Genetics Selection Evolution (Aug 2021)

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

  • Huimin Kang,
  • Di Zhao,
  • Hai Xiang,
  • Jing Li,
  • Guiping Zhao,
  • Hua Li

DOI
https://doi.org/10.1186/s12711-021-00656-9
Journal volume & issue
Vol. 53, no. 1
pp. 1 – 23

Abstract

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Abstract 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.