Article | Published:

DNA template strand sequencing of single-cells maps genomic rearrangements at high resolution

Nature Methods volume 9, pages 11071112 (2012) | Download Citation

Abstract

DNA rearrangements such as sister chromatid exchanges (SCEs) are sensitive indicators of genomic stress and instability, but they are typically masked by single-cell sequencing techniques. We developed Strand-seq to independently sequence parental DNA template strands from single cells, making it possible to map SCEs at orders-of-magnitude greater resolution than was previously possible. On average, murine embryonic stem (mES) cells exhibit eight SCEs, which are detected at a resolution of up to 23 bp. Strikingly, Strand-seq of 62 single mES cells predicts that the mm9 mouse reference genome assembly contains at least 17 incorrectly oriented segments totaling nearly 1% of the genome. These misoriented contigs and fragments have persisted through several iterations of the mouse reference genome and have been difficult to detect using conventional sequencing techniques. The ability to map SCE events at high resolution and fine-tune reference genomes by Strand-seq dramatically expands the scope of single-cell sequencing.

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Acknowledgements

We thank J. Brind'Amour and S. Rentas for discussions and J. Schein and C. Carter (Genome Sciences Centre) for BACs. We also thank K. Gan for help with preliminary MNase experiments. U.N. was supported by a Fellowship for Prospective Researchers from the Swiss National Science Foundation (project no. PBBEP3_131554). Work in the Hirst laboratory is supported by Canadian Institutes of Health Research grant RMF-92093. Work in the Lansdorp laboratory is supported by grants from the Canadian Institutes of Health Research (RMF-92093 and 105265), the US National Institutes of Health (R01GM094146) and the Terry Fox Foundation (018006). P.M.L. is a recipient of an Advanced Grant from the European Research Council.

Author information

Affiliations

  1. Terry Fox Laboratory, BC Cancer Agency, Vancouver, British Columbia, Canada.

    • Ester Falconer
    • , Mark Hills
    • , Ulrike Naumann
    • , Steven S S Poon
    • , Elizabeth A Chavez
    • , Ashley D Sanders
    •  & Peter M Lansdorp
  2. Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, British Columbia, Canada.

    • Yongjun Zhao
    •  & Martin Hirst
  3. Department of Microbiology and Immunology, Centre for High-Throughput Biology, University of British Columbia, Vancouver, British Columbia, Canada.

    • Martin Hirst
  4. Division of Hematology, Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.

    • Peter M Lansdorp
  5. European Research Institute for the Biology of Ageing, University Medical Center Groningen, Groningen, The Netherlands.

    • Peter M Lansdorp

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Contributions

E.F. designed experiments, prepared libraries and wrote the paper. M. Hills designed and refined the bioinformatic programs, performed the bioinformatic analysis and helped write the paper. U.N. made Fucci constructs, selected embryonic stem cells for studies and helped with preparation of libraries and writing of the paper. S.S.S.P. designed and wrote the additional bioinformatics programs. E.A.C. performed FISH experiments and cell synchronization and helped with preparation of libraries. A.D.S. helped with preparation of libraries. Y.Z. and M. Hirst participated in experimental design and data analysis. P.M.L. conceived of the study, interpreted results and wrote the paper.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Peter M Lansdorp.

Supplementary information

PDF files

  1. 1.

    Supplementary Text and Figures

    Supplementary Figures 1–14 and Supplementary Tables 1 and 2

  2. 2.

    Supplementary Data

    This PDF document provides chromosome ideograms and coverage statistics for four whole-genome shotgun (WGS) libraries and 62 Strand-seq libraries. The first two pages provide a summary table (pages 1–2) that lists all single-cell libraries, with clickable links to the ideograms. The table also summarizes library information such as cell input, synchronization and BrdU/Hoechst/UV treatment as well as coverage statistics including percent genomic coverage, the number of unique reads with a mapping quality score of at least 20 (q20, see Online Methods) and a summary of the number of observed chromosomes with SCEs or aneuploidy. Each library is presented on a single page (pages 3–68) with Watson and Crick reads mapped on chromosome ideograms (see main manuscript). The ideograms are the output of our bioinformatic analysis of inherited templates (BAIT) analysis pipeline (see Online Methods). The information from the summary table appears for each library. The average reads per megabase for both Watson and Crick reads appears below each chromosome in orange and blue numbers, respectively. Aneuploid chromosomes are identified with 'monosomy' or 'trisomy' written below the chromosome ideogram, with the percentage indicating the proportion of reads compared to the average genomic read depth. The overall reads per megabase for the entire genome is found in the bottom right of each page. Because the length of the horizontal orange and blue lines projecting from the chromosome ideograms represents the total number of reads per 200-kb bin (see main manuscript), the library ideograms were scaled to prevent high coverage libraries from overlapping between adjacent chromosomes (scale factor).

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DOI

https://doi.org/10.1038/nmeth.2206

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