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Genes & Genomics

, Volume 40, Issue 1, pp 63–75 | Cite as

Deciphering signature of selection affecting beef quality traits in Angus cattle

  • Mengistie Taye
  • Joon Yoon
  • Tadelle Dessie
  • Seoae Cho
  • Sung Jong Oh
  • Hak-Kyo Lee
  • Heebal Kim
Research Article

Abstract

Artificial selection towards a desired phenotype/trait has modified the genomes of livestock dramatically that generated breeds that greatly differ in morphology, production and environmental adaptation traits. Angus cattle are among the famous cattle breeds developed for superior beef quality. This paper aimed at exploring genomic regions under selection in Angus cattle that are associated with meat quality traits and other associated phenotypes. The whole genome of 10 Angus cattle was compared with 11 Hanwoo (A-H) and 9 Jersey (A-J) cattle breeds using a cross-population composite likelihood ratio (XP-CLR) statistical method. The top 1% of the empirical distribution was taken as significant and annotated using UMD3.1. As a result, 255 and 210 genes were revealed under selection from A–H and A–J comparisons, respectively. The WebGestalt gene ontology analysis resulted in sixteen (A–H) and five (A–J) significantly enriched KEGG pathways. Several pathways associated with meat quality traits (insulin signaling, type II diabetes mellitus pathway, focal adhesion pathway, and ECM-receptor interaction), and feeding efficiency (olfactory transduction, tight junction, and metabolic pathways) were enriched. Genes affecting beef quality traits (e.g., FABP3, FTO, DGAT2, ACS, ACAA2, CPE, TNNI1), stature and body size (e.g., PLAG1, LYN, CHCHD7, RPS20), fertility and dystocia (e.g., ESR1, RPS20, PPP2R1A, GHRL, PLAG1), feeding efficiency (e.g., PIK3CD, DNAJC28, DNAJC3, GHRL, PLAG1), coat color (e.g., MC1-R) and genetic disorders (e.g., ITGB6, PLAG1) were found to be under positive selection in Angus cattle. The study identified genes and pathways that are related to meat quality traits and other phenotypes of Angus cattle. The findings in this study, after validation using additional or independent dataset, will provide useful information for the study of Angus cattle in particular and beef cattle in general.

Keywords

Angus cattle Beef quality Feeding efficiency KEGG pathways Signature of selection XP-CLR 

Notes

Acknowledgements

This work was supported by a grant from the Next-Generation BioGreen 21 Program (Project No. PJ01111501), Rural Development Administration, Republic of Korea.

Author contributions

MT conceived and designed the study, analyzed the data, and wrote the paper; JY helped analyzing the data; TD, SC, SJO, HKL and HK designed the project; HK organized and supervised the project.

Compliance with ethical standards

Availability of data and material

All information supporting the results of this manuscript are included within the article and additional files.

Conflict of interest

Mengistie Taye declares that he does not have conflict of interest. Joon Yoon declares that he does not have conflict of interest. Tadelle Dessie declares that he does not have conflict of interest. Seoae Cho declares that she does not have conflict of interest. Sung Jong Oh declares that he does not have conflict of interest. Hak-Kyo Lee declares that he does not have conflict of interest. Heebal Kim declares that he does not have conflict of interest.

Ethical approval

Collection of DNA samples and genomic analysis were performed with the approval by: the Institutional Animal Care and Use Committee of the National Institute of Animal Science (No. NIAS-2014-093) for Angus and Jersey, and the Committee on Ethics of Animal Experiments of the National Institute of Animal Science (Permit Number: NIAS2015-774) for Hanwoo cattle.

Supplementary material

13258_2017_610_MOESM1_ESM.xls (66 kb)
Supplementary material 1 (XLS 66 KB)
13258_2017_610_MOESM2_ESM.docx (26 kb)
Additional file 2: Table S3. Enriched KEGG Pathways overrepresented from WebGestalt gene enrichment analysis for genes identified from Angus vs. Hanwoo, and Angus vs. Jersey comparisons; Table S4. Causative variants identified in candidate gene regions. (DOCX 25 KB)

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Copyright information

© The Genetics Society of Korea and Springer Science+Business Media B.V. 2017

Authors and Affiliations

  1. 1.Department of Agricultural Biotechnology and Research Institute of Agriculture and Life SciencesSeoul National UniversitySeoulRepublic of Korea
  2. 2.College of Agriculture and Environmental SciencesBahir Dar UniversityBahir DarEthiopia
  3. 3.Department of Natural Science, Interdisciplinary Program in BioinformaticsSeoul National UniversitySeoulRepublic of Korea
  4. 4.International Livestock Research Institute (ILRI)Addis AbabaEthiopia
  5. 5.C&K GenomicsSeoulRepublic of Korea
  6. 6.National Institute of Animal Science, RDAWanjuRepublic of Korea
  7. 7.The Animal Molecular Genetics & Breeding Center, Department of Animal BiotechnologyChonbuk National UniversityJeonjuRepublic of Korea
  8. 8.Institute for Biomedical SciencesShinshu UniversityNaganoJapan

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