In Frontiers in plant science
Wild species of lettuce (Lactuca sp.) are thought to have first been domesticated for oilseed contents to provide seed oil for human consumption. Although seed morphology is an important trait contributing to oilseed in lettuce, the underlying genetic mechanisms remain elusive. Since lettuce seeds are small, a manual phenotypic determination required for a genetic dissection of such traits is challenging. In this study, we built and applied an instance segmentation-based seed morphology quantification pipeline to measure traits in seeds generated from a cross between the domesticated oilseed type cultivar 'Oilseed' and the wild species 'UenoyamaMaruba' in an automated manner. Quantitative trait locus (QTL) mapping following ddRAD-seq revealed 11 QTLs linked to 7 seed traits (area, width, length, length-to-width ratio, eccentricity, perimeter length, and circularity). Remarkably, the three QTLs with the highest LOD scores, qLWR-3.1, qECC-3.1, and qCIR-3.1, for length-to-width ratio, eccentricity, and circularity, respectively, mapped to linkage group 3 (LG3) around 161.5 to 214.6 Mb, a region previously reported to be associated with domestication traits from wild species. These results suggest that the oilseed cultivar harbors genes acquired during domestication to control seed shape in this genomic region. This study also provides genetic evidence that domestication arose, at least in part, by selection for the oilseed type from wild species and demonstrates the effectiveness of image-based phenotyping to accelerate discoveries of the genetic basis for small morphological features such as seed size and shape.
Seki Kousuke, Toda Yosuke
2022
QTL mapping, ddRAD-seq, deep learning, lettuce domestication, neural network, seed morphology
