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

Louis T Dang,Gregory A Quaife-Ryan ,Hieu T Nim,Jerico Revote,Vincent Tano,Fernando Rossello ,Mark J Drvodelic,Enzo R Porrello,Marie A Bogoyevitch,James E Hudson,Alex Tokolyi,Helen E Cumming ,Julian Stolper ,Markus Tondl,Benedict Paten,David A Jans,Man Ho H Chiu,Michael P Eichenlaub,Jeannette C Hallab,Florence Besse,Mirana Ramialison

doi:10.1186/s12864-018-4630-0

Abstract

BackgroundA 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.ResultsWe 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.ConclusionsTrawlerWeb 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.

Highlights

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)
TrawlerWeb runs the fastest amongst popular web-based motif discovery tools We aimed to compare the performance of TrawlerWeb with the popular web-based de novo motif discovery tools RSAT peak-motifs [20, 36] and MEME-chromatin immunoprecipitation (ChIP) [18]
The same FASTA input file was used across the three different programs with the same background file used for TrawlerWeb and RSAT peak-motifs, default background was used for MEME-ChIP as it does not allow for custom background FASTA input

Summary

Introduction

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). Genome-wide binding assays such as chromatin immunoprecipitation (ChIP) [9], DNA adenine methyltransferase identification (DamID) [10, 11], and transposase-accessible chromatin (ATAC) [12] coupled with next-generation sequencing (NGS) technologies are popular methods to uncover regulatory regions that will shed light on our understanding of gene regulation [13, 14]. These methods have been coopted amongst scientists working on model organisms ranging from plants to humans [15, 16]. This input-matched background allows TrawlerWeb to account for sequence biases present in certain genomic regions (for example promoter regions are known to be enriched in CpG islands [29]).

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Results

Conclusion