MicroRNA expression in JAG1/Notch-activated periodontal ligament stem cells

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Abstract

Objectives

The study explored the expression profile of miRNAs in Notch-activated periodontal ligament stem cells (PDLSCs) and examined their potential cellular targets.

Methods

PDLSCs were cultured and treated with indirect immobilized Jagged1. The miRNA expression profile was examined using NanoString analysis. Bioinformatic analysis was performed together with enrichment, and miRNA expression was evaluated and validated using a quantitative polymerase chain reaction (qPCR).

Results

A total of 26 miRNAs were differentially expressed in Jagged1 treated PDLSCs compared with the controls. Pathway analysis revealed that altered miRNAs were significantly associated with the transforming growth factor β (TGF-β) signaling pathway. Target prediction analysis demonstrated that 11,170 genes as predictable targets of these altered miRNAs. Enrichment of predicted target genes revealed that they were related to ErbB, Ras and MAPK signaling pathways and small GTPase transduction.

Conclusions

The research concludes that several miRNAs are differentially expressed in jagged-1 treated PDLSCs. In translational terms the differential functionality of these miRNAs offer promise for the development of targeted regenerative materials that are necessary for managing lost tissue replacement in periodontal diseases.

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Most cited references 46

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Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

Kenneth Livak, Thomas D. Schmittgen (2001)

The two most commonly used methods to analyze data from real-time, quantitative PCR experiments are absolute quantification and relative quantification. Absolute quantification determines the input copy number, usually by relating the PCR signal to a standard curve. Relative quantification relates the PCR signal of the target transcript in a treatment group to that of another sample such as an untreated control. The 2(-Delta Delta C(T)) method is a convenient way to analyze the relative changes in gene expression from real-time quantitative PCR experiments. The purpose of this report is to present the derivation, assumptions, and applications of the 2(-Delta Delta C(T)) method. In addition, we present the derivation and applications of two variations of the 2(-Delta Delta C(T)) method that may be useful in the analysis of real-time, quantitative PCR data. Copyright 2001 Elsevier Science (USA).

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Predicting effective microRNA target sites in mammalian mRNAs

Vikram Agarwal, George Bell, Jin-Wu Nam … (2015)

MicroRNA targets are often recognized through pairing between the miRNA seed region and complementary sites within target mRNAs, but not all of these canonical sites are equally effective, and both computational and in vivo UV-crosslinking approaches suggest that many mRNAs are targeted through non-canonical interactions. Here, we show that recently reported non-canonical sites do not mediate repression despite binding the miRNA, which indicates that the vast majority of functional sites are canonical. Accordingly, we developed an improved quantitative model of canonical targeting, using a compendium of experimental datasets that we pre-processed to minimize confounding biases. This model, which considers site type and another 14 features to predict the most effectively targeted mRNAs, performed significantly better than existing models and was as informative as the best high-throughput in vivo crosslinking approaches. It drives the latest version of TargetScan (v7.0; targetscan.org), thereby providing a valuable resource for placing miRNAs into gene-regulatory networks. DOI: http://dx.doi.org/10.7554/eLife.05005.001

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WebGestalt 2019: gene set analysis toolkit with revamped UIs and APIs

Yuxing Liao, Jing WANG, Eric J Jaehnig … (2019)

Abstract WebGestalt is a popular tool for the interpretation of gene lists derived from large scale -omics studies. In the 2019 update, WebGestalt supports 12 organisms, 342 gene identifiers and 155 175 functional categories, as well as user-uploaded functional databases. To address the growing and unique need for phosphoproteomics data interpretation, we have implemented phosphosite set analysis to identify important kinases from phosphoproteomics data. We have completely redesigned result visualizations and user interfaces to improve user-friendliness and to provide multiple types of interactive and publication-ready figures. To facilitate comprehension of the enrichment results, we have implemented two methods to reduce redundancy between enriched gene sets. We introduced a web API for other applications to get data programmatically from the WebGestalt server or pass data to WebGestalt for analysis. We also wrapped the core computation into an R package called WebGestaltR for users to perform analysis locally or in third party workflows. WebGestalt can be freely accessed at http://www.webgestalt.org.

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Author and article information

Contributors

Supreda Suphanantachat Srithanyarat:

ORCID: http://orcid.org/0000-0001-6272-8169

supredasu@gmail.com , supreda.s@chula.ac.th

Journal

Journal ID (nlm-ta): BDJ Open

Journal ID (iso-abbrev): BDJ Open

Title: BDJ Open

Publisher: Nature Publishing Group UK (London )

ISSN (Electronic): 2056-807X

Publication date (Electronic): 5 June 2024

Publication date PMC-release: 5 June 2024

Publication date Collection: 2024

Volume: 10

Electronic Location Identifier: 45

Affiliations

[1 ]Center of Excellence for Dental Stem Cell Biology, Faculty of Dentistry, Chulalongkorn University, ( https://ror.org/028wp3y58) Bangkok, Thailand

[2 ]Department of Anatomy, Faculty of Dentistry, Chulalongkorn University, ( https://ror.org/028wp3y58) Bangkok, Thailand

[3 ]Department of Oral and Maxillofacial Surgery, Faculty of Dentistry, Chulalongkorn University, ( https://ror.org/028wp3y58) Bangkok, Thailand

[4 ]Faculty of Dentistry, University of Hong Kong, ( https://ror.org/02zhqgq86) Pok Fu Lam, 34, Hospital Road, Hong Kong

[5 ]Dean Office and Office of Research Affairs, Faculty of Dentistry, Chulalongkorn University, ( https://ror.org/028wp3y58) Bangkok, Thailand

[6 ]Department of Periodontology, Faculty of Dentistry, Chulalongkorn University, ( https://ror.org/028wp3y58) Bangkok, Thailand

[7 ]Center of Excellence for Periodontology and Dental Implants, Department of Periodontology, Faculty of Dentistry, Chulalongkorn University, ( https://ror.org/028wp3y58) Bangkok, Thailand

Author information

Supreda Suphanantachat Srithanyarat http://orcid.org/0000-0001-6272-8169

Thanaphum Osathanon http://orcid.org/0000-0003-1649-6357

Article

Publisher ID: 232

DOI: 10.1038/s41405-024-00232-5

PMC ID: 11153650

PubMed ID: 38839751

SO-VID: ee6cc42c-fb7f-436f-8814-f16d0212528d

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

History

Date received : 12 March 2024

Date revision received : 22 April 2024

Date accepted : 6 May 2024

Funding

Funded by: Program Management Unit for Human Resources & Institutional Development, Research, and Innovation (B16F640118)

Funded by: FundRef https://doi.org/10.13039/501100002873, Chulalongkorn University (CU);

Funded by: Program Management Unit for Human Resources & Institutional Development, Research, and Innovation (B16F640118)

Custom metadata

Keywords: periodontics,resorption

Data availability:

Keywords: periodontics, resorption

MicroRNA expression in JAG1/Notch-activated periodontal ligament stem cells

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Abstract

Objectives

Methods

Results

Conclusions

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Stress signalling in stem cells

Most cited references 46

Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

Predicting effective microRNA target sites in mammalian mRNAs

WebGestalt 2019: gene set analysis toolkit with revamped UIs and APIs

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