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

Author:

Serna-García Marta1ORCID,Fonseca Larissa Fernanda Simielli1,Panadero Romero Joaquin Javier2,Carretero Asuncion Julian3,dos Santos Silva Danielly Beraldo1,Salatta Bruna Maria1,Frezarim Gabriela Bonfá1,Mercadante Maria Eugênia Zerlotti45,Bonilha Sarah Figueiredo Martins45,Ferro Jesus Aparecido14ORCID,De Albuquerque Lucia Galvão14ORCID

Affiliation:

1. School of Agricultural and Veterinary Sciences, Sao Paulo State University (UNESP), Jaboticabal 14884-900, São Paulo, Brazil

2. Igenomix S.L., 46021 Valencia, Spain

3. Department of Physiology, Faculty of Medicine and Odontology, University of Valencia, 46100 Valencia, Spain

4. National Council for Scientific and Technological Development (CNPq), Brasília 71605-170, Distrito Federal, Brazil

5. Institute of Animal Science, Sertãozinho 14160-970, Sao Paulo, Brazil

Abstract

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.

Funder

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES)—Finance Code 001

São Paulo Research Foundation—FAPESP

Publisher

MDPI AG

Subject

General Veterinary,Animal Science and Zoology

Reference141 articles.

1. Martin, P. (2017). Research Handbook on Climate Change and Agricultural Law, Edward Elgar Publishing.

2. Reducing food’s environmental impacts through producers and consumers;Poore;Science,2018

3. Multisociety Consensus Quality Improvement Revised Consensus Statement for Endovascular Therapy of Acute Ischemic Stroke;Sacks;Int. J. Stroke,2018

4. (2022, January 16). Meat|OECD-FAO Agricultural Outlook 2020–2029|OECD iLibrary. Available online: https://www.oecd-ilibrary.org/sites/29248f46-en/index.html?itemId=/content/component/29248f46-en.

5. ABIEC (2019, January 03). Perfil da pecuária no Brasil. Available online: http://www.abiec.com.br/controle/uploads/arquivos/sumario2019portugues.pdf.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3