RMVar: an updated database of functional variants involved in RNA modifications

Integrative bioinformatics and experimental analysis revealed down-regulated CDC42EP3 as a novel prognostic target for ovarian cancer and its roles in immune infiltration

Ovarian cancer is a significant clinical challenge as no effective treatments are available to enhance patient survival. Recently, N6-methyladenosine (m⁶A) RNA modification has been demonstrated to play a pivotal role in tumorigenesis and progression. However, the roles of m⁶A target genes in ovarian cancer haven’t been clearly illustrated. In this study, we presented a comprehensive bioinformatics and in vitro analysis to evaluate the roles of m⁶A target genes. Cell division cycle 42 effector protein 3 (CDC42EP3), one probable m6A target gene, was identified to be down-regulated in ovarian cancer tissues and cells. Meanwhile, quantitative PCR (qPCR) and western blot were used to confirm the down-regulated CDC42EP3 in ovarian cancer cells A2780 and TOV112D. The biological function of CDC42EP3 in ovarian cancer was further validated with several algorithms, such as PrognoScan, K-M plotter, LinkedOmics and TISIDB. These findings indicated that lower expression of CDC42EP3 was correlated with poor prognosis in patients with ovarian cancer. In addition, CDC42EP3 expression was significantly associated with a diverse range of tumor-infiltrating immune cells, including natural killer cells (NK), T central memory cells (Tcm), T gamma delta cells (Tgd), etc. Taken together, this study uncovered the potential roles of m⁶A target gene CDC42EP3 in the regulation of immune microenvironment in the ovarian cancer, and identified CDC42EP3 as a novel prognostic target.

The role of RNA m5C modification in cancer metastasis

Epigenetic modification plays a crucial regulatory role in the biological processes of eukaryotic cells. The recent characterization of DNA and RNA methylation is still ongoing. Tumor metastasis has long been an unconquerable feature in the fight against cancer. As an inevitable component of the epigenetic regulatory network, 5-methylcytosine is associated with multifarious cellular processes and systemic diseases, including cell migration and cancer metastasis. Recently, gratifying progress has been achieved in determining the molecular interactions between m⁵C writers (DNMTs and NSUNs), demethylases (TETs), readers (YTHDF2, ALYREF and YBX1) and RNAs. However, the underlying mechanism of RNA m⁵C methylation in cell mobility and metastasis remains unclear. The functions of m⁵C writers and readers are believed to regulate gene expression at the post-transcription level and are involved in cellular metabolism and movement. In this review, we emphatically summarize the recent updates on m⁵C components and related regulatory networks. The content will be focused on writers and readers of the RNA m⁵C modification and potential mechanisms in diseases. We will discuss relevant upstream and downstream interacting molecules and their associations with cell migration and metastasis.

N6-methyladenosine RNA modification: A promising regulator in central nervous system injury

In addition to DNA methylation, reversible epigenetic modification occurring in RNA has been discovered recently. The most abundant type of RNA methylation is N6-methyladenosine (m6A) modification, which is dynamically regulated by methylases ("writers"), demethylases ("erasers") and m6A-binding proteins ("readers"). As an essential posttranscriptional regulator, m6A can control mRNA splicing, processing, stability, export and translation. Recent studies have revealed that m6A modification has the strongest tissue specificity for brain tissue and plays crucial roles in central nervous system (CNS) injures by affecting its downstream target genes or non-coding RNAs. This review focuses on the expression and function of m6A regulatory proteins in CNS trauma in vitro and in vivo. We also highlight the latest insights into the molecular mechanisms of pathological damage in the CNS. Understanding m6A dynamics, functions, and machinery will yield an opportunity for designing and developing novel therapeutic agents for CNS injuries.

Genome-Wide Identification of m6A-Associated Single-Nucleotide Polymorphisms in Colorectal Cancer

Background

N6-methyladenosine (m6A)-associated single-nucleotide polymorphisms (SNPs) play important roles in cancers, with previous research suggesting potential associations between m6A-SNPs and cancer. However, the relationship between the genetic determinants of m6A modification and colorectal cancer (CRC) remains unclear.

Methods

An integrative method combining raw data and summary statistics of genome-wide association studies with expression quantitative trait loci (eQTL) and differential expression data was applied to screen potential candidate CRC-associated m6A-SNPs.

Results

A total of 402 m6A-SNPs were identified as being associated with CRC (p < 0.001), with 98 showing eQTL signals. In particular, three genes were found to harbor CRC-associated m6A-SNPs: rs178184 in NOVA1, rs35782901 in HTR4, and rs60571683 in SLCO1B3. These genes were differentially expressed in at least one publicly available dataset (p < 0.05), with NOVA1 (p = 3.41×10^-11) and HTR4 (p = 5.56×10^-7) being significantly downregulated in CRC (dataset: GSE89076), and SLCO1B3 was significantly overexpressed (datasets: GSE32323 [p = 3.27×10^-5], GSE21510 [p = 1.09×10^-6], and GSE89076 [p = 7.63×10^-6]).

Conclusion

This study identified three m6A-SNPs (rs178184, rs35782901, and rs60571683) that may be associated with CRC. However, the lack of analysis of primary CRC samples in order to further elucidate the underlying pathogenesis is a major limitation of this study. Future investigations are needed to validate these CRC-associated m6A-SNPs and explore the m6A-mediated pathogenic mechanism in CRC.

Hub Long Noncoding RNAs with m6A Modification for Signatures and Prognostic Values in Kidney Renal Clear Cell Carcinoma

Background: N6-methyladenosine (m6A)–modified long noncoding RNAs (m6A-lncRNAs) have been proven to be involving in regulating tumorigenesis, invasion, and metastasis for a variety of tumors. The present study aimed to screen lncRNAs with m6A modification and investigate their biological signatures and prognostic values in kidney renal clear cell carcinoma (KIRC).

Materials and Methods: lncRNA-seq, miRNA-seq, and mRNA-seq profiles of KIRC samples and the clinical characteristics of corresponding patients were downloaded from The Cancer Genome Atlas (TCGA). The R package “edgeR” was utilized to perform differentially expressed analysis on these profiles to gain DElncRNAs, DEmiRNAs, and DEmRNAs, respectively. The results of intersection of DElncRNAs and m6A-modified genes were analyzed by the weighted gene co-expression network analysis (WGCNA) to screen hub m6A-lncRNAs. Then, WGCNA was also used to construct an lncRNA-miRNA-mRNA (ceRNA) network. The Cox regression analysis was conducted on hub m6A-lncRNAs to construct the m6A-lncRNAs prognostic index (m6AlRsPI). Receiver operating characteristic (ROC) curve was used to assess the predictive ability of m6AlRsPI. The m6AlRsPI model was tested by internal and external cohorts. The molecular signatures and prognosis for hub m6A-lncRNAs and m6AlRsPI were analyzed. The expression level of hub m6A-lncRNAs in KIRC cell lines were quantified by qRT-PCR.

Results: A total of 21 hub m6A-lncRNAs associated with tumor metastasis were identified in the light of WGCNA. The ceRNA network for 21 hub m6A-lncRNAs was developed. The Cox regression analysis was performed on the 21 hub m6A-lncRNAs, screening two m6A-lncRNAs regarded as independent prognostic risk factors. The m6AlRsPI was established based on the two m6A-lncRNAs as follows: (0.0006066 × expression level of LINC01820) + (0.0020769 × expression level of LINC02257). The cutoff of m6AlRsPI was 0.96. KM survival analysis for m6AlRsPI showed that the high m6AlRsPI group could contribute to higher mortality. The area under ROC curve for m6AlRsPI for predicting 3- and 5-year survival was 0.760 and 0.677, respectively, and the m6AlRsPI was also tested. The mutation and epithelial–mesenchymal transition (EMT) analysis for m6AlRsPI showed that the high m6AIRsPI group had more samples with gene mutation and had more likely caused EMT. Finally, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed for mRNAs interacted with the two m6A-lncRNAs, showing they were involved in the process of RNA splicing and regulation of the mRNA surveillance pathway. qRT-PCR analysis showed that the two m6A-lncRNAs were upregulated in KIRC.

Conclusion: In the present study, hub m6A-lncRNAs were determined associated with metastasis in KIRC, and the ceRNA network demonstrated the potential carcinogenic regulatory pathway. Two m6A-lncRNAs associated with the overall survival were screened and m6AlRsPI was constructed and validated. Finally, the molecular signatures for m6AlRsPI and the two m6A-lncRNAs were analyzed to investigate the potential modulated processes in KIRC.

M6A-BiNP: predicting N6-methyladenosine sites based on bidirectional position-specific propensities of polynucleotides and pointwise joint mutual information

N⁶-methyladenosine (m⁶A) plays an important role in various biological processes. Identifying m⁶A site is a key step in exploring its biological functions. One of the biggest challenges in identifying m⁶A sites is how to extract features comprising rich categorical information to distinguish m⁶A and non-m⁶A sites. To address this challenge, we propose bidirectional dinucleotide and trinucleotide position-specific propensities, respectively, in this paper. Based on this, we propose two feature-encoding algorithms: Position-Specific Propensities and Pointwise Mutual Information (PSP-PMI) and Position-Specific Propensities and Pointwise Joint Mutual Information (PSP-PJMI). PSP-PMI is based on the bidirectional dinucleotide propensity and the pointwise mutual information, while PSP-PJMI is based on the bidirectional trinucleotide position-specific propensity and the proposed pointwise joint mutual information in this paper. We introduce parameters α and β in PSP-PMI and PSP-PJMI, respectively, to represent the distance from the nucleotide to its forward or backward adjacent nucleotide or dinucleotide, so as to extract features containing local and global classification information. Finally, we propose the M6A-BiNP predictor based on PSP-PMI or PSP-PJMI and SVM classifier. The 10-fold cross-validation experimental results on the benchmark datasets of non-single-base resolution and single-base resolution demonstrate that PSP-PMI and PSP-PJMI can extract features with strong capabilities to identify m⁶A and non-m⁶A sites. The M6A-BiNP predictor based on our proposed feature encoding algorithm PSP-PJMI is better than the state-of-the-art predictors, and it is so far the best model to identify m⁶A and non-m⁶A sites.

Integrative genomic analysis of N6-methyladenosine-single nucleotide polymorphisms (m6A-SNPs) associated with breast cancer

Due to the important role of N6-methyladenosine (m⁶A) in breast cancer, single nucleotide polymorphisms (SNPs) in genes with m⁶A modification may also be involved in breast cancer pathogenesis. In this study, we used a public genome-wide association study dataset to identify m⁶A-SNPs associated with breast cancer and to further explore their potential functions. We found 113 m⁶A-SNPs associated with breast cancer that reached the genome-wide suggestive threshold (5.0E-05), and 86 m⁶A-SNPs had eQTL signals. Only six genes were differentially expressed between controls and breast cancer cases in GEO datasets (GSE15852, GSE115144, and GSE109169), and the SNPs rs4829 and rs9610915 were located next to the m⁶A modification sites in the 3ʹUTRs of TOM1L1 and MAFF, respectively. In addition, we found that polyadenylate-binding protein cytoplasmic 1 might have a potential interaction with rs4829 (TOM1L1) and rs9610915 (MAFF). In summary, these findings indicated that the SNPs rs4829 and rs9610915 are potentially associated with breast cancer because they had eQTL signals, altered gene expression, and were located next to the m⁶A modification sites in the 3ʹUTRs of their coding genes. However, further studies are still needed to clarify how genetic variation affects the epigenetic modification, m⁶A, and its subsequent functions in the pathogenesis of breast cancer.

Signatures and Prognostic Values of N6-methyladenosine (m6A) - related Immune Genes in Bladder Cancer

In recent years, genes associated with N6-methyladenosine (m6A) modification were found to participate in modulation of multiple tumor biological processes. Concomitantly, the significantly complicated dual effects of tumor microenvironment have been observed on cancer progression. The present study aims to investigate m6A-related immune genes (m6AIGs) for their signatures and prognostic values in bladder cancer (BC). Out of 2856 differentially expressed genes (DEGs) of BC, a total of 85 genes were obtained following intersection of DEGs, immune genes and m6A-related genes. The results of multivariate Cox regression analysis illustrated four genes (BGN, GRK5, IL32, and SREBF1) were significantly associated with the prognosis of BC patients. The BC samples were divided into two types based on the consensus clustering, and the principal component analysis demonstrated a separation between them. It was found that high expression of BGN and GRK5 were linked with advanced T and N stage, and the expression of SREBF1 in early T stage was higher than that in advanced T stage. Subsequently, the nomogram to predict 3- and 5-year survival probability of BC patients was developed and calibrated. GSEA analysis for risk subgroups showed WNT and TGF-beta signaling pathways were involved in regulation of BC progression in high risk level group. In the low risk level group, cytosolic DNA-Sensing cGAS-STING and RIG-I-like receptors signaling pathways were found to be correlated with BC development. These findings provide a novel insight on studies for BC progression.

Recent advances in functional annotation and prediction of the epitranscriptome

RNA modifications, in particular N⁶-methyladenosine (m⁶A), participate in every stages of RNA metabolism and play diverse roles in essential biological processes and disease pathogenesis. Thanks to the advances in sequencing technology, tens of thousands of RNA modification sites can be identified in a typical high-throughput experiment; however, it remains a major challenge to decipher the functional relevance of these sites, such as, affecting alternative splicing, regulation circuit in essential biological processes or association to diseases. As the focus of RNA epigenetics gradually shifts from site discovery to functional studies, we review here recent progress in functional annotation and prediction of RNA modification sites from a bioinformatics perspective. The review covers naïve annotation with associated biological events, e.g., single nucleotide polymorphism (SNP), RNA binding protein (RBP) and alternative splicing, prediction of key sites and their regulatory functions, inference of disease association, and mining the diagnosis and prognosis value of RNA modification regulators. We further discussed the limitations of existing approaches and some future perspectives.

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.

RNA modifications in cardiovascular diseases, the potential therapeutic targets

More than one hundred RNA modifications decorate the chemical and topological properties of these ribose nucleotides, thereby executing their biological functions through post-transcriptional regulation. In cardiovascular diseases, a wide range of RNA modifications including m⁶A (N6-adenosine methylation), m⁵C (5-methylcytidin), Nm (2'-O-ribose-methylation), Ψ (pseudouridine), m⁷G (N7-methylguanosine), and m¹A (N1-adenosine methylation) have been found in tRNA, rRNA, mRNA and other noncoding RNA, which can function as a novel mechanism in metabolic syndrome, heart failure, coronary heart disease, and hypertension. In this review, we will summarize the current understanding of the regulatory roles and significance of several types of RNA modifications in CVDs (cardiovascular diseases) and the interplay between RNA modifications and noncoding RNA, epigenetics. Finally, we will focus on the potential therapeutic strategies by using RNA modifications.

Dynamics of m6A RNA Methylome on the Hallmarks of Hepatocellular Carcinoma

Epidemiological data consistently rank hepatocellular carcinoma (HCC) as one of the leading causes of cancer-related deaths worldwide, often posing severe economic burden on health care. While the molecular etiopathogenesis associated with genetic and epigenetic modifications has been extensively explored, the biological influence of the emerging field of epitranscriptomics and its associated aberrant RNA modifications on tumorigenesis is a largely unexplored territory with immense potential for discovering new therapeutic approaches. In particular, the underlying cellular mechanisms of different hallmarks of hepatocarcinogenesis that are governed by the complex dynamics of m6A RNA methylation demand further investigation. In this review, we reveal the up-to-date knowledge on the mechanistic and functional link between m6A RNA methylation and pathogenesis of HCC.

The 2021 Nucleic Acids Research database issue and the online molecular biology database collection

The 2021 Nucleic Acids Research database Issue contains 189 papers spanning a wide range of biological fields and investigation. It includes 89 papers reporting on new databases and 90 covering recent changes to resources previously published in the Issue. A further ten are updates on databases most recently published elsewhere. Seven new databases focus on COVID-19 and SARS-CoV-2 and many others offer resources for studying the virus. Major returning nucleic acid databases include NONCODE, Rfam and RNAcentral. Protein family and domain databases include COG, Pfam, SMART and Panther. Protein structures are covered by RCSB PDB and dispersed proteins by PED and MobiDB. In metabolism and signalling, STRING, KEGG and WikiPathways are featured, along with returning KLIFS and new DKK and KinaseMD, all focused on kinases. IMG/M and IMG/VR update in the microbial and viral genome resources section, while human and model organism genomics resources include Flybase, Ensembl and UCSC Genome Browser. Cancer studies are covered by updates from canSAR and PINA, as well as newcomers CNCdatabase and Oncovar for cancer drivers. Plant comparative genomics is catered for by updates from Gramene and GreenPhylDB. The entire Database Issue is freely available online on the Nucleic Acids Research website (https://academic.oup.com/nar). The NAR online Molecular Biology Database Collection has been substantially updated, revisiting nearly 1000 entries, adding 90 new resources and eliminating 86 obsolete databases, bringing the current total to 1641 databases. It is available at https://www.oxfordjournals.org/nar/database/c/.

Advances in the profiling of N6-methyladenosine (m6A) modifications

Over 160 RNA modifications have been identified, including N⁷-methylguanine (m⁷G), N⁶-methyladenosine (m⁶A), and 5-methylcytosine (m⁵C). These modifications play key roles in regulating the fate of RNA. In eukaryotes, m⁶A is the most abundant mRNA modification, accounting for over 80% of all RNA methylation modifications. Highly dynamic m⁶A modification may exert important effects on organismal reproduction and development. Significant advances in understanding the mechanism of m⁶A modification have been made using immunoprecipitation, chemical labeling, and site-directed mutagenesis, combined with next-generation sequencing. Single-molecule real-time and nanopore direct RNA sequencing (DRS) approaches provide additional ways to study RNA modifications at the cellular level. In this review, we explore the technical history of identifying m⁶A RNA modifications, emphasizing technological advances in detecting m⁶A modification. In particular, we discuss the challenge of generating accurate dynamic single-base resolution m⁶A maps and also strategies for improving detection specificity. Finally, we outline a roadmap for future research in this area, focusing on the application of RNA epigenetic modification, represented by m⁶A modification.