Recurrent somatic mutations in regulatory regions of human cancer genomes

Epigenomic Consequences of Coding and Noncoding Driver Mutations

Chromatin alterations are integral to the pathogenic process of cancer, as demonstrated by recent discoveries of frequent mutations in chromatin-modifier genes and aberrant DNA methylation states in different cancer types. Progress is being made on elucidating how chromatin alterations, and how proteins catalyzing these alterations, mechanistically contribute to tissue-specific tumorigenesis. In parallel, technologies enabling the genome-wide profiling of histone modifications have revealed the existence of noncoding driver genetic alterations in cancer. In this review, we survey the current knowledge of coding and noncoding cancer drivers, and discuss their impact on the chromatin landscape. Translational implications of these findings for novel cancer therapies are also presented.

Gene regulatory effects of disease-associated variation in the NRF2 network

Reactive oxygen species (ROS), which are both a natural byproduct of oxidative metabolism and an undesirable byproduct of many environmental stressors, can damage all classes of cellular macromolecules and promote diseases from cancer to neurodegeneration. The actions of ROS are mitigated by the transcription factor NRF2, which regulates expression of antioxidant genes via its interaction with cis-regulatory antioxidant response elements (AREs). However, despite the seemingly straightforward relationship between the opposing forces of ROS and NRF2, regulatory precision in the NRF2 network is essential. Genetic variants that alter NRF2 stability or alter ARE sequences have been linked to a range of diseases. NRF2 hyperactivating mutations are associated with tumorigenesis. On the subtler end of the spectrum, single nucleotide variants (SNVs) that alter individual ARE sequences have been linked to neurodegenerative disorders including progressive supranuclear palsy and Parkinson’s disease, as well as other diseases. Although the human health implications of NRF2 dysregulation have been recognized for some time, a systems level view of this regulatory network is beginning to highlight key NRF2-targeted AREs consistently associated with disease.

Suppression of Enhancer Overactivation by a RACK7-Histone Demethylase Complex

Regulation of enhancer activity is important for controlling gene expression programs. Here, we report that a biochemical complex containing a potential chromatin reader, RACK7, and the histone lysine 4 tri-methyl (H3K4me3)-specific demethylase KDM5C occupies many active enhancers, including almost all super-enhancers. Loss of RACK7 or KDM5C results in overactivation of enhancers, characterized by the deposition of H3K4me3 and H3K27Ac, together with increased transcription of eRNAs and nearby genes. Furthermore, loss of RACK7 or KDM5C leads to de-repression of S100A oncogenes and various cancer-related phenotypes. Our findings reveal a RACK7/KDM5C-regulated, dynamic interchange between histone H3K4me1 and H3K4me3 at active enhancers, representing an additional layer of regulation of enhancer activity. We propose that RACK7/KDM5C functions as an enhancer "brake" to ensure appropriate enhancer activity, which, when compromised, could contribute to tumorigenesis.

Enhancer deregulation in cancer and other diseases

Mutations in enhancer-associated chromatin-modifying components and genomic alterations in non-coding regions of the genome occur frequently in cancer, and other diseases pointing to the importance of enhancer fidelity to ensure proper tissue homeostasis. In this review, I will use specific examples to discuss how mutations in chromatin-modifying factors might affect enhancer activity of disease-relevant genes. I will then consider direct evidence from single nucleotide polymorphisms, small insertions, or deletions but also larger genomic rearrangements such as duplications, deletions, translocations, and inversions of specific enhancers to demonstrate how they have the ability to impact enhancer activity of disease genes including oncogenes and tumor suppressor genes. Considering that the scientific community only fairly recently has begun to focus its attention on "enhancer malfunction" in disease, I propose that multiple new enhancer-regulated and disease-relevant processes will be uncovered in the near future that will constitute the mechanistic basis for novel therapeutic avenues.

The search for cis-regulatory driver mutations in cancer genomes

With the advent of high-throughput and relatively inexpensive whole-genome sequencing technology, the focus of cancer research has begun to shift toward analyses of somatic mutations in non-coding cis-regulatory elements of the cancer genome. Cis-regulatory elements play an important role in gene regulation, with mutations in these elements potentially resulting in changes to the expression of linked genes. The recent discoveries of recurrent TERT promoter mutations in melanoma, and recurrent mutations that create a super-enhancer regulating TAL1 expression in T-cell acute lymphoblastic leukaemia (T-ALL), have sparked significant interest in the search for other somatic cis-regulatory mutations driving cancer development. In this review, we look more closely at the TERT promoter and TAL1 enhancer alterations and use these examples to ask whether other cis-regulatory mutations may play a role in cancer susceptibility. In doing so, we make observations from the data emerging from recent research in this field, and describe the experimental and analytical approaches which could be adopted in the hope of better uncovering the true functional significance of somatic cis-regulatory mutations in cancer.

Mutational Biases Drive Elevated Rates of Substitution at Regulatory Sites across Cancer Types

Disruption of gene regulation is known to play major roles in carcinogenesis and tumour progression. Here, we comprehensively characterize the mutational profiles of diverse transcription factor binding sites (TFBSs) across 1,574 completely sequenced cancer genomes encompassing 11 tumour types. We assess the relative rates and impact of the mutational burden at the binding sites of 81 transcription factors (TFs), by comparing the abundance and patterns of single base substitutions within putatively functional binding sites to control sites with matched sequence composition. There is a strong (1.43-fold) and significant excess of mutations at functional binding sites across TFs, and the mutations that accumulate in cancers are typically more disruptive than variants tolerated in extant human populations at the same sites. CTCF binding sites suffer an exceptionally high mutational load in cancer (3.31-fold excess) relative to control sites, and we demonstrate for the first time that this effect is seen in essentially all cancer types with sufficient data. The sub-set of CTCF sites involved in higher order chromatin structures has the highest mutational burden, suggesting a widespread breakdown of chromatin organization. However, we find no evidence for selection driving these distinctive patterns of mutation. The mutational load at CTCF-binding sites is substantially determined by replication timing and the mutational signature of the tumor in question, suggesting that selectively neutral processes underlie the unusual mutation patterns. Pervasive hyper-mutation within transcription factor binding sites rewires the regulatory landscape of the cancer genome, but it is dominated by mutational processes rather than selection.

Regulatory regions of the genome are important players in cancer initiation and progression. Here, we study the patterns of mutations accumulating at short DNA segments bound by regulatory proteins (transcription factor binding sites) across many cancer types and in the human population. We find strikingly high rates of mutation at active regulatory sites across different cancers, relative to matched control sequences. This excess of mutations disrupts the binding sites of particular factors, such as CTCF, and is likely to be driven by selectively neutral processes, such as the replication timing of the genomic regions concerned. However, binding sites involved in regulatory chromatin structures suffer particularly high levels of mutation, suggesting the frequent disruption of such structures in cancers.

Evaluating the impact of single nucleotide variants on transcription factor binding

Diseases and phenotypes caused by disrupted transcription factor (TF) binding are being identified, but progress is hampered by our limited capacity to predict such functional alterations. Improving predictions may be dependent on expanding the set of bona fide TF binding alterations. Allele-specific binding (ASB) events, where TFs preferentially bind to one of the two alleles at heterozygous sites, reveal the impact of sequence variations in altered TF binding. Here, we present the largest ASB compilation to our knowledge, 10 765 ASB events retrieved from 45 ENCODE ChIP-Seq data sets. Our analysis showed that ASB events were frequently associated with motif alterations of the ChIP'ed TF and potential partner TFs, allelic difference of DNase I hypersensitivity and allelic difference of histone modifications. For TF dimers bound symmetrically to DNA, ASB data revealed that central positions of the TF binding motifs were disproportionately important for binding. Lastly, the impact of variation on TF binding was predicted by a classification model incorporating all the investigated features of ASB events. Classification models using only DNase I hypersensitivity and sequence data exhibited predictive accuracy approaching the models with substantially more features. Taken together, the combination of ASB data and the classification model represents an important step toward elucidating regulatory variants across the human genome.

The role of enhancers in cancer

Enhancer elements function as the logic gates of the genetic regulatory circuitry. One of their most important functions is the integration of extracellular signals with intracellular cell fate information to generate cell type-specific transcriptional responses. Mutations occurring in cancer often misregulate enhancers that normally control the signal-dependent expression of growth-related genes. This misregulation can result from trans-acting mechanisms, such as activation of the transcription factors or epigenetic regulators that control enhancer activity, or can be caused in cis by direct mutations that alter the activity of the enhancer or its target gene specificity. These processes can generate tumour type-specific super-enhancers and establish a 'locked' gene regulatory state that drives the uncontrolled proliferation of cancer cells. Here, we review the role of enhancers in cancer, and their potential as therapeutic targets.

Telomerase: The Devil Inside

High telomerase activity is detected in nearly all human cancers but most human cells are devoid of telomerase activity. There is well-documented evidence that reactivation of telomerase occurs during cellular transformation. In humans, tumors can rely in reactivation of telomerase or originate in a telomerase positive stem/progenitor cell, or rely in alternative lengthening of telomeres, a telomerase-independent telomere-length maintenance mechanism. In this review, we will focus on the telomerase positive tumors. In this context, the recent findings that telomerase reverse transcriptase (TERT) promoter mutations represent the most common non-coding mutations in human cancer have flared up the long-standing discussion whether cancer originates from telomerase positive stem cells or telomerase reactivation is a final step in cellular transformation. Here, we will discuss the pros and cons of both concepts in the context of telomere length-dependent and telomere length-independent functions of telomerase. Together, these observations may provoke a re-evaluation of telomere and telomerase based therapies, both in telomerase inhibition for cancer therapy and telomerase activation for tissue regeneration and anti-ageing strategies.

Exome-based Variant Detection in Core Promoters

Core promoter controls the initiation of transcription. Core promoter sequence change can disrupt transcriptional regulation, lead to impairment of gene expression and ultimately diseases. Therefore, comprehensive characterization of core promoters is essential to understand normal and abnormal gene expression in biomedical studies. Here we report the development of EVDC (Exome-based Variant Detection in Core promoters) method for genome-scale analysis of core-promoter sequence variation. This method is based on the fact that exome sequences contain the sequences not only from coding exons but also from non-coding region including core promoters generated by random fragmentation in exome sequencing process. Using exome data from three cell types of CD4+ T cells, CD19+ B cells and neutrophils of a single individual, we characterized the features of core promoter-mapped exome sequences, and analysed core-promoter variation in this individual genome. We also compared the core promoters between YRI (Yoruba in Ibadan, Nigeria) and the CEU (Utah residents of European decedent) populations using the exome data generated by the 1000 Genome project, and observed much higher variation in YRI population than in CEU population. Our study demonstrates that the EVDC method provides a simple but powerful means for genome-wile de novo characterization of core promoter sequence variation.

"PEAR-ing" Genomic and Epigenomic Analyses for Cancer Gene Discovery

Somatic structural variants in tumor genomes can deregulate transcription through repositioning of enhancer elements. A new method, PEAR-ChIP, leverages paired-end H3K27ac chromatin immunoprecipitation combined with high-throughput sequencing and current computational methods to identify such events.

The present and future of genome editing in cancer research

The widespread use of high-throughput genome sequencing methods is profoundly changing the way we understand, classify, and treat human cancers. To make sense of the deluge of sequencing data generated in the clinic, more effective and rapid assessments of the functional relevance of newly discovered cancer-associated mutations are urgently needed. In this review, we discuss how genome editing technologies are responding to this major challenge. Largely focusing on CRISPR-based methods, we will highlight their potential to accelerate discovery, discuss their current limitations, and speculate about future applications.

Negative selection maintains transcription factor binding motifs in human cancer

Background

Somatic mutations in cancer cells affect various genomic elements disrupting important cell functions. In particular, mutations in DNA binding sites recognized by transcription factors can alter regulator binding affinities and, consequently, expression of target genes. A number of promoter mutations have been linked with an increased risk of cancer. Cancer somatic mutations in binding sites of selected transcription factors have been found under positive selection. However, action and significance of negative selection in non-coding regions remain controversial.

Results

Here we present analysis of transcription factor binding motifs co-localized with non-coding variants. To avoid statistical bias we account for mutation signatures of different cancer types. For many transcription factors, including multiple members of FOX, HOX, and NR families, we show that human cancers accumulate fewer mutations than expected by chance that increase or decrease affinity of predicted binding sites. Such stability of binding motifs is even more exhibited in DNase accessible regions.

Conclusions

Our data demonstrate negative selection against binding sites alterations and suggest that such selection pressure protects cancer cells from rewiring of regulatory circuits. Further analysis of transcription factors with conserved binding motifs can reveal cell regulatory pathways crucial for the survivability of various human cancers.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2728-9) contains supplementary material, which is available to authorized users.

Predicting regulatory variants with composite statistic

MOTIVATION

Prediction and prioritization of human non-coding regulatory variants is critical for understanding the regulatory mechanisms of disease pathogenesis and promoting personalized medicine. Existing tools utilize functional genomics data and evolutionary information to evaluate the pathogenicity or regulatory functions of non-coding variants. However, different algorithms lead to inconsistent and even conflicting predictions. Combining multiple methods may increase accuracy in regulatory variant prediction.

RESULTS

Here, we compiled an integrative resource for predictions from eight different tools on functional annotation of non-coding variants. We further developed a composite strategy to integrate multiple predictions and computed the composite likelihood of a given variant being regulatory variant. Benchmarked by multiple independent causal variants datasets, we demonstrated that our composite model significantly improves the prediction performance.

AVAILABILITY AND IMPLEMENTATION

We implemented our model and scoring procedure as a tool, named PRVCS, which is freely available to academic and non-profit usage at http://jjwanglab.org/PRVCS CONTACT: wang.junwen@mayo.edu, jliu@stat.harvard.edu, or limx54@gmail.com

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

RNaseH2A is involved in human gliomagenesis through the regulation of cell proliferation and apoptosis

Mutations in the RNaseH2A gene are involved in Aicardi‑Goutieres syndrome, an autosomal recessive neurological dysfunction; however, studies assessing RNaseH2A in relation to glioma are scarce. This study aimed to assess the role of RNaseH2A in glioma and to unveil the underlying mechanisms. RNaseH2A was silenced in glioblastoma cell lines U87 and U251. Gene expression was assessed in the cells transfected with RNaseH2A shRNA or scramble shRNA by microarrays, validated by quantitative real time PCR. Protein expression was evaluated by western blot analysis. Cell proliferation was assessed by the MTT assay; cell cycle distribution and apoptosis were analyzed by flow cytometry. Finally, the effects of RNaseH2A on colony formation and tumorigenicity were assessed in vitro and in a mouse xenograft model, respectively. RNaseH2A was successively knocked down in U87 and U251 cells. Notably, RNaseH2A silencing resulted in impaired cell proliferation, with 70.7 and 57.8% reduction in the U87 and U251 cells, respectively, with the cell cycle being blocked in the G0/G1 phase in vitro. Meanwhile, clone formation was significantly reduced by RNaseH2A knockdown, which also increased cell apoptosis by approximately 4.5-fold. In nude mice, tumor size was significantly decreased after RNaseH2A knockdown: 219.29±246.43 vs. 1160.26±222.61 mm3 for the control group; similar findings were obtained for tumor weight (0.261±0.245 and 1.127±0.232 g) in the shRNA and control groups, respectively). In the microarray data, RNaseH2A was shown to modulate several signaling pathways responsible for cell proliferation and apoptosis, such as IL-6 and FAS pathways. RNaseH2A may be involved in human gliomagenesis, likely by regulating signaling pathways responsible for cell proliferation and apoptosis.

The dark matter of the cancer genome: aberrations in regulatory elements, untranslated regions, splice sites, non-coding RNA and synonymous mutations

Cancer is a disease of the genome caused by oncogene activation and tumor suppressor gene inhibition. Deep sequencing studies including large consortia such as TCGA and ICGC identified numerous tumor‐specific mutations not only in protein‐coding sequences but also in non‐coding sequences. Although 98% of the genome is not translated into proteins, most studies have neglected the information hidden in this “dark matter” of the genome. Malignancy‐driving mutations can occur in all genetic elements outside the coding region, namely in enhancer, silencer, insulator, and promoter as well as in 5′‐UTR and 3′‐UTR. Intron or splice site mutations can alter the splicing pattern. Moreover, cancer genomes contain mutations within non‐coding RNA, such as microRNA, lncRNA, and lincRNA. A synonymous mutation changes the coding region in the DNA and RNA but not the protein sequence. Importantly, oncogenes such as TERT or miR‐21 as well as tumor suppressor genes such as TP53/p53,APC,BRCA1, or RB1 can be affected by these alterations. In summary, coding‐independent mutations can affect gene regulation from transcription, splicing, mRNA stability to translation, and hence, this largely neglected area needs functional studies to elucidate the mechanisms underlying tumorigenesis. This review will focus on the important role and novel mechanisms of these non‐coding or allegedly silent mutations in tumorigenesis.

Differential DNA repair underlies mutation hotspots at active promoters in cancer genomes

Promoters are DNA sequences that have an essential role in controlling gene expression. While recent whole cancer genome analyses have identified numerous hotspots of somatic point mutations within promoters, many have not yet been shown to perturb gene expression or drive cancer development. As such, positive selection alone may not adequately explain the frequency of promoter point mutations in cancer genomes. Here we show that increased mutation density at gene promoters can be linked to promoter activity and differential nucleotide excision repair (NER). By analysing 1,161 human cancer genomes across 14 cancer types, we find evidence for increased local density of somatic point mutations within the centres of DNase I-hypersensitive sites (DHSs) in gene promoters. Mutated DHSs were strongly associated with transcription initiation activity, in which active promoters but not enhancers of equal DNase I hypersensitivity were most mutated relative to their flanking regions. Notably, analysis of genome-wide maps of NER shows that NER is impaired within the DHS centre of active gene promoters, while XPC-deficient skin cancers do not show increased promoter mutation density, pinpointing differential NER as the underlying cause of these mutation hotspots. Consistent with this finding, we observe that melanomas with an ultraviolet-induced DNA damage mutation signature show greatest enrichment of promoter mutations, whereas cancers that are not highly dependent on NER, such as colon cancer, show no sign of such enrichment. Taken together, our analysis has uncovered the presence of a previously unknown mechanism linking transcription initiation and NER as a major contributor of somatic point mutation hotspots at active gene promoters in cancer genomes.

Long Noncoding RNAs in Cancer Pathways

Genome-wide cancer mutation analyses are revealing an extensive landscape of functional mutations within the noncoding genome, with profound effects on the expression of long noncoding RNAs (lncRNAs). While the exquisite regulation of lncRNA transcription can provide signals of malignant transformation, we now understand that lncRNAs drive many important cancer phenotypes through their interactions with other cellular macromolecules including DNA, protein, and RNA. Recent advancements in surveying lncRNA molecular mechanisms are now providing the tools to functionally annotate these cancer-associated transcripts, making these molecules attractive targets for therapeutic intervention in the fight against cancer.

Gene regulatory mechanisms underpinning prostate cancer susceptibility

Molecular characterization of genome-wide association study (GWAS) loci can uncover key genes and biological mechanisms underpinning complex traits and diseases. Here we present deep, high-throughput characterization of gene regulatory mechanisms underlying prostate cancer risk loci. Our methodology integrates data from 295 prostate cancer chromatin immunoprecipitation and sequencing experiments with genotype and gene expression data from 602 prostate tumor samples. The analysis identifies new gene regulatory mechanisms affected by risk locus SNPs, including widespread disruption of ternary androgen receptor (AR)-FOXA1 and AR-HOXB13 complexes and competitive binding mechanisms. We identify 57 expression quantitative trait loci at 35 risk loci, which we validate through analysis of allele-specific expression. We further validate predicted regulatory SNPs and target genes in prostate cancer cell line models. Finally, our integrated analysis can be accessed through an interactive visualization tool. This analysis elucidates how genome sequence variation affects disease predisposition via gene regulatory mechanisms and identifies relevant genes for downstream biomarker and drug development.

Quantitative Trait Loci Identify Functional Noncoding Variation in Cancer

The interpretation of noncoding alterations in cancer genomes presents an unresolved problem in cancer studies. While the impact of somatic variations in protein-coding regions is widely accepted, noncoding aberrations are mostly considered as passenger events. However, with the advance of genome-wide profiling strategies, alterations outside the coding context entered the focus, and multiple examples highlight the role of gene deregulation as cancer-driving events. This review describes the implication of noncoding alterations in oncogenesis and provides a theoretical framework for the identification of causal somatic variants using quantitative trait loci (QTL) analysis. Assuming that functional noncoding alterations affect quantifiable regulatory processes, somatic QTL studies constitute a valuable strategy to pinpoint cancer gene deregulation. Eventually, the comprehensive identification and interpretation of coding and noncoding alterations will guide our future understanding of cancer biology.

Mutation allele burden remains unchanged in chronic myelomonocytic leukaemia responding to hypomethylating agents

The cytidine analogues azacytidine and 5-aza-2'-deoxycytidine (decitabine) are commonly used to treat myelodysplastic syndromes, with or without a myeloproliferative component. It remains unclear whether the response to these hypomethylating agents results from a cytotoxic or an epigenetic effect. In this study, we address this question in chronic myelomonocytic leukaemia. We describe a comprehensive analysis of the mutational landscape of these tumours, combining whole-exome and whole-genome sequencing. We identify an average of 14±5 somatic mutations in coding sequences of sorted monocyte DNA and the signatures of three mutational processes. Serial sequencing demonstrates that the response to hypomethylating agents is associated with changes in DNA methylation and gene expression, without any decrease in the mutation allele burden, nor prevention of new genetic alteration occurence. Our findings indicate that cytosine analogues restore a balanced haematopoiesis without decreasing the size of the mutated clone, arguing for a predominantly epigenetic effect.

Role of non-coding sequence variants in cancer

Patients with cancer carry somatic sequence variants in their tumour in addition to the germline variants in their inherited genome. Although variants in protein-coding regions have received the most attention, numerous studies have noted the importance of non-coding variants in cancer. Moreover, the overwhelming majority of variants, both somatic and germline, occur in non-coding portions of the genome. We review the current understanding of non-coding variants in cancer, including the great diversity of the mutation types--from single nucleotide variants to large genomic rearrangements--and the wide range of mechanisms by which they affect gene expression to promote tumorigenesis, such as disrupting transcription factor-binding sites or functions of non-coding RNAs. We highlight specific case studies of somatic and germline variants, and discuss how non-coding variants can be interpreted on a large-scale through computational and experimental methods.

HOCOMOCO: expansion and enhancement of the collection of transcription factor binding sites models

Models of transcription factor (TF) binding sites provide a basis for a wide spectrum of studies in regulatory genomics, from reconstruction of regulatory networks to functional annotation of transcripts and sequence variants. While TFs may recognize different sequence patterns in different conditions, it is pragmatic to have a single generic model for each particular TF as a baseline for practical applications. Here we present the expanded and enhanced version of HOCOMOCO (http://hocomoco.autosome.ru and http://www.cbrc.kaust.edu.sa/hocomoco10), the collection of models of DNA patterns, recognized by transcription factors. HOCOMOCO now provides position weight matrix (PWM) models for binding sites of 601 human TFs and, in addition, PWMs for 396 mouse TFs. Furthermore, we introduce the largest up to date collection of dinucleotide PWM models for 86 (52) human (mouse) TFs. The update is based on the analysis of massive ChIP-Seq and HT-SELEX datasets, with the validation of the resulting models on in vivo data. To facilitate a practical application, all HOCOMOCO models are linked to gene and protein databases (Entrez Gene, HGNC, UniProt) and accompanied by precomputed score thresholds. Finally, we provide command-line tools for PWM and diPWM threshold estimation and motif finding in nucleotide sequences.

Identification of significantly mutated regions across cancer types highlights a rich landscape of functional molecular alterations

Cancer sequencing studies have primarily identified cancer-driver genes by the accumulation of protein-altering mutations. An improved method would be annotation-independent, sensitive to unknown distributions of functions within proteins, and inclusive of non-coding drivers. We employed density-based clustering methods in 21 tumor types to detect variably-sized significantly mutated regions (SMRs). SMRs reveal recurrent alterations across a spectrum of coding and non-coding elements, including transcription factor binding sites and untranslated regions mutated in up to ∼15% of specific tumor types. SMRs reveal spatial clustering of mutations at molecular domains and interfaces, often with associated changes in signaling. Mutation frequencies in SMRs demonstrate that distinct protein regions are differentially mutated among tumor types, as exemplified by a linker region of PIK3CA in which biophysical simulations suggest mutations affect regulatory interactions. The functional diversity of SMRs underscores both the varied mechanisms of oncogenic misregulation and the advantage of functionally-agnostic driver identification.

Brachyury, Foxa2 and the cis-Regulatory Origins of the Notochord

A main challenge of modern biology is to understand how specific constellations of genes are activated to differentiate cells and give rise to distinct tissues. This study focuses on elucidating how gene expression is initiated in the notochord, an axial structure that provides support and patterning signals to embryos of humans and all other chordates. Although numerous notochord genes have been identified, the regulatory DNAs that orchestrate development and propel evolution of this structure by eliciting notochord gene expression remain mostly uncharted, and the information on their configuration and recurrence is still quite fragmentary. Here we used the simple chordate Ciona for a systematic analysis of notochord cis-regulatory modules (CRMs), and investigated their composition, architectural constraints, predictive ability and evolutionary conservation. We found that most Ciona notochord CRMs relied upon variable combinations of binding sites for the transcription factors Brachyury and/or Foxa2, which can act either synergistically or independently from one another. Notably, one of these CRMs contains a Brachyury binding site juxtaposed to an (AC) microsatellite, an unusual arrangement also found in Brachyury-bound regulatory regions in mouse. In contrast, different subsets of CRMs relied upon binding sites for transcription factors of widely diverse families. Surprisingly, we found that neither intra-genomic nor interspecific conservation of binding sites were reliably predictive hallmarks of notochord CRMs. We propose that rather than obeying a rigid sequence-based cis-regulatory code, most notochord CRMs are rather unique. Yet, this study uncovered essential elements recurrently used by divergent chordates as basic building blocks for notochord CRMs.

TERT promoter mutations and monoallelic activation of TERT in cancer

Here we report that promoter mutations in telomerase (TERT), the most common noncoding mutations in cancer, give rise to monoallelic expression of TERT. Through deep RNA sequencing, we find that TERT activation in human cancer cell lines can occur in either mono- or biallelic manner. Without exception, hotspot TERT promoter mutations lead to the re-expression of only one allele, accounting for approximately half of the observed cases of monoallelic TERT expression. Furthermore, we show that monoallelic TERT expression is highly prevalent in certain tumor types and widespread across a broad spectrum of cancers. Taken together, these observations provide insights into the mechanisms of TERT activation and the ramifications of noncoding mutations in cancer.

A model for gene deregulation detection using expression data

In tumoral cells, gene regulation mechanisms are severely altered. Genes that do not react normally to their regulators' activity can provide explanations for the tumoral behavior, and be characteristic of cancer subtypes. We thus propose a statistical methodology to identify the misregulated genes given a reference network and gene expression data.

Our model is based on a regulatory process in which all genes are allowed to be deregulated. We derive an EM algorithm where the hidden variables correspond to the status (under/over/normally expressed) of the genes and where the E-step is solved thanks to a message passing algorithm. Our procedure provides posterior probabilities of deregulation in a given sample for each gene. We assess the performance of our method by numerical experiments on simulations and on a bladder cancer data set.

Mutations in the noncoding genome

PURPOSE OF REVIEW

Clinical diagnostic sequencing currently focuses on identifying causal mutations in the exome, wherein most disease-causing mutations are known to occur. The rest of the genome is mostly comprised of regulatory elements that control gene expression, but these have remained largely unexplored in clinical diagnostics due to the high cost of whole genome sequencing and interpretive challenges. The purpose of this review is to illustrate examples of diseases caused by mutations in regulatory elements and introduce the diagnostic potential for whole genome sequencing. Different classes of functional elements and chromatin structure are described to provide the clinician with a foundation for understanding the basis of these mutations.

RECENT FINDINGS

The utilization of whole-genome sequence data, epigenomic maps and induced pluripotent stem (IPS) cell technologies facilitated the discovery that mutations in the pancreas-specific transcription factor 1a enhancer can cause isolated pancreatic agenesis. High resolution array comparative genomic hybridisation (CGH), whole-genome sequencing, maps of 3-D chromatin architecture, and mouse models generated using clustered regularly interspaced short palindromic repeats (CRISPR)/Cas were used to show that disruption of topological-associated domain boundary elements cause limb defects. Structural variants that reposition enhancers in somatic cells have also been described in cancer.

SUMMARY

Although not ready for diagnostics, new technologies, epigenomic maps, and improved knowledge of chromatin architecture will soon enable a better understanding and diagnostic solutions for currently unexplained genetic disorders.

Beyond the exome: the role of non-coding somatic mutations in cancer

The comprehensive identification of mutations contributing to the development of cancer is a priority of large cancer sequencing projects. To date, most studies have scrutinized mutations in coding regions of the genome, but several recent discoveries, including the identification of recurrent somatic mutations in the TERT promoter in multiple cancer types, support the idea that mutations in non-coding regions are also important in tumour development. Furthermore, analysis of whole-genome sequencing data from tumours has elucidated novel mutational patterns and processes etched into cancer genomes. Here, we present an overview of insights gleaned from the analysis of mutations from sequenced cancer genomes. We then review the mechanisms by which non-coding mutations can play a role in cancer. Finally, we discuss recent efforts aimed at identifying non-coding driver mutations, as well as the unique challenges that the analysis of non-coding mutations present in contrast to the identification of driver mutations in coding regions.

ORegAnno 3.0: a community-driven resource for curated regulatory annotation

The Open Regulatory Annotation database (ORegAnno) is a resource for curated regulatory annotation. It contains information about regulatory regions, transcription factor binding sites, RNA binding sites, regulatory variants, haplotypes, and other regulatory elements. ORegAnno differentiates itself from other regulatory resources by facilitating crowd-sourced interpretation and annotation of regulatory observations from the literature and highly curated resources. It contains a comprehensive annotation scheme that aims to describe both the elements and outcomes of regulatory events. Moreover, ORegAnno assembles these disparate data sources and annotations into a single, high quality catalogue of curated regulatory information. The current release is an update of the database previously featured in the NAR Database Issue, and now contains 1 948 307 records, across 18 species, with a combined coverage of 334 215 080 bp. Complete records, annotation, and other associated data are available for browsing and download at http://www.oreganno.org/.

Mechanisms of mutational robustness in transcriptional regulation

Robustness is the invariance of a phenotype in the face of environmental or genetic change. The phenotypes produced by transcriptional regulatory circuits are gene expression patterns that are to some extent robust to mutations. Here we review several causes of this robustness. They include robustness of individual transcription factor binding sites, homotypic clusters of such sites, redundant enhancers, transcription factors, redundant transcription factors, and the wiring of transcriptional regulatory circuits. Such robustness can either be an adaptation by itself, a byproduct of other adaptations, or the result of biophysical principles and non-adaptive forces of genome evolution. The potential consequences of such robustness include complex regulatory network topologies that arise through neutral evolution, as well as cryptic variation, i.e., genotypic divergence without phenotypic divergence. On the longest evolutionary timescales, the robustness of transcriptional regulation has helped shape life as we know it, by facilitating evolutionary innovations that helped organisms such as flowering plants and vertebrates diversify.

Demystifying the secret mission of enhancers: linking distal regulatory elements to target genes

Enhancers are short regulatory sequences bound by sequence-specific transcription factors and play a major role in the spatiotemporal specificity of gene expression patterns in development and disease. While it is now possible to identify enhancer regions genomewide in both cultured cells and primary tissues using epigenomic approaches, it has been more challenging to develop methods to understand the function of individual enhancers because enhancers are located far from the gene(s) that they regulate. However, it is essential to identify target genes of enhancers not only so that we can understand the role of enhancers in disease but also because this information will assist in the development of future therapeutic options. After reviewing models of enhancer function, we discuss recent methods for identifying target genes of enhancers. First, we describe chromatin structure-based approaches for directly mapping interactions between enhancers and promoters. Second, we describe the use of correlation-based approaches to link enhancer state with the activity of nearby promoters and/or gene expression. Third, we describe how to test the function of specific enhancers experimentally by perturbing enhancer–target relationships using high-throughput reporter assays and genome editing. Finally, we conclude by discussing as yet unanswered questions concerning how enhancers function, how target genes can be identified, and how to distinguish direct from indirect changes in gene expression mediated by individual enhancers.