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      ITScan: a web-based analysis tool for Internal Transcribed Spacer (ITS) sequences

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          Abstract

          Background

          Studies on fungal diversity and ecology aim to identify fungi and to investigate their interactions with each other and with the environment. DNA sequence-based tools are essential for these studies because they can speed up the identification process and access greater fungal diversity than traditional methods. The nucleotide sequence encoding for the internal transcribed spacer (ITS) of the nuclear ribosomal RNA has recently been proposed as a standard marker for molecular identification of fungi and evaluation of fungal diversity. However, the analysis of large sets of ITS sequences involves many programs and steps, which makes this task intensive and laborious.

          Findings

          We developed the web-based pipeline ITScan, which automates the analysis of fungal ITS sequences generated either by Sanger or Next Generation Sequencing (NGS) platforms. Validation was performed using datasets containing ca. 2,000 to 40,000 sequences each.

          Conclusions

          ITScan is an online and user-friendly automated pipeline for fungal diversity analysis and identification based on ITS sequences. It speeds up a process which would otherwise be repetitive and time-consuming for users. The ITScan tool and documentation are available at http://evol.rc.unesp.br:8083/itscan.

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          Most cited references 20

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          Accurate determination of microbial diversity from 454 pyrosequencing data.

          We present an algorithm, PyroNoise, that clusters the flowgrams of 454 pyrosequencing reads using a distance measure that models sequencing noise. This infers the true sequences in a collection of amplicons. We pyrosequenced a known mixture of microbial 16S rDNA sequences extracted from a lake and found that without noise reduction the number of operational taxonomic units is overestimated but using PyroNoise it can be accurately calculated.
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            ITS as an environmental DNA barcode for fungi: an in silico approach reveals potential PCR biases

            Background During the last 15 years the internal transcribed spacer (ITS) of nuclear DNA has been used as a target for analyzing fungal diversity in environmental samples, and has recently been selected as the standard marker for fungal DNA barcoding. In this study we explored the potential amplification biases that various commonly utilized ITS primers might introduce during amplification of different parts of the ITS region in samples containing mixed templates ('environmental barcoding'). We performed in silico PCR analyses with commonly used primer combinations using various ITS datasets obtained from public databases as templates. Results Some of the ITS primers, such as ITS1-F, were hampered with a high proportion of mismatches relative to the target sequences, and most of them appeared to introduce taxonomic biases during PCR. Some primers, e.g. ITS1-F, ITS1 and ITS5, were biased towards amplification of basidiomycetes, whereas others, e.g. ITS2, ITS3 and ITS4, were biased towards ascomycetes. The assumed basidiomycete-specific primer ITS4-B only amplified a minor proportion of basidiomycete ITS sequences, even under relaxed PCR conditions. Due to systematic length differences in the ITS2 region as well as the entire ITS, we found that ascomycetes will more easily amplify than basidiomycetes using these regions as targets. This bias can be avoided by using primers amplifying ITS1 only, but this would imply preferential amplification of 'non-dikarya' fungi. Conclusions We conclude that ITS primers have to be selected carefully, especially when used for high-throughput sequencing of environmental samples. We suggest that different primer combinations or different parts of the ITS region should be analyzed in parallel, or that alternative ITS primers should be searched for.
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              SeqTrim: a high-throughput pipeline for pre-processing any type of sequence read

              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

                Contributors
                milenef@gmail.com
                aceiro@gmail.com
                well309@gmail.com
                mbacci@rc.unesp.br
                Journal
                BMC Res Notes
                BMC Res Notes
                BMC Research Notes
                BioMed Central (London )
                1756-0500
                27 November 2014
                27 November 2014
                2014
                : 7
                : 1
                Affiliations
                [ ]Centro de Estudos de Insetos Sociais, Instituto de Biociências, UNESP - Univ Estadual Paulista, Rio Claro, SP 13506-900 Brazil
                [ ]Departamento de Bioquímica e Microbiologia, Instituto de Biociências, UNESP - Univ Estadual Paulista, Rio Claro, SP 13506-900 Brazil
                [ ]Departamento de Ciência da Computação, Universidade Federal de São Carlos, São Carlos, SP 13565-905 Brazil
                Article
                3370
                10.1186/1756-0500-7-857
                4258023
                25430816
                © Ferro et al.; licensee BioMed Central Ltd. 2014

                This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                Categories
                Technical Note
                Custom metadata
                © The Author(s) 2014

                Medicine

                fungal biodiversity, mycology, pipeline, web service

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