BIOINFORMATICS REVIEW- SEPTEMBER 2016

Sep 2016 VOL 2 ISSUE 9

“Bad times have a scientific value.

These are occasions a good learner would not miss.”

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Ralph Waldo Emerson

PcircRNA_finder: Tool to predict circular RNA in plants

PcircRNA_finder: Tool to predict circular RNA in plants

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Contents

September 2016

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Topics Editorial....

03 Tools PcircRNA_finder: Tool to predict circular RNA in plants 07

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EDITOR Dr. PRASHANT PANT FOUNDER TARIQ ABDULLAH EDITORIAL EXECUTIVE EDITOR TARIQ ABDULLAH FOUNDING EDITOR MUNIBA FAIZA SECTION EDITORS FOZAIL AHMAD ALTAF ABDUL KALAM MANISH KUMAR MISHRA SANJAY KUMAR PRAKASH JHA NABAJIT DAS REPRINTS AND PERMISSIONS You must have permission before reproducing any material from Bioinformatics Review. Send E-mail requests to info@bioinformaticsreview.com. Please include contact detail in your message.

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PUBLICATION INFORMATION Volume 1, Number 1, Bioinformatics Reviewâ„¢ is published quarterly for one year (4 issues) by Social and Educational Welfare Association (SEWA)trust (Registered under Trust Act 1882). Copyright 2015 Sewa Trust. All rights reserved. Bioinformatics Review is a trademark of Idea Quotient Labs and used under license by SEWA trust. Published in India

EDITORIAL: Welcoming BiR in its 2nd year

EDITORIAL

Bioinformatics, being one of the best field in terms of future prospect, lacks one thing - a news source. For there are a lot of journals publishing a large number of quality research on a variety of topics such as genome analysis, algorithms, sequence analysis etc., they merely get any notice in the popular press.

Dr. Prashant Pant

Editor

One reason behind this, rather disturbing trend, is that there are very few people who can successfully read a research paper and make a news out of it. Plus, the bioinformatics community has not been yet introduced to research reporting. These factors are common to every relatively new (and rising) discipline such as bioinformatics.

Although there are a number of science reporting websites and portals, very few accept entries from their audience, which is expected to have expertise in some or the other field.

Bioinformatics Review has been conceptualized to address all these concerns. We will provide an insight into the bioinformatics - as an industry and as a research discipline. We will post new developments in bioinformatics, latest research.

We will also accept entries from our audience and if possible, we will also award them. To create an ecosystem of bioinformatics research reporting, we will engage all kind of people involved in bioinformatics - Students, professors, instructors and industries. We will also provide a free job listing service for anyone who can benefit out of it.

Letters and responses: info@bioinformaticsreview.com

TOOLS

PcircRNA_finder: Tool to predict circular RNA in plants Image Credit: Stock Photos

“CircRNAs can serve as a miRNA sponge [1,2], and are capable of enhancing transcription of their host genes [3,4]. A new rRNA-depleted high-throughput RNA-Seq technology has revolutionized the discovery of circRNA in most of the species such as the mouse, human, rice and Arabidopsis [5,6].”

he non-coding circular RNAs (circRNA) play important role in controlling cellular processes. circRNAs are covalently bonded continuous closed loops which originate from the exonic region, known as exonic circRNA, but they can also arise from the intronic and the intergenic regions.

T

CircRNAs can serve as a miRNA sponge [1,2] and are capable of enhancing the transcription of their host genes [3,4]. A new rRNAdepleted high-throughput RNA-Seq technology has revolutionized the discovery of circRNA in most of the species such as the mouse, human, rice and Arabidopsis [5,6].

There are several circRNA prediction tools available such as find_circ and CIRCexplorer, which were primarily

developed using the databases of animals or humans [2,7,8-10]. Since these prediction methods are used to predict cricRNA for animal genomes and there is a large difference between the genome of animals and plants, therefore, these methods can not be used to predict the cricRNA of plants, otherwise, the results would not be accurate [11,12]. Li et al.,(2016), has developed a software known as "PcircRNA_finder" to predict the circRNA in plants genome [12].

Workflow of PcircRNA_finder:

Fig.1 Workflow of pcircRNA_finder [12] This software is basically designed to predict the exonic circRNA consisting of three modules (Fig.1): 

Catcher

It maps the paired-end reads and collect all backsplice sites on the basis of presently available fusion detection methods such as STAR-Fusion

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[13], Tophat-Fusion [14], find_circ [2], Mapsplice [15] and segemehl [16].

This gives backsplice sites and false positive sites which are filtered by the other module. 

Annotator

It annotates the candidate exonic backsplice sites on the basis of the available gene annotation [12]. It has been proved by recent studies that the backsplicing sites of circRNAs are flexible and their alternative splicing of circRNAs is prevalent [9,17]. Li et al., (2016) allowed the 5-bp flanking as many of the alternative splice sites occurred near the canonical splicing sites [12]. 

ii) Maps raw reads to it. iii) Confirm the backsplice sites.

PcircRNA_finder has been found to be more accurate after testing with a benchmark dataset by Li et al., (2016) [12].

For further reading, click here.

References: 1.

2.

3.

Hansen,T.B. et al. (2013) Natural RNA circles function as efficient microRNA sponges.

Nature, 495, 384–388 Memczak,S. et al. (2013) Circular RNAs are a large class of animal RNAs with regulatory potency. Nature, 495, 333–338.

Li,Z. et al. (2015) Exon-intron circular RNAs regulate transcription in the nucleus. Nat. Struct. Mol. Biol., 22, 256–264.

Filter 4.

This module functions for the quality control of the predicted circRNAs and requires at least one of the two kinds of splicing signals [18,19] a) a U2 based spliceosome (usually with a consensus sequence of GT-AG and GC-AG) and b) a U12-based minor spliceosome (usually with a consensus sequence of AT-AC)

5.

Lu,T. et al. (2015) Transcriptome-wide investigation of circular RNAs in rice. RNA, 21, 2076–2087.

6.

Ye,C.Y. et al. (2015) Widespread noncoding circular RNAs in plants. New Phytol., 208, 88– 95.

7.

Pan,X. and Xiong,K. (2015) PredcircRNA: computational classification of circular RNA from other long non-coding RNA using hybrid features. Mol. Biosyst., 11, 2219–2226

8.

Salzman,J. et al. (2013) Cell-type specific features of circular RNA expression. PLoS Genet., 9, e1003777

9.

Szabo,L. et al. (2015) Statistically based splicing detection reveals neural enrichment and tissue-specific induction of circular RNA

This module works as follows : i) Creates a pseudoRef file which holds all the flanking sequences of chiastic backsplice sites.

Zhang,Y. et al. (2013) Circular intronic long noncoding RNAs. Mol. Cell, 51, 792–806.

during human fetal development. Genome Biol., 16, 126., 10. Zhang,X.O. et al. (2014) Complementary sequence-mediated exon circularization. Cell, 159, 134–147 11. Ye,C.Y. et al. (2015) Widespread noncoding circular RNAs in plants. New Phytol., 208, 88– 95 12. Li Chen , Yongyi Yu , Xinchen Zhang , Chen Liu , Chuyu Ye and Longjiang Fan. PcircRNA_finder: a software for circRNA prediction in plants. Bioinformatics, 2016, 1– 2 doi: 10.1093/bioinformatics/btw496 13. Dobin,A. et al. (2013) STAR: ultrafast universal RNA-seq aligner. Bioinformatics, 29, 15–21.

14. Kim,D. and Salzberg,S.L. (2011) TopHatFusion: an algorithm for discovery of novel fusion transcripts. Genome Biol., 12, R72 15. Wang,K. et al. (2010) MapSplice: accurate mapping of RNA-seq reads for splice junction discovery. Nucleic Acids Res., 38, e178.

16. Hoffmann,S. et al. (2014) A multi-split mapping algorithm for circular RNA, splicing, trans-splicing and fusion detection. Genome Biol., 15, R34.

17. Starke,S. et al. (2015) Exon circularization requires canonical splice signals. Cell Rep., 10, 103–111 18. Reddy,A.S. et al. (2013) Complexity of the alternative splicing landscape in plants. Plant Cell, 25, 3657–3683 19. Staiger,D. and Brown,J.W. (2013) Alternative splicing at the intersection of biological timing, development, and stress responses.

Plant Cell, 25, 3640–3656

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