Theoretical and applied studies demonstrate the difficulty of detecting extremely over-dominant and smalleffect genes for quantitative traits via bulked segregant analysis(BSA)in an F_(2)population.To address this iss...Theoretical and applied studies demonstrate the difficulty of detecting extremely over-dominant and smalleffect genes for quantitative traits via bulked segregant analysis(BSA)in an F_(2)population.To address this issue,we proposed an integrated strategy for mapping various types of quantitative trait loci(QTLs)for quantitative traits via a combination of BSA and whole-genome sequencing.In this strategy,the numbers of read counts of marker alleles in two extreme pools were used to predict the numbers of read counts of marker genotypes.These observed and predicted numbers were used to construct a new statistic,G_(w),for detecting quantitative trait genes(QTGs),and the method was named dQTG-seq1.This method was significantly better than existing BSA methods.If the goal was to identify extremely over-dominant and smalleffect genes,another reserved DNA/RNA sample from each extreme phenotype F_(2)plant was sequenced,and the observed numbers of marker alleles and genotypes were used to calculate G_(w)to detect QTGs;this method was named dQTG-seq2.In simulated and real rice dataset analyses,dQTG-seq2 could identify many more extremely over-dominant and small-effect genes than BSA and QTL mapping methods.dQTGseq2 may be extended to other heterogeneous mapping populations.The significance threshold of G_(w)in this study was determined by permutation experiments.In addition,a handbook for the R software dQTG.seq,which is available at https://cran.r-project.org/web/packages/dQTG.seq/index.html,has been provided in the supplemental materials for the users’convenience.This study provides a new strategy for identifying all types of QTLs for quantitative traits in an F_(2)population.展开更多
基金This work was supported by the National Natural Science Foundation of China(32070557 and 31871242)the Fundamental Research Funds for the Central Universities(2662020ZKPY017)the Huazhong Agricul-tural University Scientific and Technological Self-Innovation Foundation(2014RC020).
文摘Theoretical and applied studies demonstrate the difficulty of detecting extremely over-dominant and smalleffect genes for quantitative traits via bulked segregant analysis(BSA)in an F_(2)population.To address this issue,we proposed an integrated strategy for mapping various types of quantitative trait loci(QTLs)for quantitative traits via a combination of BSA and whole-genome sequencing.In this strategy,the numbers of read counts of marker alleles in two extreme pools were used to predict the numbers of read counts of marker genotypes.These observed and predicted numbers were used to construct a new statistic,G_(w),for detecting quantitative trait genes(QTGs),and the method was named dQTG-seq1.This method was significantly better than existing BSA methods.If the goal was to identify extremely over-dominant and smalleffect genes,another reserved DNA/RNA sample from each extreme phenotype F_(2)plant was sequenced,and the observed numbers of marker alleles and genotypes were used to calculate G_(w)to detect QTGs;this method was named dQTG-seq2.In simulated and real rice dataset analyses,dQTG-seq2 could identify many more extremely over-dominant and small-effect genes than BSA and QTL mapping methods.dQTGseq2 may be extended to other heterogeneous mapping populations.The significance threshold of G_(w)in this study was determined by permutation experiments.In addition,a handbook for the R software dQTG.seq,which is available at https://cran.r-project.org/web/packages/dQTG.seq/index.html,has been provided in the supplemental materials for the users’convenience.This study provides a new strategy for identifying all types of QTLs for quantitative traits in an F_(2)population.
