Epigenome rewiring in human pluripotent stem cells

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.

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.

Endogenous retrovirus-derived enhancers confer the transcriptional regulation of human trophoblast syncytialization

Endogenous retroviruses (ERVs) have been proposed as a driving force for the evolution of the mammalian placenta, however, the contribution of ERVs to placental development and the underlying regulatory mechanism remain largely elusive. A key process of placental development is the formation of multinucleated syncytiotrophoblasts (STBs) in direct contact with maternal blood, through which constitutes the maternal-fetal interface critical for nutrient allocation, hormone production and immunological modulation during pregnancy. We delineate that ERVs profoundly rewire the transcriptional program of trophoblast syncytialization. Here, we first determined the dynamic landscape of bivalent ERV-derived enhancers with dual occupancy of H3K27ac and H3K9me3 in human trophoblast stem cells (hTSCs). We further demonstrated that enhancers overlapping several ERV families tend to exhibit increased H3K27ac and reduced H3K9me3 occupancy in STBs relative to hTSCs. Particularly, bivalent enhancers derived from the Simiiformes-specific MER50 transposons were linked to a cluster of genes important for STB formation. Importantly, deletions of MER50 elements adjacent to several STB genes, including MFSD2A and TNFAIP2, significantly attenuated their expression concomitant to compromised syncytium formation. Together, we propose that ERV-derived enhancers, MER50 specifically, fine-tune the transcriptional networks accounting for human trophoblast syncytialization, which sheds light on a novel ERV-mediated regulatory mechanism underlying placental development.

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.