Genomic prediction for enteric methane emission and feed efficiency-related traits in Nellore cattle, integrating whole-genome data and marker pre-selection strategies

• Grant number: 24/16663-3
• Support Opportunities: Scholarships abroad - Research Internship - Doctorate
• Start date: April 01, 2025
• End date: February 28, 2026
• Field of knowledge: Agronomical Sciences - Animal Husbandry - Genetics and Improvement of Domestic Animals
• Principal Investigator: Lucia Galvão de Albuquerque
• Grantee: Leonardo Machestropa Arikawa
• Supervisor: Flavio Schramm Schenkel
• Host Institution: Faculdade de Ciências Agrárias e Veterinárias (FCAV). Universidade Estadual Paulista (UNESP). Campus de Jaboticabal. Jaboticabal , SP, Brazil
• Institution abroad: University of Guelph, Canada
• Associated to the scholarship: 23/17818-8 - Genome-wide scan to identify selection signatures and candidate genes associated with enteric methane emission and feed efficiency traits in Nellore cattle using sequencing data, BP.DR

Abstract

With the process of globalization, population growth creates additional pressure on production systems, which must become more efficient and sustainable to avoid negative environmental impacts. Methane (CH4) emissions are the main environmental challenges related to livestock farming. In addition to its impact on the environment, CH4 production represents a loss of food energy, resulting in significant metabolic inefficiency. Improving cattle feed efficiency can be an effective strategy to reduce CH4 emissions, since more efficient animals require fewer resources to produce the same amount of meat and consequently tend to produce less CH4 per unit of body weight gained than those less efficient. Furthermore, improvements in feed efficiency have the potential to increase farmers' profitability, as feed costs have a great economic impact on the production system. However, individual-level measurements of enteric CH4 and feed efficiency-related traits are expensive and labor-intensive. Thus, the use of genomic approaches combined with whole-genome information may be an alternative to overcome these challenges. Genomic selection (GS) is a promising tool that uses information from animal genomes to predict the performance of specific traits. Additionally, the genomic predictions' accuracy can be improved by the inclusion of more variants, such as variants preselected for their effect, located near or within genes. Therefore, this project aims to assess the predictive ability of genomic selection for enteric methane emission and feed efficiency-related traits, using whole-genome sequencing data in Nellore cattle under different selection criteria. To achieve this, information from all genetic markers will be used and pre-selection strategies will be applied to reduce the number of predictors. Strategies will include the use of markers obtained from i) weighted single-step GWAS (WssGWAS) results; ii) significant SNPs based on GWAS p-values; iii) possible causal mutations obtained from fine-mapping; and iv) fixation indexes (FST). The expected results can directly benefit producers, providing more efficient and sustainable animals, and contributing significantly to climate change mitigation and food security in a growing world.