| 1. |
- Nilsson, R. Henrik, 1976, et al.
(författare)
-
Top 50 most wanted fungi
- 2016
-
Ingår i: MycoKeys. - : Pensoft Publishers. - 1314-4057 .- 1314-4049. ; 12, s. 29-40
-
Tidskriftsartikel (refereegranskat)abstract
- Environmental sequencing regularly recovers fungi that cannot be classified to any meaningful taxonomic level beyond “Fungi”. There are several examples where evidence of such lineages has been sitting in public sequence databases for up to ten years before receiving scientific attention and formal recognition. In order to highlight these unidentified lineages for taxonomic scrutiny, a search function is presented that produces updated lists of approximately genus-level clusters of fungal ITS sequences that remain unidentified at the phylum, class, and order levels, respectively. The search function (https://unite.ut.ee/top50.php) is implemented in the UNITE database for molecular identification of fungi, such that the underlying sequences and fungal lineages are open to third-party annotation. We invite researchers to examine these enigmatic fungal lineages in the hope that their taxonomic resolution will not have to wait another ten years or more.
|
|
| 2. |
- Nilsson, R. Henrik, 1976, et al.
(författare)
-
Improving ITS sequence data for identification of plant pathogenic fungi
- 2014
-
Ingår i: Fungal Diversity. - : Springer Science and Business Media LLC. - 1560-2745 .- 1878-9129. ; 67:1, s. 11-19
-
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.
|
|
| 3. |
- Bengtsson-Palme, Johan, 1985, et al.
(författare)
-
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
-
Ingår i: Methods in Ecology and Evolution. - 2041-210X. ; 4:10, s. 914-919
-
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.
|
|
| 4. |
- Eshghi Sahraei, Shadi, et al.
(författare)
-
Whole genome analyses based on single, field collected spores of the arbuscular mycorrhizal fungus Funneliformis geosporum
- 2022
-
Ingår i: Mycorrhiza. - : Springer. - 0940-6360 .- 1432-1890. ; 32:5-6, s. 361-371
-
Tidskriftsartikel (refereegranskat)abstract
- Arbuscular mycorrhizal (AM) fungi are ubiquitous mutualistic symbionts of most terrestrial plants and many complete their lifecycles underground. Whole genome analysis of AM fungi has long been restricted to species and strains that can be maintained under controlled conditions that facilitate collection of biological samples. There is some evidence suggesting that AM fungi can adapt to culture resulting in phenotypic and possibly also genotypic changes in the fungi. In this study, we used field isolated spores of AM fungi and identified them as Funneliformis geosporum based on morphology and phylogenetic analyses. We separately assembled the genomes of two representative spores using DNA sequences of 19 and 22 individually amplified nuclei. The genomes were compared with previously published data from other members of Glomeraceae including two strains of F. mosseae. No significant differences were observed among the species in terms of gene content, while the single nucleotide polymorphism density was higher in the strains of F. geosporum than in the strains of F. mosseae. In this study, we demonstrate that it is possible to sequence and assemble genomes from AM fungal spores sampled in the field, which opens up the possibility to include uncultured AM fungi in phylogenomic and comparative genomic analysis and to study genomic variation in natural populations of these important plant symbionts.
|
|
