Cell differentiation and function is carefully controlled by gene regulatory networks made up of transcription factors and their binding sites. Identifying the components of gene regulatory networks is vital for understanding development and disease. A new method, SCENIC+, integrates single cell -omics data to uncover gene regulatory networks and their targets.
What are Gene Regulatory Networks?
Gene regulatory networks (GRNs) are the orchestrators of cell identity, controlling the expression of target genes through transcription factor interactions with cis-regulatory elements. Cis-regulatory elements or CREs include promoters, enhancers, and silencers- regions of non-coding DNA near a gene that regulate its expression.
Identifying these regulatory networks and their effects on target genes is a topic of great interest in genetics research, particularly in developmental biology and disease. CREs are typically composed of specific combinations of transcription factor binding sites. Thus, existing gene regulatory network analysis techniques focus on identifying transcription factor binding sites in DNA, but these methods often require some working knowledge of the transcription factors involved, antibodies against them, or highly homologous cell populations.
SCENIC+ Combines Single Cell RNA and Chromatin Accessibility Data
To overcome these challenges, González-Blaz et al. developed a method called SCENIC+ to infer enhancer-driven gene regulatory networks from single cell -omics data. In their recent Nature Methods publication, the authors explain that their original SCENIC method from 2017 can predict transcription factor binding sites using single cell RNA-Seq data, but not the exact CRE that a transcription factor interacts with.
In contrast, the updated SCENIC+ method integrates single cell chromatin accessibility (ATAC-Seq) data with the single cell RNA-Seq data to dramatically improve transcription factor binding site predictions. SCENIC+ first identifies candidate enhancers, then identifies enriched transcription factor binding motifs, and finally links transcription factors to candidate enhancers and their target genes.
Applications of Multi-Omic GRN Analysis
The authors applied SCENIC+ to identify conserved gene regulatory networks between human and mouse cell types in the cerebral cortex, providing a useful research benchmark of the similarities and differences in these models. They also applied SCENIC+ to investigate how perturbations of transcription factors affected gene regulation and cell differentiation trajectories, demonstrating broad applicability of this method across research question types.
Notably, this is not the only paper published in the last month to describe a new technique combining scRNA-Seq and scATAC-Seq data for investigating gene regulatory networks. Chen et al. recently described MAGICAL, a computational tool used specifically to analyze the changes in host gene regulatory circuits during different types of infections. Their study was able to show a remarkable level of sensitivity in gene regulatory networks to respond in cell type and pathogen-specific manners. Taken together, these papers demonstrate exciting applications for uncovering the architecture of gene regulatory networks.
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Jane Cook, Biochemist & Content Writer, Bridge Informatics
Jane Cook, the leading Content Writer for Bridge Informatics, has written over 100 articles on the latest topics and trends for the bioinformatics community. Jane’s broad and deep interdisciplinary molecular biology experience spans developing biochemistry assays to genomics. Prior to joining Bridge, Jane held research assistant roles in biochemistry research labs across a variety of therapeutic areas. While obtaining her B.A. in Biochemistry from Trinity College in Dublin, Ireland, Jane also studied journalism at New York University’s Arthur L. Carter Journalism Institute. As a native Texan, she embraces any challenge that comes her way. Jane hails from Dallas but returns to Ireland any and every chance she gets. If you’re interested in reaching out, please email [email protected] or [email protected].