Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Protocol
  • Published:

Single-cell template strand sequencing by Strand-seq enables the characterization of individual homologs

Nature Protocols volume 12, pages 1151–1176 (2017)Cite this article

Subjects

Abstract

The ability to distinguish between genome sequences of homologous chromosomes in single cells is important for studies of copy-neutral genomic rearrangements (such as inversions and translocations), building chromosome-length haplotypes, refining genome assemblies, mapping sister chromatid exchange events and exploring cellular heterogeneity. Strand-seq is a single-cell sequencing technology that resolves the individual homologs within a cell by restricting sequence analysis to the DNA template strands used during DNA replication. This protocol, which takes up to 4 d to complete, relies on the directionality of DNA, in which each single strand of a DNA molecule is distinguished based on its 5′–3′ orientation. Culturing cells in a thymidine analog for one round of cell division labels nascent DNA strands, allowing for their selective removal during genomic library construction. To preserve directionality of template strands, genomic preamplification is bypassed and labeled nascent strands are nicked and not amplified during library preparation. Each single-cell library is multiplexed for pooling and sequencing, and the resulting sequence data are aligned, mapping to either the minus or plus strand of the reference genome, to assign template strand states for each chromosome in the cell. The major adaptations to conventional single-cell sequencing protocols include harvesting of daughter cells after a single round of BrdU incorporation, bypassing of whole-genome amplification, and removal of the BrdU+ strand during Strand-seq library preparation. By sequencing just template strands, the structure and identity of each homolog are preserved.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Overview of Strand-seq protocol.
Figure 2: Generation of directional template strand sequencing libraries.
Figure 3: Cell sorting gates based on Hoechst quenching.
Figure 4: Size selection of final Strand-seq library pool.
Figure 5: Important parameters when considering Strand-seq libraries.
Figure 6: Overview of genomic features evident from a Strand-seq experiment.
Figure 7: Probabilities for template strand changes to occur in the same vicinity between libraries.

Similar content being viewed by others

References

  1. Mills, R.E. et al. Mapping copy number variation by population-scale genome sequencing. Nature 470, 59–65 (2011).

    Article  CAS  Google Scholar 

  2. Sudmant, P.H. et al. An integrated map of structural variation in 2,504 human genomes. Nature 526, 75–81 (2015).

    Article  CAS  Google Scholar 

  3. Kandoth, C. et al. Mutational landscape and significance across 12 major cancer types. Nature 502, 333–339 (2013).

    Article  CAS  Google Scholar 

  4. Ciriello, G. et al. Emerging landscape of oncogenic signatures across human cancers. Nat. Genet. 45, 1127–1133 (2013).

    Article  CAS  Google Scholar 

  5. Alkan, C., Coe, B.P. & Eichler, E.E. Genome structural variation discovery and genotyping. Nat. Rev. Genet. 12, 363–376 (2011).

    Article  CAS  Google Scholar 

  6. Feuk, L. Inversion variants in the human genome: role in disease and genome architecture. Genome Med. 2, 11 (2010).

    Article  Google Scholar 

  7. Sindi, S.S. & Raphael, B.J. Identification of structural variation. in Genome Analysis: Current Procedures and Applications (ed. Poptsova, M.S.), (Caister Academic Press, 2014).

  8. Korbel, J.O. et al. PEMer: a computational framework with simulation-based error models for inferring genomic structural variants from massive paired-end sequencing data. Genome Biol. 10, R23 (2009).

    Article  Google Scholar 

  9. Ye, K., Schulz, M.H., Long, Q., Apweiler, R. & Ning, Z. Pindel: a pattern growth approach to detect break points of large deletions and medium sized insertions from paired-end short reads. Bioinformatics 25, 2865–2871 (2009).

    Article  CAS  Google Scholar 

  10. Rausch, T. et al. DELLY: structural variant discovery by integrated paired-end and split-read analysis. Bioinformatics 28, i333–i339 (2012).

    Article  CAS  Google Scholar 

  11. Xie, C. & Tammi, M.T. CNV-seq, a new method to detect copy number variation using high-throughput sequencing. BMC Bioinformatics 10, 80 (2009).

    Article  Google Scholar 

  12. Voet, T. et al. Single-cell paired-end genome sequencing reveals structural variation per cell cycle. Nucleic Acids Res. 41, 6119–6138 (2013).

    Article  CAS  Google Scholar 

  13. Nagano, T. et al. Single-cell Hi-C for genome-wide detection of chromatin interactions that occur simultaneously in a single cell. Nat. Protoc. 10, 1986–2003 (2015).

    Article  CAS  Google Scholar 

  14. Leung, M.L. et al. Highly multiplexed targeted DNA sequencing from single nuclei. Nat. Protoc. 11, 214–235 (2016).

    Article  CAS  Google Scholar 

  15. Bakker, B. et al. Single-cell sequencing reveals karyotype heterogeneity in murine and human malignancies. Genome Biol. 17, 115 (2016).

    Article  Google Scholar 

  16. van den Bos, H. et al. Single-cell whole genome sequencing reveals no evidence for common aneuploidy in normal and Alzheimer's disease neurons. Genome Biol. 17, 116 (2016).

    Article  Google Scholar 

  17. Navin, N.E. The first five years of single-cell cancer genomics and beyond. Genome Res. 25, 1499–1507 (2015).

    Article  CAS  Google Scholar 

  18. Navin, N. et al. Tumour evolution inferred by single-cell sequencing. Nature 472, 90–94 (2011).

    Article  CAS  Google Scholar 

  19. Macaulay, I.C. & Voet, T. Single cell genomics: advances and future perspectives. PLoS Genet. 10, e1004126 (2014).

    Article  Google Scholar 

  20. Falconer, E. et al. DNA template strand sequencing of single-cells maps genomic rearrangements at high resolution. Nat. Methods 9, 1107–1112 (2012).

    Article  CAS  Google Scholar 

  21. Sanders, A.D. et al. Characterizing polymorphic inversions in human genomes by single cell sequencing. Genome Res. 26, 1575–1587 (2016).

    Article  CAS  Google Scholar 

  22. Hills, M., O'Neill, K., Falconer, E., Brinkman, R. & Lansdorp, P.M. BAIT: organizing genomes and mapping rearrangements in single cells. Genome Med. 5, 82 (2013).

    Article  Google Scholar 

  23. Porubsky, D. et al. Building complete chromosomal haplotypes using single-cell sequencing. Genome Res. 26, 1565–1574 (2016).

    Article  CAS  Google Scholar 

  24. Falconer, E., Chavez, E., Henderson, A. & Lansdorp, P.M. Chromosome orientation fluorescence in situ hybridization to study sister chromatid segregation in vivo. Nat. Protoc. 5, 1362–1377 (2010).

    Article  CAS  Google Scholar 

  25. Smith, J.R. & Pereira-Smith, O.M. Replicative senescence: implications for in vivo aging and tumor suppression. Science 273, 63–67 (1996).

    Article  CAS  Google Scholar 

  26. Rabinovitch, P.S. Regulation of human fibroblast growth rate by both noncycling cell fraction transition probability is shown by growth in 5-bromodeoxyuridine followed by Hoechst 33258 flow cytometry. Proc. Natl. Acad. Sci. USA 80, 2951–2955 (1983).

    Article  CAS  Google Scholar 

  27. Poot, M., Silber, J.R. & Rabinovitch, P.S. A novel flow cytometric technique for drug cytotoxicity gives results comparable to colony-forming assays. Cytometry 48, 1–5 (2002).

    Article  CAS  Google Scholar 

  28. Latt, S.A., George, Y.S. & Gray, J.W. Flow cytometric analysis of bromodeoxyuridine-substituted cells stained with 33258 Hoechst. J. Histochem. Cytochem. 25, 927–934 (1977).

    Article  CAS  Google Scholar 

  29. Kubbies, M. & Rabinovitch, P.S. Flow cytometric analysis of factors which influence the BrdUrd-Hoechst quenching effect in cultivated human fibroblasts and lymphocytes. Cytometry 3, 276–281 (1983).

    Article  CAS  Google Scholar 

  30. Fogt, F. et al. Flow cytometric measurement of cell cycle kinetics in rat Walker-256 carcinoma following in vivo and in vitro pulse labelling with bromodeoxyuridine. Cytometry 12, 33–41 (1991).

    Article  CAS  Google Scholar 

  31. Langmead, B. & Salzberg, S.L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).

    Article  CAS  Google Scholar 

  32. Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).

    Article  Google Scholar 

  33. Lansdorp, P.M., Falconer, E., Tao, J., Brind'Amour, J. & Naumann, U. Epigenetic differences between sister chromatids? Ann. N. Y. Acad. Sci. 1266, 1–6 (2012).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

This work was 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), as well as an Advanced Grant (Nr 294740) from the European Research Council to P.M.L., and a Vanier Graduate Scholarship from the Natural Science and Engineering Research Council to A.D.S.

Author information

Authors and Affiliations

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

    Ashley D Sanders, Ester Falconer, Mark Hills & Peter M Lansdorp

  2. European Research Institute for the Biology of Ageing, University of Groningen, University Medical Centre Groningen, Groningen, the Netherlands

    Diana C J Spierings & Peter M Lansdorp

  3. Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia, Canada

    Peter M Lansdorp

Authors
  1. Ashley D Sanders
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ester Falconer
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mark Hills
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Diana C J Spierings
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Peter M Lansdorp
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

E.F. and A.D.S. developed and optimized the protocol. M.H. and A.D.S. designed bioinformatic analysis tools. D.C.J.S. established the protocol in a sister laboratory. A.D.S., M.H., D.C.J.S. and P.M.L. wrote the manuscript.

Corresponding author

Correspondence to Peter M Lansdorp.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Adapter and PCR primer oligonucleotides.

Sequence composition of the A) Illumina PE Adapters and B) PCR Primers required for the protocol. Following reconstitution, the adapters are annealed to generate a forked product. An internal hexamer barcode is included in the custom multiplexing primer PE 2.0, as indicated by ‘N’.

Supplementary Figure 2 PCR amplification reaction.

Inputs into the reaction mix are adapter ligation products (template strand as solid box, nicked BrdU strand as fragmented box) and PCR primers (Illumina PE 1.0 and custom multiplexing PE 2.0). The first round of amplification involves only primer PE 2.0, which anneals to the A1 adapter to initiate elongation (dashed blue line) and introduce the multiplexing barcode (red bar, labeled ‘B’) at the 3' end of the template molecule. The polymerase stalls on the fragmented BrdU-positive molecule (indicated with a blue square), terminating synthesis. The subsequent rounds of amplification (17 cycles in total) are exponential and involve both primers. The template strand is preferentially amplified during this reaction to produce a directional sequencing library. Apostrophes (e.g. A1’ or B’) are used to indicate complement DNA sequences.

Supplementary Figure 3 Size-selection using AMPure XP beads.

60ng of a 50 bp DNA ladder was input and Agencourt AMPure XP bead clean-up was performed using bead ratios of either 1.8x or 0.8x. The bioanalyzer trace illustrates the size range of products enriched for at each bead: DNA ratio, with the number of basepair (bp) indicated above each peak. The expected lengths of products and byproducts generated during the Strand-seq protocol are listed.

Supplementary Figure 4 Set up of magnetic bead separation block.

A) A solid rubber gasket (arrow) is placed around the magnet to slightly lift the 384-well plate and ensure the bead pellet is positioned lower in the well. This allows lower elution volumes and subsequently lower enzyme reaction volumes. As illustrated in B) the bead pellet remains submerged when lifted by the gasket (picture right), which is not the case when no gasket is used (picture left).

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–4, Supplementary Table 1 and Supplementary Methods. (PDF 1615 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sanders, A., Falconer, E., Hills, M. et al. Single-cell template strand sequencing by Strand-seq enables the characterization of individual homologs. Nat Protoc 12, 1151–1176 (2017). https://doi.org/10.1038/nprot.2017.029

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nprot.2017.029

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Advanced search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research