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

Hematopoietic stem cells: self-renewal and expansion

: Hematopoietic stem cells (HSCs) are a unique population of cells with the remarkable ability to replenish themselves through self-renewal and to give rise to differentiated cell lineages. Though having been discovered more than 50 years ago, and having been widely used in bone marrow transplantation to treat blood disorders including leukemia, expansion of HSCs remains an unmet task, thus affecting its more effective usage in clinical practice.

PURPOSE OF REVIEW

The purpose of this review article is to summarize past efforts in ex-vivo HSC expansion and to compare recent advances in expanding murine and human HSCs by targeting the N-methyladenosine (mA) pathway.

RECENT FINDINGS

Unlike past many efforts that mainly target single or limited pathways and often lead to lineage bias or expansion of progenitor cells or limited long-term HSCs (LT-HSCs), the blocking the degradation of mA pathway has an advantage of stabilizing hundreds of key factors required for maintaining HSCs, thus resulting in expansion of functional LT-HSCs.

SUMMARY

The new approach of targeting the mA pathway has a promising application in clinical HSC-based transplantation.

Establishment and evolution of heterochromatin

The eukaryotic genome is packaged into transcriptionally active euchromatin and silent heterochromatin, with most studies focused on the former encompassing the majority of protein-coding genes. The recent development of various sequencing techniques has refined this classic dichromatic partition and has better illuminated the composition, establishment, and evolution of this genomic and epigenomic "dark matter" in the context of topologically associated domains and phase-separated droplets. Heterochromatin includes genomic regions that can be densely stained by chemical dyes, which have been shown to be enriched for repetitive elements and epigenetic marks, including H3K9me2/3 and H3K27me3. Heterochromatin is usually replicated late, concentrated at the nuclear periphery or around nucleoli, and usually lacks highly expressed genes; and now it is considered to be as neither genetically inert nor developmentally static. Heterochromatin guards genome integrity against transposon activities and exerts important regulatory functions by targeting beyond its contained genes. Both its nucleotide sequences and regulatory proteins exhibit rapid coevolution between species. In addition, there are dynamic transitions between euchromatin and heterochromatin during developmental and evolutionary processes. We summarize here the ever-changing characteristics of heterochromatin and propose models and principles for the evolutionary transitions of heterochromatin that have been mainly learned from studies of Drosophila and yeast. Finally, we highlight the role of sex chromosomes in studying heterochromatin evolution.

Somatic mutations in colorectal cancer are associated with the epigenetic modifications

Colorectal cancer (CRC) mostly arises from progressive accumulation of somatic mutations within cells. Most commonly mutated genes like TP53, APC and KRAS can promote survival and proliferation of cancer cells. Although the molecular alterations and landscape of some specific mutations in CRC are well known, the presence of a somatic mutation signature related to genomic regions and epigenetic markers remain unclear. To find the signatures from a random distribution of somatic mutations in CRCs, we carried out enrichment analysis in different genomic regions and identified peaks of epigenetic markers. We validated that the mutation frequency in miRNA is dramatically higher than in flanking genomic regions. Moreover, we observed that somatic mutations in CRC and colon cancer cell lines are significantly enriched in CTCF binding sites. We also found these mutations are enriched for H3K27me3 in both normal sigmoid colon and colon cancer cell lines. Taken together, our findings suggest that there are some common somatic mutations signatures which provide new directions to study CRC.

Mutational signature SBS8 predominantly arises due to late replication errors in cancer

Although a majority of somatic mutations in cancer are passengers, their mutational signatures provide mechanistic insights into mutagenesis and DNA repair processes. Mutational signature SBS8 is common in most cancers, but its etiology is debated. Incorporating genomic, epigenomic, and cellular process features for multiple cell-types we develop genome-wide composite epigenomic context-maps relevant for mutagenesis and DNA repair. Analyzing somatic mutation data from multiple cancer types in their epigenomic contexts, we show that SBS8 preferentially occurs in gene-poor, lamina-proximal, late replicating heterochromatin domains. While SBS8 is uncommon among mutations in non-malignant tissues, in tumor genomes its proportions increase with replication timing and speed, and checkpoint defects further promote this signature - suggesting that SBS8 probably arises due to uncorrected late replication errors during cancer progression. Our observations offer a potential reconciliation among different perspectives in the debate about the etiology of SBS8 and its relationship with other mutational signatures.

Chromatin Structure and Drug Resistance in Candida spp

Anti-microbial resistance (AMR) is currently one of the most serious threats to global human health and, appropriately, research to tackle AMR garnishes significant investment and extensive attention from the scientific community. However, most of this effort focuses on antibiotics, and research into anti-fungal resistance (AFR) is vastly under-represented in comparison. Given the growing number of vulnerable, immunocompromised individuals, as well as the positive impact global warming has on fungal growth, there is an immediate urgency to tackle fungal disease, and the disturbing rise in AFR. Chromatin structure and gene expression regulation play pivotal roles in the adaptation of fungal species to anti-fungal stress, suggesting a potential therapeutic avenue to tackle AFR. In this review we discuss both the genetic and epigenetic mechanisms by which chromatin structure can dictate AFR mechanisms and will present evidence of how pathogenic yeast, specifically from the Candida genus, modify chromatin structure to promote survival in the presence of anti-fungal drugs. We also discuss the mechanisms by which anti-chromatin therapy, specifically lysine deacetylase inhibitors, influence the acquisition and phenotypic expression of AFR in Candida spp. and their potential as effective adjuvants to mitigate against AFR.

Chromatin network markers of leukemia

MOTIVATION

The structure of chromatin impacts gene expression. Its alteration has been shown to coincide with the occurrence of cancer. A key challenge is in understanding the role of chromatin structure (CS) in cellular processes and its implications in diseases.

RESULTS

We propose a comparative pipeline to analyze CSs and apply it to study chronic lymphocytic leukemia (CLL). We model the chromatin of the affected and control cells as networks and analyze the network topology by state-of-the-art methods. Our results show that CSs are a rich source of new biological and functional information about DNA elements and cells that can complement protein-protein and co-expression data. Importantly, we show the existence of structural markers of cancer-related DNA elements in the chromatin. Surprisingly, CLL driver genes are characterized by specific local wiring patterns not only in the CS network of CLL cells, but also of healthy cells. This allows us to successfully predict new CLL-related DNA elements. Importantly, this shows that we can identify cancer-related DNA elements in other cancer types by investigating the CS network of the healthy cell of origin, a key new insight paving the road to new therapeutic strategies. This gives us an opportunity to exploit chromosome conformation data in healthy cells to predict new drivers.

AVAILABILITY AND IMPLEMENTATION

Our predicted CLL genes and RNAs are provided as a free resource to the community at https://life.bsc.es/iconbi/chromatin/index.html.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Natural cryptic variation in epigenetic modulation of an embryonic gene regulatory network

Gene regulatory networks (GRNs) that direct animal embryogenesis must respond to varying environmental and physiological conditions to ensure robust construction of organ systems. While GRNs are evolutionarily modified by natural genomic variation, the roles of epigenetic processes in shaping plasticity of GRN architecture are not well understood. The endoderm GRN in Caenorhabditis elegans is initiated by the maternally supplied SKN-1/Nrf2 bZIP transcription factor; however, the requirement for SKN-1 in endoderm specification varies widely among distinct C. elegans wild isotypes, owing to rapid developmental system drift driven by accumulation of cryptic genetic variants. We report here that heritable epigenetic factors that are stimulated by transient developmental diapause also underlie cryptic variation in the requirement for SKN-1 in endoderm development. This epigenetic memory is inherited from the maternal germline, apparently through a nuclear, rather than cytoplasmic, signal, resulting in a parent-of-origin effect (POE), in which the phenotype of the progeny resembles that of the maternal founder. The occurrence and persistence of POE varies between different parental pairs, perduring for at least 10 generations in one pair. This long-perduring POE requires piwi-interacting RNA (piRNA) function and the germline nuclear RNA interference (RNAi) pathway, as well as MET-2 and SET-32, which direct histone H3K9 trimethylation and drive heritable epigenetic modification. Such nongenetic cryptic variation may provide a resource of additional phenotypic diversity through which adaptation may facilitate evolutionary changes and shape developmental regulatory systems.

The Role of Stochasticity in the Origin of Epigenetic Variation in Animal Populations

Epigenetic mechanisms such as DNA methylation modulate gene expression in a complex fashion are consequently recognized as among the most important contributors to phenotypic variation in natural populations of plants, animals, and microorganisms. Interactions between genetics and epigenetics are multifaceted and epigenetic variation stands at the crossroad between genetic and environmental variance, which make these mechanisms prominent in the processes of adaptive evolution. DNA methylation patterns depend on the genotype and can be reshaped by environmental conditions, while transgenerational epigenetic inheritance has been reported in various species. On the other hand, DNA methylation can influence the genetic mutation rate and directly affect the evolutionary potential of a population. The origin of epigenetic variance can be attributed to genetic, environmental, or stochastic factors. Generally less investigated than the first two components, variation lacking any predictable order is nevertheless present in natural populations and stochastic epigenetic variation, also referred to spontaneous epimutations, can sustain phenotypic diversity. Here, potential sources of such stochastic epigenetic variability in animals are explored, with a focus on DNA methylation. To this day, quantifying the importance of stochasticity in epigenetic variability remains a challenge. However, comparisons between the mutation and the epimutation rates showed a high level of the latter, suggesting a significant role of spontaneous epimutations in adaptation. The implications of stochastic epigenetic variability are multifold: by affecting development and subsequently phenotype, random changes in epigenetic marks may provide additional phenotypic diversity, which can help natural populations when facing fluctuating environments. In isogenic lineages and asexually reproducing organisms, poor or absent genetic diversity can hence be tolerated. Further implication of stochastic epigenetic variability in adaptation is found in bottlenecked invasive species populations and populations using a bet-hedging strategy.

Extreme differences between human germline and tumor mutation densities are driven by ancestral human-specific deviations

Mutations do not accumulate uniformly across the genome. Human germline and tumor mutation density correlate poorly, and each is associated with different genomic features. Here, we use non-human great ape (NHGA) germlines to determine human germline- and tumor-specific deviations from an ancestral-like great ape genome-wide mutational landscape. Strikingly, we find that the distribution of mutation densities in tumors presents a stronger correlation with NHGA than with human germlines. This effect is driven by human-specific differences in the distribution of mutations at non-CpG sites. We propose that ancestral human demographic events, together with the human-specific mutation slowdown, disrupted the human genome-wide distribution of mutation densities. Tumors partially recover this distribution by accumulating preneoplastic-like somatic mutations. Our results highlight the potential utility of using NHGA population data, rather than human controls, to establish the expected mutational background of healthy somatic cells.

Rice 3D chromatin structure correlates with sequence variation and meiotic recombination rate

Genomes of many eukaryotic species have a defined three-dimensional architecture critical for cellular processes. They are partitioned into topologically associated domains (TADs), defined as regions of high chromatin inter-connectivity. While TADs are not a prominent feature of A. thaliana genome organization, they have been reported for other plants including rice, maize, tomato and cotton and for which TAD formation appears to be linked to transcription and chromatin epigenetic status. Here we show that in the rice genome, sequence variation and meiotic recombination rate correlate with the 3D genome structure. TADs display increased SNP and SV density and higher recombination rate compared to inter-TAD regions. We associate the observed differences with the TAD epigenetic landscape, TE composition and an increased incidence of meiotic crossovers.

Golicz et al. report an increase in single nucleotide polymorphisms and structural variations across and within Topologically Associated Domains (TADs) in the rice genome, which is different to the pattern observed in the human genome. They show that this may be due to epigenetic modifications, transposable elements composition, and meiotic crossovers in the TAD regions.

SSRome: an integrated database and pipelines for exploring microsatellites in all organisms

Over the past decade, many databases focusing on microsatellite mining on a genomic scale were released online with at least one of the following major deficiencies: (i) lacking the classification of microsatellites as genic or non-genic, (ii) not comparing microsatellite motifs at both genic and non-genic levels in order to identify unique motifs for each class or (iii) missing SSR marker development. In this study, we have developed ‘SSRome’ as a web-based, user-friendly, comprehensive and dynamic database with pipelines for exploring microsatellites in 6533 organisms. In the SSRome database, 158 million microsatellite motifs are identified across all taxa, in addition to all the mitochondrial and chloroplast genomes and expressed sequence tags available from NCBI. Moreover, 45.1 million microsatellite markers were developed and classified as genic or non-genic. All the stored motif and marker datasets can be downloaded freely. In addition, SSRome provides three user-friendly tools to identify, classify and compare motifs on either a genome- or transcriptome-wide scale. With the implementation of PHP, HTML and JavaScript, users can upload their data for analysis via a user-friendly GUI. SSRome represents a powerful database and mega-tool that will assist researchers in developing and dissecting microsatellite markers on a high-throughput scale.

Accumulation of Deleterious Mutations in Landlocked Threespine Stickleback Populations

Colonization of new habitats often reduces population sizes and may result in the accumulation of deleterious mutations by genetic drift. Compared with the genomic basis for adaptation to new environments, genome-wide analysis of deleterious mutations in isolated populations remains limited. In the present study, we investigated the accumulation of deleterious mutations in five endangered freshwater populations of threespine stickleback (Gasterosteus aculeatus) in the central part of the mainland of Japan. Using whole-genome resequencing data, we first conducted phylogenomic analysis and confirmed at least two independent freshwater colonization events in the central mainland from ancestral marine ecotypes. Next, analyses of single nucleotide polymorphisms showed a substantial reduction of heterozygosity in freshwater populations compared with marine populations. Reduction in heterozygosity was more apparent at the center of each chromosome than the peripheries and on X chromosomes compared with autosomes. Third, bioinformatic analysis of deleterious mutations showed increased accumulation of putatively deleterious mutations in the landlocked freshwater populations compared with marine populations. For the majority of populations examined, the frequencies of putatively deleterious mutations were higher on X chromosomes than on autosomes. The interpopulation comparison indicated that the majority of putatively deleterious mutations may have accumulated independently. Thus, whole-genome resequencing of endangered populations can help to estimate the accumulation of deleterious mutations and inform us of which populations are the most severely endangered. Furthermore, analysis of variation among chromosomes can give insights into whether any particular chromosomes are likely to accumulate deleterious mutations.

Nucleosome positioning stability is a modulator of germline mutation rate variation across the human genome

Nucleosome organization has been suggested to affect local mutation rates in the genome. However, the lack of de novo mutation and high-resolution nucleosome data has limited the investigation of this hypothesis. Additionally, analyses using indirect mutation rate measurements have yielded contradictory and potentially confounding results. Here, we combine data on >300,000 human de novo mutations with high-resolution nucleosome maps and find substantially elevated mutation rates around translationally stable (‘strong’) nucleosomes. We show that the mutational mechanisms affected by strong nucleosomes are low-fidelity replication, insufficient mismatch repair and increased double-strand breaks. Strong nucleosomes preferentially locate within young SINE/LINE transposons, suggesting that when subject to increased mutation rates, transposons are then more rapidly inactivated. Depletion of strong nucleosomes in older transposons suggests frequent positioning changes during evolution. The findings have important implications for human genetics and genome evolution.

Nucleosome organization has been suggested to affect local mutation rates in the genome. Here, the authors analyse data on >300,000 human de novo mutations and high-resolution nucleosome maps and provide evidence that nucleosome positioning stability modulates germline mutation rate variation across the human genome.

Cytosine Methylation Affects the Mutability of Neighboring Nucleotides in Germline and Soma

Methylated cytosines deaminate at higher rates than unmethylated cytosines, and the lesions they produce are repaired less efficiently. As a result, methylated cytosines are mutational hotspots. Here, combining rare polymorphism and base-resolution methylation data in humans, Arabidopsis thaliana, and rice (Oryza sativa), we present evidence that methylation state affects mutation dynamics not only at the focal cytosine but also at neighboring nucleotides. In humans, contrary to prior suggestions, we find that nucleotides in the close vicinity (±3 bp) of methylated cytosines mutate less frequently. Reduced mutability around methylated CpGs is also observed in cancer genomes, considering single nucleotide variants alongside tissue-of-origin-matched methylation data. In contrast, methylation is associated with increased neighborhood mutation risk in A. thaliana and rice. The difference in neighborhood mutation risk is less pronounced further away from the focal CpG and modulated by regional GC content. Our results are consistent with a model where altered risk at neighboring bases is linked to lesion formation at the focal CpG and subsequent long-patch repair. Our findings indicate that cytosine methylation has a broader mutational footprint than is commonly assumed.

Local Determinants of the Mutational Landscape of the Human Genome

Large-scale chromatin features, such as replication time and accessibility influence the rate of somatic and germline mutations at the megabase scale. This article reviews how local chromatin structures -e.g., DNA wrapped around nucleosomes, transcription factors bound to DNA- affect the mutation rate at a local scale. It dissects how the interaction of some mutagenic agents and/or DNA repair systems with these local structures influence the generation of mutations. We discuss how this local mutation rate variability affects our understanding of the evolution of the genomic sequence, and the study of the evolution of organisms and tumors.

De novo mutations across 1,465 diverse genomes reveal mutational insights and reductions in the Amish founder population

De novo mutations (DNMs), or mutations that appear in an individual despite not being seen in their parents, are an important source of genetic variation whose impact is relevant to studies of human evolution, genetics, and disease. Utilizing high-coverage whole-genome sequencing data as part of the Trans-Omics for Precision Medicine (TOPMed) Program, we called 93,325 single-nucleotide DNMs across 1,465 trios from an array of diverse human populations, and used them to directly estimate and analyze DNM counts, rates, and spectra. We find a significant positive correlation between local recombination rate and local DNM rate, and that DNM rate explains a substantial portion (8.98 to 34.92%, depending on the model) of the genome-wide variation in population-level genetic variation from 41K unrelated TOPMed samples. Genome-wide heterozygosity does correlate with DNM rate, but only explains <1% of variation. While we are underpowered to see small differences, we do not find significant differences in DNM rate between individuals of European, African, and Latino ancestry, nor across ancestrally distinct segments within admixed individuals. However, we did find significantly fewer DNMs in Amish individuals, even when compared with other Europeans, and even after accounting for parental age and sequencing center. Specifically, we found significant reductions in the number of C→A and T→C mutations in the Amish, which seem to underpin their overall reduction in DNMs. Finally, we calculated near-zero estimates of narrow sense heritability (h2), which suggest that variation in DNM rate is significantly shaped by nonadditive genetic effects and the environment.

Identification of cancer driver genes based on nucleotide context

Cancer genomes contain large numbers of somatic mutations, but few of these mutations drive tumor development. Current approaches identify driver genes based on mutational recurrence, or they approximate the functional consequences of nonsynonymous mutations using bioinformatic scores. While passenger mutations are enriched in characteristic nucleotide contexts, driver mutations occur in functional positions, which are not necessarily surrounded by a particular nucleotide context. We observed that mutations in contexts that deviate from the characteristic contexts around passenger mutations provide a signal in favor of driver genes. We therefore developed a method that combines this feature with the signals traditionally used for driver gene identification. We applied our method to whole-exome sequencing data from 11,873 tumor-normal pairs and identified 460 driver genes that clustered into 21 cancer-related pathways. Our study provides a resource of driver genes across 28 tumor types with additional driver genes identified based on mutations in unusual nucleotide contexts.

Matching whole genomes to rare genetic disorders: Identification of potential causative variants using phenotype-weighted knowledge in the CAGI SickKids5 clinical genomes challenge

Precise identification of causative variants from whole-genome sequencing data, including both coding and noncoding variants, is challenging. The Critical Assessment of Genome Interpretation 5 SickKids clinical genome challenge provided an opportunity to assess our ability to extract such information. Participants in the challenge were required to match each of the 24 whole-genome sequences to the correct phenotypic profile and to identify the disease class of each genome. These are all rare disease cases that have resisted genetic diagnosis in a state-of-the-art pipeline. The patients have a range of eye, neurological, and connective-tissue disorders. We used a gene-centric approach to address this problem, assigning each gene a multiphenotype-matching score. Mutations in the top-scoring genes for each phenotype profile were ranked on a 6-point scale of pathogenicity probability, resulting in an approximately equal number of top-ranked coding and noncoding candidate variants overall. We were able to assign the correct disease class for 12 cases and the correct genome to a clinical profile for five cases. The challenge assessor found genes in three of these five cases as likely appropriate. In the postsubmission phase, after careful screening of the genes in the correct genome, we identified additional potential diagnostic variants, a high proportion of which are noncoding.

Physicochemical Foundations of Life that Direct Evolution: Chance and Natural Selection are not Evolutionary Driving Forces

The current framework of evolutionary theory postulates that evolution relies on random mutations generating a diversity of phenotypes on which natural selection acts. This framework was established using a top-down approach as it originated from Darwinism, which is based on observations made of complex multicellular organisms and, then, modified to fit a DNA-centric view. In this article, it is argued that based on a bottom-up approach starting from the physicochemical properties of nucleic and amino acid polymers, we should reject the facts that (i) natural selection plays a dominant role in evolution and (ii) the probability of mutations is independent of the generated phenotype. It is shown that the adaptation of a phenotype to an environment does not correspond to organism fitness, but rather corresponds to maintaining the genome stability and integrity. In a stable environment, the phenotype maintains the stability of its originating genome and both (genome and phenotype) are reproduced identically. In an unstable environment (i.e., corresponding to variations in physicochemical parameters above a physiological range), the phenotype no longer maintains the stability of its originating genome, but instead influences its variations. Indeed, environment- and cellular-dependent physicochemical parameters define the probability of mutations in terms of frequency, nature, and location in a genome. Evolution is non-deterministic because it relies on probabilistic physicochemical rules, and evolution is driven by a bidirectional interplay between genome and phenotype in which the phenotype ensures the stability of its originating genome in a cellular and environmental physicochemical parameter-depending manner.

A key metabolic gene for recurrent freshwater colonization and radiation in fishes

Colonization of new ecological niches has triggered large adaptive radiations. Although some lineages have made use of such opportunities, not all do so. The factors causing this variation among lineages are largely unknown. Here, we show that deficiency in docosahexaenoic acid (DHA), an essential ω-3 fatty acid, can constrain freshwater colonization by marine fishes. Our genomic analyses revealed multiple independent duplications of the fatty acid desaturase gene Fads2 in stickleback lineages that subsequently colonized and radiated in freshwater habitats, but not in close relatives that failed to colonize. Transgenic manipulation of Fads2 in marine stickleback increased their ability to synthesize DHA and survive on DHA-deficient diets. Multiple freshwater ray-finned fishes also show a convergent increase in Fads2 copies, indicating its key role in freshwater colonization.

How Prostate Cancer Cells Use Strategy Instead of Brute Force to Achieve Metastasis

Akin to many other cancers, metastasis is the predominant cause of lethality in prostate cancer (PCa). Research in the past decade or so has revealed that although metastatic manifestation is a multi-step and complex process that is orchestrated by distinct cellular and molecular mechanisms, the process in itself is an extremely inefficient one. It is now becoming increasingly evident that PCa cells employ a plethora of strategies to make the most of this inefficient process. These strategies include priming the metastatic sites ahead of colonization, devising ways to metastasize to specific organs, outsmarting the host defense surveillance, lying in a dormant state at the metastatic site for prolonged periods, and widespread reprogramming of the gene expression to suit their needs. Based on established, recent, and evolving lines of research, this review is an attempt to understand PCa metastasis from the perspective of military combat, wherein strategic maneuvering instead of brute force often plays a decisive role in the outcome.

Genomic-Destabilization-Associated Mutagenesis and Clonal Evolution of Cells with Mutations in Tumor-Suppressor Genes

The development of cancer is driven by genomic instability and mutations. In general, cancer develops via multiple steps. Each step involves the clonal evolution of cells with abrogated defense systems, such as cells with mutations in cancer-suppressor genes. However, it remains unclear how cellular defense systems are abrogated and the associated clonal evolution is triggered and propagated. In this manuscript, we review current knowledge regarding mutagenesis associated with genomic destabilization and its relationship with the clonal evolution of cells over the course of cancer development, focusing especially on mechanistic aspects.

Somatic genome alterations in relation to age in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is the most common cause of global cancer-related mortality and the major risk factor is smoking consumption. By analyzing 486 LUAD samples from The Cancer Genome Atlas, we detected a higher mutational burden among younger patients in the global cohort as well as in the TP53-mutated subcohort. The interaction effect of patient age and TP53 mutations significantly affected the mutational rate of younger TP53-mutated patients. Furthermore, we detected a significant enrichment of the smoking-related signature SI4 (SI4) among younger TP53-mutated patients, meanwhile the age-related Signature 1 (SI1) significantly increased in proportion to patient age. Although present and past smoking is reported in the TP53 wild-type patients, we observed a lower average number of somatic mutations, with no correlation with patient age. Overall, TP53 mutations were significantly higher in younger patients and mainly characterized by SI4 and Signature 24 (SI24). Therefore, TP53 seemed to acquire a particular sensitivity to smoking related C>A mutations in younger patients. We hypothesize that TP53 mutations at a younger age might be a crucial factor enhancing the sensitivity to smoking-related mutations leading to a burst of somatic alterations. The mutational profile of cancer cell might reflect the mutational processes operative in aging in a given tissue. Therefore, TP53-mutated and TP53 wild-type patient groups might represent phenotypes which endure aging-related mutational processes with different strength. Our study provides indications of age-dependent differences in mutational backgrounds that might be relevant for cancer prevention and age-adjusted treatment approaches.

EvoChromo: towards a synthesis of chromatin biology and evolution

Over the past few years, interest in chromatin and its evolution has grown. To further advance these interests, we organized a workshop with the support of The Company of Biologists to debate the current state of knowledge regarding the origin and evolution of chromatin. This workshop led to prospective views on the development of a new field of research that we term 'EvoChromo'. In this short Spotlight article, we define the breadth and expected impact of this new area of scientific inquiry on our understanding of both chromatin and evolution.

From Schizophrenia Genetics to Disease Biology: Harnessing New Concepts and Technologies

Schizophrenia (SZ) is a severe mental disorder afflicting around 1% of the population. It is highly heritable but with complex genetics. Recent research has unraveled a plethora of risk loci for SZ. Accordingly, our conceptual understanding of SZ genetics has been rapidly evolving, from oligogenic models towards polygenic or even omnigenic models. A pressing challenge to the field, however, is the translation of the many genetic findings of SZ into disease biology insights leading to more effective treatments. Bridging this gap requires the integration of genetic findings and functional genomics using appropriate cellular models. Harnessing new technologies, such as the development of human induced pluripotent stem cells (hiPSC) and the CRISPR/Cas-based genome/epigenome editing approach are expected to change our understanding of SZ disease biology to a fundamentally higher level. Here, we discuss some new developments.

Germline DNA replication timing shapes mammalian genome composition

Mammalian DNA replication is a highly organized and regulated process. Large, Mb-sized regions are replicated at defined times along S-phase. Replication Timing (RT) is thought to play a role in shaping the mammalian genome by affecting mutation rates. Previous analyses relied on somatic RT profiles. However, only germline mutations are passed on to offspring and affect genomic composition. Therefore, germ cell RT information is necessary to evaluate the influences of RT on the mammalian genome. We adapted the RT mapping technique for limited amounts of cells, and measured RT from two stages in the mouse germline - primordial germ cells (PGCs) and spermatogonial stem cells (SSCs). RT in germline cells exhibited stronger correlations to both mutation rate and recombination hotspots density than those of RT in somatic tissues, emphasizing the importance of using correct tissues-of-origin for RT profiling. Germline RT maps exhibited stronger correlations to additional genetic features including GC-content, transposable elements (SINEs and LINEs), and gene density. GC content stratification and multiple regression analysis revealed independent contributions of RT to SINE, gene, mutation, and recombination hotspot densities. Together, our results establish a central role for RT in shaping multiple levels of mammalian genome composition.

Understanding the impacts of missense mutations on structures and functions of human cancer-related genes: A preliminary computational analysis of the COSMIC Cancer Gene Census

Genomics and genome screening are proving central to the study of cancer. However, a good appreciation of the protein structures coded by cancer genes is also invaluable, especially for the understanding of functions, for assessing ligandability of potential targets, and for designing new drugs. To complement the wealth of information on the genetics of cancer in COSMIC, the most comprehensive database for cancer somatic mutations available, structural information obtained experimentally has been brought together recently in COSMIC-3D. Even where structural information is available for a gene in the Cancer Gene Census, a list of genes in COSMIC with substantial evidence supporting their impacts in cancer, this information is quite often for a single domain in a larger protein or for a single protomer in a multiprotein assembly. Here, we show that over 60% of the genes included in the Cancer Gene Census are predicted to possess multiple domains. Many are also multicomponent and membrane-associated molecular assemblies, with mutations recorded in COSMIC affecting such assemblies. However, only 469 of the gene products have a structure represented in the PDB, and of these only 87 structures have 90-100% coverage over the sequence and 69 have less than 10% coverage. As a first step to bridging gaps in our knowledge in the many cases where individual protein structures and domains are lacking, we discuss our attempts of protein structure modelling using our pipeline and investigating the effects of mutations using two of our in-house methods (SDM2 and mCSM) and identifying potential driver mutations. This allows us to begin to understand the effects of mutations not only on protein stability but also on protein-protein, protein-ligand and protein-nucleic acid interactions. In addition, we consider ways to combine the structural information with the wealth of mutation data available in COSMIC. We discuss the impacts of COSMIC missense mutations on protein structure in order to identify and assess the molecular consequences of cancer-driving mutations.

Integrative analysis of DNA methylation suggests down-regulation of oncogenic pathways and reduced somatic mutation rates in survival outliers of glioblastoma

The study of survival outliers of glioblastoma can provide important clues on gliomagenesis as well as on the ways to alter clinical course of this almost uniformly lethal cancer type. However, there has been little consensus on genetic and epigenetic signatures of the long-term survival outliers of glioblastoma. Although the two classical molecular markers of glioblastoma including isocitrate dehydrogenase 1 or 2 (IDH1/2) mutation and O6-methylguanine DNA methyltransferase (MGMT) promoter methylation are associated with overall survival rate of glioblastoma patients, they are not specific to the survival outliers. In this study, we compared the two groups of survival outliers of glioblastoma with IDH wild-type, consisting of the glioblastoma patients who lived longer than 3 years (n = 17) and the patients who lived less than 1 year (n = 12) in terms of genome-wide DNA methylation profile. Statistical analyses were performed to identify differentially methylated sites between the two groups. Functional implication of DNA methylation patterns specific to long-term survivors of glioblastoma were investigated by comprehensive enrichment analyses with genomic and epigenomic features. We found that the genome of long-term survivors of glioblastoma is differentially methylated relative to short-term survivor patients depending on CpG density: hypermethylation near CpG islands (CGIs) and hypomethylation far from CGIs. Interestingly, these two patterns are associated with distinct oncogenic aspects in gliomagenesis. In the long-term survival glioblastoma-specific sites distant from CGI, somatic mutations of glioblastoma are enriched with higher DNA methylation, suggesting that the hypomethylation in long-term survival glioblastoma can contribute to reduce the rate of somatic mutation. On the other hand, the hypermethylation near CGIs associates with transcriptional downregulation of genes involved in cancer progression pathways. Using independent cohorts of IDH1/2- wild type glioblastoma, we also showed that these two patterns of DNA methylation can be used as molecular markers of long-term survival glioblastoma. Our results provide extended understanding of DNA methylation, especially of DNA hypomethylation, in cancer genome and reveal clinical importance of DNA methylation pattern as prognostic markers of glioblastoma.

Understanding the 3D genome: Emerging impacts on human disease

Recent burst of new technologies that allow for quantitatively delineating chromatin structure has greatly expanded our understanding of how the genome is organized in the three-dimensional (3D) space of the nucleus. It is now clear that the hierarchical organization of the eukaryotic genome critically impacts nuclear activities such as transcription, replication, as well as cellular and developmental events such as cell cycle, cell fate decision and embryonic development. In this review, we discuss new insights into how the structural features of the 3D genome hierarchy are established and maintained, how this hierarchy undergoes dynamic rearrangement during normal development and how its perturbation will lead to human disease, highlighting the accumulating evidence that links the diverse 3D genome architecture components to a multitude of human diseases and the emerging mechanisms by which 3D genome derangement causes disease phenotypes.

Oligonucleotide Analogs and Mimics for Sensing Macromolecular Biocompounds

Living organisms create life-sustaining macromolecular biocompounds including biopolymers. Artificial polymers can selectively recognize biocompounds and are more resistant to harsh physical, chemical, and physiological conditions than biopolymers are. Due to recognition at a molecular level, molecularly imprinted polymers (MIPs) provide powerful tools to correlate structure with biological functionality and are often used to build next-generation chemosensors. We envision an increasing emergence of nucleic acid analogs (NAAs) or biorelevant monomers built into nature-mimicking polymers. For example, if nucleobases bearing monomers arranged by a complementary template are polymerized to form NAAs, the resulting MIPs will open up novel perspectives for synthesizing NAAs. Despite their usefulness, it is still challenging to use MIPs to devise adaptive biomaterials and to implement them in point-of-care testing.

HELLS Regulates Chromatin Remodeling and Epigenetic Silencing of Multiple Tumor Suppressor Genes in Human Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the third most lethal cancer worldwide. Increasing evidence shows that epigenetic alterations play an important role in human carcinogenesis. Deregulation of DNA methylation and histone modifications have recently been characterized in HCC, but the significance of chromatin remodeling in liver carcinogenesis remains to be explored. In this study, by systematically analyzing the expression of chromatin remodeling genes in human HCCs, we found that helicase, lymphoid-specific (HELLS), an SWI2/SNF2 chromatin remodeling enzyme, was remarkably overexpressed in HCC. Overexpression of HELLS correlated with more aggressive clinicopathological features and poorer patient prognosis compared to patients with lower HELLS expression. We further showed that up-regulation of HELLS in HCC was conferred by hyperactivation of transcription factor specificity protein 1 (SP1). To investigate the functions of HELLS in HCC, we generated both gain-of-function and loss-of-function models by the CRISPR activation system, lentiviral short hairpin RNA, and the CRISPR/Cas9 genome editing system. We demonstrated that overexpression of HELLS augmented HCC cell proliferation and migration. In contrast, depletion of HELLS reduced HCC growth and metastasis both in vitro and in vivo. Moreover, inactivation of HELLS led to metabolic reprogramming and reversed the Warburg effect in HCC cells. Mechanistically, by integrating analysis of RNA sequencing and micrococcal nuclease sequencing, we revealed that overexpression of HELLS increased nucleosome occupancy, which obstructed the accessibility of enhancers and hindered formation of the nucleosome-free region (NFR) at the transcription start site. Though this mechanism, up-regulation of HELLS mediated epigenetic silencing of multiple tumor suppressor genes including E-cadherin, FBP1, IGFBP3, XAF1 and CREB3L3 in HCC. Conclusion: Our data reveal that HELLS is a key epigenetic driver of HCC; by altering the nucleosome occupancy at the NFR and enhancer, HELLS epigenetically suppresses multiple tumor suppressor genes to promote HCC progression.

Colocalization analyses of genomic elements: approaches, recommendations and challenges

MOTIVATION

Many high-throughput methods produce sets of genomic regions as one of their main outputs. Scientists often use genomic colocalization analysis to interpret such region sets, for example to identify interesting enrichments and to understand the interplay between the underlying biological processes. Although widely used, there is little standardization in how these analyses are performed. Different practices can substantially affect the conclusions of colocalization analyses.

RESULTS

Here, we describe the different approaches and provide recommendations for performing genomic colocalization analysis, while also discussing common methodological challenges that may influence the conclusions. As illustrated by concrete example cases, careful attention to analysis details is needed in order to meet these challenges and to obtain a robust and biologically meaningful interpretation of genomic region set data.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

An Overview of Methods for Reconstructing 3-D Chromosome and Genome Structures from Hi-C Data

Over the past decade, methods for predicting three-dimensional (3-D) chromosome and genome structures have proliferated. This has been primarily due to the development of high-throughput, next-generation chromosome conformation capture (3C) technologies, which have provided next-generation sequencing data about chromosome conformations in order to map the 3-D genome structure. The introduction of the Hi-C technique-a variant of the 3C method-has allowed researchers to extract the interaction frequency (IF) for all loci of a genome at high-throughput and at a genome-wide scale. In this review we describe, categorize, and compare the various methods developed to map chromosome and genome structures from 3C data-particularly Hi-C data. We summarize the improvements introduced by these methods, describe the approach used for method evaluation, and discuss how these advancements shape the future of genome structure construction.

Early in life effects and heredity: reconciling neo-Darwinism with neo-Lamarckism under the banner of the inclusive evolutionary synthesis

Recent discoveries show that early in life effects often have long-lasting influences, sometimes even spanning several generations. Such intergenerational effects of early life events appear not easily reconcilable with strict genetic inheritance. However, an integrative evolutionary medicine of early life effects needs a sound view of inheritance in development and evolution. Here, we show how to articulate the gene-centred and non-gene-centred visions of inheritance. We first recall the coexistence of two gene concepts in scientific discussions, a statistical one (focused on patterns of parent-offspring resemblance, and implicitly including non-DNA-sequence-based resemblance), and a molecular one (based on the DNA sequence). We then show how all the different mechanisms of inheritance recently discovered can be integrated into an inclusive theory of evolution where different mechanisms would enable adaptation to changing environments at different timescales. One surprising consequence of this integrative vision of inheritance is that early in life effects start much earlier than fertilization. This article is part of the theme issue 'Developing differences: early-life effects and evolutionary medicine'.

Chromatin landscapes reveal developmentally encoded transcriptional states that define human glioblastoma

Mack et al. defined active chromatin landscapes of glioblastoma stem cells (GSCs) and primary tumor specimens, revealing novel transcriptional regulatory circuits and therapeutic targets. Super-enhancers identified essential transcription factors that underlie GSC identity and intertumoral diversity, potentially informing precision medicine.

Glioblastoma is an incurable brain cancer characterized by high genetic and pathological heterogeneity. Here, we mapped active chromatin landscapes with gene expression, whole exomes, copy number profiles, and DNA methylomes across 44 patient-derived glioblastoma stem cells (GSCs), 50 primary tumors, and 10 neural stem cells (NSCs) to identify essential super-enhancer (SE)–associated genes and the core transcription factors that establish SEs and maintain GSC identity. GSCs segregate into two groups dominated by distinct enhancer profiles and unique developmental core transcription factor regulatory programs. Group-specific transcription factors enforce GSC identity; they exhibit higher activity in glioblastomas versus NSCs, are associated with poor clinical outcomes, and are required for glioblastoma growth in vivo. Although transcription factors are commonly considered undruggable, group-specific enhancer regulation of the MAPK/ERK pathway predicts sensitivity to MEK inhibition. These data demonstrate that transcriptional identity can be leveraged to identify novel dependencies and therapeutic approaches.

Chromatin reprogramming as an adaptation mechanism in advanced prostate cancer

Tumor evolution is based on the ability to constantly mutate and activate different pathways under the selective pressure of targeted therapies. Epigenetic alterations including those of the chromatin structure are associated with tumor initiation, progression and drug resistance. Many cancers, including prostate cancer, present enlarged nuclei, and chromatin appears altered and irregular. These phenotypic changes are likely to result from epigenetic dysregulation. High-throughput sequencing applied to bulk samples and now to single cells has made it possible to study these processes in unprecedented detail. It is therefore timely to review the impact of chromatin relaxation and increased DNA accessibility on prostate cancer growth and drug resistance, and their effects on gene expression. In particular, we focus on the contribution of chromatin-associated proteins such as the bromodomain-containing proteins to chromatin relaxation. We discuss the consequence of this for androgen receptor transcriptional activity and briefly summarize wider gain-of-function effects on other oncogenic transcription factors and implications for more effective prostate cancer treatment.

Mismatch repair-signature mutations activate gene enhancers across human colorectal cancer epigenomes

Commonly-mutated genes have been found for many cancers, but less is known about mutations in cis-regulatory elements. We leverage gains in tumor-specific enhancer activity, coupled with allele-biased mutation detection from H3K27ac ChIP-seq data, to pinpoint potential enhancer-activating mutations in colorectal cancer (CRC). Analysis of a genetically-diverse cohort of CRC specimens revealed that microsatellite instable (MSI) samples have a high indel rate within active enhancers. Enhancers with indels show evidence of positive selection, increased target gene expression, and a subset is highly recurrent. The indels affect short homopolymer tracts of A/T and increase affinity for FOX transcription factors. We further demonstrate that signature mismatch-repair (MMR) mutations activate enhancers using a xenograft tumor metastasis model, where mutations are induced naturally via CRISPR/Cas9 inactivation of MLH1 prior to tumor cell injection. Our results suggest that MMR signature mutations activate enhancers in CRC tumor epigenomes to provide a selective advantage.

Mutational and Antigenic Landscape in Tumor Progression and Cancer Immunotherapy

Evolving neoplasms accumulate non-synonymous mutations at a high rate, potentially enabling the expression of antigenic epitopes that can be recognized by the immune system. Since they are not covered by central tolerance, such tumor neoantigens (TNAs) should be under robust immune control as they surge. However, genetic defects that impair cancer cell eradication by the immune system coupled with the establishment of local immunosuppression can enable TNA accumulation, which is generally associated with improved clinical sensitivity to various immunotherapies. Here, we explore how tumor-intrinsic factors and immunological processes shape the mutational and antigenic landscape of evolving neoplasms to influence clinical responses to immunotherapy, and propose strategies to achieve robust immunological control of the disease despite disabled immunosurveillance.

Recurrent mutations at estrogen receptor binding sites alter chromatin topology and distal gene expression in breast cancer

BACKGROUND

The mutational processes underlying non-coding cancer mutations and their biological significance in tumor evolution are poorly understood. To get better insights into the biological mechanisms of mutational processes in breast cancer, we integrate whole-genome level somatic mutations from breast cancer patients with chromatin states and transcription factor binding events.

RESULTS

We discover that a large fraction of non-coding somatic mutations in estrogen receptor (ER)-positive breast cancers are confined to ER binding sites. Notably, the highly mutated estrogen receptor binding sites are associated with more frequent chromatin loop contacts and the associated distal genes are expressed at higher level. To elucidate the functional significance of these non-coding mutations, we focus on two of the recurrently mutated estrogen receptor binding sites. Our bioinformatics and biochemical analysis suggest loss of DNA-protein interactions due to the recurrent mutations. Through CRISPR interference, we find that the recurrently mutated regulatory element at the LRRC3C-GSDMA locus impacts the expression of multiple distal genes. Using a CRISPR base editor, we show that the recurrent C→T conversion at the ZNF143 locus results in decreased TF binding, increased chromatin loop formation, and increased expression of multiple distal genes. This single point mutation mediates reduced response to estradiol-induced cell proliferation but increased resistance to tamoxifen-induced growth inhibition.

CONCLUSIONS

Our data suggest that ER binding is associated with localized accumulation of somatic mutations, some of which affect chromatin architecture, distal gene expression, and cellular phenotypes in ER-positive breast cancer.

Long-read sequencing technology indicates genome-wide effects of non-B DNA on polymerization speed and error rate

DNA conformation may deviate from the classical B-form in ∼13% of the human genome. Non-B DNA regulates many cellular processes; however, its effects on DNA polymerization speed and accuracy have not been investigated genome-wide. Such an inquiry is critical for understanding neurological diseases and cancer genome instability. Here, we present the first simultaneous examination of DNA polymerization kinetics and errors in the human genome sequenced with Single-Molecule Real-Time (SMRT) technology. We show that polymerization speed differs between non-B and B-DNA: It decelerates at G-quadruplexes and fluctuates periodically at disease-causing tandem repeats. Analyzing polymerization kinetics profiles, we predict and validate experimentally non-B DNA formation for a novel motif. We demonstrate that several non-B motifs affect sequencing errors (e.g., G-quadruplexes increase error rates), and that sequencing errors are positively associated with polymerase slowdown. Finally, we show that highly divergent G4 motifs have pronounced polymerization slowdown and high sequencing error rates, suggesting similar mechanisms for sequencing errors and germline mutations.

Aberrant PRDM9 expression impacts the pan-cancer genomic landscape

The binding of PRDM9 to chromatin is a key step in the induction of DNA double-strand breaks associated with meiotic recombination hotspots; it is normally expressed solely in germ cells. We interrogated 1879 cancer samples in 39 different cancer types and found that PRDM9 is unexpectedly expressed in 20% of these tumors even after stringent gene homology correction. The expression levels of PRDM9 in tumors are significantly higher than those found in healthy neighboring tissues and in healthy nongerm tissue databases. Recurrently mutated regions located within 5 Mb of the PRDM9 loci, as well as differentially expressed genes in meiotic pathways, correlate with PRDM9 expression. In samples with aberrant PRDM9 expression, structural variant breakpoints frequently neighbor the DNA motif recognized by PRDM9, and there is an enrichment of structural variants at sites of known meiotic PRDM9 activity. This study is the first to provide evidence of an association between aberrant expression of the meiosis-specific gene PRDM9 with genomic instability in cancer.