PlumX Metrics
Embed PlumX Metrics

Influence of coat color on genetic parameter estimates in horses

Journal of Applied Genetics, ISSN: 2190-3883, Vol: 62, Issue: 2, Page: 297-306
2021
  • 5
    Citations
  • 0
    Usage
  • 13
    Captures
  • 0
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

Article Description

The aim of this study was to verify the effect of the inclusion of coat color on the genetic parameter estimation for linear measurements in Campolina horses. Two models (1 and 2) were applied. For model 1, coat color effect was not included as variable of the contemporary group formation; in model 2, it was included. Model 2 presented the best fitting with a Deviance Information Criterion (DIC) of −979,459.020 compared with −1,818,458.572 DIC from model 1. The average of heritability estimates ranged from low to high magnitude (0.15 to 0.53) for model 1 and from moderate to high magnitude for model 2 (0.21 to 0.47). The estimated values varied according to the analyses (models 1 and 2). The highest heritability was found for withers height (0.52), croup height (0.53), and back height (0.51). The genetic correlations ranged from values of moderate to high magnitude for models 1 (0.23 to 0.98) and 2 (0.29 to 0.99), respectively. The finding that genetic variance differed among models 1 and 2 may indicate that genotypes react differently to different coat colors, a fact implying the existence of interaction between these traits and the effect under study. The coat color influence might be explained as a pleiotropic effect of the genes that cause this phenotypic variation and also influence morphometric measures. The inclusion of the coat color effect better estimated the additive genetic variance of morphometric traits in horses. As a consequence, the genetic parameters were also more accurately estimated when it is included in the evaluation model.

Bibliographic Details

Junqueira, Gleb Strauss Borges; Diaz, Iara Del Pilar Solar; da Cruz, Valdecy Aparecida Rocha; de Araújo Oliveira, Chiara Albano; de Godoi, Fernanda Nascimento; de Camargo, Gregório Miguel Ferreira; Costa, Raphael Bermal

Springer Science and Business Media LLC

Biochemistry, Genetics and Molecular Biology

Provide Feedback

Have ideas for a new metric? Would you like to see something else here?Let us know