Format

Send to

Choose Destination
Genome Biol. 2019 Jun 4;20(1):110. doi: 10.1186/s13059-019-1713-4.

Single-cell transcriptomics unveils gene regulatory network plasticity.

Author information

1
CNAG-CRG, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Baldiri Reixac 4, 08028, Barcelona, Spain. giovanni.iacono@cnag.crg.eu.
2
CNAG-CRG, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Baldiri Reixac 4, 08028, Barcelona, Spain.
3
CNAG-CRG, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Baldiri Reixac 4, 08028, Barcelona, Spain. holger.heyn@cnag.crg.eu.
4
Universitat Pompeu Fabra (UPF), Barcelona, Spain. holger.heyn@cnag.crg.eu.

Abstract

BACKGROUND:

Single-cell RNA sequencing (scRNA-seq) plays a pivotal role in our understanding of cellular heterogeneity. Current analytical workflows are driven by categorizing principles that consider cells as individual entities and classify them into complex taxonomies.

RESULTS:

We devise a conceptually different computational framework based on a holistic view, where single-cell datasets are used to infer global, large-scale regulatory networks. We develop correlation metrics that are specifically tailored to single-cell data, and then generate, validate, and interpret single-cell-derived regulatory networks from organs and perturbed systems, such as diabetes and Alzheimer's disease. Using tools from graph theory, we compute an unbiased quantification of a gene's biological relevance and accurately pinpoint key players in organ function and drivers of diseases.

CONCLUSIONS:

Our approach detects multiple latent regulatory changes that are invisible to single-cell workflows based on clustering or differential expression analysis, significantly broadening the biological insights that can be obtained with this leading technology.

PMID:
31159854
PMCID:
PMC6547541
DOI:
10.1186/s13059-019-1713-4
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for BioMed Central Icon for PubMed Central
Loading ...
Support Center