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An SNP map of the human genome generated by reduced representation shotgun sequencing

Author

Listed:
  • David Altshuler

    (Whitehead Institute/MIT Center for Genome Research, Nine Cambridge Center
    Diabetes Unit, Harvard Medical School)

  • Victor J. Pollara

    (Whitehead Institute/MIT Center for Genome Research, Nine Cambridge Center)

  • Chris R. Cowles

    (Whitehead Institute/MIT Center for Genome Research, Nine Cambridge Center)

  • William J. Van Etten

    (Whitehead Institute/MIT Center for Genome Research, Nine Cambridge Center)

  • Jennifer Baldwin

    (Whitehead Institute/MIT Center for Genome Research, Nine Cambridge Center)

  • Lauren Linton

    (Whitehead Institute/MIT Center for Genome Research, Nine Cambridge Center)

  • Eric S. Lander

    (Whitehead Institute/MIT Center for Genome Research, Nine Cambridge Center
    Massachusetts Institute of Technology)

Abstract

Most genomic variation is attributable to single nucleotide polymorphisms (SNPs), which therefore offer the highest resolution for tracking disease genes and population history1,2,3. It has been proposed that a dense map of 30,000–500,000 SNPs can be used to scan the human genome for haplotypes associated with common diseases4,5,6. Here we describe a simple but powerful method, called reduced representation shotgun (RRS) sequencing, for creating SNP maps. RRS re-samples specific subsets of the genome from several individuals, and compares the resulting sequences using a highly accurate SNP detection algorithm. The method can be extended by alignment to available genome sequence, increasing the yield of SNPs and providing map positions. These methods are being used by The SNP Consortium, an international collaboration of academic centres, pharmaceutical companies and a private foundation, to discover and release at least 300,000 human SNPs. We have discovered 47,172 human SNPs by RRS, and in total the Consortium has identified 148,459 SNPs. More broadly, RRS facilitates the rapid, inexpensive construction of SNP maps in biomedically and agriculturally important species. SNPs discovered by RRS also offer unique advantages for large-scale genotyping.

Suggested Citation

  • David Altshuler & Victor J. Pollara & Chris R. Cowles & William J. Van Etten & Jennifer Baldwin & Lauren Linton & Eric S. Lander, 2000. "An SNP map of the human genome generated by reduced representation shotgun sequencing," Nature, Nature, vol. 407(6803), pages 513-516, September.
    • Handle: RePEc:nat:nature:v:407:y:2000:i:6803:d:10.1038_35035083
    DOI: 10.1038/35035083
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    Cited by:

    1. Sean Myles & Jer-Ming Chia & Bonnie Hurwitz & Charles Simon & Gan Yuan Zhong & Edward Buckler & Doreen Ware, 2010. "Rapid Genomic Characterization of the Genus Vitis," PLOS ONE, Public Library of Science, vol. 5(1), pages 1-9, January.
    2. Alexander R Macalalad & Michael C Zody & Patrick Charlebois & Niall J Lennon & Ruchi M Newman & Christine M Malboeuf & Elizabeth M Ryan & Christian L Boutwell & Karen A Power & Doug E Brackney & Kendr, 2012. "Highly Sensitive and Specific Detection of Rare Variants in Mixed Viral Populations from Massively Parallel Sequence Data," PLOS Computational Biology, Public Library of Science, vol. 8(3), pages 1-10, March.

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