Predicción genómica de peso vivo con dos métodos de validación cruzada en ganado bovino

Autores/as

  • Francisco Joel Jahuey-Martínez Universidad Autónoma de Chihuahua
  • Juan Gabriel Magaña-Monforte Universidad Autónoma de Yucatán
  • José Candelario Segura-Correa Universidad Autónoma de Yucatán
  • Juan Carlos Martínez-González Universidad Autónoma de Tamaulipas
  • Raciel J. Estrada-León Instituto Tecnológico Superior de Calkiní
  • Gaspar Manuel Parra-Bracamonte Instituto Politécnico Nacional, Centro de Biotecnología Genómica

DOI:

https://doi.org/10.19136/era.a11n1.3817

Palabras clave:

BLUP, Charolais, crecimiento, evaluación genómica de un solo paso, SNP, selección genómica

Resumen

Se estimó la exactitud de la predicción (EP) de valores genómicos estimados (GEBV) para variables de peso vivo de ganado Charolais utilizando dos métodos de validación cruzada. Se ajustó un modelo BLUP y diferentes métodos de predicción genómica (PG) Genomic-based best linear unbiased prediction (GBLUP), Bayes C (BC) y Single-step Bayesian regression (SSBR). La EP fue comparada mediante grupos de validación (GV) formados aleatoriamente y mediante GC. Los resultados mostraron que los tres métodos de PG proporcionaron exactitudes de predicción similares entre los

GV

pero no exactitudes de predicción superiores a BLUP. La exactitud de predicción de GBLUP y BLUP fue 0.35 y 0.37 para PN, y de 0.30 y 0.41 para PD, respectivamente. Los resultados muestran bajas exactitudes de PG bajo los escenarios evaluados; por lo que para su correcta implementación es necesario incrementar el número de animales y usar valorees genéticos desregresados como variables de respuesta.

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Biografía del autor/a

Gaspar Manuel Parra-Bracamonte, Instituto Politécnico Nacional, Centro de Biotecnología Genómica

Biotecnología y agropecuarias

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Publicado

2024-02-19

Cómo citar

Jahuey-Martínez, F. J., Magaña-Monforte, J. G., Segura-Correa, J. C., Martínez-González, J. C., Estrada-León, R. J., & Parra-Bracamonte, G. M. (2024). Predicción genómica de peso vivo con dos métodos de validación cruzada en ganado bovino. Ecosistemas Y Recursos Agropecuarios, 11(1). https://doi.org/10.19136/era.a11n1.3817

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