Genomic prediction models trained with historical records enable populating the German ex situ genebank bio-digital resource center of barley (Hordeum sp.) with information on resistances to soilborne barley mosaic viruses.
Theor Appl Genet
; 134(7): 2181-2196, 2021 Jul.
Article
en En
| MEDLINE
| ID: mdl-33768281
KEY MESSAGE: Genomic prediction with special weight of major genes is a valuable tool to populate bio-digital resource centers. Phenotypic information of crop genetic resources is a prerequisite for an informed selection that aims to broaden the genetic base of the elite breeding pools. We investigated the potential of genomic prediction based on historical screening data of plant responses against the Barley yellow mosaic viruses for populating the bio-digital resource center of barley. Our study includes dense marker data for 3838 accessions of winter barley, and historical screening data of 1751 accessions for Barley yellow mosaic virus (BaYMV) and of 1771 accessions for Barley mild mosaic virus (BaMMV). Linear mixed models were fitted by considering combinations for the effects of genotypes, years, and locations. The best linear unbiased estimations displayed a broad spectrum of plant responses against BaYMV and BaMMV. Prediction abilities, computed as correlations between predictions and observed phenotypes of accessions, were low for the marker-assisted selection approach amounting to 0.42. In contrast, prediction abilities of genomic best linear unbiased predictions were high, with values of 0.62 for BaYMV and 0.64 for BaMMV. Prediction abilities of genomic prediction were improved by up to ~ 5% using W-BLUP, in which more weight is given to markers with significant major effects found by association mapping. Our results outline the utility of historical screening data and W-BLUP model to predict the performance of the non-phenotyped individuals in genebank collections. The presented strategy can be considered as part of the different approaches used in genebank genomics to valorize genetic resources for their usage in disease resistance breeding and research.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Enfermedades de las Plantas
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Hordeum
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Potyviridae
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Resistencia a la Enfermedad
Tipo de estudio:
Prognostic_studies
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Risk_factors_studies
Idioma:
En
Revista:
Theor Appl Genet
Año:
2021
Tipo del documento:
Article
País de afiliación:
Alemania
Pais de publicación:
Alemania