Methylated Bases Research Articles

Detecting m6A RNA modification from nanopore sequencing using a semisupervised learning framework.

Direct nanopore-based RNA sequencing can be used to detect posttranscriptional base modifications, such as N6-methyladenosine (m6A) methylation, based on the electric current signals produced by the distinct chemical structures of modified bases. A key challenge is the scarcity of adequate training data with known methylation modifications. We present Xron, a hybrid encoder-decoder framework that delivers a direct methylation-distinguishing basecaller by training on synthetic RNA data and immunoprecipitation (IP)-based experimental data in two steps. First, we generate data with more diverse modification combinations through in silico cross-linking. Second, we use this data set to train an end-to-end neural network basecaller followed by fine-tuning on IP-based experimental data with label smoothing. The trained neural network basecaller outperforms existing methylation detection methods on both read-level and site-level prediction scores. Xron is a standalone, end-to-end m6A-distinguishing basecaller capable of detecting methylated bases directly from raw sequencing signals, enabling de novo methylome assembly.

Chromosome-level genome assembly of the morabine grasshopper Vandiemenella viatica19

Morabine grasshoppers in the Vandiemenella viatica species group, which show karyotype diversity, have been studied for their ecological distribution and speciation in relation to their genetic and chromosomal diversity. They are good models for studying sex chromosome evolution as “old” and newly emerged sex chromosomes co-exist within the group. Here we present a reference genome for the viatica19 chromosomal race, that possesses the ancestral karyotype within the group. Using PacBio HiFi and Hi-C sequencing, we generated a chromosome-level assembly of 4.09 Gb in span, scaffold N50 of 429 Mb, and complete BUSCO score of 98.1%, containing 10 pseudo-chromosomes. We provide Illumina datasets of males and females, used to identify the X chromosome. The assembly contains 19,034 predicted protein-coding genes, and a total of 75.21% of repetitive DNA sequences. By leveraging HiFi reads, we mapped the genome-wide distribution of methylated bases (5mC and 6 mA). This comprehensive assembly offers a robust reference for morabine grasshoppers and supports further research into speciation and sex chromosome diversification within the group and its related species.

Decoding chromosome organization using CheC-PLS: chromosome conformation by proximity labeling and long-read sequencing.

Genomic approaches have provided detailed insight into chromosome architecture. However, commonly deployed techniques do not preserve connectivity-based information, leaving large-scale genome organization poorly characterized. Here, we developed CheC-PLS: a proximity-labeling technique that indelibly marks, and then decodes, protein-associated sites. CheC-PLS tethers dam methyltransferase to a protein of interest, followed by Nanopore sequencing to identify methylated bases - indicative of in vivo proximity - along reads >100kb. As proof-of-concept we analyzed, in budding yeast, a cohesin-based meiotic backbone that organizes chromatin into an array of loops. Our data recapitulates previously obtained association patterns, and, importantly, exposes variability between cells. Single read data reveals cohesin translocation on DNA and, by anchoring reads onto unique regions, we define the internal organization of the ribosomal DNA locus. Our versatile technique, which we also deployed on isolated nuclei with nanobodies, promises to illuminate diverse chromosomal processes by describing the in vivo conformations of single chromosomes.

Comparison of CcrM-dependent methylation in Caulobacter crescentus and Brucella abortus by nanopore sequencing.

Bacteria rely on DNA methylation for restriction-modification systems and epigenetic control of gene expression. Here, we use direct detection of methylated bases by nanopore sequencing to monitor global DNA methylation in Alphaproteobacteria, where use of this technique has not yet been reported. One representative of this order, Caulobacter crescentus, relies on DNA methylation to control cell cycle progression, but it is unclear whether other members of this order, such as Brucella abortus, depend on the same systems. We addressed these questions by first measuring CcrM-dependent DNA methylation in Caulobacter and showing excellent correlation between nanopore-based detection and previously published results. We then directly measure the impact of Lon-mediated CcrM degradation on the epigenome, verifying that loss of Lon results in pervasive methylation. We also show that the AlkB demethylase has no global impact on DNA methylation during normal growth. Next, we report on the global DNA methylation in B. abortus for the first time and find that CcrM-dependent methylation is reliant on Lon but impacts the two chromosomes differently. Finally, we explore the impact of the MucR transcription factor, known to compete with CcrM methylation, on the Brucella methylome and share the results with a publicly available visualization package. Our work demonstrates the utility of nanopore-based sequencing for epigenome measurements in Alphaproteobacteria and reveals new features of CcrM-dependent methylation in a zoonotic pathogen.IMPORTANCEDNA methylation plays an important role in bacteria, maintaining genome integrity and regulating gene expression. We used nanopore sequencing to directly measure methylated bases in Caulobacter crescentus and Brucella abortus. In Caulobacter, we showed that stabilization of the CcrM methyltransferase upon loss of the Lon protease results in prolific methylation and discovered that the putative methylase AlkB is unlikely to have a global physiological effect. We measured genome-wide methylation in Brucella for the first time, revealing a similar role for CcrM in cell-cycle methylation but a more complex regulation by the Lon protease than in Caulobacter. Finally, we show how the virulence factor MucR impacts DNA methylation patterns in Brucella.

Chromosome-scale genome assembly of bread wheat’s wild relative Triticum timopheevii

Wheat (Triticum aestivum) is one of the most important food crops with an urgent need for increase in its production to feed the growing world. Triticum timopheevii (2n = 4x = 28) is an allotetraploid wheat wild relative species containing the At and G genomes that has been exploited in many pre-breeding programmes for wheat improvement. In this study, we report the generation of a chromosome-scale reference genome assembly of T. timopheevii accession PI 94760 based on PacBio HiFi reads and chromosome conformation capture (Hi-C). The assembly comprised a total size of 9.35 Gb, featuring a contig N50 of 42.4 Mb and included the mitochondrial and plastid genome sequences. Genome annotation predicted 166,325 gene models including 70,365 genes with high confidence. DNA methylation analysis showed that the G genome had on average more methylated bases than the At genome. In summary, the T. timopheevii genome assembly provides a valuable resource for genome-informed discovery of agronomically important genes for food security.

Abstract SY16-01: What IDH mouse models have taught us about hematological diseases, from leukemia to T cell lymphoma

Abstract SY16-01: What IDH mouse models have taught us about hematological diseases, from leukemia to T cell lymphoma

Can methylated purine bases act as photoionization hotspots?

The direct photoionization of DNA canonical bases under ultraviolet radiation is difficult due to the high ionization potentials. According to previous quantum chemical calculations, methylation can have great influence on the ionization potential. Are methylated nucleobases prone to photoionization and cause DNA damage? As an important epigenetic modification in transcription, expression, and regulation of genes, it is of great biological significance to explore the effect of methylation on base photoionization from the experimental perspective. Herein, we study the photoionization behavior of methylated purines 6 mA and 6mG at 266 nm using a nanosecond transient UV-Vis spectroscopy. The hydrated electron and methylated base radicals are observed, indicating the occurrence of photoionization for both 6mG and 6 mA. We measured one-photon ionization yields to be (5.0 ± 0.2) × 10-3 and (1.4 ± 0.2) × 10-3 for 6mG and 6 mA, respectively. These are higher than those of (dA)20 and (dA20 )·(dT20 ) previously reported, indicating that methylation significantly promotes base photoionization with a stronger effect than base stacking, consistent with calculations in literature. Given that the hydrated electrons and methylated base radicals from photoionization can trigger a cascade of deleterious reactions, the methylated purine bases may act as hotspots of DNA photoionization damage of living organisms.

Shaping eukaryotic epigenetic systems by horizontal gene transfer.

DNA methylation constitutes one of the pillars of epigenetics, relying on covalent bonds for addition and/or removal of chemically distinct marks within the major groove of the double helix. DNA methyltransferases, enzymes which introduce methyl marks, initially evolved in prokaryotes as components of restriction-modification systems protecting host genomes from bacteriophages and other invading foreign DNA. In early eukaryotic evolution, DNA methyltransferases were horizontally transferred from bacteria into eukaryotes several times and independently co-opted into epigenetic regulatory systems, primarily via establishing connections with the chromatin environment. While C5-methylcytosine is the cornerstone of plant and animal epigenetics and has been investigated in much detail, the epigenetic role of other methylated bases is less clear. The recent addition of N4-methylcytosine of bacterial origin as a metazoan DNA modification highlights the prerequisites for foreign gene co-option into the host regulatory networks, and challenges the existing paradigms concerning the origin and evolution of eukaryotic regulatory systems.

Machine learning-assisted global DNA methylation fingerprint analysis for differentiating early-stage lung cancer from benign lung diseases

DNA methylation plays a critical role in the development of human tumors. However, routine characterization of DNA methylation can be time-consuming and labor-intensive. We herein describe a sensitive, simple surface-enhanced Raman spectroscopy (SERS) approach for identifying the DNA methylation pattern in early-stage lung cancer (LC) patients. By comparing SERS spectra of methylated DNA bases or sequences with their counterparts, we identified a reliable spectral marker of cytosine methylation. To move toward clinical applications, we applied our SERS strategy to detect the methylation patterns of genomic DNA (gDNA) extracted from cell line models as well as formalin-fixed paraffin-embedded tissues of early-stage LC and benign lung diseases (BLD) patients. In a clinical cohort of 106 individuals, our results showed distinct methylation patterns in gDNA between early-stage LC (n = 65) and BLD patients (n = 41), suggesting cancer-induced DNA methylation alterations. Combined with partial least square discriminant analysis, early-stage LC and BLD patients were differentiated with an area under the curve (AUC) value of 0.85. We believe that the SERS profiling of DNA methylation alterations, together with machine learning could potentially offer a promising new route toward the early detection of LC.

Probing RNA Structure with Dimethyl Sulfate Mutational Profiling with Sequencing <em>In Vitro</em> and in Cells

The role of RNA structure in virtually any biological process has become increasingly evident, especially in the past decade. However, classical approaches to solving RNA structure, such as RNA crystallography or cryo-EM, have failed to keep up with the rapidly evolving field and the need for high-throughput solutions. Mutational profiling with sequencing using dimethyl sulfate (DMS) MaPseq is a sequencing-based approach to infer the RNA structure from a base's reactivity with DMS. DMS methylates the N1 nitrogen in adenosines and the N3 in cytosines at their Watson-Crick face when the base is unpaired. Reverse-transcribing the modified RNA with the thermostable group II intron reverse transcriptase (TGIRT-III) leads to the methylated bases being incorporated as mutations into the cDNA. When sequencing the resulting cDNA and mapping it back to a reference transcript, the relative mutation rates for each base are indicative of the base's "status" as paired or unpaired. Even though DMS reactivities have a high signal-to-noise ratio both in vitro and in cells, this method is sensitive to bias in the handling procedures. To reduce this bias, this paper provides a protocol for RNA treatment with DMS in cells and with in vitro transcribed RNA.

DNA Demethylation in the Processes of Repair and Epigenetic Regulation Performed by 2-Ketoglutarate-Dependent DNA Dioxygenases.

Site-specific DNA methylation plays an important role in epigenetic regulation of gene expression. Chemical methylation of DNA, including the formation of various methylated nitrogenous bases, leads to the formation of genotoxic modifications that impair DNA functions. Despite the fact that different pathways give rise to methyl groups in DNA, the main pathway for their removal is oxidative demethylation, which is catalyzed by nonheme Fe(II)/α-ketoglutarate–dependent DNA dioxygenases. DNA dioxygenases share a common catalytic mechanism of the oxidation of the alkyl groups on nitrogenous bases in nucleic acids. This review presents generalized data on the catalytic mechanism of action of DNA dioxygenases and on the participation of typical representatives of this superfamily, such as prokaryotic enzyme AlkB and eukaryotic enzymes ALKBH1–8 and TET1–3, in both processes of direct repair of alkylated DNA adducts and in the removal of an epigenetic mark (5-methylcytosine).

Deciphering Epitranscriptome: Modification of mRNA Bases Provides a New Perspective for Post-transcriptional Regulation of Gene Expression.

Gene regulation depends on dynamic and reversibly modifiable biological and chemical information in the epigenome/epitranscriptome. Accumulating evidence suggests that messenger RNAs (mRNAs) are generated in flashing bursts in the cells in a precisely regulated manner. However, the different aspects of the underlying mechanisms are not fully understood. Cellular RNAs are post-transcriptionally modified at the base level, which alters the metabolism of mRNA. The current understanding of epitranscriptome in the animal system is far ahead of that in plants. The accumulating evidence indicates that the epitranscriptomic changes play vital roles in developmental processes and stress responses. Besides being non-genetically encoded, they can be of reversible nature and involved in fine-tuning the expression of gene. However, different aspects of base modifications in mRNAs are far from adequate to assign the molecular basis/functions to the epitranscriptomic changes. Advances in the chemogenetic RNA-labeling and high-throughput next-generation sequencing techniques are enabling functional analysis of the epitranscriptomic modifications to reveal their roles in mRNA biology. Mapping of the common mRNA modifications, including N6-methyladenosine (m6A), and 5-methylcytidine (m5C), have enabled the identification of other types of modifications, such as N1-methyladenosine. Methylation of bases in a transcript dynamically regulates the processing, cellular export, translation, and stability of the mRNA; thereby influence the important biological and physiological processes. Here, we summarize the findings in the field of mRNA base modifications with special emphasis on m6A, m5C, and their roles in growth, development, and stress tolerance, which provide a new perspective for the regulation of gene expression through post-transcriptional modification. This review also addresses some of the scientific and technical issues in epitranscriptomic study, put forward the viewpoints to resolve the issues, and discusses the future perspectives of the research in this area.

Excision of mutagenic replication-blocking lesions suppresses cancer but promotes cytotoxicity and lethality in nitrosamine-exposed mice

N-Nitrosodimethylamine (NDMA) is a DNA-methylating agent that has been discovered to contaminate water, food, and drugs. The alkyladenine DNA glycosylase (AAG) removes methylated bases to initiate the base excision repair (BER) pathway. To understand how gene-environment interactions impact disease susceptibility, we study Aag-knockout (Aag-/-) and Aag-overexpressing mice that harbor increased levels of either replication-blocking lesions (3-methyladenine [3MeA]) or strand breaks (BER intermediates), respectively. Remarkably, the disease outcome switches from cancer to lethality simply by changing AAG levels. To understand the underlying basis for this observation, we integrate a suite of molecular, cellular, and physiological analyses. We find that unrepaired 3MeA is somewhat toxic, but highly mutagenic (promoting cancer), whereas excess strand breaks are poorly mutagenic and highly toxic (suppressing cancer and promoting lethality). We demonstrate that the levels of a single DNA repair protein tip the balance between blocks and breaks and thus dictate the disease consequences of DNA damage.

In Vivo Footprinting Analysis in Trichoderma reesei.

The in vivo footprinting method identifies protein-targeted DNA regions under different conditions such as carbon sources. Dimethyl sulfate (DMS) generates methylated purine bases at DNA sites which are not bound by proteins or transcription factors. The DNA is cleaved by HCl, and the resulting DNA fragments are 5'-end [6-FAM]-labeled by a linker-mediated PCR (LM-PCR). Fluorescent fragments are separated and analyzed on a capillary sequencer, followed by automated data analysis using the software tool ivFAST.

SequelTools: a suite of tools for working with PacBio Sequel raw sequence data

BackgroundPacBio sequencing is an incredibly valuable third-generation DNA sequencing method due to very long read lengths, ability to detect methylated bases, and its real-time sequencing methodology. Yet, hitherto no tool was available for analyzing the quality of, subsampling, and filtering PacBio data.ResultsHere we present SequelTools, a command-line program containing three tools: Quality Control, Read Subsampling, and Read Filtering. The Quality Control tool quickly processes PacBio Sequel raw sequence data from multiple SMRTcells producing multiple statistics and publication-quality plots describing the quality of the data including N50, read length and count statistics, PSR, and ZOR. The Read Subsampling tool allows the user to subsample reads by one or more of the following criteria: longest subreads per CLR or random CLR selection. The Read Filtering tool provides options for normalizing data by filtering out certain low-quality scraps reads and/or by minimum CLR length. SequelTools is implemented in bash, R, and Python using only standard libraries and packages and is platform independent.ConclusionsSequelTools is a program that provides the only free, fast, and easy-to-use quality control tool, and the only program providing this kind of read subsampling and read filtering for PacBio Sequel raw sequence data, and is available at https://github.com/ISUgenomics/SequelTools.

NanoReviser: An Error-Correction Tool for Nanopore Sequencing Based on a Deep Learning Algorithm.

Nanopore sequencing is regarded as one of the most promising third-generation sequencing (TGS) technologies. Since 2014, Oxford Nanopore Technologies (ONT) has developed a series of devices based on nanopore sequencing to produce very long reads, with an expected impact on genomics. However, the nanopore sequencing reads are susceptible to a fairly high error rate owing to the difficulty in identifying the DNA bases from the complex electrical signals. Although several basecalling tools have been developed for nanopore sequencing over the past years, it is still challenging to correct the sequences after applying the basecalling procedure. In this study, we developed an open-source DNA basecalling reviser, NanoReviser, based on a deep learning algorithm to correct the basecalling errors introduced by current basecallers provided by default. In our module, we re-segmented the raw electrical signals based on the basecalled sequences provided by the default basecallers. By employing convolution neural networks (CNNs) and bidirectional long short-term memory (Bi-LSTM) networks, we took advantage of the information from the raw electrical signals and the basecalled sequences from the basecallers. Our results showed NanoReviser, as a post-basecalling reviser, significantly improving the basecalling quality. After being trained on standard ONT sequencing reads from public E. coli and human NA12878 datasets, NanoReviser reduced the sequencing error rate by over 5% for both the E. coli dataset and the human dataset. The performance of NanoReviser was found to be better than those of all current basecalling tools. Furthermore, we analyzed the modified bases of the E. coli dataset and added the methylation information to train our module. With the methylation annotation, NanoReviser reduced the error rate by 7% for the E. coli dataset and specifically reduced the error rate by over 10% for the regions of the sequence rich in methylated bases. To the best of our knowledge, NanoReviser is the first post-processing tool after basecalling to accurately correct the nanopore sequences without the time-consuming procedure of building the consensus sequence. The NanoReviser package is freely available at https://github.com/pkubioinformatics/NanoReviser.

The N-terminal domain of Staphylothermus marinus McrB shares structural homology with PUA-like RNA binding proteins

McrBC is a conserved modification-dependent restriction system that in Escherichia coli specifically targets foreign DNA containing methylated cytosines. Crystallographic data show that the N-terminal domain of Escherichia coli McrB binds substrates via a base flipping mechanism. This region is poorly conserved among the plethora of McrB homologs, suggesting that other species may use alternative binding strategies and/or recognize different targets. Here we present the crystal structure of the N-terminal domain from Stayphlothermus marinus McrB (Sm3-180) at 1.92 Å, which adopts a PUA-like EVE fold that is closely related to the YTH and ASCH RNA binding domains. Unlike most PUA-like domains, Sm3-180 binds DNA and can associate with different modified substrates. We find the canonical ‘aromatic cage’ binding pocket that confers specificity for methylated bases in other EVE/YTH domains is degenerate and occluded in Sm3-180, which may contribute to its promiscuity in target recognition. Further structural comparison between different PUA-like domains identifies motifs and conformational variations that correlate with the preference for binding either DNA or RNA. Together these data have important implications for PUA-like domain specificity and suggest a broader biological versatility for the McrBC family than previously described.

Excision of Mutagenic Replication-Blocking Lesions Suppresses Cancer But Promotes Cytotoxicity and Lethality in Nitrosamine-Exposed Mice

N-nitrosodimethylamine (NDMA) is a DNA methylating agent that has been discovered to contaminate water, food and drugs. The alkyladenine glycosylase (AAG) removes methylated bases to initiate the base excision repair (BER) pathway. To understand how gene-environment interactions impact disease susceptibility, we studied Aag-/- and Aag-overexpressing mice that harbor increased levels of either replication-blocking lesions (3-methyladenine, or 3MeA) or strand breaks (BER intermediates), respectively. Remarkably, the disease outcome switched from cancer to lethality simply by changing AAG levels. To understand the underlying basis for this observation, we integrated a suite of molecular, cellular and physiological analyses. We found that unrepaired 3MeA is somewhat toxic but highly mutagenic (promoting cancer), whereas excess strand breaks are poorly mutagenic and highly toxic (suppressing cancer and promoting lethality). We demonstrate that the levels of a single DNA repair protein tips the balance between blocks and breaks, and thus dictates the disease consequences of DNA damage.

Comparative Analysis of Whole-Genome and Methylome Profiles of a Smooth and a Rough Mycobacterium abscessus Clinical Strain.

Mycobacterium abscessus is a fast growing Mycobacterium species mainly causing skin and respiratory infections in human. M. abscessus is resistant to numerous drugs, which is a major challenge for the treatment. In this study, we have sequenced the genomes of two clinical M. abscessus strains having rough and smooth morphology, using the single molecule real-time and Illumina HiSeq sequencing technology. In addition, we reported the first comparative methylome profiles of a rough and a smooth M. abscessus clinical strains. The number of N4-methylcytosine (4mC) and N6-methyladenine (6mA) modified bases obtained from smooth phenotype were two-fold and 1.6 fold respectively higher than that of rough phenotype. We have also identified 4 distinct novel motifs in two clinical strains and genes encoding antibiotic-modifying/targeting enzymes and genes associated with intracellular survivability having different methylation patterns. To our knowledge, this is the first report about genome-wide methylation profiles of M. abscessus strains and identification of a natural linear plasmid (15 kb) in this critical pathogen harboring methylated bases. The pan-genome analysis of 25 M. abscessus strains including two clinical strains revealed an open pan genome comprises of 7596 gene clusters. Likewise, structural variation analysis revealed that the genome of rough phenotype strain contains more insertions and deletions than the smooth phenotype and that of the reference strain. A total of 391 single nucleotide variations responsible for the non-synonymous mutations were detected in clinical strains compared to the reference genome. The comparative genomic analysis elucidates the genome plasticity in this emerging pathogen. Furthermore, the detection of genome-wide methylation profiles of M. abscessus clinical strains may provide insight into the significant role of DNA methylation in pathogenicity and drug resistance in this opportunistic pathogen.

MethylToSNP: identifying SNPs in Illumina DNA methylation array data

BackgroundCurrent array-based methods for the measurement of DNA methylation rely on the process of sodium bisulfite conversion to differentiate between methylated and unmethylated cytosine bases in DNA. In the absence of genotype data this process can lead to ambiguity in data interpretation when a sample has polymorphisms at a methylation probe site. A common way to minimize this problem is to exclude such potentially problematic sites, with some methods removing as much as 60% of array probes from consideration before data analysis.ResultsHere, we present an algorithm implemented in an R Bioconductor package, MethylToSNP, which detects a characteristic data pattern to infer sites likely to be confounded by polymorphisms. Additionally, the tool provides a stringent reliability score to allow thresholding on SNP predictions. We calibrated parameters and thresholds used by the algorithm on simulated and real methylation data sets. We illustrate findings using methylation data from YRI (Yoruba in Ibadan, Nigeria), CEPH (European descent) and KhoeSan (southern African) populations. Our polymorphism predictions made using MethylToSNP have been validated through SNP databases and bisulfite and genomic sequencing.ConclusionsThe benefits of this method are threefold. First, it prevents extensive data loss by considering only SNPs specific to the individuals in the study. Second, it offers the possibility to identify new polymorphisms in samples for which there is little known about the genetic landscape. Third, it identifies variants as they exist in functional regions of a genome, such as in CTCF (transcriptional repressor) sites and enhancers, that may be common alleles or personal mutations with potential to deleteriously affect genomic regulatory activities. We demonstrate that MethylToSNP is applicable to the Illumina 450K and Illumina 850K EPIC array data and is also backwards compatible to the 27K methylation arrays. Going forward, this kind of nuanced approach can increase the amount of information derived from precious data sets by considering samples of the project individually to enable more informed decisions about data cleaning.