Muscle transcriptome analysis reveals genes and metabolic pathways related to mineral concentration in Bos indicus

Abstract

Mineral content affects the biological processes underlying beef quality. Muscle mineral concentration depends not only on intake-outtake balance and muscle type, but also on age, environment, breed, and genetic factors. To unveil the genetic factors involved in muscle mineral concentration, we applied a pairwise differential gene expression analysis in groups of Nelore steers genetically divergent for nine different mineral concentrations. Here, based on significant expression differences between contrasting groups, we presented candidate genes for the genetic regulation of mineral concentration in muscle. Functional enrichment and protein-protein interaction network analyses were carried out to search for gene regulatory processes concerning each mineral. The core genetic regulation for all minerals studied, except Zn, seems to rest on interactions between components of the extracellular matrix. Regulation of adipogenesis-related pathways was also significant in our results. Antagonistic patterns of gene expression for fatty acid metabolism-related genes may explain the Cu and Zn antagonistic effect on fatty acid accumulation. Our results shed light on the role of these minerals on cell function.

Genetic regulators of mineral amount in Nelore cattle muscle predicted by a new co-expression and regulatory impact factor approach

“…expressed genes (DEGs) for contrasting mineral amount sample groups 9,10 , transcription factors (TF) 17 and genes affected by Expression Quantitative Trait Locus (eQTLs) 18 . This information, along with genes with significant RIFs, was used as node attributes and included in the network analyses ( Fig.…”

“…Besides, by the inclusion of correlated genes and pathways from the Reactome database 19 , we identified new pathways for K, related to protein metabolism, as well as for Ca, Cu, S and Fe, related to immune response, and for S related to signalling. All the pathways enriched for S are new, when compared with our previous work 9 . A list of the pathways enriched for each mineral, considering both the ones detected with the inclusion of correlated genes expressions and the ones from the previous work 9,10 , is shown in Table 4.…”

“…In this analysis we estimated the correlations between the expression of a gene or miRNA, which was found to be correlated to a mineral in the present work, and DEGs previously identified for the same mineral 9,10 . This analysis was carried out for each mineral separately and included the same genes with regulatory potential as in the previous section (DEGs 9,10 , TFs 17 , genes affected by eQTLs 18 and genes with significant RIF). To identify elements with regulatory potential, we then selected the genes that were network hubs or that were significant according to RIF (see methods).…”

“…As we included the differentially expressed genes regarding mineral amount previously detected in the same population 9,10 , most of the over-represented pathways identified correspond to the previously detected pathways. Besides, by the inclusion of correlated genes and pathways from the Reactome database 19 , we identified new pathways for K, related to protein metabolism, as well as for Ca, Cu, S and Fe, related to immune response, and for S related to signalling.…”

“…A differential expression approach detected genes and pathways underlying mineral amount in Nelore cattle by comparing extremes of the experimental population used herein 9,10 . However, as mineral amount traits have a continuous distribution trend, it is necessary to study the whole population in order to verify these relationships and infer regulatory modes of action.…”