7
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Improving Taxonomic Delimitation of Fungal Species in the Age of Genomics and Phenomics

      review-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Species concepts have long provided a source of debate among biologists. These lively debates have been important for reaching consensus on how to communicate across scientific disciplines and for advancing innovative strategies to study evolution, population biology, ecology, natural history, and disease epidemiology. Species concepts are also important for evaluating variability and diversity among communities, understanding biogeographical distributions, and identifying causal agents of disease across animal and plant hosts. While there have been many attempts to address the concept of species in the fungi, there are several concepts that have made taxonomic delimitation especially challenging. In this review we discuss these major challenges and describe methodological approaches that show promise for resolving ambiguity in fungal taxonomy by improving discrimination of genetic and functional traits. We highlight the relevance of eco-evolutionary theory used in conjunction with integrative taxonomy approaches to improve the understanding of interactions between environment, ecology, and evolution that give rise to distinct species boundaries. Beyond recent advances in genomic and phenomic methods, bioinformatics tools and modeling approaches enable researchers to test hypothesis and expand our knowledge of fungal biodiversity. Looking to the future, the pairing of integrative taxonomy approaches with multi-locus genomic sequencing and phenomic techniques, such as transcriptomics and proteomics, holds great potential to resolve many unknowns in fungal taxonomic classification.

          Graphical Abstract

          Enhanced resolution of spices boundaries.

          Related collections

          Most cited references89

          • Record: found
          • Abstract: found
          • Article: not found

          Basic local alignment search tool.

          A new approach to rapid sequence comparison, basic local alignment search tool (BLAST), directly approximates alignments that optimize a measure of local similarity, the maximal segment pair (MSP) score. Recent mathematical results on the stochastic properties of MSP scores allow an analysis of the performance of this method as well as the statistical significance of alignments it generates. The basic algorithm is simple and robust; it can be implemented in a number of ways and applied in a variety of contexts including straightforward DNA and protein sequence database searches, motif searches, gene identification searches, and in the analysis of multiple regions of similarity in long DNA sequences. In addition to its flexibility and tractability to mathematical analysis, BLAST is an order of magnitude faster than existing sequence comparison tools of comparable sensitivity.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            DADA2: High resolution sample inference from Illumina amplicon data

            We present DADA2, a software package that models and corrects Illumina-sequenced amplicon errors. DADA2 infers sample sequences exactly, without coarse-graining into OTUs, and resolves differences of as little as one nucleotide. In several mock communities DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy.

              The Ribosomal Database Project (RDP) Classifier, a naïve Bayesian classifier, can rapidly and accurately classify bacterial 16S rRNA sequences into the new higher-order taxonomy proposed in Bergey's Taxonomic Outline of the Prokaryotes (2nd ed., release 5.0, Springer-Verlag, New York, NY, 2004). It provides taxonomic assignments from domain to genus, with confidence estimates for each assignment. The majority of classifications (98%) were of high estimated confidence (> or = 95%) and high accuracy (98%). In addition to being tested with the corpus of 5,014 type strain sequences from Bergey's outline, the RDP Classifier was tested with a corpus of 23,095 rRNA sequences as assigned by the NCBI into their alternative higher-order taxonomy. The results from leave-one-out testing on both corpora show that the overall accuracies at all levels of confidence for near-full-length and 400-base segments were 89% or above down to the genus level, and the majority of the classification errors appear to be due to anomalies in the current taxonomies. For shorter rRNA segments, such as those that might be generated by pyrosequencing, the error rate varied greatly over the length of the 16S rRNA gene, with segments around the V2 and V4 variable regions giving the lowest error rates. The RDP Classifier is suitable both for the analysis of single rRNA sequences and for the analysis of libraries of thousands of sequences. Another related tool, RDP Library Compare, was developed to facilitate microbial-community comparison based on 16S rRNA gene sequence libraries. It combines the RDP Classifier with a statistical test to flag taxa differentially represented between samples. The RDP Classifier and RDP Library Compare are available online at http://rdp.cme.msu.edu/.
                Bookmark

                Author and article information

                Contributors
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                17 February 2022
                2022
                : 13
                : 847067
                Affiliations
                [1] 1Complex Biosystems Interdisciplinary Life Sciences, University of Nebraska-Lincoln , Lincoln, NE, United States
                [2] 2Department of Agronomy and Horticulture, University of Nebraska-Lincoln , Lincoln, NE, United States
                [3] 3Department of Plant Pathology, University of Nebraska-Lincoln , Lincoln, NE, United States
                [4] 4Department of Chemical and Biomolecular Engineering, University of Nebraska-Lincoln , Lincoln, NE, United States
                [5] 5School of Biological Sciences, University of Nebraska-Lincoln , Lincoln, NE, United States
                [6] 6Center for Plant Science Innovation, University of Nebraska-Lincoln , Lincoln, NE, United States
                Author notes

                Edited by: Sabine Dagmar Zimmermann, Délégation Languedoc Roussillon, Center for the National Scientific Research (CNRS), France

                Reviewed by: Lucia Muggia, University of Trieste, Italy; Nicolas Corradi, University of Ottawa, Canada

                *Correspondence: Ashley Stengel, ashley.stengel@ 123456huskers.unl.edu
                Joshua R. Herr, jherr@ 123456unl.edu

                ORCID: Ashley Stengel, orcid.org/0000-0002-6731-8203; Kimberly M. Stanke, orcid.org/0000-0001-6917-7363; Amanda C. Quattrone, orcid.org/0000-0003-3918-0419; Joshua R. Herr, orcid.org/0000-0003-3425-292X

                This article was submitted to Evolutionary and Genomic Microbiology, a section of the journal Frontiers in Microbiology

                Article
                10.3389/fmicb.2022.847067
                8892103
                35250961
                ce4d2612-72bf-449c-b831-2583b251d712
                Copyright © 2022 Stengel, Stanke, Quattrone and Herr.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 01 January 2022
                : 28 January 2022
                Page count
                Figures: 3, Tables: 0, Equations: 0, References: 89, Pages: 10, Words: 7142
                Funding
                Funded by: National Science Foundation, doi 10.13039/100000001;
                Categories
                Microbiology
                Mini Review

                Microbiology & Virology
                fungal diversity,eco-evolutionary theory,integrative taxonomy,species delimitation,omics,bioinformatics

                Comments

                Comment on this article