Reverse BSA-QTLseq: a new genotype-driven bioinformatics approach for simultaneous trait mapping
Author(s)
Date Issued
2025
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article
Journal
Abstract
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 leverages genotype-driven bulk reconstruction through bioinformatics, enabling the simultaneous mapping of multiple traits from the same genotypic dataset. The Reverse BSA-QTLseq approach employs a two-step strategy - low-resolution genotyping of the entire population followed by high-resolution sequencing of selected bulks - enabling cost-effective prioritization of genetically informative lines to enhance the discovery of quantitative trait loci (QTLs). Using a bread wheat recombinant inbred line (RIL) population as a case study, loci associated with heading date (HD) and plant height (PH) were mapped, confirming approximately 95% of known QTLs, including dwarfing genes (e.g., Rht-B1, Rht-5) and flowering-time regulators (e.g., Vrn-A1), as well as identifying 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 of the parental lines of the RIL population, from which the bulks were derived, aided in identifying candidate genes and regulatory networks underlying trait variation, including loci associated with photoperiod response, nutrient transport, and stress adaptation. The versatility and potential for data reuse of 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 improvements in crops.
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