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The effect of copy number variations on gene expression and bovine meat quality

Grant number: 20/00340-0
Support Opportunities:Scholarships in Brazil - Post-Doctoral
Effective date (Start): August 01, 2020
Effective date (End): March 31, 2022
Field of knowledge:Agronomical Sciences - Animal Husbandry - Genetics and Improvement of Domestic Animals
Principal Investigator:Luiz Lehmann Coutinho
Grantee:Vinicius Henrique da Silva
Host Institution: Escola Superior de Agricultura Luiz de Queiroz (ESALQ). Universidade de São Paulo (USP). Piracicaba , SP, Brazil
Associated research grant:19/04089-2 - The Nelore hologenome: implications in beef quality and feed efficiency, AP.ESCIENCE.TEM


Brazil is one of the largest beef exporters in the world, and Nelore breed is a widespread breed in Brazil mainly because this breed is highly adapted to tropical weathers. To strengthen the Brazilian beef production, recent efforts have been made to unravel the main genetic variants associated with production and meat quality traits in the Nelore breed. Although the knowledge about which genetic variants are underlying interesting traits is growing, it is usually challenging to differ causal variants from the associated variants with linkage-disequilibrium with the causal one. Moreover, in these classical Genome-Wide Association Studies (GWAS), the biological pathways underlying phenotypes of interest can be unclear. However, by combining different molecular and bioinformatic approaches such as genotyping, gene expression and network it is possible to highlight the likely molecular mechanisms causing variation in traits of interest. Genetic variants can be punctual or structural and the last is more challenging to detect and explore. Nevertheless, structural variants have been associated with different production traits in several domestic animals, including Nelore cattle. This projects intends to investigate the associations of a type of structural rearrangement, i.e. Copy Number Variants (CNVs), with meat quality traits (CNV-GWAS) and gene expression (CNV-eQTLs) in liver and muscle as well as the directly association of gene expression with meat quality traits (WGCNA). All three approaches will be integrated, CNVs will be interpreted in the light of genomic architecture and the algorithms developed or improved here will be implemented in the open-source R/Bioconductor package CNVRanger. (AU)

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