Strawberry fruit shape: quantification by image analysis and QTL detection by genome-wide association analysis.

Abstract

Fruit shape of cultivated strawberry ( Fragaria × ananassa Duch.) is an important breeding target. To detect genomic regions associated with this trait, its quantitative evaluation is needed. Previously we created a multi-parent advanced-generation inter-cross (MAGIC) strawberry population derived from six founder parents. In this study, we used this population to quantify fruit shape. Elliptic Fourier descriptors (EFDs) were generated from 2 969 two-dimensional binarized fruit images, and principal component (PC) scores were calculated on the basis of the EFD coefficients. PC1-PC3 explained 96% of variation in shape and thus adequately quantified it. In genome-wide association study, the PC scores were used as phenotypes. Genome wide association study using mixed linear models revealed 2 quantitative trait loci (QTLs) for fruit shape. Our results provide a novel and effective method to analyze strawberry fruit morphology; the detected QTLs and presented method can support marker-assisted selection in practical breeding programs to improve fruit shape.

Plant phenotyping relevance

画像解析と楕円フーリエ記述子によりイチゴ果実形状を定量化する手法が研究の中心であり、育種への応用も示しているため。

Code and data availability

The paper describes strawberry fruit image analysis (SIAnalysis, SHAPE on R) and GWAS on a MAGIC population, but no public deposit of the 2,969 fruit images, phenotype data, or author analysis code is stated. The only URLs in the text are cited references (qqman preprint, MAFF test guidelines, Tokyo market statistics),

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