Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
An observation of circular RNAs in bacterial RNA-seq data.
KTH, School of Computer Science and Communication (CSC), Computational Biology, CB. (Computational Biological Physics, CBP)
KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
Luxembourg Centre for Systems Biomedicine, University of Luxembourg.
KTH, School of Computer Science and Communication (CSC), Computational Biology, CB. (Computational Biological Physics, CBP)
2015 (English)Manuscript (preprint) (Other academic)
Abstract [en]

Circular RNAs (circRNAs) are a class of RNA with an important role in micro RNA (miRNA) regulation recently discovered in Human and various other eukaryotes as well as in archaea. Here, we have analyzed RNA-seq data obtained from Enterococcus faecalis and Escherichia coli in a way similar to previous studies performed on eukaryotes. We report observations of circRNAs in RNA-seq data that are reproducible across multiple experiments performed with different protocols or growth conditions.

Place, publisher, year, edition, pages
2015.
Keyword [en]
Circular RNA, RNA-seq
National Category
Bioinformatics and Systems Biology
Research subject
Biological Physics; Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-173215OAI: oai:DiVA.org:kth-173215DiVA: diva2:853408
Note

QS 2015

Available from: 2015-09-13 Created: 2015-09-07 Last updated: 2016-02-02Bibliographically approved
In thesis
1. Data Analysis and Next Generation Sequencing : Applications in Microbiology.
Open this publication in new window or tab >>Data Analysis and Next Generation Sequencing : Applications in Microbiology.
2015 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Next Generation Sequencing (NGS) is a new technology that has revolutionized the way we study living organisms. Where previously only a few genes could be studied at a time through targeted direct probing, NGS offers the possibility to perform measurements for a whole genome at once. The drawback is that the amount of data generated in the process is large and extracting useful information from it requires new methods to process and analyze it.

The main contribution of this thesis is the development of a novel experimental method coined tagRNA-seq, combining 5’tagRACE, a previously developed technique, with RNA-sequencing technology. Briefly, tagRNA-seq makes it possible to identify the 5’ ends of RNAs in bacteria and directly probe for their type, primary or processed, by ligating short RNA sequences, the tags, to the beginnings of RNA molecules. We used the method to directly probe for transcription start and processing sites in two bacterial species, Escherichiacoli and Enterococcus faecalis. It was also used to study polyadenylation in E. coli, where the ability to identify processed RNA molecules proved to be useful to separate direct and indirect regulatory effects of this mechanism. We also demonstrate how data from tagRNA-seq experiments can be used to increase confidence on the discovery of anti-sense transcripts in bacteria. Analyses of RNA-seq data obtained in the context of these experiments revealed subtle artifacts in the coverage signal towards gene ends, that we were able to explain and quantify based Kolmogorov’s broken stick model. We also discovered evidences for circularization of a few RNA transcripts, both in our own data sets and publicly available data.

Designing the tags used in tagRNA-seq led us to the problem of words absent from a text. We focus on a particular subset of these, the minimal absent words (MAWs), and develop a theory providing a complete description of their size distribution in random text. We also show that MAWs in genomes from viruses and living organisms almost always exhibit a behavior different from random texts in the tail of the distribution, and that MAWs from this tail are closely related to sequences present in the genome that preferentially appear in regions with important regulatory functions.

Finally, and independently from tagRNA-seq, we propose a new approach to the problem of bacterial community reconstruction in metagenomic, based on techniques from compressed sensing. We provide a novel algorithm competing with state-of-the-art techniques in the field.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2015. xviii, 154 p.
Series
TRITA-CSC-A, ISSN 1653-5723 ; 2015:15
Keyword
RNA-seq, tagRNA-seq, primary and processed RNA, Enterococcus faecalis, Complex transcription, Metagenomics, 5'tagRACE, minimal absent words, compressed sensing, metagenomics, bacterial community reconstruction
National Category
Bioinformatics (Computational Biology) Microbiology Other Biological Topics Genetics
Research subject
Biological Physics
Identifiers
urn:nbn:se:kth:diva-173219 (URN)978-91-7595-699-2 (ISBN)
Public defence
2015-10-30, FA32, Roslagstullsbacken 21, Stockholm, 14:00 (English)
Opponent
Supervisors
Note

QC 20150930

Available from: 2015-09-30 Created: 2015-09-07 Last updated: 2015-11-06Bibliographically approved

Open Access in DiVA

No full text

Search in DiVA

By author/editor
Innocenti, NicolasNguyen, Hoang-SonAurell, Erik
By organisation
Computational Biology, CB
Bioinformatics and Systems Biology

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 652 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf