AUTHOR=Cockerton Helen M. , Karlström Amanda , Johnson Abigail W. , Li Bo , Stavridou Eleftheria , Hopson Katie J. , Whitehouse Adam B. , Harrison Richard J. 

TITLE=Genomic Informed Breeding Strategies for Strawberry Yield and Fruit Quality Traits

JOURNAL=Frontiers in Plant Science

VOLUME=Volume 12 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2021.724847

DOI=10.3389/fpls.2021.724847

ISSN=1664-462X

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 report extensive phenotyping of fruit quality and yield traits in a multi-parental strawberry population to allow genomic prediction and 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 highlights 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 QTL was associated with perceived acidity and pH whereas multiple loci were associated with firmness traits, we therefore recommend the implementation of both MAS and genomic prediction to capture the observed variation respectively. Furthermore, we identify 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 suggest 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 to mass traits. As such, selecting using “number” traits should lead to faster genetic gain.