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Large-scale transcriptome sequencing in broiler chickens to identify candidate genes for breast muscle weight and intramuscular fat content

BACKGROUND: In broiler production, breast muscle weight and intramuscular fat (IMF) content are important economic traits. Understanding the genetic mechanisms that underlie these traits is essential to implement effective genetic improvement programs. To date, genome-wide association studies (GWAS)...

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Autores principales: Kang, Huimin, Zhao, Di, Xiang, Hai, Li, Jing, Zhao, Guiping, Li, Hua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8369645/
https://www.ncbi.nlm.nih.gov/pubmed/34399688
http://dx.doi.org/10.1186/s12711-021-00656-9
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author Kang, Huimin
Zhao, Di
Xiang, Hai
Li, Jing
Zhao, Guiping
Li, Hua
author_facet Kang, Huimin
Zhao, Di
Xiang, Hai
Li, Jing
Zhao, Guiping
Li, Hua
author_sort Kang, Huimin
collection PubMed
description BACKGROUND: In broiler production, breast muscle weight and intramuscular fat (IMF) content are important economic traits. Understanding the genetic mechanisms that underlie these traits is essential to implement effective genetic improvement programs. To date, genome-wide association studies (GWAS) and gene expression analyses have been performed to identify candidate genes for these traits. However, GWAS mainly detect associations at the DNA level, while differential expression analyses usually have low power because they are typically based on small sample sizes. To detect candidate genes for breast muscle weight and IMF contents (intramuscular fat percentage and relative content of triglycerides, cholesterol, and phospholipids), we performed association analyses based on breast muscle transcriptomic data on approximately 400 Tiannong partridge chickens at slaughter age. RESULTS: First, by performing an extensive simulation study, we evaluated the statistical properties of association analyses of gene expression levels and traits based on the linear mixed model (LMM) and three regularized linear regression models, i.e., least absolute shrinkage and selection operator (LASSO), ridge regression (RR), and elastic net (EN). The results show that LMM, LASSO and EN with tuning parameters that are determined based on the one standard error rule exhibited the lowest type I error rates. Using results from all three models, we detected 43 candidate genes with expression levels that were associated with breast muscle weight. In addition, candidate genes were detected for intramuscular fat percentage (1), triglyceride content (2), cholesterol content (1), and phospholipid content (1). Many of the identified genes have been demonstrated to play roles in the development and metabolism of skeletal muscle or adipocyte. Moreover, weighted gene co-expression network analyses revealed that many candidate genes were harbored by gene co-expression modules, which were also significantly correlated with the traits of interest. The results of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses indicated that these modules are involved in muscle development and contraction, and in lipid metabolism. CONCLUSIONS: Our study provides valuable insight into the transcriptomic bases of breast muscle weight and IMF contents in Chinese indigenous yellow broilers. Our findings could be useful for the genetic improvement of these traits in broiler chickens. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12711-021-00656-9.
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spelling pubmed-83696452021-08-18 Large-scale transcriptome sequencing in broiler chickens to identify candidate genes for breast muscle weight and intramuscular fat content Kang, Huimin Zhao, Di Xiang, Hai Li, Jing Zhao, Guiping Li, Hua Genet Sel Evol Research Article BACKGROUND: In broiler production, breast muscle weight and intramuscular fat (IMF) content are important economic traits. Understanding the genetic mechanisms that underlie these traits is essential to implement effective genetic improvement programs. To date, genome-wide association studies (GWAS) and gene expression analyses have been performed to identify candidate genes for these traits. However, GWAS mainly detect associations at the DNA level, while differential expression analyses usually have low power because they are typically based on small sample sizes. To detect candidate genes for breast muscle weight and IMF contents (intramuscular fat percentage and relative content of triglycerides, cholesterol, and phospholipids), we performed association analyses based on breast muscle transcriptomic data on approximately 400 Tiannong partridge chickens at slaughter age. RESULTS: First, by performing an extensive simulation study, we evaluated the statistical properties of association analyses of gene expression levels and traits based on the linear mixed model (LMM) and three regularized linear regression models, i.e., least absolute shrinkage and selection operator (LASSO), ridge regression (RR), and elastic net (EN). The results show that LMM, LASSO and EN with tuning parameters that are determined based on the one standard error rule exhibited the lowest type I error rates. Using results from all three models, we detected 43 candidate genes with expression levels that were associated with breast muscle weight. In addition, candidate genes were detected for intramuscular fat percentage (1), triglyceride content (2), cholesterol content (1), and phospholipid content (1). Many of the identified genes have been demonstrated to play roles in the development and metabolism of skeletal muscle or adipocyte. Moreover, weighted gene co-expression network analyses revealed that many candidate genes were harbored by gene co-expression modules, which were also significantly correlated with the traits of interest. The results of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses indicated that these modules are involved in muscle development and contraction, and in lipid metabolism. CONCLUSIONS: Our study provides valuable insight into the transcriptomic bases of breast muscle weight and IMF contents in Chinese indigenous yellow broilers. Our findings could be useful for the genetic improvement of these traits in broiler chickens. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12711-021-00656-9. BioMed Central 2021-08-16 /pmc/articles/PMC8369645/ /pubmed/34399688 http://dx.doi.org/10.1186/s12711-021-00656-9 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Kang, Huimin
Zhao, Di
Xiang, Hai
Li, Jing
Zhao, Guiping
Li, Hua
Large-scale transcriptome sequencing in broiler chickens to identify candidate genes for breast muscle weight and intramuscular fat content
title Large-scale transcriptome sequencing in broiler chickens to identify candidate genes for breast muscle weight and intramuscular fat content
title_full Large-scale transcriptome sequencing in broiler chickens to identify candidate genes for breast muscle weight and intramuscular fat content
title_fullStr Large-scale transcriptome sequencing in broiler chickens to identify candidate genes for breast muscle weight and intramuscular fat content
title_full_unstemmed Large-scale transcriptome sequencing in broiler chickens to identify candidate genes for breast muscle weight and intramuscular fat content
title_short Large-scale transcriptome sequencing in broiler chickens to identify candidate genes for breast muscle weight and intramuscular fat content
title_sort large-scale transcriptome sequencing in broiler chickens to identify candidate genes for breast muscle weight and intramuscular fat content
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8369645/
https://www.ncbi.nlm.nih.gov/pubmed/34399688
http://dx.doi.org/10.1186/s12711-021-00656-9
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