Genetic Analysis of Walnut ( Juglans regia L.) Pellicle Pigment Variation Through a Novel, High-Throughput Phenotyping Platform.

Abstract

Abstract Walnut pellicle color is a key quality attribute that drives consumer preference and walnut sales. For the first time a high-throughput, computer vision-based phenotyping platform using a custom algorithm to quantitatively score each walnut pellicle in L* a* b* color space was deployed at large-scale. This was compared to traditional qualitative scoring by eye and was used to dissect the genetics of pellicle pigmentation. Progeny from both a bi-parental population of 168 trees (‘Chandler’ × ‘Idaho’) and a genome-wide association (GWAS) with 528 trees of the UC Davis Walnut Improvement Program were analyzed. Color phenotypes were found to have overlapping regions in the ‘Chandler’ genetic map on Chr01 suggesting complex genetic control. In the GWAS population, multiple, small effect QTL across Chr01, Chr07, Chr08, Chr09, Chr10, Chr12 and Chr13 were discovered. Marker trait associations were co-localized with QTL mapping on Chr01, Chr10, Chr14, and Chr16. Putative candidate genes controlling walnut pellicle pigmentation were postulated.

Plant phenotyping relevance

クルミ果皮色を対象に、コンピュータビジョンと独自アルゴリズムで色形質を定量化する高スループット表現型解析プラットフォームを開発・適用しており、手法が研究の中心である。

Code and data availability

The paper's supplemental files on figshare contain the paper-specific phenotyping assets: raw color score data for both populations, CVS calibration and CIE analysis FIJI macros (analysis code), genetic maps with phenotypic data, breeding value phenotypes, and GWAS principal components. The figshare DOI is explicitly a