[논문]Gene Expression Profile in Similar Tissues Using Transcriptome Sequencing Data of Whole-Body Horse Skeletal Muscle

Lee, Ho-Yeon; Kim, Jae-Yoon; Kim, Kyoung Hyoun; Jeong, Seongmun; Cho, Youngbum; Kim, Namshin

doi:10.3390/genes11111359

[해외논문] Gene Expression Profile in Similar Tissues Using Transcriptome Sequencing Data of Whole-Body Horse Skeletal Muscle 원문보기

Genes, v.11 no.11, 2020년, pp.1359 -

Lee, Ho-Yeon (Genome Editing Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Korea) , Kim, Jae-Yoon (hylee@kribb.re.kr (H.-Y.L.)) , Kim, Kyoung Hyoun (jyoon@kribb.re.kr (J.-Y.K.)) , Jeong, Seongmun (kekgoo@gmail.com (K.H.K.)) , Cho, Youngbum (lovemun@kribb.re.kr (S.J.)) , Kim, Namshin (yycho@kribb.re.kr (Y.C.))

Abstract ▼ AI-Helper

Horses have been studied for exercise function rather than food production, unlike most livestock. Therefore, the role and characteristics of tissue landscapes are critically understudied, except for certain muscles used in exercise-related studies. In the present study, we compared RNA-Seq data from 18 Jeju horse skeletal muscles to identify differentially expressed genes (DEGs) between tissues that have similar functions and to characterize these differences. We identified DEGs between different muscles using pairwise differential expression (DE) analyses of tissue transcriptome expression data and classified the samples using the expression values of those genes. Each tissue was largely classified into two groups and their subgroups by k-means clustering, and the DEGs identified in comparison between each group were analyzed by functional/pathway level using gene set enrichment analysis and gene level, confirming the expression of significant genes. As a result of the analysis, the differences in metabolic properties like glycolysis, oxidative phosphorylation, and exercise adaptation of the groups were detected. The results demonstrated that the biochemical and anatomical features of a wide range of muscle tissues in horses could be determined through transcriptome expression analysis, and provided proof-of-concept data demonstrating that RNA-Seq analysis can be used to classify and study in-depth differences between tissues with similar properties.

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