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An estimate of the total number of true human miRNAs.

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TLDR
The experimentally validated miRNAs will contribute to revising targetomes hypothesized by utilizing falsely annotated miRNA candidates, 1115 of which are currently annotated in miRBase V22.
Abstract
While the number of human miRNA candidates continuously increases, only a few of them are completely characterized and experimentally validated. Toward determining the total number of true miRNAs, we employed a combined in silico high- and experimental low-throughput validation strategy. We collected 28 866 human small RNA sequencing data sets containing 363.7 billion sequencing reads and excluded falsely annotated and low quality data. Our high-throughput analysis identified 65% of 24 127 mature miRNA candidates as likely false-positives. Using northern blotting, we experimentally validated miRBase entries and novel miRNA candidates. By exogenous overexpression of 108 precursors that encode 205 mature miRNAs, we confirmed 68.5% of the miRBase entries with the confirmation rate going up to 94.4% for the high-confidence entries and 18.3% of the novel miRNA candidates. Analyzing endogenous miRNAs, we verified the expression of 8 miRNAs in 12 different human cell lines. In total, we extrapolated 2300 true human mature miRNAs, 1115 of which are currently annotated in miRBase V22. The experimentally validated miRNAs will contribute to revising targetomes hypothesized by utilizing falsely annotated miRNAs.

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dbDEMC 3.0: Functional Exploration of Differentially Expressed miRNAs in Cancers of Human and Model Organisms

TL;DR: The database of differentially expressed miRNAs (DEMs) in human cancers (dbDEMC) 3.0 as mentioned in this paper contains 3268 unique DEMs in 40 different cancer types.
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MicroRNA-214 in Health and Disease

TL;DR: A comprehensive review of the miR-214 literature can be found in this article, where relevant roles in health and disease, areas of disagreement, and the future direction of the field are discussed.
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Role of Non-Coding RNAs in the Progression of Liver Cancer: Evidence from Experimental Models.

TL;DR: Current findings on the roles noncoding RNAs play in the progression of liver cancer and the various animal models used in current research to elucidate those data are summarized.
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From Molecular Mechanisms to Therapeutics: Understanding MicroRNA-21 in Cancer

J. Rhim, +3 more
- 01 Sep 2022 - 
TL;DR: The roles of miR-21 as a key modulator in various cancers and its potential as a therapeutic target are outlined.
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Insights from circulating microRNAs in cardiovascular entities in turner syndrome patients.

TL;DR: The identified circulating miRNAs signature for TS patients with manifestations associated with cardiovascular diseases provide new insights into the molecular mechanism of TS that may guide the development of novel diagnostic approaches.
References
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Journal ArticleDOI

MicroRNAs: Genomics, Biogenesis, Mechanism, and Function

TL;DR: Although they escaped notice until relatively recently, miRNAs comprise one of the more abundant classes of gene regulatory molecules in multicellular organisms and likely influence the output of many protein-coding genes.
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MicroRNAs: Target Recognition and Regulatory Functions

TL;DR: The current understanding of miRNA target recognition in animals is outlined and the widespread impact of miRNAs on both the expression and evolution of protein-coding genes is discussed.
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The functions of animal microRNAs

TL;DR: Evidence is mounting that animal miRNAs are more numerous, and their regulatory impact more pervasive, than was previously suspected.
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Characteristics of a Human Cell Line Transformed by DNA from Human Adenovirus Type 5

TL;DR: Human embryonic kidney cells have been transformed by exposing cells to sheared fragments of adenovirus type 5 DNA, and the transformed cells exhibited many of the characteristics of transformation including the elaboration of a virus-specific tumour antigen.
Journal ArticleDOI

miRBase: annotating high confidence microRNAs using deep sequencing data.

TL;DR: An update of the miRBase database is described, including the collation and use of deep sequencing data sets to assign levels of confidence to miR base entries, and a high confidence subset of miR Base entries are provided, based on the pattern of mapped reads.
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