MyDGR is a web server providing integrated prediction and visualization of Diversity-Generating Retroelements (DGR) systems in query nucleotide sequences. It is built upon an enhanced version of DGRscan, a tool we previously developed for identification of DGR systems. DGR systems are remarkable genetic elements that use error-prone reverse transcriptases to generate vast sequence variants in specific target genes, which have been shown to benefit their hosts (bacteria, archaea or phages). As the first web server for annotation of DGR systems, myDGR is freely available on the web at http://omics.informatics.indiana.edu/myDGR with all major browsers supported. MyDGR accepts query nucleotide sequences in FASTA format, and outputs all the important features of a predicted DGR system, including a reverse transcriptase, a template repeat and one (or more) variable repeats and their alignment featuring A-to-N (N can be C, T or G) substitutions, and VR-containing target gene(s). In addition to providing the results as text files for download, myDGR generates a visual summary of the results for users to explore the predicted DGR systems. Users can also directly access pre-calculated, putative DGR systems identified in currently available reference bacterial genomes and a few other collections of sequences (including human microbiomes).

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Reverse transcriptases (RTs) are found in different systems including group II introns, Diversity Generating Retroelements (DGRs), retrons, CRISPR-Cas systems, and Abortive Infection (Abi) systems in prokaryotes. Different classes of RTs can play different roles, such as template switching and mobility in group II introns, spacer acquisition in CRISPR-Cas systems, mutagenic retrohoming in DGRs, programmed cell suicide in Abi systems, and recently discovered phage defense in retrons. While some classes of RTs have been studied extensively, others remain to be characterized. There is a lack of computational tools for identifying and characterizing various classes of RTs. In this study, we built a tool (called myRT) for identification and classification of prokaryotic RTs. In addition, our tool provides information about the genomic neighborhood of each RT, providing potential functional clues. We applied our tool to predict RTs in all complete and draft bacterial genomes, and created a collection that can be used for exploration of putative RTs and their associated protein domains. Application of myRT to metagenomes showed that gut metagenomes encode proportionally more RTs related to DGRs, outnumbering retron-related RTs, as compared to the collection of reference genomes. MyRT is both available as a standalone software (https://github.com/mgtools/myRT) and also through a website (https://omics.informatics.indiana.edu/myRT/).

Microbes play important roles in almost every aspect of life, including human health and diseases. Facilitated by the rapid development of sequencing technologies, metagenomics research has accelerated the accumulation of genomic sequences of microbial species that had been inaccessible before. Analysis of the metagenomic sequencing data can reveal not only the species but also the functional composition of microbial communities. Here, we report a pipeline for functional annotation of metagenomic datasets. The pipeline is built from several programs that we have developed for metagenomic sequence analysis including a protein-coding gene predictor for short reads (or contigs) and a fast similarity search tool. Given a metagenomic dataset, the pipeline reports putative protein-coding genes (or gene fragments) and functional annotations of the genes in Gene Ontology (GO) terms and Enzyme Commission (EC) numbers, and potential metabolic pathways that are likely encoded by the metagenome. Fun4Me is available for download at https://sourceforge.net/projects/fun4me .