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Phenotypic, genetic correlations and genomic wide association between feed efficiency and enteric methane emission of Nellore cattle

Grant number: 19/11738-7
Support type:Scholarships in Brazil - Doctorate
Effective date (Start): October 01, 2020
Effective date (End): February 28, 2023
Field of knowledge:Agronomical Sciences - Animal Husbandry - Genetics and Improvement of Domestic Animals
Principal researcher:Josineudson Augusto Ii de Vasconcelos Silva
Grantee:Luana Lelis Souza
Home Institution: Faculdade de Medicina Veterinária e Zootecnia (FMVZ). Universidade Estadual Paulista (UNESP). Campus de Botucatu. Botucatu , SP, Brazil
Associated research grant:17/10630-2 - Genetic aspects of meat production quality, efficiency and sustainability in Nelore breed animals, AP.TEM

Abstract

As the methane emission characteristics (CH4) are difficult to measure and there is little scientific information about their genetic variation, it is expected that estimates of genetic parameters and genetic variants associated to these characteristics favor the implementation of the selection to reduce the emission of CH4 by cattle. The objectives of the project are: to evaluate the characteristics related to the emission of CH4 and its phenotypic and genetic associations with food efficiency characteristics, and to conduct a broad genomic association study of CH4 emission characteristics. Whole males of the Nelore breed (from the Institute of Animal Science and Nelore Qualitas) will remain in collective pickets equipped with electronic troughs to evaluate residual food consumption (RFI) in performance tests. Dry matter intake, average daily gain, metabolic live weight, as well as RFI and crude food efficiency will be evaluated. Estimation of CH4 emission in g/day will be obtained using modified SF6 tracer gas methodology. The SF6 and CH4 concentrations of the samples will be determined by gas chromatography. All animals with CH4 emission phenotype will be genotyped with GeneSeek® Genomic Profiler Indicus HD-GGP75Ki (NEOGEN) containing 74,677 markers. The (co) variance components will be estimated using the GBLUP single-step methodology, considering the animal model. SNPs that explain more than 5% of the additive genetic variance will be used to prospect for genes in the Ensemble Genome Biomart database and functional enrichment through the Panther Classification System. (AU)

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