Integration of multi-omics functional information to better understand the fetal programming effects on bulls

• Grant number: 23/09113-4
• Support Opportunities: Scholarships abroad - Research Internship - Doctorate
• Start date: December 01, 2024
• End date: November 30, 2025
• Field of knowledge: Agronomical Sciences - Animal Husbandry - Animal Production
• Principal Investigator: Miguel Henrique de Almeida Santana
• Grantee: Guilherme Henrique Gebim Polizel
• Supervisor: Angela Canovas
• Host Institution: Faculdade de Zootecnia e Engenharia de Alimentos (FZEA). Universidade de São Paulo (USP). Pirassununga , SP, Brazil
• Institution abroad: University of Guelph, Canada
• Associated to the scholarship: 21/03265-1 - Use of systems biology tools to evaluate the effects of fetal programming in beef cattle, BP.DR

Abstract

Nutrition during the gestation period in beef cattle impacts on several productive and health phenotypes of the offspring, but the molecular mechanisms of fetal programming are complex and still need to be studied. In this project, an innovative form of analysis is proposed, aiming to integrate different omics to understand the different effects of fetal programming in the offspring. This project seeks to elucidate part of the mechanisms for multiomic and tissue integration in male Nellore animals that have been identified with different prenatal supplementation strategies. This study will be based on 63 animals from 3 different nutritional prenatal treatments: NP - only mineral supplementation (common to all treatments), PP - protein-energy supplementation in the final third of pregnancy and FP - protein-energy supplementation throughout the gestation. We collected several phenotypes (weight, weight gain, scrotal circumference and carcass ultrasound measures) and tissues (plasma, muscle, liver, subcutaneous fat thickness and ruminal fluid) throughout the productive life of the animals. All the animals were genotyped and randomly selected to the omics analyses (N=15; trancriptomics, metabolomics and metagenomics). The integration of transcriptomics and genomic data will be performed using the GALLO package in R, considering the treatments as covariates. From that metabolomic data will be normalized using MetaboAnalyst 5.0, and integration with eQTL results will be done using the Miodin package in R. Metagenomic data from ruminal fluid will be processed with edgeR, and integration with eQTLs will be performed using Miodin package. Phenotypic data, including scrotal circumference, weight, weight gain, and carcass ultrasound measures, will be integrated with eQTL results using the Miodin package also. Statistical methods such as partial least squares (PLS) regression, canonical correlation analysis (CCA) and co-inertia analysis (CIA) will be applied for association analyses. The integrated results will provide insights into the molecular mechanisms and biomarkers associated with the prenatal treatments. This project may demonstrate the biological basis of the influence of fetal programming on the performance of Nellore animals.