Reproducible Analysis of Sequencing-Based RNA Structure Probing Data with User-Friendly Tools

2015 ◽  
pp. 153-180 ◽  
Author(s):  
Lukasz Jan Kielpinski ◽  
Nikolaos Sidiropoulos ◽  
Jeppe Vinther
Keyword(s):  
Rna Structure ◽  
Structure Probing ◽  
Reproducible Analysis ◽  
User Friendly

scholarly journals RASP: an atlas of transcriptome-wide RNA secondary structure probing data

2020 ◽  
Vol 49 (D1) ◽  
pp. D183-D191
Author(s):  
Pan Li ◽  
Xiaolin Zhou ◽  
Kui Xu ◽  
Qiangfeng Cliff Zhang
Keyword(s):  
Secondary Structure ◽  
Rna Structure ◽  
Rna Secondary Structure ◽  
Rna Virus ◽  
Complex Structures ◽  
Biological Processes ◽  
Rna Molecules ◽  
Structure Probing ◽  
Technological Developments ◽  
User Friendly

Abstract RNA molecules fold into complex structures that are important across many biological processes. Recent technological developments have enabled transcriptome-wide probing of RNA secondary structure using nucleases and chemical modifiers. These approaches have been widely applied to capture RNA secondary structure in many studies, but gathering and presenting such data from very different technologies in a comprehensive and accessible way has been challenging. Existing RNA structure probing databases usually focus on low-throughput or very specific datasets. Here, we present a comprehensive RNA structure probing database called RASP (RNA Atlas of Structure Probing) by collecting 161 deduplicated transcriptome-wide RNA secondary structure probing datasets from 38 papers. RASP covers 18 species across animals, plants, bacteria, fungi, and also viruses, and categorizes 18 experimental methods including DMS-seq, SHAPE-Seq, SHAPE-MaP, and icSHAPE, etc. Specially, RASP curates the up-to-date datasets of several RNA secondary structure probing studies for the RNA genome of SARS-CoV-2, the RNA virus that caused the on-going COVID-19 pandemic. RASP also provides a user-friendly interface to query, browse, and visualize RNA structure profiles, offering a shortcut to accessing RNA secondary structures grounded in experimental data. The database is freely available at http://rasp.zhanglab.net.

scholarly journals DIscBIO: A User-Friendly Pipeline for Biomarker Discovery in Single-Cell Transcriptomics

2021 ◽  
Vol 22 (3) ◽  
pp. 1399
Author(s):  
Salim Ghannoum ◽  
Waldir Leoncio Netto ◽  
Damiano Fantini ◽  
Benjamin Ragan-Kelley ◽  
Amirabbas Parizadeh ◽  
...  
Keyword(s):  
Single Cell ◽  
Biomarker Discovery ◽  
Enrichment Analysis ◽  
Myxoid Liposarcoma ◽  
R Package ◽  
Differential Analysis ◽  
A Cell ◽  
Reproducible Analysis ◽  
Transcriptomic Level ◽  
User Friendly

The growing attention toward the benefits of single-cell RNA sequencing (scRNA-seq) is leading to a myriad of computational packages for the analysis of different aspects of scRNA-seq data. For researchers without advanced programing skills, it is very challenging to combine several packages in order to perform the desired analysis in a simple and reproducible way. Here we present DIscBIO, an open-source, multi-algorithmic pipeline for easy, efficient and reproducible analysis of cellular sub-populations at the transcriptomic level. The pipeline integrates multiple scRNA-seq packages and allows biomarker discovery with decision trees and gene enrichment analysis in a network context using single-cell sequencing read counts through clustering and differential analysis. DIscBIO is freely available as an R package. It can be run either in command-line mode or through a user-friendly computational pipeline using Jupyter notebooks. We showcase all pipeline features using two scRNA-seq datasets. The first dataset consists of circulating tumor cells from patients with breast cancer. The second one is a cell cycle regulation dataset in myxoid liposarcoma. All analyses are available as notebooks that integrate in a sequential narrative R code with explanatory text and output data and images. R users can use the notebooks to understand the different steps of the pipeline and will guide them to explore their scRNA-seq data. We also provide a cloud version using Binder that allows the execution of the pipeline without the need of downloading R, Jupyter or any of the packages used by the pipeline. The cloud version can serve as a tutorial for training purposes, especially for those that are not R users or have limited programing skills. However, in order to do meaningful scRNA-seq analyses, all users will need to understand the implemented methods and their possible options and limitations.

scholarly journals FragSeq: transcriptome-wide RNA structure probing using high-throughput sequencing

2010 ◽  
Vol 7 (12) ◽  
pp. 995-1001 ◽  
Author(s):  
Jason G Underwood ◽  
Andrew V Uzilov ◽  
Sol Katzman ◽  
Courtney S Onodera ◽  
Jacob E Mainzer ◽  
...  
Keyword(s):  
High Throughput ◽  
Rna Structure ◽  
High Throughput Sequencing ◽  
Structure Probing

scholarly journals An ultra low-input method for global RNA structure probing uncovers Regnase-1-mediated regulation in macrophages

2021 ◽  
Author(s):  
Meiling Piao ◽  
Pan Li ◽  
Xiaomin Zeng ◽  
Xi-Wen Wang ◽  
Lan Kang ◽  
...  
Keyword(s):  
Rna Structure ◽  
Low Input ◽  
Input Method ◽  
Structure Probing

scholarly journals Physical and Functional Analysis of Viral RNA Genomes by SHAPE

2019 ◽  
Vol 6 (1) ◽  
pp. 93-117 ◽  
Author(s):  
Mark A. Boerneke ◽  
Jeffrey E. Ehrhardt ◽  
Kevin M. Weeks
Keyword(s):  
Rna Structure ◽  
Rna Viruses ◽  
Genome Structure ◽  
Regulatory Elements ◽  
Viral Rna ◽  
Host Immune Responses ◽  
Linear Sequence ◽  
Structure Probing ◽  
Shape Structure ◽  
Shape Selective

RNA viruses encode the information required to usurp cellular metabolism and gene regulation and to enable their own replication in two ways: in the linear sequence of their RNA genomes and in higher-order structures that form when the genomic RNA strand folds back on itself. Application of high-resolution SHAPE (selective 2′-hydroxyl acylation analyzed by primer extension) structure probing to viral RNA genomes has identified numerous new regulatory elements, defined new principles by which viral RNAs interact with the cellular host and evade host immune responses, and revealed relationships between virus evolution and RNA structure. This review summarizes our current understanding of genome structure-function interrelationships for RNA viruses, as informed by SHAPE structure probing, and outlines opportunities for future studies.

scholarly journals mRNA adenosine methylase (MTA) deposits m6A on pri-miRNAs to modulate miRNA biogenesis inArabidopsis thaliana

2020 ◽  
Vol 117 (35) ◽  
pp. 21785-21795 ◽  
Author(s):  
Susheel Sagar Bhat ◽  
Dawid Bielewicz ◽  
Tomasz Gulanicz ◽  
Zsuzsanna Bodi ◽  
Xiang Yu ◽  
...  
Keyword(s):  
Secondary Structure ◽  
Rna Polymerase ◽  
Rna Polymerase Ii ◽  
Rna Structure ◽  
Methylation Status ◽  
Mirna Biogenesis ◽  
Stem Loop ◽  
Structure Probing ◽  
Plant Transcriptome ◽  
Loop Regions

InArabidopsis thaliana, the METTL3 homolog, mRNA adenosine methylase (MTA) introducesN6-methyladenosine (m6A) into various coding and noncoding RNAs of the plant transcriptome. Here, we show that an MTA-deficient mutant (mta) has decreased levels of microRNAs (miRNAs) but accumulates primary miRNA transcripts (pri-miRNAs). Moreover, pri-miRNAs are methylated by MTA, and RNA structure probing analysis reveals a decrease in secondary structure within stem–loop regions of these transcripts inmtamutant plants. We demonstrate interaction between MTA and both RNA Polymerase II and TOUGH (TGH), a plant protein needed for early steps of miRNA biogenesis. Both MTA and TGH are necessary for efficient colocalization of the Microprocessor components Dicer-like 1 (DCL1) and Hyponastic Leaves 1 (HYL1) with RNA Polymerase II. We propose that secondary structure of miRNA precursors induced by their MTA-dependent m6A methylation status, together with direct interactions between MTA and TGH, influence the recruitment of Microprocessor to plant pri-miRNAs. Therefore, the lack of MTA inmtamutant plants disturbs pri-miRNA processing and leads to the decrease in miRNA accumulation. Furthermore, our findings reveal that reduced miR393b levels likely contributes to the impaired auxin response phenotypes ofmtamutant plants.

scholarly journals Robust statistical modeling improves sensitivity of high-throughput RNA structure probing experiments

2016 ◽  
Vol 14 (1) ◽  
pp. 83-89 ◽  
Author(s):  
Alina Selega ◽  
Christel Sirocchi ◽  
Ira Iosub ◽  
Sander Granneman ◽  
Guido Sanguinetti
Keyword(s):  
Statistical Modeling ◽  
High Throughput ◽  
Rna Structure ◽  
Structure Probing

scholarly journals RNA structure probing to characterize RNA-protein interactions on a low abundance pre-mRNA in living cells

RNA ◽  
2020 ◽  
pp. rna.077263.120
Author(s):  
Jodi L Bubenik ◽  
Melissa Hale ◽  
Ona McConnell ◽  
Eric Wang ◽  
Maurice S. Swanson ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Rna Structure ◽  
Living Cells ◽  
Structure Probing
Sign in / Sign up

Export Citation Format

Share Document