Grant number: | 15/12396-1 |
Support Opportunities: | Scholarships in Brazil - Post-Doctoral |
Effective date (Start): | October 01, 2015 |
Effective date (End): | May 31, 2018 |
Field of knowledge: | Agronomical Sciences - Animal Husbandry - Genetics and Improvement of Domestic Animals |
Principal Investigator: | Humberto Tonhati |
Grantee: | Daniel Jordan de Abreu Santos |
Host Institution: | Faculdade de Ciências Agrárias e Veterinárias (FCAV). Universidade Estadual Paulista (UNESP). Campus de Jaboticabal. Jaboticabal , SP, Brazil |
Associated scholarship(s): | 17/00462-5 - Genomic homology between cattle and buffaloes and comparison of different machine learning methods for genotype imputation in buffalo genome, BE.EP.PD |
Abstract The Buffalo River has aptitude for meat and milk production. The buffalo milk is rich in content, which enables the production of dairy products such as butter and cheese, especially the "mozzarella". Among the breeds of buffalo brought to Brazil, the Murrah breed, due to milk production, has important economic participation in Brazilian cities, mainly in São Paulo State. Thus, the genetic improvement for the milk yield and content is desired and an important step for this is to apply methods for accurate identification of top genotypes in short term. The latest technology called genomic selection (GS) may be useful for genetic evaluations of buffaloes, because the reliability of genomic breeding values for young sires may be higher than those obtained with traditional evaluation. However, the cost reduction of genotyping is a important point for the viability of this technology. The use of panels with smaller number of SNPs with an imputation process in the genetic evaluation is an economic alternative. Therefore, the aim of this project is to study the imputation of genotypes of the markers present on the Illumina® panel for cattle "BovineHD BeadChip" and on the "Axiom® Buffalo Genotyping" from Affymetrix panel for buffalo, comparing different scenarios with fewer markers, and to evaluate the impact of genomic predictions of milk yield and content in the Murrah breed from these imputed data. | |
News published in Agência FAPESP Newsletter about the scholarship: | |
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