Cluster analysis to explore additive-genetic patterns for the identification of sheep resistant, resilient and susceptible to gastrointestinal nematodes

Author(s)

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

• Document type: Journal article
• Source: Veterinary Parasitology; v. 301, p. 5-pg., 2022-01-01.

Abstract

Infection caused by gastrointestinal nematodes is an important issue for animal health and production. Controlling worm infections improves the sustainability of the sheep industry. Genetic selection of animals that are resistant to gastrointestinal nematodes is another strategy to render sheep production more sustainable by decreasing the use of anthelmintics. The aims of this study were (1) to explore the additive-genetic pattern of EBVs for Famacha(C) (FAM), packed-cell volume (PVC), and fecal egg counts (FEC) of Santa Ines sheep, (2) to propose a classification of animals that are resistant, resilient and susceptible to gastrointestinal nematodes based on their additive-genetic patterns, and (3) to identify the most suitable animals for selection based on their genetic pattern. A dataset of 2,241 records from 747 animals was used to predict the breeding values for indicator traits of resistance to gastrointestinal nematodes with THRGIBBS1F90 and to carry out cluster analyses was used R software. Three clusters of animals were found in the population using hierarchical cluster analysis of the breeding values for FAM, PCV and FEC. Each cluster was characterized by different additive-genetic patterns identified by k-means non-hierarchical cluster analysis. Among a total of 747 animals, 196 were classified as resistant, 288 as resilient, and 263 as susceptible. Cluster analysis is a valuable tool for data screening that permits to evaluate only selection candidates based on their additive-genetic pattern for gastrointestinal nematode resistance. EBVs for FEC were decisive to divide the population into resilient, resistant and susceptible animals. It is also important to include the EBVs for PCV and FAM to adequately distinguish resistant from resilient animals. Finally, the resistant cluster consisted of the most desirable animals to be used as selection candidates in order to genetically improve resistance to infection with gastrointestinal nematodes. This cluster contained animals with the most appropriate additive-genetic pattern to achieve the breeding goal, with positive breeding values for PCV and negative breeding values for FAM and FEC. (AU)

• FAPESP's process: 16/14522-7 - Genomic studies associated with resistance to endoparasites traits in Santa Inês sheep
• Grantee: Claudia Cristina Paro de Paz
• Support Opportunities: Research Projects - Thematic Grants
• FAPESP's process: 18/01540-2 - Prediction of genomic values using Bayesian models and neural networks for endoparasite resistance traits in Santa Inês sheep
• Grantee: Luara Afonso de Freitas Januário
• Support Opportunities: Scholarships in Brazil - Doctorate
• FAPESP's process: 12/15982-0 - Selection criteria for economic importance traits in Santa Inês sheep
• Grantee: Claudia Cristina Paro de Paz
• Support Opportunities: Regular Research Grants