis of GWAS and transcriptome data of lactating mammary gland tissues of Mediterranean river buffaloes at different lactation stages. Through a weighted gene co‐expression network analysis, they identified a set of 12 hub genes ( BNIPL , TUBA1C , C2CD4B , DCP1B , MAP3K5 , PDCD11 , SRGAP1 , GDPD5 , BARX2 , SCARA3 , CTU2 and RPL27A ) involved in several pathways related to milk production.…”
Section: Introductionmentioning
confidence: 99%
“…Genome-wide gene expression data from thousands of studies have been accumulating and made available through public repositories such as the Gene Expression Omnibus (GEO; Edgar et al, 2002). Recently, GWAS results have been interpreted by interrogating significant SNP for associations with gene expression data in livestock (Ballester et al, 2017;Fang et al, 2017;Kommadath et al, 2017;Cai et al, 2018;Deng et al, 2019). These studies have integrated GWAS and gene expression data post-GWAS.…”
Section: Introductionmentioning
confidence: 99%