Gene regulatory network reconfiguration in direct lineage reprogramming.

Area of Science:

• Computational Biology
• Developmental Biology
• Genetics

Background:

• Transcription factor (TF) overexpression is key for direct lineage conversion, reprogramming cell identity by altering gene regulatory networks (GRNs).
• CellOracle is a computational tool developed to infer GRNs from single-cell transcriptome and epigenome data.
• Inferred GRNs allow for in silico simulation of TF perturbation effects on gene expression.

Purpose of the Study:

• To combine CellOracle analysis with lineage tracing for fibroblast to induced endoderm progenitor (iEP) conversion.
• To link early GRN states to reprogramming outcomes and identify network configurations associated with successful and failed cell fate conversion.
• To identify novel factors for enhancing direct lineage reprogramming through in silico TF perturbation simulations.

Main Methods:

• Inference of gene regulatory networks (GRNs) using the CellOracle computational method.
• Integration of CellOracle analysis with experimental lineage tracing data.
• In silico simulation of transcription factor (TF) perturbations to predict gene expression changes.

Main Results:

• Distinct GRN configurations were identified that distinguish successful from failed direct lineage reprogramming.
• CellOracle analysis linked early network states to the ultimate reprogramming outcome.
• In silico TF perturbation simulations identified Fos and Yap1 as crucial factors for successful iEP conversion.

Conclusions:

• CellOracle effectively infers and interprets cell-type-specific GRN configurations.
• The study provides new mechanistic insights into the process of direct lineage reprogramming.
• Identification of Fos and Yap1 highlights their potential as targets for improving reprogramming efficiency.