Parallel genome-scale CRISPR-Cas9 screens uncouple human pluripotent stem cell identity versus fitness.

Pluripotent stem cells have remarkable self-renewal capacity: the ability to proliferate indefinitely while maintaining the pluripotent identity essential for their ability to differentiate into almost any cell type in the body. To investigate the interplay between these two aspects of self-renewal, we perform four parallel genome-scale CRISPR-Cas9 loss-of-function screens interrogating stem cell fitness in hPSCs and the dissolution of primed pluripotent identity during early differentiation. These screens distinguish genes with distinct roles in pluripotency regulation, including mitochondrial and metabolism regulators crucial for stem cell fitness, and chromatin regulators that control pluripotent identity during early differentiation. We further identify a core set of genes controlling both stem cell fitness and pluripotent identity, including a network of chromatin factors. Here, unbiased screening and comparative analyses disentangle two interconnected aspects of pluripotency, provide a valuable resource for exploring pluripotent stem cell identity versus cell fitness, and offer a framework for categorizing gene function.

CRISPR screening uncovers a long-range enhancer for ONECUT1 in pancreatic differentiation and links a diabetes risk variant.

Functional enhancer annotation is critical for understanding tissue-specific transcriptional regulation and prioritizing disease-associated non-coding variants. However, unbiased enhancer discovery in disease-relevant contexts remains challenging. To identify enhancers pertinent to diabetes, we conducted a CRISPR interference (CRISPRi) screen in the human pluripotent stem cell (hPSC) pancreatic differentiation system. Among the enhancers identified, we focused on an enhancer we named ONECUT1e-664kb, ∼664 kb from the ONECUT1 promoter. Previous studies have linked ONECUT1 coding mutations to pancreatic hypoplasia and neonatal diabetes. We found that homozygous deletion of ONECUT1e-664kb in hPSCs leads to a near-complete loss of ONECUT1 expression and impaired pancreatic differentiation. ONECUT1e-664kb contains a type 2 diabetes-associated variant (rs528350911) disrupting a GATA motif. Introducing the risk variant into hPSCs reduced binding of key pancreatic transcription factors (GATA4, GATA6, and FOXA2), supporting its causal role in diabetes. This work highlights the utility of unbiased enhancer discovery in disease-relevant settings for understanding monogenic and complex disease.

CRISPR Screening Uncovers a Long-Range Enhancer for ONECUT1 in Pancreatic Differentiation and Links a Diabetes Risk Variant.

Functional enhancer annotation is a valuable first step for understanding tissue-specific transcriptional regulation and prioritizing disease-associated non-coding variants for investigation. However, unbiased enhancer discovery in physiologically relevant contexts remains a major challenge. To discover regulatory elements pertinent to diabetes, we conducted a CRISPR interference screen in the human pluripotent stem cell (hPSC) pancreatic differentiation system. Among the enhancers uncovered, we focused on a long-range enhancer ∼664 kb from the ONECUT1 promoter, since coding mutations in ONECUT1 cause pancreatic hypoplasia and neonatal diabetes. Homozygous enhancer deletion in hPSCs was associated with a near-complete loss of ONECUT1 gene expression and compromised pancreatic differentiation. This enhancer contains a confidently fine-mapped type 2 diabetes associated variant (rs528350911) which disrupts a GATA motif. Introduction of the risk variant into hPSCs revealed substantially reduced binding of key pancreatic transcription factors (GATA4, GATA6 and FOXA2) on the edited allele, accompanied by a slight reduction of ONECUT1 transcription, supporting a causal role for this risk variant in metabolic disease. This work expands our knowledge about transcriptional regulation in pancreatic development through the characterization of a long-range enhancer and highlights the utility of enhancer discovery in disease-relevant settings for understanding monogenic and complex disease.

ChromaFold predicts the 3D contact map from single-cell chromatin accessibility.

Identifying cell-type-specific 3D chromatin interactions between regulatory elements can help decipher gene regulation and interpret disease-associated non-coding variants. However, achieving this resolution with current 3D genomics technologies is often infeasible given limited input cell numbers. We therefore present ChromaFold, a deep learning model that predicts 3D contact maps, including regulatory interactions, from single-cell ATAC sequencing (scATAC-seq) data alone. ChromaFold uses pseudobulk chromatin accessibility, co-accessibility across metacells, and a CTCF motif track as inputs and employs a lightweight architecture to train on standard GPUs. Trained on paired scATAC-seq and Hi-C data in human samples, ChromaFold accurately predicts the 3D contact map and peak-level interactions across diverse human and mouse test cell types. Compared to leading contact map prediction models that use ATAC-seq and CTCF ChIP-seq, ChromaFold achieves state-of-the-art performance using only scATAC-seq. Finally, fine-tuning ChromaFold on paired scATAC-seq and Hi-C in a complex tissue enables deconvolution of chromatin interactions across cell subpopulations.

Parallel genome-scale CRISPR screens distinguish pluripotency and self-renewal.

Pluripotent stem cells are defined by both the ability to unlimitedly self-renew and differentiate to any somatic cell lineage, but understanding the mechanisms that control stem cell fitness versus the pluripotent cell identity is challenging. We performed four parallel genome-scale CRISPR-Cas9 screens to investigate the interplay between these two aspects of pluripotency. Our comparative analyses led to the discovery of genes with distinct roles in pluripotency regulation, including many mitochondrial and metabolism regulators crucial for stem cell fitness, and chromatin regulators that control stem cell identity. We further discovered a core set of factors that control both stem cell fitness and pluripotency identity, including an interconnected network of chromatin factors that safeguard pluripotency. Our unbiased and systematic screening and comparative analyses disentangle two interconnected aspects of pluripotency, provide rich datasets for exploring pluripotent cell identity versus self-renewal, and offer a valuable model for categorizing gene function in broad biological contexts.

Dynamic network-guided CRISPRi screen reveals CTCF loop-constrained nonlinear enhancer-gene regulatory activity in cell state transitions.

Comprehensive enhancer discovery is challenging because most enhancers, especially those affected in complex diseases, have weak effects on gene expression. Our network modeling revealed that nonlinear enhancer-gene regulation during cell state transitions can be leveraged to improve the sensitivity of enhancer discovery. Utilizing hESC definitive endoderm differentiation as a dynamic transition system, we conducted a mid-transition CRISPRi-based enhancer screen. The screen discovered a comprehensive set of enhancers (4 to 9 per locus) for each of the core endoderm lineage-specifying transcription factors, and many enhancers had strong effects mid-transition but weak effects post-transition. Through integrating enhancer activity measurements and three-dimensional enhancer-promoter interaction information, we were able to develop a CTCF loop-constrained Interaction Activity (CIA) model that can better predict functional enhancers compared to models that rely on Hi-C-based enhancer-promoter contact frequency. Our study provides generalizable strategies for sensitive and more comprehensive enhancer discovery in both normal and pathological cell state transitions.

Discovery of Competent Chromatin Regions in Human Embryonic Stem Cells.

The mechanisms underlying the ability of embryonic stem cells (ESCs) to rapidly activate lineage-specific genes during differentiation remain largely unknown. Through multiple CRISPR-activation screens, we discovered human ESCs have pre-established transcriptionally competent chromatin regions (CCRs) that support lineage-specific gene expression at levels comparable to differentiated cells. CCRs reside in the same topological domains as their target genes. They lack typical enhancer-associated histone modifications but show enriched occupancy of pluripotent transcription factors, DNA demethylation factors, and histone deacetylases. TET1 and QSER1 protect CCRs from excessive DNA methylation, while HDAC1 family members prevent premature activation. This "push and pull" feature resembles bivalent domains at developmental gene promoters but involves distinct molecular mechanisms. Our study provides new insights into pluripotency regulation and cellular plasticity in development and disease. One sentence summary: We report a class of distal regulatory regions distinct from enhancers that confer human embryonic stem cells with the competence to rapidly activate the expression of lineage-specific genes.

Dynamic network-guided CRISPRi screen identifies CTCF-loop-constrained nonlinear enhancer gene regulatory activity during cell state transitions.

Comprehensive enhancer discovery is challenging because most enhancers, especially those contributing to complex diseases, have weak effects on gene expression. Our gene regulatory network modeling identified that nonlinear enhancer gene regulation during cell state transitions can be leveraged to improve the sensitivity of enhancer discovery. Using human embryonic stem cell definitive endoderm differentiation as a dynamic transition system, we conducted a mid-transition CRISPRi-based enhancer screen. We discovered a comprehensive set of enhancers for each of the core endoderm-specifying transcription factors. Many enhancers had strong effects mid-transition but weak effects post-transition, consistent with the nonlinear temporal responses to enhancer perturbation predicted by the modeling. Integrating three-dimensional genomic information, we were able to develop a CTCF-loop-constrained Interaction Activity model that can better predict functional enhancers compared to models that rely on Hi-C-based enhancer-promoter contact frequency. Our study provides generalizable strategies for sensitive and systematic enhancer discovery in both normal and pathological cell state transitions.

ChromaFold predicts the 3D contact map from single-cell chromatin accessibility.

The identification of cell-type-specific 3D chromatin interactions between regulatory elements can help to decipher gene regulation and to interpret the function of disease-associated non-coding variants. However, current chromosome conformation capture (3C) technologies are unable to resolve interactions at this resolution when only small numbers of cells are available as input. We therefore present ChromaFold, a deep learning model that predicts 3D contact maps and regulatory interactions from single-cell ATAC sequencing (scATAC-seq) data alone. ChromaFold uses pseudobulk chromatin accessibility, co-accessibility profiles across metacells, and predicted CTCF motif tracks as input features and employs a lightweight architecture to enable training on standard GPUs. Once trained on paired scATAC-seq and Hi-C data in human cell lines and tissues, ChromaFold can accurately predict both the 3D contact map and peak-level interactions across diverse human and mouse test cell types. In benchmarking against a recent deep learning method that uses bulk ATAC-seq, DNA sequence, and CTCF ChIP-seq to make cell-type-specific predictions, ChromaFold yields superior prediction performance when including CTCF ChIP-seq data as an input and comparable performance without. Finally, fine-tuning ChromaFold on paired scATAC-seq and Hi-C in a complex tissue enables deconvolution of chromatin interactions across cell subpopulations. ChromaFold thus achieves state-of-the-art prediction of 3D contact maps and regulatory interactions using scATAC-seq alone as input data, enabling accurate inference of cell-type-specific interactions in settings where 3C-based assays are infeasible.

CRISPR screening uncovers a central requirement for HHEX in pancreatic lineage commitment and plasticity restriction.

The pancreas and liver arise from a common pool of progenitors. However, the underlying mechanisms that drive their lineage diversification from the foregut endoderm are not fully understood. To tackle this question, we undertook a multifactorial approach that integrated human pluripotent-stem-cell-guided differentiation, genome-scale CRISPR-Cas9 screening, single-cell analysis, genomics and proteomics. We discovered that HHEX, a transcription factor (TF) widely recognized as a key regulator of liver development, acts as a gatekeeper of pancreatic lineage specification. HHEX deletion impaired pancreatic commitment and unleashed an unexpected degree of cellular plasticity towards the liver and duodenum fates. Mechanistically, HHEX cooperates with the pioneer TFs FOXA1, FOXA2 and GATA4, shared by both pancreas and liver differentiation programmes, to promote pancreas commitment, and this cooperation restrains the shared TFs from activating alternative lineages. These findings provide a generalizable model for how gatekeeper TFs like HHEX orchestrate lineage commitment and plasticity restriction in broad developmental contexts.

Altered RNA Splicing by Mutant p53 Activates Oncogenic RAS Signaling in Pancreatic Cancer.

Pancreatic ductal adenocarcinoma (PDAC) is driven by co-existing mutations in KRAS and TP53. However, how these mutations collaborate to promote this cancer is unknown. Here, we uncover sequence-specific changes in RNA splicing enforced by mutant p53 which enhance KRAS activity. Mutant p53 increases expression of splicing regulator hnRNPK to promote inclusion of cytosine-rich exons within GTPase-activating proteins (GAPs), negative regulators of RAS family members. Mutant p53-enforced GAP isoforms lose cell membrane association, leading to heightened KRAS activity. Preventing cytosine-rich exon inclusion in mutant KRAS/p53 PDACs decreases tumor growth. Moreover, mutant p53 PDACs are sensitized to inhibition of splicing via spliceosome inhibitors. These data provide insight into co-enrichment of KRAS and p53 mutations and therapeutics targeting this mechanism in PDAC.

Genome-scale screens identify JNK-JUN signaling as a barrier for pluripotency exit and endoderm differentiation.

Human embryonic stem cells (ESCs) and human induced pluripotent stem cells hold great promise for cell-based therapies and drug discovery. However, homogeneous differentiation remains a major challenge, highlighting the need for understanding developmental mechanisms. We performed genome-scale CRISPR screens to uncover regulators of definitive endoderm (DE) differentiation, which unexpectedly uncovered five Jun N-terminal kinase (JNK)-JUN family genes as key barriers of DE differentiation. The JNK-JUN pathway does not act through directly inhibiting the DE enhancers. Instead, JUN co-occupies ESC enhancers with OCT4, NANOG, SMAD2 and SMAD3, and specifically inhibits the exit from the pluripotent state by impeding the decommissioning of ESC enhancers and inhibiting the reconfiguration of SMAD2 and SMAD3 chromatin binding from ESC to DE enhancers. Therefore, the JNK-JUN pathway safeguards pluripotency from precocious DE differentiation. Direct pharmacological inhibition of JNK significantly improves the efficiencies of generating DE and DE-derived pancreatic and lung progenitor cells, highlighting the potential of harnessing the knowledge from developmental studies for regenerative medicine.