4.7 Article

Transcriptome Profiling of the Liver in Nellore Cattle Phenotypically Divergent for RFI in Two Genetic Groups

期刊

ANIMALS
卷 13, 期 3, 页码 -

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MDPI
DOI: 10.3390/ani13030359

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bovine; biomarkers; feed efficiency; liver tissue; non-coding RNAs; RNA-Seq

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By studying the RNA-seq data of Nellore cattle, we identified genes and metabolic pathways associated with residual feed intake (RFI) and identified potential gene markers. This study is of great significance for quantitative methods of animal husbandry and management, and can help select more efficient animals, thus reducing meat production costs and environmental impacts.
Simple Summary The selection of genetically superior animals for residual feed intake (RFI) does not affect animal growth, reproduction or the meat quality but it does lead to animals with lower consumption and lower maintenance requirements. This trait is difficult and costly to measure and is influenced by different biological processes and multiple genes. We used the RNA seq methodology of the liver in Nellore cattle with divergent RFI in two genetic groups. Eighty-eight common, differentially-expressed genes were identified in the two genetic groups. We highlight the B2M gene participating in most cellular processes that differentiate groups with a greater or lesser food efficiency. The biological pathways associated with RFI in the two genetic groups were for energy metabolism, protein turnover, redox homeostasis and the immune response. Additionally, we found non-coding RNAs, highlighting microRNA 25, which can act by blocking cytotoxicity and oxidative stress, and RNase_MRP, as a blocker of mitochondrial damage. This work could help future approaches in quantitative methods of animal husbandry and management and allow the use of possible markers for selecting more efficient animals, thus helping meat production costs and environmental impacts. The identification and selection of genetically superior animals for residual feed intake (RFI) could enhance productivity and minimize environmental impacts. The aim of this study was to use RNA-seq data to identify the differentially expressed genes (DEGs), known non-coding RNAs (ncRNAs), specific biomarkers and enriched biological processes associated with RFI of the liver in Nellore cattle in two genetic groups. In genetic group 1 (G1), 24 extreme RFI animals (12 low RFI (LRFI) versus 12 high RFI (HRFI)) were selected from a population of 60 Nellore bulls. The RNA-seq of the samples from their liver tissues was performed using an Illumina HiSeq 2000. In genetic group 2 (G2), 20 samples of liver tissue of Nellore bulls divergent for RFI (LRFI, n = 10 versus HRFI, n = 10) were selected from 83 animals. The raw data of the G2 were chosen from the ENA repository. A total of 1811 DEGs were found for the G1 and 2054 for the G2 (p-value <= 0.05). We detected 88 common genes in both genetic groups, of which 33 were involved in the immune response and in blocking oxidative stress. In addition, seven (B2M, ADSS, SNX2, TUBA4A, ARHGAP18, MECR, and ABCF3) possible gene biomarkers were identified through a receiver operating characteristic analysis (ROC) considering an AUC > 0.70. The B2M gene was overexpressed in the LRFI group. This gene regulates the lipid metabolism protein turnover and inhibits cell death. We also found non-coding RNAs in both groups. MIR25 was up-regulated and SNORD16 was down-regulated in the LRFI for G1. For G2, up-regulated RNase_MRP and SCARNA10 were found. We highlight MIR25 as being able to act by blocking cytotoxicity and oxidative stress and RMRP as a blocker of mitochondrial damage. The biological pathways associated with RFI of the liver in Nellore cattle in the two genetic groups were for energy metabolism, protein turnover, redox homeostasis and the immune response. The common transcripts, biomarkers and metabolic pathways found in the two genetic groups make this unprecedented work even more relevant, since the results are valid for different herds raised in different ways. The results reinforce the biological importance of these known processes but also reveal new insights into the complexity of the liver tissue transcriptome of Nellore cattle.

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