Candidate Cis-regulatory Elements Research Articles

Comparative 3D genome analysis between neural retina and retinal pigment epithelium reveals differential cis-regulatory interactions at retinal disease loci

BackgroundVision depends on the interplay between photoreceptor cells of the neural retina and the underlying retinal pigment epithelium (RPE). Most genes involved in inherited retinal diseases display specific spatiotemporal expression within these interconnected retinal components through the local recruitment of cis-regulatory elements (CREs) in 3D nuclear space.ResultsTo understand the role of differential chromatin architecture in establishing tissue-specific expression at inherited retinal disease loci, we mapped genome-wide chromatin interactions using in situ Hi-C and H3K4me3 HiChIP on neural retina and RPE/choroid from human adult donor eyes. We observed chromatin looping between active promoters and 32,425 and 8060 candidate CREs in the neural retina and RPE/choroid, respectively. A comparative 3D genome analysis between these two retinal tissues revealed that 56% of 290 known inherited retinal disease genes were marked by differential chromatin interactions. One of these was ABCA4, which is implicated in the most common autosomal recessive inherited retinal disease. We zoomed in on retina- and RPE-specific cis-regulatory interactions at the ABCA4 locus using high-resolution UMI-4C. Integration with bulk and single-cell epigenomic datasets and in vivo enhancer assays in zebrafish revealed tissue-specific CREs interacting with ABCA4.ConclusionsThrough comparative 3D genome mapping, based on genome-wide, promoter-centric, and locus-specific assays of human neural retina and RPE, we have shown that gene regulation at key inherited retinal disease loci is likely mediated by tissue-specific chromatin interactions. These findings do not only provide insight into tissue-specific regulatory landscapes at retinal disease loci, but also delineate the search space for non-coding genomic variation underlying unsolved inherited retinal diseases.Graphical

Chromatin accessibility during human first-trimester neurodevelopment.

The human brain develops through a tightly organized cascade of patterning events, induced by transcription factor expression and changes in chromatin accessibility. Although gene expression across the developing brain has been described at single-cell resolution1, similar atlases of chromatin accessibility have been primarily focused on the forebrain2-4. Here we describe chromatin accessibility and paired gene expression across the entire developing human brain during the first trimester (6-13 weeks after conception). We defined 135 clusters and used multiomic measurements to link candidate cis-regulatory elements to gene expression. The number of accessible regions increased both with age and along neuronal differentiation. Using a convolutional neural network, we identified putative functional transcription factor-binding sites in enhancers characterizing neuronal subtypes. We applied this model to cis-regulatory elements linked to ESRRB to elucidate its activation mechanism in the Purkinje cell lineage. Finally, by linking disease-associated single nucleotide polymorphisms to cis-regulatory elements, we validated putative pathogenic mechanisms in several diseases and identified midbrain-derived GABAergic neurons as being the most vulnerable to major depressive disorder-related mutations. Our findings provide a more detailed view of key gene regulatory mechanisms underlying the emergence of brain cell types during the first trimester and a comprehensive reference for future studies related to human neurodevelopment.

Multicenter integrated analysis of noncoding CRISPRi screens

The ENCODE Consortium’s efforts to annotate noncoding cis-regulatory elements (CREs) have advanced our understanding of gene regulatory landscapes. Pooled, noncoding CRISPR screens offer a systematic approach to investigate cis-regulatory mechanisms. The ENCODE4 Functional Characterization Centers conducted 108 screens in human cell lines, comprising >540,000 perturbations across 24.85 megabases of the genome. Using 332 functionally confirmed CRE–gene links in K562 cells, we established guidelines for screening endogenous noncoding elements with CRISPR interference (CRISPRi), including accurate detection of CREs that exhibit variable, often low, transcriptional effects. Benchmarking five screen analysis tools, we find that CASA produces the most conservative CRE calls and is robust to artifacts of low-specificity single guide RNAs. We uncover a subtle DNA strand bias for CRISPRi in transcribed regions with implications for screen design and analysis. Together, we provide an accessible data resource, predesigned single guide RNAs for targeting 3,275,697 ENCODE SCREEN candidate CREs with CRISPRi and screening guidelines to accelerate functional characterization of the noncoding genome.

Construction of single-cell cross-species chromatin accessibility landscapes with combinatorial-hybridization-based ATAC-seq

Despite recent advances in single-cell genomics, the lack of maps for single-cell candidate cis-regulatory elements (cCREs) in non-mammal species has limited our exploration of conserved regulatory programs across vertebrates and invertebrates. Here, we developed a combinatorial-hybridization-based method for single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) named CH-ATAC-seq, enabling the construction of single-cell accessible chromatin landscapes for zebrafish, Drosophila, and earthworms (Eisenia andrei). By integrating scATAC censuses of humans, monkeys, and mice, we systematically identified 152 distinct main cell types and around 0.8 million cell-type-specific cCREs. Our analysis provided insights into the conservation of neural, muscle, and immune lineages across species, while epithelial cells exhibited a higher organ-origin heterogeneity. Additionally, a large-scale gene regulatory network (GRN) was constructed in four vertebrates by integrating scRNA-seq censuses. Overall, our study provides a valuable resource for comparative epigenomics, identifying the evolutionary conservation and divergence of gene regulation across different species.

Neuronal MAPT expression is mediated by long-range interactions with cis-regulatory elements

Tauopathies are a group of neurodegenerative diseases defined by abnormal aggregates of tau, a microtubule-associated protein encoded by MAPT. MAPT expression is near absent in neural progenitor cells (NPCs) and increases during differentiation. This temporally dynamic expression pattern suggests that MAPT expression could be controlled by transcription factors and cis-regulatory elements specific to differentiated cell types. Given the relevance of MAPT expression to neurodegeneration pathogenesis, identification of such elements is relevant to understanding disease risk and pathogenesis. Here, we performed chromatin conformation assays (HiC& Capture-C), single-nucleus multiomics (RNA-seq+ATAC-seq), bulk ATAC-seq, and ChIP-seq for H3K27ac and CTCF in NPCs and differentiated neurons to nominate candidate cis-regulatory elements (cCREs). We assayed these cCREs using luciferase assays and CRISPR interference (CRISPRi) experiments to measure their effects on MAPT expression. Finally, we integrated cCRE annotations into an analysis of genetic variation in neurodegeneration-affected individuals and control subjects. We identified both proximal and distal regulatory elements for MAPT and confirmed the regulatory function for several regions, including three regions centromeric to MAPT beyond the H1/H2 haplotype inversion breakpoint. We also found that rare and predicted damaging genetic variation in nominated CREs was nominally depleted in dementia-affected individuals relative to control subjects, consistent with the hypothesis that variants that disrupt MAPT enhancer activity, and thereby reduced MAPT expression, may be protective against neurodegenerative disease. Overall, this study provides compelling evidence for pursuing detailed knowledge of CREs for genes of interest to permit better understanding of disease risk.

Conserved and divergent gene regulatory programs of the mammalian neocortex

Divergence of cis-regulatory elements drives species-specific traits1, but how this manifests in the evolution of the neocortex at the molecular and cellular level remains unclear. Here we investigated the gene regulatory programs in the primary motor cortex of human, macaque, marmoset and mouse using single-cell multiomics assays, generating gene expression, chromatin accessibility, DNA methylome and chromosomal conformation profiles from a total of over 200,000 cells. From these data, we show evidence that divergence of transcription factor expression corresponds to species-specific epigenome landscapes. We find that conserved and divergent gene regulatory features are reflected in the evolution of the three-dimensional genome. Transposable elements contribute to nearly 80% of the human-specific candidate cis-regulatory elements in cortical cells. Through machine learning, we develop sequence-based predictors of candidate cis-regulatory elements in different species and demonstrate that the genomic regulatory syntax is highly preserved from rodents to primates. Finally, we show that epigenetic conservation combined with sequence similarity helps to uncover functional cis-regulatory elements and enhances our ability to interpret genetic variants contributing to neurological disease and traits.

Single-cell analysis of chromatin accessibility in the adult mouse brain

Recent advances in single-cell technologies have led to the discovery of thousands of brain cell types; however, our understanding of the gene regulatory programs in these cell types is far from complete1–4. Here we report a comprehensive atlas of candidate cis-regulatory DNA elements (cCREs) in the adult mouse brain, generated by analysing chromatin accessibility in 2.3 million individual brain cells from 117 anatomical dissections. The atlas includes approximately 1 million cCREs and their chromatin accessibility across 1,482 distinct brain cell populations, adding over 446,000 cCREs to the most recent such annotation in the mouse genome. The mouse brain cCREs are moderately conserved in the human brain. The mouse-specific cCREs—specifically, those identified from a subset of cortical excitatory neurons—are strongly enriched for transposable elements, suggesting a potential role for transposable elements in the emergence of new regulatory programs and neuronal diversity. Finally, we infer the gene regulatory networks in over 260 subclasses of mouse brain cells and develop deep-learning models to predict the activities of gene regulatory elements in different brain cell types from the DNA sequence alone. Our results provide a resource for the analysis of cell-type-specific gene regulation programs in both mouse and human brains.

Integrative single‐nucleus multi‐omics analysis prioritizes candidate cis and trans regulatory networks and their target genes in Alzheimer’s disease brains

AbstractBackgroundThe genetic underpinnings of late‐onset Alzheimer’s disease (LOAD) are yet to be fully elucidated. Although numerous LOAD‐associated loci have been discovered, the causal variants and their target genes remain largely unknown. Since the brain is composed of heterogenous cell subtypes, it is imperative to study the brain on a cell subtype specific level to explore the biological processes underlying LOAD.MethodsIn this study we performed a parallel single‐nucleus (sn) multi‐omics analysis to simultaneously profile gene expression (snRNA‐seq) and chromatin accessibility (snATAC‐seq) using nuclei from 12 normal and 12 LOAD brains. We developed a pipeline based on integrative analysis of multimodal datasets that utilizes several bioinformatics packages to catalogue cis‐ and trans‐ regulatory network and their target genes.ResultsWe identified cell subtype specific LOAD‐associated differentially expressed genes (DEGs), differentially accessible peaks (DAPs) and cis co‐accessibility networks (CCANs). Integrative analysis defined disease‐relevant CCANs in multiple cell subtypes and discovered LOAD‐associated cell subtype specific candidate cis regulatory elements (cCRE), their candidate target genes, and trans‐interacting transcription factors (TF), some of which were LOAD‐DEG, for example, ELK1 in a specific sub type of excitatory neurons and ATF7 and JUN, found in multiple cell subtypes. Overall, our analysis discovered 53 new candidate LOAD genes and validated 16 gene previously implicated in LOAD. Finally, we focused on a subset of cell subtype‐specific CCANs that overlap known LOAD‐GWAS regions and catalogued putative functional SNPs disrupting TF motifs within LOAD‐cCREs linked to LOAD‐DEGs including, APOE and MYO1E in a specific subtype of microglia.ConclusionsIn this study we identified candidate cis‐ and trans‐ regulatory factors and their target genes that contribute to the pathogenesis of LOAD. To our knowledge, this study represents the most comprehensive systematic interrogation of regulatory networks underlying gene dysregulation in LOAD at an unprecedented cell‐subtype resolution. Collectively, our findings provide a rich dataset for future mechanistic experiments, confirm known LOAD‐GWAS loci while also identifying novel loci, and suggest the disease‐relevant cell types and subtypes for follow‐up validation studies using in vitro and in vivo disease model systems. This information is important for the development of new therapeutic targets and interventions for LOAD.

CREaTor: zero-shot cis-regulatory pattern modeling with attention mechanisms

Linking cis-regulatory sequences to target genes has been a long-standing challenge. In this study, we introduce CREaTor, an attention-based deep neural network designed to model cis-regulatory patterns for genomic elements up to 2 Mb from target genes. Coupled with a training strategy that predicts gene expression from flanking candidate cis-regulatory elements (cCREs), CREaTor can model cell type-specific cis-regulatory patterns in new cell types without prior knowledge of cCRE-gene interactions or additional training. The zero-shot modeling capability, combined with the use of only RNA-seq and ChIP-seq data, allows for the ready generalization of CREaTor to a broad range of cell types.

A comparative atlas of single-cell chromatin accessibility in the human brain.

Recent advances in single-cell transcriptomics have illuminated the diverse neuronal and glial cell types within the human brain. However, the regulatory programs governing cell identity and function remain unclear. Using a single-nucleus assay for transposase-accessible chromatin using sequencing (snATAC-seq), we explored open chromatin landscapes across 1.1 million cells in 42 brain regions from three adults. Integrating this data unveiled 107 distinct cell types and their specific utilization of 544,735 candidate cis-regulatory DNA elements (cCREs) in the human genome. Nearly a third of the cCREs demonstrated conservation and chromatin accessibility in the mouse brain cells. We reveal strong links between specific brain cell types and neuropsychiatric disorders including schizophrenia, bipolar disorder, Alzheimer's disease (AD), and major depression, and have developed deep learning models to predict the regulatory roles of noncoding risk variants in these disorders.

Integrative single-nucleus multi-omics analysis prioritizes candidate cis and trans regulatory networks and their target genes in Alzheimer’s disease brains

BackgroundThe genetic underpinnings of late-onset Alzheimer’s disease (LOAD) are yet to be fully elucidated. Although numerous LOAD-associated loci have been discovered, the causal variants and their target genes remain largely unknown. Since the brain is composed of heterogenous cell subtypes, it is imperative to study the brain on a cell subtype specific level to explore the biological processes underlying LOAD.MethodsHere, we present the largest parallel single-nucleus (sn) multi-omics study to simultaneously profile gene expression (snRNA-seq) and chromatin accessibility (snATAC-seq) to date, using nuclei from 12 normal and 12 LOAD brains. We identified cell subtype clusters based on gene expression and chromatin accessibility profiles and characterized cell subtype-specific LOAD-associated differentially expressed genes (DEGs), differentially accessible peaks (DAPs) and cis co-accessibility networks (CCANs).ResultsIntegrative analysis defined disease-relevant CCANs in multiple cell subtypes and discovered LOAD-associated cell subtype-specific candidate cis regulatory elements (cCREs), their candidate target genes, and trans-interacting transcription factors (TFs), some of which, including ELK1, JUN, and SMAD4 in excitatory neurons, were also LOAD-DEGs. Finally, we focused on a subset of cell subtype-specific CCANs that overlap known LOAD-GWAS regions and catalogued putative functional SNPs changing the affinities of TF motifs within LOAD-cCREs linked to LOAD-DEGs, including APOE and MYO1E in a specific subtype of microglia and BIN1 in a subpopulation of oligodendrocytes.ConclusionsTo our knowledge, this study represents the most comprehensive systematic interrogation to date of regulatory networks and the impact of genetic variants on gene dysregulation in LOAD at a cell subtype resolution. Our findings reveal crosstalk between epigenetic, genomic, and transcriptomic determinants of LOAD pathogenesis and define catalogues of candidate genes, cCREs, and variants involved in LOAD genetic etiology and the cell subtypes in which they act to exert their pathogenic effects. Overall, these results suggest that cell subtype-specific cis–trans interactions between regulatory elements and TFs, and the genes dysregulated by these networks contribute to the development of LOAD.

Functional characterization of Alzheimer's disease genetic variants in microglia.

Candidate cis-regulatory elements (cCREs) in microglia demonstrate the most substantial enrichment for Alzheimer's disease (AD) heritability compared to other brain cell types. However, whether and how these genome-wide association studies (GWAS) variants contribute to AD remain elusive. Here we prioritize 308 previously unreported AD risk variants at 181 cCREs by integrating genetic information with microglia-specific 3D epigenome annotation. We further establish the link between functional variants and target genes by single-cell CRISPRi screening in microglia. In addition, we show that AD variants exhibit allelic imbalance on target gene expression. In particular, rs7922621 is the effective variant in controlling TSPAN14 expression among other nominated variants in the same cCRE and exerts multiple physiological effects including reduced cell surface ADAM10 and altered soluble TREM2 (sTREM2) shedding. Our work represents a systematic approach to prioritize and characterize AD-associated variants and provides a roadmap for advancing genetic association to experimentally validated cell-type-specific phenotypes and mechanisms.

Droplet-based single-cell joint profiling of histone modifications and transcriptomes.

We previously reported Paired-Tag, a combinatorial indexing-based method that can simultaneously map histone modifications and gene expression at single-cell resolution at scale. However, the lengthy procedure of Paired-Tag has hindered its general adoption in the community. To address this bottleneck, we developed a droplet-based Paired-Tag protocol that is faster and more accessible than the previous method. Using cultured mammalian cells and primary brain tissues, we demonstrate its superior performance at identifying candidate cis-regulatory elements and associating their dynamic chromatin state to target gene expression in each constituent cell type in a complex tissue.

Characterization of an eye field-like state during optic vesicle organoid development.

Specification of the eye field (EF) within the neural plate marks the earliest detectable stage of eye development. Experimental evidence, primarily from non-mammalian model systems, indicates that the stable formation of this group of cells requires the activation of a set of key transcription factors (TFs). This critical event is challenging to probe in mammals and, quantitatively, little is known regarding the regulation of the transition of cells to this ocular fate. Using optic vesicle organoids to model the onset of the EF, we generate timecourse transcriptomic data allowing us to identify dynamic gene expression programs that characterise this cellular-state transition. Integrating this with chromatin accessibility data suggests a direct role of canonical EFTFs in regulating these gene expression changes, and highlights candidate cis-regulatory elements through which these TFs act. Finally, we begin to test a subset of these candidate enhancer elements, within the organoid system, by perturbing the underlying DNA sequence and measuring transcriptomic changes during EF activation.

Bioinformatics pipeline to guide post-GWAS studies in Alzheimer's: A new catalogue of disease candidate short structural variants.

Short structural variants (SSVs), including insertions/deletions (indels), are common in the human genome and impact disease risk. The role of SSVs in late-onset Alzheimer's disease (LOAD) has been understudied. In this study, we developed a bioinformatics pipeline of SSVs within LOAD-genome-wide association study (GWAS) regions to prioritize regulatory SSVs based on the strength of their predicted effect on transcription factor (TF) binding sites. The pipeline utilized publicly available functional genomics data sources including candidate cis-regulatory elements (cCREs) from ENCODE and single-nucleus (sn)RNA-seq data from LOAD patient samples. We catalogued 1581 SSVs in candidate cCREs in LOAD GWAS regions that disrupted 737 TF sites. That included SSVs that disrupted the binding of RUNX3, SPI1, and SMAD3, within the APOE-TOMM40, SPI1, and MS4A6A LOAD regions. The pipeline developed here prioritized non-coding SSVs in cCREs and characterized their putative effects on TF binding. The approach integrates multiomics datasets for validation experiments using disease models.

Interpreting non-coding disease-associated human variants using single-cell epigenomics.

Genome-wide association studies (GWAS) have linked hundreds of thousands of sequence variants in the human genome to common traits and diseases. However, translating this knowledge into a mechanistic understanding of disease-relevant biology remains challenging, largely because such variants are predominantly in non-protein-coding sequences that still lack functional annotation at cell-type resolution. Recent advances in single-cell epigenomics assays have enabled the generation of cell type-, subtype- and state-resolved maps of the epigenome in heterogeneous human tissues. These maps have facilitated cell type-specific annotation of candidate cis-regulatory elements and their gene targets in the human genome, enhancing our ability to interpret the genetic basis of common traits and diseases.

Mammalian evolution of human cis-regulatory elements and transcription factor binding sites.

Understanding the regulatory landscape of the human genome is a long-standing objective of modern biology. Using the reference-free alignment across 241 mammalian genomes produced by the Zoonomia Consortium, we charted evolutionary trajectories for 0.92 million human candidate cis-regulatory elements (cCREs) and 15.6 million human transcription factor binding sites (TFBSs). We identified 439,461 cCREs and 2,024,062 TFBSs under evolutionary constraint. Genes near constrained elements perform fundamental cellular processes, whereas genes near primate-specific elements are involved in environmental interaction, including odor perception and immune response. About 20% of TFBSs are transposable element-derived and exhibit intricate patterns of gains and losses during primate evolution whereas sequence variants associated with complex traits are enriched in constrained TFBSs. Our annotations illuminate the regulatory functions of the human genome.

Snapshot: a package for clustering and visualizing epigenetic history during cell differentiation

BackgroundEpigenetic modification of chromatin plays a pivotal role in regulating gene expression during cell differentiation. The scale and complexity of epigenetic data pose significant challenges for biologists to identify the regulatory events controlling cell differentiation.ResultsTo reduce the complexity, we developed a package, called Snapshot, for clustering and visualizing candidate cis-regulatory elements (cCREs) based on their epigenetic signals during cell differentiation. This package first introduces a binarized indexing strategy for clustering the cCREs. It then provides a series of easily interpretable figures for visualizing the signal and epigenetic state patterns of the cCREs clusters during the cell differentiation. It can also use different hierarchies of cell types to highlight the epigenetic history specific to any particular cell lineage. We demonstrate the utility of Snapshot using data from a consortium project for ValIdated Systematic IntegratiON (VISION) of epigenomic data in hematopoiesis.ConclusionThe package Snapshot can identify all distinct clusters of genomic locations with unique epigenetic signal patterns during cell differentiation. It outperforms other methods in terms of interpreting and reproducing the identified cCREs clusters. The package of Snapshot is available at GitHub: https://github.com/guanjue/Snapshot.

Major cell-types in multiomic single-nucleus datasets impact statistical modeling of links between regulatory sequences and target genes

Epigenomic profiling, including ATACseq, is one of the main tools used to define enhancers. Because enhancers are overwhelmingly cell-type specific, inference of their activity is greatly limited in complex tissues. Multiomic assays that probe in the same nucleus both the open chromatin landscape and gene expression levels enable the study of correlations (links) between these two modalities. Current best practices to infer the regulatory effect of candidate cis-regulatory elements (cCREs) in multiomic data involve removing biases associated with GC content by generating null distributions of matched ATACseq peaks drawn from different chromosomes. This strategy has been broadly adopted by popular single-nucleus multiomic workflows such as Signac. Here, we uncovered limitations and confounders of this approach. We found a strong loss of power to detect a regulatory effect for cCREs with high read counts in the dominant cell-type. We showed that this is largely due to cell-type-specific trans-ATACseq peak correlations creating bimodal null distributions. We tested alternative models and concluded that physical distance and/or the raw Pearson correlation coefficients are the best predictors for peak-gene links when compared to predictions from Epimap (e.g. CD14 area under the curve [AUC] = 0.51 with the method implemented in Signac vs. 0.71 with the Pearson correlation coefficients) or validation by CRISPR perturbations (AUC = 0.63 vs. 0.73).

Single nucleus multiomics identifies ZEB1 and MAFB as candidate regulators of Alzheimer's disease-specific cis-regulatory elements.

Cell type-specific transcriptional differences between brain tissues from donors with Alzheimer's disease (AD) and unaffected controls have been well documented, but few studies have rigorously interrogated the regulatory mechanisms responsible for these alterations. We performed single nucleus multiomics (snRNA-seq plus snATAC-seq) on 105,332 nuclei isolated from cortical tissues from 7 AD and 8 unaffected donors to identify candidate cis-regulatory elements (CREs) involved in AD-associated transcriptional changes. We detected 319,861 significant correlations, or links, between gene expression and cell type-specific transposase accessible regions enriched for active CREs. Among these, 40,831 were unique to AD tissues. Validation experiments confirmed the activity of many regions, including several candidateregulators of APP expression. We identified ZEB1 and MAFB as candidate transcription factorsplaying important roles in AD-specific gene regulation in neurons and microglia, respectively. Microglia links were globally enriched for heritability of AD risk and previously identified active regulatory regions.