Showing papers by "Conrad L. Schoch published in 2021"
Free University of Berlin1, Purdue University2, National Institutes of Health3, University of Illinois at Urbana–Champaign4, National Agriculture and Food Research Organization5, National Taiwan University6, University of Perugia7, Utrecht University8, Wageningen University and Research Centre9, Nanjing Agricultural University10, Vienna University of Technology11, Pennsylvania State University12, University of Mauritius13, Landcare Research14, Royal Botanic Gardens15, Federal University of Pernambuco16, University of Gothenburg17, University of Tartu18, Goethe University Frankfurt19, Leibniz Association20, Rutgers University21
TL;DR: In this paper, the authors propose a solution for the nomenclature of taxa known only from sequences to facilitate consistent reporting and communication in the literature and public sequence repositories.
Abstract: The identification and proper naming of microfungi, in particular plant, animal and human pathogens, remains challenging. Molecular identification is becoming the default approach for many fungal groups, and environmental metabarcoding is contributing an increasing amount of sequence data documenting fungal diversity on a global scale. This includes lineages represented only by sequence data. At present, these taxa cannot be formally described under the current nomenclature rules. By considering approaches used in bacterial taxonomy, we propose solutions for the nomenclature of taxa known only from sequences to facilitate consistent reporting and communication in the literature and public sequence repositories.
70 citations
Purdue University1, University of Illinois at Urbana–Champaign2, National Agriculture and Food Research Organization3, Utrecht University4, Chinese Academy of Sciences5, Natural History Museum6, Royal Botanic Gardens7, Mae Fah Luang University8, Free University of Berlin9, Federal University of Pernambuco10, Agriculture and Agri-Food Canada11, Oregon State University12, Goethe University Frankfurt13, Leibniz Association14, Rutgers University15, National Institutes of Health16
TL;DR: The International Commission on the Taxonomy of Fungi (ICTF) produced an overview of requirements and best practices for describing a new fungal species as mentioned in this paper, and the ICNafp has changed from its former name (the International Code of Botanical Nomenclature) and introduced new formal requirements for valid publication of species scientific names.
Abstract: It is now a decade since The International Commission on the Taxonomy of Fungi (ICTF) produced an overview of requirements and best practices for describing a new fungal species. In the meantime the International Code of Nomenclature for algae, fungi, and plants (ICNafp) has changed from its former name (the International Code of Botanical Nomenclature) and introduced new formal requirements for valid publication of species scientific names, including the separation of provisions specific to Fungi and organisms treated as fungi in a new Chapter F. Equally transformative have been changes in the data collection, data dissemination, and analytical tools available to mycologists. This paper provides an updated and expanded discussion of current publication requirements along with best practices for the description of new fungal species and publication of new names and for improving accessibility of their associated metadata that have developed over the last 10 years. Additionally, we provide: (1) model papers for different fungal groups and circumstances; (2) a checklist to simplify meeting (i) the requirements of the ICNafp to ensure the effective, valid and legitimate publication of names of new taxa, and (ii) minimally accepted standards for description; and, (3) templates for preparing standardized species descriptions.
59 citations
TL;DR: Ribovore as mentioned in this paper is a software package for sequence analysis of rRNA sequences, which is used to generate high-quality datasets of rRNAs from different taxonomic groups.
Abstract: Background The DNA sequences encoding ribosomal RNA genes (rRNAs) are commonly used as markers to identify species, including in metagenomics samples that may combine many organismal communities. The 16S small subunit ribosomal RNA (SSU rRNA) gene is typically used to identify bacterial and archaeal species. The nuclear 18S SSU rRNA gene, and 28S large subunit (LSU) rRNA gene have been used as DNA barcodes and for phylogenetic studies in different eukaryote taxonomic groups. Because of their popularity, the National Center for Biotechnology Information (NCBI) receives a disproportionate number of rRNA sequence submissions and BLAST queries. These sequences vary in quality, length, origin (nuclear, mitochondria, plastid), and organism source and can represent any region of the ribosomal cistron. Results To improve the timely verification of quality, origin and loci boundaries, we developed Ribovore, a software package for sequence analysis of rRNA sequences. The ribotyper and ribosensor programs are used to validate incoming sequences of bacterial and archaeal SSU rRNA. The ribodbmaker program is used to create high-quality datasets of rRNAs from different taxonomic groups. Key algorithmic steps include comparing candidate sequences against rRNA sequence profile hidden Markov models (HMMs) and covariance models of rRNA sequence and secondary-structure conservation, as well as other tests. Nine freely available blastn rRNA databases created and maintained with Ribovore are used for checking incoming GenBank submissions and used by the blastn browser interface at NCBI. Since 2018, Ribovore has been used to analyze more than 50 million prokaryotic SSU rRNA sequences submitted to GenBank, and to select at least 10,435 fungal rRNA RefSeq records from type material of 8350 taxa. Conclusion Ribovore combines single-sequence and profile-based methods to improve GenBank processing and analysis of rRNA sequences. It is a standalone, portable, and extensible software package for the alignment, classification and validation of rRNA sequences. Researchers planning on submitting SSU rRNA sequences to GenBank are encouraged to download and use Ribovore to analyze their sequences prior to submission to determine which sequences are likely to be automatically accepted into GenBank.
2 citations
TL;DR: Ribovore as mentioned in this paper is a software package for sequence analysis of rRNA sequences that combines single-sequence and profile-based methods to improve GenBank processing and analysis of RRNA sequences.
Abstract: Background: The DNA sequences encoding ribosomal RNA genes (rRNAs) are commonly used as markers to identify species, including in metagenomics samples that may combine many organismal communities. The 16S small subunit ribosomal RNA (SSU rRNA) gene is typically used to identify bacterial and archaeal species. The nuclear 18S SSU rRNA gene, and 28S large subunit (LSU) rRNA gene have been used as DNA barcodes and for phylogenetic studies in different eukaryote taxonomic groups. Because of their popularity, the National Center for Biotechnology Information (NCBI) receives a disproportionate number of rRNA sequence submissions and BLAST queries. These sequences vary in quality, length, origin (nuclear, mitochondria, plastid), and organism source and can represent any region of the ribosomal cistron. Results: To improve the timely verification of quality, origin and loci boundaries, we developed Ribovore, a software package for sequence analysis of rRNA sequences. The ribotyper and ribosensor programs are used to validate incoming sequences of bacterial and archaeal SSU rRNA. The ribodbmaker program is used to create high-quality datasets of rRNAs from different taxonomic groups. Key algorithmic steps include comparing candidate sequences against rRNA sequence profile hidden Markov models (HMMs) and covariance models of rRNA sequence and secondary-structure conservation, as well as other tests. At least nine freely available blastn rRNA databases created and maintained with Ribovore are used either for checking incoming GenBank submissions or by the blastn browser interface at NCBI or both. Since 2018, Ribovore has been used to analyze more than 50 million prokaryotic SSU rRNA sequences submitted to GenBank, and to select at least 10,435 fungal rRNA RefSeq records from type material of 8,350 taxa. Conclusion: Ribovore combines single-sequence and profile-based methods to improve GenBank processing and analysis of rRNA sequences. It is a standalone, portable, and extensible software package for the alignment, classification and validation of rRNA sequences. Researchers planning on submitting SSU rRNA sequences to GenBank are encouraged to download and use Ribovore to analyze their sequences prior to submission to determine which sequences are likely to be automatically accepted into GenBank.