Format

Send to

Choose Destination
Nat Biotechnol. 2017 Jun;35(6):551-560. doi: 10.1038/nbt.3854. Epub 2017 May 1.

Single-cell topological RNA-seq analysis reveals insights into cellular differentiation and development.

Author information

1
Department of Biochemistry and Molecular Biophysics, Columbia University Medical Center, New York, New York, USA.
2
The Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, New York, USA.
3
Department of Systems Biology, Columbia University Medical Center, New York, New York, USA.
4
Department of Biomedical Informatics, Columbia University Medical Center, New York, New York, USA.
5
Howard Hughes Medical Institute, Columbia University Medical Center, New York, New York, USA.

Abstract

Transcriptional programs control cellular lineage commitment and differentiation during development. Understanding of cell fate has been advanced by studying single-cell RNA-sequencing (RNA-seq) but is limited by the assumptions of current analytic methods regarding the structure of data. We present single-cell topological data analysis (scTDA), an algorithm for topology-based computational analyses to study temporal, unbiased transcriptional regulation. Unlike other methods, scTDA is a nonlinear, model-independent, unsupervised statistical framework that can characterize transient cellular states. We applied scTDA to the analysis of murine embryonic stem cell (mESC) differentiation in vitro in response to inducers of motor neuron differentiation. scTDA resolved asynchrony and continuity in cellular identity over time and identified four transient states (pluripotent, precursor, progenitor, and fully differentiated cells) based on changes in stage-dependent combinations of transcription factors, RNA-binding proteins, and long noncoding RNAs (lncRNAs). scTDA can be applied to study asynchronous cellular responses to either developmental cues or environmental perturbations.

PMID:
28459448
PMCID:
PMC5569300
DOI:
10.1038/nbt.3854
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Nature Publishing Group Icon for PubMed Central
Loading ...
Support Center