Abstract
BackgroundThe aim of this study was to use transcriptome RNA-Seq data from longissimus thoracis muscle of uncastrated Nelore males to identify hub genes based on co-expression network obtained from differentially expressed genes (DEGs) associated with intramuscular fat content.ResultsA total of 30 transcriptomics datasets (RNA-Seq) obtained from longissimus thoracis muscle were selected based on the phenotypic value of divergent intramuscular fat content: 15 with the highest intramuscular fat content (HIF) and 15 with the lowest intramuscular fat content (LIF). The transcriptomics datasets were aligned with a reference genome and 65 differentially expressed genes (DEGs) were identified, including 21 upregulated and 44 downregulated genes in HIF animals. The normalized count data from DEGs was then used for co-expression network construction. From the co-expression network, four modules were identified. The topological properties of the network were analyzed; those genes engaging in the most interactions (maximal clique centrality method) with other DEGs were predicted to be hub genes (PDE4D, KLHL30 and IL1RAP), which consequently may play a role in cellular and/or systemic lipid biology in Nelore cattle. Top modules screened from the gene co-expression network were identify. The two candidate modules had clear associated biological pathways related to fat development, cell adhesion, and muscle differentiation, immune system, among others. The hub genes belonged in top modules and were downregulated in HIF animals. PDE4D and IL1RAP have known effects on lipid metabolism and the immune system through the regulation of cAMP signaling. Given that cAMP is known to play a role in lipid systems, PDE4D and IL1RAP downregulation may contribute to increased levels of intracellular cAMP and thus may have effects on IF content differences in Nelore cattle. KLHL30 may have effects on muscle metabolism. Klhl protein families play a role in protein degradation. However, the downregulation of this gene and its role in lipid metabolism has not yet been clarified.ConclusionsThe results reported in this study indicate candidate genes and molecular mechanisms involved in IF content difference in Nelore cattle.
Highlights
The aim of this study was to use transcriptome RNA-Seq data from longissimus thoracis muscle of uncastrated Nelore males to identify hub genes based on co-expression network obtained from differentially expressed genes (DEGs) associated with intramuscular fat content
Our results show that muscle cells of Nelore cattle phenotypically divergent for Intramuscular fat (IF) expressed genes related to lipid and muscle metabolism, as well as genes related to the immune system
Through gene co-expression network analysis, we identify modules and hub genes, which are the main regulators of other DEGs identified and may play a role in Nelore cattle’s cellular or systemic lipid biology
Summary
The aim of this study was to use transcriptome RNA-Seq data from longissimus thoracis muscle of uncastrated Nelore males to identify hub genes based on co-expression network obtained from differentially expressed genes (DEGs) associated with intramuscular fat content. Santos Silva et al BMC Genomics (2019) 20:520 phenotypes [5, 6] This technology has been used to identify differentially expressed genes (DEGs) in muscle tissue of Nelore cattle divergent to different meat traits, as such: tenderness [7], fatty acid composition [8], intramuscular fat content (measured by marbling scores) [9], residual feed intake [10] and iron content [11]. Using RNA-seq (mRNA sequencing) data, Cesar et al [9] identified differentially expressed genes (DEGs) in muscle tissue and elucidated some of the molecular mechanisms involved in the lipid metabolism in Nelore steers breeding herd (castrated males, belonging a experimental population) genetically divergent for intramuscular fat (measured by marbling scores). Understanding the biological and functional mechanisms that regulate IF content in uncastrated Nelore cattle is a compelling question in meat science, since this knowledge are still unclear
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