Genomic prediction in
SNP markers
genomic prediction
imputation
whole-genome sequencing
Journal
Genome
ISSN: 1480-3321
Titre abrégé: Genome
Pays: Canada
ID NLM: 8704544
Informations de publication
Date de publication:
06 May 2024
06 May 2024
Historique:
medline:
6
5
2024
pubmed:
6
5
2024
entrez:
6
5
2024
Statut:
aheadofprint
Résumé
Advances in sequencing technology allow whole plant genomes to be sequenced with high quality. Combining genotypic and phenotypic data in genomic prediction helps breeders to select crossing partners in partially phenotyped populations. In plant breeding programs, the cost of sequencing entire breeding populations still exceeds available genotyping budgets. Hence, the method for genotyping is still mainly single nucleotide polymorphism (SNP) arrays; however, arrays are unable to assess the entire genome- and population-wide diversity. A compromise involves genotyping the entire population using an SNP array and a subset of the population with whole-genome sequencing. Both datasets can then be used to impute markers from whole-genome sequencing onto the entire population. Here, we evaluate whether imputation of whole-genome sequencing data enhances genomic predictions, using data from a nested association mapping population of rapeseed (
Identifiants
pubmed: 38708850
doi: 10.1139/gen-2023-0126
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Déclaration de conflit d'intérêts
Amine Abbadi and Tobias Kox are employed at NPZ innovation GmbH. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.