scholarly journals sRNA Profiler: A User-Focused Interface for Small RNA Mapping and Profiling

Cells ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 1771
Author(s):  
Charith Raj Adkar-Purushothama ◽  
Pavithran Sridharan Iyer ◽  
Teruo Sano ◽  
Jean-Pierre Perreault
Keyword(s):  
Deep Sequencing ◽  
Small Rnas ◽  
Sequence Similarity ◽  
Circular Rna ◽  
Sequencing Data ◽  
Rna Molecules ◽  
Non Coding Rna ◽  
Viroid Pathogenicity ◽  
Rna Mapping ◽  
Target Rna

Viroids are circular, highly structured, single-stranded, non-coding RNA pathogens known to infect and cause disease in several plant species. They are known to trigger the host plant’s RNA silencing machinery. The detection of viroid-derived small RNAs (vd-sRNA) in viroid-infected host plants opened a new avenue of study in host–viroid pathogenicity. Since then, several viroid research groups have studied the vd-sRNA retrieved from different host–viroid combinations. Such studies require the segregation of 21- to 24-nucleotide long small RNAs (sRNA) from a deep-sequencing databank, followed by separating the vd-sRNA from any sRNA within this group that showed sequence similarity with either the genomic or the antigenomic strands of the viroid. Such mapped vdsRNAs are then profiled on both the viroid’s genomic and antigenomic strands for visualization. Although several commercial interfaces are currently available for this purpose, they are all programmed for linear RNA molecules. Hence, viroid researchers must develop a computer program that accommodates the sRNAs derived from the circular viroid genome. This is a laborious process, and consequently, it often creates a bottleneck for biologists. In order to overcome this constraint, and to help the research community in general, in this study, a python-based pattern matching interface was developed so as to be able to both profile and map sRNAs on a circular genome. A “matching tolerance” feature has been included in the program, thus permitting the mapping of the sRNAs derived from the quasi-species. Additionally, the “topology” feature allows the researcher to profile sRNA derived from both linear and circular RNA molecules. The efficiency of the program was tested using previously reported deep-sequencing data obtained from two independent studies. Clearly, this novel software should be a key tool with which to both evaluate the production of sRNA and to profile them on their target RNA species, irrespective of the topology of the target RNA molecule.

scholarly journals Oasis2.0: improved online analysis of small RNA-seq data

2017 ◽  
Author(s):  
Raza-Ur Rahman ◽  
Abhivyakti Gautam ◽  
Jörn Bethune ◽  
Abdul Sattar ◽  
Maksims Fiosins ◽  
...  
Keyword(s):  
Deep Sequencing ◽  
Small Rna ◽  
Small Rnas ◽  
Web Application ◽  
The Novel ◽  
Sequencing Data ◽  
Essential Information ◽  
Deep Sequencing Data ◽  
Small Rna Deep Sequencing ◽  
User Friendly

AbstractOasis 2 is a new main release of the Oasis web application for the detection, differential expression, and classification of small RNAs in deep sequencing data. Compared to its predecessor Oasis, Oasis 2 features a novel and speed-optimized sRNA detection module that supports the identification of small RNAs in any organism with higher accuracy. Next to the improved detection of small RNAs in a target organism, the software now also recognizes potential cross-species miRNAs and viral and bacterial sRNAs in infected samples. In addition, novel miRNAs can now be queried and visualized interactively, providing essential information for over 700 high-quality miRNA predictions across 14 organisms. Robust biomarker signatures can now be obtained using the novel enhanced classification module. Oasis 2 enables biologists and medical researchers to rapidly analyze and query small RNA deep sequencing data with improved precision, recall, and speed, in an interactive and user-friendly environment.Availability and Implementation: Oasis 2 is implemented in Java, J2EE, mysql, Python, R, PHP and JavaScript. It is freely available at http://oasis.dzne.de

scholarly journals deepBase v2.0: identification, expression, evolution and function of small RNAs, LncRNAs and circular RNAs from deep-sequencing data

2015 ◽  
Vol 44 (D1) ◽  
pp. D196-D202 ◽  
Author(s):  
Ling-Ling Zheng ◽  
Jun-Hao Li ◽  
Jie Wu ◽  
Wen-Ju Sun ◽  
Shun Liu ◽  
...  
Keyword(s):  
Deep Sequencing ◽  
Small Rnas ◽  
Circular Rnas ◽  
Sequencing Data ◽  
Deep Sequencing Data ◽  
Expression Evolution ◽  
And Function

scholarly journals Identification of Novel MicroRNA-Like Molecules Generated from Herpesvirus and Host tRNA Transcripts

2010 ◽  
Vol 84 (19) ◽  
pp. 10344-10353 ◽  
Author(s):  
Tiffany A. Reese ◽  
Jing Xia ◽  
L. Steven Johnson ◽  
Xiang Zhou ◽  
Weixiong Zhang ◽  
...  
Keyword(s):  
Deep Sequencing ◽  
Small Rnas ◽  
Northern Blot Analysis ◽  
Sequencing Data ◽  
Viral Genomes ◽  
Murine Gammaherpesvirus ◽  
Deep Sequencing Technology ◽  
Gammaherpesvirus 68 ◽  
Pol Iii ◽  
Murine Gammaherpesvirus 68

ABSTRACT We applied deep sequencing technology to small RNA fractions from cells lytically infected with murine gammaherpesvirus 68 (γHV68) in order to define in detail small RNAs generated from a cluster of tRNA-related polycistronic structures located at the left end of the viral genome. We detected 10 new candidate microRNAs (miRNAs), six of which were confirmed by Northern blot analysis, leaving four as provisional. In addition, we determined that previously identified and annotated viral miRNA molecules were not necessarily represented as the most abundant sequence originating from a transcript. Based on these new small RNAs and previously reported γHV68 miRNAs, we were able to further describe and annotate the distinctive γHV68 tRNA-miRNA structures. We used this deep sequencing data and computational analysis to identify similar structures in the mouse genome and validated that these host structures also give rise to small RNAs. This reveals a possible convergent usage of tRNA/polymerase III (pol III) transcripts to generate small RNAs from both mammalian and viral genomes.

scholarly journals Filtering of deep sequencing data reveals the existence of abundant Dicer-dependent small RNAs derived from tRNAs

RNA ◽  
2009 ◽  
Vol 15 (12) ◽  
pp. 2147-2160 ◽  
Author(s):  
C. Cole ◽  
A. Sobala ◽  
C. Lu ◽  
S. R. Thatcher ◽  
A. Bowman ◽  
...  
Keyword(s):  
Deep Sequencing ◽  
Small Rnas ◽  
Sequencing Data ◽  
Deep Sequencing Data

How to find small non-coding RNAs in bacteria

2005 ◽  
Vol 386 (12) ◽  
pp. 1219-1238 ◽  
Author(s):  
Jörg Vogel ◽  
Cynthia Mira Sharma
Keyword(s):  
Small Rnas ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Critical Role ◽  
Rna Molecules ◽  
Regulatory Circuit ◽  
Non Coding Rna ◽  
Genome Wide ◽  
Response To Stress ◽  
Non Coding Rnas

AbstractSmall non-coding RNAs (sRNAs) have attracted considerable attention as an emerging class of gene expression regulators. In bacteria, a few regulatory RNA molecules have long been known, but the extent of their role in the cell was not fully appreciated until the recent discovery of hundreds of potential sRNA genes in the bacteriumEscherichia coli. Orthologs of theseE. colisRNA genes, as well as unrelated sRNAs, were also found in other bacteria. Here we review the disparate experimental approaches used over the years to identify sRNA molecules and their genes in prokaryotes. These include genome-wide searches based on the biocomputational prediction of non-coding RNA genes, global detection of non-coding transcripts using microarrays, and shotgun cloning of small RNAs (RNomics). Other sRNAs were found by either co-purification with RNA-binding proteins, such as Hfq or CsrA/RsmA, or classical cloning of abundant small RNAs after size fractionation in polyacrylamide gels. In addition, bacterial genetics offers powerful tools that aid in the search for sRNAs that may play a critical role in the regulatory circuit of interest, for example, the response to stress or the adaptation to a change in nutrient availability. Many of the techniques discussed here have also been successfully applied to the discovery of eukaryotic and archaeal sRNAs.

scholarly journals Hybridization-based reconstruction of small non-coding RNA transcripts from deep sequencing data

2012 ◽  
Vol 40 (16) ◽  
pp. 7633-7643 ◽  
Author(s):  
Chikako Ragan ◽  
Bryan J. Mowry ◽  
Denis C. Bauer
Keyword(s):  
Deep Sequencing ◽  
Sequencing Data ◽  
Rna Transcripts ◽  
Deep Sequencing Data ◽  
Non Coding Rna

scholarly journals The Role of cis- and trans-Acting RNA Regulatory Elements in Leukemia

Cancers ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3854
Author(s):  
Irina A. Elcheva ◽  
Vladimir S. Spiegelman
Keyword(s):  
Phenotypic Diversity ◽  
Circular Rna ◽  
Regulatory Elements ◽  
Micro Rna ◽  
Aberrant Expression ◽  
Cis Acting ◽  
Rna Molecules ◽  
Non Coding Rna ◽  
Recurrent Mutations ◽  
Cis And Trans

RNA molecules are a source of phenotypic diversity and an operating system that connects multiple genetic and metabolic processes in the cell. A dysregulated RNA network is a common feature of cancer. Aberrant expression of long non-coding RNA (lncRNA), micro RNA (miRNA), and circular RNA (circRNA) in tumors compared to their normal counterparts, as well as the recurrent mutations in functional regulatory cis-acting RNA motifs have emerged as biomarkers of disease development and progression, opening avenues for the design of novel therapeutic approaches. This review looks at the progress, challenges and future prospects of targeting cis-acting and trans-acting RNA elements for leukemia diagnosis and treatment.

C/D box sRNA, CRISPR RNA and tRNA processing in an archaeon with a minimal fragmented genome

2013 ◽  
Vol 41 (1) ◽  
pp. 411-415 ◽  
Author(s):  
Hagen Richter ◽  
Sabine Mohr ◽  
Lennart Randau
Keyword(s):  
Rna Processing ◽  
Sequencing Data ◽  
Rna Molecules ◽  
Non Coding Rna ◽  
Genome Wide ◽  
Single Organism ◽  
A Genome ◽  
Processing Pathways ◽  
Trna Half ◽  
Nanoarchaeum Equitans

The analysis of deep sequencing data allows for a genome-wide overview of all the small RNA molecules (the ‘sRNome’) that are present in a single organism. In the present paper, we review the processing of CRISPR (clustered regularly interspaced short palindromic repeats) RNA, C/D box sRNA (small non-coding RNA) and tRNA in Nanoarchaeum equitans. The minimal and fragmented genome of this tiny archaeon permits a sequencing depth that enables the identification of processing intermediates in the study of RNA processing pathways. These intermediates include circular C/D box sRNA molecules and tRNA half precursors.

scholarly journals SnoRNA in Cancer Progression, Metastasis and Immunotherapy Response

Biology ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 809
Author(s):  
Jildou van der Werf ◽  
Chue Vin Chin ◽  
Nicholas Ian Fleming
Keyword(s):  
Cancer Progression ◽  
Drug Targets ◽  
Cell Function ◽  
Immune Cell ◽  
Rna Molecules ◽  
Non Coding Rna ◽  
Cancer Types ◽  
Target Rna ◽  
Nucleolar Rna ◽  
Mtor Signalling

Small nucleolar RNA (snoRNA) were one of our earliest recognised classes of non-coding RNA, but were largely ignored by cancer investigators due to an assumption that their activities were confined to the nucleolus. However, as full genome sequences have become available, many new snoRNA genes have been identified, and multiple studies have shown their functions to be diverse. The consensus now is that many snoRNA are dysregulated in cancers, are differentially expressed between cancer types, stages and metastases, and they can actively modify disease progression. In addition, the regulation of the snoRNA class is dominated by the cancer-supporting mTOR signalling pathway, and they may have particular significance to immune cell function and anti-tumour immune responses. Given the recent advent of therapeutics that can target RNA molecules, snoRNA have robust potential as drug targets, either solely or in the context of immunotherapies.

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