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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| Format: | Article |
| Language: | English |
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BMC
2018-04-01
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| Series: | BMC Genomics |
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| Online Access: | http://link.springer.com/article/10.1186/s12864-018-4630-0 |
| _version_ | 1818284021685157888 |
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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 |
| 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 |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-12-13T00:46:11Z |
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| id | doaj.art-0f1f44ab434441b7b91c6e11217543db |
| institution | Directory Open Access Journal |
| issn | 1471-2164 |
| language | English |
| last_indexed | 2024-12-13T00:46:11Z |
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| series | BMC Genomics |
| spelling | doaj.art-0f1f44ab434441b7b91c6e11217543db2022-12-22T00:05:01ZengBMCBMC 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 |
| 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 |
| title | 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_short | 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 |
| 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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