Imputation of genetic composition for missing pedigree data in Serrasalmidae using morphometric data

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Abstract

This study aimed to impute the genetic makeup of individual fishes of Serrasalmidae family on the basis of body weight and morphometric measurements. Eighty-three juveniles, belonging to the genetic groups Pacu, Pirapitinga, Tambaqui, Tambacu, Tambatinga, Patinga, Paqui and Piraqui, were separated into 16 water tanks in a recirculation system, with two tanks per genetic group, where they remained until they reached 495 days of age. They were then weighed and analyzed according to the following morphometric parameters: Standard Length (SL), Head Length (HL), Body Height (BH), and Body Width (BW). The identity of each fish was confirmed with two SNPs and two mitochondrial markers. Two analyses were performed: one for the validating the imputation and another for imputing a genetic composition of animals considered to be advanced hybrids (post F1). In both analyses, we used linear mixed models with a mixture of normal distributions to impute the genetic makeup of the fish based on phenotype. We applied the mixed models method, whereby the environmental effects were estimated by the Empirical Best Linear Unbiased Estimator (EBLUE) and genetic effects are considered random, obtaining the Empirical Best Linear Unbiased Predictor (EBLUP) from the general (GCA) and the specific (SCA) combining ability effects. The results showed that validation of the genetic makeup imputation based on body weight can be used because of the strong correlation between the observed and imputed genotype. The fish classified as advanced hybrids had a genetic composition with a high probability of belonging to known genotypes and there was consistency in genotype imputation according to the different characteristics used.

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Costa, A. C., Balestre, M., Botelho, H. A., de Freitas, R. T. F., Gomes, R. C. da S., Campos, S. A. de S., … Mendonça, M. A. C. (2017). Imputation of genetic composition for missing pedigree data in Serrasalmidae using morphometric data. Scientia Agricola, 74(6), 443–449. https://doi.org/10.1590/1678-992x-2016-0251

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