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Genomic Informed Breeding Strategies for Strawberry Yield and Fruit Quality Traits

Cockerton, Helen M., Kalrström, Amanda, Johnson, Abigail W., Li, Bo, Stavridou, Eleftheria, Hopson, Katie J., Whitehouse, Adam B., Harrison, Richard J. (2021) Genomic Informed Breeding Strategies for Strawberry Yield and Fruit Quality Traits. Frontiers in Plant Science, 12 . Article Number 724847. E-ISSN 1664-462X. (doi:10.3389/fpls.2021.724847) (KAR id:93841)

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Official URL
http://dx.doi.org/10.3389/fpls.2021.724847

Abstract

Over the last two centuries, breeders have drastically modified the fruit quality of strawberries through artificial selection. However, there remains significant variation in quality across germplasm with scope for further improvements to be made. We reported extensive phenotyping of fruit quality and yield traits in a multi-parental strawberry population to allow genomic prediction and quantitative trait nucleotide (QTN) identification, thereby enabling the description of genetic architecture to inform the efficacy of implementing advanced breeding strategies. A negative relationship (r = -0.21) between total soluble sugar content and class one yield was identified, indicating a trade-off between these two essential traits. This result highlighted an established dilemma for strawberry breeders and a need to uncouple the relationship, particularly under June-bearing, protected production systems comparable to this study. A large effect of quantitative trait nucleotide was associated with perceived acidity and pH whereas multiple loci were associated with firmness. Therefore, we recommended the implementation of both marker assisted selection (MAS) and genomic prediction to capture the observed variation respectively. Furthermore, we identified a large effect locus associated with a 10% increase in the number of class one fruit and a further 10 QTN which, when combined, are associated with a 27% increase in the number of marketable strawberries. Ultimately, our results suggested that the best method to improve strawberry yield is through selecting parental lines based upon the number of marketable fruits produced per plant. Not only were strawberry number metrics less influenced by environmental fluctuations, but they had a larger additive genetic component when compared with mass traits. As such, selecting using "number" traits should lead to faster genetic gain.

Item Type: Article
DOI/Identification number: 10.3389/fpls.2021.724847
Uncontrolled keywords: QTL mapping; achene; acidity; breeding; flavour; genomic prediction; organoleptic; yield.
Subjects: Q Science > QH Natural history > QH426 Genetics
Q Science > QP Physiology (Living systems)
Divisions: Divisions > Division of Natural Sciences > Biosciences
Funders: Innovate UK (https://ror.org/05ar5fy68)
Biotechnology and Biological Sciences Research Council (https://ror.org/00cwqg982)
Depositing User: Helen Cockerton
Date Deposited: 04 Apr 2022 14:27 UTC
Last Modified: 05 Apr 2022 08:26 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/93841 (The current URI for this page, for reference purposes)
Cockerton, Helen M.: https://orcid.org/0000-0002-7375-1804
Harrison, Richard J.: https://orcid.org/0000-0002-3307-3519
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