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miRNA 靶标鉴定:重新审视易接近性和种子锚定。

MicroRNA Target Identification: Revisiting Accessibility and Seed Anchoring.

机构信息

Laboratoire de Biométrie et Biologie Evolutive, Université de Lyon, CNRS, UMR5558, 69622 Villeurbanne, France.

INRIA Lyon Centre, 69100 Villeurbanne, France.

出版信息

Genes (Basel). 2023 Mar 7;14(3):664. doi: 10.3390/genes14030664.

DOI:10.3390/genes14030664
PMID:36980936
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10048102/
Abstract

By pairing to messenger RNAs (mRNAs for short), microRNAs (miRNAs) regulate gene expression in animals and plants. Accurately identifying which mRNAs interact with a given miRNA and the precise location of the interaction sites is crucial to reaching a more complete view of the regulatory network of an organism. Only a few experimental approaches, however, allow the identification of both within a single experiment. Computational predictions of miRNA-mRNA interactions thus remain generally the first step used, despite their drawback of a high rate of false-positive predictions. The major computational approaches available rely on a diversity of features, among which anchoring the miRNA seed and measuring mRNA accessibility are the key ones, with the first being universally used, while the use of the second remains controversial. Revisiting the importance of each is the aim of this paper, which uses Cross-Linking, Ligation, And Sequencing of Hybrids (CLASH) datasets to achieve this goal. Contrary to what might be expected, the results are more ambiguous regarding the use of the seed match as a feature, while accessibility appears to be a feature worth considering, indicating that, at least under some conditions, it may favour anchoring by miRNAs.

摘要

通过与信使 RNA(简称 mRNA)配对,microRNAs(miRNAs)在动植物中调节基因表达。准确识别与特定 miRNA 相互作用的 mRNAs 以及相互作用位点的精确位置,对于更全面地了解生物体的调控网络至关重要。然而,只有少数实验方法可以在单个实验中同时识别这两者。因此,尽管计算预测 miRNA-mRNA 相互作用存在高假阳性预测率的缺点,但仍然是普遍采用的第一步。现有的主要计算方法依赖于多种特征,其中锚定 miRNA 种子和测量 mRNA 可及性是关键特征,前者被普遍使用,而后者的使用仍存在争议。本文旨在重新审视每个特征的重要性,为此使用交联、连接和杂交测序 (CLASH) 数据集来实现这一目标。出乎意料的是,关于将种子匹配用作特征的使用结果更加模棱两可,而可及性似乎是一个值得考虑的特征,表明至少在某些条件下,它可能有利于 miRNA 的锚定。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0bc4/10048102/1cd6e790e637/genes-14-00664-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0bc4/10048102/099ee60ec817/genes-14-00664-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0bc4/10048102/272768579f89/genes-14-00664-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0bc4/10048102/e2a4e2a64642/genes-14-00664-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0bc4/10048102/164053b2e480/genes-14-00664-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0bc4/10048102/1cd6e790e637/genes-14-00664-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0bc4/10048102/099ee60ec817/genes-14-00664-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0bc4/10048102/272768579f89/genes-14-00664-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0bc4/10048102/e2a4e2a64642/genes-14-00664-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0bc4/10048102/164053b2e480/genes-14-00664-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0bc4/10048102/1cd6e790e637/genes-14-00664-g005.jpg

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本文引用的文献

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2
Too Many False Targets for MicroRNAs: Challenges and Pitfalls in Prediction of miRNA Targets and Their Gene Ontology in Model and Non-model Organisms.太多的 miRNA 假靶标:在模型和非模型生物中预测 miRNA 靶标及其基因本体论所面临的挑战和陷阱。
Bioessays. 2019 Apr;41(4):e1800169. doi: 10.1002/bies.201800169.
3
Cross-kingdom RNA trafficking and environmental RNAi-nature's blueprint for modern crop protection strategies.
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Med Oncol. 2024 Dec 17;42(1):30. doi: 10.1007/s12032-024-02579-z.
4
Identification and characterization of host miRNAs that target the mouse mammary tumour virus (MMTV) genome.靶向小鼠乳腺肿瘤病毒(MMTV)基因组的宿主微小RNA(miRNA)的鉴定与特征分析。
Open Biol. 2024 Dec;14(12):240203. doi: 10.1098/rsob.240203. Epub 2024 Dec 11.
跨界 RNA 转移与环境 RNAi——现代作物保护策略的自然蓝图。
Curr Opin Microbiol. 2018 Dec;46:58-64. doi: 10.1016/j.mib.2018.02.003. Epub 2018 Mar 14.
4
IntaRNA 2.0: enhanced and customizable prediction of RNA-RNA interactions.IntaRNA 2.0:增强和可定制的 RNA-RNA 相互作用预测。
Nucleic Acids Res. 2017 Jul 3;45(W1):W435-W439. doi: 10.1093/nar/gkx279.
5
The Host Shapes the Gut Microbiota via Fecal MicroRNA.宿主通过粪便微小RNA塑造肠道微生物群。
Cell Host Microbe. 2016 Jan 13;19(1):32-43. doi: 10.1016/j.chom.2015.12.005.
6
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7
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Elife. 2015 Aug 12;4:e05005. doi: 10.7554/eLife.05005.
8
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Nucleic Acids Res. 2015 Jul 1;43(W1):W39-49. doi: 10.1093/nar/gkv416. Epub 2015 May 7.
9
The origin, function, and diagnostic potential of RNA within extracellular vesicles present in human biological fluids.细胞外囊泡中 RNA 的来源、功能和诊断潜力存在于人体生物体液中。
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10
Mapping the human miRNA interactome by CLASH reveals frequent noncanonical binding.通过 CLASH 绘制人类 miRNA 相互作用组揭示了频繁的非经典结合。
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