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Exploring eQTL analysis for beef fatty acid profile in Nelore cattle

Grant number: 17/21757-3
Support Opportunities:Scholarships abroad - Research Internship - Post-doctor
Effective date (Start): March 01, 2018
Effective date (End): February 28, 2019
Field of knowledge:Agronomical Sciences - Animal Husbandry - Genetics and Improvement of Domestic Animals
Principal Investigator:Henrique Nunes de Oliveira
Grantee:Camila Urbano Braz
Supervisor: Guilherme Jordao de Magalhaes Rosa
Host Institution: Faculdade de Ciências Agrárias e Veterinárias (FCAV). Universidade Estadual Paulista (UNESP). Campus de Jaboticabal. Jaboticabal , SP, Brazil
Research place: University of Wisconsin-Madison (UW-Madison), United States  
Associated to the scholarship:16/21201-2 - Mapping and characterization of eQTL associated with meat fatty acids in Nelore cattle, BP.PD


Health professionals have recommended a reduction in overall consumption of saturated fatty acids and an increase in the intake of unsaturated fatty acids. This has motivated the development of strategies that objective to alter the beef fatty acid composition to be more compatible with the consumer requirements. Many genome-wide association studies (GWAS) have identified genetic variants in non-coding regions of the genome for beef fatty acids in Bos indicus and Bos taurus, which are likely to be involved in gene regulation. The determination of which genomic regions are responsible for the regulation of transcription can be achieved through eQTL mapping. Co-localization analyses between eQTL and phenotypic QTL, and gene co-expression networks are approaches to explore eQTL information in animal breeding. Thus, the aim of this project is to overlap eQTLs found in Nelore cattle muscle RNA-seq data with SNPs and haplotypes associated with beef fatty acids, and to perform a gene co-expression network analysis to identify regulatory networks and hub genes. Sixteen Individual fatty acids will be analyzed in GWAS (based on SNPs and haplotypes) using GEMMA software and will be co-localized with the significant eQTLs. In addition, a well-established network-based approach, Weighted Gene Co-Expression Network Analysis (WGCNA) implemented in R WGCNA package will be adopted to identify modules in co-expression gene networks using the regulated genes associated with fatty acids. Combining all of this analysis, it is expected a better understanding of molecular mechanisms underlying beef fatty acids profile in Nelore cattle.

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