| Grant number: | 14/01438-2 |
| Support Opportunities: | Scholarships abroad - Research Internship - Master's degree |
| Effective date (Start): | April 01, 2014 |
| Effective date (End): | September 30, 2014 |
| Field of knowledge: | Agronomical Sciences - Animal Husbandry - Genetics and Improvement of Domestic Animals |
| Principal Investigator: | Luiz Lehmann Coutinho |
| Grantee: | Vinicius Henrique da Silva |
| Supervisor: | Ralf Zimmer |
| Host Institution: | Escola Superior de Agricultura Luiz de Queiroz (ESALQ). Universidade de São Paulo (USP). Piracicaba , SP, Brazil |
| Research place: | Ludwig Maximilian University of Munich (LMU Munich), Germany |
| Associated to the scholarship: | 12/23717-5 - Identification of CNVs in the Nelore genome and its association with meat tenderness, BP.MS |
Abstract Brazil has the largest commercial cattle herd in the world and occupies the first position in worldwide meat export. About 80% of Brazilian herd consists of Zebu breeds (Bos taurus indicus). Nelore breed represents 90% of zebuine cattle, showing great representability and adaptability. The great adaptability of Nelore breed in Brazilian tropical climate, however, is not associated with meat tenderness. To investigate underlying genetic factors the "Molecular basis of meat quality in Nelore beef cattle" project has been launched by Brazilian Agricultural Research Corporation (EMBRAPA - Southeast Livestock) in collaboration with the University of São Paulo - Luiz de Queiroz College of Agriculture (USP - ESALQ). One important genetic source of phenotypic variance investigated in the project is copy number variation (CNV), i.e. deviation from the normal number of copies of certain DNA sections in the genome. Previously, genotyping of a Nelore population of approximately 800 animals identified more than 2000 regions of copy number variation (CNVRs). Out of them, ten CNVRs holding SNPs (single nucleotide polymorphism) associated with meat tenderness were too analyzed by qPCR. Additionally, 40 animals of the population were subjected to transcriptome analysis using next-generation sequencing (RNA-seq). This work aim is to combine CNVR and gene expression data to identify genes, which are differentially expressed between different CNVR genotypes. Another aim is to analyze whether differentially expressed genes share similar functions or belong to similar metabolic pathways using state-of-the-art enrichment approaches. This will substantially improve the biological interpretation of the CNVRs and will enable the detection of relevant candidates associated with beef tenderness. (AU) | |
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