TrawlerWeb: an online de novo motif discovery tool for next-generation sequencing datasets

Abstract Background A strong focus of the post-genomic era is mining of the non-coding regulatory genome in order to unravel the function of regulatory elements that coordinate gene expression (Nat 489:57–74, 2012; Nat 507:462–70, 2014; Nat 507:455–61, 2014; Nat 518:317–30, 2015). Whole-genome appro...

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Main Authors: Louis T. Dang, Markus Tondl, Man Ho H. Chiu, Jerico Revote, Benedict Paten, Vincent Tano, Alex Tokolyi, Florence Besse, Greg Quaife-Ryan, Helen Cumming, Mark J. Drvodelic, Michael P. Eichenlaub, Jeannette C. Hallab, Julian S. Stolper, Fernando J. Rossello, Marie A. Bogoyevitch, David A. Jans, Hieu T. Nim, Enzo R. Porrello, James E. Hudson, Mirana Ramialison
Format: Article
Language:English
Published: BMC 2018-04-01
Series:BMC Genomics
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12864-018-4630-0
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author Louis T. Dang
Markus Tondl
Man Ho H. Chiu
Jerico Revote
Benedict Paten
Vincent Tano
Alex Tokolyi
Florence Besse
Greg Quaife-Ryan
Helen Cumming
Mark J. Drvodelic
Michael P. Eichenlaub
Jeannette C. Hallab
Julian S. Stolper
Fernando J. Rossello
Marie A. Bogoyevitch
David A. Jans
Hieu T. Nim
Enzo R. Porrello
James E. Hudson
Mirana Ramialison
spellingShingle Louis T. Dang
Markus Tondl
Man Ho H. Chiu
Jerico Revote
Benedict Paten
Vincent Tano
Alex Tokolyi
Florence Besse
Greg Quaife-Ryan
Helen Cumming
Mark J. Drvodelic
Michael P. Eichenlaub
Jeannette C. Hallab
Julian S. Stolper
Fernando J. Rossello
Marie A. Bogoyevitch
David A. Jans
Hieu T. Nim
Enzo R. Porrello
James E. Hudson
Mirana Ramialison
TrawlerWeb: an online de novo motif discovery tool for next-generation sequencing datasets
BMC Genomics
Motif discovery
Transcription factor binding site
Motif conservation
Chromatin immunoprecipitation
Next generation sequencing
author_facet Louis T. Dang
Markus Tondl
Man Ho H. Chiu
Jerico Revote
Benedict Paten
Vincent Tano
Alex Tokolyi
Florence Besse
Greg Quaife-Ryan
Helen Cumming
Mark J. Drvodelic
Michael P. Eichenlaub
Jeannette C. Hallab
Julian S. Stolper
Fernando J. Rossello
Marie A. Bogoyevitch
David A. Jans
Hieu T. Nim
Enzo R. Porrello
James E. Hudson
Mirana Ramialison
author_sort Louis T. Dang
title TrawlerWeb: an online de novo motif discovery tool for next-generation sequencing datasets
title_short TrawlerWeb: an online de novo motif discovery tool for next-generation sequencing datasets
title_full TrawlerWeb: an online de novo motif discovery tool for next-generation sequencing datasets
title_fullStr TrawlerWeb: an online de novo motif discovery tool for next-generation sequencing datasets
title_full_unstemmed TrawlerWeb: an online de novo motif discovery tool for next-generation sequencing datasets
title_sort trawlerweb: an online de novo motif discovery tool for next-generation sequencing datasets
publisher BMC
series BMC Genomics
issn 1471-2164
publishDate 2018-04-01
description Abstract Background A strong focus of the post-genomic era is mining of the non-coding regulatory genome in order to unravel the function of regulatory elements that coordinate gene expression (Nat 489:57–74, 2012; Nat 507:462–70, 2014; Nat 507:455–61, 2014; Nat 518:317–30, 2015). Whole-genome approaches based on next-generation sequencing (NGS) have provided insight into the genomic location of regulatory elements throughout different cell types, organs and organisms. These technologies are now widespread and commonly used in laboratories from various fields of research. This highlights the need for fast and user-friendly software tools dedicated to extracting cis-regulatory information contained in these regulatory regions; for instance transcription factor binding site (TFBS) composition. Ideally, such tools should not require prior programming knowledge to ensure they are accessible for all users. Results We present TrawlerWeb, a web-based version of the Trawler_standalone tool (Nat Methods 4:563–5, 2007; Nat Protoc 5:323–34, 2010), to allow for the identification of enriched motifs in DNA sequences obtained from next-generation sequencing experiments in order to predict their TFBS composition. TrawlerWeb is designed for online queries with standard options common to web-based motif discovery tools. In addition, TrawlerWeb provides three unique new features: 1) TrawlerWeb allows the input of BED files directly generated from NGS experiments, 2) it automatically generates an input-matched biologically relevant background, and 3) it displays resulting conservation scores for each instance of the motif found in the input sequences, which assists the researcher in prioritising the motifs to validate experimentally. Finally, to date, this web-based version of Trawler_standalone remains the fastest online de novo motif discovery tool compared to other popular web-based software, while generating predictions with high accuracy. Conclusions TrawlerWeb provides users with a fast, simple and easy-to-use web interface for de novo motif discovery. This will assist in rapidly analysing NGS datasets that are now being routinely generated. TrawlerWeb is freely available and accessible at: http://trawler.erc.monash.edu.au.
topic Motif discovery
Transcription factor binding site
Motif conservation
Chromatin immunoprecipitation
Next generation sequencing
url http://link.springer.com/article/10.1186/s12864-018-4630-0
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spelling doaj-0f1f44ab434441b7b91c6e11217543db2020-11-24T23:56:09ZengBMCBMC Genomics1471-21642018-04-011911910.1186/s12864-018-4630-0TrawlerWeb: an online de novo motif discovery tool for next-generation sequencing datasetsLouis T. Dang0Markus Tondl1Man Ho H. Chiu2Jerico Revote3Benedict Paten4Vincent Tano5Alex Tokolyi6Florence Besse7Greg Quaife-Ryan8Helen Cumming9Mark J. Drvodelic10Michael P. Eichenlaub11Jeannette C. Hallab12Julian S. Stolper13Fernando J. Rossello14Marie A. Bogoyevitch15David A. Jans16Hieu T. Nim17Enzo R. Porrello18James E. Hudson19Mirana Ramialison20Australian Regenerative Medicine Institute, Systems Biology Institute Australia, Monash UniversityAustralian Regenerative Medicine Institute, Systems Biology Institute Australia, Monash UniversityAustralian Regenerative Medicine Institute, Systems Biology Institute Australia, Monash UniversityeResearch, Monash UniversityUC Santa Cruz Genomics Institute, University of CaliforniaDepartment of Biochemistry and Molecular Biology, Bio21 Institute and Cell Signalling Research Laboratories, The University of MelbourneAustralian Regenerative Medicine Institute, Systems Biology Institute Australia, Monash UniversityCNRS, Inserm, Institute of Biology Valrose, Université Côte d’AzurSchool of Biomedical Sciences, The University of QueenslandCentre for Innate Immunity and Infectious Diseases, Hudson Institute of Medical Research, Monash UniversityAustralian Regenerative Medicine Institute, Systems Biology Institute Australia, Monash UniversityAustralian Regenerative Medicine Institute, Systems Biology Institute Australia, Monash UniversityAustralian Regenerative Medicine Institute, Systems Biology Institute Australia, Monash UniversityAustralian Regenerative Medicine Institute, Systems Biology Institute Australia, Monash UniversityAustralian Regenerative Medicine Institute, Systems Biology Institute Australia, Monash UniversityDepartment of Biochemistry and Molecular Biology, Bio21 Institute and Cell Signalling Research Laboratories, The University of MelbourneDepartment of Biochemistry and Molecular Biology, Monash UniversityAustralian Regenerative Medicine Institute, Systems Biology Institute Australia, Monash UniversityMurdoch Children’s Research Institute, The Royal Children’s HospitalSchool of Biomedical Sciences, The University of QueenslandAustralian Regenerative Medicine Institute, Systems Biology Institute Australia, Monash UniversityAbstract Background A strong focus of the post-genomic era is mining of the non-coding regulatory genome in order to unravel the function of regulatory elements that coordinate gene expression (Nat 489:57–74, 2012; Nat 507:462–70, 2014; Nat 507:455–61, 2014; Nat 518:317–30, 2015). Whole-genome approaches based on next-generation sequencing (NGS) have provided insight into the genomic location of regulatory elements throughout different cell types, organs and organisms. These technologies are now widespread and commonly used in laboratories from various fields of research. This highlights the need for fast and user-friendly software tools dedicated to extracting cis-regulatory information contained in these regulatory regions; for instance transcription factor binding site (TFBS) composition. Ideally, such tools should not require prior programming knowledge to ensure they are accessible for all users. Results We present TrawlerWeb, a web-based version of the Trawler_standalone tool (Nat Methods 4:563–5, 2007; Nat Protoc 5:323–34, 2010), to allow for the identification of enriched motifs in DNA sequences obtained from next-generation sequencing experiments in order to predict their TFBS composition. TrawlerWeb is designed for online queries with standard options common to web-based motif discovery tools. In addition, TrawlerWeb provides three unique new features: 1) TrawlerWeb allows the input of BED files directly generated from NGS experiments, 2) it automatically generates an input-matched biologically relevant background, and 3) it displays resulting conservation scores for each instance of the motif found in the input sequences, which assists the researcher in prioritising the motifs to validate experimentally. Finally, to date, this web-based version of Trawler_standalone remains the fastest online de novo motif discovery tool compared to other popular web-based software, while generating predictions with high accuracy. Conclusions TrawlerWeb provides users with a fast, simple and easy-to-use web interface for de novo motif discovery. This will assist in rapidly analysing NGS datasets that are now being routinely generated. TrawlerWeb is freely available and accessible at: http://trawler.erc.monash.edu.au.http://link.springer.com/article/10.1186/s12864-018-4630-0Motif discoveryTranscription factor binding siteMotif conservationChromatin immunoprecipitationNext generation sequencing