Genomic reaction norm models under metafounders approach for evaluating heat stress in Angus, Brangus, and Nelore cattle considering adaptive and fertility traits

• Grant number: 24/20994-5
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Start date: August 01, 2025
• End date: July 31, 2028
• Field of knowledge: Agronomical Sciences - Animal Husbandry - Genetics and Improvement of Domestic Animals
• Principal Investigator: Lenira El Faro Zadra
• Grantee: Eula Regina Carrara
• Host Institution: Instituto de Zootecnia. Agência Paulista de Tecnologia dos Agronegócios (APTA). Secretaria de Agricultura e Abastecimento (São Paulo - Estado). Nova Odessa , SP, Brazil
• Associated research grant: 21/11922-2 - Science Center for the Development of Climate Neutrality for Beef in Tropical Regions, AP.CCD

Abstract

The beef cattle production systems in Brazil are diverse, influenced by cultural factorsand the country's vast territorial expanse. In this context, genotype by environmentinteraction (GxE) studies that consider heat stress are especially relevant for the beefsector in Brazil. Research on GxE that includes multibreed genetic evaluations canbenefit breeding programs, supporting both purebred and crossbred animals. This projectaims to assess models with and without the GxE component using the metafoundersapproach, focusing on Angus, Nelore, and Brangus breeds in a multibreed evaluation.Phenotypic, genomic, and pedigree data for these breeds, provided by the NaturaProgram from "GenSys Consultores Associados", will be used. Traits assessed includeweaning weight gain, age at first calving, tick resistance, temperament, coatcharacteristics at weaning and yearling stages. The environmental variable will be theTemperature and Humidity Index (THI), with climatic data sourced from the NASAPOWER database. Four models will be evaluated: i) single-step genomic BLUP(ssGBLUP), without the GxE component and without metafounders; ii) ssGBLUP withGxE, without metafounders; iii) ssGBLUP without GxE but with metafounders; and iv)ssGBLUP with both GxE and metafounders. The models will be compared based onpredictive ability and bias using linear regression method (LR), which comparespredictions based on whole and partial data. Additionally, they will be evaluated foraccuracy of breeding values and for animal ranking. The goal is to identify animals thatare resilient to changes in THI and possibly more resistant to heat stress, contributing toimproved productivity and sustainability in Brazilian beef production. (AU)