Predicted state of H3K27me3 histone modification in Nellore cattle muscle as an indicator of gene modulation associated with mineral amount and meat quality traits

Abstract

Several factors affect beef quality, with tenderness, the amount of intramuscular fat and the nutritional values some of the attributes used as a criterion of choice by consumers. Despite the previous identification of genes and genomic regions involved with the prementioned traits, the mechanisms of gene regulation affecting these genes are not yet fully known. Therefore, our objective is to predict in silico genes that are discordantly activated, based on the predicted absence of the H3K27me3 hysteric modification, whose presence causes gene silencing. This analysis will be carried out between Longissimus thoracis muscle samples of Nelore steers contrasting for mineral amount and beef quality traits, in order to relate the observed patterns to the phenotypes of interest to breeding. For this, a repressive tendency score related to the predicted absence of H3K27me3 will be calculated for each of the genes expressed, homologous to human genes, in each of the of 113 Nelore samples, using a discordant score, a method developed for human genes by an Australian research group, collaborators of our project. Based on this score, we are proposing a new methodology in which the genes of each sample will be ranked and the ranking between contrasting sample groups regarding the studied phenotypes will be compared to determine which genes are more discordantly activated between them. Analyses with the Partial Correlation with Information Theory (PCIT) and Regulatory Impact Factor (RIF) algorithms will be performed to obtain the genes correlated to tenderness and intramuscular fat and their potential regulatory impacts on these characteristics, complementing analysis already implemented for mineral amount. Functional analyses will be carried out in all lists of genes discordantly activated. The results will be integrated with data already obtained from transcription factors expressed in our samples, genes being affected by cis and trans eQTLs and differentially expressed or with expression values correlated to the phenotypes in order to achieve a wider range of regulatory events affecting each gene. (AU)