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High-resolution mapping of copy-number alterations with massively parallel sequencing

Nature Methods volume 6, pages 99–103 (2009)Cite this article

Abstract

Cancer results from somatic alterations in key genes, including point mutations, copy-number alterations and structural rearrangements. A powerful way to discover cancer-causing genes is to identify genomic regions that show recurrent copy-number alterations (gains and losses) in tumor genomes. Recent advances in sequencing technologies suggest that massively parallel sequencing may provide a feasible alternative to DNA microarrays for detecting copy-number alterations. Here we present: (i) a statistical analysis of the power to detect copy-number alterations of a given size; (ii) SegSeq, an algorithm to segment equal copy numbers from massively parallel sequence data; and (iii) analysis of experimental data from three matched pairs of tumor and normal cell lines. We show that a collection of ∼14 million aligned sequence reads from human cell lines has comparable power to detect events as the current generation of DNA microarrays and has over twofold better precision for localizing breakpoints (typically, to within ∼1 kilobase).

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Figure 1: Theoretical coverage required to detect single-copy gains and losses.
Figure 2: Segmentation algorithm for aligned sequenced reads.
Figure 3: Mapping the chromosomal breakpoints of homozygous deletions.

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Acknowledgements

We thank C. Mermel, M. Berger and E. Hom for commenting on the manuscript. This work was supported by the US National Institutes of Health (grants 5U24CA126546 to M.M. and 5U54HG003-67 to E.S.L.).

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Author notes

  1. Derek Y Chiang and Gad Getz: These authors contributed equally to this work.

Authors and Affiliations

  1. Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, 7 Cambridge Center, Cambridge, 02142, Massachusetts, USA

    Derek Y Chiang, Gad Getz, David B Jaffe, Michael J T O'Kelly, Scott L Carter, Carsten Russ, Chad Nusbaum, Matthew Meyerson & Eric S Lander

  2. Department of Medical Oncology and Center for Cancer Genome Discovery, Dana-Farber Cancer Institute, 44 Binney Street, Boston, 02115, Massachusetts, USA

    Derek Y Chiang & Matthew Meyerson

  3. Novartis Institutes for Biomedical Research, 250 Massachusetts Avenue, Cambridge, 02139, Massachusetts, USA

    Xiaojun Zhao

  4. The Harvard-MIT Division of Health Sciences and Technology, 77 Massachusetts Ave., Cambridge, 02139, Massachusetts, USA

    Scott L Carter

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  1. Derek Y Chiang
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Contributions

D.Y.C., G.G., D.B.J., M.M. and E.S.L. designed the study; D.B.J., C.R., C.N. and E.S.L. oversaw sequencing and alignment; D.Y.C. and G.G. created the segmentation algorithm; D.Y.C. and X.Z. experimentally mapped breakpoints; D.Y.C., G.G., D.B.J., M.J.T.O.'K., X.Z., S.L.C., C.R, C.N., M.M. and E.S.L. analyzed the data; D.Y.C., G.G., M.M. and E.S.L. wrote the manuscript.

Corresponding author

Correspondence to Eric S Lander.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–14, Supplementary Tables 1–3, Supplementary Methods (PDF 1625 kb)

Supplementary Data

Chromosomal breakpoints and copy-number ratios inferred from the segmentation of sequencing data from HCC1954, HCC1143 or NCI-H2347. (PDF 316 kb)

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Chiang, D., Getz, G., Jaffe, D. et al. High-resolution mapping of copy-number alterations with massively parallel sequencing. Nat Methods 6, 99–103 (2009). https://doi.org/10.1038/nmeth.1276

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