Co-abundance networks and multi-omic integration: impacts of creep-feeding and rearing/finishing systems on the muscle phenotype of Nellore cattle

• Grant number: 26/01227-9
• Support Opportunities: Scholarships abroad - Research Internship - Master's degree
• Start date: June 29, 2026
• End date: December 28, 2026
• Field of knowledge: Agronomical Sciences - Animal Husbandry - Genetics and Improvement of Domestic Animals
• Principal Investigator: Rogério Abdallah Curi
• Grantee: Gabriel Luiz Navarro Liberal
• Supervisor: Wellison Jarles da Silva Diniz
• Host Institution: Faculdade de Medicina Veterinária e Zootecnia (FMVZ). Universidade Estadual Paulista (UNESP). Campus de Botucatu. Botucatu , SP, Brazil
• Institution abroad: Auburn University, United States
• Associated to the scholarship: 24/23763-4 - Effect of supplementation during the rearing phase associated with intensive growth and finishing on the skeletal muscle proteome of Nellore cattle, BP.MS

Abstract

Brazilian livestock seeks efficiency in the Nellore breed, which presents limitations in fat and performance compared to taurine breeds. Creep-feeding explores plasticity windows (imprinting) to optimize carcass and marbling, but the molecular mechanisms in the muscle proteome remain unexplored. The isolated proteomic analysis from the Master's project is insufficient to capture complex dynamic interactions. Thus, integrating lipidomics and building co-abundance networks is fundamental for a holistic view of the biological response to nutritional management.The general objective of this project is based on characterizing the metabolic and physiological processes altered by different nutritional managements during the calf, backgrounding, and finishing phases in Nellore cattle. To achieve this goal, the construction of protein co-abundance networks is proposed at weaning and pre-slaughter, while the lipid network and multi-omics integration between discriminant proteome and lipidome will be performed exclusively on pre-slaughter data, comparing animals subjected or not to creep-feeding. Specifically, the plan aims to build co-abundance networks via PCIT methodology to identify functional modules and central regulatory molecules (hubs), ensuring an understanding of coordinated systemic functioning. Additionally, a statistical integration will be performed using the IntLIM 2.0 method to identify protein-lipid pairs whose association changes as a function of nutritional management. The integrative functional analysis will proceed with KEGG pathway mapping via Joint Pathway Analysis (JPA) and the quantification of continuous activity scores at the sample level using ReactomeGSA in multi-omics mode. Finally, the results from both platforms will be compared to identify robust convergences, culminating in the development of an integrative functional model that elucidates the lasting effects of early supplementation on the muscle and lipid metabolism of the Nellore breed.Proteomic and lipidomic data matrices will be subjected to rigorous filtering and normalization protocols (VSN and PQN) for the reduction of technical noise and detection of outliers via PCA. The PCIT algorithm will be applied to reconstruct biological networks, using partial correlations to distinguish direct interactions from spurious associations. Statistical integration via IntLIM 2.0 will test analyte-phenotype interactions through linear models, where the coefficient of interest will be the interaction indicating whether the relationship between analytes depends on the nutritional treatment. Integrative functional enrichment will use the hypergeometric test and pathway topology analysis to highlight central components in metabolism. Complementarily, the Gene Set Variation Analysis (GSVA) method in ReactomeGSA will allow for a "side-by-side" multi-omics comparison of the previously normalized matrices.The internship will be conducted at Auburn University, a leading institution with access to High-Performance Computing systems, indispensable for processing large data volumes. Dr. Wellison Diniz's supervision ensures expertise in biostatistics and systems biology. The execution will allow for the transfer of high-complexity methodologies not yet performed by the research group in Brazil, strengthening international competitiveness. It is expected to identify proteins and pathways modulated by early nutrition, providing subsidies for the elaboration of more efficient nutritional strategies based on molecular mechanisms in beef cattle production. (AU)