Genes Involved in Feed Efficiency Identified in a Meta-Analysis of Rumen Tissue from Two Populations of Beef Steers

A review of the role of transcription factors in regulating adipogenesis and lipogenesis in beef cattle

In the past few decades, genomic selection and other refined strategies have been used to increase the growth rate and lean meat production of beef cattle. Nevertheless, the fast growth rates of cattle breeds are often accompanied by a reduction in intramuscular fat (IMF) deposition, impairing meat quality. Transcription factors play vital roles in regulating adipogenesis and lipogenesis in beef cattle. Meanwhile, understanding the role of transcription factors in regulating adipogenesis and lipogenesis in beef cattle has gained significant attention to increase IMF deposition and meat quality. Therefore, the aim of this paper was to provide a comprehensive summary and valuable insight into the complex role of transcription factors in adipogenesis and lipogenesis in beef cattle. This review summarizes the contemporary studies in transcription factors in adipogenesis and lipogenesis, genome-wide analysis of transcription factors, epigenetic regulation of transcription factors, nutritional regulation of transcription factors, metabolic signalling pathways, functional genomics methods, transcriptomic profiling of adipose tissues, transcription factors and meat quality and comparative genomics with other livestock species. In conclusion, transcription factors play a crucial role in promoting adipocyte development and fatty acid biosynthesis in beef cattle. They control adipose tissue formation and metabolism, thereby improving meat quality and maintaining metabolic balance. Understanding the processes by which these transcription factors regulate adipose tissue deposition and lipid metabolism will simplify the development of marbling or IMF composition in beef cattle.

Transcriptome analysis of mRNA and miRNA in the development of LeiZhou goat muscles

The progression of muscle development is a pivotal aspect of animal ontogenesis, where miRNA and mRNA exert substantial influence as prominent players. It is important to understand the molecular mechanisms involved in skeletal muscle development to enhance the quality and yield of meat produced by Leizhou goats. We employed RNA sequencing (RNA-SEQ) technology to generate miRNA-mRNA profiles in Leizhou goats, capturing their developmental progression at 0, 3, and 6 months of age. A total of 977 mRNAs and 174 miRNAs were found to be differentially expressed based on our analysis. Metabolic pathways, calcium signaling pathways, and amino acid synthesis and metabolism were found to be significantly enriched among the differentially expressed mRNA in the enrichment analysis. Meanwhile, we found that among these differentially expressed mRNA, some may be related to muscle development, such as MYL10, RYR3, and CSRP3. Additionally,, we identified five muscle-specific miRNAs (miR-127-3p, miR-133a-3p, miR-193b-3p, miR-365-3p, and miR-381) that consistently exhibited high expression levels across all three stages. These miRNAs work with their target genes (FHL3, SESN1, PACSIN3, LMCD1) to regulate muscle development. Taken together, our findings suggest that several miRNAs and mRNAs are involved in regulating muscle development and cell growth in goats. By uncovering the molecular mechanisms involved in muscle growth and development, these findings contribute valuable knowledge that can inform breeding strategies aimed at enhancing meat yield and quality in Leizhou goats.

Recent developments and future directions in meta-analysis of differential gene expression in livestock RNA-Seq

Decreases in the costs of high-throughput sequencing technologies have led to continually increasing numbers of livestock RNA-Seq studies in the last decade. Although the number of studies has increased dramatically, most livestock RNA-Seq experiments are limited by cost to a small number of biological replicates. Meta-analysis procedures can be used to integrate and jointly analyze data from multiple independent studies. Meta-analyses increase the sample size, which in turn increase both statistical power and robustness of the results. In this work, we discuss cutting edge approaches to combining results from multiple independent RNA-Seq studies to improve livestock transcriptomics research. We review currently published RNA-Seq meta-analyses in livestock, describe many of the key issues specific to RNA-Seq meta-analysis in livestock species, and discuss future perspectives.