1. Computational and Systems Biology
  2. Stem Cells and Regenerative Medicine
Download icon

Self-assembling manifolds in single-cell RNA sequencing data

  1. Alexander J Tarashansky
  2. Yuan Xue
  3. Pengyang Li
  4. Stephen R Quake
  5. Bo Wang  Is a corresponding author
  1. Stanford University, United States
Tools and Resources
  • Cited 4
  • Views 3,921
  • Annotations
Cite this article as: eLife 2019;8:e48994 doi: 10.7554/eLife.48994

Abstract

Single-cell RNA sequencing has spurred the development of computational methods that enable researchers to classify cell types, delineate developmental trajectories, and measure molecular responses to external perturbations. Many of these technologies rely on their ability to detect genes whose cell-to-cell variations arise from the biological processes of interest rather than transcriptional or technical noise. However, for datasets in which the biologically relevant differences between cells are subtle, identifying these genes is challenging. We present the self-assembling manifold (SAM) algorithm, an iterative soft feature selection strategy to quantify gene relevance and improve dimensionality reduction. We demonstrate its advantages over other state-of-the-art methods with experimental validation in identifying novel stem cell populations of Schistosoma mansoni, a prevalent parasite that infects hundreds of millions of people. Extending our analysis to a total of 56 datasets, we show that SAM is generalizable and consistently outperforms other methods in a variety of biological and quantitative benchmarks.

Article and author information

Author details

  1. Alexander J Tarashansky

    Department of Bioengineering, Stanford University, Stanford, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Yuan Xue

    Department of Bioengineering, Stanford University, Stanford, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Pengyang Li

    Department of Bioengineering, Stanford University, Stanford, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Stephen R Quake

    Department of Bioengineering, Stanford University, Stanford, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1613-0809
  5. Bo Wang

    Department of Bioengineering, Stanford University, Stanford, United States
    For correspondence
    wangbo@stanford.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8880-1432

Funding

Burroughs Wellcome Fund

  • Bo Wang

Arnold and Mabel Beckman Foundation

  • Bo Wang

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Animal experimentation: In adherence to the Animal Welfare Act and the Public Health Service Policy on Humane Care and Use of Laboratory Animals, all experiments with and care of mice were performed in accordance with protocols approved by the Institutional Animal Care and Use Committees (IACUC) of Stanford University (protocol approval number 30366).

Reviewing Editor

  1. Alex K Shalek, Broad Institute of MIT and Harvard, United States

Publication history

  1. Received: June 3, 2019
  2. Accepted: September 16, 2019
  3. Accepted Manuscript published: September 16, 2019 (version 1)
  4. Version of Record published: October 16, 2019 (version 2)

Copyright

© 2019, Tarashansky et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 3,921
    Page views
  • 695
    Downloads
  • 4
    Citations

Article citation count generated by polling the highest count across the following sources: PubMed Central, Crossref, Scopus.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Download citations (links to download the citations from this article in formats compatible with various reference manager tools)

Open citations (links to open the citations from this article in various online reference manager services)

Further reading

    1. Computational and Systems Biology
    2. Immunology and Inflammation
    George Ueda et al.
    Research Article

    Multivalent presentation of viral glycoproteins can substantially increase the elicitation of antigen-specific antibodies. To enable a new generation of anti-viral vaccines, we designed self-assembling protein nanoparticles with geometries tailored to present the ectodomains of influenza, HIV, and RSV viral glycoprotein trimers. We first de novo designed trimers tailored for antigen fusion, featuring N-terminal helices positioned to match the C termini of the viral glycoproteins. Trimers that experimentally adopted their designed configurations were incorporated as components of tetrahedral, octahedral, and icosahedral nanoparticles, which were characterized by cryo-electron microscopy and assessed for their ability to present viral glycoproteins. Electron microscopy and antibody binding experiments demonstrated that the designed nanoparticles presented antigenically intact prefusion HIV-1 Env, influenza hemagglutinin, and RSV F trimers in the predicted geometries. This work demonstrates that antigen-displaying protein nanoparticles can be designed from scratch, and provides a systematic way to investigate the influence of antigen presentation geometry on the immune response to vaccination.

    1. Computational and Systems Biology
    2. Developmental Biology
    Bjoern Gaertner et al.
    Research Article

    Long noncoding RNAs (lncRNAs) are a heterogenous group of RNAs, which can encode small proteins. The extent to which developmentally regulated lncRNAs are translated and whether the produced microproteins are relevant for human development is unknown. Using a human embryonic stem cell (hESC)-based pancreatic differentiation system, we show that many lncRNAs in direct vicinity of lineage-determining transcription factors (TFs) are dynamically regulated, predominantly cytosolic, and highly translated. We genetically ablated ten such lncRNAs, most of them translated, and found that nine are dispensable for pancreatic endocrine cell development. However, deletion of LINC00261 diminishes insulin+ cells, in a manner independent of the nearby TF FOXA2. One-by-one deletion of each of LINC00261's open reading frames suggests that the RNA, rather than the produced microproteins, is required for endocrine development. Our work highlights extensive translation of lncRNAs during hESC pancreatic differentiation and provides a blueprint for dissection of their coding and noncoding roles.