Differential expression of genes related with meat tenderness in Nellore cattle

• Ano de defesa: 2015
• Autor(a) principal: Gonçalves, Tássia Mangetti
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Biblioteca Digitais de Teses e Dissertações da USP
• Palavras-chave em Português: Bos indicus; Bos taurus indicus; Cuffdiff; Força de cisalhamento; Networks; QuasiSeq; Redes; RNA-Seq; RNASeq; Shear force; Transcriptoma; Transcriptome
• Link de acesso: http://www.teses.usp.br/teses/disponiveis/11/11139/tde-12052015-165345/

Beef quality in Brazil is important for both consumers and the food industry due to high demand and competitiveness in the domestic and international markets. Therefore, it is necessary to develop research to improve beef quality of Nellore cattle (Bos indicus), mainly tenderness, one of the main features to add value to meat. New-generation technologies provide accurate, rapid and inexpensive information on the entire genome, showing great advantage over conventional methods for sequencing and gene expression. However, these new technologies generate large database, which require the use of bioinformatics tools for data analyses of sequencing and for a better understanding of biological regulation mechanisms , cellular control, gene interactions, among other applications. In a previous study, samples were collected from the Longissimus dorsi muscle of 790 animals from Nellore cattle and shear force assessments were made 24 hours after slaughter, with seven and 14 days of aging. Aiming to identify differentially expressed (DE) genes, 34 samples from Nellore animals with extreme levels of estimated breeding value (EBV) for shear force (SF) were selected, sequenced by the method of RNA sequencing (RNA-Seq) (Illumina HiScanSQ). This study performed the processing of data generated by RNA-Seq using software QuasiSeq and Cuffdiff. In the QuasiSeq analysis, 22 DE genes were found, while in the Cuffdiff analysis, 113 DE genes were found. To better understand the biological process involved in meat tenderness, integrative analysis identified possible regulators that can explain the activity of transcriptional regulation in this process using partial correlation coefficient with information theory (PCIT), phenotypic impact factor (PIF) and regulatory impact factor (RIF) methods. The genes found in the PCIT analysis USP2, GBR10, ANO1 and TMBIM4; microRNAs found in RIF analysis bta-mir-133a-2 and bta-mir-22, and the genes with high PIF value MB, ENO3, CA3 could be fundamental to unravel the complex molecular mechanisms that control the meat tenderness in Nellore cattle.