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Accurate microRNA annotation of animal genomes using trained covariance models of curated microRNA complements in MirMachine

Authors :
Sinan Uğur Umu
Vanessa M. Paynter
Håvard Trondsen
Tilo Buschmann
Trine B. Rounge
Kevin J. Peterson
Bastian Fromm
Publication Year :
2022
Publisher :
Cold Spring Harbor Laboratory, 2022.

Abstract

SummaryThe annotation of microRNAs, an important class of post-transcriptional regulators, depends on the availability of transcriptomics data and expert knowledge. This led to a large gap between novel genomes made available and high-quality microRNA complements. Using >16,000 microRNAs from the manually curated microRNA gene database MirGeneDB, we generated trained covariance models for all conserved microRNA families. These models are available in MirMachine, our new tool for the annotation of conserved microRNA complements from genomes only. We successfully applied MirMachine to a wide range of animal species, including those with very large genomes, additional genome duplications and extinct species, where smallRNA sequencing will be hard to achieve. We further describe a microRNA score of expected microRNAs that can be used to assess the completeness of genome assemblies. MirMachine closes a long-persisting gap in the microRNA field facilitating automated genome annotation pipelines and deeper studies on the evolution of genome regulation, even in extinct organisms.HighlightsAn annotation pipeline using trained covariance models of microRNA familiesEnables massive parallel annotation of microRNA complements of genomesMirMachine creates meaningful annotations for very large and extinct genomesmicroRNA score to assess genome assembly completenessGraphical abstract

Details

Database :
OpenAIRE
Accession number :
edsair.doi...........4c604d1ab2b61da870c872582ef0f708
Full Text :
https://doi.org/10.1101/2022.11.23.517654