Local Determinants of the Mutational Landscape of the Human Genome

Mutational bias in spermatogonia impacts the anatomy of regulatory sites in the human genome

Mutation in the germline is the ultimate source of genetic variation, but little is known about the influence of germline chromatin structure on mutational processes. Using ATAC-seq, we profile the open chromatin landscape of human spermatogonia, the most proliferative cell type of the germline, identifying transcription factor binding sites (TFBSs) and PRDM9 binding sites, a subset of which will initiate meiotic recombination. We observe an increase in rare structural variant (SV) breakpoints at PRDM9-bound sites, implicating meiotic recombination in the generation of structural variation. Many germline TFBSs, such as NRF1, are also associated with increased rates of SV breakpoints, apparently independent of recombination. Singleton short insertions (≥5 bp) are highly enriched at TFBSs, particularly at sites bound by testis active TFs, and their rates correlate with those of structural variant breakpoints. Short insertions often duplicate the TFBS motif, leading to clustering of motif sites near regulatory regions in this male-driven evolutionary process. Increased mutation loads at germline TFBSs disproportionately affect neural enhancers with activity in spermatogonia, potentially altering neurodevelopmental regulatory architecture. Local chromatin structure in spermatogonia is thus pervasive in shaping both evolution and disease.

CTCF binding modulates UV damage formation to promote mutation hot spots in melanoma

Somatic mutations in DNA-binding sites for CCCTC-binding factor (CTCF) are significantly elevated in many cancers. Prior analysis has suggested that elevated mutation rates at CTCF-binding sites in skin cancers are a consequence of the CTCF-cohesin complex inhibiting repair of UV damage. Here, we show that CTCF binding modulates the formation of UV damage to induce mutation hot spots. Analysis of genome-wide CPD-seq data in UV-irradiated human cells indicates that formation of UV-induced cyclobutane pyrimidine dimers (CPDs) is primarily suppressed by CTCF binding but elevated at specific locations within the CTCF motif. Locations of CPD hot spots in the CTCF-binding motif coincide with mutation hot spots in melanoma. A similar pattern of damage formation is observed at CTCF-binding sites in vitro, indicating that UV damage modulation is a direct consequence of CTCF binding. We show that CTCF interacts with binding sites containing UV damage and inhibits repair by a model repair enzyme in vitro. Structural analysis and molecular dynamic simulations reveal the molecular mechanism for how CTCF binding modulates CPD formation.

Deciphering genes associated with diffuse large B-cell lymphoma with lymphomatous effusions: A mutational accumulation scoring approach

Introduction

Earlier studies have shown that lymphomatous effusions in patients with diffuse large B-cell lymphoma (DLBCL) are associated with a very poor prognosis, even worse than for non-effusion-associated patients with stage IV disease. We hypothesized that certain genetic abnormalities were associated with lymphomatous effusions, which would help to identify related pathways, oncogenic mechanisms, and therapeutic targets.

Methods

We compared whole-exome sequencing on DLBCL samples involving solid organs (n = 22) and involving effusions (n = 9). We designed a mutational accumulation-based approach to score each gene and used mutation interpreters to identify candidate pathogenic genes associated with lymphomatous effusions. Moreover, we performed gene-set enrichment analysis from a microarray comparison of effusion-associated versus non-effusion-associated DLBCL cases to extract the related pathways.

Results

We found that genes involved in identified pathways or with high accumulation scores in the effusion-based DLBCL cases were associated with migration/invasion. We validated expression of 8 selected genes in DLBCL cell lines and clinical samples: MUC4, SLC35G6, TP53BP2, ARAP3, IL13RA1, PDIA4, HDAC1 and MDM2, and validated expression of 3 proteins (MUC4, HDAC1 and MDM2) in an independent cohort of DLBCL cases with (n = 31) and without (n = 20) lymphomatous effusions. We found that overexpression of HDAC1 and MDM2 correlated with the presence of lymphomatous effusions, and HDAC1 overexpression was associated with the poorest prognosis. 

Conclusion

Our findings suggest that DLBCL associated with lymphomatous effusions may be associated mechanistically with TP53-MDM2 pathway and HDAC-related chromatin remodeling mechanisms.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40364-021-00330-8.

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.

Mutperiod: Analysis of periodic mutation rates in nucleosomes

Nucleosomes modulate DNA damage and repair, resulting in periodic mutation rates in nucleosomal DNA. Previous research has characterized these patterns in many sequenced tumor genomes; however, computational tools to identify and quantify these periodicities have not been developed for the broader scientific community. Here, we describe mutperiod, a Python and R based toolset that quantifies nucleosome mutational periodicities and compares them across different genetic and cellular backgrounds. We use mutperiod to demonstrate that DNA mismatch repair contributes to the nucleosome mutational periodicity observed in esophageal adenocarcinomas, and that the strength of this mutational periodicity varies in different chromatin states.

Gene expression levels modulate germline mutation rates through the compound effects of transcription-coupled repair and damage

Of all mammalian organs, the testis has long been observed to have the most diverse gene expression profile. To account for this widespread gene expression, we have proposed a mechanism termed 'transcriptional scanning', which reduces germline mutation rates through transcription-coupled repair (TCR). Our hypothesis contrasts with an earlier observation that mutation rates are overall positively correlated with gene expression levels in yeast, implying that transcription is mutagenic due to effects dominated by transcription-coupled damage (TCD). Here we report evidence that the compound effects of both TCR and TCD during spermatogenesis modulate human germline mutation rates, with TCR dominating in most genes, thus supporting the transcriptional scanning hypothesis. Our analyses address potentially confounding factors, distinguish the differential mutagenic effects acting on the highly expressed genes and the low-to-moderately expressed genes, and resolve concerns relating to the validation of the results using a de novo mutation dataset. We also discuss the theoretical possibility of transcriptional scanning hypothesis from an evolutionary perspective. Together, these analyses support a model by which the coupling of transcription-coupled repair and damage establishes the pattern of germline mutation rates and provide an evolutionary explanation for widespread gene expression during spermatogenesis.

Biology before the SOS Response-DNA Damage Mechanisms at Chromosome Fragile Sites

The Escherichia coli SOS response to DNA damage, discovered and conceptualized by Evelyn Witkin and Miroslav Radman, is the prototypic DNA-damage stress response that upregulates proteins of DNA protection and repair, a radical idea when formulated in the late 1960s and early 1970s. SOS-like responses are now described across the tree of life, and similar mechanisms of DNA-damage tolerance and repair underlie the genome instability that drives human cancer and aging. The DNA damage that precedes damage responses constitutes upstream threats to genome integrity and arises mostly from endogenous biology. Radman's vision and work on SOS, mismatch repair, and their regulation of genome and species evolution, were extrapolated directly from bacteria to humans, at a conceptual level, by Radman, then many others. We follow his lead in exploring bacterial molecular genomic mechanisms to illuminate universal biology, including in human disease, and focus here on some events upstream of SOS: the origins of DNA damage, specifically at chromosome fragile sites, and the engineered proteins that allow us to identify mechanisms. Two fragility mechanisms dominate: one at replication barriers and another associated with the decatenation of sister chromosomes following replication. DNA structures in E. coli, additionally, suggest new interpretations of pathways in cancer evolution, and that Holliday junctions may be universal molecular markers of chromosome fragility.

RepairSig: Deconvolution of DNA damage and repair contributions to the mutational landscape of cancer

Cancer genomes accumulate a large number of somatic mutations resulting from a combination of stochastic errors in DNA processing, cancer-related aberrations of the DNA repair machinery, or carcinogenic exposures; each mutagenic process leaves a characteristic mutational signature. A key challenge is understanding the interactions between signatures, particularly as DNA repair deficiencies often modify the effects of other mutagens. Here, we introduce RepairSig, a computational method that explicitly models additive primary mutagenic processes; non-additive secondary processes, which interact with the primary processes; and a mutation opportunity, that is, the distribution of sites across the genome that are vulnerable to damage or preferentially repaired. We demonstrate that RepairSig accurately recapitulates experimentally identified signatures, identifies autonomous signatures of deficient DNA repair processes, and explains mismatch repair deficiency in breast cancer by de novo inference of both primary and secondary signatures from patient data. RepairSig is freely available for download at https://github.com/ncbi/RepairSig.

Non-coding driver mutations in human cancer

Tumour formation involves random mutagenic events and positive evolutionary selection acting on a subset of such events, referred to as driver mutations. A decade of careful surveying of tumour DNA using exome-based analyses has revealed a multitude of protein-coding somatic driver mutations, some of which are clinically actionable. Today, a transition towards whole-genome analysis is well under way, technically enabling the discovery of potential driver mutations occurring outside protein-coding sequences. Mutations are abundant in this vast non-coding space, which is more than 50 times larger than the coding exome, but reliable identification of selection signals in non-coding DNA remains a challenge. In this Review, we discuss recent findings in the field, where the emerging landscape is one in which non-coding driver mutations appear to be relatively infrequent. Nevertheless, we highlight several notable discoveries. We consider possible reasons for the relative absence of non-coding driver events, as well as the difficulties associated with detecting signals of positive selection in non-coding DNA.

In silico saturation mutagenesis of cancer genes

Despite the existence of good catalogues of cancer genes^1,2, identifying the specific mutations of those genes that drive tumorigenesis across tumour types is still a largely unsolved problem. As a result, most mutations identified in cancer genes across tumours are of unknown significance to tumorigenesis³. We propose that the mutations observed in thousands of tumours-natural experiments testing their oncogenic potential replicated across individuals and tissues-can be exploited to solve this problem. From these mutations, features that describe the mechanism of tumorigenesis of each cancer gene and tissue may be computed and used to build machine learning models that encapsulate these mechanisms. Here we demonstrate the feasibility of this solution by building and validating 185 gene-tissue-specific machine learning models that outperform experimental saturation mutagenesis in the identification of  driver and passenger mutations. The models and their assessment of each mutation are designed to be interpretable, thus avoiding a black-box prediction device. Using these models, we outline the blueprints of potential driver mutations in cancer genes, and demonstrate the role of mutation probability in shaping the landscape of observed driver mutations. These blueprints will support the interpretation of newly sequenced tumours in patients and the study of the mechanisms of tumorigenesis of cancer genes across tissues.

Mutational Signatures: From Methods to Mechanisms

Mutations are the driving force of evolution, yet they underlie many diseases, in particular, cancer. They are thought to arise from a combination of stochastic errors in DNA processing, naturally occurring DNA damage (e.g., the spontaneous deamination of methylated CpG sites), replication errors, and dysregulation of DNA repair mechanisms. High-throughput sequencing has made it possible to generate large datasets to study mutational processes in health and disease. Since the emergence of the first mutational process studies in 2012, this field is gaining increasing attention and has already accumulated a host of computational approaches and biomedical applications.

The landscape of driver mutations in cutaneous squamous cell carcinoma

Cutaneous squamous cell carcinoma is a form of skin cancer originating from keratinocytes in the skin. It is the second most common type of cancer and is responsible for an estimated 8000 deaths per year in the United States. Compared to other cancer subtypes with similar incidences and death tolls, our understanding of the somatic mutations driving cutaneous squamous cell carcinoma is limited. The main challenge is that these tumors have high mutation burdens, primarily a consequence of UV-radiation-induced DNA damage from sunlight, making it difficult to distinguish driver mutations from passenger mutations. We overcame this challenge by performing a meta-analysis of publicly available sequencing data covering 105 tumors from 10 different studies. Moreover, we eliminated tumors with issues, such as low neoplastic cell content, and from the tumors that passed quality control, we utilized multiple strategies to reveal genes under selection. In total, we nominated 30 cancer genes. Among the more novel genes, mutations frequently affected EP300, PBRM1, USP28, and CHUK. Collectively, mutations in the NOTCH and p53 pathways were ubiquitous, and to a lesser extent, mutations affected genes in the Hippo pathway, genes in the Ras/MAPK/PI3K pathway, genes critical for cell-cycle checkpoint control, and genes encoding chromatin remodeling factors. Taken together, our study provides a catalog of driver genes in cutaneous squamous cell carcinoma, offering points of therapeutic intervention and insights into the biology of cutaneous squamous cell carcinoma.

Single-cell damagenome profiling unveils vulnerable genes and functional pathways in human genome toward DNA damage

We report a novel single-cell whole-genome amplification method (LCS-WGA) that can efficiently capture spontaneous DNA damage existing in single cells. We refer to these damage-associated single-nucleotide variants as "damSNVs," and the whole-genome distribution of damSNVs as the damagenome. We observed that in single human neurons, the damagenome distribution was significantly correlated with three-dimensional genome structures. This nonuniform distribution indicates different degrees of DNA damage effects on different genes. Next, we identified the functionals that were significantly enriched in the high-damage genes. Similar functionals were also enriched in the differentially expressed genes (DEGs) detected by single-cell transcriptome of both Alzheimer's disease (AD) and autism spectrum disorder (ASD). This result can be explained by the significant enrichment of high-damage genes in the DEGs of neurons for both AD and ASD. The discovery of high-damage genes sheds new lights on the important roles of DNA damage in human diseases and disorders.

A Dynamic View of the Interaction of Histone Tails with Clustered Abasic Sites in a Nucleosome Core Particle

Apurinic/apyrimidinic sites are the most common forms of DNA damage under physiological conditions, yet their structural and dynamical behavior within nucleosome core particles has just begun to be investigated and is dramatically different from that of abasic sites in B-DNA. Clusters of two or more abasic sites are repaired even less efficiently and hence constitute hot spots of high mutagenicity notably due to enhanced double-strand break formation. On the basis of an X-ray structure of a 146 bp DNA wrapped onto a histone core, we investigate the structural behavior of two bistranded abasic sites positioned at mutational hot spots during microsecond-range molecular dynamics simulations. Our simulations allow us to probe interactions of histone tails at clustered abasic site locations, with a definitive assignment of the key residues involved in the NCP-catalyzed formation of DNA-protein cross-linking in line with recent experimental findings, and pave the way for a systematic assessment of the response of histone tails to DNA lesions.

Reading the chromatinized genome

Eukaryotic DNA-binding proteins operate in the context of chromatin, where nucleosomes are the elementary building blocks. Nucleosomal DNA is wrapped around a histone core, thereby rendering a large fraction of the DNA surface inaccessible to DNA-binding proteins. Nevertheless, first responders in DNA repair and sequence-specific transcription factors bind DNA target sites obstructed by chromatin. While early studies examined protein binding to histone-free DNA, it is only now beginning to emerge how DNA sequences are interrogated on nucleosomes. These readout strategies range from the release of nucleosomal DNA from histones, to rotational/translation register shifts of the DNA motif, and nucleosome-specific DNA binding modes that differ from those observed on naked DNA. Since DNA motif engagement on nucleosomes strongly depends on position and orientation, we argue that motif location and nucleosome positioning co-determine protein access to DNA in transcription and DNA repair.

The Physics-Biology continuum challenges darwinism: Evolution is directed by the homeostasis-dependent bidirectional relation between genome and phenotype

The physics-biology continuum relies on the fact that life emerged from prebiotic molecules. Here, I argue that life emerged from the coupling between nucleic acid and protein synthesis during which proteins (or proto-phenotypes) maintained the physicochemical parameter equilibria (or proto-homeostasis) in the proximity of their encoding nucleic acids (or proto-genomes). This protected the proto-genome physicochemical integrity (i.e., atomic composition) from environmental physicochemical constraints, and therefore increased the probability of reproducing the proto-genome without variation. From there, genomes evolved depending on the biological activities they generated in response to environmental fluctuations. Thus, a genome maintaining homeostasis (i.e., internal physicochemical parameter equilibria), despite and in response to environmental fluctuations, maintains its physicochemical integrity and has therefore a higher probability to be reproduced without variation. Consequently, descendants have a higher probability to share the same phenotype than their parents. Otherwise, the genome is modified during replication as a consequence of the imbalance of the internal physicochemical parameters it generates, until new mutation-deriving biological activities maintain homeostasis in offspring. In summary, evolution depends on feedforward and feedback loops between genome and phenotype, as the internal physicochemical conditions that a genome generates ─ through its derived phenotype in response to environmental fluctuations ─ in turn either guarantee its stability or direct its variation. Evolution may not be explained by the Darwinism-derived, unidirectional principle (random mutations-phenotypes-natural selection) but rather by the bidirectional relationship between genome and phenotype, in which the phenotype in interaction with the environment directs the evolution of the genome it derives from.

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.

Preferential CEBP binding to T:G mismatches and increased C-to-T human somatic mutations

DNA cytosine methylation in mammals modulates gene expression and chromatin accessibility. It also impacts mutation rates, via spontaneous oxidative deamination of 5-methylcytosine (5mC) to thymine. In most cases the resulting T:G mismatches are repaired, following T excision by one of the thymine DNA glycosylases, TDG or MBD4. We found that C-to-T mutations are enriched in the binding sites of CCAAT/enhancer binding proteins (CEBP). Within a CEBP site, the presence of a T:G mismatch increased CEBPβ binding affinity by a factor of >60 relative to the normal C:G base pair. This enhanced binding to a mismatch inhibits its repair by both TDG and MBD4 in vitro. Furthermore, repair of the deamination product of unmethylated cytosine, which yields a U:G DNA mismatch that is normally repaired via uracil DNA glycosylase, is also inhibited by CEBPβ binding. Passage of a replication fork over either a T:G or U:G mismatch, before repair can occur, results in a C-to-T mutation in one of the daughter duplexes. Our study thus provides a plausible mechanism for accumulation of C-to-T human somatic mutations.

Functional and genetic determinants of mutation rate variability in regulatory elements of cancer genomes

Background

Cancer genomes are shaped by mutational processes with complex spatial variation at multiple scales. Entire classes of regulatory elements are affected by local variations in mutation frequency. However, the underlying mechanisms with functional and genetic determinants remain poorly understood.

Results

We characterise the mutational landscape of 1.3 million gene-regulatory and chromatin architectural elements in 2419 whole cancer genomes with transcriptional and pathway activity, functional conservation and recurrent driver events. We develop RM2, a statistical model that quantifies mutational enrichment or depletion in classes of genomic elements through genetic, trinucleotide and megabase-scale effects. We report a map of localised mutational processes affecting CTCF binding sites, transcription start sites (TSS) and tissue-specific open-chromatin regions. Increased mutation frequency in TSSs associates with mRNA abundance in most cancer types, while open-chromatin regions are generally enriched in mutations. We identify ~ 10,000 CTCF binding sites with core DNA motifs and constitutive binding in 66 cell types that represent focal points of mutagenesis. We detect site-specific mutational signature enrichments, such as SBS40 in open-chromatin regions in prostate cancer and SBS17b in CTCF binding sites in gastrointestinal cancers. Candidate drivers of localised mutagenesis are also apparent: BRAF mutations associate with mutational enrichments at CTCF binding sites in melanoma, and ARID1A mutations with TSS-specific mutagenesis in pancreatic cancer.

Conclusions

Our method and catalogue of localised mutational processes provide novel perspectives to cancer genome evolution, mutagenesis, DNA repair and driver gene discovery. The functional and genetic correlates of mutational processes suggest mechanistic hypotheses for future studies.

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?'

Molecular Mechanisms of Oncogenesis through the Lens of Nucleosomes and Histones

At the cellular level, cancer is the disease of both the genome and the epigenome, and the interplay between genetic mutations and epigenetic states may occur at the level of elementary chromatin units, the nucleosomes. They are formed by a segment of DNA wrapped around an octamer of histone proteins. In this review, we survey various mechanisms of cancer etiology and progression mediated by histones and nucleosomes. In particular, we discuss the effects of mutations in histones, changes in their expression and slicing on epigenetic dysregulation and carcinogenesis. The links between cancer phenotypes and differential expression of histone variants and isoforms are summarized. Finally, we discourse the geometric and steric effects of DNA compaction in nucleosomes on DNA mutation rate, interactions with transcription factors, including pioneer transcription factors, and prospects of cancer cells' genome and epigenome editing.

Cancer mutational signatures representation by large-scale context embedding

Motivation

The accumulation of somatic mutations plays critical roles in cancer development and progression. However, the global patterns of somatic mutations, especially non-coding mutations, and their roles in defining molecular subtypes of cancer have not been well characterized due to the computational challenges in analysing the complex mutational patterns.

Results

Here, we develop a new algorithm, called MutSpace, to effectively extract patient-specific mutational features using an embedding framework for larger sequence context. Our method is motivated by the observation that the mutation rate at megabase scale and the local mutational patterns jointly contribute to distinguishing cancer subtypes, both of which can be simultaneously captured by MutSpace. Simulation evaluations show that MutSpace can effectively characterize mutational features from known patient subgroups and achieve superior performance compared with previous methods. As a proof-of-principle, we apply MutSpace to 560 breast cancer patient samples and demonstrate that our method achieves high accuracy in subtype identification. In addition, the learned embeddings from MutSpace reflect intrinsic patterns of breast cancer subtypes and other features of genome structure and function. MutSpace is a promising new framework to better understand cancer heterogeneity based on somatic mutations.

Availability and implementation

Source code of MutSpace can be accessed at: https://github.com/ma-compbio/MutSpace.

Supplementary information

Supplementary data are available at Bioinformatics online.

Exons and introns exhibit transcriptional strand asymmetry of dinucleotide distribution, damage formation and DNA repair

Recent cancer sequencing efforts have uncovered asymmetry in DNA damage induced mutagenesis between the transcribed and non-transcribed strands of genes. Here, we investigate the major type of damage induced by ultraviolet (UV) radiation, the cyclobutane pyrimidine dimers (CPDs), which are formed primarily in TT dinucleotides. We reveal that a transcriptional asymmetry already exists at the level of TT dinucleotide frequency and therefore also in CPD damage formation. This asymmetry is conserved in vertebrates and invertebrates and is completely reversed between introns and exons. We show the asymmetry in introns is linked to the transcription process itself, and is also found in enhancer elements. In contrast, the asymmetry in exons is not correlated to transcription, and is associated with codon usage preferences. Reanalysis of nucleotide excision repair, normalizing repair to the underlying TT frequencies, we show repair of CPDs is more efficient in exons compared to introns, contributing to the maintenance and integrity of coding regions. Our results highlight the importance of considering the primary sequence of the DNA in determining DNA damage sensitivity and mutagenic potential.

Comprehensive analysis of cancer breakpoints reveals signatures of genetic and epigenetic contribution to cancer genome rearrangements

Understanding mechanisms of cancer breakpoint mutagenesis is a difficult task and predictive models of cancer breakpoint formation have to this time failed to achieve even moderate predictive power. Here we take advantage of a machine learning approach that can gather important features from big data and quantify contribution of different factors. We performed comprehensive analysis of almost 630,000 cancer breakpoints and quantified the contribution of genomic and epigenomic features-non-B DNA structures, chromatin organization, transcription factor binding sites and epigenetic markers. The results showed that transcription and formation of non-B DNA structures are two major processes responsible for cancer genome fragility. Epigenetic factors, such as chromatin organization in TADs, open/closed regions, DNA methylation, histone marks are less informative but do make their contribution. As a general trend, individual features inside the groups show a relatively high contribution of G-quadruplexes and repeats and CTCF, GABPA, RXRA, SP1, MAX and NR2F2 transcription factors. Overall, the cancer breakpoint landscape can be represented by well-predicted hotspots and poorly predicted individual breakpoints scattered across genomes. We demonstrated that hotspot mutagenesis has genomic and epigenomic factors, and not all individual cancer breakpoints are just random noise but have a definite mutation signature. Besides we found a long-range action of some features on breakpoint mutagenesis. Combining omics data, cancer-specific individual feature importance and adding the distant to local features, predictive models for cancer breakpoint formation achieved 70-90% ROC AUC for different cancer types; however precision remained low at 2% and the recall did not exceed 50%. On the one hand, the power of models strongly correlates with the size of available cancer breakpoint and epigenomic data, and on the other hand finding strong determinants of cancer breakpoint formation still remains a challenge. The strength of predictive signals of each group and of each feature inside a group can be converted into cancer-specific breakpoint mutation signatures. Overall our results add to the understanding of cancer genome rearrangement processes.

Determinants of genome-wide distribution and evolution of uORFs in eukaryotes

Upstream open reading frames (uORFs) play widespread regulatory functions in modulating mRNA translation in eukaryotes, but the principles underlying the genomic distribution and evolution of uORFs remain poorly understood. Here, we analyze ~17 million putative canonical uORFs in 478 eukaryotic species that span most of the extant taxa of eukaryotes. We demonstrate how positive and purifying selection, coupled with differences in effective population size (Ne), has shaped the contents of uORFs in eukaryotes. Besides, gene expression level is important in influencing uORF occurrences across genes in a species. Our analyses suggest that most uORFs might play regulatory roles rather than encode functional peptides. We also show that the Kozak sequence context of uORFs has evolved across eukaryotic clades, and that noncanonical uORFs tend to have weaker suppressive effects than canonical uORFs in translation regulation. This study provides insights into the driving forces underlying uORF evolution in eukaryotes.

Mutational processes in cancer preferentially affect binding of particular transcription factors

Protein binding microarrays provide comprehensive information about the DNA binding specificities of transcription factors (TFs), and can be used to quantitatively predict the effects of DNA sequence variation on TF binding. There has also been substantial progress in dissecting the patterns of mutations, i.e., the "mutational signatures", generated by different mutational processes. By combining these two layers of information we can investigate whether certain mutational processes tend to preferentially affect binding of particular classes of TFs. Such preferential alterations of binding might predispose to particular oncogenic pathways. We developed and implemented a method, termed "Signature-QBiC", that integrates protein binding microarray data with the signatures of mutational processes, with the aim of predicting which TFs’ binding profiles are preferentially perturbed by particular mutational processes. We used Signature-QBiC to predict the effects of 47 signatures of mutational processes on 582 human TFs. Pathway analysis showed that binding of TFs involved in NOTCH1 signaling is strongly affected by the signatures of several mutational processes, including exposure to ultraviolet radiation. Additionally, toll-like-receptor signaling pathways are also vulnerable to disruption by this exposure. This study provides a novel overview of the effects of mutational processes on TF binding and the potential of these processes to activate oncogenic pathways through mutating TF binding sites.

Variable interplay of UV-induced DNA damage and repair at transcription factor binding sites

An abnormally high rate of UV-light related mutations appears at transcription factor binding sites (TFBS) across melanomas. The binding of transcription factors (TFs) to the DNA impairs the repair of UV-induced lesions and certain TFs have been shown to increase the rate of generation of these lesions at their binding sites. However, the precise contribution of these two elements to the increase in mutation rate at TFBS in these malignant cells is not understood. Here, exploiting nucleotide-resolution data, we computed the rate of formation and repair of UV-lesions within the binding sites of TFs of different families. We observed, at certain dipyrimidine positions within the binding site of TFs in the Tryptophan Cluster family, an increased rate of formation of UV-induced lesions, corroborating previous studies. Nevertheless, across most families of TFs, the observed increased mutation rate within the entire DNA region covered by the protein results from the decreased repair efficiency. While the rate of mutations across all TFBS does not agree with the amount of UV-induced lesions observed immediately after UV exposure, it strongly agrees with that observed after 48 h. This corroborates the determinant role of the impaired repair in the observed increase of mutation rate.

Heritable pattern of oxidized DNA base repair coincides with pre-targeting of repair complexes to open chromatin

Human genome stability requires efficient repair of oxidized bases, which is initiated via damage recognition and excision by NEIL1 and other base excision repair (BER) pathway DNA glycosylases (DGs). However, the biological mechanisms underlying detection of damaged bases among the million-fold excess of undamaged bases remain enigmatic. Indeed, mutation rates vary greatly within individual genomes, and lesion recognition by purified DGs in the chromatin context is inefficient. Employing super-resolution microscopy and co-immunoprecipitation assays, we find that acetylated NEIL1 (AcNEIL1), but not its non-acetylated form, is predominantly localized in the nucleus in association with epigenetic marks of uncondensed chromatin. Furthermore, chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) revealed non-random AcNEIL1 binding near transcription start sites of weakly transcribed genes and along highly transcribed chromatin domains. Bioinformatic analyses revealed a striking correspondence between AcNEIL1 occupancy along the genome and mutation rates, with AcNEIL1-occupied sites exhibiting fewer mutations compared to AcNEIL1-free domains, both in cancer genomes and in population variation. Intriguingly, from the evolutionarily conserved unstructured domain that targets NEIL1 to open chromatin, its damage surveillance of highly oxidation-susceptible sites to preserve essential gene function and to limit instability and cancer likely originated ∼500 million years ago during the buildup of free atmospheric oxygen.

Use of signals of positive and negative selection to distinguish cancer genes and passenger genes

A major goal of cancer genomics is to identify all genes that play critical roles in carcinogenesis. Most approaches focused on genes positively selected for mutations that drive carcinogenesis and neglected the role of negative selection. Some studies have actually concluded that negative selection has no role in cancer evolution. We have re-examined the role of negative selection in tumor evolution through the analysis of the patterns of somatic mutations affecting the coding sequences of human genes. Our analyses have confirmed that tumor suppressor genes are positively selected for inactivating mutations, oncogenes, however, were found to display signals of both negative selection for inactivating mutations and positive selection for activating mutations. Significantly, we have identified numerous human genes that show signs of strong negative selection during tumor evolution, suggesting that their functional integrity is essential for the growth and survival of tumor cells.

Super hotspots and super coldspots in the repair of UV-induced DNA damage in the human genome

The formation of UV-induced DNA damage and its repair are influenced by many factors that modulate lesion formation and the accessibility of repair machinery. However, it remains unknown which genomic sites are prioritized for immediate repair after UV damage induction, and whether these prioritized sites overlap with hotspots of UV damage. We identified the super hotspots subject to the earliest repair for (6-4) pyrimidine-pyrimidone photoproduct by using the eXcision Repair-sequencing (XR-seq) method. We further identified super coldspots for (6-4) pyrimidine-pyrimidone photoproduct repair and super hotspots for cyclobutane pyrimidine dimer repair by analyzing available XR-seq time-course data. By integrating datasets of XR-seq, Damage-seq, adductSeq, and cyclobutane pyrimidine dimer-seq, we show that neither repair super hotspots nor repair super coldspots overlap hotspots of UV damage. Furthermore, we demonstrate that repair super hotspots are significantly enriched in frequently interacting regions and superenhancers. Finally, we report our discovery of an enrichment of cytosine in repair super hotspots and super coldspots. These findings suggest that local DNA features together with large-scale chromatin features contribute to the orders of magnitude variability in the rates of UV damage repair.

The evolution of relapse of adult T cell acute lymphoblastic leukemia

BACKGROUND

Adult T cell acute lymphoblastic leukemia (T-ALL) is a rare disease that affects less than 10 individuals in one million. It has been less studied than its cognate pediatric malignancy, which is more prevalent. A higher percentage of the adult patients relapse, compared to children. It is thus essential to study the mechanisms of relapse of adult T-ALL cases.

RESULTS

We profile whole-genome somatic mutations of 19 primary T-ALLs from adult patients and the corresponding relapse malignancies and analyze their evolution upon treatment in comparison with 238 pediatric and young adult ALL cases. We compare the mutational processes and driver mutations active in primary and relapse adult T-ALLs with those of pediatric patients. A precise estimation of clock-like mutations in leukemic cells shows that the emergence of the relapse clone occurs several months before the diagnosis of the primary T-ALL. Specifically, through the doubling time of the leukemic population, we find that in at least 14 out of the 19 patients, the population of relapse leukemia present at the moment of diagnosis comprises more than one but fewer than 108 blasts. Using simulations, we show that in all patients the relapse appears to be driven by genetic mutations.

CONCLUSIONS

The early appearance of a population of leukemic cells with genetic mechanisms of resistance across adult T-ALL cases constitutes a challenge for treatment. Improving early detection of the malignancy is thus key to prevent its relapse.

Higher Germline Mutagenesis of Genes with Stronger Testis Expressions Refutes the Transcriptional Scanning Hypothesis

Why are more genes expressed in the testis than in any other organ in mammals? The recently proposed transcriptional scanning hypothesis posits that transcription alleviates mutagenesis through transcription-coupled repair so has been selected in the testis to modulate the germline mutation rate in a gene-specific manner. Here, we show that this hypothesis is theoretically untenable because the selection would be too weak to have an effect in mammals. Furthermore, the analysis purported to support the hypothesis did not control known confounding factors and inappropriately excluded genes with no observed de novo mutations. After remedying these problems, we find the human germline mutation rate of a gene to rise with its testis expression level. This trend also exists for inferred coding strand-originated mutations, suggesting that it arises from transcription-associated mutagenesis. Furthermore, the testis expression level of a gene robustly correlates with its overall expression in other organs, nullifying the need to explain the testis silencing of a minority of genes by adaptive germline mutagenesis. Taken together, our results demonstrate that human testis transcription increases the germline mutation rate, rejecting the transcriptional scanning hypothesis of extensive gene expressions in the mammalian testis.

Pan-cancer analysis of somatic mutations in miRNA genes

Background

miRNAs are considered important players in oncogenesis, serving either as oncomiRs or suppressormiRs. Although the accumulation of somatic alterations is an intrinsic aspect of cancer development and many important cancer-driving mutations have been identified in protein-coding genes, the area of functional somatic mutations in miRNA genes is heavily understudied.

Methods

Here, based on the analysis of large genomic datasets, mostly the whole-exome sequencing of over 10,000 cancer/normal sample pairs deposited within the TCGA repository, we undertook an analysis of somatic mutations in miRNA genes.

Findings

We identified and characterized over 10,000 somatic mutations and showed that some of the miRNA genes are overmutated in Pan-Cancer and/or specific cancers. Nonrandom occurrence of the identified mutations was confirmed by a strong association of overmutated miRNA genes with KEGG pathways, most of which were related to specific cancer types or cancer-related processes. Additionally, we showed that mutations in some of the overmutated genes correlate with miRNA expression, cancer staging, and patient survival.

Interpretation

Our study is the first comprehensive Pan-Cancer study of cancer somatic mutations in miRNA genes. It may help to understand the consequences of mutations in miRNA genes and the identification of miRNA functional mutations. The results may also be the first step (form the basis and provide the resources) in the development of computational and/or statistical approaches/tools dedicated to the identification of cancer-driver miRNA genes.

Funding

This work was supported by research grants from the Polish National Science Centre 2016/22/A/NZ2/00184 and 2015/17/N/NZ3/03629.

Genomic Chaos Begets Psychiatric Disorder

The processes that created the primordial genome are inextricably linked to current day vulnerability to developing a psychiatric disorder as summarized in this review article. Chaos and dynamic forces including duplication, transposition, and recombination generated the protogenome. To survive early stages of genome evolution, self-organization emerged to curb chaos. Eventually, the human genome evolved through a delicate balance of chaos/instability and organization/stability. However, recombination coldspots, silencing of transposable elements, and other measures to limit chaos also led to retention of variants that increase risk for disease. Moreover, ongoing dynamics in the genome creates various new mutations that determine liability for psychiatric disorders. Homologous recombination, long-range gene regulation, and gene interactions were all guided by spooky action-at-a-distance, which increased variability in the system. A probabilistic system of life was required to deal with a changing environment. This ensured the generation of outliers in the population, which enhanced the probability that some members would survive unfavorable environmental impacts. Some of the outliers produced through this process in man are ill suited to cope with the complex demands of modern life. Genomic chaos and mental distress from the psychological challenges of modern living will inevitably converge to produce psychiatric disorders in man.

A compendium of mutational cancer driver genes

A fundamental goal in cancer research is to understand the mechanisms of cell transformation. This is key to developing more efficient cancer detection methods and therapeutic approaches. One milestone towards this objective is the identification of all the genes with mutations capable of driving tumours. Since the 1970s, the list of cancer genes has been growing steadily. Because cancer driver genes are under positive selection in tumorigenesis, their observed patterns of somatic mutations across tumours in a cohort deviate from those expected from neutral mutagenesis. These deviations, which constitute signals of positive selection, may be detected by carefully designed bioinformatics methods, which have become the state of the art in the identification of driver genes. A systematic approach combining several of these signals could lead to a compendium of mutational cancer genes. In this Review, we present the Integrative OncoGenomics (IntOGen) pipeline, an implementation of such an approach to obtain the compendium of mutational cancer drivers. Its application to somatic mutations of more than 28,000 tumours of 66 cancer types reveals 568 cancer genes and points towards their mechanisms of tumorigenesis. The application of this approach to the ever-growing datasets of somatic tumour mutations will support the continuous refinement of our knowledge of the genetic basis of cancer.

The road ahead in genetics and genomics

In celebration of the 20th anniversary of Nature Reviews Genetics, we asked 12 leading researchers to reflect on the key challenges and opportunities faced by the field of genetics and genomics. Keeping their particular research area in mind, they take stock of the current state of play and emphasize the work that remains to be done over the next few years so that, ultimately, the benefits of genetic and genomic research can be felt by everyone.

To celebrate the first 20 years of Nature Reviews Genetics, we asked 12 leading scientists to reflect on the key challenges and opportunities faced by the field of genetics and genomics.

Amy L. McGuire is the Leon Jaworski Professor of Biomedical Ethics and Director of the Center for Medical Ethics and Health Policy at Baylor College of Medicine. She has received numerous teaching awards at Baylor College of Medicine, was recognized by the Texas Executive Women as a Woman on the Move in 2016 and was invited to give a TedMed talk titled “There is No Genome for the Human Spirit” in 2014. In 2020, she was elected as a Hastings Center Fellow. Her research focuses on ethical and policy issues related to emerging technologies, with a particular focus on genomic research, personalized medicine and the clinical integration of novel neurotechnologies.

Stacey Gabriel is the Senior Director of the Genomics Platform at the Broad Institute since 2012 and has led platform development, execution and operation since its founding. She is Chair of Institute Scientists and serves on the institute’s executive leadership team. She is widely recognized as a leader in genomic technology and project execution. She has led the Broad’s contributions to numerous flagship projects in human genetics, including the International HapMap Project, the 1000 Genomes Project, The Cancer Genome Atlas, the National Heart, Lung, and Blood Institute’s Exome Sequencing Project and the TOPMed programme. She is Principal Investigator of the Broad’s All of Us (AoU) Genomics Center and serves on the AoU Program Steering Committee.

Sarah A. Tishkoff is the David and Lyn Silfen University Associate Professor in Genetics and Biology at the University of Pennsylvania, Philadelphia, USA, and holds appointments in the School of Medicine and the School of Arts and Sciences. She is a member of the US National Academy of Sciences and a recipient of an NIH Pioneer Award, a David and Lucile Packard Career Award, a Burroughs/Wellcome Fund Career Award and an American Society of Human Genetics Curt Stern Award. Her work focuses on genomic variation in Africa, human evolutionary history, the genetic basis of adaptation and phenotypic variation in Africa, and the genetic basis of susceptibility to infectious disease in Africa.

Ambroise Wonkam is Professor of Medical Genetics, Director of GeneMAP (Genetic Medicine of African Populations Research Centre) and Deputy Dean Research in the Faculty of Health Sciences, University of Cape Town, South Africa. He has successfully led numerous NIH- and Wellcome Trust-funded projects over the past decade to investigate clinical variability in sickle cell disease, hearing impairment genetics and the return of individual findings in genetic research in Africa. He won the competitive Clinical Genetics Society International Award for 2014 from the British Society of Genetic Medicine. He is president of the African Society of Human Genetics.

Aravinda Chakravarti is Director of the Center for Human Genetics and Genomics, the Muriel G. and George W. Singer Professor of Neuroscience and Physiology, and Professor of Medicine at New York University School of Medicine. He is an elected member of the US National Academy of Sciences, the US National Academy of Medicine and the Indian National Science Academy. He has been a key participant in the Human Genome Project, the International HapMap Project and the 1000 Genomes Project. His research attempts to understand the molecular basis of multifactorial disease. He was awarded the 2013 William Allan Award by the American Society of Human Genetics and the 2018 Chen Award by the Human Genome Organization.

Eileen E. M. Furlong is Head of the Genome Biology Department at the European Molecular Biology Laboratory (EMBL) and a member of the EMBL Directorate. She is an elected member of the European Molecular Biology Organization (EMBO) and the Academia Europaea, and a European Research Council (ERC) advanced investigator. Her group dissects fundamental principles of how the genome is regulated and how it drives cell fate decisions during embryonic development, including how developmental enhancers are organized and function within the 3D nucleus. Her work combines genetics, (single-cell) genomics, imaging and computational approaches to understand these processes. Her research has advanced the development of genomic methods for use in complex multicellular organisms.

Barbara Treutlein is Associate Professor of Quantitative Developmental Biology in the Department of Biosystems Science and Engineering of ETH Zurich in Basel, Switzerland. Her group uses and develops single-cell genomics approaches in combination with stem cell-based 2D and 3D culture systems to study how human organs develop and regenerate and how cell fate is regulated. For her work, Barbara has received multiple awards, including the Friedmund Neumann Prize of the Schering Foundation, the Dr. Susan Lim Award for Outstanding Young Investigator of the International Society of Stem Cell Research and the EMBO Young Investigator Award.

Alexander Meissner is a scientific member of the Max Planck Society and currently Managing Director of the Max Planck Institute (MPI) for Molecular Genetics in Berlin, Germany. He heads the Department of Genome Regulation and is a visiting scientist in the Department of Stem Cell and Regenerative Biology at Harvard University. Before his move to the MPI, he was a tenured professor at Harvard University and a senior associate member of the Broad Institute, where he co-directed the epigenomics programme. In 2018, he was elected as an EMBO member. His laboratory uses genomic tools to study developmental and disease biology with a particular focus on epigenetic regulation.

Howard Y. Chang is the Virginia and D. K. Ludwig Professor of Cancer Genomics at Stanford University and an investigator at the Howard Hughes Medical Institute. He is a physician–scientist who has focused on deciphering the hidden information in the non-coding genome. His laboratory is best known for studies of long non-coding RNAs in gene regulation and development of new epigenomic technologies. He is an elected member of the US National Academy of Sciences, the US National Academy of Medicine, and the American Academy of Arts and Sciences.

Núria López-Bigas is ICREA research Professor at the Institute for Research in Biomedicine and Associate Professor at the University Pompeu Fabra. She obtained an ERC Consolidator Grant in 2015 and was elected as an EMBO member in 2016. Her work has been recognized with the prestigious Banc de Sabadell Award for Research in Biomedicine, the Catalan National Award for Young Research Talent and the Career Development Award from the Human Frontier Science Program. Her research focuses on the identification of cancer driver mutations, genes and pathways across tumour types and in understanding the mutational processes that lead to the accumulation of mutations in cancer cells.

Eran Segal is Professor in the Department of Computer Science and Applied Mathematics at the Weizmann Institute of Science, heading a multidisciplinary laboratory with extensive experience in machine learning, computational biology and analysis of heterogeneous high-throughput genomic data. His research focuses on the microbiome, nutrition and genetics, and their effect on health and disease and aims to develop personalized medicine based on big data from human cohorts. He has published more than 150 publications and received several awards and honours for his work, including the Overton and the Michael Bruno awards. He was recently elected as an EMBO member and as a member of the Israel Young Academy.

Jin-Soo Kim is Director of the Center for Genome Engineering in the Institute for Basic Science in Daejon, South Korea. He has received numerous awards, including the 2017 Asan Award in Medicine, the 2017 Yumin Award in Science and the 2019 Research Excellence Award (Federation of Asian and Oceanian Biochemists and Molecular Biologists). He was featured as one of ten Science Stars of East Asia in Nature (558, 502–510 (2018)) and has been recognized as a highly cited researcher by Clarivate Analytics since 2018. His work focuses on developing tools for genome editing in biomedical research.

Prostate cancer reactivates developmental epigenomic programs during metastatic progression

Epigenetic processes govern prostate cancer (PCa) biology, as evidenced by the dependency of PCa cells on the androgen receptor (AR), a prostate master transcription factor. We generated 268 epigenomic datasets spanning two state transitions-from normal prostate epithelium to localized PCa to metastases-in specimens derived from human tissue. We discovered that reprogrammed AR sites in metastatic PCa are not created de novo; rather, they are prepopulated by the transcription factors FOXA1 and HOXB13 in normal prostate epithelium. Reprogrammed regulatory elements commissioned in metastatic disease hijack latent developmental programs, accessing sites that are implicated in prostate organogenesis. Analysis of reactivated regulatory elements enabled the identification and functional validation of previously unknown metastasis-specific enhancers at HOXB13, FOXA1 and NKX3-1. Finally, we observed that prostate lineage-specific regulatory elements were strongly associated with PCa risk heritability and somatic mutation density. Examining prostate biology through an epigenomic lens is fundamental for understanding the mechanisms underlying tumor progression.

Functional and genetic determinants of mutation rate variability in regulatory elements of cancer genomes.. [DOI: 10.1101/2020.07.29.226373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Background

Cancer genomes are shaped by mutational processes with complex spatial variation at multiple scales. Entire classes of regulatory elements are affected by local variations in mutation frequency. However, the underlying mutational mechanisms with functional and genetic determinants remain poorly understood.

Results

We characterised the mutational landscape of 1.3 million gene regulatory and chromatin architectural elements in 2,419 whole cancer genomes with transcriptional and pathway activity, functional conservation and recurrent driver events. We developed RM2, a statistical model that quantifies mutational enrichment or depletion in classes of genomic elements through genetic, trinucleotide and megabase-scale effects. We report a map of localised mutational processes affecting CTCF binding sites, transcription start sites (TSS) and tissue-specific open-chromatin regions. We show that increased mutational frequency in TSSs correlates with mRNA abundance in most cancer types, while open-chromatin regions are generally enriched in mutations. We identified ∼10,000 CTCF binding sites with core DNA motifs and constitutive binding in 66 cell types that represent focal points of local mutagenesis. We detected site-specific mutational signatures, such as SBS40 in open-chromatin regions in prostate cancer and SBS17b in CTCF binding sites in gastrointestinal cancers. We also proposed candidate drivers of localised mutagenesis: BRAF mutations associate with mutational enrichments at CTCF binding sites in melanoma, and ARID1A mutations with TSS-specific mutations in pancreatic cancer.

Conclusions

Our method and catalogue of localised mutational processes provide novel perspectives to cancer genome evolution, mutagenesis, DNA repair and driver discovery. Functional and genetic correlates of localised mutagenesis provide mechanistic hypotheses for future studies.

Genome-Wide Somatic Alterations in Multiple Myeloma Reveal a Superior Outcome Group

PURPOSE

Multiple myeloma (MM) is accompanied by heterogeneous somatic alterations. The overall goal of this study was to describe the genomic landscape of myeloma using deep whole-genome sequencing (WGS) and develop a model that identifies patients with long survival.

METHODS

We analyzed deep WGS data from 183 newly diagnosed patients with MM treated with lenalidomide, bortezomib, and dexamethasone (RVD) alone or RVD + autologous stem cell transplant (ASCT) in the IFM/DFCI 2009 study (ClinicalTrials.gov identifier: NCT01191060). We integrated genomic markers with clinical data.

RESULTS

We report significant variability in mutational load and processes within MM subgroups. The timeline of observed activation of mutational processes provides the basis for 2 distinct models of acquisition of mutational changes detected at the time of diagnosis of myeloma. Virtually all MM subgroups have activated DNA repair-associated signature as a prominent late mutational process, whereas APOBEC signature targeting C>G is activated in the intermediate phase of disease progression in high-risk MM. Importantly, we identify a genomically defined MM subgroup (17% of newly diagnosed patients) with low DNA damage (low genomic scar score with chromosome 9 gain) and a superior outcome (100% overall survival at 69 months), which was validated in a large independent cohort. This subgroup allowed us to distinguish patients with low- and high-risk hyperdiploid MM and identify patients with prolongation of progression-free survival. Genomic characteristics of this subgroup included lower mutational load with significant contribution from age-related mutations as well as frequent NRAS mutation. Surprisingly, their overall survival was independent of International Staging System and minimal residual disease status.

CONCLUSION

This is a comprehensive study identifying genomic markers of a good-risk group with prolonged survival. Identification of this patient subgroup will affect future therapeutic algorithms and research planning.

Human genes differ by their UV sensitivity estimated through analysis of UV-induced silent mutations in melanoma

We hypothesized that human genes differ by their sensitivity to ultraviolet (UV) exposure. We used somatic mutations detected by genome-wide screens in melanoma and reported in the Catalog Of Somatic Mutations In Cancer. As a measure of UV sensitivity, we used the number of silent mutations generated by C>T transitions in pyrimidine dimers of a given transcript divided by the number of potential sites for this type of mutations in the transcript. We found that human genes varied by UV sensitivity by two orders of magnitude. We noted that the melanoma-associated tumor suppressor gene CDKN2A was among the top five most UV-sensitive genes in the human genome. Melanoma driver genes have a higher UV-sensitivity compared with other genes in the human genome. The difference was more prominent for tumor suppressors compared with oncogene. The results of this study suggest that differential sensitivity of human transcripts to UV light may explain melanoma specificity of some driver genes. Practical significance of the study relates to the fact that differences in UV sensitivity among human genes need to be taken into consideration whereas predicting melanoma-associated genes by the number of somatic mutations detected in a given gene.

Widespread Transcriptional Scanning in the Testis Modulates Gene Evolution Rates

The testis expresses the largest number of genes of any mammalian organ, a finding that has long puzzled molecular biologists. Our single-cell transcriptomic data of human and mouse spermatogenesis provide evidence that this widespread transcription maintains DNA sequence integrity in the male germline by correcting DNA damage through a mechanism we term transcriptional scanning. We find that genes expressed during spermatogenesis display lower mutation rates on the transcribed strand and have low diversity in the population. Moreover, this effect is fine-tuned by the level of gene expression during spermatogenesis. The unexpressed genes, which in our model do not benefit from transcriptional scanning, diverge faster over evolutionary timescales and are enriched for sensory and immune-defense functions. Collectively, we propose that transcriptional scanning shapes germline mutation signatures and modulates mutation rates in a gene-specific manner, maintaining DNA sequence integrity for the bulk of genes but allowing for faster evolution in a specific subset.

Modeling and analysis of site-specific mutations in cancer identifies known plus putative novel hotspots and bias due to contextual sequences

In cancer, recurrently mutated sites in DNA and proteins, called hotspots, are thought to be raised by positive selection and therefore important due to its potential functional impact. Although recent evidence for APOBEC enzymatic activity have shown that specific types of sequences are likely to be false, the identification of putative hotspots is important to confirm either its functional role or its mechanistic bias. In this work, an algorithm and a statistical model is presented to detect hotspots. The model consists of a beta-binomial component plus fixed effects that efficiently fits the distribution of mutated sites. The algorithm employs an optimal stepwise approach to find the model parameters. Simulations show that the proposed algorithmic model is highly accurate for common hotspots. The approach has been applied to TCGA mutational data from 33 cancer types. The results show that well-known cancer hotspots are easily detected. Besides, novel hotspots are also detected. An analysis of the sequence context of detected hotspots show a preference for TCG sites that may be related to APOBEC or other unknown mechanistic biases. The detected hotspots are available online in http://bioinformatica.mty.itesm.mx/HotSpotsAnnotations.

GPSeq reveals the radial organization of chromatin in the cell nucleus

With the exception of lamina-associated domains, the radial organization of chromatin in mammalian cells remains largely unexplored. Here, we describe genomic loci positioning by sequencing (GPSeq), a genome-wide method for inferring distances to the nuclear lamina all along the nuclear radius. GPSeq relies on gradual restriction digestion of chromatin from the nuclear lamina towards the nucleus center, followed by sequencing of the generated cut sites. Using GPSeq, we mapped the radial organization of the human genome at 100 kb resolution, which revealed radial patterns of genomic and epigenomic features, gene expression, as well as A/B subcompartments. By combining radial information with chromosome contact frequencies measured by Hi-C, we substantially improved the accuracy of whole-genome structure modeling. Finally, we charted the radial topography of DNA double-strand breaks, germline variants and cancer mutations, and found that they have distinctive radial arrangements in A/B subcompartments. We conclude that GPSeq can reveal fundamental aspects of genome architecture.

Experimental investigations of carcinogen-induced mutation spectra: Innovation, challenges and future directions

Recent years have witnessed an expansion of mutagenesis research focusing on experimentally modeled genome-scale mutational signatures of carcinogens and of endogenous processes. Experimental mutational signatures can explain etiologic links to patterns found in human tumors that may be linked to same exposures, and can serve as biomarkers of exposure history and may even provide insights on causality. A number of innovative exposure models have been employed and reported, based on cells cultured in monolayers or in 3-D, on organoids, induced pluripotent stem cells, non-mammalian organisms, microorganisms and rodent bioassays. Here we discuss some of the latest developments and pros and cons of these experimental systems used in mutational signature analysis. Integrative designs that bring together multiple exposure systems (in vitro, in vivo and in silico pan-cancer data mining) started emerging as powerful tools to identify robust mutational signatures of the tested cancer risk agents. We further propose that devising a new generation of cell-based models is warranted to streamline systematic testing of carcinogen effects on the cell genomes, while seeking to increasingly supplant animal with non-animal systems to address relevant ethical issues and accentuate the 3R principles. We conclude that the knowledge accumulating from the growing body of signature modelling investigations has considerable power to advance cancer etiology studies and to support cancer prevention efforts through streamlined characterization of cancer-causing agents and the recognition of their specific effects.

Comprehensive analysis of indels in whole-genome microsatellite regions and microsatellite instability across 21 cancer types

Microsatellites are repeats of 1- to 6-bp units, and approximately 10 million microsatellites have been identified across the human genome. Microsatellites are vulnerable to DNA mismatch errors and have thus been used to detect cancers with mismatch repair deficiency. To reveal the mutational landscape of microsatellite repeat regions at the genome level, we analyzed approximately 20.1 billion microsatellites in 2717 whole genomes of pan-cancer samples across 21 tissue types. First, we developed a new insertion and deletion caller (MIMcall) that takes into consideration the error patterns of different types of microsatellites. Among the 2717 pan-cancer samples, our analysis identified 31 samples, including colorectal, uterus, and stomach cancers, with a higher proportion of mutated microsatellite (≥0.03), which we defined as microsatellite instability (MSI) cancers of genome-wide level. Next, we found 20 highly mutated microsatellites that can be used to detect MSI cancers with high sensitivity. Third, we found that replication timing and DNA shape were significantly associated with mutation rates of microsatellites. Last, analysis of mutations in mismatch repair genes showed that somatic SNVs and short indels had larger functional impacts than germline mutations and structural variations. Our analysis provides a comprehensive picture of mutations in the microsatellite regions and reveals possible causes of mutations, as well as provides a useful marker set for MSI detection.

Mutational processes of distinct POLE exonuclease domain mutants drive an enrichment of a specific TP53 mutation in colorectal cancer

Cancer genomes with mutations in the exonuclease domain of Polymerase Epsilon (POLE) present with an extraordinarily high somatic mutation burden. In vitro studies have shown that distinct POLE mutants exhibit different polymerase activity. Yet, genome-wide mutation patterns and driver mutation formation arising from different POLE mutants remains unclear. Here, we curated somatic mutation calls from 7,345 colorectal cancer samples from published studies and publicly available databases. These include 44 POLE mutant samples including 9 with whole genome sequencing data available. The POLE mutant samples were categorized based on the specific POLE mutation present. Mutation spectrum, associations of somatic mutations with epigenomics features and co-occurrence with specific driver mutations were examined across different POLE mutants. We found that different POLE mutants exhibit distinct mutation spectrum with significantly higher relative frequency of C>T mutations in POLE V411L mutants. Our analysis showed that this increase frequency in C>T mutations is not dependent on DNA methylation and not associated with other genomic features and is thus specifically due to DNA sequence context alone. Notably, we found strong association of the TP53 R213* mutation specifically with POLE P286R mutants. This truncation mutation occurs within the TT[C>T]GA context. For C>T mutations, this sequence context is significantly more likely to be mutated in POLE P286R mutants compared with other POLE exonuclease domain mutants. This study refines our understanding of DNA polymerase fidelity and underscores genome-wide mutation spectrum and specific cancer driver mutation formation observed in POLE mutant cancers.

Cancer arises through the accumulation of somatic mutations. The way that these somatic mutations form can vary greatly in different cancers. One of the most mutagenic processes that have been identified is caused by mutations within a replicative DNA polymerase known as Polymerase Epsilon (POLE). Cancers with such mutations present with hundreds of thousands of somatic mutations in their genome. Previous cancer genomics studies have identified a number of mutation hotspots in POLE, however how these different POLE mutants behave in affecting mutation distribution has not been studied. Here, we describe the genome-wide mutation profiles of distinct POLE mutant cancers. We find that different mutants indeed result in different mutation profiles and that this can be explained by the different fidelities of these mutants in replicating specific DNA sequences. Significantly, these differences have important implications in cancer formation as we found that a POLE mutation is strongly associated with a specific truncation of the TP53 cancer driver gene. This study furthers our understanding of the POLE mutagenic process in cancer and provide important insights into carcinogenesis in cancers with such mutations.

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.

Candidate Cancer Driver Mutations in Distal Regulatory Elements and Long-Range Chromatin Interaction Networks

A comprehensive catalog of cancer driver mutations is essential for understanding tumorigenesis and developing therapies. Exome-sequencing studies have mapped many protein-coding drivers, yet few non-coding drivers are known because genome-wide discovery is challenging. We developed a driver discovery method, ActiveDriverWGS, and analyzed 120,788 cis-regulatory modules (CRMs) across 1,844 whole tumor genomes from the ICGC-TCGA PCAWG project. We found 30 CRMs with enriched SNVs and indels (FDR < 0.05). These frequently mutated regulatory elements (FMREs) were ubiquitously active in human tissues, showed long-range chromatin interactions and mRNA abundance associations with target genes, and were enriched in motif-rewiring mutations and structural variants. Genomic deletion of one FMRE in human cells caused proliferative deficiencies and transcriptional deregulation of cancer genes CCNB1IP1, CDH1, and CDKN2B, validating observations in FMRE-mutated tumors. Pathway analysis revealed further sub-significant FMREs at cancer genes and processes, indicating an unexplored landscape of infrequent driver mutations in the non-coding genome.

Pan-cancer analysis of somatic mutations and epigenetic alterations in insulated neighbourhood boundaries

Recent evidence shows that the disruption of constitutive insulated neighbourhoods might lead to oncogene dysregulation. We present here a systematic pan-cancer characterisation of the associations between constitutive boundaries and genome alterations in cancer. Specifically, we investigate the enrichment of somatic mutation, abnormal methylation, and copy number alteration events in the proximity of CTCF bindings overlapping with topological boundaries (junctions) in 26 cancer types. Focusing on CTCF motifs that are both in-boundary (overlapping with junctions) and active (overlapping with peaks of CTCF expression), we find a significant enrichment of somatic mutations in several cancer types. Furthermore, mutated junctions are significantly conserved across cancer types, and we also observe a positive selection of transversions rather than transitions in many cancer types. We also analyzed the mutational signature found on the different classes of CTCF motifs, finding some signatures (such as SBS26) to have a higher weight within in-boundary than off-bounday motifs. Regarding methylation, we find a significant number of over-methylated active in-boundary CTCF motifs in several cancer types; similarly to somatic-mutated junctions, they also have a significant conservation across cancer types. Finally, in several cancer types we observe that copy number alterations tend to overlap with active junctions more often than in matched normal samples. While several articles have recently reported a mutational enrichment at CTCF binding sites for specific cancer types, our analysis is pan-cancer and investigates abnormal methylation and copy number alterations in addition to somatic mutations. Our method is fully replicable and suggests several follow-up tumour-specific analyses.