High-throughput genotyping by whole-genome resequencing

  1. Xuehui Huang1,6,
  2. Qi Feng1,2,6,
  3. Qian Qian3,6,
  4. Qiang Zhao1,2,6,
  5. Lu Wang1,6,
  6. Ahong Wang1,6,
  7. Jianping Guan1,
  8. Danlin Fan1,
  9. Qijun Weng1,
  10. Tao Huang1,
  11. Guojun Dong3,
  12. Tao Sang1,4 and
  13. Bin Han1,5,7
  1. 1 National Center for Gene Research and Institute of Plant Physiology and Ecology, Shanghai Institutes of Biological Sciences, Chinese Academy of Sciences, Shanghai 200233, China;
  2. 2 College of Life Science and Biotechnology, Shanghai Jiaotong University, Shanghai 200240, China;
  3. 3 State Key Lab of Rice Biology, China National Rice Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou 310006, China;
  4. 4 Department of Plant Biology, Michigan State University, East Lansing, Michigan 48824, USA;
  5. 5 Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100029, China
    1. 6 These authors contributed equally to this work.

    Abstract

    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 ∼20× faster in data collection and 35× 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.

    Footnotes

    • 7 Corresponding author.

      E-mail bhan{at}ncgr.ac.cn; fax 86-21-64825775.

    • [Supplemental material is available online at www.genome.org. Pseudomolecules harboring 1,226,791 SNPs identified between Oryza sativa ssp. indica cv. 9311 and ssp. japonica cv. Nipponbare are available at http://www.ncgr.ac.cn/english/edatabase.htm. The raw Illumina sequencing data are available in the EBI European Nucleotide Archive (ftp://ftp.era.ebi.ac.uk/) with accession number ERA000078.]

    • Article published online before print. Article and publication date are at http://www.genome.org/cgi/doi/10.1101/gr.089516.108.

      • Received November 24, 2008.
      • Accepted March 23, 2009.
    • Freely available online through the Genome Research Open Access option.

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