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Bioinformatics of RNA Modifications and Epitranscriptome
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Bioinformatics of RNA Modifications and Epitranscriptome

A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Bioinformatics".

Deadline for manuscript submissions: 20 July 2024 | Viewed by 2304

Special Issue Editors

Dr. Bowen Song

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Guest Editor
Department of Public Health, Nanjing University of Chinese Medicine, Nanjing 210023, China
Interests: RNA modification; bioinformatics; epitranscriptomics; data mining
Dr. Kunqi Chen

E-Mail Website
Guest Editor
Key Laboratory of Ministry of Education for Gastrointestinal Cancer, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350004, China
Interests: epitranscriptomics; bioinformatics; cancer biology
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Fuyi Li

E-Mail Website
Guest Editor
College of Information Engineering, Northwest A&F University, Yangling 712100, China
Interests: bioinformatics; epitranscriptomics; machine learning

Special Issue Information

Dear Colleagues,

We would like to invite you to participate to this Special Issue, titled “Bioinformatics of RNA modifications and Epitranscriptome”.

To date, more than 170 types of post-transcriptional RNA modifications which occur on all types of RNA and regulate nearly every stage of RNA life have been discovered. Increasing evidence has suggested that RNA modifications regulate many molecular functions and biological processes, including (but not limited to) gene expression regulation, translation, embryo development, and mRNA stability. With the accumulation of a large number of high-throughput datasets, bioinformatics approaches have become increasingly critical for unraveling the epitranscriptome.

In this Special Issue, we aim to gather articles from every aspect of the emerging topics in epitranscriptome bioinformatics. We will consider, among other things, new results from computational and experimental combined analysis, novel bioinformatics approaches/pipelines, bioinformatics and epigenetics analysis, new/updated epitranscriptome databases, and new software tools for analysis epigenetics data, as well as review articles for publication.

Dr. Bowen Song
Dr. Kunqi Chen
Prof. Dr. Fuyi Li
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Genes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • epitranscriptomics
  • RNA modification
  • data mining
  • database
  • bioinformatics

Published Papers (2 papers)

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Research

18 pages, 3983 KiB  
Article
Unveiling the Impact of ApoF Deficiency on Liver and Lipid Metabolism: Insights from Transcriptome-Wide m6A Methylome Analysis in Mice
by Xuebin Shen, Mengting Chen, Jian Zhang, Yifan Lin, Xinyue Gao, Jionghong Tu, Kunqi Chen, An Zhu and Shanghua Xu
Genes 2024, 15(3), 347; https://doi.org/10.3390/genes15030347 - 09 Mar 2024
Viewed by 871
Abstract
Lipid metabolism participates in various physiological processes and has been shown to be connected to the development and progression of multiple diseases, especially metabolic hepatopathy. Apolipoproteins (Apos) act as vectors that combine with lipids, such as cholesterol and triglycerides (TGs). Despite being involved [...] Read more.
Lipid metabolism participates in various physiological processes and has been shown to be connected to the development and progression of multiple diseases, especially metabolic hepatopathy. Apolipoproteins (Apos) act as vectors that combine with lipids, such as cholesterol and triglycerides (TGs). Despite being involved in lipid transportation and metabolism, the critical role of Apos in the maintenance of lipid metabolism has still not been fully revealed. This study sought to clarify variations related to m6A methylome in ApoF gene knockout mice with disordered lipid metabolism based on the bioinformatics method of transcriptome-wide m6A methylome epitranscriptomics. High-throughput methylated RNA immunoprecipitation sequencing (MeRIP-seq) was conducted in both wild-type (WT) and ApoF knockout (KO) mice. As a result, the liver histopathology presented vacuolization and steatosis, and the serum biochemical assays reported abnormal lipid content in KO mice. The m6A-modified mRNAs were conformed consensus sequenced in eukaryotes, and the distribution was enriched within the coding sequences and 3′ non-coding regions. In KO mice, the functional annotation terms of the differentially expressed genes (DEGs) included cholesterol, steroid and lipid metabolism, and lipid storage. In the differentially m6A-methylated mRNAs, the functional annotation terms included cholesterol, TG, and long-chain fatty acid metabolic processes; lipid transport; and liver development. The overlapping DEGs and differential m6A-modified mRNAs were also enriched in terms of lipid metabolism disorder. In conclusion, transcriptome-wide MeRIP sequencing in ApoF KO mice demonstrated the role of this crucial apolipoprotein in liver health and lipid metabolism. Full article
(This article belongs to the Special Issue Bioinformatics of RNA Modifications and Epitranscriptome)
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20 pages, 6508 KiB  
Article
Molecular Characterization and Establishment of a Prognostic Model Based on Primary Immunodeficiency Features in Association with RNA Modifications in Triple-Negative Breast Cancer
by Hongzhuo Xia, Xi Xu, Yuxuan Guo, Xiyun Deng, Yian Wang and Shujun Fu
Genes 2023, 14(12), 2172; https://doi.org/10.3390/genes14122172 - 02 Dec 2023
Viewed by 1026
Abstract
Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer. Although immunotherapy is effective for some patients, most find it difficult to benefit from it. This study aims to explore the impact of specific immune pathways and their regulated molecular mechanisms [...] Read more.
Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer. Although immunotherapy is effective for some patients, most find it difficult to benefit from it. This study aims to explore the impact of specific immune pathways and their regulated molecular mechanisms in TNBC. The gene expression data of breast cancer patients were obtained from the TCGA and METABRIC databases. Gene set variation analysis (GSVA) revealed specific upregulation or abnormal expression of immunodeficiency pathways in TNBC patients. Multi-omics data showed significant differential expression of Primary Immunodeficiency Genes (PIDGs) in TNBC patients, who are prone to genomic-level variations. Consensus clustering was used in two datasets to classify patients into two distinct molecular subtypes based on PIDGs expression patterns, with each displaying different biological features and immune landscapes. To further explore the prognostic characteristics of PIDGs-regulated molecules, we constructed a four-gene prognostic PIDG score model and a nomogram using least absolute shrinkage and selection operator (LASSO) regression analysis in combination with clinicopathological parameters. The PIDG score was closely associated with the immune therapy and drug sensitivity of TNBC patients, providing potential guidance for clinical treatment. Particularly noteworthy is the close association of this scoring with RNA modifications; patients with different scores also exhibited different mutation landscapes. This study offers new insights for the clinical treatment of TNBC and for identifying novel prognostic markers and therapeutic targets in TNBC. Full article
(This article belongs to the Special Issue Bioinformatics of RNA Modifications and Epitranscriptome)
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