RMBase v3.0: decode the landscape, mechanisms and functions of RNA modifications.

Although over 170 chemical modifications have been identified, their prevalence, mechanism and function remain largely unknown. To enable integrated analysis of diverse RNA modification profiles, we have developed RMBase v3.0 (http://bioinformaticsscience.cn/rmbase/), a comprehensive platform consisting of eight modules. These modules facilitate the exploration of transcriptome-wide landscape, biogenesis, interactome and functions of RNA modifications. By mining thousands of epitranscriptome datasets with novel pipelines, the 'RNA Modifications' module reveals the map of 73 RNA modifications of 62 species. the 'Genes' module allows to retrieve RNA modification profiles and clusters by gene and transcript. The 'Mechanisms' module explores 23 382 enzyme-catalyzed or snoRNA-guided modified sites to elucidate their biogenesis mechanisms. The 'Co-localization' module systematically formulates potential correlations between 14 histone modifications and 6 RNA modifications in various cell-lines. The 'RMP' module investigates the differential expression profiles of 146 RNA-modifying proteins (RMPs) in 18 types of cancers. The 'Interactome' integrates the interactional relationships between 73 RNA modifications with RBP binding events, miRNA targets and SNPs. The 'Motif' illuminates the enriched motifs for 11 types of RNA modifications identified from epitranscriptome datasets. The 'Tools' introduces a novel web-based 'modGeneTool' for annotating modifications. Overall, RMBase v3.0 provides various resources and tools for studying RNA modifications.

TP53-inducible putative long noncoding RNAs encode functional polypeptides that suppress cell proliferation.

Polypeptides encoded by long noncoding RNAs (lncRNAs) are a novel class of functional molecules. However, whether these hidden polypeptides participate in the TP53 pathway and play a significant biological role is still unclear. Here, we discover that TP53-regulated lncRNAs can encode peptides, two of which are functional in various human cell lines. Using ribosome profiling and RNA-seq approaches in HepG2 cells, we systematically identified more than 300 novel TP53-regulated lncRNAs and further confirmed that 15 of these TP53-regulated lncRNAs encode peptides. Furthermore, several peptides were validated by mass spectrometry. Ten of the novel translational lncRNAs are directly inducible by TP53 in response to DNA damage. We show that the TP53-inducible peptides TP53LC02 and TP53LC04, but not their lncRNAs, can suppress cell proliferation. TP53LC04 peptide also has a function associated with cell proliferation by regulating the cell cycle in response to DNA damage. This study shows that TP53-regulated lncRNAs can encode new functional peptides, leading to the expansion of the TP53 tumor-suppressor network and providing novel potential targets for cancer therapy.

Histone H3 trimethylation at lysine 36 guides m6A RNA modification co-transcriptionally.

DNA and histone modifications have notable effects on gene expression1. Being the most prevalent internal modification in mRNA, the N6-methyladenosine (m6A) mRNA modification is as an important post-transcriptional mechanism of gene regulation2-4 and has crucial roles in various normal and pathological processes5-12. However, it is unclear how m6A is specifically and dynamically deposited in the transcriptome. Here we report that histone H3 trimethylation at Lys36 (H3K36me3), a marker for transcription elongation, guides m6A deposition globally. We show that m6A modifications are enriched in the vicinity of H3K36me3 peaks, and are reduced globally when cellular H3K36me3 is depleted. Mechanistically, H3K36me3 is recognized and bound directly by METTL14, a crucial component of the m6A methyltransferase complex (MTC), which in turn facilitates the binding of the m6A MTC to adjacent RNA polymerase II, thereby delivering the m6A MTC to actively transcribed nascent RNAs to deposit m6A co-transcriptionally. In mouse embryonic stem cells, phenocopying METTL14 knockdown, H3K36me3 depletion also markedly reduces m6A abundance transcriptome-wide and in pluripotency transcripts, resulting in increased cell stemness. Collectively, our studies reveal the important roles of H3K36me3 and METTL14 in determining specific and dynamic deposition of m6A in mRNA, and uncover another layer of gene expression regulation that involves crosstalk between histone modification and RNA methylation.

tModBase: deciphering the landscape of tRNA modifications and their dynamic changes from epitranscriptome data.

tRNA molecules contain dense, abundant modifications that affect tRNA structure, stability, mRNA decoding and tsRNA formation. tRNA modifications and related enzymes are responsive to environmental cues and are associated with a range of physiological and pathological processes. However, there is a lack of resources that can be used to mine and analyse these dynamically changing tRNA modifications. In this study, we established tModBase (https://www.tmodbase.com/) for deciphering the landscape of tRNA modification profiles from epitranscriptome data. We analysed 103 datasets generated with second- and third-generation sequencing technologies and illustrated the misincorporation and termination signals of tRNA modification sites in ten species. We thus systematically demonstrate the modification profiles across different tissues/cell lines and summarize the characteristics of tRNA-associated human diseases. By integrating transcriptome data from 32 cancers, we developed novel tools for analysing the relationships between tRNA modifications and RNA modification enzymes, the expression of 1442 tRNA-derived small RNAs (tsRNAs), and 654 DNA variations. Our database will provide new insights into the features of tRNA modifications and the biological pathways in which they participate.

ChIPBase v3.0: the encyclopedia of transcriptional regulations of non-coding RNAs and protein-coding genes.

Non-coding RNAs (ncRNAs) are emerging as key regulators of various biological processes. Although thousands of ncRNAs have been discovered, the transcriptional mechanisms and networks of the majority of ncRNAs have not been fully investigated. In this study, we updated ChIPBase to version 3.0 (https://rnasysu.com/chipbase3/) to provide the most comprehensive transcriptional regulation atlas of ncRNAs and protein-coding genes (PCGs). ChIPBase has identified ∼151 187 000 regulatory relationships between ∼171 600 genes and ∼3000 regulators by analyzing ∼55 000 ChIP-seq datasets, which represent a 30-fold expansion. Moreover, we de novo identified ∼29 000 motif matrices of transcription factors. In addition, we constructed a novel 'Enhancer' module to predict ∼1 837 200 regulation regions functioning as poised, active or super enhancers under ∼1300 conditions. Importantly, we constructed exhaustive coexpression maps between regulators and their target genes by integrating expression profiles of ∼65 000 normal and ∼15 000 tumor samples. We built a 'Disease' module to obtain an atlas of the disease-associated variations in the regulation regions of genes. We also constructed an 'EpiInter' module to explore potential interactions between epitranscriptome and epigenome. Finally, we designed 'Network' module to provide extensive and gene-centred regulatory networks. ChIPBase will serve as a useful resource to facilitate integrative explorations and expand our understanding of transcriptional regulation.

RNA-Guided RNA Modifications: Biogenesis, Functions, and Applications.

ConspectusPost-transcriptional modifications are ubiquitous in both protein-coding and noncoding RNAs (ncRNAs), playing crucial functional roles in diverse biological processes across all kingdoms of life. These RNA modifications can be achieved through two distinct mechanisms: RNA-independent and RNA-guided (also known as RNA-dependent). In the RNA-independent mechanism, modifications are directly introduced onto RNA molecules by enzymes without the involvement of other RNA molecules, while the cellular RNA-guided RNA modification system exists in the form of RNA-protein complexes, wherein one guide RNA collaborates with a set of proteins, including the modifying enzyme. The primary function of guide RNAs lies in their ability to bind to complementary regions within the target RNAs, orchestrating the installation of specific modifications. Both mechanisms offer unique advantages and are critical to the diverse and dynamic landscape of RNA modifications. RNA-independent modifications provide rapid and direct modification of RNA molecules, while RNA-guided mechanisms offer precise and programmable means to introduce modifications at specific RNA sites. Recently, emerging evidence has shed light on RNA-guided RNA modifications as a captivating area of research, providing precise and programmable control over RNA sequences and functions.In this Account, we focus on RNA modifications synthesized in an RNA-guided manner, including 2'-O-methylated nucleotides (Nm), pseudouridine (Ψ), N4-acetylcytidine (ac4C), and inosine (I). This Account sheds light on the intricate processes of biogenesis and elucidates the regulatory roles of these modifications in RNA metabolism. These roles include pivotal functions such as RNA stability, translation, and splicing, where each modification contributes to the diverse and finely tuned regulatory landscape of RNA biology. In addition to elucidating the biogenesis and functions of these modifications, we also provide an overview of high-throughput methods and their underlying biochemical principles used for the transcriptome-wide investigation of these modifications and their fundamental interactions in RNA-guided systems. This includes exploring RNA-protein interactions and RNA-RNA interactions, which play crucial roles in the dynamic regulatory networks of RNA-guided modifications. The ever-advancing methodologies have greatly enhanced our understanding of the dynamic and widespread nature of RNA-guided RNA modifications and their regulatory functions. Furthermore, the applications of RNA-guided RNA modifications are discussed, illuminating their potential in diverse fields. From basic research to gene therapy, the programmable nature of RNA-guided modifications presents exciting opportunities for manipulating gene expression and developing innovative therapeutic strategies.

Pol3Base: a resource for decoding the interactome, expression, evolution, epitranscriptome and disease variations of Pol III-transcribed ncRNAs.

RNA polymerase III (Pol III) transcribes hundreds of non-coding RNA genes (ncRNAs), which involve in a variety of cellular processes. However, the expression, functions, regulatory networks and evolution of these Pol III-transcribed ncRNAs are still largely unknown. In this study, we developed a novel resource, Pol3Base (http://rna.sysu.edu.cn/pol3base/), to decode the interactome, expression, evolution, epitranscriptome and disease variations of Pol III-transcribed ncRNAs. The current release of Pol3Base includes thousands of regulatory relationships between ∼79 000 ncRNAs and transcription factors by mining 56 ChIP-seq datasets. By integrating CLIP-seq datasets, we deciphered the interactions of these ncRNAs with >240 RNA binding proteins. Moreover, Pol3Base contains ∼9700 RNA modifications located within thousands of Pol III-transcribed ncRNAs. Importantly, we characterized expression profiles of ncRNAs in >70 tissues and 28 different tumor types. In addition, by comparing these ncRNAs from human and mouse, we revealed about 4000 evolutionary conserved ncRNAs. We also identified ∼11 403 tRNA-derived small RNAs (tsRNAs) in 32 different tumor types. Finally, by analyzing somatic mutation data, we investigated the mutation map of these ncRNAs to help uncover their potential roles in diverse diseases. This resource will help expand our understanding of potential functions and regulatory networks of Pol III-transcribed ncRNAs.

tsRFun: a comprehensive platform for decoding human tsRNA expression, functions and prognostic value by high-throughput small RNA-Seq and CLIP-Seq data.

tRNA-derived small RNA (tsRNA), a novel type of regulatory small noncoding RNA, plays an important role in physiological and pathological processes. However, the understanding of the functional mechanism of tsRNAs in cells and their role in the occurrence and development of diseases is limited. Here, we integrated multiomics data such as transcriptome, epitranscriptome, and targetome data, and developed novel computer tools to establish tsRFun, a comprehensive platform to facilitate tsRNA research (http://rna.sysu.edu.cn/tsRFun/ or http://biomed.nscc-gz.cn/DB/tsRFun/). tsRFun evaluated tsRNA expression profiles and the prognostic value of tsRNAs across 32 types of cancers, identified tsRNA target molecules utilizing high-throughput CLASH/CLEAR or CLIP sequencing data, and constructed the interaction networks among tsRNAs, microRNAs, and mRNAs. In addition to its data presentation capabilities, tsRFun offers multiple real-time online tools for tsRNA identification, target prediction, and functional enrichment analysis. In summary, tsRFun provides a valuable data resource and multiple analysis tools for tsRNA investigation.

ColorCells: a database of expression, classification and functions of lncRNAs in single cells.

Although long noncoding RNAs (lncRNAs) have significant tissue specificity, their expression and variability in single cells remain unclear. Here, we developed ColorCells (http://rna.sysu.edu.cn/colorcells/), a resource for comparative analysis of lncRNAs expression, classification and functions in single-cell RNA-Seq data. ColorCells was applied to 167 913 publicly available scRNA-Seq datasets from six species, and identified a batch of cell-specific lncRNAs. These lncRNAs show surprising levels of expression variability between different cell clusters, and has the comparable cell classification ability as known marker genes. Cell-specific lncRNAs have been identified and further validated by in vitro experiments. We found that lncRNAs are typically co-expressed with the mRNAs in the same cell cluster, which can be used to uncover lncRNAs' functions. Our study emphasizes the need to uncover lncRNAs in all cell types and shows the power of lncRNAs as novel marker genes at single cell resolution.

deepBase v3.0: expression atlas and interactive analysis of ncRNAs from thousands of deep-sequencing data.

Eukaryotic genomes encode thousands of small and large non-coding RNAs (ncRNAs). However, the expression, functions and evolution of these ncRNAs are still largely unknown. In this study, we have updated deepBase to version 3.0 (deepBase v3.0, http://rna.sysu.edu.cn/deepbase3/index.html), an increasingly popular and openly licensed resource that facilitates integrative and interactive display and analysis of the expression, evolution, and functions of various ncRNAs by deeply mining thousands of high-throughput sequencing data from tissue, tumor and exosome samples. We updated deepBase v3.0 to provide the most comprehensive expression atlas of small RNAs and lncRNAs by integrating ∼67 620 data from 80 normal tissues and ∼50 cancer tissues. The extracellular patterns of various ncRNAs were profiled to explore their applications for discovery of noninvasive biomarkers. Moreover, we constructed survival maps of tRNA-derived RNA Fragments (tRFs), miRNAs, snoRNAs and lncRNAs by analyzing >45 000 cancer sample data and corresponding clinical information. We also developed interactive webs to analyze the differential expression and biological functions of various ncRNAs in ∼50 types of cancers. This update is expected to provide a variety of new modules and graphic visualizations to facilitate analyses and explorations of the functions and mechanisms of various types of ncRNAs.

The cardiac translational landscape reveals that micropeptides are new players involved in cardiomyocyte hypertrophy.

Hypertrophic growth of cardiomyocytes is one of the major compensatory responses in the heart after physiological or pathological stimulation. Protein synthesis enhancement, which is mediated by the translation of messenger RNAs, is one of the main features of cardiomyocyte hypertrophy. Although the transcriptome shift caused by cardiac hypertrophy induced by different stimuli has been extensively investigated, translatome dynamics in this cellular process has been less studied. Here, we generated a nucleotide-resolution translatome as well as transcriptome data from isolated primary cardiomyocytes undergoing hypertrophy. More than 10,000 open reading frames (ORFs) were detected from the deep sequencing of ribosome-protected fragments (Ribo-seq), which orchestrated the shift of the translatome in hypertrophied cardiomyocytes. Our data suggest that rather than increase the translational rate of ribosomes, the increased efficiency of protein synthesis in cardiomyocyte hypertrophy was attributable to an increased quantity of ribosomes. In addition, more than 100 uncharacterized short ORFs (sORFs) were detected in long noncoding RNA genes from Ribo-seq with potential of micropeptide coding. In a random test of 15 candidates, the coding potential of 11 sORFs was experimentally supported. Three micropeptides were identified to regulate cardiomyocyte hypertrophy by modulating the activities of oxidative phosphorylation, the calcium signaling pathway, and the mitogen-activated protein kinase (MAPK) pathway. Our study provides a genome-wide overview of the translational controls behind cardiomyocyte hypertrophy and demonstrates an unrecognized role of micropeptides in cardiomyocyte biology.

Novel organization of mitochondrial minicircles and guide RNAs in the zoonotic pathogen Trypanosoma lewisi.

Kinetoplastid flagellates are known for several unusual features, one of which is their complex mitochondrial genome, known as kinetoplast (k) DNA, composed of mutually catenated maxi- and minicircles. Trypanosoma lewisi is a member of the Stercorarian group of trypanosomes which is, based on human infections and experimental data, now considered a zoonotic pathogen. By assembling a total of 58 minicircle classes, which fall into two distinct categories, we describe a novel type of kDNA organization in T. lewisi. RNA-seq approaches allowed us to map the details of uridine insertion and deletion editing events upon the kDNA transcriptome. Moreover, sequencing of small RNA molecules enabled the identification of 169 unique guide (g) RNA genes, with two differently organized minicircle categories both encoding essential gRNAs. The unprecedented organization of minicircles and gRNAs in T. lewisi broadens our knowledge of the structure and expression of the mitochondrial genomes of these human and animal pathogens. Finally, a scenario describing the evolution of minicircles is presented.

An LTR retrotransposon-derived lncRNA interacts with RNF169 to promote homologous recombination.

LTR retrotransposons are abundant repetitive elements in the human genome, but their functions remain poorly understood. Here, we report the function and regulatory mechanism of an ERV-9 LTR retrotransposon-derived lncRNA called p53-regulated lncRNA for homologous recombination (HR) repair 1 (PRLH1) in human cells. PRLH1 is highly expressed in p53-mutated hepatocellular carcinoma (HCC) samples and promotes cell proliferation in p53-mutated HCC cells, and its transcription is promoted by NF-Y and suppressed by p53. Mechanistically, PRLH1 specifically binds to an uncharacterized domain of RNF169 through two GCUUCA boxes in its 5' terminal region to form a DNA repair complex that supplants 53BP1 at double-strand break (DSB) sites and then promotes the initiation of HR repair. Notably, PRLH1 is essential for the stabilization of RNF169, acting as an RNA platform to recruit and assemble HR protein factors. This study characterizes PRLH1 as a novel HR-promoting factor and provides new insights into the function and mechanism of LTR retrotransposon-derived lncRNAs.

Differential impacts of charcoal-stripped fetal bovine serum on c-Myc among distinct subtypes of breast cancer cell lines.

Charcoal-stripped fetal bovine serum (CS-FBS) is frequently used in studies on hormone-responsive cancers to provide hormone-free cell culture conditions. CS-FBS may influence the growth of cancer cells; however, the underlying mechanisms remain unclear. In this study, we aimed to clarify the effects of CS-FBS on distinct subtypes of breast cancer cells. We found that the crucial oncoprotein c-Myc was significantly inhibited in estrogen receptor alpha (ER-α)-positive breast cancer cells when cultured in CS-FBS-supplemented medium, but it was not suppressed in ER-α-negative cells. The addition of 17ß-estradiol (E2) to CS-FBS-supplemented medium rescued the CS-FBS-induced inhibition of c-Myc, while treatment with 5α-dihydrotestosterone (DHT) suppressed c-Myc expression. Our data demonstrated that CS-FBS may impede the growth of ER-α-positive breast cancer cells via c-Myc inhibition, and this was possibly due to the removal of estrogen. These results highlighted that the core drivers of c-Myc expression were subtype-specific depending on the distinct cell context and special caution should be exercised when using CS-FBS in studies of hormone-responsive cancer cells.

RMBase v2.0: deciphering the map of RNA modifications from epitranscriptome sequencing data.

More than 100 distinct chemical modifications to RNA have been characterized so far. However, the prevalence, mechanisms and functions of various RNA modifications remain largely unknown. To provide transcriptome-wide landscapes of RNA modifications, we developed the RMBase v2.0 (http://rna.sysu.edu.cn/rmbase/), which is a comprehensive database that integrates epitranscriptome sequencing data for the exploration of post-transcriptional modifications of RNAs and their relationships with miRNA binding events, disease-related single-nucleotide polymorphisms (SNPs) and RNA-binding proteins (RBPs). RMBase v2.0 was expanded with ∼600 datasets and ∼1 397 000 modification sites from 47 studies among 13 species, which represents an approximately 10-fold expansion when compared with the previous release. It contains ∼1 373 000 N6-methyladenosines (m6A), ∼5400 N1-methyladenosines (m1A), ∼9600 pseudouridine (Ψ) modifications, ∼1000 5-methylcytosine (m5C) modifications, ∼5100 2'-O-methylations (2'-O-Me), and ∼2800 modifications of other modification types. Moreover, we built a new module called 'Motif' that provides the visualized logos and position weight matrices (PWMs) of the modification motifs. We also constructed a novel module termed 'modRBP' to study the relationships between RNA modifications and RBPs. Additionally, we developed a novel web-based tool named 'modMetagene' to plot the metagenes of RNA modification along a transcript model. This database will help researchers investigate the potential functions and mechanisms of RNA modifications.

dreamBase: DNA modification, RNA regulation and protein binding of expressed pseudogenes in human health and disease.

Although thousands of pseudogenes have been annotated in the human genome, their transcriptional regulation, expression profiles and functional mechanisms are largely unknown. In this study, we developed dreamBase (http://rna.sysu.edu.cn/dreamBase) to facilitate the investigation of DNA modification, RNA regulation and protein binding of potential expressed pseudogenes from multidimensional high-throughput sequencing data. Based on ∼5500 ChIP-seq and DNase-seq datasets, we identified genome-wide binding profiles of various transcription-associated factors around pseudogene loci. By integrating ∼18 000 RNA-seq data, we analysed the expression profiles of pseudogenes and explored their co-expression patterns with their parent genes in 32 cancers and 31 normal tissues. By combining microRNA binding sites, we demonstrated complex post-transcriptional regulation networks involving 275 microRNAs and 1201 pseudogenes. We generated ceRNA networks to illustrate the crosstalk between pseudogenes and their parent genes through competitive binding of microRNAs. In addition, we studied transcriptome-wide interactions between RNA binding proteins (RBPs) and pseudogenes based on 458 CLIP-seq datasets. In conjunction with epitranscriptome sequencing data, we also mapped 1039 RNA modification sites onto 635 pseudogenes. This database will provide insights into the transcriptional regulation, expression, functions and mechanisms of pseudogenes as well as their roles in biological processes and diseases.

ChIPBase v2.0: decoding transcriptional regulatory networks of non-coding RNAs and protein-coding genes from ChIP-seq data.

The abnormal transcriptional regulation of non-coding RNAs (ncRNAs) and protein-coding genes (PCGs) is contributed to various biological processes and linked with human diseases, but the underlying mechanisms remain elusive. In this study, we developed ChIPBase v2.0 (http://rna.sysu.edu.cn/chipbase/) to explore the transcriptional regulatory networks of ncRNAs and PCGs. ChIPBase v2.0 has been expanded with ∼10 200 curated ChIP-seq datasets, which represent about 20 times expansion when comparing to the previous released version. We identified thousands of binding motif matrices and their binding sites from ChIP-seq data of DNA-binding proteins and predicted millions of transcriptional regulatory relationships between transcription factors (TFs) and genes. We constructed 'Regulator' module to predict hundreds of TFs and histone modifications that were involved in or affected transcription of ncRNAs and PCGs. Moreover, we built a web-based tool, Co-Expression, to explore the co-expression patterns between DNA-binding proteins and various types of genes by integrating the gene expression profiles of ∼10 000 tumor samples and ∼9100 normal tissues and cell lines. ChIPBase also provides a ChIP-Function tool and a genome browser to predict functions of diverse genes and visualize various ChIP-seq data. This study will greatly expand our understanding of the transcriptional regulations of ncRNAs and PCGs.

A group of tissue-specific microRNAs contribute to the silencing of CUX1 in different cell lineages during development.

Cut-like homeobox 1 (CUX1) is a highly conserved homeoprotein that functions as a transcriptional repressor of genes specifying terminal differentiation. We previously showed that liver-specific microRNA-122 (miR-122) regulates the timing of liver development by silencing CUX1 post-transcriptionally. Since the CUX1 protein is expressed in a subset of embryonic tissues, we hypothesized that it is regulated by specific microRNAs (miRNAs) in each cell type during development. Using a large-scale screening method, we identified ten tissue-specific miRNAs from different cell lineages that directly targeted CUX1. An analysis of the interaction between heart-specific microRNA-208a (miR-208a) and CUX1 in the hearts of developing mouse embryos and in P19CL6 cells undergoing cardiac differentiation indicated that CUX1 is regulated by miR-208a during heart development and cardiomyocyte differentiation. Functional analysis of miR-208a in P19CL6 cells using lentiviral-mediated over-expression showed that it regulates the transition between cellular proliferation and differentiation. These results suggest that these tissue-specific miRNAs might play a common role in timing the progression of terminal differentiation of different cell lineages, possibly by silencing the differentiation repressor CUX1.

RMBase: a resource for decoding the landscape of RNA modifications from high-throughput sequencing data.

Although more than 100 different types of RNA modifications have been characterized across all living organisms, surprisingly little is known about the modified positions and their functions. Recently, various high-throughput modification sequencing methods have been developed to identify diverse post-transcriptional modifications of RNA molecules. In this study, we developed a novel resource, RMBase (RNA Modification Base, http://mirlab.sysu.edu.cn/rmbase/), to decode the genome-wide landscape of RNA modifications identified from high-throughput modification data generated by 18 independent studies. The current release of RMBase includes ∼ 9500 pseudouridine (Ψ) modifications generated from Pseudo-seq and CeU-seq sequencing data, ∼ 1000 5-methylcytosines (m(5)C) predicted from Aza-IP data, ∼ 124 200 N6-Methyladenosine (m(6)A) modifications discovered from m(6)A-seq and ∼ 1210 2'-O-methylations (2'-O-Me) identified from RiboMeth-seq data and public resources. Moreover, RMBase provides a comprehensive listing of other experimentally supported types of RNA modifications by integrating various resources. It provides web interfaces to show thousands of relationships between RNA modification sites and microRNA target sites. It can also be used to illustrate the disease-related SNPs residing in the modification sites/regions. RMBase provides a genome browser and a web-based modTool to query, annotate and visualize various RNA modifications. This database will help expand our understanding of potential functions of RNA modifications.