An optimal DNA pooling strategy for progressive fine mapping.
We present a cost-effective DNA pooling strategy for fine mapping of a single Mendelian gene in controlled crosses. The theoretical argument suggests that it is potentially possible for a single-stage pooling approach to reduce the overall experimental expense considerably by balancing costs for genotyping and sample collection. Further, the genotyping burden can be reduced through multi-stage pooling. Numerical results are provided for practical guidelines. For example, the genotyping effort can be reduced to only a small fraction of that needed for individual genotyping at a small loss of estimation accuracy or at a cost of increasing sample sizes slightly when recombination rates are 0.5% or less. An optimal two-stage pooling scheme can reduce the amount of genotyping to 19.5%, 14.5% and 6.4% of individual genotyping efforts for identifying a gene within 1, 0.5, and 0.1 cM, respectively. Finally, we use a genetic data set for mapping the rice xl(t) gene to demonstrate the feasibility and efficiency of the DNA pooling strategy. Taken together, the results demonstrate that this DNA pooling strategy can greatly reduce the genotyping burden and the overall cost in fine mapping experiments.
Chi
Xiao-Fei
XF
IAEA-Zhejiang University Collaborating Center and National Key Laboratory of Rice Biology, Institute of Nuclear Agricultural Sciences, Zhejiang University, 268 Kaixuan Road, Huajia Pool Campus, Hangzhou, 310029, People's Republic of China.
Lou
Xiang-Yang
XY
Yang
Mark C K
MC
Shu
Qing-Yao
QY
D002874:Chromosome Mapping / Q000191:economics / Q000379:methods*; D004247:DNA / Q000737:chemistry*; D005788:Gene Pool; D005838:Genotype; D008957:Models, Genetic; D012275:Oryza / Q000235:genetics
D004247:DNA