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使用MirMachine中经过训练的特定微小RNA互补序列的协方差模型对动物基因组进行准确的微小RNA注释。

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

作者信息

Umu Sinan Uğur, Paynter Vanessa M, Trondsen Håvard, Buschmann Tilo, Rounge Trine B, Peterson Kevin J, Fromm Bastian

机构信息

Department of Pathology, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.

The Arctic University Museum of Norway, UiT - The Arctic University of Norway, Tromsø, Norway.

出版信息

Cell Genom. 2023 Jun 23;3(8):100348. doi: 10.1016/j.xgen.2023.100348. eCollection 2023 Aug 9.

Abstract

The annotation of microRNAs depends on the availability of transcriptomics data and expert knowledge. This has led to a gap between the availability of novel genomes 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 our tool MirMachine, which annotates conserved microRNAs within genomes. We successfully applied MirMachine to a range of animal species, including those with large genomes and genome duplications and extinct species, where small RNA sequencing is 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 by facilitating automated genome annotation pipelines and deeper studies into the evolution of genome regulation, even in extinct organisms.

摘要

微小RNA的注释依赖于转录组学数据的可用性和专业知识。这导致了新基因组的可用性与高质量微小RNA互补序列之间存在差距。我们使用来自人工整理的微小RNA基因数据库MirGeneDB的16000多个微小RNA,为所有保守的微小RNA家族生成了经过训练的协方差模型。这些模型可在我们的工具MirMachine中获取,该工具可注释基因组中的保守微小RNA。我们成功地将MirMachine应用于一系列动物物种,包括那些基因组庞大、经历过基因组加倍的物种以及已灭绝的物种,在这些物种中进行小RNA测序很难实现。我们进一步描述了一种预期微小RNA的评分,可用于评估基因组组装的完整性。MirMachine通过促进自动化基因组注释流程以及对基因组调控进化进行更深入的研究,填补了微小RNA领域长期存在的空白,甚至在已灭绝的生物体中也是如此。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2a1a/10435380/74184e427fbc/fx1.jpg

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