ESTclean: a cleaning tool for next-gen transcriptome shotgun sequencing

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Abstract

Background

With the advent of next-generation sequencing (NGS) technologies, full cDNA shotgun sequencing has become a major approach in the study of transcriptomes, and several different protocols in 454 sequencing have been invented. As each protocol uses its own short DNA tags or adapters attached to the ends of cDNA fragments for labeling or sequencing, different contaminants may lead to mis-assembly and inaccurate sequence products.

Results

We have designed and implemented a new program for raw sequence cleaning in a graphical user interface and a batch script. The cleaning process consists of several modules including barcode trimming, sequencing adapter trimming, amplification primer trimming, poly-A tail trimming, vector screening and low quality region trimming. These modules can be combined based on various sequencing applications.

Conclusions

ESTclean is a software package not only for cleaning cDNA sequences, but also for helping to develop sequencing protocols by providing summary tables and figures for sequencing quality control in a graphical user interface. It outperforms in cleaning read sequences from complicated sequencing protocols which use barcodes and multiple amplification primers.

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Most cited references 4

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Sequencing and de novo analysis of a coral larval transcriptome using 454 GSFlx

Eli Meyer, Galina Aglyamova, Shi Wang … (2009)

Background New methods are needed for genomic-scale analysis of emerging model organisms that exemplify important biological questions but lack fully sequenced genomes. For example, there is an urgent need to understand the potential for corals to adapt to climate change, but few molecular resources are available for studying these processes in reef-building corals. To facilitate genomics studies in corals and other non-model systems, we describe methods for transcriptome sequencing using 454, as well as strategies for assembling a useful catalog of genes from the output. We have applied these methods to sequence the transcriptome of planulae larvae from the coral Acropora millepora. Results More than 600,000 reads produced in a single 454 sequencing run were assembled into ~40,000 contigs with five-fold average sequencing coverage. Based on sequence similarity with known proteins, these analyses identified ~11,000 different genes expressed in a range of conditions including thermal stress and settlement induction. Assembled sequences were annotated with gene names, conserved domains, and Gene Ontology terms. Targeted searches using these annotations identified the majority of genes associated with essential metabolic pathways and conserved signaling pathways, as well as novel candidate genes for stress-related processes. Comparisons with the genome of the anemone Nematostella vectensis revealed ~8,500 pairs of orthologs and ~100 candidate coral-specific genes. More than 30,000 SNPs were detected in the coral sequences, and a subset of these validated by re-sequencing. Conclusion The methods described here for deep sequencing of the transcriptome should be widely applicable to generate catalogs of genes and genetic markers in emerging model organisms. Our data provide the most comprehensive sequence resource currently available for reef-building corals, and include an extensive collection of potential genetic markers for association and population connectivity studies. The characterization of the larval transcriptome for this widely-studied coral will enable research into the biological processes underlying stress responses in corals and evolutionary adaptation to global climate change.

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DNA sequence quality trimming and vector removal.

H-H Chou, M. Holmes (2001)

Most sequence comparison methods assume that the data being compared are trustworthy, but this is not the case with raw DNA sequences obtained from automatic sequencing machines. Nevertheless, sequence comparisons need to be done on them in order to remove vector splice sites and contaminants. This step is necessary before other genomic data processing stages can be carried out, such as fragment assembly or EST clustering. A specialized tool is therefore needed to solve this apparent dilemma. We have designed and implemented a program that specifically addresses the problem. This program, called LUCY, has been in use since 1998 at The Institute for Genomic Research (TIGR). During this period, many rounds of experience-driven modifications were made to LUCY to improve its accuracy and its ability to deal with extremely difficult input cases. We believe we have finally obtained a useful program which strikes a delicate balance among the many issues involved in the raw sequence cleaning problem, and we wish to share it with the research community. LUCY is available directly from TIGR (http://www.tigr.org/softlab). Academic users can download LUCY after accepting a free academic use license. Business users may need to pay a license fee to use LUCY for commercial purposes. Questions regarding the quality assessment module of LUCY should be directed to Michael Holmes (mholmes@tigr.org). Questions regarding other aspects of LUCY should be directed to Hui-Hsien Chou (hhchou@iastate.edu).

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SeqTrim: a high-throughput pipeline for pre-processing any type of sequence read

Juan Falgueras, Antonio J Lara, Noe Fernandez-Pozo … (2010)

Background High-throughput automated sequencing has enabled an exponential growth rate of sequencing data. This requires increasing sequence quality and reliability in order to avoid database contamination with artefactual sequences. The arrival of pyrosequencing enhances this problem and necessitates customisable pre-processing algorithms. Results SeqTrim has been implemented both as a Web and as a standalone command line application. Already-published and newly-designed algorithms have been included to identify sequence inserts, to remove low quality, vector, adaptor, low complexity and contaminant sequences, and to detect chimeric reads. The availability of several input and output formats allows its inclusion in sequence processing workflows. Due to its specific algorithms, SeqTrim outperforms other pre-processors implemented as Web services or standalone applications. It performs equally well with sequences from EST libraries, SSH libraries, genomic DNA libraries and pyrosequencing reads and does not lead to over-trimming. Conclusions SeqTrim is an efficient pipeline designed for pre-processing of any type of sequence read, including next-generation sequencing. It is easily configurable and provides a friendly interface that allows users to know what happened with sequences at every pre-processing stage, and to verify pre-processing of an individual sequence if desired. The recommended pipeline reveals more information about each sequence than previously described pre-processors and can discard more sequencing or experimental artefacts.

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Author and article information

Journal

Journal ID (nlm-ta): BMC Bioinformatics

Journal ID (iso-abbrev): BMC Bioinformatics

Title: BMC Bioinformatics

Publisher: BioMed Central

ISSN (Electronic): 1471-2105

Publication date Collection: 2012

Publication date (Electronic): 26 September 2012

Volume: 13

Page: 247

Affiliations

[1 ]Cancer Center, Department of Biostatistics, Georgia Health Sciences University, Augusta, GA 30912, USA

[2 ]The Center for Genomics and Bioinformatics, Indiana University, Bloomington, IN 47401, USA

Article

Publisher ID: 1471-2105-13-247

DOI: 10.1186/1471-2105-13-247

PMC ID: 3630001

PubMed ID: 23009593

SO-VID: fe40ad2f-08d7-4949-92ab-609ae25617da

License:

This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

ESTclean: a cleaning tool for next-gen transcriptome shotgun sequencing

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Abstract

Background

Results

Conclusions

Related collections

Computational epistasis

Most cited references 4

Sequencing and de novo analysis of a coral larval transcriptome using 454 GSFlx

DNA sequence quality trimming and vector removal.

SeqTrim: a high-throughput pipeline for pre-processing any type of sequence read

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