m5C-Atlas: a comprehensive database for decoding and annotating the 5-methylcytosine (m5C) epitranscriptome

Ma, Jiongming; Song, Bowen; Wei, Zhen; Huang, Daiyun; Zhang, Yuxin; Su, Jionglong; Magalhães, João Pedro de; Rigden, Daniel J.; Meng, Jia; Chen, Kunqi

doi:10.1093/nar/gkab1075

Cited by 66 publications

(45 citation statements)

References 50 publications

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“…Research groups focusing on non-coding RNAs have identified the m 5 C modification of mitochondrial tRNAs and one rRNA ( 11 , 28–30 ), indicating the presence of NSUN2 ( 29 , 31 ), NSUN3 ( 32 , 33 ) and NSUN4 ( 30 , 34–36 ) activity within the mitochondrial complex. Some studies identified methylated mRNAs originating from the mitochondrial genome ( 14 , 16 , 22 ), however, other studies were unable to support this finding ( 15 , 37 ).…”

Section: Introductionmentioning

confidence: 97%

Systematic evaluation of parameters in RNA bisulfite sequencing data generation and analysis

Johnson

Pacholec

et al. 2022

NAR Genomics and Bioinformatics

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The presence of 5-methylcytosine (m5C) in RNA molecules has been known for decades and its importance in regulating RNA metabolism has gradually become appreciated. Despite recent advances made in the functional and mechanistic understanding of RNA m5C modifications, the detection and quantification of methylated RNA remains a challenge. In this study, we compared four library construction procedures for RNA bisulfite sequencing and implemented an analytical pipeline to assess the key parameters in the process of m5C calling. We found that RNA fragmentation after bisulfite conversion increased the yield significantly, and an additional high temperature treatment improved bisulfite conversion efficiency especially for sequence reads mapped to the mitochondrial transcriptome. Using Unique Molecular Identifiers (UMIs), we observed that PCR favors the amplification of unmethylated templates. The low sequencing quality of bisulfite-converted bases is a major contributor to the methylation artifacts. In addition, we found that mitochondrial transcripts are frequently resistant to bisulfite conversion and no p-m5C sites with high confidence could be identified on mitochondrial mRNAs. Taken together, this study reveals the various sources of artifacts in RNA bisulfite sequencing data and provides an improved experimental procedure together with analytical methodology.

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Section: Introductionmentioning

confidence: 97%

Systematic evaluation of parameters in RNA bisulfite sequencing data generation and analysis

Johnson

Pacholec

et al. 2022

NAR Genomics and Bioinformatics

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“…Secondly, our research mainly focused on bioinformatic analysis, more experimental studies exploring the function of m 5 C on the different types of RNA and sites in COAD are in urgent need in future work. The m 5 C-Atlas database, a comprehensive database for decoding and annotating the m 5 C epitranscriptome, may be useful in the research ( Ma et al, 2022 ). Thirdly, overall survival between cluster Ⅰ and cluster Ⅱ had no significant difference, more m 5 C-related regulators and more cohort need to be included in future analysis.…”

Section: Discussionmentioning

confidence: 99%

Exploration of Potential Roles of m5C-Related Regulators in Colon Adenocarcinoma Prognosis

Huang

Jiang

et al. 2022

Front. Genet.

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Objectives: The purpose of this study was to investigate the role of 13 m5C-related regulators in colon adenocarcinoma (COAD) and determine their prognostic value.Methods: Gene expression and clinicopathological data were obtained from The Cancer Genome Atlas (TCGA) datasets. The expression of m5C-related regulators was analyzed with clinicopathological characteristics and alterations within m5C-related regulators. Subsequently, different subtypes of patients with COAD were identified. Then, the prognostic value of m5C-related regulators in COAD was confirmed via univariate Cox regression and least absolute shrinkage and selection operator (LASSO) Cox regression analyses. The prognostic value of risk scores was evaluated using the Kaplan-Meier method, receiver operating characteristic (ROC) curve. The correlation between the two m5C-related regulators, risk score, and clinicopathological characteristics were explored. Additionally, Gene Set Enrichment Analysis (GSEA), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and Gene Ontology (GO) analysis were performed for biological functional analysis. Finally, the expression level of two m5C-related regulators in clinical samples and cell lines was detected by quantitative reverse transcription-polymerase chain reaction and through the Human Protein Atlas database.Results: m5C-related regulators were found to be differentially expressed in COAD with different clinicopathological features. We observed a high alteration frequency in these genes, which were significantly correlated with their mRNA expression levels. Two clusters with different prognostic features were identified. Based on two independent prognostic m5C-related regulators (NSUN6 and ALYREF), a risk signature with good predictive significance was constructed. Univariate and multivariate Cox regression analyses suggested that the risk score was an independent prognostic factor. Furthermore, this risk signature could serve as a prognostic indicator for overall survival in subgroups of patients with different clinical characteristics. Biological processes and pathways associated with cancer, immune response, and RNA processing were identified.Conclusion: We revealed the genetic signatures and prognostic values of m5C-related regulators in COAD. Together, this has improved our understanding of m5C RNA modification and provided novel insights to identify predictive biomarkers and develop molecular targeted therapy for COAD.

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“…m6A-Atlas ( Tang et al, 2021 ) and SRAMP( Zhou et al, 2016 ) were used to predict the m6A site of the lncRNAs; m5C-Atlas ( Ma et al, 2022 ) and RNAm5Cfinder ( Li et al, 2018 ) were used to predict the m5C site of the lncRNAs; m7GHub ( Song et al, 2020 ) and iRNA-m7G ( Chen et al, 2019 ) databases were used to predict the m7G site of the lncRNAs.…”

Section: Methodsmentioning

confidence: 99%

Identification of RNA Methylation-Related lncRNAs Signature for Predicting Hot and Cold Tumors and Prognosis in Colon Cancer

Man

Huang

et al. 2022

Front. Genet.

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N6-methyladenosine (m6A), N1-methyladenosine (m1A), 5-methylcytosine (m5C), and 7-methylguanosine (m7G) are the major forms of RNA methylation modifications, which are closely associated with the development of many tumors. However, the prognostic value of RNA methylation-related long non-coding RNAs (lncRNAs) in colon cancer (CC) has not been defined. This study summarised 50 m6A/m1A/m5C/m7G-related genes and downloaded 41 normal and 471 CC tumor samples with RNA-seq data and clinicopathological information from The Cancer Genome Atlas (TCGA) database. A total of 1057 RNA methylation-related lncRNAs (RMlncRNAs) were identified with Pearson correlation analysis. Twenty-three RMlncRNAs with prognostic values were screened using univariate Cox regression analysis. By consensus clustering analysis, CC patients were classified into two molecular subtypes (Cluster 1 and Cluster 2) with different clinical outcomes and immune microenvironmental infiltration characteristics. Cluster 2 was considered to be the “hot tumor” with a better prognosis, while cluster 1 was regarded as the “cold tumor” with a poorer prognosis. Subsequently, we constructed a seven-lncRNA prognostic signature using the least absolute shrinkage and selection operator (LASSO) Cox regression. In combination with other clinical traits, we found that the RNA methylation-related lncRNA prognostic signature (called the “RMlnc-score”) was an independent prognostic factor for patients with colon cancer. In addition, immune infiltration, immunotherapy response analysis, and half-maximum inhibitory concentration (IC50) showed that the low RMlnc-score group was more sensitive to immunotherapy, while the high RMlnc-score group was sensitive to more chemotherapeutic agents. In summary, the RMlnc-score we developed could be used to predict the prognosis, immunotherapy response, and drug sensitivity of CC patients, guiding more accurate, and personalized treatment regimens.

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m5C-Atlas: a comprehensive database for decoding and annotating the 5-methylcytosine (m5C) epitranscriptome

Cited by 66 publications

References 50 publications

Systematic evaluation of parameters in RNA bisulfite sequencing data generation and analysis

Systematic evaluation of parameters in RNA bisulfite sequencing data generation and analysis

Exploration of Potential Roles of m5C-Related Regulators in Colon Adenocarcinoma Prognosis

Identification of RNA Methylation-Related lncRNAs Signature for Predicting Hot and Cold Tumors and Prognosis in Colon Cancer

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