Epitranscriptome: Review of Top 25 Most-Studied RNA Modifications

Striving for clarity in language about gene expression

What do we mean when we say 'gene expression'? In the decades following Crick's 1958 central dogma of molecular biology, whereby genetic information flows from DNA (genes) to RNA (transcripts) to protein (products), we have learned a great deal about DNA, RNA, proteins, and the ensuing phenotypic changes. With the advent of high-throughput technologies (1990s), molecular biologists and computer scientists forged critical collaborations to understand the vast amount of data being generated, rapidly escalating gene expression research to the 'omics' level: entire sets of genes (genomes), transcribed RNAs (transcriptomes), and synthesized proteins (proteomes). However, some concessions came to be made for molecular biologists and computer scientists to understand each other-one of the most prevalent being the increasingly widespread use of 'gene' to mean 'RNAs originating from a DNA segment'. This loosening of terminology, we will argue, creates ambiguity and confusion. We propose guidelines to increase precision and clarity when communicating about gene expression, most notably to reserve 'gene' for the DNA template and 'transcript' for the RNA transcribed from that gene. Striving to use perspicuous terminology will promote rigorous gene expression science and accelerate discovery in this highly promising area of biology.

Substrate diversity of NSUN enzymes and links of 5-methylcytosine to mRNA translation and turnover

Maps of the RNA modification 5-methylcytosine (m5C) often diverge markedly not only because of differences in detection methods, data depand analysis pipelines but also biological factors. We re-analysed bisulfite RNA sequencing datasets from five human cell lines and seven tissues using a coherent m5C site calling pipeline. With the resulting union list of 6,393 m5C sites, we studied site distribution, enzymology, interaction with RNA-binding proteins and molecular function. We confirmed tRNA:m5C methyltransferases NSUN2 and NSUN6 as the main mRNA m5C "writers," but further showed that the rRNA:m5C methyltransferase NSUN5 can also modify mRNA. Each enzyme recognises mRNA features that strongly resemble their canonical substrates. By analysing proximity between mRNA m5C sites and footprints of RNA-binding proteins, we identified new candidates for functional interactions, including the RNA helicases DDX3X, involved in mRNA translation, and UPF1, an mRNA decay factor. We found that lack of NSUN2 in HeLa cells affected both steady-state levels of, and UPF1-binding to, target mRNAs. Our studies emphasise the emerging diversity of m5C writers and readers and their effect on mRNA function.

Direct RNA sequencing in plants: Practical applications and future perspectives

The transcriptome serves as a bridge that links genomic variation to phenotypic diversity. A vast number of studies using next-generation RNA sequencing (RNA-seq) over the last 2 decades have emphasized the essential roles of the plant transcriptome in response to developmental and environmental conditions, providing numerous insights into the dynamic changes, evolutionary traces, and elaborate regulation of the plant transcriptome. With substantial improvement in accuracy and throughput, direct RNA sequencing (DRS) has emerged as a new and powerful sequencing platform for precise detection of native and full-length transcripts, overcoming many limitations such as read length and PCR bias that are inherent to short-read RNA-seq. Here, we review recent advances in dissecting the complexity and diversity of plant transcriptomes using DRS as the main technological approach, covering many aspects of RNA metabolism, including novel isoforms, poly(A) tails, and RNA modification, and we propose a comprehensive workflow for processing of plant DRS data. Many challenges to the application of DRS in plants, such as the need for machine learning tools tailored to plant transcriptomes, remain to be overcome, and together we outline future biological questions that can be addressed by DRS, such as allele-specific RNA modification. This technology provides convenient support on which the connection of distinct RNA features is tightly built, sustainably refining our understanding of the biological functions of the plant transcriptome.

Post-transcriptional regulation as a conserved driver of neural crest and cancer-cell migration

Cells have evolved mechanisms to migrate for diverse biological functions. A process frequently deployed during metazoan cell migration is the epithelial-mesenchymal transition (EMT). During EMT, adherent epithelial cells undergo coordinated cellular transitions to mesenchymalize and reduce their intercellular attachments. This is achieved via tightly regulated changes in gene expression, which modulates cell-cell and cell-matrix adhesion to allow movement. The acquisition of motility and invasive properties following EMT allows some mesenchymal cells to migrate through complex environments to form tissues during embryogenesis; however, these processes may also be leveraged by cancer cells, which often co-opt these endogenous programs to metastasize. Post-transcriptional regulation is now emerging as a major conserved mechanism by which cells modulate EMT and migration, which we discuss here in the context of vertebrate development and cancer.

Genetic regulation of m6A RNA methylation and its contribution in human complex diseases

N6-methyladenosine (m6A) has been established as the most prevalent chemical modification in message RNA (mRNA), playing an essential role in determining the fate of RNA molecules. Dysregulation of m6A has been revealed to lead to abnormal physiological conditions and cause various types of human diseases. Recent studies have delineated the genetic regulatory maps for m6A methylation by mapping the quantitative trait loci of m6A (m6A-QTLs), thereby building up the regulatory circuits linking genetic variants, m6A, and human complex traits. Here, we review the recent discoveries concerning the genetic regulatory maps of m6A, describing the methodological and technical details of m6A-QTL identification, and introducing the key findings of the cis- and trans-acting drivers of m6A. We further delve into the tissue- and ethnicity-specificity of m6A-QTL, the association with other molecular phenotypes in light of genetic regulation, the regulators underlying m6A genetics, and importantly, the functional roles of m6A in mediating human complex diseases. Lastly, we discuss potential research avenues that can accelerate the translation of m6A genetics studies toward the development of therapies for human genetic diseases.

ADAR-Mediated A>I(G) RNA Editing in the Genotoxic Drug Response of Breast Cancer

Epitranscriptomics is a field that delves into post-transcriptional changes. Among these modifications, the conversion of adenosine to inosine, traduced as guanosine (A>I(G)), is one of the known RNA-editing mechanisms, catalyzed by ADARs. This type of RNA editing is the most common type of editing in mammals and contributes to biological diversity. Disruption in the A>I(G) RNA-editing balance has been linked to diseases, including several types of cancer. Drug resistance in patients with cancer represents a significant public health concern, contributing to increased mortality rates resulting from therapy non-responsiveness and disease progression, representing the greatest challenge for researchers in this field. The A>I(G) RNA editing is involved in several mechanisms over the immunotherapy and genotoxic drug response and drug resistance. This review investigates the relationship between ADAR1 and specific A>I(G) RNA-edited sites, focusing particularly on breast cancer, and the impact of these sites on DNA damage repair and the immune response over anti-cancer therapy. We address the underlying mechanisms, bioinformatics, and in vitro strategies for the identification and validation of A>I(G) RNA-edited sites. We gathered databases related to A>I(G) RNA editing and cancer and discussed the potential clinical and research implications of understanding A>I(G) RNA-editing patterns. Understanding the intricate role of ADAR1-mediated A>I(G) RNA editing in breast cancer holds significant promise for the development of personalized treatment approaches tailored to individual patients' A>I(G) RNA-editing profiles.

Methylation modifications in tRNA and associated disorders: Current research and potential therapeutic targets

High-throughput sequencing has sparked increased research interest in RNA modifications, particularly tRNA methylation, and its connection to various diseases. However, the precise mechanisms underpinning the development of these diseases remain largely elusive. This review sheds light on the roles of several tRNA methylations (m1A, m3C, m5C, m1G, m2G, m7G, m5U, and Nm) in diverse biological functions, including metabolic processing, stability, protein interactions, and mitochondrial activities. It further outlines diseases linked to aberrant tRNA modifications, related enzymes, and potential underlying mechanisms. Moreover, disruptions in tRNA regulation and abnormalities in tRNA-derived small RNAs (tsRNAs) contribute to disease pathogenesis, highlighting their potential as biomarkers for disease diagnosis. The review also delves into the exploration of drugs development targeting tRNA methylation enzymes, emphasizing the therapeutic prospects of modulating these processes. Continued research is imperative for a comprehensive comprehension and integration of these molecular mechanisms in disease diagnosis and treatment.

Prognostic signature and immune efficacy of m1A-, m5C-, m6A-, m7G-, and DNA methylation-related regulators in hepatocellular carcinoma

Background: Hepatocellular carcinoma (HCC) is the main type of primary liver cancer, and its related death ranks third worldwide. The curative methods and progress prediction markers of HCC are not sufficient enough. Nevertheless, little progress has been made in the signature of m1A-, m5C-, m6A-, m7G-, and DNA methylation of HCC. Results: We calibrated a risk gene signature model that can be used to categorize HCC patients based on univariate, multivariate, and LASSO Cox regression analysis. This gene signature classified the patients into high- and low-risk subgroups. Patients in the high-risk group showed significantly reduced overall survival (OS) compared with patients in the low-risk group. The gene set variation analysis (GSVA), immune infiltration, and immunotherapy response were analyzed. The results demonstrated that an immunosuppressive environment was exited and the high-risk group had higher sensitivity to 5-fluorouracil, cisplatin, sorafenib, tamoxifen, and epirubicin. These results indicated personalized therapy should be taken into consideration. Conclusions: Our findings enriched our understanding of the molecular heterogeneity, tumor microenvironment (TME), and drug susceptibility of HCC. m1A-, m5C-, m6A-, m7G-, and DNA methylation-related regulators may be promising biomarkers for future research.

Detection and Quantification of 5moU RNA Modification from Direct RNA Sequencing Data

Background

Chemically modified therapeutic mRNAs have gained momentum recently. In addition to commonly used modifications (e.g., pseudouridine), 5moU is considered a promising substitution for uridine in therapeutic mRNAs. Accurate identification of 5-methoxyuridine (5moU) would be crucial for the study and quality control of relevant in vitro-transcribed (IVT) mRNAs. However, current methods exhibit deficiencies in providing quantitative methodologies for detecting such modification. Utilizing the capabilities of Oxford nanopore direct RNA sequencing, in this study, we present NanoML-5moU, a machine-learning framework designed specifically for the read-level detection and quantification of 5moU modification for IVT data.

Materials and Methods

Nanopore direct RNA sequencing data from both 5moU-modified and unmodified control samples were collected. Subsequently, a comprehensive analysis and modeling of signal event characteristics (mean, median current intensities, standard deviations, and dwell times) were performed. Furthermore, classical machine learning algorithms, notably the Support Vector Machine (SVM), Random Forest (RF), and XGBoost were employed to discern 5moU modifications within NNUNN (where N represents A, C, U, or G) 5-mers.

Results

Notably, the signal event attributes pertaining to each constituent base of the NNUNN 5-mers, in conjunction with the utilization of the XGBoost algorithm, exhibited remarkable performance levels (with a maximum AUROC of 0.9567 in the "AGTTC" reference 5-mer dataset and a minimum AUROC of 0.8113 in the "TGTGC" reference 5-mer dataset). This accomplishment markedly exceeded the efficacy of the prevailing background error comparison model (ELIGOs AUC 0.751 for site-level prediction). The model's performance was further validated through a series of curated datasets, which featured customized modification ratios designed to emulate broader data patterns, demonstrating its general applicability in quality control of IVT mRNA vaccines. The NanoML-5moU framework is publicly available on GitHub (https://github.com/JiayiLi21/NanoML-5moU).

Conclusion

NanoML-5moU enables accurate read-level profiling of 5moU modification with nanopore direct RNA-sequencing, which is a powerful tool specialized in unveiling signal patterns in in vitro-transcribed (IVT) mRNAs.

Morphine-Driven m6A Epitranscriptomic Neuroadaptations in Primary Cortical Cultures

Opioid overdose is the leading cause of accidental death in the United States and remains a major public health concern, despite significant resources aimed at combating opioid misuse. Neurobiological research to elucidate molecular and cellular consequences of opioid exposure is required to define avenues to explore for reversal of opioid-induced neuroadaptations. Opioids impart well-documented regulation of the transcriptome and epigenetic modifications in the brain, but opioid-induced epitranscriptomic posttranscriptional regulation of RNA is vastly understudied. N6-methyladenosine (m6A) RNA methylation is significantly enriched in the brain and involved in learning, memory, and reward. m6A modifications have not been studied in opioid use disorder, despite being the most common RNA modification. We detected significant regulation of m6A-modifying enzymes in rat primary cortical cultures following morphine treatment, including AlkB Homolog 5 (Alkbh5). The m6a demethylase ALKBH5 functions as an m6A eraser, removing m6A modifications from mRNA. We hypothesized that chronic opioid treatment regulates m6A modifications through modulation of Alkbh5 and profiled m6A modifications in primary cortical cultures following chronic morphine treatment and Alkbh5 knock-down. We observed differential regulation of m6A modifications for a common set of transcripts following morphine or Alkbh5 knock-down, and the two treatments elicited concordant m6A epitranscriptomic profiles, suggesting that a subset of morphine-driven m6A modifications may be mediated through downregulation of Alkbh5 in cortical cultures. Gene Ontology terms of commonly regulated transcripts included serotonin secretion, synapse disassembly, neuron remodeling, and immune response. Thus, we conclude that morphine can drive epitranscriptomic changes, a subset of which may occur in an Alkbh5-dependent manner.

Cigarette smoking combined with genetic variation regulates the m6A methylation of CRNKL1 and is associated with bladder cancer risk

Cigarette smoking was known to accelerate the occurrence and development of bladder cancer by regulating RNA modification. However, the association between the combination of cigarette smoking and RNA modification-related single nucleotide polymorphisms (RNAm-SNPs) and bladder cancer risk remains unclear. In this study, 1681 participants, including 580 cases and 1101 controls, were recruited for genetic association analysis. In total, 1 287 990 RNAm-SNPs involving nine RNA modifications (m6A, m1A, m6Am, 2'-O-Me, m5C, m7G, A-to-I, m5U, and pseudouridine modification) were obtained from the RMVar database. The interactive effect of cigarette smoking and RNAm-SNPs on bladder cancer risk was assessed through joint analysis. The susceptibility analysis revealed that 89 RNAm-SNPs involving m6A, m1A, and A-to-I modifications were associated with bladder cancer risk. Among them, m6A-related rs2273058 in CRNKL1 was associated with bladder cancer risk (odds ratios (OR) = 1.35, padj = 1.78 × 10-4), and CRNKL1 expression was increased in bladder cancer patients (p = 0.035). Cigarette smoking combined with the A allele of rs2273058 increased bladder cancer risk compared with nonsmokers with the G allele of rs2273058 (OR = 2.40, padj = 3.11 × 10-9). Mechanistically, the A allele of rs2273058 endowed CRNKL1 with an additional m6A motif, facilitating recognition by m6A reader IGF2BP1, thereby promoting CRNKL1 expression under cigarette smoking (r = 0.142, p = 0.017). Moreover, elevated CRNKL1 expression may accelerate cell cycle and proliferation, thereby increasing bladder cancer risk. In summary, our study demonstrated that cigarette smoking combined with RNAm-SNPs contributes to bladder cancer risk, which provides a potential target for bladder cancer prevention.

A role for a Trypanosoma brucei cytosine RNA methyltransferase homolog in ribosomal RNA processing

In Trypanosoma brucei, gene expression is primarily regulated posttranscriptionally making RNA metabolism critical. T. brucei has an epitranscriptome containing modified RNA bases. Yet, the identity of the enzymes catalyzing modified RNA base addition and the functions of the enzymes and modifications remain unclear. Homology searches indicate the presence of numerous T. brucei cytosine RNA methyltransferase homologs. One such homolog, TbNop2 was studied in detail. TbNop2 contains the six highly conserved motifs found in cytosine RNA methyltransferases and is evolutionarily related to the Nop2 protein family required for rRNA modification and processing. RNAi experiments targeting TbNop2 resulted in reduced levels of TbNop2 RNA and protein, and a cessation of parasite growth. Next generation sequencing of bisulfite-treated RNA (BS-seq) detected the presence of two methylation sites in the large rRNA; yet TbNop2 RNAi did not result in a significant reduction of methylation. However, TbNop2 RNAi resulted in the retention of 28S internal transcribed spacer RNAs, indicating a role for TbNop2 in rRNA processing.

Adenine Methylation Enhances the Conformational Flexibility of an RNA Hairpin Tetraloop

The N6-methyladenosine modification is one of the most abundant post-transcriptional modifications in ribonucleic acid (RNA) molecules. Using molecular dynamics simulations and alchemical free-energy calculations, we studied the structural and energetic implications of incorporating this modification in an adenine mononucleotide and an RNA hairpin structure. At the mononucleotide level, we found that the syn configuration is more favorable than the anti configuration by 2.05 ± 0.15 kcal/mol. The unfavorable effect of methylation was due to the steric overlap between the methyl group and a nitrogen atom in the purine ring. We then probed the effect of methylation in an RNA hairpin structure containing an AUCG tetraloop, which is recognized by a "reader" protein (YTHDC1) to promote transcriptional silencing of long noncoding RNAs. While methylation had no significant conformational effect on the hairpin stem, the methylated tetraloop showed enhanced conformational flexibility compared to the unmethylated tetraloop. The increased flexibility was associated with the outward flipping of two bases (A6 and U7) which formed stacking interactions with each other and with the C8 and G9 bases in the tetraloop, leading to a conformation similar to that in the RNA/reader protein complex. Therefore, methylation-induced conformational flexibility likely facilitates RNA recognition by the reader protein.

m6A-TCPred: a web server to predict tissue-conserved human m6A sites using machine learning approach

BACKGROUND

N6-methyladenosine (m6A) is the most prevalent post-transcriptional modification in eukaryotic cells that plays a crucial role in regulating various biological processes, and dysregulation of m6A status is involved in multiple human diseases including cancer contexts. A number of prediction frameworks have been proposed for high-accuracy identification of putative m6A sites, however, none have targeted for direct prediction of tissue-conserved m6A modified residues from non-conserved ones at base-resolution level.

RESULTS

We report here m6A-TCPred, a computational tool for predicting tissue-conserved m6A residues using m6A profiling data from 23 human tissues. By taking advantage of the traditional sequence-based characteristics and additional genome-derived information, m6A-TCPred successfully captured distinct patterns between potentially tissue-conserved m6A modifications and non-conserved ones, with an average AUROC of 0.871 and 0.879 tested on cross-validation and independent datasets, respectively.

CONCLUSION

Our results have been integrated into an online platform: a database holding 268,115 high confidence m6A sites with their conserved information across 23 human tissues; and a web server to predict the conserved status of user-provided m6A collections. The web interface of m6A-TCPred is freely accessible at: www.rnamd.org/m6ATCPred .

Interconnections between m6A RNA modification, RNA structure, and protein-RNA complex assembly

Protein-RNA complexes exist in many forms within the cell, from stable machines such as the ribosome to transient assemblies like the spliceosome. All protein-RNA assemblies rely on spatially and temporally coordinated interactions between specific proteins and RNAs to achieve a functional form. RNA folding and structure are often critical for successful protein binding and protein-RNA complex formation. RNA modifications change the chemical nature of a given RNA and often alter its folding kinetics. Both these alterations can affect how and if proteins or other RNAs can interact with the modified RNA and assemble into complexes. N6-methyladenosine (m6A) is the most common base modification on mRNAs and regulatory noncoding RNAs and has been shown to impact RNA structure and directly modulate protein-RNA interactions. In this review, focusing on the mechanisms and available quantitative information, we discuss first how the METTL3/14 m6A writer complex is specifically targeted to RNA assisted by protein-RNA and other interactions to enable site-specific and co-transcriptional RNA modification and, once introduced, how the m6A modification affects RNA folding and protein-RNA interactions.

LSA-ac4C: A hybrid neural network incorporating double-layer LSTM and self-attention mechanism for the prediction of N4-acetylcytidine sites in human mRNA

N4-acetylcytidine (ac4C) is a vital constituent of the epitranscriptome and plays a crucial role in the regulation of mRNA expression. Numerous studies have established correlations between ac4C and the incidence, progression and prognosis of various cancers. Therefore, accurately predicting ac4C sites is an important step towards comprehending the biological functions of this modification and devising effective therapeutic interventions. Wet experiments are primary methods for studying ac4C, but computational methods have emerged as a promising supplement due to their cost-effectiveness and shorter research cycles. However, current models still have inherent limitations in terms of predictive performance and generalization ability. Here, we utilized automated machine learning technology to establish a reliable baseline and constructed a deep hybrid neural network, LSA-ac4C, which combines double-layer Long Short-Term Memory (LSTM) and self-attention mechanism for accurate ac4C sites prediction. Benchmarking comparisons demonstrate that LSA-ac4C exhibits superior performance compared to the current state-of-the-art method, with ACC, MCC and AUROC improving by 2.89 %, 5.96 % and 1.53 %, respectively, on an independent test set. Overall, LSA-ac4C serves as a powerful tool for predicting ac4C sites in human mRNA, thus benefiting research on RNA modification. For the convenience of the research community, a web server has been established at http://tubic.org/ac4C.

Identifying N6-Methyladenosine Sites in HepG2 Cell Lines Using Oxford Nanopore Technology

RNA modifications, particularly N6-methyladenosine (m6A), are pivotal regulators of RNA functionality and cellular processes. We analyzed m6A modifications by employing Oxford Nanopore technology and the m6Anet algorithm, focusing on the HepG2 cell line. We identified 3968 potential m6A modification sites in 2851 transcripts, corresponding to 1396 genes. A gene functional analysis revealed the active involvement of m6A-modified genes in ubiquitination, transcription regulation, and protein folding processes, aligning with the known role of m6A modifications in histone ubiquitination in cancer. To ensure data robustness, we assessed reproducibility across technical replicates. This study underscores the importance of evaluating algorithmic reproducibility, especially in supervised learning. Furthermore, we examined correlations between transcriptomic, translatomic, and proteomic levels. A strong transcriptomic-translatomic correlation was observed. In conclusion, our study deepens our understanding of m6A modifications' multifaceted impacts on cellular processes and underscores the importance of addressing reproducibility concerns in analytical approaches.

Workability of mRNA Sequencing for Predicting Protein Abundance

Transcriptomics methods (RNA-Seq, PCR) today are more routine and reproducible than proteomics methods, i.e., both mass spectrometry and immunochemical analysis. For this reason, most scientific studies are limited to assessing the level of mRNA content. At the same time, protein content (and its post-translational status) largely determines the cell's state and behavior. Such a forced extrapolation of conclusions from the transcriptome to the proteome often seems unjustified. The ratios of "transcript-protein" pairs can vary by several orders of magnitude for different genes. As a rule, the correlation coefficient between transcriptome-proteome levels for different tissues does not exceed 0.3-0.5. Several characteristics determine the ratio between the content of mRNA and protein: among them, the rate of movement of the ribosome along the mRNA and the number of free ribosomes in the cell, the availability of tRNA, the secondary structure, and the localization of the transcript. The technical features of the experimental methods also significantly influence the levels of the transcript and protein of the corresponding gene on the outcome of the comparison. Given the above biological features and the performance of experimental and bioinformatic approaches, one may develop various models to predict proteomic profiles based on transcriptomic data. This review is devoted to the ability of RNA sequencing methods for protein abundance prediction.

Mapping epigenetic modifications by sequencing technologies

The "epigenetics" concept was first described in 1942. Thus far, chemical modifications on histones, DNA, and RNA have emerged as three important building blocks of epigenetic modifications. Many epigenetic modifications have been intensively studied and found to be involved in most essential biological processes as well as human diseases, including cancer. Precisely and quantitatively mapping over 100 [1], 17 [2], and 160 [3] different known types of epigenetic modifications in histone, DNA, and RNA is the key to understanding the role of epigenetic modifications in gene regulation in diverse biological processes. With the rapid development of sequencing technologies, scientists are able to detect specific epigenetic modifications with various quantitative, high-resolution, whole-genome/transcriptome approaches. Here, we summarize recent advances in epigenetic modification sequencing technologies, focusing on major histone, DNA, and RNA modifications in mammalian cells.

Selective Functionalisation of 5-Methylcytosine by Organic Photoredox Catalysis

The epigenetic modification 5-methylcytosine plays a vital role in development, cell specific gene expression and disease states. The selective chemical modification of the 5-methylcytosine methyl group is challenging. Currently, no such chemistry exists. Direct functionalisation of 5-methylcytosine would improve the detection and study of this epigenetic feature. We report a xanthone-photosensitised process that introduces a 4-pyridine modification at a C(sp3)-H bond in the methyl group of 5-methylcytosine. We propose a reaction mechanism for this type of reaction based on density functional calculations and apply transition state analysis to rationalise differences in observed reaction efficiencies between cyanopyridine derivatives. The reaction is initiated by single electron oxidation of 5-methylcytosine followed by deprotonation to generate the methyl group radical. Cross coupling of the methyl radical with 4-cyanopyridine installs a 4-pyridine label at 5-methylcytosine. We demonstrate use of the pyridination reaction to enrich 5-methylcytosine-containing ribonucleic acid.

Selective Functionalisation of 5-Methylcytosine by Organic Photoredox Catalysis

The epigenetic modification 5-methylcytosine plays a vital role in development, cell specific gene expression and disease states. The selective chemical modification of the 5-methylcytosine methyl group is challenging. Currently, no such chemistry exists. Direct functionalisation of 5-methylcytosine would improve the detection and study of this epigenetic feature. We report a xanthone-photosensitised process that introduces a 4-pyridine modification at a C(sp3 )-H bond in the methyl group of 5-methylcytosine. We propose a reaction mechanism for this type of reaction based on density functional calculations and apply transition state analysis to rationalise differences in observed reaction efficiencies between cyanopyridine derivatives. The reaction is initiated by single electron oxidation of 5-methylcytosine followed by deprotonation to generate the methyl group radical. Cross coupling of the methyl radical with 4-cyanopyridine installs a 4-pyridine label at 5-methylcytosine. We demonstrate use of the pyridination reaction to enrich 5-methylcytosine-containing ribonucleic acid.

Pitfalls of using sequence databases for heterologous expression studies - a technical review

Synthesis of DNA fragments based on gene sequences that are available in public resources has become an efficient and affordable method that has gradually replaced traditional cloning efforts such as PCR cloning from cDNA. However, database entries based on genome sequencing results are prone to errors which can lead to false sequence information and, ultimately, errors in functional characterisation of proteins such as ion channels and transporters in heterologous expression systems. We have identified five common problems that repeatedly appear in public resources: (1) Not every gene has yet been annotated; (2) not all gene annotations are necessarily correct; (3) transcripts may contain automated corrections; (4) there are mismatches between gene, mRNA and protein sequences; and (5) splicing patterns often lack experimental validation. This technical review highlights and provides a strategy to bypass these issues in order to avoid critical mistakes that could impact future studies of any gene/protein of interest in heterologous expression systems.