Improved software detection and extraction of ITS1 and ITS2 from ribosomal ITS sequences of fungi and other eukaryotes for analysis of environmental sequencing data
Journal article, 2013
The nuclear ribosomal internal transcribed spacer (ITS) region is the primary choice for molecular identification of fungi. Its two highly variable spacers (ITS1 and ITS2) are usually species specific, whereas the intercalary 5.8S gene is highly conserved. For sequence clustering and blast searches, it is often advantageous to rely on either one of the variable spacers but not the conserved 5.8S gene. To identify and extract ITS1 and ITS2 from large taxonomic and environmental data sets is, however, often difficult, and many ITS sequences are incorrectly delimited in the public sequence databases.
We introduce ITSx, a Perl-based software tool to extract ITS1, 5.8S and ITS2 – as well as full-length ITS sequences – from both Sanger and high-throughput sequencing data sets. ITSx uses hidden Markov models computed from large alignments of a total of 20 groups of eukaryotes, including fungi, metazoans and plants, and the sequence extraction is based on the predicted positions of the ribosomal genes in the sequences.
ITSx has a very high proportion of true-positive extractions and a low proportion of false-positive extractions. Additionally, process parallelization permits expedient analyses of very large data sets, such as a one million sequence amplicon pyrosequencing data set. ITSx is rich in features and written to be easily incorporated into automated sequence analysis pipelines.
ITSx paves the way for more sensitive blast searches and sequence clustering operations for the ITS region in eukaryotes. The software also permits elimination of non-ITS sequences from any data set. This is particularly useful for amplicon-based next-generation sequencing data sets, where insidious non-target sequences are often found among the target sequences. Such non-target sequences are difficult to find by other means and would contribute noise to diversity estimates if left in the data set.
molecular ecology
next-generation sequencing
Perl
Fungi
ribosomal DNA
Author
Johan Bengtsson-Palme
University of Gothenburg
Martin Ryberg
Uppsala University
Martin Hartmann
Eidgenossische Forschungsanstalt fur Wald, Schnee Und Landschaft Eth-Bereichs
Forschungsanstalt Agroscope Reckenholz-Tanikon
Sara Branco
University of California
Zheng Wang
Yale University
Anna Godhe
University of Gothenburg
Pierre De Wit
University of Gothenburg
Marisol Sánchez-García
University of Tennessee
Ingo Ebersberger
Goethe University Frankfurt
Filipe de Sousa
University of Gothenburg
Anthony S. Amend
University of Hawaii
Ari Jumpponen
Kansas State University
Martin Unterseher
University of Greifswald
Erik Kristiansson
Chalmers, Mathematical Sciences, Mathematical Statistics
University of Gothenburg
Kessy Abarenkov
University of Tartu
Yann Bertrand
University of Gothenburg
Kemal Sanli
University of Gothenburg
Martin Eriksson
Chalmers, Shipping and Marine Technology
Unni Vik
University of Oslo
Vilmar Veldre
R. Henrik Nilsson
University of Gothenburg
Methods in Ecology and Evolution
2041210x (eISSN)
Vol. 4 10 914-919Subject Categories
Botany
Biological Systematics
Soil Science
Environmental Sciences related to Agriculture and Land-use
Ecology
Microbiology
Bioinformatics (Computational Biology)
Microbiology in the medical area
Bioinformatics and Systems Biology
Zoology
Computer Science
DOI
10.1111/2041-210X.12073