Bayesian analysis of buffalo lactation curves combining pedigree and genomic information

• Grant number: 19/22136-8
• Support Opportunities: Scholarships abroad - Research Internship - Post-doctor
• Effective date (Start): January 01, 2020
• Effective date (End): December 31, 2020
• Field of knowledge: Agronomical Sciences - Animal Husbandry - Genetics and Improvement of Domestic Animals
• Principal Investigator: Humberto Tonhati
• Grantee: Sirlene Fernandes Lazaro
• Supervisor: Luiz Fernando Brito
• Host Institution: Faculdade de Ciências Agrárias e Veterinárias (FCAV). Universidade Estadual Paulista (UNESP). Campus de Jaboticabal. Jaboticabal , SP, Brazil
• Research place: Purdue University, United States
• Associated to the scholarship: 17/23818-0 - GENOMIC EVALUATION OF BUFFALO LACTATION CURVES USING BAYESIAN MODELS, BP.PD

Abstract

Lactation curves can be modeled by different mathematical functions that present a small number of parameters with biological interpretations. Thus, desirable changes in the shape of curves can be obtained by considering the estimates of these parameters as phenotypic observations in genetic evaluation statistical models. Given the importance of genomic information, the use of these phenotypes can be expanded to more sophisticated models, such as Genome-Wide Association Studies (GWAS) and genomic selection. Therefore, this project aims to evaluate the lactation curve based on the Bayesian hierarchical structure regarding GWAS and genomic selection, using genotype and phenotype information, with or without pedigree information; and identify chromosomal regions and candidate genes related to lactation curve parameters. The used data refer to 12 farms that participate in the dairy control program of the Animal Science Department of Sao Paulo State University, UNESP, in Jaboticabal, SP. The databank contains information on 4,588 animals born between 1,971 and 2,014, of which 978 animals were genotyped using the Axiom® Buffalo Genotyping Array 90K (Affymetrix). Five traits are going to be analyzed: accumulated milk yield, fat and protein percentage, and fat and protein yield. The Bayesian hierarchical model will be applied first to analyze the lactation curve, followed by modeling of the function parameters using multi-trait linear models, and comparison of their predictive capabilities through cross-validation, to determine the best performance. (AU)

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

LAZARO, SIRLENE F.; TONHATI, HUMBERTO; OLIVEIRA, HINAYAH R.; SILVA, ALESSANDRA A.; NASCIMENTO, V, ANDRE; SANTOS, DANIEL J. A.; STEFANI, GABRIELA; BRITO, LUIZ F.. Genomic studies of milk-related traits in water buffalo (Bubalus bubalis) based on single-step genomic best linear unbiased prediction and random regression models. JOURNAL OF DAIRY SCIENCE, v. 104, n. 5, p. 5768-5793, MAY 2021. (17/23818-0, 19/22136-8)