Biology subjects

Amgalan, D.

Publications and source records attributed to Amgalan, D..

3 recordsLinked to original sources

bioRxiv2026

Mapping the regulatory wiring of endothelial cell differentiation reveals a critical role for Hippo mechanosignaling

At each step of development, stem cells encounter a branching decision to differentiate into one type of cell or another. This decision is executed through the action of competing gene programs that specify different cellular identities. Consequently, creating a comprehensive map of the gene programs that drive each branching step of human cell differentiation remains a long-sought goal of developmental and stem cell biology. Here, we introduce a framework combining genome-wide CRISPR screens, single-cell readouts, and gene program inference to systematically discover and characterize regulators of cell differentiation. This framework includes a method for CRISPR perturbations paired with single-cell RNA-seq called circular capture Perturb-seq (CC-Perturb-seq), which improves gRNA detection from split-pool combinatorial indexing protocols and enables perturbing many candidate regulators to map their effects on gene programs. We applied this framework to map how human pluripotent stem cells differentiate into arterial endothelial cells (ECs), and identified 174 regulators that promote or inhibit EC differentiation. By tracking gene programs across three stages of differentiation, we resolved when and how regulators divert cells toward alternative fates. This map revealed an unexpected requirement for the Hippo mechanosignaling pathway in EC specification. During lateral mesoderm differentiation, Hippo mechanosignaling was required to activate ETV2, the master transcriptional regulator of endothelial identity. Inhibiting Hippo blocked ETV2 even in the presence of VEGF and diverted progenitors to a mesenchymal fate in vitro. Likewise, Hippo signaling was required for maximal etv2 expression in developing zebrafish embryos. Conversely, pharmacologically activating the Hippo pathway increased the purity of both arterial and venous EC differentiation in vitro. Our framework thus identifies novel regulators of endothelial cell differentiation, improves stem-cell differentiation protocols via manipulation of mechanosignaling, and provides a generalizable platform for mapping the regulatory wiring of human development.

genomics↗

bioRxiv2025

An unbiased survey of distal element-gene regulatory interactions with direct-capture targeted Perturb-seq

Identifying the impact of distal regulatory elements on gene expression is a core challenge in human genetics. Large-scale CRISPR screens have not captured lower effect size element-gene interactions due to selection bias and limited statistical power. We developed a framework for highly powered CRISPR screens, consisting of Direct-Capture Targeted Perturb-seq (DC-TAP-seq), unbiased target selection, and a pipeline accounting for statistical power. Surveying 10,000 random distal element-gene pairs revealed most element-gene interactions have effect sizes <10%, which were virtually undetectable in prior studies. Most interactions occur within 100kb, many elements bind CTCF without classical enhancer chromatin, and housekeeping genes have similar frequencies of distal regulatory elements but with weaker effects. We also highlight limitations of predictive models and suggest that new models consider elements with smaller effect sizes. Our study provides an expanded view of distal regulatory elements and a framework for building more comprehensive maps of distal regulation.

genomics↗

bioRxiv2024

Mapping enhancer-gene regulatory interactions from single-cell data

Mapping enhancers and their target genes in specific cell types is crucial for understanding gene regulation and human disease genetics. However, accurately predicting enhancer-gene regulatory interactions from single-cell datasets has been challenging. Here, we introduce a new family of classification models, scE2G, to predict enhancer-gene regulation. These models use features from single-cell ATAC-seq or multiomic RNA and ATAC-seq data and are trained on a CRISPR perturbation dataset including >10,000 evaluated element-gene pairs. We benchmark scE2G models against CRISPR perturbations, fine-mapped eQTLs, and GWAS variant-gene associations and demonstrate state-of-the-art performance at prediction tasks across multiple cell types and categories of perturbations. We apply scE2G to build maps of enhancer-gene regulatory interactions in heterogeneous tissues and interpret noncoding variants associated with complex traits, nominating regulatory interactions linking INPP4B and IL15 to lymphocyte counts. The scE2G models will enable accurate mapping of enhancer-gene regulatory interactions across thousands of diverse human cell types.

genetics↗