Trends in Free-access Genomic Data Accelerate Advances in Cyanobacteria Taxonomy

© 2021 Phycological Society of America.

Bibliographische Detailangaben
Veröffentlicht in:Journal of phycology. - 1966. - 57(2021), 5 vom: 02. Okt., Seite 1392-1402
1. Verfasser: Dextro, Rafael B (VerfasserIn)
Weitere Verfasser: Delbaje, Endrews, Cotta, Simone R, Zehr, Jonathan P, Fiore, Marli F
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2021
Zugriff auf das übergeordnete Werk:Journal of phycology
Schlagworte:Journal Article Research Support, Non-U.S. Gov't Review Melainabacteria bioinformatics database high-throughput sequencing metagenome-assembled genomes
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520 |a Free access databases of DNA sequences containing microbial genetic information have changed the way scientists look at the microbial world. Currently, the NCBI database includes about 516 distinct search results for Cyanobacterial genomes distributed in a taxonomy based on a polyphasic approach. While their classification and taxonomic relationships are widely used as is, recent proposals to alter their grouping include further exploring the relationship between Cyanobacteria and Melainabacteria. Nowadays, most cyanobacteria still are named under the Botanical Code; however, there is a proposal made by the Genome Taxonomy Database (GTDB) to harmonize cyanobacteria nomenclature with the other bacteria, an initiative to standardize microbial taxonomy based on genome phylogeny, in order to contribute to an overall better phylogenetic resolution of microbiota. Furthermore, the assembly level of the genomes and their geographical origin demonstrates some trends of cyanobacteria genomics on the scientific community, such as low availability of complete genomes and underexplored sampling locations. By describing how available cyanobacterial genomes from free-access databases fit within different taxonomic classifications, this mini-review provides a holistic view of the current knowledge of cyanobacteria and indicates some steps towards improving our efforts to create a more cohesive and inclusive classifying system, which can be greatly improved by using large-scale sequencing and metagenomic techniques 
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700 1 |a Cotta, Simone R  |e verfasserin  |4 aut 
700 1 |a Zehr, Jonathan P  |e verfasserin  |4 aut 
700 1 |a Fiore, Marli F  |e verfasserin  |4 aut 
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