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dc.contributor.authorSverrisdóttir, Elsa
dc.contributor.authorByrne, Stephen
dc.contributor.authorSundmark, Ea Høegh Riis
dc.contributor.authorJohnsen, Heidi Øllegaard
dc.contributor.authorKirk, Hanne Grethe
dc.contributor.authorAsp, Torben
dc.contributor.authorJanss, Luc
dc.contributor.authorNielsen, Kåre L.
dc.date.accessioned2023-02-27T14:27:36Z
dc.date.available2023-02-27T14:27:36Z
dc.date.issued2017-07-13
dc.identifier.citationSverrisdóttir, E., Byrne, S., Sundmark, E.H.R. et al. Genomic prediction of starch content and chipping quality in tetraploid potato using genotyping-by-sequencing. Theor Appl Genet 130, 2091–2108 (2017). https://doi.org/10.1007/s00122-017-2944-yen_US
dc.identifier.urihttp://hdl.handle.net/11019/2894
dc.descriptionpeer-revieweden_US
dc.description.abstractGenomic prediction models for starch content and chipping quality show promising results, suggesting that genomic selection is a feasible breeding strategy in tetraploid potato. Genomic selection uses genome-wide molecular markers to predict performance of individuals and allows selections in the absence of direct phenotyping. It is regarded as a useful tool to accelerate genetic gain in breeding programs, and is becoming increasingly viable for crops as genotyping costs continue to fall. In this study, we have generated genomic prediction models for starch content and chipping quality in tetraploid potato to facilitate varietal development. Chipping quality was evaluated as the colour of a potato chip after frying following cold induced sweetening. We used genotyping-by-sequencing to genotype 762 offspring, derived from a population generated from biparental crosses of 18 tetraploid parents. Additionally, 74 breeding clones were genotyped, representing a test panel for model validation. We generated genomic prediction models from 171,859 single-nucleotide polymorphisms to calculate genomic estimated breeding values. Cross-validated prediction correlations of 0.56 and 0.73 were obtained within the training population for starch content and chipping quality, respectively, while correlations were lower when predicting performance in the test panel, at 0.30-0.31 and 0.42-0.43, respectively. Predictions in the test panel were slightly improved when including representatives from the test panel in the training population but worsened when preceded by marker selection. Our results suggest that genomic prediction is feasible, however, the extremely high allelic diversity of tetraploid potato necessitates large training populations to efficiently capture the genetic diversity of elite potato germplasm and enable accurate prediction across the entire spectrum of elite potatoes. Nonetheless, our results demonstrate that GS is a promising breeding strategy for tetraploid potato.en_US
dc.description.sponsorshipThe Danish Council of Strategic Research
dc.language.isoenen_US
dc.publisherSpringer Science and Business Media LLCen_US
dc.relation.ispartofseriesTheoretical and Applied Genetics;Vol 130
dc.rightsAttribution-NonCommercial-ShareAlike 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/*
dc.subjectGeneticsen_US
dc.subjectpotatoen_US
dc.subjectgenomic selectionen_US
dc.subjectBreeding strategyen_US
dc.subjectstarch contenten_US
dc.subjectchipping qualityen_US
dc.subjectvarietal developmenten_US
dc.titleGenomic prediction of starch content and chipping quality in tetraploid potato using genotyping-by-sequencingen_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.1007/s00122-017-2944-y
dc.contributor.sponsorThe Danish Council of Strategic Researchen_US
dc.contributor.sponsorThe Danish Council for Strategic Researchen_US
dc.contributor.sponsorGrantNumber12-132452en_US
dc.contributor.sponsorGrantNumber11-116190en_US
dc.source.volume130
dc.source.issue10
dc.source.beginpage2091
dc.source.endpage2108
refterms.dateFOA2023-02-27T14:27:37Z
dc.source.journaltitleTheoretical and Applied Genetics


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