The effects of chromatin organization on variation in mutation rates in the genome

Mechanistic analysis of enhancer sequences in the estrogen receptor transcriptional program

Estrogen Receptor α (ERα) is a major lineage determining transcription factor (TF) in mammary gland development. Dysregulation of ERα-mediated transcriptional program results in cancer. Transcriptomic and epigenomic profiling of breast cancer cell lines has revealed large numbers of enhancers involved in this regulatory program, but how these enhancers encode function in their sequence remains poorly understood. A subset of ERα-bound enhancers are transcribed into short bidirectional RNA (enhancer RNA or eRNA), and this property is believed to be a reliable marker of active enhancers. We therefore analyze thousands of ERα-bound enhancers and build quantitative, mechanism-aware models to discriminate eRNAs from non-transcribing enhancers based on their sequence. Our thermodynamics-based models provide insights into the roles of specific TFs in ERα-mediated transcriptional program, many of which are supported by the literature. We use in silico perturbations to predict TF-enhancer regulatory relationships and integrate these findings with experimentally determined enhancer-promoter interactions to construct a gene regulatory network. We also demonstrate that the model can prioritize breast cancer-related sequence variants while providing mechanistic explanations for their function. Finally, we experimentally validate the model-proposed mechanisms underlying three such variants.

H3K4me1 recruits DNA repair proteins in plants

DNA repair proteins can be recruited by their histone reader domains to specific epigenomic features, with consequences on intragenomic mutation rate variation. Here, we investigated H3K4me1-associated hypomutation in plants. We first examined 2 proteins which, in plants, contain Tudor histone reader domains: PRECOCIOUS DISSOCIATION OF SISTERS 5 (PDS5C), involved in homology-directed repair, and MUTS HOMOLOG 6 (MSH6), a mismatch repair protein. The MSH6 Tudor domain of Arabidopsis (Arabidopsis thaliana) binds to H3K4me1 as previously demonstrated for PDS5C, which localizes to H3K4me1-rich gene bodies and essential genes. Mutations revealed by ultradeep sequencing of wild-type and msh6 knockout lines in Arabidopsis show that functional MSH6 is critical for the reduced rate of single-base substitution (SBS) mutations in gene bodies and H3K4me1-rich regions. We explored the breadth of these mechanisms among plants by examining a large rice (Oryza sativa) mutation data set. H3K4me1-associated hypomutation is conserved in rice as are the H3K4me1-binding residues of MSH6 and PDS5C Tudor domains. Recruitment of DNA repair proteins by H3K4me1 in plants reveals convergent, but distinct, epigenome-recruited DNA repair mechanisms from those well described in humans. The emergent model of H3K4me1-recruited repair in plants is consistent with evolutionary theory regarding mutation modifier systems and offers mechanistic insight into intragenomic mutation rate variation in plants.

Extrinsic and intrinsic drivers of natural killer cell clonality

Clonal expansion of antigen-specific lymphocytes is the fundamental mechanism enabling potent adaptive immune responses and the generation of immune memory. Accompanied by pronounced epigenetic remodeling, the massive proliferation of individual cells generates a critical mass of effectors for the control of acute infections, as well as a pool of memory cells protecting against future pathogen encounters. Classically associated with the adaptive immune system, recent work has demonstrated that innate immune memory to human cytomegalovirus (CMV) infection is stably maintained as large clonal expansions of natural killer (NK) cells, raising questions on the mechanisms for clonal selection and expansion in the absence of re-arranged antigen receptors. Here, we discuss clonal NK cell memory in the context of the mechanisms underlying clonal competition of adaptive lymphocytes and propose alternative selection mechanisms that might decide on the clonal success of their innate counterparts. We propose that the integration of external cues with cell-intrinsic sources of heterogeneity, such as variegated receptor expression, transcriptional states, and somatic variants, compose a bottleneck for clonal selection, contributing to the large size of memory NK cell clones.

Cell cycle gene alterations associate with a redistribution of mutation risk across chromosomal domains in human cancers

Mutations in human cells exhibit increased burden in heterochromatic, late DNA replication time (RT) chromosomal domains, with variation in mutation rates between tissues mirroring variation in heterochromatin and RT. We observed that regional mutation risk further varies between individual tumors in a manner independent of cell type, identifying three signatures of domain-scale mutagenesis in >4,000 tumor genomes. The major signature reflects remodeling of heterochromatin and of the RT program domains seen across tumors, tissues and cultured cells, and is robustly linked with higher expression of cell proliferation genes. Regional mutagenesis is associated with loss of activity of the tumor-suppressor genes RB1 and TP53, consistent with their roles in cell cycle control, with distinct mutational patterns generated by the two genes. Loss of regional heterogeneity in mutagenesis is associated with deficiencies in various DNA repair pathways. These mutation risk redistribution processes modify the mutation supply towards important genes, diverting the course of somatic evolution.

Tissue-Predisposition to Cancer Driver Mutations

Driver mutations are considered the cornerstone of cancer initiation. They are defined as mutations that convey a competitive fitness advantage, and hence, their mutation frequency in premalignant tissue is expected to exceed the basal mutation rate. In old terms, that translates to "the survival of the fittest" and implies that a selective process underlies the frequency of cancer driver mutations. In that sense, each tissue is its own niche that creates a molecular selective pressure that may favor the propagation of a mutation or not. At the heart of this stands one of the biggest riddles in cancer biology: the tissue-predisposition to cancer driver mutations. The frequency of cancer driver mutations among tissues is non-uniform: for instance, mutations in APC are particularly frequent in colorectal cancer, and 99% of chronic myeloid leukemia patients harbor the driver BCR-ABL1 fusion mutation, which is rarely found in solid tumors. Here, we provide a mechanistic framework that aims to explain how tissue-specific features, ranging from epigenetic underpinnings to the expression of viral transposable elements, establish a molecular basis for selecting cancer driver mutations in a tissue-specific manner.

Epigenomic divergence correlates with sequence polymorphism in Arabidopsis paralogs

Processes affecting rates of sequence polymorphism are fundamental to the evolution of gene duplicates. The relationship between gene activity and sequence polymorphism can influence the likelihood that functionally redundant gene copies are co-maintained in stable evolutionary equilibria vs other outcomes such as neofunctionalization. Here, we investigate genic variation in epigenome-associated polymorphism rates in Arabidopsis thaliana and consider whether these affect the evolution of gene duplicates. We compared the frequency of sequence polymorphism and patterns of genetic differentiation between genes classified by exon methylation patterns: unmethylated (unM), gene-body methylated (gbM), and transposon-like methylated (teM) states, which reflect divergence in gene expression. We found that the frequency of polymorphism was higher in teM (transcriptionally repressed, tissue-specific) genes and lower in gbM (active, constitutively expressed) genes. Comparisons of gene duplicates were largely consistent with genome-wide patterns - gene copies that exhibit teM accumulate more variation, evolve faster, and are in chromatin states associated with reduced DNA repair. This relationship between expression, the epigenome, and polymorphism may lead to the breakdown of equilibrium states that would otherwise maintain genetic redundancies. Epigenome-mediated polymorphism rate variation may facilitate the evolution of novel gene functions in duplicate paralogs maintained over evolutionary time.

Identifying predictors of glioma evolution from longitudinal sequencing

Clonal evolution drives cancer progression and therapeutic resistance. Recent studies have revealed divergent longitudinal trajectories in gliomas, but early molecular features steering posttreatment cancer evolution remain unclear. Here, we collected sequencing and clinical data of initial-recurrent tumor pairs from 544 adult diffuse gliomas and performed multivariate analysis to identify early molecular predictors of tumor evolution in three diffuse glioma subtypes. We found that CDKN2A deletion at initial diagnosis preceded tumor necrosis and microvascular proliferation that occur at later stages of IDH-mutant glioma. Ki67 expression at diagnosis was positively correlated with acquiring hypermutation at recurrence in the IDH-wild-type glioma. In all glioma subtypes, MYC gain or MYC-target activation at diagnosis was associated with treatment-induced hypermutation at recurrence. To predict glioma evolution, we constructed CELLO2 (Cancer EvoLution for LOngitudinal data version 2), a machine learning model integrating features at diagnosis to forecast hypermutation and progression after treatment. CELLO2 successfully stratified patients into subgroups with distinct prognoses and identified a high-risk patient group featured by MYC gain with worse post-progression survival, from the low-grade IDH-mutant-noncodel subtype. We then performed chronic temozolomide-induction experiments in glioma cell lines and isogenic patient-derived gliomaspheres and demonstrated that MYC drives temozolomide resistance by promoting hypermutation. Mechanistically, we demonstrated that, by binding to open chromatin and transcriptionally active genomic regions, c-MYC increases the vulnerability of key mismatch repair genes to treatment-induced mutagenesis, thus triggering hypermutation. This study reveals early predictors of cancer evolution under therapy and provides a resource for precision oncology targeting cancer dynamics in diffuse gliomas.

Predicting regional somatic mutation rates using DNA motifs

How the locus-specificity of epigenetic modifications is regulated remains an unanswered question. A contributing mechanism is that epigenetic enzymes are recruited to specific loci by DNA binding factors recognizing particular sequence motifs (referred to as epi-motifs). Using these motifs to predict biological outputs depending on local epigenetic state such as somatic mutation rates would confirm their functionality. Here, we used DNA motifs including known TF motifs and epi-motifs as a surrogate of epigenetic signals to predict somatic mutation rates in 13 cancers at an average 23kbp resolution. We implemented an interpretable neural network model, called contextual regression, to successfully learn the universal relationship between mutations and DNA motifs, and uncovered motifs that are most impactful on the regional mutation rates such as TP53 and epi-motifs associated with H3K9me3. Furthermore, we identified genomic regions with significantly higher mutation rates than the expected values in each individual tumor and demonstrated that such cancer-related regions can accurately predict cancer types. Interestingly, we found that the same mutation signatures often have different contributions to cancer-related and cancer-independent regions, and we also identified the motifs with the most contribution to each mutation signature.

Underlying causes for prevalent false positives and false negatives in STARR-seq data

Self-transcribing active regulatory region sequencing (STARR-seq) and its variants have been widely used to characterize enhancers. However, it has been reported that up to 87% of STARR-seq peaks are located in repressive chromatin and are not functional in the tested cells. While some of the STARR-seq peaks in repressive chromatin might be active in other cell/tissue types, some others might be false positives. Meanwhile, many active enhancers may not be identified by the current STARR-seq methods. Although methods have been proposed to mitigate systematic errors caused by the use of plasmid vectors, the artifacts due to the intrinsic limitations of current STARR-seq methods are still prevalent and the underlying causes are not fully understood. Based on predicted cis-regulatory modules (CRMs) and non-CRMs in the human genome as well as predicted active CRMs and non-active CRMs in a few human cell lines/tissues with STARR-seq data available, we reveal prevalent false positives and false negatives in STARR-seq peaks generated by major variants of STARR-seq methods and possible underlying causes. Our results will help design strategies to improve STARR-seq methods and interpret the results.

Duplex sequencing provides detailed characterization of mutation frequencies and spectra in the bone marrow of MutaMouse males exposed to procarbazine hydrochloride

Mutagenicity testing is an essential component of health safety assessment. Duplex Sequencing (DS), an emerging high-accuracy DNA sequencing technology, may provide substantial advantages over conventional mutagenicity assays. DS could be used to eliminate reliance on standalone reporter assays and provide mechanistic information alongside mutation frequency (MF) data. However, the performance of DS must be thoroughly assessed before it can be routinely implemented for standard testing. We used DS to study spontaneous and procarbazine (PRC)-induced mutations in the bone marrow (BM) of MutaMouse males across a panel of 20 diverse genomic targets. Mice were exposed to 0, 6.25, 12.5, or 25 mg/kg-bw/day for 28 days by oral gavage and BM sampled 42 days post-exposure. Results were compared with those obtained using the conventional lacZ viral plaque assay on the same samples. DS detected significant increases in mutation frequencies and changes to mutation spectra at all PRC doses. Low intra-group variability within DS samples allowed for detection of increases at lower doses than the lacZ assay. While the lacZ assay initially yielded a higher fold-change in mutant frequency than DS, inclusion of clonal mutations in DS mutation frequencies reduced this discrepancy. Power analyses suggested that three animals per dose group and 500 million duplex base pairs per sample is sufficient to detect a 1.5-fold increase in mutations with > 80% power. Overall, we demonstrate several advantages of DS over classical mutagenicity assays and provide data to support efforts to identify optimal study designs for the application of DS as a regulatory test.

Cell-type specificity of the human mutation landscape with respect to DNA replication dynamics

The patterns of genomic mutations are associated with various genomic features, most notably late replication timing, yet it remains contested which mutation types and signatures relate to DNA replication dynamics and to what extent. Here, we perform high-resolution comparisons of mutational landscapes between lymphoblastoid cell lines, chronic lymphocytic leukemia tumors, and three colon adenocarcinoma cell lines, including two with mismatch repair deficiency. Using cell-type-matched replication timing profiles, we demonstrate that mutation rates exhibit heterogeneous replication timing associations among cell types. This cell-type heterogeneity extends to the underlying mutational pathways, as mutational signatures show inconsistent replication timing bias between cell types. Moreover, replicative strand asymmetries exhibit similar cell-type specificity, albeit with different relationships to replication timing than mutation rates. Overall, we reveal an underappreciated complexity and cell-type specificity of mutational pathways and their relationship to replication timing.

On the Role of Glycolysis in Early Tumorigenesis-Permissive and Executioner Effects

Reprogramming energy production from mitochondrial respiration to glycolysis is now considered a hallmark of cancer. When tumors grow beyond a certain size they give rise to changes in their microenvironment (e.g., hypoxia, mechanical stress) that are conducive to the upregulation of glycolysis. Over the years, however, it has become clear that glycolysis can also associate with the earliest steps of tumorigenesis. Thus, many of the oncoproteins most commonly involved in tumor initiation and progression upregulate glycolysis. Moreover, in recent years, considerable evidence has been reported suggesting that upregulated glycolysis itself, through its enzymes and/or metabolites, may play a causative role in tumorigenesis, either by acting itself as an oncogenic stimulus or by facilitating the appearance of oncogenic mutations. In fact, several changes induced by upregulated glycolysis have been shown to be involved in tumor initiation and early tumorigenesis: glycolysis-induced chromatin remodeling, inhibition of premature senescence and induction of proliferation, effects on DNA repair, O-linked N-acetylglucosamine modification of target proteins, antiapoptotic effects, induction of epithelial-mesenchymal transition or autophagy, and induction of angiogenesis. In this article we summarize the evidence that upregulated glycolysis is involved in tumor initiation and, in the following, we propose a mechanistic model aimed at explaining how upregulated glycolysis may play such a role.

Transgenerational Epigenetic Inheritance of Traumatic Experience in Mammals

In recent years, we have seen an increasing amount of evidence pointing to the existence of a non-genetic heredity of the effects of events such as separation from parents, threat to life, or other traumatising experiences such as famine. This heredity is often mediated by epigenetic regulations of gene expression and may be transferred even across several generations. In this review, we focus on studies which involve transgenerational epigenetic inheritance (TEI), with a short detour to intergenerational studies focused on the inheritance of trauma or stressful experiences. The reviewed studies show a plethora of universal changes which stress exposure initiates on multiple levels of organisation ranging from hormonal production and the hypothalamic-pituitary-adrenal (HPA) axis modulation all the way to cognition, behaviour, or propensity to certain psychiatric or metabolic disorders. This review will also provide an overview of relevant methodology and difficulties linked to implementation of epigenetic studies. A better understanding of these processes may help us elucidate the evolutionary pathways which are at work in the course of emergence of the diseases and disorders associated with exposure to trauma, either direct or in a previous generation.

MSNet-4mC: learning effective multi-scale representations for identifying DNA N4-methylcytosine sites

MOTIVATION

N4-methylcytosine (4mC) is an essential kind of epigenetic modification that regulates a wide range of biological processes. However, experimental methods for detecting 4mC sites are time-consuming and labor-intensive. As an alternative, computational methods that are capable of automatically identifying 4mC with data analysis techniques become a reasonable option. A major challenge is how to develop effective methods to fully exploit the complex interactions within the DNA sequences to improve the predictive capability.

RESULTS

In this work, we propose MSNet-4mC, a lightweight neural network building upon convolutional operations with multi-scale receptive fields to perceive cross-element relationships over both short and long ranges of given DNA sequences. With strong imbalances in the number of candidates in different species in mind, we compute and apply class weights in the cross-entropy loss to balance the training process. Extensive benchmarking experiments show that our method achieves a significant performance improvement and outperforms other state-of-the-art methods.

AVAILABILITY AND IMPLEMENTATION

The source code and models are freely available for download at https://github.com/LIU-CT/MSNet-4mC, implemented in Python and supported on Linux and Windows.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Unblinding the watchmaker: cancer treatment and drug design in the face of evolutionary pressure

INTRODUCTION

Death due to cancer is mostly associated with therapy ineffectiveness, i.e. tumor cells no longer responding to treatment. The underlying dynamics that facilitate this mutational escape from selective pressure are well studied in several other fields and several interesting approaches exist to combat this phenomenon, for example in the context of antibiotic-resistance in bacteria.

AREAS COVERED

Ninety percent of all cancer-related deaths are associated with treatment failure. Here, we discuss the common treatment modalities and prior attempts to overcome acquired resistance to therapy. The underlying molecular mechanisms are discussed and the implications of emerging resistance in other systems, such as bacteria, are discussed in the context of cancer.

EXPERT OPINION

Reevaluating emerging therapy resistance in tumors as an evolutionary mechanism to survive in a rapidly and drastically altering fitness landscape leads to novel treatment strategies and distinct requirements for new drugs. Here, we propose a scheme of considerations that need to be applied prior to the discovery of novel therapeutic drugs.

Population Epigenetics: The Extent of DNA Methylation Variation in Wild Animal Populations

Population epigenetics explores the extent of epigenetic variation and its dynamics in natural populations encountering changing environmental conditions. In contrast to population genetics, the basic concepts of this field are still in their early stages, especially in animal populations. Epigenetic variation may play a crucial role in phenotypic plasticity and local adaptation as it can be affected by the environment, it is likely to have higher spontaneous mutation rate than nucleotide sequences do, and it may be inherited via non-mendelian processes. In this review, we aim to bring together natural animal population epigenetic studies to generate new insights into ecological epigenetics and its evolutionary implications. We first provide an overview of the extent of DNA methylation variation and its autonomy from genetic variation in wild animal population. Second, we discuss DNA methylation dynamics which create observed epigenetic population structures by including basic population genetics processes. Then, we highlight the relevance of DNA methylation variation as an evolutionary mechanism in the extended evolutionary synthesis. Finally, we suggest new research directions by highlighting gaps in the knowledge of the population epigenetics field. As for our results, DNA methylation diversity was found to reveal parameters that can be used to characterize natural animal populations. Some concepts of population genetics dynamics can be applied to explain the observed epigenetic structure in natural animal populations. The set of recent advancements in ecological epigenetics, especially in transgenerational epigenetic inheritance in wild animal population, might reshape the way ecologists generate predictive models of the capacity of organisms to adapt to changing environments.

Individual Genetic Heterogeneity

Genetic variation has been widely covered in literature, however, not from the perspective of an individual in any species. Here, a synthesis of genetic concepts and variations relevant for individual genetic constitution is provided. All the different levels of genetic information and variation are covered, ranging from whether an organism is unmixed or hybrid, has variations in genome, chromosomes, and more locally in DNA regions, to epigenetic variants or alterations in selfish genetic elements. Genetic constitution and heterogeneity of microbiota are highly relevant for health and wellbeing of an individual. Mutation rates vary widely for variation types, e.g., due to the sequence context. Genetic information guides numerous aspects in organisms. Types of inheritance, whether Mendelian or non-Mendelian, zygosity, sexual reproduction, and sex determination are covered. Functions of DNA and functional effects of variations are introduced, along with mechanism that reduce and modulate functional effects, including TARAR countermeasures and intraindividual genetic conflict. TARAR countermeasures for tolerance, avoidance, repair, attenuation, and resistance are essential for life, integrity of genetic information, and gene expression. The genetic composition, effects of variations, and their expression are considered also in diseases and personalized medicine. The text synthesizes knowledge and insight on individual genetic heterogeneity and organizes and systematizes the central concepts.

Identification of chromatin organization-related gene signature for hepatocellular carcinoma prognosis and predicting immunotherapy response

BACKGROUND

Chromatin organization is associated with tumorigenesis; however, information on its role in hepatocellular carcinoma (HCC) is limited. Moreover, although immune checkpoint inhibitors (ICIs) have proven effective against HCC, the optimal index remains unknown. In this study, we aimed to construct a chromatin organization-related gene signature (CORGS) for prognosis and predicting response to ICIs in HCC.

METHODS

HCC-related data were obtained from The Cancer Genome Atlas (TCGA) and International Cancer Genome Construction (ICGC). Chromatin organization-related genes (CORGs) were retrieved from Gene Set Enrichment Analysis. Differentially expressed genes (DEGs) and prognostic genes were then applied to select candidate genes using advanced statistical methods, including learning vector quantization, random forest, and lasso regression. Subsequently, the CORGS was established based on chromatin organization-related hub genes using multivariate Cox regression analysis, evaluated with Kaplan-Meier survival curves, and verified in 64 samples of HCC patients from Fujian Provincial Hospital (FPH) via quantitative PCR. Subsequently, functional enrichment analysis, tumor somatic mutation analysis, and tumor immune analysis were performed to evaluate the potential value of the CORGS.

RESULTS

Three hundred and thirty-nine CORGs were identified as DEGs, and 186 were associated with HCC prognosis (all P < 0.05). Four intersection genes were selected to establish the CORGS using TCGA cohort, which was found to serve as an independent risk factor for HCC patients. CORGS was then validated in an ICGC cohort. In addition, CORGS reliability was verified in 64 samples from HCC patients and 26 adjacent non-tumorous tissues, collected from the FPH. The CORGS was also associated with tumor immune microenvironment characteristics and ICI response. Moreover, data from "IMvigor 210" revealed that more patients in the low CORGS group responded to atezolizumab compared to high CORGS patients (P < 0.05). Finally, a nomogram of tumor characteristics and the CORGS was established, exhibiting superior discrimination and calibration compared to the current staging system and published models.

CONCLUSIONS

CORGS may serve as an effective predictive biomarker for HCC as well as a potential index of the tumor immune microenvironment and ICI response.

Duplex sequencing identifies genomic features that determine susceptibility to benzo(a)pyrene-induced in vivo mutations

Exposure to environmental mutagens increases the risk of cancer and genetic disorders. We used Duplex Sequencing (DS), a high-accuracy error-corrected sequencing technology, to analyze mutation induction across twenty 2.4 kb intergenic and genic targets in the bone marrow of MutaMouse males exposed to benzo(a)pyrene (BaP), a widespread environmental pollutant. DS revealed a linear dose-related induction of mutations across all targets with low intra-group variability. Heterochromatic and intergenic regions exhibited the highest mutation frequencies (MF). C:G > A:T transversions at CCA, CCC and GCC trinucleotides were enriched in BaP-exposed mice consistent with the known etiology of BaP mutagenesis. However, GC-content had no effect on mutation susceptibility. A positive correlation was observed between DS and the “gold-standard” transgenic rodent gene mutation assay. Overall, we demonstrate that DS is a promising approach to study in vivo mutagenesis and yields critical insight into the genomic features governing mutation susceptibility, spectrum, and variability across the genome.

Population genetics and microevolution of clinical Candida glabrata reveals recombinant sequence types and hyper-variation within mitochondrial genomes, virulence genes, and drug targets

Candida glabrata is the second most common etiological cause of worldwide systemic candidiasis in adult patients. Genome analysis of 68 isolates from 8 hospitals across Scotland, together with 83 global isolates, revealed insights into the population genetics and evolution of C. glabrata. Clinical isolates of C. glabrata from across Scotland are highly genetically diverse, including at least 19 separate sequence types that have been recovered previously in globally diverse locations, and 1 newly discovered sequence type. Several sequence types had evidence for ancestral recombination, suggesting transmission between distinct geographical regions has coincided with genetic exchange arising in new clades. Three isolates were missing MATα1, potentially representing a second mating type. Signatures of positive selection were identified in every sequence type including enrichment for epithelial adhesins thought to facilitate fungal adhesin to human epithelial cells. In patent microevolution was identified from 7 sets of recurrent cases of candidiasis, revealing an enrichment for nonsynonymous and frameshift indels in cell surface proteins. Microevolution within patients also affected epithelial adhesins genes, and several genes involved in drug resistance including the ergosterol synthesis gene ERG4 and the echinocandin target FKS1/2, the latter coinciding with a marked drop in fluconazole minimum inhibitory concentration. In addition to nuclear genome diversity, the C. glabrata mitochondrial genome was particularly diverse, with reduced conserved sequence and conserved protein-encoding genes in all nonreference ST15 isolates. Together, this study highlights the genetic diversity within the C. glabrata population that may impact virulence and drug resistance, and 2 major mechanisms generating this diversity: microevolution and genetic exchange/recombination.

Integration of DNA Repair, Antigenic Variation, Cytoadhesion, and Chance in Babesia Survival: A Perspective

Apicomplexan parasites live in hostile environments in which they are challenged chemically and their hosts attempt in many ways to kill them. In response, the parasites have evolved multiple mechanisms that take advantage of these challenges to enhance their survival. Perhaps the most impressive example is the evolutionary co-option of DNA repair mechanisms by the parasites as a means to rapidly manipulate the structure, antigenicity, and expression of the products of specific multigene families. The purpose of variant proteins that mediate cytoadhesion has long been thought to be primarily the avoidance of splenic clearance. Based upon known biology, I present an alternative perspective in which it is survival of the oxidative environment within which Babesia spp. parasites live that has driven integration of DNA repair, antigenic variation, and cytoadhesion, and speculate on how genome organization affects that integration. This perspective has ramifications for the development of parasite control strategies.

Strand asymmetry influences mismatch resolution during a single-strand annealing

Background

Biases of DNA repair can shape the nucleotide landscape of genomes at evolutionary timescales. The molecular mechanisms of those biases are still poorly understood because it is difficult to isolate the contributions of DNA repair from those of DNA damage.

Results

Here, we develop a genome-wide assay whereby the same DNA lesion is repaired in different genomic contexts. We insert thousands of barcoded transposons carrying a reporter of DNA mismatch repair in the genome of mouse embryonic stem cells. Upon inducing a double-strand break between tandem repeats, a mismatch is generated if the break is repaired through single-strand annealing. The resolution of the mismatch showed a 60–80% bias in favor of the strand with the longest 3′ flap. The location of the lesion in the genome and the type of mismatch had little influence on the bias. Instead, we observe a complete reversal of the bias when the longest 3′ flap is moved to the opposite strand by changing the position of the double-strand break in the reporter.

Conclusions

These results suggest that the processing of the double-strand break has a major influence on the repair of mismatches during a single-strand annealing.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13059-022-02665-3.

Physiological mechanisms of stress-induced evolution

Organisms mount the cellular stress response whenever environmental parameters exceed the range that is conducive to maintaining homeostasis. This response is critical for survival in emergency situations because it protects macromolecular integrity and, therefore, cell/organismal function. From an evolutionary perspective, the cellular stress response counteracts severe stress by accelerating adaptation via a process called stress-induced evolution. In this Review, we summarize five key physiological mechanisms of stress-induced evolution. Namely, these are stress-induced changes in: (1) mutation rates, (2) histone post-translational modifications, (3) DNA methylation, (4) chromoanagenesis and (5) transposable element activity. Through each of these mechanisms, organisms rapidly generate heritable phenotypes that may be adaptive, maladaptive or neutral in specific contexts. Regardless of their consequences to individual fitness, these mechanisms produce phenotypic variation at the population level. Because variation fuels natural selection, the physiological mechanisms of stress-induced evolution increase the likelihood that populations can avoid extirpation and instead adapt under the stress of new environmental conditions.

Data-driven design of targeted gene panels for estimating immunotherapy biomarkers

Tumour mutation burden and other exome-wide biomarkers are used to determine which patients will benefit from immunotherapy. However, the cost of whole exome sequencing limits the widespread use of such biomarkers. Here, we introduce a data-driven framework for the design of targeted gene panels for estimating a broad class of biomarkers including tumour mutation burden and tumour indel burden. Our first goal is to develop a generative model for the profile of mutation across the exome, which allows for gene- and variant type-dependent mutation rates. Based on this model, we then propose a procedure for constructing biomarker estimators. Our approach allows the practitioner to select a targeted gene panel of prespecified size and construct an estimator that only depends on the selected genes. Alternatively, our method may be applied to make predictions based on an existing gene panel, or to augment a gene panel to a given size. We demonstrate the excellent performance of our proposal using data from three non small-cell lung cancer studies, as well as data from six other cancer types.

A data-driven procedure to estimate immunotherapy biomarkers is shown to perform well on data from three Non-Small Cell Lung Cancer studies as well as data from six other cancer types. The method is based on a generative model of how mutations arise in the tumour exome.

Epigenetics and Helicobacter pylori

Epigenetics regulates gene expression, cell type development during differentiation, and the cell response to environmental stimuli. To survive, bacteria need to evade the host immune response. Bacteria, including Helicobacter pylori (Hp), reach this target epigenetically, altering the chromatin of the host cells, in addition to several more approaches, such as DNA mutation and recombination. This review shows that Hp prevalently silences the genes of the human gastric mucosa by DNA methylation. Epigenetics includes different mechanisms. However, DNA methylation persists after DNA replication and therefore is frequently associated with the inheritance of repressed genes. Chromatin modification can be transmitted to daughter cells leading to heritable changes in gene expression. Aberrant epigenetic alteration of the gastric mucosa DNA remains the principal cause of gastric cancer. Numerous methylated genes have been found in cancer as well as in precancerous lesions of Hp-infected patients. These methylated genes inactivate tumor-suppressor genes. It is time for us to complain about our genetic and epigenetic makeups for our diseases.

Not all RAS mutations are equal: A detailed review of the functional diversity of RAS hot spot mutations

The RAS family of small GTPases are among the most frequently mutated oncogenes in human cancer. Approximately 20% of cancers harbor a RAS mutation, and >150 different missense mutations have been detected. Many of these mutations have mutant-specific biochemical defects that alter nucleotide binding and hydrolysis, effector interactions and cell signaling, prompting renewed efforts in the development of anti-RAS therapies, including the mutation-specific strategies. Previously viewed as undruggable, the recent FDA approval of a KRAS^G12C-selective inhibitor has offered real promise to the development of allele-specific RAS therapies. A broader understanding of the mutational consequences on RAS function must be developed to exploit additional allele-specific vulnerabilities. Approximately 94% of RAS mutations occur at one of three mutational "hot spots" at Gly¹², Gly¹³ and Gln⁶¹. Further, the single-nucleotide substitutions represent >99% of these mutations. Within this scope, we discuss the mutational frequencies of RAS isoforms in cancer, mutant-specific effector interactions and biochemical properties. By limiting our analysis to this mutational subset, we simplify the analysis while only excluding a small percentage of total mutations. Combined, these data suggest that the presence or absence of select RAS mutations in human cancers can be linked to their biochemical properties. Continuing to examine the biochemical differences in each RAS-mutant protein will continue to provide additional breakthroughs in allele-specific therapeutic strategies.

Deviation from baseline mutation burden provides powerful and robust rare-variants association test for complex diseases

Identifying rare variants that contribute to complex diseases is challenging because of the low statistical power in current tests comparing cases with controls. Here, we propose a novel and powerful rare variants association test based on the deviation of the observed mutation burden of a gene in cases from a baseline predicted by a weighted recursive truncated negative-binomial regression (RUNNER) on genomic features available from public data. Simulation studies show that RUNNER is substantially more powerful than state-of-the-art rare variant association tests and has reasonable type 1 error rates even for stratified populations or in small samples. Applied to real case-control data, RUNNER recapitulates known genes of Hirschsprung disease and Alzheimer's disease missed by current methods and detects promising new candidate genes for both disorders. In a case-only study, RUNNER successfully detected a known causal gene of amyotrophic lateral sclerosis. The present study provides a powerful and robust method to identify susceptibility genes with rare risk variants for complex diseases.

Anticancer drug resistance: An update and perspective

Driver mutations promote initiation and progression of cancer. Pharmacological treatment can inhibit the action of the mutant protein; however, drug resistance almost invariably emerges. Multiple studies revealed that cancer drug resistance is based upon a plethora of distinct mechanisms. Drug resistance mutations can occur in the same protein or in different proteins; as well as in the same pathway or in parallel pathways, bypassing the intercepted signaling. The dilemma that the clinical oncologist is facing is that not all the genomic alterations as well as alterations in the tumor microenvironment that facilitate cancer cell proliferation are known, and neither are the alterations that are likely to promote metastasis. For example, the common KRasG12C driver mutation emerges in different cancers. Most occur in NSCLC, but some occur, albeit to a lower extent, in colorectal cancer and pancreatic ductal carcinoma. The responses to KRasG12C inhibitors are variable and fall into three categories, (i) new point mutations in KRas, or multiple copies of KRAS G12C which lead to higher expression level of the mutant protein; (ii) mutations in genes other than KRAS; (iii) original cancer transitioning to other cancer(s). Resistance to adagrasib, an experimental antitumor agent exerting its cytotoxic effect as a covalent inhibitor of the G12C KRas, indicated that half of the cases present multiple KRas mutations as well as allele amplification. Redundant or parallel pathways included MET amplification; emerging driver mutations in NRAS, BRAF, MAP2K1, and RET; gene fusion events in ALK, RET, BRAF, RAF1, and FGFR3; and loss-of-function mutations in NF1 and PTEN tumor suppressors. In the current review we discuss the molecular mechanisms underlying drug resistance while focusing on those emerging to common targeted cancer drivers. We also address questions of why cancers with a common driver mutation are unlikely to evolve a common drug resistance mechanism, and whether one can predict the likely mechanisms that the tumor cell may develop. These vastly important and tantalizing questions in drug discovery, and broadly in precision medicine, are the focus of our present review. We end with our perspective, which calls for target combinations to be selected and prioritized with the help of the emerging massive compute power which enables artificial intelligence, and the increased gathering of data to overcome its insatiable needs.

The Mutagenic Impact of Environmental Exposures in Human Cells and Cancer: Imprints Through Time

During life, the DNA of our cells is continuously exposed to external damaging processes. Despite the activity of various repair mechanisms, DNA damage eventually results in the accumulation of mutations in the genomes of our cells. Oncogenic mutations are at the root of carcinogenesis, and carcinogenic agents are often highly mutagenic. Over the past decade, whole genome sequencing data of healthy and tumor tissues have revealed how cells in our body gradually accumulate mutations because of exposure to various mutagenic processes. Dissection of mutation profiles based on the type and context specificities of the altered bases has revealed a variety of signatures that reflect past exposure to environmental mutagens, ranging from chemotherapeutic drugs to genotoxic gut bacteria. In this review, we discuss the latest knowledge on somatic mutation accumulation in human cells, and how environmental mutagenic factors further shape the mutation landscapes of tissues. In addition, not all carcinogenic agents induce mutations, which may point to alternative tumor-promoting mechanisms, such as altered clonal selection dynamics. In short, we provide an overview of how environmental factors induce mutations in the DNA of our healthy cells and how this contributes to carcinogenesis. A better understanding of how environmental mutagens shape the genomes of our cells can help to identify potential preventable causes of cancer.

Epigenetic modifications affect the rate of spontaneous mutations in a pathogenic fungus

Mutations are the source of genetic variation and the substrate for evolution. Genome-wide mutation rates appear to be affected by selection and are probably adaptive. Mutation rates are also known to vary along genomes, possibly in response to epigenetic modifications, but causality is only assumed. In this study we determine the direct impact of epigenetic modifications and temperature stress on mitotic mutation rates in a fungal pathogen using a mutation accumulation approach. Deletion mutants lacking epigenetic modifications confirm that histone mark H3K27me3 increases whereas H3K9me3 decreases the mutation rate. Furthermore, cytosine methylation in transposable elements (TE) increases the mutation rate 15-fold resulting in significantly less TE mobilization. Also accessory chromosomes have significantly higher mutation rates. Finally, we find that temperature stress substantially elevates the mutation rate. Taken together, we find that epigenetic modifications and environmental conditions modify the rate and the location of spontaneous mutations in the genome and alter its evolutionary trajectory.

Developmental and temporal characteristics of clonal sperm mosaicism

Throughout development and aging, human cells accumulate mutations resulting in genomic mosaicism and genetic diversity at the cellular level. Mosaic mutations present in the gonads can affect both the individual and the offspring and subsequent generations. Here, we explore patterns and temporal stability of clonal mosaic mutations in male gonads by sequencing ejaculated sperm. Through 300× whole-genome sequencing of blood and sperm from healthy men, we find each ejaculate carries on average 33.3 ± 12.1 (mean ± SD) clonal mosaic variants, nearly all of which are detected in serial sampling, with the majority absent from sampled somal tissues. Their temporal stability and mutational signature suggest origins during embryonic development from a largely immutable stem cell niche. Clonal mosaicism likely contributes a transmissible, predicted pathogenic exonic variant for 1 in 15 men, representing a life-long threat of transmission for these individuals and a significant burden on human population health.

Heterogeneity of DNA damage incidence and repair in different chromatin contexts

It has been long known that some regions of the genome are more susceptible to damage and mutagenicity than others. Recent advances have determined a critical role of chromatin both in the incidence of damage and in its repair. Thus, chromatin arises as a guardian of the stability of the genome, which is altered in cancer cells. In this review, we focus into the mechanisms by which chromatin influences the occurrence and repair of the most cytotoxic DNA lesions, double-strand breaks, in particular at actively transcribed chromatin or related to DNA replication.

Topographic correlates of driver mutations and endogenous gene expression in pediatric diffuse midline gliomas and hemispheric high-grade gliomas

We evaluate the topographic distribution of diffuse midline gliomas and hemispheric high-grade gliomas in children with respect to their normal gene expression patterns and pathologic driver mutation patterns. We identified 19 pediatric patients with diffuse midline or high-grade glioma with preoperative MRI from tumor board review. 7 of these had 500 gene panel mutation testing, 11 patients had 50 gene panel mutation testing and one 343 gene panel testing from a separate institution were included as validation set. Tumor imaging features and gene expression patterns were analyzed using Allen Brain Atlas. Twelve patients had diffuse midline gliomas and seven had hemispheric high-grade gliomas. Three diffuse midline gliomas had the K27M mutation in the tail of histone H3 protein. All patients undergoing 500 gene panel testing had additional mutations, the most common being in ACVR1, PPM1D, and p53. Hemispheric high-grade gliomas had either TP53 or IDH1 mutation and diffuse midline gliomas had H3 K27M-mutation. Gene expression analysis in normal brains demonstrated that genes mutated in diffuse midline gliomas had higher expression along midline structures as compared to the cerebral hemispheres. Our study suggests that topographic location of pediatric diffuse midline gliomas and hemispheric high-grade gliomas correlates with driver mutations of tumor to the endogenous gene expression in that location. This correlation suggests that cellular state that is required for increased gene expression predisposes that location to mutations and defines the driver mutations within tumors that arise from that region.

An analysis of methylome evolution in primates

Although the investigation of the epigenome becomes increasingly important, still little is known about the long-term evolution of epigenetic marks and systematic investigation strategies are still lacking. Here, we systematically demonstrate the transfer of classic phylogenetic methods such as maximum likelihood based on substitution models, parsimony, and distance-based to interval-scaled epigenetic data. Using a great apes blood data set, we demonstrate that DNA methylation is evolutionarily conserved at the level of individual CpGs in promotors, enhancers, and genic regions. Our analysis also reveals that this epigenomic conservation is significantly correlated with its transcription factor binding density. Binding sites for transcription factors involved in neuron differentiation and components of AP-1 evolve at a significantly higher rate at methylation than at the nucleotide level. Moreover, our models suggest an accelerated epigenomic evolution at binding sites of BRCA1, chromobox homolog protein 2, and factors of the polycomb repressor 2 complex in humans. For most genomic regions, the methylation-based reconstruction of phylogenetic trees is at par with sequence-based reconstruction. Most strikingly, phylogenetic reconstruction using methylation rates in enhancer regions was ineffective independently of the chosen model. We identify a set of phylogenetically uninformative CpG sites enriched in enhancers controlling immune-related genes.

A molecular Rosetta Stone to decipher the impact of chromatin features on the repair of Cas9-mediated DNA double-strand breaks

Using a barcoded reporter introduced within a thousand different chromatin locations in human cells, (Schep et al., 2021) characterize repair outcomes of Cas9-induced DNA double-strand breaks (DSBs) and the relative use of DSB repair pathways depending on the local chromatin context.

Coupling between Sequence-Mediated Nucleosome Organization and Genome Evolution

The nucleosome is a major modulator of DNA accessibility to other cellular factors. Nucleosome positioning has a critical importance in regulating cell processes such as transcription, replication, recombination or DNA repair. The DNA sequence has an influence on the position of nucleosomes on genomes, although other factors are also implicated, such as ATP-dependent remodelers or competition of the nucleosome with DNA binding proteins. Different sequence motifs can promote or inhibit the nucleosome formation, thus influencing the accessibility to the DNA. Sequence-encoded nucleosome positioning having functional consequences on cell processes can then be selected or counter-selected during evolution. We review the interplay between sequence evolution and nucleosome positioning evolution. We first focus on the different ways to encode nucleosome positions in the DNA sequence, and to which extent these mechanisms are responsible of genome-wide nucleosome positioning in vivo. Then, we discuss the findings about selection of sequences for their nucleosomal properties. Finally, we illustrate how the nucleosome can directly influence sequence evolution through its interactions with DNA damage and repair mechanisms. This review aims to provide an overview of the mutual influence of sequence evolution and nucleosome positioning evolution, possibly leading to complex evolutionary dynamics.

The impact of epigenetic information on genome evolution

Epigenetic information affects gene function by interacting with chromatin, while not changing the DNA sequence itself. However, it has become apparent that the interactions between epigenetic information and chromatin can, in fact, indirectly lead to DNA mutations and ultimately influence genome evolution. This review evaluates the ways in which epigenetic information affects genome sequence and evolution. We discuss how DNA methylation has strong and pervasive effects on DNA sequence evolution in eukaryotic organisms. We also review how the physical interactions arising from the connections between histone proteins and DNA affect DNA mutation and repair. We then discuss how a variety of epigenetic mechanisms exert substantial effects on genome evolution by suppressing the movement of transposable elements. Finally, we examine how genome expansion through gene duplication is also partially controlled by epigenetic information. Overall, we conclude that epigenetic information has widespread indirect effects on DNA sequences in eukaryotes and represents a potent cause and constraint of genome evolution. This article is part of the theme issue 'How does epigenetics influence the course of evolution?'

Mechanisms of enhancer action: the known and the unknown

Differential gene expression mechanisms ensure cellular differentiation and plasticity to shape ontogenetic and phylogenetic diversity of cell types. A key regulator of differential gene expression programs are the enhancers, the gene-distal cis-regulatory sequences that govern spatiotemporal and quantitative expression dynamics of target genes. Enhancers are widely believed to physically contact the target promoters to effect transcriptional activation. However, our understanding of the full complement of regulatory proteins and the definitive mechanics of enhancer action is incomplete. Here, we review recent findings to present some emerging concepts on enhancer action and also outline a set of outstanding questions.

Correlated Evolution of Large DNA Fragments in the 3D Genome of Arabidopsis thaliana

In eukaryotes, the three-dimensional (3D) conformation of the genome is far from random, and this nonrandom chromatin organization is strongly correlated with gene expression and protein function, which are two critical determinants of the selective constraints and evolutionary rates of genes. However, whether genes and other elements that are located close to each other in the 3D genome evolve in a coordinated way has not been investigated in any organism. To address this question, we constructed chromatin interaction networks (CINs) in Arabidopsis thaliana based on high-throughput chromosome conformation capture data and demonstrated that adjacent large DNA fragments in the CIN indeed exhibit more similar levels of polymorphism and evolutionary rates than random fragment pairs. Using simulations that account for the linear distance between fragments, we proved that the 3D chromosomal organization plays a role in the observed correlated evolution. Spatially interacting fragments also exhibit more similar mutation rates and functional constraints in both coding and noncoding regions than the random expectations, indicating that the correlated evolution between 3D neighbors is a result of combined evolutionary forces. A collection of 39 genomic and epigenomic features can explain much of the variance in genetic diversity and evolutionary rates across the genome. Moreover, features that have a greater effect on the evolution of regional sequences tend to show higher similarity between neighboring fragments in the CIN, suggesting a pivotal role of epigenetic modifications and chromatin organization in determining the correlated evolution of large DNA fragments in the 3D genome.

EvoLSTM: context-dependent models of sequence evolution using a sequence-to-sequence LSTM

Motivation

Accurate probabilistic models of sequence evolution are essential for a wide variety of bioinformatics tasks, including sequence alignment and phylogenetic inference. The ability to realistically simulate sequence evolution is also at the core of many benchmarking strategies. Yet, mutational processes have complex context dependencies that remain poorly modeled and understood.

Results

We introduce EvoLSTM, a recurrent neural network-based evolution simulator that captures mutational context dependencies. EvoLSTM uses a sequence-to-sequence long short-term memory model trained to predict mutation probabilities at each position of a given sequence, taking into consideration the 14 flanking nucleotides. EvoLSTM can realistically simulate mammalian and plant DNA sequence evolution and reveals unexpectedly strong long-range context dependencies in mutation probabilities. EvoLSTM brings modern machine-learning approaches to bear on sequence evolution. It will serve as a useful tool to study and simulate complex mutational processes.

Availability and implementation

Code and dataset are available at https://github.com/DongjoonLim/EvoLSTM.

Supplementary information

Supplementary data are available at Bioinformatics online.

Non-B DNA: a major contributor to small- and large-scale variation in nucleotide substitution frequencies across the genome

Approximately 13% of the human genome can fold into non-canonical (non-B) DNA structures (e.g. G-quadruplexes, Z-DNA, etc.), which have been implicated in vital cellular processes. Non-B DNA also hinders replication, increasing errors and facilitating mutagenesis, yet its contribution to genome-wide variation in mutation rates remains unexplored. Here, we conducted a comprehensive analysis of nucleotide substitution frequencies at non-B DNA loci within noncoding, non-repetitive genome regions, their ±2 kb flanking regions, and 1-Megabase windows, using human-orangutan divergence and human single-nucleotide polymorphisms. Functional data analysis at single-base resolution demonstrated that substitution frequencies are usually elevated at non-B DNA, with patterns specific to each non-B DNA type. Mirror, direct and inverted repeats have higher substitution frequencies in spacers than in repeat arms, whereas G-quadruplexes, particularly stable ones, have higher substitution frequencies in loops than in stems. Several non-B DNA types also affect substitution frequencies in their flanking regions. Finally, non-B DNA explains more variation than any other predictor in multiple regression models for diversity or divergence at 1-Megabase scale. Thus, non-B DNA substantially contributes to variation in substitution frequencies at small and large scales. Our results highlight the role of non-B DNA in germline mutagenesis with implications to evolution and genetic diseases.

BRG1 knockdown inhibits proliferation through multiple cellular pathways in prostate cancer

Background

BRG1 (encoded by SMARCA4) is a catalytic component of the SWI/SNF chromatin remodelling complex, with key roles in modulating DNA accessibility. Dysregulation of BRG1 is observed, but functionally uncharacterised, in a wide range of malignancies. We have probed the functions of BRG1 on a background of prostate cancer to investigate how BRG1 controls gene expression programmes and cancer cell behaviour.

Results

Our investigation of SMARCA4 revealed that BRG1 is over-expressed in the majority of the 486 tumours from The Cancer Genome Atlas prostate cohort, as well as in a complementary panel of 21 prostate cell lines. Next, we utilised a temporal model of BRG1 depletion to investigate the molecular effects on global transcription programmes. Depleting BRG1 had no impact on alternative splicing and conferred only modest effect on global expression. However, of the transcriptional changes that occurred, most manifested as down-regulated expression. Deeper examination found the common thread linking down-regulated genes was involvement in proliferation, including several known to increase prostate cancer proliferation (KLK2, PCAT1 and VAV3). Interestingly, the promoters of genes driving proliferation were bound by BRG1 as well as the transcription factors, AR and FOXA1. We also noted that BRG1 depletion repressed genes involved in cell cycle progression and DNA replication, but intriguingly, these pathways operated independently of AR and FOXA1. In agreement with transcriptional changes, depleting BRG1 conferred G1 arrest.

Conclusions

Our data have revealed that BRG1 promotes cell cycle progression and DNA replication, consistent with the increased cell proliferation associated with oncogenesis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-021-01023-7.

Epigenomic differences in the human and chimpanzee genomes are associated with structural variation

Structural variation (SV), including insertions and deletions (indels), is a primary mechanism of genome evolution. However, the mechanism by which SV contributes to epigenome evolution is poorly understood. In this study, we characterized the association between lineage-specific indels and epigenome differences between human and chimpanzee to investigate how SVs might have shaped the epigenetic landscape. By intersecting medium-to-large human-chimpanzee indels (20 bp-50 kb) with putative promoters and enhancers in cranial neural crest cells (CNCCs) and repressed regions in induced pluripotent cells (iPSCs), we found that 12% of indels overlap putative regulatory and repressed regions (RRRs), and 15% of these indels are associated with lineage-biased RRRs. Indel-associated putative enhancer and repressive regions are approximately 1.3 times and approximately three times as likely to be lineage-biased, respectively, as those not associated with indels. We found a twofold enrichment of medium-sized indels (20-50 bp) in CpG island (CGI)-containing promoters than expected by chance. Lastly, from human-specific transposable element insertions, we identified putative regulatory elements, including NR2F1-bound putative CNCC enhancers derived from SVAs and putative iPSC promoters derived from LTR5s. Our results show that different types of indels are associated with specific epigenomic diversity between human and chimpanzee.

Somatic mutation distributions in cancer genomes vary with three-dimensional chromatin structure

Somatic mutations in driver genes may ultimately lead to the development of cancer. Understanding how somatic mutations accumulate in cancer genomes and the underlying factors that generate somatic mutations is therefore crucial for developing novel therapeutic strategies. To understand the interplay between spatial genome organization and specific mutational processes, we studied 3,000 tumor-normal-pair whole-genome datasets from 42 different human cancer types. Our analyses reveal that the change in somatic mutational load in cancer genomes is co-localized with topologically-associating-domain boundaries. Domain boundaries constitute a better proxy to track mutational load change than replication timing measurements. We show that different mutational processes lead to distinct somatic mutation distributions where certain processes generate mutations in active domains, and others generate mutations in inactive domains. Overall, the interplay between three-dimensional genome organization and active mutational processes has a substantial influence on the large-scale mutation-rate variations observed in human cancers.