Integrating weather variables and genome sequencing to assess genotype-by-environment interactions via genomic reaction norms for reproductive performance in Nellore heifers

• Grant number: 24/22461-4
• Support Opportunities: Scholarships abroad - Research Internship - Post-doctor
• Start date: September 01, 2025
• End date: August 31, 2026
• Field of knowledge: Agronomical Sciences - Animal Husbandry - Genetics and Improvement of Domestic Animals
• Principal Investigator: Henrique Nunes de Oliveira
• Grantee: Lúcio Flávio Macedo Mota
• Supervisor: Luiz Fernando Brito
• Host Institution: Faculdade de Ciências Agrárias e Veterinárias (FCAV). Universidade Estadual Paulista (UNESP). Campus de Jaboticabal. Jaboticabal , SP, Brazil
• Institution abroad: Purdue University, United States
• Associated to the scholarship: 22/11852-7 - Structural equation modeling as a tool to interpret genotype-environment interaction and genome-wide association (GWAS) for growth and reproductive traits in Nellore heifers using whole-genome sequence data, BP.PD

Abstract

Beef cattle reproductive efficiency, particularly early pregnancy and rebreeding rates, plays a crucial role in the sustainability of tropical cattle production systems. Nellore heifers in tropical regions often face environmental stressors such as heat and variations in forage availability and quality, leading to significant genotype-by-environment (GxE) interactions that impact reproductive traits. This research project aims to understand how environmental stressors lead to GxE interaction by combining DNA whole-genome sequence data and weather variables through reaction norm (RN) models. For this, we will evaluate the GxE interaction affecting reproductive traits, including heifer early pregnancy (HP) and heifer rebreeding (HR), using whole-genome markers and environmental data. First, weather variables that influence reproductive performance in different tropical systems will be identified, and then genetic variation caused by these factors will be assessed. The project will analyze data from approximately 920,758 Nellore heifers across different regions in tropical environments (Brazil, Bolivia, Colombia, and Paraguay). Phenotypic data for age at first calving (AFC), HP, and HR will be combined with genomic data from approximately 21,454 genotyped heifers. The genomic data will be imputed to whole-genome sequence, and animals with low imputation accuracy will be removed from the analyses. Environmental conditions, including temperature, humidity, and rainfall, will be sourced from NASA's satellite data, allowing for a comprehensive evaluation of heat stress and other environmental factors on reproductive traits. A single-step genomic RN (ssGRN) model will be used to assess the influence of GxE interactions on reproductive performance by combining genomic and environmental data, enhancing prediction accuracy. This project aims to provide a better understanding of the genomic and environmental factors that affect reproductive performance in tropical beef cattle production. By identifying the heifers with more reproductive resilience in adverse environmental conditions, breeding programs can be optimized to select animals that are not only genetically superior but also more adaptable to environmental challenges. This will enhance productivity and animal welfare in tropical production systems, contributing to the development of sustainable beef cattle farming practices. This project will provide a better understanding of the GxE interactions affecting reproductive traits in tropical beef production systems, improve the knowledge on the impact of weather variables on reproductive performance in tropical beef production systems, and identify the genetic components related to adaptability and resilience. By integrating genomic and phenotypic data with environmental variables, we will enhance the ability to select more resilient and reproductively efficient animals. The findings will contribute to developing breeding strategies that improve both the productivity and adaptability of Nellore heifers in tropical regions facing climatic challenges.