High-throughput genotyping by whole-genome resequencing

文献类型： 外文期刊

第一作者： Huang, Xuehui

作者： Huang, Xuehui;Feng, Qi;Zhao, Qiang;Wang, Lu;Wang, Ahong;Guan, Jianping;Fan, Danlin;Weng, Qijun;Huang, Tao;Sang, Tao;Han, Bin;Huang, Xuehui;Feng, Qi;Zhao, Qiang;Wang, Lu;Wang, Ahong;Guan, Jianping;Fan, Danlin;Weng, Qijun;Huang, Tao;Sang, Tao;Han, Bin;Feng, Qi;Zhao, Qiang;Qian, Qian;Dong, Guojun;Sang, Tao;Han, Bin

作者机构：

期刊名称：GENOME RESEARCH （ 影响因子：9.043； 五年影响因子：12.808 ）

ISSN： 1088-9051

年卷期： 2009 年 19 卷 6 期

页码：

收录情况： SCI

摘要： The next-generation sequencing technology coupled with the growing number of genome sequences opens the opportunity to redesign genotyping strategies for more effective genetic mapping and genome analysis. We have developed a high-throughput method for genotyping recombinant populations utilizing whole-genome resequencing data generated by the Illumina Genome Analyzer. A sliding window approach is designed to collectively examine genome-wide single nucleotide polymorphisms for genotype calling and recombination breakpoint determination. Using this method, we constructed a genetic map for 150 rice recombinant inbred lines with an expected genotype calling accuracy of 99.94% and a resolution of recombination breakpoints within an average of 40 kb. In comparison to the genetic map constructed with 287 PCR-based markers for the rice population, the sequencing-based method was; 203 faster in data collection and 353 more precise in recombination breakpoint determination. Using the sequencing-based genetic map, we located a quantitative trait locus of large effect on plant height in a 100-kb region containing the rice "green revolution'' gene. Through computer simulation, we demonstrate that the method is robust for different types of mapping populations derived from organisms with variable quality of genome sequences and is feasible for organisms with large genome sizes and low polymorphisms. With continuous advances in sequencing technologies, this genome-based method may replace the conventional marker-based genotyping approach to provide a powerful tool for large-scale gene discovery and for addressing a wide range of biological questions.

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