Genomic prediction in a multiploid crop: genotype by environment interaction and allele dosage effects on predictive ability in banana

Vista sencilla de ítem
dc.creatorNyine, M.
dc.creatorUwimana, Brigitte
dc.creatorBlavet, N.
dc.creatorHřibová, E.
dc.creatorVanrespaille, H.
dc.creatorBatte, M.
dc.creatorAkech, V.
dc.creatorBrown, A.
dc.creatorLorenzen, J.H.
dc.creatorSwennen, Rony L.
dc.creatorDoležel, Jaroslav
dc.date2018-07-01
dc.date2018-05-16T14:13:18Z
dc.date2018-05-16T14:13:18Z
dc.date.accessioned2026-06-27T13:49:54Z
dc.descriptionImproving the efficiency of selection in conventional crossbreeding is a major priority in banana (Musa spp.) breeding. Routine application of classical marker assisted selection (MAS) is lagging in banana due to limitations in MAS tools. Genomic selection (GS) based on genomic prediction models can address some limitations of classical MAS, but the use of GS in banana has not been reported to date. The aim of this study was to evaluate the predictive ability of six genomic prediction models for 15 traits in a multi-ploidy training population. The population consisted of 307 banana genotypes phenotyped under low and high input field management conditions for two crop cycles. The single nucleotide polymorphism (SNP) markers used to fit the models were obtained from genotyping by sequencing (GBS) data. Models that account for additive genetic effects provided better predictions with 12 out of 15 traits. The performance of BayesB model was superior to other models particularly on fruit filling and fruit bunch traits. Models that included averaged environment data were more robust in trait prediction even with a reduced number of markers. Accounting for allele dosage in SNP markers (AD-SNP) reduced predictive ability relative to traditional bi-allelic SNP (BA-SNP), but the prediction trend remained the same across traits. The high predictive values (0.47– 0.75) of fruit filling and fruit bunch traits show the potential of genomic prediction to increase selection efficiency in banana breeding.
dc.formatapplication/pdf
dc.identifierhttps://hdl.handle.net/10568/92577
dc.identifier.urihttp://hdl.handle.net/123456789/67112
dc.languageen
dc.publisherWiley
dc.rightsOpen Access
dc.sourceNyine, M., Uwimana, B., Blavet, N., Hřibová, E., Vanrespaille, H., Batte, M., ... & Doležel, J. (2018). Genomic prediction in a multiploid crop: genotype by environment interaction and allele dosage effects on predictive ability in banana. Plant Genome, 1-16.
dc.subjectbananas
dc.subjectmusa
dc.subjectgenotypes
dc.subjectgenomic prediction
dc.subjectgenotype by environment interaction
dc.subjectallele dosage
dc.titleGenomic prediction in a multiploid crop: genotype by environment interaction and allele dosage effects on predictive ability in banana
dc.typeJournal Article

Archivos

Colecciones

Bioversity International