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 10 914-919

Subject 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

More information

Latest update

5/26/2023