Reverse BSA-QTLseq: A new genotype-driven bioinformatics approach for simultaneous trait mapping

Bulked segregant analysis (BSA) is a widely used method for identifying genomic loci associated with traits of interest in crops. However, conventional BSA is limited by its reliance on phenotype-driven bulk sampling, which restricts its scalability and confines its applicability to single-trait analysis. This study introduces a novel method, reverse BSA-QTLseq, which uses genotype-driven bulk reconstruction through bioinformatics, enabling the simultaneous mapping of multiple traits from the same genotypic dataset. Reverse BSA-QTLseq uses a two-step strategy-low-resolution genotyping of the entire population followed by high-resolution sequencing of selected bulks-enabling cost-effective identification of genetically divergent lines to enhance the discovery of quantitative trait loci (QTLs). Using a bread wheat recombinant inbred line (RIL) population as a case study, we mapped loci associated with heading date and plant height , confirming approximately 95% of known QTLs, including both dwarfing genes (e.g., Rht-B1 and Rht-5) and flowering-time regulators (e.g., Vrn-A1), and identified novel QTLs and candidate loci with strong phenotypic effects. The phased genotyping strategy maximized genetic distance in the initial sampling, facilitating the in silico reconstruction of trait-specific contrasting bulks. Integration of transcriptional profiles from the parental lines of the RIL population, from which the bulks were derived, aided in identifying candidate genes and regulatory networks underlying the variation of traits such as photoperiod response, nutrient transport, and stress adaptation. The versatility and potential for data reuse offered by the proposed method represent a significant advancement in QTL mapping, with broad implications for marker-assisted breeding and selection programs. Future integration of transcriptomic and epigenomic data is expected to further enhance the power of reverse BSA-QTLseq, accelerating genetic improvement in crops.