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Summary: Addressing deleterious effects of noncoding mutations is an essential step towards the identification of disease-causal mutations of gene regulatory elements. Several methods for quantifying the deleteriousness of noncoding mutations using artificial intelligence, deep learning and other approaches have been recently proposed. Although the majority of the proposed methods have demonstrated excellent accuracy on different test sets, there is rarely a consensus. In addition, advanced statistical and artificial learning approaches used by these methods make it difficult porting these methods outside of the labs that have developed them. To address these challenges and to transform the methodological advances in predicting deleterious noncoding mutations into a practical resource available for the broader functional genomics and population genetics communities, we developed SNPDelScore, which uses a panel of proposed methods for quantifying deleterious effects of noncoding mutations to precompute and compare the deleteriousness scores of all common SNPs in the human genome in 44 cell lines. The panel of deleteriousness scores of a SNP computed using different methods is supplemented by functional information from the GWAS Catalog, libraries of transcription factor-binding sites, and genic characteristics of mutations. SNPDelScore comes with a genome browser capable of displaying and comparing large sets of SNPs in a genomic locus and rapidly identifying consensus SNPs with the highest deleteriousness scores making those prime candidates for phenotype-causal polymorphisms. [ABSTRACT FROM AUTHOR]

Lineage-specific regulatory elements underlie adaptation of species and play a role in disease susceptibility. We compared functionally conserved and lineage-specific enhancers by cross-mapping 5042 human and 6564 mouse heart enhancers. Of these, 79 per cent are lineage-specific, lacking a functional orthologue. Heart enhancers tend to cluster and, commonly, there are multiple heart enhancers in a heart locus providing a regulatory stability to the locus. We observed little cross-clustering, however, between lineage-specific and functionally conserved heart enhancers suggesting regulatory function acquisition and development in loci previously lacking heart activity. We also identified 862 human-specific heart enhancers: 417 featuring sequence conservation with mouse (class II) and 445 with neither sequence nor function conservation (class III). Ninety-eight per cent of class III enhancers were deleted from the mouse genome, and we estimated a similar-sized enhancer gain in the human lineage. Human-specific enhancers display no detectable decrease in the negative selection pressure and are strongly associated with genes partaking in the heart regulatory programmes. The loss of a heart enhancer could be compensated by activity of a redundant heart enhancer; however, we observed redundancy in only 15 per cent of class II and III enhancer loci indicating a large-scale reprogramming of the heart regulatory programme in mammals. [ABSTRACT FROM AUTHOR]

The article presents a study which explores about De novo human brain enhancers created by single-nucleotide mutations. It mentions that results of the study 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.

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Speciation is associated with substantial rewiring of the regulatory circuitry underlying the expression of genes. Determining which changes are relevant and underlie the emergence of the human brain or its unique susceptibility to neural disease has been challenging. Here we annotate changes to gene regulatory elements (GREs) at cell type resolution in the brains of multiple primate species spanning most of primate evolution. We identify a unique set of regulatory elements that emerged in hominins prior to the separation of humans and chimpanzees. We demonstrate that these hominin gains perferentially affect oligodendrocyte function postnatally and are preferentially affected in the brains of autism patients. This preference is also observed for human-specific GREs suggesting this system is under continued selective pressure. Our data provide a roadmap of regulatory rewiring across primate evolution providing insight into the genomic changes that underlie the emergence of the brain and its susceptibility to neural disease. The understanding of the changes regulating gene expression relevant for the emergence of the human brain and its susceptibility to disease is limited. Here, the authors identified a set of regulatory elements that evolved in hominins affecting oligodendrocyte function, and link these to autism. [ABSTRACT FROM AUTHOR]

Despite continual progress in the cataloging of vertebrate regulatory elements, little is known about their organization and regulatory architecture. Here we describe a massively parallel experiment to systematically test the impact of copy number, spacing, combination and order of transcription factor binding sites on gene expression. A complex library of ∼5,000 synthetic regulatory elements containing patterns from 12 liver-specific transcription factor binding sites was assayed in mice and in HepG2 cells. We find that certain transcription factors act as direct drivers of gene expression in homotypic clusters of binding sites, independent of spacing between sites, whereas others function only synergistically. Heterotypic enhancers are stronger than their homotypic analogs and favor specific transcription factor binding site combinations, mimicking putative native enhancers. Exhaustive testing of binding site permutations suggests that there is flexibility in binding site order. Our findings provide quantitative support for a flexible model of regulatory element activity and suggest a framework for the design of synthetic tissue-specific enhancers. [ABSTRACT FROM AUTHOR]

Identifying gene regulatory elements and their target genes in vertebrates remains a significant challenge. It is now recognized that transcriptional regulatory sequences are critical in orchestrating dynamic controls of tissue-specific gene expression during vertebrate development and in adult tissues, and that these elements can be positioned at great distances in relation to the promoters of the genes they control. While significant progress has been made in mapping DNA binding regions by combining chromatin immunoprecipitation and next generation sequencing, functional validation remains a limiting step in improving our ability to correlate in silico predictions with biological function. We recently developed a computational method that synergistically combines genome-wide gene-expression profiling, vertebrate genome comparisons, and transcription factor binding-site analysis to predict tissue-specific enhancers in the human genome. We applied this method to 270 genes highly expressed in skeletal muscle and predicted 190 putative cis-regulatory modules. Furthermore, we optimized Tol2 transgenic constructs in Xenopus laevis to interrogate 20 of these elements for their ability to function as skeletal muscle-specific transcriptional enhancers during embryonic development. We found 45% of these elements expressed only in the fast muscle fibers that are oriented in highly organized chevrons in the Xenopus laevis tadpole. Transcription factor binding site analysis identified >2 Mef2/MyoD sites within ∼200 bp regions in 6 of the validated enhancers, and systematic mutagenesis of these sites revealed that they are critical for the enhancer function. The data described herein introduces a new reporter system suitable for interrogating tissue-specific cis-regulatory elements which allows monitoring of enhancer activity in real time, throughout early stages of embryonic development, in Xenopus. [ABSTRACT FROM AUTHOR]

Illuminating the primary sequence encryption of enhancers is central to understanding the regulatory architecture of genomes. We have developed a machine learning approach to decipher motif patterns of hindbrain enhancers and identify 40,000 sequences in the human genome that we predict display regulatory control that includes the hindbrain. Consistent with their roles in hindbrain patterning, MEIS1, NKX6-1, as well as HOX and POU family binding motifs contributed strongly to this enhancer model. Predicted hindbrain enhancers are overrepresented at genes expressed in hindbrain and associated with nervous system development, and primarily reside in the areas of open chromatin. In addition, 77 (0.2%) of these predictions are identified as hindbrain enhancers on the VISTA Enhancer Browser, and 26,000 (60%) overlap enhancer marks (H3K4me1 or H3K27ac). To validate these putative hindbrain enhancers, we selected 55 elements distributed throughout our predictions and six low scoring controls for evaluation in a zebrafish transgenic assay. When assayed in mosaic transgenic embryos, 51/55 elements directed expression in the central nervous system. Furthermore, 30/34 (88%) predicted enhancers analyzed in stable zebrafish transgenic lines directed expression in the larval zebrafish hindbrain. Subsequent analysis of sequence fragments selected based upon motif clustering further confirmed the critical role of the motifs contributing to the classifier. Our results demonstrate the existence of a primary sequence code characteristic to hindbrain enhancers. This code can be accurately extracted using machine-learning approaches and applied successfully for de novo identification of hindbrain enhancers. This study represents a critical step toward the dissection of regulatory control in specific neuronal subtypes. [ABSTRACT FROM AUTHOR]

Nonhuman primates represent the most relevant model organisms to understand the biology of Homo sapiens. The recent divergence and associated overall sequence conservation between individual members of this taxon have nonetheless largely precluded the use of primates in comparative sequence studies. We used sequence comparisons of an extensive set of Old World and New World monkeys and hominoids to identify functional regions in the human genome. Analysis of these data enabled the discovery of primate-specific gene regulatory elements and the demarcation of the exons of multiple genes. Much of the information content of the comprehensive primate sequence comparisons could be captured with a small subset of phylogenetically close primates. These results demonstrate the utility of intraprimate sequence comparisons to discover common mammalian as well as primate-specific functional elements in the human genome, which are unattainable through the evaluation of more evolutionarily distant species. [ABSTRACT FROM AUTHOR]

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. • enSERT—a highly efficient CRISPR/Cas9-mediated site-specific transgenic mouse assay • In vivo assessment of all rare variants linked to polydactyly in a human enhancer • In vivo testing showed normal enhancer activity for 30% of presumed pathogenic variants • Systematic mutagenesis of this human enhancer identifies novel pathogenic variants Development of a scalable in vivo mouse enhancer-reporter assay and its use to systematically interrogate the canonical human ZRS enhancer, which drives Sonic hedgehog expression in mammalian limb development, broadly illuminates enhancer variant pathogenicity. [ABSTRACT FROM AUTHOR]