Genetic evaluation of growth and resistance to gastrointestinal nematode parasites in Santa Ines sheep using random regression models and multivariate analyzes

Author(s)

Luara Afonso de Freitas

• Document type: Master's Dissertation
• Press: Jaboticabal. 2018-02-28.
• Institution: Universidade Estadual Paulista (Unesp). Faculdade de Ciências Agrárias e Veterinárias. Jaboticabal
• Defense date: 2018-02-21
• Advisor: Danisio Prado Munari; Claudia Cristina Paro de Paz; Rodrigo Pelicioni Savegnago

Abstract

The use of resistant animals to gastrointestinal nematode parasites within the meat production system is one of the most efficient alternatives to increase meat yield in sheep. The control of mating between related animals is of great importance to reduce losses in meat production by increasing the homozygosity of deleterious alleles. Application of Random regression models in the genetic evaluation of longitudinal measurements is generally recommended to adjust growth curves and to estimate genetic parameters of longitudinal data. The multivariate analyzes are a set of statistical methods that make possible the simultaneous analysis of multiple measures for each individual or observed phenomena. The aims of this study were: (1) to analyze the population structure and verify the effect of inbreeding on phenotypic traits of growth and resistance to gastrointestinal nematode parasites, (2) to compare structures (homogeneity and heterogeneity of variances) to model residual variance in random regression models, (3) to study the influence of this modeling in the estimation of genetic parameters in order to determine the most appropriate model to study the growth and resistance to gastrointestinal nematode parasites curves, and (4) evaluate the genetic association and explore the genetic profile of meat production and resistance to gastrointestinal nematode parasites in Santa Inês sheep. The data contained 2,159 body weight records from 753 animals, 1,468 mean corpuscular volume records from 476 animals and 981 records of fecal egg counts from 375 animals and pedigree information from 2,410 in Santa Ines sheep. The animals were divided into 10 age classes (CI90 = 30 to 90 days of age CI180 = 91 to 180 days of age, CI270 = 181 to 270 days of age, CI360 = 271 to 360 days of age, CI450 = 361 to 450, CI540 = 451 to 540 days of age, CI630 = 541 to 630 days of age, CI720 = 631 to 720 days of age, CI810 = 721 to 810 days of age, CI900 = 811 to 900 days of age). The structure of the pedigree was analyzed using the program Endog 4.8. Analyzes of the variance component estimates were performed using a one-trait model of random regression using the restricted maximum likelihood method. The Bayesian information criterion was used to select the best model. The principal component analysis was performed in STATISTIC software and hierarchical and non-hierarchical analysis grouping was performed in the software R. There was an increase in the inbreeding coefficient up to the 6th maximum generation and also an increase in the average relatedness and in the percentage of inbred animals up to the 7th maximum generation. Genetic correlation estimates for all traits in the age classes presented values close to the unit at close weighings, with a reduction in the magnitude of the correlations as the time interval between weighings increased. The Legendre polynomial of order 3 (intercept, linear and quadratic) provided the best fit of the data for body weight, mean corpuscular volume, and fecal egg counts. The selection of the animals could be made based on body weight from 271 days of age, as the heritability estimate was moderate, 0.23 (0.03), and showed high genetic correlations with most body weights, except with body weight from 30 to 90 days of age. Selection of these animals for resistance to gastrointestinal nematode parasites if carried out may result in low efficiency due to the low estimates of heritability for the mean corpuscular volume (0.09 ± 0.01 to 0.18 ± 0.02) and fecal egg counts (0.01 ± 0.02 to 0.17 ± 0.03), therefore, the genetic gain will be low and in the long term. The selection of body weight could bring favorable genetic gains to the mean corpuscular volume due to the proximity of the traits in the axis of the main component one. In cluster analysis, only one of the three genetic groups identified has a genetic profile indicated for selection for the studied traits. (AU)

• FAPESP's process: 16/10583-1 - Genetic evaluation of growth characteristics and resistance to worms in sheep breed Santa Inês using random regression models and cluster analysis
• Grantee: Luara Afonso de Freitas Januário
• Support Opportunities: Scholarships in Brazil - Master