Single Cell Genomics: Advances and Future Perspectives

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Advances in whole-genome and whole-transcriptome amplification have permitted the sequencing of the minute amounts of DNA and RNA present in a single cell, offering a window into the extent and nature of genomic and transcriptomic heterogeneity which occurs in both normal development and disease. Single-cell approaches stand poised to revolutionise our capacity to understand the scale of genomic, epigenomic, and transcriptomic diversity that occurs during the lifetime of an individual organism. Here, we review the major technological and biological breakthroughs achieved, describe the remaining challenges to overcome, and provide a glimpse into the promise of recent and future developments.

Related collections

Most cited references 88

Record: found
Abstract: found
Article: not found

Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells

Alex Shalek, Rahul Satija, Xian Adiconis … (2013)

Recent molecular studies have revealed that, even when derived from a seemingly homogenous population, individual cells can exhibit substantial differences in gene expression, protein levels, and phenotypic output 1–5 , with important functional consequences 4,5 . Existing studies of cellular heterogeneity, however, have typically measured only a few pre-selected RNAs 1,2 or proteins 5,6 simultaneously because genomic profiling methods 3 could not be applied to single cells until very recently 7–10 . Here, we use single-cell RNA-Seq to investigate heterogeneity in the response of bone marrow derived dendritic cells (BMDCs) to lipopolysaccharide (LPS). We find extensive, and previously unobserved, bimodal variation in mRNA abundance and splicing patterns, which we validate by RNA-fluorescence in situ hybridization (RNA-FISH) for select transcripts. In particular, hundreds of key immune genes are bimodally expressed across cells, surprisingly even for genes that are very highly expressed at the population average. Moreover, splicing patterns demonstrate previously unobserved levels of heterogeneity between cells. Some of the observed bimodality can be attributed to closely related, yet distinct, known maturity states of BMDCs; other portions reflect differences in the usage of key regulatory circuits. For example, we identify a module of 137 highly variable, yet co-regulated, antiviral response genes. Using cells from knockout mice, we show that variability in this module may be propagated through an interferon feedback circuit involving the transcriptional regulators Stat2 and Irf7. Our study demonstrates the power and promise of single-cell genomics in uncovering functional diversity between cells and in deciphering cell states and circuits.

0 comments Cited 518 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Accounting for technical noise in single-cell RNA-seq experiments.

Philip Brennecke, Simon Anders, Jong Kim … (2013)

Single-cell RNA-seq can yield valuable insights about the variability within a population of seemingly homogeneous cells. We developed a quantitative statistical method to distinguish true biological variability from the high levels of technical noise in single-cell experiments. Our approach quantifies the statistical significance of observed cell-to-cell variability in expression strength on a gene-by-gene basis. We validate our approach using two independent data sets from Arabidopsis thaliana and Mus musculus.

0 comments Cited 452 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Genetic programs in human and mouse early embryos revealed by single-cell RNA sequencing.

Zhigang Xue, Kevin Huang, Chaochao Cai … (2013)

Mammalian pre-implantation development is a complex process involving dramatic changes in the transcriptional architecture. We report here a comprehensive analysis of transcriptome dynamics from oocyte to morula in both human and mouse embryos, using single-cell RNA sequencing. Based on single-nucleotide variants in human blastomere messenger RNAs and paternal-specific single-nucleotide polymorphisms, we identify novel stage-specific monoallelic expression patterns for a significant portion of polymorphic gene transcripts (25 to 53%). By weighted gene co-expression network analysis, we find that each developmental stage can be delineated concisely by a small number of functional modules of co-expressed genes. This result indicates a sequential order of transcriptional changes in pathways of cell cycle, gene regulation, translation and metabolism, acting in a step-wise fashion from cleavage to morula. Cross-species comparisons with mouse pre-implantation embryos reveal that the majority of human stage-specific modules (7 out of 9) are notably preserved, but developmental specificity and timing differ between human and mouse. Furthermore, we identify conserved key members (or hub genes) of the human and mouse networks. These genes represent novel candidates that are likely to be key in driving mammalian pre-implantation development. Together, the results provide a valuable resource to dissect gene regulatory mechanisms underlying progressive development of early mammalian embryos.

0 comments Cited 410 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Contributors

Nancy Maizels: Role: Editor

Journal

Journal ID (nlm-ta): PLoS Genet

Journal ID (iso-abbrev): PLoS Genet

Journal ID (publisher-id): plos

Journal ID (pmc): plosgen

Title: PLoS Genetics

Publisher: Public Library of Science (San Francisco, USA )

ISSN (Print): 1553-7390

ISSN (Electronic): 1553-7404

Publication date Collection: January 2014

Publication date (Electronic): 30 January 2014

Volume: 10

Issue: 1

Electronic Location Identifier: e1004126

Affiliations

[1 ]Single Cell Genomics Centre, Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom

[2 ]Laboratory of Reproductive Genomics, Department of Human Genetics, KU Leuven, Belgium

University of Washington, United States of America

Author notes

* E-mail: Thierry.Voet@ 123456med.kuleuven.be

I have read the journal's policy and have the following conflicts: TV is a named inventor on submitted patent applications PCT/EP2011/060211; PCT/EP2013/070858; ZL913096.

Article

Publisher ID: PGENETICS-D-13-02293

DOI: 10.1371/journal.pgen.1004126

PMC ID: 3907301

PubMed ID: 24497842

SO-VID: fb96a33c-e98b-42ad-a915-98a89f4417ff

License:

This is an open-access article distributed under the terms of the http://creativecommons.org/licenses/by/4.0/Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

History

Page count

Pages: 9

Funding

We acknowledge the Wellcome Trust (UK; http://www.wellcome.ac.uk/ and http://www.sanger.ac.uk/), the Research Foundation Flanders (FWO; http://www.fwo.be/; Belgium) [FWO-G.A093.11 to TV], and the KU Leuven [ http://www.kuleuven.be/; Belgium; SymBioSys, PFV/10/016 to TV]. The funders had no role in the preparation of the article.

Single Cell Genomics: Advances and Future Perspectives

Read this article at

Abstract

Related collections

Arabidopsis genomics

Most cited references 88

Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells

Accounting for technical noise in single-cell RNA-seq experiments.

Genetic programs in human and mouse early embryos revealed by single-cell RNA sequencing.

Author and article information

Contributors

Journal

Affiliations

Author notes

Article

History

Page count

Funding

Categories

Comments

Comment on this article

Similar content 336

Cited by 120

Most referenced authors 2,230