Your browser doesn't support javascript.
loading
GROND: a quality-checked and publicly available database of full-length 16S-ITS-23S rRNA operon sequences.
Walsh, Calum J; Srinivas, Meghana; Stinear, Timothy P; van Sinderen, Douwe; Cotter, Paul D; Kenny, John G.
Affiliation
  • Walsh CJ; Doherty Applied Microbial Genomics, Department of Microbiology & Immunology, The University of Melbourne at the Peter Doherty Institute for Infection & Immunity, 792 Elizabeth Street, Melbourne VIC 3000, Australia.
  • Srinivas M; Teagasc Food Research Centre, Moorepark, Cork, Ireland.
  • Stinear TP; APC Microbiome Ireland & School of Microbiology, University College Cork, Cork, Ireland.
  • van Sinderen D; Doherty Applied Microbial Genomics, Department of Microbiology & Immunology, The University of Melbourne at the Peter Doherty Institute for Infection & Immunity, 792 Elizabeth Street, Melbourne VIC 3000, Australia.
  • Cotter PD; APC Microbiome Ireland & School of Microbiology, University College Cork, Cork, Ireland.
  • Kenny JG; Teagasc Food Research Centre, Moorepark, Cork, Ireland.
Microb Genom ; 10(6)2024 Jun.
Article in En | MEDLINE | ID: mdl-38847800
ABSTRACT
Sequence comparison of 16S rRNA PCR amplicons is an established approach to taxonomically identify bacterial isolates and profile complex microbial communities. One potential application of recent advances in long-read sequencing technologies is to sequence entire rRNA operons and capture significantly more phylogenetic information compared to sequencing of the 16S rRNA (or regions thereof) alone, with the potential to increase the proportion of amplicons that can be reliably classified to lower taxonomic ranks. Here we describe GROND (Genome-derived Ribosomal Operon Database), a publicly available database of quality-checked 16S-ITS-23S rRNA operons, accompanied by multiple taxonomic classifications. GROND will aid researchers in analysis of their data and act as a standardised database to allow comparison of results between studies.
Subject(s)
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Phylogeny / Bacteria / RNA, Ribosomal, 16S Language: En Journal: Microb Genom Year: 2024 Document type: Article Affiliation country: Australia

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Phylogeny / Bacteria / RNA, Ribosomal, 16S Language: En Journal: Microb Genom Year: 2024 Document type: Article Affiliation country: Australia