Journal of Animal Breeding and Genomics (J Anim Breed Genom)
Ji Yeong Kim1, Ho Chan Kang1, Cheol Hyun Myung1, Hyun Tae Lim1,2*
1Department of Animal Science, Gyeongsang National University, Jinju 52828, Korea
2Institute of Agriculture and Life Science, Gyeongsang National University, Jinju 52828, Korea
Correspondence to Hyun Tae Lim, E-mail: s_htim@gnu.ac.kr
Volume 8, Number 3, Pages 61-67, September 2024.
Journal of Animal Breeding and Genomics 2024, 8(3), 61-67. https://doi.org/10.12972/jabng.20240302
Received on 03 September, 2024, Revised on 20 September, 2024, Accepted on 20 September, 2024, Published on 30 September, 2024.
Copyright © 2024 Korean Society of Animal Breeding and Genetics.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0).
Setting breeding objectives to enhance carcass traits in Hanwoo is essential for increasing the profitability of the Hanwoo industry and ensuring that consumers receive high-quality meat. Key carcass traits, including carcass weight (CWT), eye muscle area (EMA), back-fat thickness (BFT), and marbling score (MS), are genetically correlated. Understanding the causal relationships among these traits is vital for comprehending the complex biological systems of Hanwoo. This study analyzed data from 392 Hanwoo using a Genome-Wide Association Study (GWAS) to identify genetic variants. These variants were subsequently employed as instrumental variables in a Mendelian Randomization (MR) analysis to infer causality. With CWT as the exposure variable and MS as the outcome variable, the selected instrumental variables were validated for their assumptions through tests for heterogeneity and pleiotropy. The MR analysis revealed that, except for the MR-Egger model, significant positive relationships were observed across all models, indicating that an increase in CWT causally influences an increase in MS, beyond mere genetic correlations. It was confirmed that a 1 kg increase in CWT results in an approximate 0.01-point increase in MS. Thus, this study underscores the importance of utilizing genetic variants identified through GWAS as instrumental variables for inferring causal relationships between CWT and MS via MR analysis. These findings can contribute to developing effective breeding strategies and improve our understanding of the biological mechanisms related to carcass traits.
carcass trait, causal inference, Genome-Wide Association Study, Hanwoo
농촌진흥청(Rural Development Administration) 공동연구사업(과제번호: RS-2021-RD010297)의 지원에 의해 이루어진 것이며, 연구비 지원에 감사드립니다.
No potential conflict of interest relevant to this article is reported.
Alam M, Lee SH, Lee DH, Cho C, Park MN. 2021. Genetic Analysis of Major Carcass Traits of Korean Hanwoo Males Raised for Thirty Months. Animals 11(6):1792. doi:10.3390/ani11061792.
[DOI][PubMed][PMC]
Bertrand JK, Willham RL, Berger PJ. 1983. Beef, dairy and beef× dairy carcass characteristics. Journal of Animal Science 57(6):1440-1448. doi:10.2527/jas1983.5751154x
[DOI]
Bhuiyan MSA, Kim HJ, Lee DH, Lee SH, Cho SH, Yang BS, Kim SD, Lee SH. 2017. Genetic parameters of carcass and meat quality traits in different muscles (longissimus dorsi and semimembranosus) of Hanwoo (Korean cattle), Journal of Animal Science 95(8):359-369. doi:10.2527/jas.2017.1493
[DOI][PubMed]
Bhuiyan MSA, Kim YK, Lee DH, Chung Y, Lee DJ, Kang JM, Lee SH. 2024. Evaluation of non-additive genetic effects on carcass and meat quality traits in Korean Hanwoo cattle using genomic models. Animal 18(5):101152. doi:10.1016/j.animal.2024.101152
[DOI][PubMed]
He C, Zhang M, Li J, Wang Y, Chen L, Qi B, Wen J, Yang J, Lin S, Liu D, Dong Y, Wang L, Wang Q, Chen P. 2022. Novel insights into the consequences of obesity: a phenotype-wide Mendelian randomization study. European Journal of Human Genetics. 30(5):540-546. doi:10.1038/s41431-021-00978-8.
[DOI][PubMed][PMC]
Hemani G, Zheng J, Elsworth B, Wade KH, Haberland V, Baird D, Laurin C, Burgess S, Bowden J, Langdon R et al. 2018. The MR-Base platform supports systematic causal inference across the human phenome. elife 7: e34408. doi:10.7554/eLife.34408
[DOI][PubMed][PMC]
Hoa VB, Song DH, Seol KH, Kang SM, Kim HW, Bae IS, Kim ES, Park YS, Cho SH. 2023. A Comparative Study on the Carcass and Meat Chemical Composition, and Lipid-Metabolism-Related Gene Expression in Korean Hanwoo and Brindle Chikso Cattle. Current Issues in Molecular Biology 45: 3279-3290. doi:10.3390/cimb45040214.
[DOI][PubMed][PMC]
Hwang LD, Davies NM, Warrington NM, Evans DM. 2021. Integrating Family-Based and Mendelian Randomization Designs. Cold Spring Harbor Perspectives in Medicine 11(3):a039503. doi:10.1101/cshperspect.a039503.
[DOI][PubMed][PMC]
Korea Institute of Animal Products Quality Evaluation (KAPE) Statistical Yearbook for Livestock product grade determination in 2023. [(accessed on 27 March 2024)]. Public Notion No. 2024.03.27. Available online: https://www.ekape.or.kr/board/list.do
Moon SS, Hwang HH, Jin SK, Joo ST, Park GB. 2003. Carcass Traits Determining Quality and Yield Grades of Hanwoo Steers. Asian-Australasian Journal of Animal Sciences 16(7): 1049-1054. doi:10.5713/ajas.2003.1049
[DOI]
Naserkheil M, Lee DH, Kong HS, Seong J, Mehrban H. 2021. Estimation of genetic parameters and correlation between yearling ultrasound measurements and carcass traits in Hanwoo cattle. Animals 11(5): 1425. doi:10.3390/ani11051425
[DOI][PubMed][PMC]
Pan S, Liu X, Liu T, Zhao Z, Dai Y, Wang YY, Jia P, Liu F. 2022. Causal Inference of Genetic Variants and Genes in Amyotrophic Lateral Sclerosis. Frontiers in Genetics 13: 917142. doi:10.3389/fgene.2022.917142.
[DOI][PubMed][PMC]
Park B, Choi TJ, Park MN, Oh SH. 2020. Estimation of environmental effects and genetic parameters of carcass traits on Chikso (Korean brindle cattle). Asian-Australasian Journal of Animal Sciences 33(4): 525-530. doi:10.5713/ajas.19.0136.
[DOI][PubMed][PMC]
Picard B, Gagaoua M, Micol D, Cassar-Malek I, Hocquette JF, Terlouw CEM. 2014. Inverse Relationships between Biomarkers and Beef Tenderness According to Contractile and Metabolic Properties of the Muscle. Journal of Agricultural and Food Chemistry 62(40): 9808-9818. doi:10.1021/jf501528s.
[DOI][PubMed]
Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MAR, Bender D, Maller J, Sklar P, de Bakker, PI, Daly MJ, Sham PC. 2007. PLINK: a tool set for whole-genome association and population-based linkage analyses. The American Journal of Human Genetics 81(3):559-575. doi:10.1086/519795.
[DOI][PubMed][PMC]
Tiago B, Tiago LP, Camila UB, Anderson ACA, Roberto C, Luiz ALC, Guilherme JMR, Lucia GA. 2022. Investigating potential causal relationships among carcass and meat quality traits using structural equation model in Nellore cattle. Meat Science 187:108771. doi:10.1016/j.meatsci.2022.108771.
[DOI][PubMed]
Walker VM, Zheng J, Gaunt TR, Smith GD. 2022. Phenotypic causal inference using genome-wide association study data: Mendelian randomization and beyond. Annual review of biomedical data science 5:1-17.
[DOI][PubMed][PMC]
Widmer S, Seefried FR, von Rohr P, Häfliger IM, Spengeler M, Drögemüller C. 2021. A major QTL at the LHCGR/FSHR locus for multiple birth in Holstein cattle. Genetics Selection Evolution 53:57. doi:10.1186/s12711-021-00650-1
[DOI][PubMed][PMC]
Zhou X, Stephens M. 2012. Genome-wide efficient mixed-model analysis for association studies. Nature Genetics 44(7): 821-824. doi:10.1038/ng.2310.
[DOI][PubMed][PMC]