Target-oriented prioritization: targeted selection strategy by integrating organismal and molecular traits through predictive analytics in breeding.
Genome Biol
; 23(1): 80, 2022 03 15.
Article
en En
| MEDLINE
| ID: mdl-35292095
ABSTRACT
Genomic prediction in crop breeding is hindered by modeling on limited phenotypic traits. We propose an integrative multi-trait breeding strategy via machine learning algorithm, target-oriented prioritization (TOP). Using a large hybrid maize population, we demonstrate that the accuracy for identifying a candidate that is phenotypically closest to an ideotype, or target variety, achieves up to 91%. The strength of TOP is enhanced when omics level traits are included. We show that TOP enables selection of inbreds or hybrids that outperform existing commercial varieties. It improves multiple traits and accurately identifies improved candidates for new varieties, which will greatly influence breeding.
Palabras clave
Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
Fitomejoramiento
/
Modelos Genéticos
Tipo de estudio:
Prognostic_studies
/
Risk_factors_studies
Idioma:
En
Revista:
Genome Biol
Asunto de la revista:
BIOLOGIA MOLECULAR
/
GENETICA
Año:
2022
Tipo del documento:
Article
País de afiliación:
China