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Genomic studies associated with resistance to endoparasites traits in Santa Inês sheep

Abstract

The Brazilian sheep flock has been increasing but is not self-sufficient to attend the demand of lamb market. Some reasons that contribute to that is the old-fashioned management adopted by most producers in which animals are raised extensively with little or no technology, and the susceptibility to the of the gastrointestinal endoparasites, specially the Haemonchus contortus. Some traits used to measure the resistance of gastrointestinal endoparasites are Color of Ocular Conjunctiva (COC), fecal Eggs Per Gram (EPG), Total Plasmatic Protein (TPP), Packed Cell Volume (PCV) and Stool Test (ST%) which measures the percentage of endoparasite Haemonchus contortus. Taking into account the important to study the endoparasitism resistance of the sheep flock, the objectives of this project will be 1) to genotype about 1,150 Santa Inês sheep with Ovine SNP50 Genotyping BeadChip (Illumina); 2) to estimate genetic parameters for traits related to gastrointestinal endoparasitism resistance using mixed models by the method of restricted maximum likelihood and Bayesian inference; 3) to test Bayesian Lasso and Regularized Neural Networks to predict genomic breeding values using the SNPs genotypes; 4) to conduct genomic association studies (GWAS) for the traits related to endoparasitism resistance; 5) to calculate the linkage disequilibrium of the population and inbreeding levels using traditional pedigree and genomic information by the runs of homozygosity approach (ROH); 6) to identify regions with copy number variation in the DNA segments (CNVs) to detect candidate genes related to the studied traits. Functional enrichment analyzes will be performed from the regions identified by GWAS and CNV using the DAVID software (v.6.7). It is expected with this project to access the estimates of genetic parameters related to endoparasitism resistance to include them in the selection objectives in the breeding program of sheep; to evaluate the gain in prediction accuracy of genomic breeding values using the single nucleotide polymorphism in the genomic models over traditional mixed model; to use the genomic information to access the inbreeding of individuals to evaluate how to control the inbreeding; and to characterize the genomic regions associated with the resistance traits in order to identify candidate genes. (AU)

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Scientific publications (4)
(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)
DE FREITAS, LUARA AFONSO; SAVEGNAGO, RODRIGO PELICIONI; MENEGATTO, LEONARDO SARTORI; DO BEM, RICARDO DUTRA; STAFUZZA, NEDENIA BONVINO; ALMEIDA ROLLO DE PAZ, ANA CAROLINA; PIRES, BIANCA VILELA; DIAS DA COSTA, RICARDO LOPES; PARO DE PAZ, CLAUDIA CRISTINA. Cluster analysis to explore additive-genetic patterns for the identification of sheep resistant, resilient and susceptible to gastrointestinal nematodes. Veterinary Parasitology, v. 301, p. 5-pg., . (16/14522-7, 18/01540-2, 12/15982-0)
OLIVEIRA, ELISA JUNQUEIRA; SAVEGNAGO, RODRIGO PELICIONI; FREITAS, ANIELLY DE PAULA; DE FREITAS, LUARA AFONSO; DE PAZ, ANA CAROLINA ALMEIDA ROLLO; EL FARO, LENIRA; SIMILI, FLAVIA FERNANDA; VERCESI FILHO, ANIBAL EUGENIO; DA COSTA, RICARDO LOPES DIAS; DE PAZ, CLAUDIA CRISTINA PARO. Genetic parameters for body weight and morphometric traits in Santa Ines sheep using Bayesian inference. Small Ruminant Research, v. 201, . (18/01540-2, 12/15982-0, 16/14522-7)
FREITAS, LUARA; FERREIRA, RAFAEL; SAVEGNAGO, RODRIGO; DOREA, JOAO R.; ROSA, GUILHERME J. J. M.; PAZ, CLAUDIA. Computer Vision System to Predict Famacha (c) Degree in Sheep from Ocular Conjunctiva Images. JOURNAL OF ANIMAL SCIENCE, v. 100, p. 1-pg., . (16/14522-7, 18/01540-2, 20/03575-8)
FREITAS, LUARA; SAVEGNAGO, RODRIGO; CARVALHO ALVES, ANDERSON A.; COSTA, RICARDO; ROSA, GUILHERME J. J. M.; PAZ, CLAUDIA. Classification Performance of Multinomial Logistic Regression for Identifying Resistance, Resilience, and Susceptibility to Gastrointestinal Nematode Infections in Sheep. JOURNAL OF ANIMAL SCIENCE, v. 100, p. 1-pg., . (16/14522-7, 18/01540-2, 20/03575-8)

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