QTL Mapping of Leaf-Related Traits Using a High-Density Bin Map in Brassica rapa

Abstract

The species Brassica rapa includes enormous leafy vegetables with extreme leaf morphological diversity. Leaf traits such as size, shape, weight, and ratio of the leaf blade to the petiole contribute to yield, appearance, and desirability to consumers. These leaf-related traits are controlled by quantitative trait loci (QTLs). The construction of high-density bin maps using low-coverage sequencing is a powerful method for QTL fine-mapping and gene identification. In this study, we performed whole-genome re-sequencing of Wutacai ‘Zhongbaye’ and Chinese cabbage ‘HN53’ and 150 F2 individuals to construct a high-density bin map for QTL mapping of 11 leaf-related traits. The parental lines and F2 population were re-sequenced at 10x and 1x coverage, respectively. A map containing 565 bin markers was constructed based on parental single-nucleotide polymorphisms and a modified sliding window approach. The total map length was 944.6 cM and the average distance of the bins was 1.65 cM. In total, 60 significant QTLs controlling 11 leaf-related traits were detected. We further identified candidate genes responsible for these complex leaf-related traits. These findings suggest that this cost-effective bin-mapping approach is capable of rapid identification of QTLs and candidate genes, and will thus facilitate the dissection of the underlying molecular basis of leaf morphological variations and accelerate the improvement of B. rapa vegetable breeding.