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- 2019
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Tidskriftsartikel (refereegranskat)
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| 2. |
- Bengtsson-Palme, Johan, 1985, et al.
(författare)
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Improved software detection and extraction of ITS1 and ITS2 from ribosomal ITS sequences of fungi and other eukaryotes for analysis of environmental sequencing data
- 2013
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Ingår i: Methods in Ecology and Evolution. - 2041-210X. ; 4:10, s. 914-919
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 3. |
- Bengtsson-Palme, Johan, 1985, et al.
(författare)
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Megraft: A software package to graft ribosomal small subunit (16S/18S) fragments onto full-length sequences for accurate species richness and sequencing depth analysis in pyrosequencing-length metagenomes
- 2012
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Ingår i: Research in Microbiology. - : Elsevier BV. - 0923-2508. ; 163:6-7, s. 407-412
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Tidskriftsartikel (refereegranskat)abstract
- Metagenomic libraries represent subsamples of the total DNA found at a study site and offer unprecedented opportunities to study ecological and functional aspects of microbial communities. To examine the depth of a community sequencing effort, rarefaction analysis of the ribosomal small subunit (SSU/16S/18S) gene in the metagenome is usually performed. The fragmentary, non-overlapping nature of SSU sequences in metagenomic libraries poses a problem for this analysis, however. We introduce a software package – Megraft – that grafts SSU fragments onto full-length SSU sequences, accounting for observed and unobserved variability, for accurate assessment of species richness and sequencing depth in metagenomics endeavors.
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| 4. |
- Nilsson, R. Henrik, 1976, et al.
(författare)
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A comprehensive, automatically updated fungal ITS sequence dataset for reference-based chimera control in environmental sequencing efforts
- 2015
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Ingår i: Microbes and Environments. - 1342-6311 .- 1347-4405. ; 30:2, s. 145-150
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Tidskriftsartikel (refereegranskat)abstract
- The nuclear ribosomal internal transcribed spacer (ITS) region is the most commonly chosen genetic marker for the molecular identification of fungi in environmental sequencing and molecular ecology studies. Several analytical issues complicate such efforts, one of which is the formation of chimeric—artificially joined—DNA sequences during PCR amplification or sequence assembly. Several software tools are currently available for chimera detection, but rely to various degrees on the presence of a chimera-free reference dataset for optimal performance. However, no such dataset is available for use with the fungal ITS region. This study introduces a comprehensive, automatically updated reference dataset for fungal ITS sequences based on the UNITE database for the molecular identification of fungi. This dataset supports chimera detection throughout the fungal kingdom and for full-length ITS sequences as well as partial (ITS1 or ITS2 only) datasets. The performance of the dataset on a large set of artificial chimeras was above 99.5%, and we subsequently used the dataset to remove nearly 1,000 compromised fungal ITS sequences from public circulation. The dataset is available at http://unite.ut.ee/repository.php and is subject to web-based third-party curation.
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| 5. |
- Nilsson, R. Henrik, 1976, et al.
(författare)
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Five simple guidelines for establishing basic authenticity and reliability of newly generated fungal ITS sequences
- 2012
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Ingår i: MycoKeys. - : Pensoft Publishers. - 1314-4057 .- 1314-4049. ; 4, s. 37-63
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Tidskriftsartikel (refereegranskat)abstract
- Molecular data form an important research tool in most branches of mycology. A non-trivial proportion of the public fungal DNA sequences are, however, compromised in terms of quality and reliability, contributing noise and bias to sequence-borne inferences such as phylogenetic analysis, diversity assessment, and barcoding. In this paper we discuss various aspects and pitfalls of sequence quality assessment. Based on our observations, we provide a set of guidelines to assist in manual quality management of newly generated, near-full-length (Sanger-derived) fungal ITS sequences and to some extent also sequences of shorter read lengths, other genes or markers, and groups of organisms. The guidelines are intentionally non-technical and do not require substantial bioinformatics skills or significant computational power. Despite their simple nature, we feel they would have caught the vast majority of the severely compromised ITS sequences in the public corpus. Our guidelines are nevertheless not infallible, and common sense and intuition remain important elements in the pursuit of compromised sequence data. The guidelines focus on basic sequence authenticity and reliability of the newly generated sequences, and the user may want to consider additional resources and steps to accomplish the best possible quality control. A discussion on the technical resources for further sequence quality management is therefore provided in the supplementary material.
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| 6. |
- Nilsson, R. Henrik, 1976, et al.
(författare)
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Improving ITS sequence data for identification of plant pathogenic fungi
- 2014
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Ingår i: Fungal Diversity. - : Springer Science and Business Media LLC. - 1560-2745 .- 1878-9129. ; 67:1, s. 11-19
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Tidskriftsartikel (refereegranskat)abstract
- Plant pathogenic fungi are a large and diverse assemblage of eukaryotes with substantial impacts on natural ecosystems and human endeavours. These taxa often have complex and poorly understood life cycles, lack observable, discriminatory morphological characters, and may not be amenable to in vitro culturing. As a result, species identification is frequently difficult. Molecular (DNA sequence) data have emerged as crucial information for the taxonomic identification of plant pathogenic fungi, with the nuclear ribosomal internal transcribed spacer (ITS) region being the most popular marker. However, international nucleotide sequence databases are accumulating numerous sequences of compromised or low-resolution taxonomic annotations and substandard technical quality, making their use in the molecular identification of plant pathogenic fungi problematic. Here we report on a concerted effort to identify high-quality reference sequences for various plant pathogenic fungi and to re-annotate incorrectly or insufficiently annotated public ITS sequences from these fungal lineages. A third objective was to enrich the sequences with geographical and ecological metadata. The results – a total of 31,954 changes – are incorporated in and made available through the UNITE database for molecular identification of fungi (http://unite.ut.ee), including standalone FASTA files of sequence data for local BLAST searches, use in the next-generation sequencing analysis platforms QIIME and mothur, and related applications. The present initiative is just a beginning to cover the wide spectrum of plant pathogenic fungi, and we invite all researchers with pertinent expertise to join the annotation effort.
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| 7. |
- Abarenkov, Kessy, et al.
(författare)
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Annotating public fungal ITS sequences from the built environment according to the MIxS-Built Environment standard – a report from a May 23-24, 2016 workshop (Gothenburg, Sweden)
- 2016
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Ingår i: MycoKeys. - : Pensoft Publishers. - 1314-4057 .- 1314-4049. ; 16, s. 1-15
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Tidskriftsartikel (refereegranskat)abstract
- Recent molecular studies have identified substantial fungal diversity in indoor environments. Fungi and fungal particles have been linked to a range of potentially unwanted effects in the built environment, including asthma, decay of building materials, and food spoilage. The study of the built mycobiome is hampered by a number of constraints, one of which is the poor state of the metadata annotation of fungal DNA sequences from the built environment in public databases. In order to enable precise interrogation of such data – for example, “retrieve all fungal sequences recovered from bathrooms” – a workshop was organized at the University of Gothenburg (May 23-24, 2016) to annotate public fungal barcode (ITS) sequences according to the MIxS-Built Environment annotation standard (http://gensc.org/mixs/). The 36 participants assembled a total of 45,488 data points from the published literature, including the addition of 8,430 instances of countries of collection from a total of 83 countries, 5,801 instances of building types, and 3,876 instances of surface-air contaminants. The results were implemented in the UNITE database for molecular identification of fungi (http://unite.ut.ee) and were shared with other online resources. Data obtained from human/animal pathogenic fungi will furthermore be verified on culture based metadata for subsequent inclusion in the ISHAM-ITS database (http://its.mycologylab.org).
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| 8. |
- Bengtsson-Palme, Johan, 1985, et al.
(författare)
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Metaxa: a software tool for automated detection and discrimination among ribosomal small subunit (12S/16S/18S) sequences of archaea, bacteria, eukaryotes, mitochondria, and chloroplasts in metagenomes and environmental sequencing datasets
- 2011
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Ingår i: Antonie van Leeuwenhoek: international journal of general and molecular microbiology. - : Springer Science and Business Media LLC. - 0003-6072 .- 1572-9699. ; 100:3, s. 471-475
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Tidskriftsartikel (refereegranskat)abstract
- The ribosomal small subunit (SSU) rRNA gene has emerged as an important genetic marker for taxonomic identification in environmental sequencing datasets. In addition to being present in the nucleus of eukaryotes and the core genome of prokaryotes, the gene is also found in the mitochondria of eukaryotes and in the chloroplasts of photosynthetic eukaryotes. These three sets of genes are conceptually paralogous and should in most situations not be aligned and analyzed jointly. To identify the origin of SSU sequences in complex sequence datasets has hitherto been a time-consuming and largely manual undertaking. However, the present study introduces Metaxa (http://microbiology.se/software/metaxa/), an automated software tool to extract full-length and partial SSU sequences from larger sequence datasets and assign them to an archaeal, bacterial, nuclear eukaryote, mitochondrial, or chloroplast origin. Using data from reference databases and from full-length organelle and organism genomes, we show that Metaxa detects and scores SSU sequences for origin with very low proportions of false positives and negatives. We believe that this tool will be useful in microbial and evolutionary ecology as well as in metagenomics.
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| 9. |
- Bengtsson-Palme, Johan, 1985, et al.
(författare)
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Metaxa, overview
- 2013
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Ingår i: Encyclopedia of Metagenomics. - Berlin : Springer.
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Bokkapitel (refereegranskat)abstract
- Metaxa is a software tool for extracting full-length and partial ribosomal small subunit (SSU; 16S/18S/12S) sequences from metagenomic datasets, and for classifying the extracted sequences to taxonomic domains and organelle of origin. Metaxa is freely available from http://microbiology.se/software/metaxa
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| 10. |
- Bengtsson-Palme, Johan, 1985, et al.
(författare)
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Metaxa2 Database Builder: enabling taxonomic identification from metagenomic or metabarcoding data using any genetic marker
- 2018
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Ingår i: Bioinformatics (Oxford, England). - : Oxford University Press (OUP). - 1367-4811 .- 1367-4803. ; 34:23, s. 4027-4033
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Tidskriftsartikel (refereegranskat)abstract
- Correct taxonomic identification of DNA sequences is central to studies of biodiversity using both shotgun metagenomic and metabarcoding approaches. However, no genetic marker gives sufficient performance across all the biological kingdoms, hampering studies of taxonomic diversity in many groups of organisms. This has led to the adoption of a range of genetic markers for DNA metabarcoding. While many taxonomic classification software tools can be re-trained on these genetic markers, they are often designed with assumptions that impair their utility on genes other than the SSU and LSU rRNA. Here, we present an update to Metaxa2 that enables the use of any genetic marker for taxonomic classification of metagenome and amplicon sequence data.We evaluated the Metaxa2 Database Builder on eleven commonly used barcoding regions and found that while there are wide differences in performance between different genetic markers, our software performs satisfactorily provided that the input taxonomy and sequence data are of high quality.Freely available on the web as part of the Metaxa2 package at http://microbiology.se/software/metaxa2/.Supplementary data are available at Bioinformatics online.
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