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

Nature volume 407, pages 513516 (28 September 2000) | Download Citation

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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.

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Acknowledgements

We are indebted to the staff of the Whitehead Institute/MIT Center for Genome Research Sequencing Center for high-throughput sequencing and to N. Stange-Thomann for contributions to library construction. We would like to thank B. Blumenstiel and R. Lane for library construction and SNP validation, and M. Molla, L. Friedland, J. Ireland and B. Gilman for informatics assistance. We appreciate helpful discussions with members of The SNP Consortium, as well as colleagues at the Whitehead/MIT Genome Center. D.A. is a recipient of a Howard Hughes Medical Institute Postdoctoral Fellowship for Physicians. C.R.C. is supported by the Cancer Research Fund of the Damon Runyon / Walter Winchell Foundation. This work was conducted under grants from the Wellcome Trust and The SNP Consortium to E.S.L.

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Affiliations

  1. *Whitehead Institute/MIT Center for Genome Research, Nine Cambridge Center, Cambridge, Massachusetts 02142, USA

    • David Altshuler
    • , Victor J. Pollara
    • , Chris R. Cowles
    • , William J. Van Etten
    • , Jennifer Baldwin
    • , Lauren Linton
    •  & Eric S. Lander
  2. †Diabetes Unit, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston , Massachusetts 02114, USA

    • David Altshuler
  3. ‡Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA

    • Eric S. Lander

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Correspondence to Eric S. Lander.

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https://doi.org/10.1038/35035083

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