myRT

myRT identifies and classifies Reverse Transcriptases (RTs) in bacterial genomes and metagenomes to characterize RT classes and their genomic neighborhoods.


Key Features:

  • RT detection: Identifies Reverse Transcriptases (RTs) within bacterial genomes and metagenomes.
  • RT classification: Classifies RTs into prokaryotic RT classes including group II introns, Diversity Generating Retroelements (DGRs), retrons, CRISPR-Cas–associated RTs, and Abortive Infection (Abi)–associated RTs.
  • Genomic neighborhood analysis: Analyzes genomic neighborhood of RTs to provide functional clues about RT roles and mechanisms.
  • Large-scale genome screening: Applied to all complete and draft bacterial genomes to generate a curated collection of putative RTs.
  • Metagenome profiling: Applied to gut metagenomes to compare RT class abundances, reporting a higher proportion of DGR-related RTs than retron-related RTs in gut samples.

Scientific Applications:

  • RT repertoire characterization: Characterize the distribution and diversity of Reverse Transcriptases (RTs) across bacterial genomes and metagenomes.
  • Functional inference of RT-associated systems: Infer functions of RTs in group II introns, DGRs, retrons, CRISPR-Cas systems, and Abi systems using classification and neighborhood context.
  • Comparative metagenomics: Compare prevalence of RT classes between reference genomes and complex microbial communities such as gut microbiomes.
  • Microbial genetics and evolution: Provide annotated RT datasets to support studies of microbial genetics and evolutionary dynamics.

Methodology:

Applied to all complete and draft bacterial genomes to produce a curated collection of putative RTs and applied to gut metagenomes to assess RT class abundance.

Topics

Details

Tool Type:
command-line tool, web application
Programming Languages:
C, Perl
Added:
3/19/2021
Last Updated:
4/11/2021

Operations

Publications

Sharifi F, Ye Y. Identification and Classification of Reverse Transcriptases in Bacterial Genomes and Metagenomes. Unknown Journal. 2021. doi:10.1101/2021.01.26.428298.

Links