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Home / Equine Research Bank / Genes (Basel) / Gene Expression Profile in Similar Tissues Using Transcripto...
Genes2020; 11(11); 1359; doi: 10.3390/genes11111359

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

Abstract: 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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Publication Date: 2020-11-17 PubMed ID: 33213000PubMed Central: PMC7698552DOI: 10.3390/genes11111359Google Scholar: Lookup
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  • Journal Article
  • Research Support
  • Non-U.S. Gov't

Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

This research aimed to identify different genes expressed in various skeletal muscle tissues in horses using RNA-Seq data, helping to pinpoint their distinct properties linked to metabolism and exercise adaptation.

Objective of the Study

  • This study primarily aimed to understand the unique characteristics and functions of different horse skeletal muscles by identifying differentially expressed genes (DEGs).
  • It used transcriptome sequencing data from 18 skeletal muscles of Jeju horses, a Korean breed known for its strength and endurance.
  • The researchers targeted muscle tissues because, unlike in most livestock where food production is the central focus of study, muscles are the primary area of study in horses, particularly related to exercise function.

Methodology

  • The researchers applied RNA-Seq data analysis on muscles of the horses. RNA-Seq is a technology that utilizes sequencing to reveal the presence and quantity of RNA in a biological sample at a given moment.
  • They performed pairwise differential expression (DE) analyses of tissue transcriptome expression data to identify DEGs between different muscles.
  • Using the expression values of the identified genes, they classified the sampled tissues. The classification was mainly done into two groups and their respective subgroups via k-means clustering.

Results & Findings

  • After comparing and analyzing the DEGs, it was noticed that groups had distinctive metabolic properties, for instance, differences in glycolysis, oxidative phosphorylation, and exercise adaptation.
  • This analysis allowed them to understand the biochemical and anatomical features of a wide range of horse muscle tissues.

Conclusions

  • The study was successful in showing that RNA-Seq analysis could be used to classify and study in-depth differences between tissues with similar properties.
  • The findings emphasized the potential of transcriptome analysis in identifying the unique metabolic and exercise adaptation properties of different muscle tissues, providing a basis for further investigation into muscle functionality in horses and potentially other animals.

Cite This Article

APA
Lee HY, Kim JY, Kim KH, Jeong S, Cho Y, Kim N. (2020). Gene Expression Profile in Similar Tissues Using Transcriptome Sequencing Data of Whole-Body Horse Skeletal Muscle. Genes (Basel), 11(11), 1359. https://doi.org/10.3390/genes11111359

Publication

Genes
ISSN: 2073-4425
NlmUniqueID: 101551097
Country: Switzerland
Language: English
Volume: 11
Issue: 11
PII: 1359

Researcher Affiliations

Lee, Ho-Yeon
  • Genome Editing Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Korea.
  • Department of Bioinformatics, KRIBB School of Bioscience, University of Science and Technology (UST), Daejeon 34141, Korea.
Kim, Jae-Yoon
  • Genome Editing Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Korea.
  • Department of Bioinformatics, KRIBB School of Bioscience, University of Science and Technology (UST), Daejeon 34141, Korea.
Kim, Kyoung Hyoun
  • Genome Editing Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Korea.
  • Department of Bioinformatics, KRIBB School of Bioscience, University of Science and Technology (UST), Daejeon 34141, Korea.
Jeong, Seongmun
  • Genome Editing Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Korea.
Cho, Youngbum
  • Genome Editing Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Korea.
  • Department of Bioinformatics, KRIBB School of Bioscience, University of Science and Technology (UST), Daejeon 34141, Korea.
Kim, Namshin
  • Genome Editing Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Korea.
  • Department of Bioinformatics, KRIBB School of Bioscience, University of Science and Technology (UST), Daejeon 34141, Korea.

MeSH Terms

  • Animals
  • Glycolysis / genetics
  • Horses / genetics
  • Muscle, Skeletal / physiology
  • Oxidative Phosphorylation
  • Transcriptome

Conflict of Interest Statement

The authors declare no conflict of interest.

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