The contribution of silencer variants to human diseases.

Although disease-causal genetic variants have been found within silencer sequences, we still lack a comprehensive analysis of the association of silencers with diseases. Here, we profiled GWAS variants in 2.8 million candidate silencers across 97 human samples derived from a diverse panel of tissues and developmental time points, using deep learning models. We show that candidate silencers exhibit strong enrichment in disease-associated variants, and several diseases display a much stronger association with silencer variants than enhancer variants. Close to 52% of candidate silencers cluster, forming silencer-rich loci, and, in the loci of Parkinson's-disease-hallmark genes TRIM31 and MAL, the associated SNPs densely populate clustered candidate silencers rather than enhancers displaying an overall 2-fold enrichment in silencers versus enhancers. The disruption of apoptosis in neuronal cells is associated with both schizophrenia and bipolar disorder and can largely be attributed to variants within candidate silencers. Our model permits a mechanistic explanation of causative SNP effects by identifying altered binding of tissue-specific repressors and activators, validated with a 70% of directional concordance using SNP-SELEX. Narrowing the focus of the analysis to individual silencer variants, experimental data confirms the role of the rs62055708 SNP in Parkinson's disease, rs2535629 in schizophrenia, and rs6207121 in Type 1 diabetes. In summary, our results indicate that advances in deep learning models for discovery of disease-causal variants within candidate silencers effectively 'double' the number of functionally characterized GWAS variants. This provides a basis for explaining mechanisms of action and designing novel diagnostics and therapeutics.

Detection of new pioneer transcription factors as cell-type-specific nucleosome binders.

Wrapping of DNA into nucleosomes restricts accessibility to DNA and may affect the recognition of binding motifs by transcription factors. A certain class of transcription factors, the pioneer transcription factors, can specifically recognize their DNA binding sites on nucleosomes, initiate local chromatin opening, and facilitate the binding of co-factors in a cell-type-specific manner. For the majority of human pioneer transcription factors, the locations of their binding sites, mechanisms of binding, and regulation remain unknown. We have developed a computational method to predict the cell-type-specific ability of transcription factors to bind nucleosomes by integrating ChIP-seq, MNase-seq, and DNase-seq data with details of nucleosome structure. We have demonstrated the ability of our approach in discriminating pioneer from canonical transcription factors and predicted new potential pioneer transcription factors in H1, K562, HepG2, and HeLa-S3 cell lines. Last, we systematically analyzed the interaction modes between various pioneer transcription factors and detected several clusters of distinctive binding sites on nucleosomal DNA.

Modeling islet enhancers using deep learning identifies candidate causal variants at loci associated with T2D and glycemic traits.

Genetic association studies have identified hundreds of independent signals associated with type 2 diabetes (T2D) and related traits. Despite these successes, the identification of specific causal variants underlying a genetic association signal remains challenging. In this study, we describe a deep learning (DL) method to analyze the impact of sequence variants on enhancers. Focusing on pancreatic islets, a T2D relevant tissue, we show that our model learns islet-specific transcription factor (TF) regulatory patterns and can be used to prioritize candidate causal variants. At 101 genetic signals associated with T2D and related glycemic traits where multiple variants occur in linkage disequilibrium, our method nominates a single causal variant for each association signal, including three variants previously shown to alter reporter activity in islet-relevant cell types. For another signal associated with blood glucose levels, we biochemically test all candidate causal variants from statistical fine-mapping using a pancreatic islet beta cell line and show biochemical evidence of allelic effects on TF binding for the model-prioritized variant. To aid in future research, we publicly distribute our model and islet enhancer perturbation scores across ~67 million genetic variants. We anticipate that DL methods like the one presented in this study will enhance the prioritization of candidate causal variants for functional studies.

Detection of new pioneer transcription factors as cell-type specific nucleosome binders.

Wrapping of DNA into nucleosomes restricts accessibility to the DNA and may affect the recognition of binding motifs by transcription factors. A certain class of transcription factors, the pioneer transcription factors, can specifically recognize their DNA binding sites on nucleosomes, may initiate local chromatin opening and facilitate the binding of co-factors in a cell-type-specific manner. For the majority of human pioneer transcription factors, the locations of their binding sites, mechanisms of binding and regulation remain unknown. We have developed a computational method to predict the cell-type-specific ability of transcription factors to bind nucleosomes by integrating ChIP-seq, MNase-seq and DNase-seq data with details of nucleosome structure. We have demonstrated the ability of our approach in discriminating pioneer from canonical transcription factors and predicted new potential pioneer transcription factors in H1, K562, HepG2 and HeLa cell lines. Lastly, we systemically analyzed the interaction modes between various pioneer transcription factors and detected several clusters of distinctive binding sites on nucleosomal DNA.

ChromDL: a next-generation regulatory DNA classifier.

MOTIVATION: Predicting the regulatory function of non-coding DNA using only the DNA sequence continues to be a major challenge in genomics. With the advent of improved optimization algorithms, faster GPU speeds, and more intricate machine-learning libraries, hybrid convolutional and recurrent neural network architectures can be constructed and applied to extract crucial information from non-coding DNA. RESULTS: Using a comparative analysis of the performance of thousands of Deep Learning architectures, we developed ChromDL, a neural network architecture combining bidirectional gated recurrent units, convolutional neural networks, and bidirectional long short-term memory units, which significantly improves upon a range of prediction metrics compared to its predecessors in transcription factor binding site, histone modification, and DNase-I hyper-sensitive site detection. Combined with a secondary model, it can be utilized for accurate classification of gene regulatory elements. The model can also detect weak transcription factor binding as compared to previously developed methods and has the potential to help delineate transcription factor binding motif specificities. AVAILABILITY AND IMPLEMENTATION: The ChromDL source code can be found at https://github.com/chrishil1/ChromDL.

Sequence characteristics and an accurate model of abundant hyperactive loci in the human genome.

Enhancers and promoters are classically considered to be bound by a small set of TFs in a sequence-specific manner. This assumption has come under increasing skepticism as the datasets of ChIP-seq assays of TFs have expanded. In particular, high-occupancy target (HOT) loci attract hundreds of TFs with seemingly no detectable correlation between ChIP-seq peaks and DNA-binding motif presence. Here, we used a set of 1,003 TF ChIP-seq datasets (HepG2, K562, H1) to analyze the patterns of ChIP-seq peak co-occurrence in combination with functional genomics datasets. We identified 43,891 HOT loci forming at the promoter (53%) and enhancer (47%) regions. HOT promoters regulate housekeeping genes, whereas HOT enhancers are involved in tissue-specific process regulation. HOT loci form the foundation of human super-enhancers and evolve under strong negative selection, with some of these loci being located in ultraconserved regions. Sequence-based classification analysis of HOT loci suggested that their formation is driven by the sequence features, and the density of mapped ChIP-seq peaks across TF-bound loci correlates with sequence features and the expression level of flanking genes. Based on the affinities to bind to promoters and enhancers we detected 5 distinct clusters of TFs that form the core of the HOT loci. We report an abundance of HOT loci in the human genome and a commitment of 51% of all TF ChIP-seq binding events to HOT locus formation thus challenging the classical model of enhancer activity and propose a model of HOT locus formation based on the existence of large transcriptional condensates.

De novo human brain enhancers created by single-nucleotide mutations.

Advanced human cognition is attributed to increased neocortex size and complexity, but the underlying evolutionary and regulatory mechanisms are largely unknown. Using human and macaque embryonic neocortical H3K27ac data coupled with a deep learning model of enhancers, we identified ~4000 enhancer gains in humans, which, per our model, can often be attributed to single-nucleotide essential mutations. Our analyses suggest that functional gains in embryonic brain development are associated with de novo enhancers whose putative target genes exhibit increased expression in progenitor cells and interneurons and partake in critical neural developmental processes. Essential mutations alter enhancer activity through altered binding of key transcription factors (TFs) of embryonic neocortex, including ISL1, POU3F2, PITX1/2, and several SOX TFs, and are associated with central nervous system disorders. Overall, our results suggest that essential mutations lead to gain of embryonic neocortex enhancers, which orchestrate expression of genes involved in critical developmental processes associated with human cognition.

ChromDL: A Next-Generation Regulatory DNA Classifier.

Motivation: Predicting the regulatory function of non-coding DNA using only the DNA sequence continues to be a major challenge in genomics. With the advent of improved optimization algorithms, faster GPU speeds, and more intricate machine learning libraries, hybrid convolutional and recurrent neural network architectures can be constructed and applied to extract crucial information from non-coding DNA. Results: Using a comparative analysis of the performance of thousands of Deep Learning (DL) architectures, we developed ChromDL, a neural network architecture combining bidirectional gated recurrent units (BiGRU), convolutional neural networks (CNNs), and bidirectional long short-term memory units (BiLSTM), which significantly improves upon a range of prediction metrics compared to its predecessors in transcription factor binding site (TFBS), histone modification (HM), and DNase-I hypersensitive site (DHS) detection. Combined with a secondary model, it can be utilized for accurate classification of gene regulatory elements. The model can also detect weak transcription factor (TF) binding with higher accuracy as compared to previously developed methods and has the potential to accurately delineate TF binding motif specificities. Availability: The ChromDL source code can be found at https://github.com/chrishil1/ChromDL .

A regulatory network of Sox and Six transcription factors initiate a cell fate transformation during hearing regeneration in adult zebrafish.

Using adult zebrafish inner ears as a model for sensorineural regeneration, we ablated the mechanosensory receptors and characterized the single-cell epigenome and transcriptome at consecutive time points during hair cell regeneration. We utilized deep learning on the regeneration-induced open chromatin sequences and identified cell-specific transcription factor (TF) motif patterns. Enhancer activity correlated with gene expression and identified potential gene regulatory networks. A pattern of overlapping Sox- and Six-family TF gene expression and binding motifs was detected, suggesting a combinatorial program of TFs driving regeneration and cell identity. Pseudotime analysis of single-cell transcriptomic data suggested that support cells within the sensory epithelium changed cell identity to a "progenitor" cell population that could differentiate into hair cells. We identified a 2.6 kb DNA enhancer upstream of the sox2 promoter that, when deleted, showed a dominant phenotype that resulted in a hair-cell-regeneration-specific deficit in both the lateral line and adult inner ear.

Heterogeneity of enhancers embodies shared and representative functional groups underlying developmental and cell type-specific gene regulation.

While enhancers in a particular tissue coordinately fulfill regulatory functions, these functions are heterogeneous in nature and comprise of multiple enhancer subclasses and the associated regulatory mechanisms. In this work, we used multiple cell lines to identify enhancer subclasses linked to development, differentiation, and cellular identity. We found that enhancer functional heterogeneity during development encompasses subclasses of ubiquitous functions (11%), development specific regulatory activity (62%), and chromatin interactions (12%). In differentiated cell lines, ubiquitous enhancers (10%) stay active across multiple cell lines.They are accompanied by a large enhancer subclass (ranging from 33% to 63%) with functions specific to the corresponding lineage. The remaining enhancers (27-40%) establish regulatory chromatin structure and facilitate interactions of cell type-specific enhancers with their target promoters. In addition to specialized functions of cell type-specific enhancers, we show that proper accounting of enhancer heterogeneity leads to a 10% increase in accuracy of enhancer classification, which significantly improves the modeling of enhancers and identification of underlying regulatory mechanisms. In summary, our observations suggest that although cell type-specific enhancers are heterogeneous and coordinate different regulatory programs, enhancers from different cell lines maintain common categories of functional groups across developmental and differentiation stages, indicating a higher order rule followed by enhancer-gene regulation.

Enhancer-silencer transitions in the human genome.

Dual-function regulatory elements (REs), acting as enhancers in some cellular contexts and as silencers in others, have been reported to facilitate the precise gene regulatory response to developmental signals in Drosophila melanogaster However, with few isolated examples detected, dual-function REs in mammals have yet to be systematically studied. We herein investigated this class of REs in the human genome and profiled their activity across multiple cell types. Focusing on enhancer-silencer transitions specific to the development of T cells, we built an accurate deep learning classifier of REs and identified about 12,000 silencers active in primary peripheral blood T cells that act as enhancers in embryonic stem cells. Compared with regular silencers, these dual-function REs are evolving under stronger purifying selection and are enriched for mutations associated with disease phenotypes and altered gene expression. In addition, they are enriched in the loci of transcriptional regulators, such as transcription factors (TFs) and chromatin remodeling genes. Dual-function REs consist of two intertwined but largely distinct sets of binding sites bound by either activating or repressing TFs, depending on the type of RE function in a given cell line. This indicates the recruitment of different TFs for different regulatory modes and a complex DNA sequence composition of these REs with dual activating and repressive encoding. With an estimated >6% of cell type-specific human silencers acting as dual-function REs, this overlooked class of REs requires a specific investigation on how their inherent functional plasticity might be a contributing factor to human diseases.

A model of active transcription hubs that unifies the roles of active promoters and enhancers.

An essential questions of gene regulation is how large number of enhancers and promoters organize into gene regulatory loops. Using transcription-factor binding enrichment as an indicator of enhancer strength, we identified a portion of H3K27ac peaks as potentially strong enhancers and found a universal pattern of promoter and enhancer distribution: At actively transcribed regions of length of ∼200-300 kb, the numbers of active promoters and enhancers are inversely related. Enhancer clusters are associated with isolated active promoters, regardless of the gene's cell-type specificity. As the number of nearby active promoters increases, the number of enhancers decreases. At regions where multiple active genes are closely located, there are few distant enhancers. With Hi-C analysis, we demonstrate that the interactions among the regulatory elements (active promoters and enhancers) occur predominantly in clusters and multiway among linearly close elements and the distance between adjacent elements shows a preference of ∼30 kb. We propose a simple rule of spatial organization of active promoters and enhancers: Gene transcriptions and regulations mainly occur at local active transcription hubs contributed dynamically by multiple elements from linearly close enhancers and/or active promoters. The hub model can be represented with a flower-shaped structure and implies an enhancer-like role of active promoters.

Comprehensive In Vivo Interrogation Reveals Phenotypic Impact of Human Enhancer Variants.

Establishing causal links between non-coding variants and human phenotypes is an increasing challenge. Here, we introduce a high-throughput mouse reporter assay for assessing the pathogenic potential of human enhancer variants in vivo and examine nearly a thousand variants in an enhancer repeatedly linked to polydactyly. We show that 71% of all rare non-coding variants previously proposed as causal lead to reporter gene expression in a pattern consistent with their pathogenic role. Variants observed to alter enhancer activity were further confirmed to cause polydactyly in knockin mice. We also used combinatorial and single-nucleotide mutagenesis to evaluate the in vivo impact of mutations affecting all positions of the enhancer and identified additional functional substitutions, including potentially pathogenic variants hitherto not observed in humans. Our results uncover the functional consequences of hundreds of mutations in a phenotype-associated enhancer and establish a widely applicable strategy for systematic in vivo evaluation of human enhancer variants.

Enhancer jungles establish robust tissue-specific regulatory control in the human genome.

An increasing number of studies suggest that functionally redundant enhancers safeguard development via buffering gene expression against environmental and genetic perturbations. Here, we identified over-represented clusters of enhancers (enhancer jungles or EJs) in human B lymphoblastoid cells. We found that EJs tend to associate with genes involved in the activation of the immune system response. Although spanning multiple genes, the enhancers within an EJ tend to collaborate with each other on regulating a single gene. The employment of homotypic transcription factor binding sites (TFBSs) in EJ enhancers and heterotypic TFBSs between constituent enhancers within an EJ may safeguard a robust transcriptional output of the target gene. EJ enhancers evolve under a weaker selective pressure compared to regular enhancers (REs), and approximately 35% of EJs do not have orthologues in the mouse genome. In GM12878, these human-specific EJs appear to regulate genes associated with the adaptive immune system response, while the conserved EJs are associated with innate immunity. Recently acquired human EJs are associated with the higher level of target gene expression compared with conserved EJs, thus facilitating the environmental adaptation of the organism during evolution. In short, the existence of EJs is a common regulatory architecture conferring a robust regulatory control for key lineage genes.

The first enhancer in an enhancer chain safeguards subsequent enhancer-promoter contacts from a distance.

BACKGROUND: Robustness and evolutionary stability of gene expression in the human genome are established by an array of redundant enhancers. RESULTS: Using Hi-C data in multiple cell lines, we report a comprehensive map of promoters and active enhancers connected by chromatin contacts, spanning 9000 enhancer chains in 4 human cell lines associated with 2600 human genes. We find that the first enhancer in a chain that directly contacts the target promoter is commonly located at a greater genomic distance from the promoter than the second enhancer in a chain, 96 kb vs. 45 kb, respectively. The first enhancer also features higher similarity to the promoter in terms of tissue specificity and higher enrichment of loop factors, suggestive of a stable primary contact with the promoter. In contrast, a chain of enhancers which connects to the target promoter through a neutral DNA segment instead of an enhancer is associated with a significant decrease in target gene expression, suggesting an important role of the first enhancer in initiating transcription using the target promoter and bridging the promoter with other regulatory elements in the locus. CONCLUSIONS: The widespread chained structure of gene enhancers in humans reveals that the primary, critical enhancer is distal, commonly located further away than other enhancers. This first, distal enhancer establishes contacts with multiple regulatory elements and safeguards a complex regulatory program of its target gene.

Stable enhancers are active in development, and fragile enhancers are associated with evolutionary adaptation.

BACKGROUND: Despite continual progress in the identification and characterization of trait- and disease-associated variants that disrupt transcription factor (TF)-DNA binding, little is known about the distribution of TF binding deactivating mutations (deMs) in enhancer sequences. Here, we focus on elucidating the mechanism underlying the different densities of deMs in human enhancers. RESULTS: We identify two classes of enhancers based on the density of nucleotides prone to deMs. Firstly, fragile enhancers with abundant deM nucleotides are associated with the immune system and regular cellular maintenance. Secondly, stable enhancers with only a few deM nucleotides are associated with the development and regulation of TFs and are evolutionarily conserved. These two classes of enhancers feature different regulatory programs: the binding sites of pioneer TFs of FOX family are specifically enriched in stable enhancers, while tissue-specific TFs are enriched in fragile enhancers. Moreover, stable enhancers are more tolerant of deMs due to their dominant employment of homotypic TF binding site (TFBS) clusters, as opposed to the larger-extent usage of heterotypic TFBS clusters in fragile enhancers. Notably, the sequence environment and chromatin context of the cognate motif, other than the motif itself, contribute more to the susceptibility to deMs of TF binding. CONCLUSIONS: This dichotomy of enhancer activity is conserved across different tissues, has a specific footprint in epigenetic profiles, and argues for a bimodal evolution of gene regulatory programs in vertebrates. Specifically encoded stable enhancers are evolutionarily conserved and associated with development, while differently encoded fragile enhancers are associated with the adaptation of species.

Identification of human silencers by correlating cross-tissue epigenetic profiles and gene expression.

Compared to enhancers, silencers are notably difficult to identify and validate experimentally. In search for human silencers, we utilized H3K27me3-DNase I hypersensitive site (DHS) peaks with tissue specificity negatively correlated with the expression of nearby genes across 25 diverse cell lines. These regions are predicted to be silencers since they are physically linked, using Hi-C loops, or associated, using expression quantitative trait loci (eQTL) results, with a decrease in gene expression much more frequently than general H3K27me3-DHSs. Also, these regions are enriched for the binding sites of transcriptional repressors (such as CTCF, MECOM, SMAD4, and SNAI3) and depleted of the binding sites of transcriptional activators. Using sequence signatures of these regions, we constructed a computational model and predicted approximately 10,000 additional silencers per cell line and demonstrated that the majority of genes linked to these silencers are expressed at a decreased level. Furthermore, single nucleotide polymorphisms (SNPs) in predicted silencers are significantly associated with disease phenotypes. Finally, our results show that silencers commonly interact with enhancers to affect the transcriptional dynamics of tissue-specific genes and to facilitate fine-tuning of transcription in the human genome.

Dichotomy in redundant enhancers points to presence of initiators of gene regulation.

BACKGROUND: The regulatory landscape of a gene locus often consists of several functionally redundant enhancers establishing phenotypic robustness and evolutionary stability of its regulatory program. However, it is unclear what mechanisms are employed by redundant enhancers to cooperatively orchestrate gene expression. RESULTS: By comparing redundant enhancers to single enhancers (enhancers present in a single copy in a gene locus), we observed that the DNA sequence encryption differs between these two classes of enhancers, suggesting a difference in their regulatory mechanisms. Initiator enhancers, which are a subset of redundant enhancers and show similar sequence encryption to single enhancers, differ from the rest of redundant enhancers in their sequence encryption, evolutionary conservation and proximity to target genes. Genes hosting initiator enhancers in their loci feature elevated levels of expression. Initiator enhancers show a high level of 3D chromatin contacts with both transcription start sites and regular enhancers, suggesting their roles as primary activators and intermediate catalysts of gene expression, through which the regulatory signals of redundant enhancers are propagated to the target genes. In addition, GWAS and eQTLs variants are significantly enriched in initiator enhancers compared to redundant enhancers, suggesting a key functional role these sequences play in gene regulation. CONCLUSIONS: The specific characteristics and widespread abundance of initiator enhancers advocate for a possible universal hierarchical mechanism of tissue-specific gene regulation involving multiple redundant enhancers acting through initiator enhancers.

Enhancer reprogramming in mammalian genomes.

BACKGROUND: Transcription factor binding site (TFBS) loss, gain, and reshuffling within the sequence of a regulatory element could alter the function of that regulatory element. Some of the changes will be detrimental to the fitness of the species and will result in gradual removal from a population, while other changes would be either beneficial or just a part of genetic drift and end up being fixed in a population. This "reprogramming" of regulatory elements results in modification of the gene regulatory landscape during evolution. RESULTS: We identified reprogrammed enhancers (RPEs) by comparing the distribution of tissue-specific enhancers in the human and mouse genomes. We observed that around 30% of mammalian enhancers have been reprogrammed after the human-mouse speciation. In 79% of cases, the reprogramming of an enhancer resulted in a quantifiably different expression of a flanking gene. In the case of the Thy-1 cell surface antigen gene, for example, enhancer reprogramming is associated with cortex to thymus change in gene expression. To understand the mechanisms of enhancer reprogramming, we profiled the evolutionary changes in the TFBS enhancer content and found that enhancer reprogramming took place through the acquisition of new TFBSs in 72% of reprogramming events. CONCLUSIONS: Our results suggest that enhancer reprogramming takes place within well-established regulatory loci with RPEs contributing additively to fine-tuning of the gene regulatory program in mammals. We also found evidence for acquisition of novel gene function through enhancer reprogramming, which allows expansion of gene regulatory landscapes into new regulatory domains.

The hypothesis of ultraconserved enhancer dispensability overturned.

Two recent studies explore how redundant enhancers in mice really are.