AAQSP increases mapping resolution of stable QTLs through applying NGS-BSA in multiple genetic backgrounds.

KEY MESSAGE: In this study, we present AAQSP as an extension of existing NGS-BSA applications for identifying stable QTLs at high resolution. GhPAP16 and GhIQD14 fine mapped on chromosome D09 of upland cotton are identified as important candidate genes for lint percentage (LP). Bulked segregant analysis combined with next generation sequencing (NGS-BSA) allows rapid identification of genome sequence differences responsible for phenotypic variation. The NGS-BSA approach applied to crops mainly depends on comparing two bulked DNA samples of individuals from an F2 population. Since some F2 individuals still maintain high heterozygosity, heterosis will exert complications in pursuing NGS-BSA in such populations. In addition, the genetic background influences the stability of gene expression in crops, so some QTLs mapped in one segregating population may not be widely applied in crop improvement. The AAQSP (Association Analysis of QTL-seq on Semi-homologous Populations) reported in our study combines the optimized scheme of constructing BSA bulks with NGS-BSA analysis in two (or more) different parental genetic backgrounds for isolating the stable QTLs. With application of AAQSP strategy and construction of a high-density linkage map, we have successfully identified a QTL significantly related to lint percentage (LP) in cultivated upland cotton, followed by map-based cloning to dissect two candidate genes, GhPAP16 and GhIQD14. This study demonstrated that AAQSP can efficiently identify stable QTLs for complex traits of interest, and thus accelerate the genetic improvement of upland cotton and other crop plants.