Suitability of Single-Nucleotide Polymorphism Arrays Versus Genotyping-By-Sequencing for Genebank Genomics in Wheat.
genebank genomics
genome-wide prediction
genotyping-by-sequencing (GBS)
molecular diversity
simple sequence repeats (SSR)
single-nucleotide polymorphism (SNPs)
wheat
Journal
Frontiers in plant science
ISSN: 1664-462X
Titre abrégé: Front Plant Sci
Pays: Switzerland
ID NLM: 101568200
Informations de publication
Date de publication:
2020
2020
Historique:
received:
15
10
2019
accepted:
13
01
2020
entrez:
3
3
2020
pubmed:
3
3
2020
medline:
3
3
2020
Statut:
epublish
Résumé
Genebank genomics promises to unlock valuable diversity for plant breeding but first, one key question is which marker system is most suitable to fingerprint entire genebank collections. Using wheat as model species, we tested for the presence of an ascertainment bias and investigated its impact on estimates of genetic diversity and prediction ability obtained using three marker platforms: simple sequence repeat (SSR), genotyping-by-sequencing (GBS), and array-based SNP markers. We used a panel of 378 winter wheat genotypes including 190 elite lines and 188 plant genetic resources (PGR), which were phenotyped in multi-environmental trials for grain yield and plant height. We observed an ascertainment bias for the array-based SNP markers, which led to an underestimation of the molecular diversity within the population of PGR. In contrast, the marker system played only a minor role for the overall picture of the population structure and precision of genome-wide predictions. Interestingly, we found that rare markers contributed substantially to the prediction ability. This combined with the expectation that valuable novel diversity is most likely rare suggests that markers with minor allele frequency deserve careful consideration in the design of a pre-breeding program.
Identifiants
pubmed: 32117381
doi: 10.3389/fpls.2020.00042
pmc: PMC7033508
doi:
Types de publication
Journal Article
Langues
eng
Pagination
42Informations de copyright
Copyright © 2020 Chu, Zhao, Beier, Schulthess, Stein, Philipp, Röder and Reif.
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