A single-cell multimodal view on gene regulatory network inference from transcriptomics and chromatin accessibility data.

ABSTRACT: Eukaryotic gene regulation is a combinatorial, dynamic, and quantitative process that plays a vital role in development and disease and can be modeled at a systems level in gene regulatory networks (GRNs). The wealth of multi-omics data measured on the same samples and even on the same cells has lifted the field of GRN inference to the next stage. Combinations of (single-cell) transcriptomics and chromatin accessibility allow the prediction of fine-grained regulatory programs that go beyond mere correlation of transcription factor and target gene expression, with enhancer GRNs (eGRNs) modeling molecular interactions between transcription factors, regulatory elements, and target genes. In this review, we highlight the key components for successful (e)GRN inference from (sc)RNA-seq and (sc)A

SUBMITTER: Loers JU 

PROVIDER: S-EPMC11359808 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature