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A software pipeline for processing and identification of fungal ITS sequences

Artikel i vetenskaplig tidskrift
Författare R. Henrik Nilsson
Gunilla Bok
Martin Ryberg
Erik Kristiansson
Nils Hallenberg
Publicerad i Source Code for Biology and Medicine
Volym 4
Nummer/häfte 1
ISSN 1751-0473
Publiceringsår 2009
Publicerad vid Institutionen för växt- och miljövetenskaper
Zoologiska institutionen
Språk en
Länkar www.scfbm.org/content/4/1/1
Ämneskategorier Programvaruteknik, Molekylärbiologi, Mikrobiologi, Morfologi, Bioinformatik och systembiologi, Terrestrisk ekologi, Biologisk systematik, Medicinsk mikrobiologi

Sammanfattning

Background Fungi from environmental samples are typically identified to species level through DNA sequencing of the nuclear ribosomal internal transcribed spacer (ITS) region for use in BLAST-based similarity searches in the International Nucleotide Sequence Databases. These searches are time-consuming and regularly require a significant amount of manual intervention and complementary analyses. We here present software - in the form of an identification pipeline for large sets of fungal ITS sequences - developed to automate the BLAST process and several additional analysis steps. The performance of the pipeline was evaluated on a dataset of 350 ITS sequences from fungi growing as epiphytes on building material. Results The pipeline was written in Perl and uses a local installation of NCBI-BLAST for the similarity searches of the query sequences. The variable subregion ITS2 of the ITS region is extracted from the sequences and used for additional searches of higher sensitivity. Multiple alignments of each query sequence and its closest matches are computed, and query sequences sharing at least 50 % of their best matches are clustered to facilitate the evaluation of hypothetically conspecific groups. The pipeline proved to speed up the processing, as well as enhance the resolution, of the evaluation dataset considerably, and the fungi were found to belong chiefly to the Ascomycota, with Penicillium and Aspergillus as the two most common genera. The ITS2 was found to indicate a different taxonomic affiliation than did the complete ITS region for 10 % of the query sequences, though this figure is likely to vary with the taxonomic scope of the query sequences. Conclusions The present software readily assigns large sets of fungal query sequences to their respective best matches in the international sequence databases and places them in a larger biological context. The output is highly structured to be easy to process, although it still needs to be inspected and possibly corrected for the impact of the incomplete and sometimes erroneously annotated fungal entries in these databases. The open source pipeline is available for UNIX-type platforms, and updated releases of the target database are made available biweekly. The pipeline is easily modified to operate on other molecular regions and organism groups.

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