MeT-DB: a database of transcriptome methylation in mammalian cells

Variable calling of m6A and associated features in databases: a guide for end-users

N6-methyladenosine (m$^{6}$A) is a widely-studied methylation to messenger RNAs, which has been linked to diverse cellular processes and human diseases. Numerous databases that collate m$^{6}$A profiles of distinct cell types have been created to facilitate quick and easy mining of m$^{6}$A signatures associated with cell-specific phenotypes. However, these databases contain inherent complexities that have not been explicitly reported, which may lead to inaccurate identification and interpretation of m$^{6}$A-associated biology by end-users who are unaware of them. Here, we review various m$^{6}$A-related databases, and highlight several critical matters. In particular, differences in peak-calling pipelines across databases drive substantial variability in both peak number and coordinates with only moderate reproducibility, and the inclusion of peak calls from early m$^{6}$A sequencing protocols may lead to the reporting of false positives or negatives. The awareness of these matters will help end-users avoid the inclusion of potentially unreliable data in their studies and better utilize m$^{6}$A databases to derive biologically meaningful results.

Comprehensive review on lipid metabolism and RNA methylation: Biological mechanisms, perspectives and challenges

Adipose tissue plays a crucial role in maintaining energy balance, regulating hormones, and promoting metabolic health. To address disorders related to obesity and develop effective therapies, it is essential to have a deep understanding of adipose tissue biology. In recent years, RNA methylation has emerged as a significant epigenetic modification involved in various cellular functions and metabolic pathways. Particularly in the realm of adipogenesis and lipid metabolism, extensive research is ongoing to uncover the mechanisms and functional importance of RNA methylation. Increasing evidence suggests that RNA methylation plays a regulatory role in adipocyte development, metabolism, and lipid utilization across different organs. This comprehensive review aims to provide an overview of common RNA methylation modifications, their occurrences, and regulatory mechanisms, focusing specifically on their intricate connections to fat metabolism. Additionally, we discuss the research methodologies used in studying RNA methylation and highlight relevant databases that can aid researchers in this rapidly advancing field.

m6A Methylated Long Noncoding RNA LOC339803 Regulates Intestinal Inflammatory Response

Cytokine mediated sustained inflammation increases the risk to develop different complex chronic inflammatory diseases, but the implicated mechanisms remain unclear. Increasing evidence shows that long noncoding RNAs (lncRNAs) play key roles in the pathogenesis of inflammatory disorders, while inflammation associated variants are described to affect their function or essential RNA modifications as N6-methyladenosine (m6A) methylation, increasing predisposition to inflammatory diseases. Here, the functional implication of the intestinal inflammation associated lncRNA LOC339803 in the production of cytokines by intestinal epithelial cells is described. Allele-specific m6A methylation is found to affect YTHDC1 mediated protein binding affinity. LOC339803-YTHDC1 interaction dictates chromatin localization of LOC339803 ultimately inducing the expression of NFκB mediated proinflammatory cytokines and contributing to the development of intestinal inflammation. These findings are confirmed using human intestinal biopsy samples from different intestinal inflammatory conditions and controls. Additionally, it is demonstrated that LOC339803 targeting can be a useful strategy for the amelioration of intestinal inflammation in vitro and ex vivo. Overall, the results support the importance of the methylated LOC339803 lncRNA as a mediator of intestinal inflammation, explaining genetic susceptibility and presenting this lncRNA as a potential novel therapeutic target for the treatment of inflammatory intestinal disorders.

Biclustering for Epi-Transcriptomic Co-functional Analysis

Dynamic and reversible N6-methyladenosine (m6A) modifications are associated with many essential cellular functions as well as physiological and pathological phenomena. In-depth study of m6A co-functional patterns in epi-transcriptomic data may help to understand its complex regulatory mechanisms. In this chapter, we describe several biclustering mining algorithms for epi-transcriptomic data to discover potential co-functional patterns. The concepts and computational methods discussed in this chapter will be particularly useful for researchers working in related fields. We also aim to introduce new deep learning techniques into the field of co-functional analysis of epi-transcriptomic data.

Analysis approaches for the identification and prediction of N6-methyladenosine sites

The global dynamics in a variety of biological processes can be revealed by mapping transcriptional m⁶A sites, in particular full-transcriptome m⁶A. And individual m⁶A sites have contributed to biological function, which can be evaluated by stoichiometric information obtained from the single nucleotide resolution. Currently, the identification of m⁶A sites is mainly carried out by experiment and prediction methods, based on high-throughput sequencing and machine learning model respectively. This review summarizes the recent topics and progress made in bioinformatics methods of deciphering the m⁶A methylation, including the experimental detection of m⁶A methylation sites, techniques of data analysis, the way of predicting m⁶A methylation sites, m⁶A methylation databases, and detection of m⁶A modification in circRNA. At the end, the essay makes a brief discussion for the development perspective in this area.

Evaluation and development of deep neural networks for RNA 5-Methyluridine classifications using autoBioSeqpy

Post-transcriptionally RNA modifications, also known as the epitranscriptome, play crucial roles in the regulation of gene expression during development. Recently, deep learning (DL) has been employed for RNA modification site prediction and has shown promising results. However, due to the lack of relevant studies, it is unclear which DL architecture is best suited for some pyrimidine modifications, such as 5-methyluridine (m⁵U). To fill this knowledge gap, we first performed a comparative evaluation of various commonly used DL models for epigenetic studies with the help of autoBioSeqpy. We identified optimal architectural variations for m⁵U site classification, optimizing the layer depth and neuron width. Second, we used this knowledge to develop Deepm5U, an improved convolutional-recurrent neural network that accurately predicts m⁵U sites from RNA sequences. We successfully applied Deepm5U to transcriptomewide m⁵U profiling data across different sequencing technologies and cell types. Third, we showed that the techniques for interpreting deep neural networks, including LayerUMAP and DeepSHAP, can provide important insights into the internal operation and behavior of models. Overall, we offered practical guidance for the development, benchmark, and analysis of deep learning models when designing new algorithms for RNA modifications.

RNA modifications in aging-associated cardiovascular diseases

Cardiovascular disease (CVD) is a leading cause of morbidity and mortality worldwide that bears an enormous healthcare burden and aging is a major contributing factor to CVDs. Functional gene expression network during aging is regulated by mRNAs transcriptionally and by non-coding RNAs epi-transcriptionally. RNA modifications alter the stability and function of both mRNAs and non-coding RNAs and are involved in differentiation, development, and diseases. Here we review major chemical RNA modifications on mRNAs and non-coding RNAs, including N6-adenosine methylation, N1-adenosine methylation, 5-methylcytidine, pseudouridylation, 2′ -O-ribose-methylation, and N7-methylguanosine, in the aging process with an emphasis on cardiovascular aging. We also summarize the currently available methods to detect RNA modifications and the bioinformatic tools to study RNA modifications. More importantly, we discussed the specific implication of the RNA modifications on mRNAs and non-coding RNAs in the pathogenesis of aging-associated CVDs, including atherosclerosis, hypertension, coronary heart diseases, congestive heart failure, atrial fibrillation, peripheral artery disease, venous insufficiency, and stroke.

Dynamic Alteration Profile and New Role of RNA m6A Methylation in Replicative and H2O2-Induced Premature Senescence of Human Embryonic Lung Fibroblasts

N6-methyladenosine (m6A) methylation is one of the most common RNA modifications, regulating RNA fate at the posttranscriptional level, and is closely related to cellular senescence. Both models of replicative and premature senescence induced by hydrogen peroxide (H₂O₂) were used to detect m6A regulation during the senescence of human embryonic lung fibroblasts (HEFs). The ROS level accumulated gradually with senescence, leading to normal replicative senescence. H₂O₂-treated cells had dramatically increased ROS level, inducing the onset of acute premature senescence. Compared with replicative senescence, ROS changed the expression profiles for m6A-related enzymes and binding proteins, including higher levels of METTL3, METTL14, WTAP, KIAA1429, and FTO, and lower levels of METTL16, ALKBH5, YTHDC1, and YTHDF1/2/3 in the premature senescence persistence group, respectively. Meanwhile, senescent cells decreased total m6A content and RNA methylation enzymes activity, regardless of replicative or premature senescence. Moreover, specific m6A methylation levels regulated the expression of SIRT3, IRS2, and E2F3 between replicative and premature senescence separately. Taken together, differential m6A epitranscription microenvironment and the targeted genes can be used as epigenetic biomarkers to cell senescence and the related diseases, offering new clues for the prevention and intervention of cellular senescence.

The Impact of Epitranscriptomics on Antiviral Innate Immunity

Epitranscriptomics, i.e., chemical modifications of RNA molecules, has proven to be a new layer of modulation and regulation of protein expression, asking for the revisiting of some aspects of cellular biology. At the virological level, epitranscriptomics can thus directly impact the viral life cycle itself, acting on viral or cellular proteins promoting replication, or impacting the innate antiviral response of the host cell, the latter being the focus of the present review.

Downregulation of Fat Mass and Obesity-Related Protein in the Anterior Cingulate Cortex Participates in Anxiety- and Depression-Like Behaviors Induced by Neuropathic Pain

N6-methyladenosine (m⁶A) is the most abundant methylation modification on mRNA in mammals. Fat mass and obesity-related protein (FTO) is the main RNA m⁶A demethylase. FTO is involved in the occurrence and maintenance of neuropathic pain (NP). NP often induces mental disorders. We found that NP downregulated the expression of FTO in the anterior cingulate cortex (ACC), inhibited the expression of matrix metalloproteinase-9 (MMP-9) in the ACC, maladjusted the brain-derived neurotrophic factor precursor (proBDNF) and mature brain-derived neurotrophic factor (mBDNF) levels in the ACC, and induced anxiety- and depression-like behaviors in mice. Blocking the downregulation of FTO in the ACC induced by peripheral nerve injury could reverse the anxiety- and depression-like behaviors of mice. Contrarily, downregulation of simulated FTO induced anxiety- and depression-like behaviors in mice. After peripheral nerve injury, the binding of FTO to MMP-9 mRNA decreased and the enrichment of m⁶A on MMP-9 mRNA increased. In conclusion, downregulation of FTO in ACC by regulating MMP-9 mRNA methylation level contributes to the occurrence of anxiety- and depression-like behaviors in NP mice.

Interactions of circRNAs with methylation: An important aspect of circRNA biogenesis and function (Review)

Circular RNA (circRNA) molecules are noncoding RNAs with unique circular covalently closed structures that contribute to gene expression regulation, protein translation and act as microRNA sponges. circRNAs also have important roles in human disease, particularly tumorigenesis and antitumor processes. Methylation is an epigenetic modification that regulates the expression and roles of DNA and coding RNA and their interactions, as well as of noncoding RNA molecules. Previous studies have focused on the effects of methylation modification on circRNA expression, transport, stability, translation and degradation of circRNAs, as well as how circRNA methylation occurs and the influence of circRNAs on methylation modification processes. circRNA and methylation can also regulate disease pathogenesis via these interactions. In the present study, we define the relationship between circRNAs and methylation, as well as the functions and mechanisms of their interactions during disease progression.

Dynamic m6A-ncRNAs association and their impact on cancer pathogenesis, immune regulation and therapeutic response

Several types of modifications have been proven to participate in the metabolism and processing of different RNA types, including non-coding RNAs (ncRNAs). N-6-methyladenosine (m6A) is a dynamic and reversible RNA modification that is closely involved in the ncRNA homeostasis, and serves as a crucial regulator for multiple cancer-associated signaling pathways. The ncRNAs usually regulate the epigenetic modification, mRNA transcription and other biological processes, displaying enormous roles in human cancers. In this review, we summarized the significant implications of m6A-ncRNA interaction in various types of cancers. In particular, the interplay between m6A and ncRNAs in cancer pathogenesis and therapeutic resistance are being widely recognized. We also discussed the relevance of m6A-ncRNA interaction in immune regulation, followed by the interference on cancer immunotherapeutic procedures. In addition, we briefly highlighted the computation tools that could identify the accurate features of m6A methylome among ncRNAs. In summary, this review would pave the way for a better understanding of the biological functions of m6A-ncRNA crosstalk in cancer research and treatment.

Caspases Switch off the m6A RNA Modification Pathway to Foster the Replication of a Ubiquitous Human Tumor Virus

The methylation of RNA at the N6 position of adenosine (m⁶A) orchestrates multiple biological processes to control development, differentiation, and cell cycle, as well as various aspects of the virus life cycle. How the m⁶A RNA modification pathway is regulated to finely tune these processes remains poorly understood. Here, we discovered the m⁶A reader YTHDF2 as a caspase substrate via proteome-wide prediction, followed by in vitro and in vivo validations. We further demonstrated that cleavage-resistant YTHDF2 blocks, while cleavage-mimicking YTHDF2 fragments promote, the replication of a common human oncogenic virus, Epstein-Barr virus (EBV). Intriguingly, our study revealed a feedback regulation between YTHDF2 and caspase-8 via m⁶A modification of CASP8 mRNA and YTHDF2 cleavage during EBV replication. Further, we discovered that caspases cleave multiple components within the m⁶A RNA modification pathway to benefit EBV replication. Our study establishes that caspase disarming of the m⁶A RNA modification machinery fosters EBV replication. IMPORTANCE The discovery of an N⁶-methyladenosine (m⁶A) RNA modification pathway has fundamentally altered our understanding of the central dogma of molecular biology. This pathway is controlled by methyltransferases (writers), demethylases (erasers), and specific m⁶A binding proteins (readers). Emerging studies have linked the m⁶A RNA modification pathway to the life cycle of various viruses. However, very little is known regarding how this pathway is subverted to benefit viral replication. In this study, we established an unexpected linkage between cellular caspases and the m⁶A modification pathway, which is critical to drive the reactivation of a common tumor virus, Epstein-Barr virus (EBV).

The functional roles, cross-talk and clinical implications of m6A modification and circRNA in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related deaths worldwide. HCC has high rates of death and recurrence, as well as very low survival rates. N6-methyladenosine (m6A) is the most abundant modification in eukaryotic RNAs, and circRNAs are a class of circular noncoding RNAs that are generated by back-splicing and they modulate multiple functions in a variety of cellular processes. Although the carcinogenesis of HCC is complex, emerging evidence has indicated that m6A modification and circRNA play vital roles in HCC development and progression. However, the underlying mechanisms governing HCC, their cross-talk, and clinical implications have not been fully elucidated. Therefore, in this paper, we elucidated the biological functions and molecular mechanisms of m6A modification in the carcinogenesis of HCC by illustrating three different regulatory factors ("writer", "eraser", and "reader") of the m6A modification process. Additionally, we dissected the functional roles of circRNAs in various malignant behaviors of HCC, thereby contributing to HCC initiation, progression and relapse. Furthermore, we demonstrated the cross-talk and interplay between m6A modification and circRNA by revealing the effects of the collaboration of circRNA and m6A modification on HCC progression. Finally, we proposed the clinical potential and implications of m6A modifiers and circRNAs as diagnostic biomarkers and therapeutic targets for HCC diagnosis, treatment and prognosis evaluation.

ATF3 Modulates the Resistance of Breast Cancer Cells to Tamoxifen through an N6-Methyladenosine-Based Epitranscriptomic Mechanism

Tamoxifen has been used for years for treating estrogen receptor-positive breast cancer; drug resistance, however, constitutes one of the main challenges for this therapy. We found that the protein expression level of ATF3 is significantly higher in tamoxifen-resistant (TamR) MCF-7 cells than the corresponding parental cancer cells. In addition, ATF3 protein expression is positively correlated with the resistance of TamR MCF-7 cells to 4-hydroxytamoxifen (4-OHT). Mechanistically, elevated ATF3 protein expression in TamR MCF-7 cells results from a lower level of expression of YTHDF2, an m⁶A reader protein, and the ensuing stabilization and increased translational efficiency of ATF3 mRNA. Additionally, TamR MCF-7 cells exhibited decreased methylation at A131, a consensus motif site for m⁶A, in the 5'-untranslated region (5'-UTR) of ATF3 mRNA. Moreover, augmented ATF3 stimulates the expression of ABCB1, an efflux pump that confers drug resistance in breast cancer cells, and ATF3 itself is also positively regulated by adenylate kinase 4. Together, our results uncovered a novel molecular target for m⁶A modification (i.e., ATF3 mRNA) and the epitranscriptomic regulator for this target (i.e., YTHDF2). We also illustrated the role of ATF3 in drug resistance, revealed its downstream target (i.e., ABCB1), and suggested ATF3 as a candidate therapeutic target for overcoming drug resistance in cancer cells.

The Role of RNA Methyltransferase METTL3 in Hepatocellular Carcinoma: Results and Perspectives

Hepatocellular carcinoma (HCC) is the 6th most prevalent cancer and the 4th leading cause of cancer-related death worldwide. Mechanisms explaining the carcinogenesis of HCC are not clear yet. In recent years, rapid development of N⁶-methyladenosine (m6A) modification provides a fresh approach to disclosing this mystery. As the most prevalent mRNA modification in eukaryotes, m6A modification is capable to post-transcriptionally affect RNA splicing, stability, and translation, thus participating in a variety of biological and pathological processes including cell proliferation, apoptosis, tumor invasion and metastasis. METTL3 has been recognized as a pivotal methyltransferase and essential to the performance of m6A modification. METTL3 can regulate RNA expression in a m6A-dependent manner and contribute to the carcinogenesis, tumor progression, and drug resistance of HCC. In the present review, we are going to make a clear summary of the known roles of METTL3 in HCC, and explicitly narrate the potential mechanisms for these roles.

Elucidating the Functions of Non-Coding RNAs from the Perspective of RNA Modifications

It is now commonly accepted that most of the mammalian genome is transcribed as RNA, yet less than 2% of such RNA encode for proteins. A majority of transcribed RNA exists as non-protein-coding RNAs (ncRNAs) with various functions. Because of the lack of sequence homologies among most ncRNAs species, it is difficult to infer the potential functions of ncRNAs by examining sequence patterns, such as catalytic domains, as in the case of proteins. Added to the existing complexity of predicting the functions of the ever-growing number of ncRNAs, increasing evidence suggests that various enzymes modify ncRNAs (e.g., ADARs, METTL3, and METTL14), which has opened up a new field of study called epitranscriptomics. Here, we examine the current status of ncRNA research from the perspective of epitranscriptomics.

A brief review of RNA modification related database resources

To date, over 150 different RNA modifications have been identified, playing crucial roles in biological processes and disease pathogenesis. Thanks to the advancement of high-throughput sequencing technologies employed for transcriptome-wide mapping, a bunch of RNA modification databases have emerged as an exciting area, which promotes further investigation of the mechanisms and functions of these modified ribonucleotides. This article introduces the high-throughput sequencing technique developed for transcriptome-wide mapping of RNA modifications, as well as the procedures and main techniques of building these databases from the developers' perspective. It also reviews existing RNA modification databases in terms of their main functions, species, the number of sites they collected, the annotations, and the tools they provided. From the view of users, we further analyze and compare these databases in terms of their functions. For instance, these databases can be applied to record chemical structures and biosynthetic pathways, or unravel the epi-transcriptome comprehensively, or only investigate specific features of RNA modifications. Additionally, the limitations of the existing approaches are discussed, and some future suggestions are offered.

N6-methyladenosine dynamics in neurodevelopment and aging, and its potential role in Alzheimer's disease

BACKGROUND

N6-methyladenosine (m6A) modification is known to impact many aspects of RNA metabolism, including mRNA stability and translation, and is highly prevalent in the brain.

RESULTS

We show that m6A modification displays temporal and spatial dynamics during neurodevelopment and aging. Genes that are temporally differentially methylated are more prone to have mRNA expression changes and affect many pathways associated with nervous system development. Furthermore, m6A shows a distinct tissue-specific methylation profile, which is most pronounced in the hypothalamus. Tissue-specific methylation is associated with an increase in mRNA expression and is associated with tissue-specific developmental processes. During the aging process, we observe significantly more m6A sites as age increases, in both mouse and human. We show a high level of overlap between mouse and human; however, humans at both young and old ages consistently show more m6A sites compared to mice. Differential m6A sites are found to be enriched in alternative untranslated regions of genes that affect aging-related pathways. These m6A sites are associated with a strong negative effect on mRNA expression. We also show that many Alzheimer-related transcripts exhibit decreased m6A methylation in a mouse model of Alzheimer's disease, which is correlated with reduced protein levels.

CONCLUSIONS

Our results suggest that m6A exerts a critical function in both early and late brain development in a spatio-temporal fashion. Furthermore, m6A controls protein levels of key genes involved in Alzheimer's disease-associated pathways, suggesting that m6A plays an important role in aging and neurodegenerative disease.

A long isoform of GIV/Girdin contains a PDZ-binding module that regulates localization and G-protein binding

PDZ domains are one of the most abundant protein domains in eukaryotes and are frequently found on junction-localized scaffold proteins. Various signaling molecules bind to PDZ proteins via PDZ-binding motifs (PBM) and fine-tune cellular signaling. However, how such interaction affects protein function is difficult to predict and must be solved empirically. Here we describe a long isoform of the guanine nucleotide exchange factor GIV/Girdin (CCDC88A) that we named GIV-L, which is conserved throughout evolution, from invertebrates to vertebrates, and contains a PBM. Unlike GIV, which lacks PBM and is cytosolic, GIV-L localizes onto cell junctions and has a PDZ interactome (as shown through annotating Human Cell Map and BioID-proximity labeling studies), which impacts GIV-L's ability to bind and activate trimeric G-protein, Gαi, through its guanine-nucleotide exchange modulator (GEM) module. This GEM module is found exclusively in vertebrates. We propose that the two functional modules in GIV may have evolved sequentially: the ability to bind PDZ proteins via the PBM evolved earlier in invertebrates, whereas G-protein binding and activation may have evolved later only among vertebrates. Phenotypic studies in Caco-2 cells revealed that GIV and GIV-L may have antagonistic effects on cell growth, proliferation (cell cycle), and survival. Immunohistochemical analysis in human colon tissues showed that GIV expression increases with a concomitant decrease in GIV-L during cancer initiation. Taken together, these findings reveal how regulation in GIV/CCDC88A transcript helps to achieve protein modularity, which allows the protein to play opposing roles either as a tumor suppressor (GIV-L) or as an oncogene (GIV).

The oncofetal RNA-binding protein IGF2BP1 is a druggable, post-transcriptional super-enhancer of E2F-driven gene expression in cancer

The IGF2 mRNA-binding protein 1 (IGF2BP1) is a non-catalytic post-transcriptional enhancer of tumor growth upregulated and associated with adverse prognosis in solid cancers. However, conserved effector pathway(s) and the feasibility of targeting IGF2BP1 in cancer remained elusive. We reveal that IGF2BP1 is a post-transcriptional enhancer of the E2F-driven hallmark in solid cancers. IGF2BP1 promotes G1/S cell cycle transition by stabilizing mRNAs encoding positive regulators of this checkpoint like E2F1. This IGF2BP1-driven shortening of the G1 cell cycle phase relies on 3′UTR-, miRNA- and m⁶A-dependent regulation and suggests enhancement of cell cycle progression by m⁶A-modifications across cancers. In addition to E2F transcription factors, IGF2BP1 also stabilizes E2F-driven transcripts directly indicating post-transcriptional ‘super’-enhancer role of the protein in E2F-driven gene expression in cancer. The small molecule BTYNB disrupts this enhancer function by impairing IGF2BP1-RNA association. Consistently, BTYNB interferes with E2F-driven gene expression and tumor growth in experimental mouse tumor models.

REW-ISA: unveiling local functional blocks in epi-transcriptome profiling data via an RNA expression-weighted iterative signature algorithm

Background

Recent studies have shown that N⁶-methyladenosine (m⁶A) plays a critical role in numbers of biological processes and complex human diseases. However, the regulatory mechanisms of most methylation sites remain uncharted. Thus, in-depth study of the epi-transcriptomic patterns of m⁶A may provide insights into its complex functional and regulatory mechanisms.

Results

Due to the high economic and time cost of wet experimental methods, revealing methylation patterns through computational models has become a more preferable way, and drawn more and more attention. Considering the theoretical basics and applications of conventional clustering methods, an RNA Expression Weighted Iterative Signature Algorithm (REW-ISA) is proposed to find potential local functional blocks (LFBs) based on MeRIP-Seq data, where sites are hyper-methylated or hypo-methylated simultaneously across the specific conditions. REW-ISA adopts RNA expression levels of each site as weights to make sites of lower expression level less significant. It starts from random sets of sites, then follows iterative search strategies by thresholds of rows and columns to find the LFBs in m⁶A methylation profile. Its application on MeRIP-Seq data of 69,446 methylation sites under 32 experimental conditions unveiled 6 LFBs, which achieve higher enrichment scores than ISA. Pathway analysis and enzyme specificity test showed that sites remained in LFBs are highly relevant to the m⁶A methyltransferase, such as METTL3, METTL14, WTAP and KIAA1429. Further detailed analyses for each LFB even showed that some LFBs are condition-specific, indicating that methylation profiles of some specific sites may be condition relevant.

Conclusions

REW-ISA finds potential local functional patterns presented in m⁶A profiles, where sites are co-methylated under specific conditions.

Evolution of Modularity, Interactome and Functions of GIV/Girdin (CCDC88A) from Invertebrates to Vertebrates.. [DOI: 10.1101/2020.09.28.317172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

PDZ domains are one of the most abundant protein domains in eukaryotes and frequently found on junction-localized scaffold proteins. Various signaling molecules bind to PDZ proteins via PDZ-binding motifs (PBM) and finetune cellular signaling. Here we describe the presence of a PBM on GIV/Girdin (CCDC88A) that is conserved throughout evolution, from invertebrates to vertebrates, and is generated as a long isoform-variant in humans, which we named GIV-L. Unlike GIV, which lacks PBM and is cytosolic, GIV-L localizes to the cell junctions, and has a unique PDZ-interactome, which impacts GIV-L’s ability to bind and activate trimeric G-protein, Gi through its guanine-nucleotide exchange modulator (GEM) module; the GEM module is found exclusively in vertebrates. Thus, the two functional modules in GIV evolved sequentially: the ability to bind PDZ proteins via the PBM evolved earlier in invertebrates, whereas G-protein binding and activation may have evolved later only among vertebrates. Phenotypic studies in Caco-2 cells revealed that GIV and GIV-L may have antagonistic effects on cell growth, proliferation (cell cycle), and survival. Immunohistochemical analyses in human colon tissues showed that GIV expression increases with a concomitant decrease in GIV-L during cancer initiation. Taken together, these findings reveal how GIV/CCDC88A in humans displays evolutionary flexibility in modularity, which allows the resultant isoforms to play opposing roles either as a tumor suppressor (GIV-L) or as an oncogene (GIV).

Adenylate Kinase 4 Modulates the Resistance of Breast Cancer Cells to Tamoxifen through an m6A-Based Epitranscriptomic Mechanism

N⁶-methyladenosine (m⁶A) is the most abundant internal modification in mRNA and this methylation constitutes an important regulatory mechanism for the stability and translational efficiency of mRNA. In this study, we found that the protein levels of adenylate kinase 4 (AK4) and m⁶A writer METTL3 are significantly higher in tamoxifen-resistant (TamR) MCF-7 cells than in parental cells. The TamR MCF-7 cells also exhibit increased methylation at multiple m⁶A consensus motif sites in the 5' untranslated region (5' UTR) of AK4 mRNA, and genetic depletion of METTL3 in TamR MCF-7 cells led to a diminished AK4 protein level and attenuated resistance to tamoxifen. In addition, we observed augmented levels of reactive oxygen species (ROS) and p38 activity in TamR MCF-7 cells, and both are diminished upon genetic depletion of AK4. Reciprocally, overexpression of AK4 in MCF-7 cells stimulates ROS and p38 phosphorylation levels, and it suppresses mitochondrial apoptosis. Moreover, scavenging of intracellular ROS leads to reduced p38 activity and re-sensitizes TamR MCF-7 cells to tamoxifen. Thus, our results uncover a novel m⁶A-mediated epitranscriptomic mechanism for the regulation of AK4, illustrate the cellular pathways through which increased AK4 expression contributes to tamoxifen resistance, and reveal AK4 as a potential therapeutic target for overcoming tamoxifen resistance.

A Census and Categorization Method of Epitranscriptomic Marks

In the past few years, thorough investigation of chemical modifications operated in the cells on ribonucleic acid (RNA) molecules is gaining momentum. This new field of research has been dubbed “epitranscriptomics”, in analogy to best-known epigenomics, to stress the potential of ensembles of RNA modifications to constitute a post-transcriptional regulatory layer of gene expression orchestrated by writer, reader, and eraser RNA-binding proteins (RBPs). In fact, epitranscriptomics aims at identifying and characterizing all functionally relevant changes involving both non-substitutional chemical modifications and editing events made to the transcriptome. Indeed, several types of RNA modifications that impact gene expression have been reported so far in different species of cellular RNAs, including ribosomal RNAs, transfer RNAs, small nuclear RNAs, messenger RNAs, and long non-coding RNAs. Supporting functional relevance of this largely unknown regulatory mechanism, several human diseases have been associated directly to RNA modifications or to RBPs that may play as effectors of epitranscriptomic marks. However, an exhaustive epitranscriptome’s characterization, aimed to systematically classify all RNA modifications and clarify rules, actors, and outcomes of this promising regulatory code, is currently not available, mainly hampered by lack of suitable detecting technologies. This is an unfortunate limitation that, thanks to an unprecedented pace of technological advancements especially in the sequencing technology field, is likely to be overcome soon. Here, we review the current knowledge on epitranscriptomic marks and propose a categorization method based on the reference ribonucleotide and its rounds of modifications (“stages”) until reaching the given modified form. We believe that this classification scheme can be useful to coherently organize the expanding number of discovered RNA modifications.

Bioinformatics approaches for deciphering the epitranscriptome: Recent progress and emerging topics

Post-transcriptional RNA modification occurs on all types of RNA and plays a vital role in regulating every aspect of RNA function. Thanks to the development of high-throughput sequencing technologies, transcriptome-wide profiling of RNA modifications has been made possible. With the accumulation of a large number of high-throughput datasets, bioinformatics approaches have become increasing critical for unraveling the epitranscriptome. We review here the recent progress in bioinformatics approaches for deciphering the epitranscriptomes, including epitranscriptome data analysis techniques, RNA modification databases, disease-association inference, general functional annotation, and studies on RNA modification site prediction. We also discuss the limitations of existing approaches and offer some future perspectives.

Oocyte competence is maintained by m6A methyltransferase KIAA1429-mediated RNA metabolism during mouse follicular development

KIAA1429 (also known as vir-like m⁶A methyltransferase-associated protein (VIRMA)), a newly identified component of the RNA m⁶A methyltransferase complex, plays critical roles in guiding region-selective m⁶A deposition. However, in mammals, whether KIAA1429 mediates RNA m⁶A regulatory pathway functions in vivo remains unknown. Here, we show that the Kiaa1429-specific deficiency in oocytes resulted in female infertility with defective follicular development and fully grown germinal vesicle (GV) oocytes failing to undergo germinal vesicle breakdown (GVBD) and consequently losing the ability to resume meiosis. The oocyte growth is accompanied by the accumulation of abundant RNAs and posttranscriptional regulation. We found that the loss of Kiaa1429 could also lead to abnormal RNA metabolism in GV oocytes. RNA-seq profiling revealed that Kiaa1429 deletion altered the expression pattern of the oocyte-derived factors essential for follicular development. In addition, our data show that the conditional depletion of Kiaa1429 decreased the m⁶A levels in oocytes and mainly affected the alternative splicing of genes associated with oogenesis. In summary, the m⁶A methyltransferase KIAA1429-mediated RNA metabolism plays critical roles in folliculogenesis and the maintenance of oocyte competence.

Are Small Nucleolar RNAs "CRISPRable"? A Report on Box C/D Small Nucleolar RNA Editing in Human Cells

CRISPR technologies are nowadays widely used for targeted knockout of numerous protein-coding genes and for the study of various processes and metabolic pathways in human cells. Most attention in the genome editing field is now focused on the cleavage of protein-coding genes or genes encoding long non-coding RNAs (lncRNAs), while the studies on targeted knockout of intron-encoded regulatory RNAs are sparse. Small nucleolar RNAs (snoRNAs) present a class of non-coding RNAs encoded within the introns of various host genes and involved in post-transcriptional maturation of ribosomal RNAs (rRNAs) in eukaryotic cells. Box C/D snoRNAs direct 2'-O-methylation of rRNA nucleotides. These short RNAs have specific elements in their structure, namely, boxes C and D, and a target-recognizing region. Here, we present the study devoted to CRISPR/Cas9-mediated editing of box C/D snoRNA genes in Gas5. We obtained monoclonal cell lines carrying mutations in snoRNA genes and analyzed the levels of the mutant box C/D snoRNA as well as the 2'-O-methylation status of the target rRNA nucleotide in the obtained cells. Mutations in SNORD75 in the obtained monoclonal cell line were shown to result in aberrant splicing of Gas5 with exclusion of exons 3 to 5, which was confirmed by RT-PCR and RNA-Seq. The obtained results suggest that SNORD75 contains an element for binding of some factors regulating maturation of Gas5 pre-lncRNA. We suggest that METTL3/METTL14 is among such factors, and m⁶A-methylation pathways are involved in regulation of Gas5 splicing. Our results shell light on the role of SNORDs in regulating splicing of the host gene.

In search of the mRNA modification landscape in plants

BACKGROUND

Precise regulation of gene expression is indispensable for the proper functioning of organisms in both optimal and challenging conditions. The most commonly known regulative mechanisms include the modulation of transcription, translation and adjustment of the transcript, and protein half-life. New players have recently emerged in the arena of gene expression regulators - chemical modifications of mRNAs.

MAIN TEXT

The latest studies show that modified ribonucleotides affect transcript splicing, localization, secondary structures, interaction with other molecules and translation efficiency. Thus far, attention has been focused mostly on the most widespread mRNA modification - adenosine methylation at the N6 position (m6A). However, initial reports on the formation and possible functions of other modified ribonucleotides, such as cytosine methylated at the 5' position (m5C), 8-hydroxyguanosine (8-OHG) and 8-nitroguanosine (8-NO2G), have started to appear in the literature. Additionally, some reports indicate that pseudouridine (Ψ) is present in mRNAs and might perform important regulatory functions in eukaryotic cells. The present review summarizes current knowledge regarding the above-mentioned modified ribonucleotides (m6A, m5C, 8-OHG, 8-NO2G) in transcripts across various plant species, including Arabidopsis, rice, sunflower, wheat, soybean and potato.

CONCLUSIONS

Chemical modifications of ribonucleotides affect mRNA stability and translation efficiency. They thus constitute a newly discovered layer of gene expression regulation and have a profound effect on the development and functioning of various organisms, including plants.

N6-methyladenosine modification of ITGA6 mRNA promotes the development and progression of bladder cancer

Background

Accumulating evidence has revealed the critical roles of N⁶-methyladenosine (m⁶A) modification of mRNA in various cancers. However, the biological function and regulation of m⁶A in bladder cancer (BC) are not yet fully understood.

Methods

We performed cell phenotype analysis and established in vivo mouse xenograft models to assess the effects of m⁶A-modified ITGA6 on BC growth and progression. Methylated RNA immunoprecipitation (MeRIP), RNA immunoprecipitation and luciferase reporter and mutagenesis assays were used to define the mechanism of m⁶A-modified ITGA6. Immunohistochemical analysis was performed to assess the correlation between METTL3 and ITGA6 expression in bladder cancer patients.

Findings

We show that the m⁶A writer METTL3 and eraser ALKBH5 altered cell adhesion by regulating ITGA6 expression in bladder cancer cells. Moreover, upregulation of ITGA6 is correlated with the increase in METTL3 expression in human BC tissues, and higher expression of ITGA6 in patients indicates a lower survival rate. Mechanistically, m⁶A is highly enriched within the ITGA6 transcripts, and increased m⁶A methylations of the ITGA6 mRNA 3’UTR promotes the translation of ITGA6 mRNA via binding of the m⁶A readers YTHDF1 and YTHDF3. Inhibition of ITGA6 results in decreased growth and progression of bladder cancer cells in vitro and in vivo. Furthermore, overexpression of ITGA6 in METTL3-depleted cells partially restores the BC adhesion, migration and invasion phenotypes.

Interpretation

Our results demonstrate an oncogenic role of m⁶A-modified ITGA6 and show its regulatory mechanisms in BC development and progression, thus identifying a potential therapeutic target for BC.

Fund

This work was supported by National Natural Science Foundation of China (81772699, 81472999).

m6AVar: a database of functional variants involved in m6A modification

Identifying disease-causing variants among a large number of single nucleotide variants (SNVs) is still a major challenge. Recently, N⁶-methyladenosine (m⁶A) has become a research hotspot because of its critical roles in many fundamental biological processes and a variety of diseases. Therefore, it is important to evaluate the effect of variants on m⁶A modification, in order to gain a better understanding of them. Here, we report m6AVar (http://m6avar.renlab.org), a comprehensive database of m⁶A-associated variants that potentially influence m⁶A modification, which will help to interpret variants by m⁶A function. The m⁶A-associated variants were derived from three different m⁶A sources including miCLIP/PA-m⁶A-seq experiments (high confidence), MeRIP-Seq experiments (medium confidence) and transcriptome-wide predictions (low confidence). Currently, m6AVar contains 16 132 high, 71 321 medium and 326 915 low confidence level m⁶A-associated variants. We also integrated the RBP-binding regions, miRNA-targets and splicing sites associated with variants to help users investigate the effect of m⁶A-associated variants on post-transcriptional regulation. Because it integrates the data from genome-wide association studies (GWAS) and ClinVar, m6AVar is also a useful resource for investigating the relationship between the m⁶A-associated variants and disease. Overall, m6AVar will serve as a useful resource for annotating variants and identifying disease-causing variants.

Arabidopsis ABF3 and ABF4 Transcription Factors Act with the NF-YC Complex to Regulate SOC1 Expression and Mediate Drought-Accelerated Flowering

The drought-escape response accelerates flowering in response to drought stress, allowing plants to adaptively shorten their life cycles. Abscisic acid (ABA) mediates plant responses to drought, but the role of ABA-responsive element (ABRE)-binding factors (ABFs) in the drought-escape response is poorly understood. Here, we show that Arabidopsis thaliana ABF3 and ABF4 regulate flowering in response to drought through transcriptional regulation of the floral integrator SUPPRESSOR OF OVEREXPRESSION OF CONSTANS1 (SOC1). The abf3 abf4 mutant displayed ABA-insensitive late flowering under long-day conditions. Ectopic expression of ABF3 or ABF4 in the vasculature, but not in the shoot apex, induced early flowering, whereas expression of ABF3 fused with the SRDX transcriptional repressor domain delayed flowering. We identified SOC1 as a direct downstream target of ABF3/4, and found that SOC1 mRNA levels were lower in abf3 abf4 than in wild-type plants. Moreover, induction of SOC1 by ABA was hampered in abf3 abf4 mutants. ABF3 and ABF4 were enriched at the -1028- to -657-bp region of the SOC1 promoter, which does not contain canonical ABF-ABRE-binding motifs but has the NF-Y binding element. We found that ABF3 and ABF4 interact with nuclear factor Y subunit C (NF-YC) 3/4/9 in vitro and in planta, and induction of SOC1 by ABA was hampered in nf-yc3 yc4 yc9 mutants. Interestingly, the abf3 abf4, nf-yc3 yc4 yc9, and soc1 mutants displayed a reduced drought-escape response. Taken together, these results suggest that ABF3 and ABF4 act with NF-YCs to promote flowering by inducing SOC1 transcription under drought conditions. This mechanism might contribute to adaptation by enabling plants to complete their life cycles under drought stress.

FTO affects hippocampal function by regulation of BDNF processing

Initially, the function of the fat mass and obesity associated (Fto) gene seemed to be primarily the regulation of the body weight. Here we show that loss of Fto results in a hyperactivation of the hypothalamic-pituitary-adrenal (HPA) axis. In consequence, Fto-/- mice display an anxiety-like behavior and impairments in working memory. Furthermore, differentiation of neurons is affected in the hippocampus. As a cause of these impairments we identified a processing defect of the neurotrophin BDNF which is most likely the result of a reduced expression of MMP-9. Therefore, we propose FTO as a possible new target to develop novel approaches for the treatment of diseases associated with hippocampal disorders. In parallel, we also would like to make the point that any anti-obesity therapy via blocking FTO function can have negative effects on the proper function of the hippocampus.

Clustering Count-based RNA Methylation Data Using a Nonparametric Generative Model

Background:

RNA methylome has been discovered as an important layer of gene regulation and can be profiled directly with count-based measurements from high-throughput sequencing data. Although the detailed regulatory circuit of the epitranscriptome remains uncharted, clustering effect in methylation status among different RNA methylation sites can be identified from transcriptome-wide RNA methylation profiles and may reflect the epitranscriptomic regulation. Count-based RNA methylation sequencing data has unique features, such as low reads coverage, which calls for novel clustering approaches. <P><P> Objective: Besides the low reads coverage, it is also necessary to keep the integer property to approach clustering analysis of count-based RNA methylation sequencing data. <P><P> Method: We proposed a nonparametric generative model together with its Gibbs sampling solution for clustering analysis. The proposed approach implements a beta-binomial mixture model to capture the clustering effect in methylation level with the original count-based measurements rather than an estimated continuous methylation level. Besides, it adopts a nonparametric Dirichlet process to automatically determine an optimal number of clusters so as to avoid the common model selection problem in clustering analysis. <P><P> Results: When tested on the simulated system, the method demonstrated improved clustering performance over hierarchical clustering, K-means, MClust, NMF and EMclust. It also revealed on real dataset two novel RNA N6-methyladenosine (m6A) co-methylation patterns that may be induced directly by METTL14 and WTAP, which are two known regulatory components of the RNA m6A methyltransferase complex. <P><P> Conclusion: Our proposed DPBBM method not only properly handles the count-based measurements of RNA methylation data from sites of very low reads coverage, but also learns an optimal number of clusters adaptively from the data analyzed. <P><P> Availability: The source code and documents of DPBBM R package are freely available through the Comprehensive R Archive Network (CRAN): https://cran.r-project.org/web/packages/DPBBM/.

RNA modifications in structure prediction - Status quo and future challenges

Chemical modifications of RNA nucleotides change their identity and characteristics and thus alter genetic and structural information encoded in the genomic DNA. tRNA and rRNA are probably the most heavily modified genes, and often depend on derivatization or isomerization of their nucleobases in order to correctly fold into their functional structures. Recent RNomics studies, however, report transcriptome wide RNA modification and suggest a more general regulation of structuredness of RNAs by this so called epitranscriptome. Modification seems to require specific substrate structures, which in turn are stabilized or destabilized and thus promote or inhibit refolding events of regulatory RNA structures. In this review, we revisit RNA modifications and the related structures from a computational point of view. We discuss known substrate structures, their properties such as sub-motifs as well as consequences of modifications on base pairing patterns and possible refolding events. Given that efficient RNA structure prediction methods for canonical base pairs have been established several decades ago, we review to what extend these methods allow the inclusion of modified nucleotides to model and study epitranscriptomic effects on RNA structures.

Imbalance learning for the prediction of N6-Methylation sites in mRNAs

Background

N⁶-methyladenosine (m⁶A) is an important epigenetic modification which plays various roles in mRNA metabolism and embryogenesis directly related to human diseases. To identify m⁶A in a large scale, machine learning methods have been developed to make predictions on m⁶A sites. However, there are two main drawbacks of these methods. The first is the inadequate learning of the imbalanced m⁶A samples which are much less than the non-m⁶A samples, by their balanced learning approaches. Second, the features used by these methods are not outstanding to represent m⁶A sequence characteristics.

Results

We propose to use cost-sensitive learning ideas to resolve the imbalance data issues in the human mRNA m⁶A prediction problem. This cost-sensitive approach applies to the entire imbalanced dataset, without random equal-size selection of negative samples, for an adequate learning. Along with site location and entropy features, top-ranked positions with the highest single nucleotide polymorphism specificity in the window sequences are taken as new features in our imbalance learning. On an independent dataset, our overall prediction performance is much superior to the existing predictors. Our method shows stronger robustness against the imbalance changes in the tests on 9 datasets whose imbalance ratios range from 1:1 to 9:1. Our method also outperforms the existing predictors on 1226 individual transcripts. It is found that the new types of features are indeed of high significance in the m⁶A prediction. The case studies on gene c-Jun and CBFB demonstrate the detailed prediction capacity to improve the prediction performance.

Conclusion

The proposed cost-sensitive model and the new features are useful in human mRNA m⁶A prediction. Our method achieves better correctness and robustness than the existing predictors in independent test and case studies. The results suggest that imbalance learning is promising to improve the performance of m⁶A prediction.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4928-y) contains supplementary material, which is available to authorized users.

Above the Epitranscriptome: RNA Modifications and Stem Cell Identity

Sequence databases and transcriptome-wide mapping have revealed different reversible and dynamic chemical modifications of the nitrogen bases of RNA molecules. Modifications occur in coding RNAs and noncoding-RNAs post-transcriptionally and they can influence the RNA structure, metabolism, and function. The result is the expansion of the variety of the transcriptome. In fact, depending on the type of modification, RNA molecules enter into a specific program exerting the role of the player or/and the target in biological and pathological processes. Many research groups are exploring the role of RNA modifications (alias epitranscriptome) in cell proliferation, survival, and in more specialized activities. More recently, the role of RNA modifications has been also explored in stem cell biology. Our understanding in this context is still in its infancy. Available evidence addresses the role of RNA modifications in self-renewal, commitment, and differentiation processes of stem cells. In this review, we will focus on five epitranscriptomic marks: N6-methyladenosine, N1-methyladenosine, 5-methylcytosine, Pseudouridine (Ψ) and Adenosine-to-Inosine editing. We will provide insights into the function and the distribution of these chemical modifications in coding RNAs and noncoding-RNAs. Mainly, we will emphasize the role of epitranscriptomic mechanisms in the biology of naïve, primed, embryonic, adult, and cancer stem cells.

Enhancing Epitranscriptome Module Detection from m6A-Seq Data Using Threshold-Based Measurement Weighting Strategy

To date, with well over 100 different types of RNA modifications associated with various molecular functions identified on diverse types of RNA molecules, the epitranscriptome has emerged to be an important layer for gene expression regulation. It is of crucial importance and increasing interest to understand how the epitranscriptome is regulated to facilitate different biological functions from a global perspective, which may be carried forward by finding biologically meaningful epitranscriptome modules that respond to upstream epitranscriptome regulators and lead to downstream biological functions; however, due to the intrinsic properties of RNA molecules, RNA modifications, and relevant sequencing technique, the epitranscriptome profiled from high-throughput sequencing approaches often suffers from various artifacts, jeopardizing the effectiveness of epitranscriptome modules identification when using conventional approaches. To solve this problem, we developed a convenient measurement weighting strategy, which can largely tolerate the artifacts of high-throughput sequencing data. We demonstrated on real data that the proposed measurement weighting strategy indeed brings improved performance in epitranscriptome module discovery in terms of both module accuracy and biological significance. Although the new approach is integrated with Euclidean distance measurement in a hierarchical clustering scenario, it has great potential to be extended to other distance measurements and algorithms as well for addressing various tasks in epitranscriptome analysis. Additionally, we show for the first time with rigorous statistical analysis that the epitranscriptome modules are biologically meaningful with different GO functions enriched, which established the functional basis of epitranscriptome modules, fulfilled a key prerequisite for functional characterization, and deciphered the epitranscriptome and its regulation.

RNA N6-methyladenosine methyltransferase-like 3 promotes liver cancer progression through YTHDF2-dependent posttranscriptional silencing of SOCS2

Epigenetic alterations have contributed greatly to human carcinogenesis. Conventional epigenetic studies have predominantly focused on DNA methylation, histone modifications, and chromatin remodeling. Recently, diverse and reversible chemical modifications of RNAs have emerged as a new layer of epigenetic regulation. N6-methyladenosine (m6A) is the most abundant chemical modification of eukaryotic messenger RNA (mRNA) and is important for the regulation of mRNA stability, splicing, and translation. Using transcriptome sequencing, we discovered that methyltransferase-like 3 (METTL3), a major RNA N6-adenosine methyltransferase, was significantly up-regulated in human hepatocellular carcinoma (HCC) and multiple solid tumors. Clinically, overexpression of METTL3 is associated with poor prognosis of patients with HCC. Functionally, we proved that knockdown of METTL3 drastically reduced HCC cell proliferation, migration, and colony formation in vitro. Knockout of METTL3 remarkably suppressed HCC tumorigenicity and lung metastasis in vivo. On the other hand, using the CRISPR/dCas9-VP64 activation system, we demonstrated that overexpression of METTL3 significantly promoted HCC growth both in vitro and in vivo. Through transcriptome sequencing, m6A sequencing, and m6A methylated RNA immuno-precipitation quantitative reverse-transcription polymerase chain reaction, we identified suppressor of cytokine signaling 2 (SOCS2) as a target of METTL3-mediated m6A modification. Knockdown of METTL3 substantially abolished SOCS2 mRNA m6A modification and augmented SOCS2 mRNA expression. We also showed that m6A-mediated SOCS2 mRNA degradation relied on the m6A reader protein YTHDF2-dependent pathway.

CONCLUSION

METTL3 is frequently up-regulated in human HCC and contributes to HCC progression. METTL3 represses SOCS2 expression in HCC through an m6A-YTHDF2-dependent mechanism. Our findings suggest an important mechanism of epigenetic alteration in liver carcinogenesis. (Hepatology 2018;67:2254-2270).

Comparative Analysis of Human Genes Frequently and Occasionally Regulated by m6A Modification

The m⁶A modification has been implicated as an important epitranscriptomic marker, which plays extensive roles in the regulation of transcript stability, splicing, translation, and localization. Nevertheless, only some genes are repeatedly modified across various conditions and the principle of m⁶A regulation remains elusive. In this study, we performed a systems-level analysis of human genes frequently regulated by m⁶A modification (m⁶Afreq genes) and those occasionally regulated by m⁶A modification (m⁶Aocca genes). Compared to the m⁶Aocca genes, the m⁶Afreq genes exhibit gene importance-related features, such as lower dN/dS ratio, higher protein–protein interaction network degree, and reduced tissue expression specificity. Signaling network analysis indicates that the m⁶Afreq genes are associated with downstream components of signaling cascades, high-linked signaling adaptors, and specific network motifs like incoherent feed forward loops. Moreover, functional enrichment analysis indicates significant overlaps between the m⁶Afreq genes and genes involved in various layers of gene expression, such as being the microRNA targets and the regulators of RNA processing. Therefore, our findings suggest the potential interplay between m⁶A epitranscriptomic regulation and other gene expression regulatory machineries.

MeT-DB V2.0: elucidating context-specific functions of N6-methyl-adenosine methyltranscriptome

Methyltranscriptome is an exciting new area that studies the mechanisms and functions of methylation in transcripts. A knowledge base with the systematic collection and curation of context specific transcriptome-wide methylations is critical for elucidating their biological functions as well as for developing bioinformatics tools. Since its inception in 2014, the Met-DB (Liu, H., Flores, M.A., Meng, J., Zhang, L., Zhao, X., Rao, M.K., Chen, Y. and Huang, Y. (2015) MeT-DB: a database of transcriptome methylation in mammalian cells. Nucleic Acids Res., 43, D197-D203), has become an important resource for methyltranscriptome, especially in the N6-methyl-adenosine (m6A) research community. Here, we report Met-DB v2.0, the significantly improved second version of Met-DB, which is entirely redesigned to focus more on elucidating context-specific m6A functions. Met-DB v2.0 has a major increase in context-specific m6A peaks and single-base sites predicted from 185 samples for 7 species from 26 independent studies. Moreover, it is also integrated with a new database for targets of m6A readers, erasers and writers and expanded with more collections of functional data. The redesigned Met-DB v2.0 web interface and genome browser provide more friendly, powerful, and informative ways to query and visualize the data. More importantly, MeT-DB v2.0 offers for the first time a series of tools specifically designed for understanding m6A functions. Met-DB V2.0 will be a valuable resource for m6A methyltranscriptome research. The Met-DB V2.0 database is available at http://compgenomics.utsa.edu/MeTDB/ and http://www.xjtlu.edu.cn/metdb2.

The RNA m6A Reader YTHDF2 Is Essential for the Post-transcriptional Regulation of the Maternal Transcriptome and Oocyte Competence

YTHDF2 binds and destabilizes N⁶-methyladenosine (m⁶A)-modified mRNA. The extent to which this branch of m⁶A RNA-regulatory pathway functions in vivo and contributes to mammalian development remains unknown. Here we find that YTHDF2 deficiency is partially permissive in mice and results in female-specific infertility. Using conditional mutagenesis, we demonstrate that YTHDF2 is autonomously required within the germline to produce MII oocytes that are competent to sustain early zygotic development. Oocyte maturation is associated with a wave of maternal RNA degradation, and the resulting relative changes to the MII transcriptome are integral to oocyte quality. The loss of YTHDF2 results in the failure to regulate transcript dosage of a cohort of genes during oocyte maturation, with enrichment observed for the YTHDF2-binding consensus and evidence of m⁶A in these upregulated genes. In summary, the m⁶A-reader YTHDF2 is an intrinsic determinant of mammalian oocyte competence and early zygotic development.

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YTHDF2 deficiency is partially permissive in mice and required for female fertility

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YTHDF2 is maternally required for early zygotic development

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YTHDF2 post-transcriptionally regulates transcript dosage during oocyte maturation

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Maternal YTHDF2 is a key determinant of mammalian egg quality

Distinct 5-methylcytosine profiles in poly(A) RNA from mouse embryonic stem cells and brain

BACKGROUND

Recent work has identified and mapped a range of posttranscriptional modifications in mRNA, including methylation of the N6 and N1 positions in adenine, pseudouridylation, and methylation of carbon 5 in cytosine (m5C). However, knowledge about the prevalence and transcriptome-wide distribution of m5C is still extremely limited; thus, studies in different cell types, tissues, and organisms are needed to gain insight into possible functions of this modification and implications for other regulatory processes.

RESULTS

We have carried out an unbiased global analysis of m5C in total and nuclear poly(A) RNA of mouse embryonic stem cells and murine brain. We show that there are intriguing differences in these samples and cell compartments with respect to the degree of methylation, functional classification of methylated transcripts, and position bias within the transcript. Specifically, we observe a pronounced accumulation of m5C sites in the vicinity of the translational start codon, depletion in coding sequences, and mixed patterns of enrichment in the 3' UTR. Degree and pattern of methylation distinguish transcripts modified in both embryonic stem cells and brain from those methylated in either one of the samples. We also analyze potential correlations between m5C and micro RNA target sites, binding sites of RNA binding proteins, and N6-methyladenosine.

CONCLUSION

Our study presents the first comprehensive picture of cytosine methylation in the epitranscriptome of pluripotent and differentiated stages in the mouse. These data provide an invaluable resource for future studies of function and biological significance of m5C in mRNA in mammals.

DiseaseMeth version 2.0: a major expansion and update of the human disease methylation database

The human disease methylation database (DiseaseMeth, http://bioinfo.hrbmu.edu.cn/diseasemeth/) is an interactive database that aims to present the most complete collection and annotation of aberrant DNA methylation in human diseases, especially various cancers. Recently, the high-throughput microarray and sequencing technologies have promoted the production of methylome data that contain comprehensive knowledge of human diseases. In this DiseaseMeth update, we have increased the number of samples from 3610 to 32 701, the number of diseases from 72 to 88 and the disease–gene associations from 216 201 to 679 602. DiseaseMeth version 2.0 provides an expanded comprehensive list of disease–gene associations based on manual curation from experimental studies and computational identification from high-throughput methylome data. Besides the data expansion, we also updated the search engine and visualization tools. In particular, we enhanced the differential analysis tools, which now enable online automated identification of DNA methylation abnormalities in human disease in a case-control or disease–disease manner. To facilitate further mining of the disease methylome, three new web tools were developed for cluster analysis, functional annotation and survival analysis. DiseaseMeth version 2.0 should be a useful resource platform for further understanding the molecular mechanisms of human diseases.

Guitar: An R/Bioconductor Package for Gene Annotation Guided Transcriptomic Analysis of RNA-Related Genomic Features

Biological features, such as genes and transcription factor binding sites, are often denoted with genome-based coordinates as the genomic features. While genome-based representation is usually very effective in correlating various biological features, it can be tedious to examine the relationship between RNA-related genomic features and the landmarks of RNA transcripts with existing tools due to the difficulty in the conversion between genome-based coordinates and RNA-based coordinates. We developed here an open source Guitar R/Bioconductor package for sketching the transcriptomic view of RNA-related biological features represented by genome based coordinates. Internally, Guitar package extracts the standardized RNA coordinates with respect to the landmarks of RNA transcripts, with which hundreds of millions of RNA-related genomic features can then be efficiently analyzed within minutes. We demonstrated the usage of Guitar package in analyzing posttranscriptional RNA modifications (5-methylcytosine and N6-methyladenosine) derived from high-throughput sequencing approaches (MeRIP-Seq and RNA BS-Seq) and show that RNA 5-methylcytosine (m⁵C) is enriched in 5′UTR. The newly developed Guitar R/Bioconductor package achieves stable performance on the data tested and revealed novel biological insights. It will effectively facilitate the analysis of RNA methylation data and other RNA-related biological features in the future.

SRAMP: prediction of mammalian N6-methyladenosine (m6A) sites based on sequence-derived features

N⁶-methyladenosine (m⁶A) is a prevalent RNA methylation modification involved in the regulation of degradation, subcellular localization, splicing and local conformation changes of RNA transcripts. High-throughput experiments have demonstrated that only a small fraction of the m⁶A consensus motifs in mammalian transcriptomes are modified. Therefore, accurate identification of RNA m⁶A sites becomes emergently important. For the above purpose, here a computational predictor of mammalian m⁶A site named SRAMP is established. To depict the sequence context around m⁶A sites, SRAMP combines three random forest classifiers that exploit the positional nucleotide sequence pattern, the K-nearest neighbor information and the position-independent nucleotide pair spectrum features, respectively. SRAMP uses either genomic sequences or cDNA sequences as its input. With either kind of input sequence, SRAMP achieves competitive performance in both cross-validation tests and rigorous independent benchmarking tests. Analyses of the informative features and overrepresented rules extracted from the random forest classifiers demonstrate that nucleotide usage preferences at the distal positions, in addition to those at the proximal positions, contribute to the classification. As a public prediction server, SRAMP is freely available at http://www.cuilab.cn/sramp/.

DRME: Count-based differential RNA methylation analysis at small sample size scenario

Differential methylation, which concerns difference in the degree of epigenetic regulation via methylation between two conditions, has been formulated as a beta or beta-binomial distribution to address the within-group biological variability in sequencing data. However, a beta or beta-binomial model is usually difficult to infer at small sample size scenario with discrete reads count in sequencing data. On the other hand, as an emerging research field, RNA methylation has drawn more and more attention recently, and the differential analysis of RNA methylation is significantly different from that of DNA methylation due to the impact of transcriptional regulation. We developed DRME to better address the differential RNA methylation problem. The proposed model can effectively describe within-group biological variability at small sample size scenario and handles the impact of transcriptional regulation on RNA methylation. We tested the newly developed DRME algorithm on simulated and 4 MeRIP-Seq case-control studies and compared it with Fisher's exact test. It is in principle widely applicable to several other RNA-related data types as well, including RNA Bisulfite sequencing and PAR-CLIP. The code together with an MeRIP-Seq dataset is available online (https://github.com/lzcyzm/DRME) for evaluation and reproduction of the figures shown in this article.

TSGene 2.0: an updated literature-based knowledgebase for tumor suppressor genes

Tumor suppressor genes (TSGs) are a major type of gatekeeper genes in the cell growth. A knowledgebase with the systematic collection and curation of TSGs in multiple cancer types is critically important for further studying their biological functions as well as for developing therapeutic strategies. Since its development in 2012, the Tumor Suppressor Gene database (TSGene), has become a popular resource in the cancer research community. Here, we reported the TSGene version 2.0, which has substantial updates of contents (e.g. up-to-date literature and pan-cancer genomic data collection and curation), data types (noncoding RNAs and protein-coding genes) and content accessibility. Specifically, the current TSGene 2.0 contains 1217 human TSGs (1018 protein-coding and 199 non-coding genes) curated from over 9000 articles. Additionally, TSGene 2.0 provides thousands of expression and mutation patterns derived from pan-cancer data of The Cancer Genome Atlas. A new web interface is available at http://bioinfo.mc.vanderbilt.edu/TSGene/. Systematic analyses of 199 non-coding TSGs provide numerous cancer-specific non-coding mutational events for further screening and clinical use. Intriguingly, we identified 49 protein-coding TSGs that were consistently down-regulated in 11 cancer types. In summary, TSGene 2.0, which is the only available database for TSGs, provides the most updated TSGs and their features in pan-cancer.