Summary
Understanding the evolution of organismic complexity and the genomic basis of gene-regulation is one of the main challenges in the postgenomic era. While thousands of new genomes are available today, no accurate methods exist to reliably mine those for microRNAs, an important class of post-transcriptional regulators. Currently, their prediction and annotation depend on the availability of transcriptomics data sets and hands-on expert knowledge leading to the large discrepancy between novel genomes made available and the availability of high-quality microRNA complements. Using the more than 16,000 microRNA entries from the manually curated microRNA gene database MirGeneDB, we generated and trained covariance models for each conserved microRNA family. These models are available in MirMachine, our new pipeline for automated annotation of conserved microRNAs. We show that MirMachine can be used to accurately and precisely predict conserved microRNA complements from genome assemblies, correctly identifying the number of paralogues, and by establishing the novel microRNA score, the completeness of assemblies. Built and trained on representative metazoan microRNA complements, we used MirMachine on a wide range of animal species, including those with very large genomes or additional genome duplications and extinct species such as mammoths, where deep small RNA sequencing data will be hard to produce. With accurate predictions of conserved microRNAs, the MirMachine workflow closes a long-persisting gap in the microRNA field that will not only facilitate automated genome annotation pipelines and can serve as a solid foundation for manual curation efforts, but deeper studies on the evolution of genome regulation, even in extinct organisms. MirMachine is freely available (https://github.com/sinanugur/MirMachine) and also implemented as a web application (www.mirmachine.org).
Highlights
An annotation pipeline using trained covariance models of microRNA families
Enables massive parallel annotation of microRNA complements of genomes
MirMachine creates meaningful annotations for very large and extinct genomes
microRNA score to assess genome assembly completeness
Competing Interest Statement
The authors have declared no competing interest.
