Review Article | Published:

Single-cell sequencing-based technologies will revolutionize whole-organism science

Nature Reviews Genetics volume 14, pages 618630 (2013) | Download Citation

Abstract

The unabated progress in next-generation sequencing technologies is fostering a wave of new genomics, epigenomics, transcriptomics and proteomics technologies. These sequencing-based technologies are increasingly being targeted to individual cells, which will allow many new and longstanding questions to be addressed. For example, single-cell genomics will help to uncover cell lineage relationships; single-cell transcriptomics will supplant the coarse notion of marker-based cell types; and single-cell epigenomics and proteomics will allow the functional states of individual cells to be analysed. These technologies will become integrated within a decade or so, enabling high-throughput, multi-dimensional analyses of individual cells that will produce detailed knowledge of the cell lineage trees of higher organisms, including humans. Such studies will have important implications for both basic biological research and medicine.

Key points

  • Advances in DNA sequencing enable the analysis of the genomes and transcriptomes of single cells and will soon enable single-cell epigenomic and proteomic analyses.

  • Single-cell genomic analysis can reveal genomic variability among individual cells, which can be used to reconstruct cellular ancestries in the form of a lineage tree.

  • Single-cell transcriptome analysis can be used to study the functional states of individual cells and to infer and discover cell types in an unbiased manner.

  • Future integrated single-cell analyses based on high-throughput sequencing will enable the simultaneous analysis of genomic, transcriptomic and epigenomic states of cells. Such data will reveal the ancestries of cells, their types, their current functional states and may be used to infer the types and functional states of their ancestors.

  • Integrated single-cell analyses will shed light on fundamental questions of biology and medicine, including questions of the origin and development of cancer, the number of and relationship between human cell types, and the rate and structure of cell turnover in regenerating tissues.

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Acknowledgements

The work of S.L. was supported by grant 261063 from the European Research Council and by the Swedish Research Council STARGET consortium. The work of E.S. and T.B. was supported by The European Union FP7-ERC-AdG grant and by a grant from the Kenneth and Sally Leafman Appelbaum Discovery Fund. E.S. is the Incumbent of The Harry Weinrebe Professorial Chair of Computer Science and Biology. The contribution of E.S. to this Review was inspired by a research proposal prepared by E.S. in collaboration with I. Amit, A. Tanay and M. Schwarz.

Author information

Affiliations

  1. Department of Computer Science and Applied Math, Weizmann Institute of Science, Rehovot 76100, Israel.

    • Ehud Shapiro
    •  & Tamir Biezuner
  2. Department of Biological Chemistry, Weizmann Institute of Science, Rehovot 76100, Israel.

    • Ehud Shapiro
    •  & Tamir Biezuner
  3. Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Scheeles väg 2, 17177 Stockholm, Sweden.

    • Sten Linnarsson

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  1. Search for Ehud Shapiro in:

  2. Search for Tamir Biezuner in:

  3. Search for Sten Linnarsson in:

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Ehud Shapiro or Sten Linnarsson.

Glossary

Next-generation sequencing

(NGS). High-throughput DNA sequencing of a large number of DNA molecules in parallel. There is a trade-off between read length and throughput that depends on the sequencing technology, run time and quality.

Organismal cell lineage tree

A mathematical entity capturing all cell division and death events in the life of an organism up to a particular time point. The tree consists of labelled nodes, which represent all organismal cells, and directed edges, which represent progeny relationships among them. A reconstructed tree describes lineage relationships among cells sampled from an organism, and is precise only if it is a subtree of the (true) organismal cell lineage tree.

Cell type

A classification of cells by morphology, genotype, phenotype or developmental origin. There is no consensus on which properties are necessary and sufficient for this classification, nor is there general agreement on the actual number of cell types or their proper classification in any higher organism, including in humans.

Fluorescence-activated cell sorting

(FACS). A tool that enables high-speed counting and/or sorting of cells according to features detected by fluorescence.

Laser-capture microdissection

(LCM). A method that combines high-resolution microscopy and the accurate isolation of user-defined regions of a tissue slice for downstream analysis. Typically, a powerful laser is used to cut an outline of the target region, which can then be ejected into a sample tube.

Microsatellites

Repetitive elements in the genome that consist of basic units 1–6 bp long that are repeated from a few to a few dozen times. Microsatellites occupy 3% of the human genome.

Cell depth

The number of divisions a cell underwent since the zygote.

Sequencing depth

The total amount of raw sequence mapped to a reference genome, divided by the length of the genome.

Whole-genome amplification

(WGA). Refers to methods that are used to amplify the genomic DNA of single cells to increase the number of copies of DNA for downstream processing.

Clonal expansion

A method to retrieve representative DNA from a single cell following its proliferation. A single cell is isolated, cultured ex vivo, and allowed to divide several times. DNA is isolated from the bulk cell population using standard DNA extraction techniques that do not involve amplification.

Single-nucleotide polymorphism calls

(SNP calls). Following sequencing read assembly, this is the identification of single nucleotides that are different from the nucleotide at the same position in a specific reference genome. This process requires high-quality sequencing and adequate sequencing depth for statistical significance.

Sequencing coverage

In a sequencing experiment, the number of reads covering a specific nucleotide position is the coverage of that position. Increasing read depth leads to increasing coverage, and to increasing accuracy of the base calls.

Amplicons

DNA products of PCR amplifications.

Higher moments

Measures of the shape of a statistical distribution beyond mean and variance, such as skewness and kurtosis.

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