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

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Kunqi Chen ◽  
Zhen Wei ◽  
Hui Liu ◽  
João Pedro de Magalhães ◽  
Rong Rong ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
Gene Expression Regulation ◽  
Functional Characterization ◽  
Biological Significance ◽  
Global Perspective ◽  
Biological Functions ◽  
Rna Modifications ◽  
Rna Molecules ◽  
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.

scholarly journals Emerging Roles of Estrogen-Regulated Enhancer and Long Non-Coding RNAs

2020 ◽  
Vol 21 (10) ◽  
pp. 3711
Author(s):  
Melina J. Sedano ◽  
Alana L. Harrison ◽  
Mina Zilaie ◽  
Chandrima Das ◽  
Ramesh Choudhari ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Expression Patterns ◽  
Biological Significance ◽  
Rna Seq ◽  
Biological Functions ◽  
Protein Coding ◽  
Rna Molecules ◽  
Non Coding Rna ◽  
Genome Wide ◽  
Non Coding Rnas

Genome-wide RNA sequencing has shown that only a small fraction of the human genome is transcribed into protein-coding mRNAs. While once thought to be “junk” DNA, recent findings indicate that the rest of the genome encodes many types of non-coding RNA molecules with a myriad of functions still being determined. Among the non-coding RNAs, long non-coding RNAs (lncRNA) and enhancer RNAs (eRNA) are found to be most copious. While their exact biological functions and mechanisms of action are currently unknown, technologies such as next-generation RNA sequencing (RNA-seq) and global nuclear run-on sequencing (GRO-seq) have begun deciphering their expression patterns and biological significance. In addition to their identification, it has been shown that the expression of long non-coding RNAs and enhancer RNAs can vary due to spatial, temporal, developmental, or hormonal variations. In this review, we explore newly reported information on estrogen-regulated eRNAs and lncRNAs and their associated biological functions to help outline their markedly prominent roles in estrogen-dependent signaling.

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

2015 ◽  
Vol 44 (D1) ◽  
pp. D259-D265 ◽  
Author(s):  
Wen-Ju Sun ◽  
Jun-Hao Li ◽  
Shun Liu ◽  
Jie Wu ◽  
Hui Zhou ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
Sequencing Data ◽  
Rna Modifications ◽  
High Throughput Sequencing Data

scholarly journals HIV Modifies the m6A and m5C Epitranscriptomic Landscape of the Host Cell

2021 ◽  
Vol 1 ◽  
Author(s):  
Sara Cristinelli ◽  
Paolo Angelino ◽  
Andrew Janowczyk ◽  
Mauro Delorenzi ◽  
Angela Ciuffi
Keyword(s):  
Hiv Infection ◽  
High Throughput ◽  
Rna Splicing ◽  
High Throughput Sequencing ◽  
Infection Model ◽  
Rna Modifications ◽  
Hiv Replication ◽  
Web Resource ◽  
Mrna Extraction ◽  
The Impact

The study of RNA modifications, today known as epitranscriptomics, is of growing interest. The N6-methyladenosine (m6A) and 5-methylcytosine (m5C) RNA modifications are abundantly present on mRNA molecules, and impact RNA interactions with other proteins or molecules, thereby affecting cellular processes, such as RNA splicing, export, stability, and translation. Recently m6A and m5C marks were found to be present on human immunodeficiency (HIV) transcripts as well and affect viral replication. Therefore, the discovery of RNA methylation provides a new layer of regulation of HIV expression and replication, and thus offers novel array of opportunities to inhibit replication. However, no study has been performed to date to investigate the impact of HIV replication on the transcript methylation level in the infected cell. We used a productive HIV infection model, consisting of the CD4+ SupT1 T cell line infected with a VSV-G pseudotyped HIVeGFP-based vector, to explore the temporal landscape of m6A and m5C epitranscriptomic marks upon HIV infection, and to compare it to mock-treated cells. Cells were collected at 12, 24, and 36 h post-infection for mRNA extraction and FACS analysis. M6A RNA modifications were investigated by methylated RNA immunoprecipitation followed by high-throughput sequencing (MeRIP-Seq). M5C RNA modifications were investigated using a bisulfite conversion approach followed by high-throughput sequencing (BS-Seq). Our data suggest that HIV infection impacted the methylation landscape of HIV-infected cells, inducing mostly increased methylation of cellular transcripts upon infection. Indeed, differential methylation (DM) analysis identified 59 m6A hypermethylated and only 2 hypomethylated transcripts and 14 m5C hypermethylated transcripts and 7 hypomethylated ones. All data and analyses are also freely accessible on an interactive web resource (http://sib-pc17.unil.ch/HIVmain.html). Furthermore, both m6A and m5C methylations were detected on viral transcripts and viral particle RNA genomes, as previously described, but additional patterns were identified. This work used differential epitranscriptomic analysis to identify novel players involved in HIV life cycle, thereby providing innovative opportunities for HIV regulation.

scholarly journals Structures to the people!

eLife ◽  
2015 ◽  
Vol 4 ◽  
Author(s):  
Nathan J Baird ◽  
Sebastian A Leidel
Keyword(s):  
High Throughput ◽  
3D Modeling ◽  
High Throughput Sequencing ◽  
Three Dimensional ◽  
Rna Molecules ◽  
The People

A combination of 3D modeling and high-throughput sequencing may offer a faster way to determine the three-dimensional structures of RNA molecules.

scholarly journals Characterization of Spanish Olive Virome by High Throughput Sequencing Opens New Insights and Uncertainties

Viruses ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2233
Author(s):  
Ana Belén Ruiz-García ◽  
Celia Canales ◽  
Félix Morán ◽  
Manuel Ruiz-Torres ◽  
Magdalena Herrera-Mármol ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
Biological Significance ◽  
Euphyllura Olivina ◽  
Leaf Yellowing ◽  
Full Length Sequence ◽  
Pros And Cons ◽  
Olive Trees ◽  
First Time ◽  
Viral Sequences

The use of high throughput sequencing (HTS) for the analysis of Spanish olive trees showing leaf yellowing discoloration, defoliation, and/or decline has provided new insights into the olive viruses present in Spain and has opened discussions about the pros and cons of these technologies for diagnostic purposes. In this study, we report for the first time in Spanish orchards the presence of olive leaf yellowing-associated virus (OLYaV), for which the second full coding sequence has been determined. This virus has also been detected in a putative vector, the psyllid Euphyllura olivina. In addition, the presence in Spain of Olea europaea geminivirus (OEGV), recently reported in Italy, has been confirmed, and the full-length sequence of two isolates was obtained by HTS and Sanger sequencing. These results, as well as the detection of other viral sequences related to olive latent virus 3 (OLV-3) and olive viral satellite RNA, raises questions on the biological significance of the findings, about the requirement of standardization on the interpretation of HTS results, and the necessity of additional tests to confirm the relevance of the HTS detection of viral sequences.

scholarly journals RNA modifications detection by comparative Nanopore direct RNA sequencing

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Adrien Leger ◽  
Paulo P. Amaral ◽  
Luca Pandolfini ◽  
Charlotte Capitanchik ◽  
Federica Capraro ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
High Throughput Sequencing ◽  
Control Sample ◽  
Analytical Framework ◽  
Rna Modifications ◽  
Rna Molecules ◽  
Oxford Nanopore ◽  
Experimental Approaches

AbstractRNA molecules undergo a vast array of chemical post-transcriptional modifications (PTMs) that can affect their structure and interaction properties. In recent years, a growing number of PTMs have been successfully mapped to the transcriptome using experimental approaches relying on high-throughput sequencing. Oxford Nanopore direct-RNA sequencing has been shown to be sensitive to RNA modifications. We developed and validated Nanocompore, a robust analytical framework that identifies modifications from these data. Our strategy compares an RNA sample of interest against a non-modified control sample, not requiring a training set and allowing the use of replicates. We show that Nanocompore can detect different RNA modifications with position accuracy in vitro, and we apply it to profile m6A in vivo in yeast and human RNAs, as well as in targeted non-coding RNAs. We confirm our results with orthogonal methods and provide novel insights on the co-occurrence of multiple modified residues on individual RNA molecules.

scholarly journals RNA modifications detection by comparative Nanopore direct RNA sequencing

2019 ◽  
Author(s):  
Adrien Leger ◽  
Paulo P. Amaral ◽  
Luca Pandolfini ◽  
Charlotte Capitanchik ◽  
Federica Capraro ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Single Molecule ◽  
High Throughput Sequencing ◽  
Control Sample ◽  
Analytical Framework ◽  
Rna Modifications ◽  
Rna Molecules ◽  
Naturally Occurring ◽  
Oxford Nanopore ◽  
Experimental Approaches

AbstractRNA molecules undergo a vast array of chemical post-transcriptional modifications (PTMs) that can affect their structure and interaction properties. To date, over 150 naturally occurring PTMs have been identified, however the overwhelming majority of their functions remain elusive. In recent years, a small number of PTMs have been successfully mapped to the transcriptome using experimental approaches relying on high-throughput sequencing. Oxford Nanopore direct-RNA sequencing (DRS) technology has been shown to be sensitive to RNA modifications. We developed and validated Nanocompore, a robust analytical framework to evaluate the presence of modifications in DRS data. To do so, we compare an RNA sample of interest against a non-modified control sample. Our strategy does not require a training set and allows the use of replicates to model biological variability. Here, we demonstrate the ability of Nanocompore to detect RNA modifications at single-molecule resolution in human polyA+ RNAs, as well as in targeted non-coding RNAs. Our results correlate well with orthogonal methods, confirm previous observations on the distribution of N6-methyladenosine sites and provide novel insights into the distribution of RNA modifications in the coding and non-coding transcriptomes. The latest version of Nanocompore can be obtained at https://github.com/tleonardi/nanocompore.

Sign in / Sign up

Export Citation Format

Share Document