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A comparative analysis of high-throughput platforms for validation of a circulating microRNA signature in diabetic retinopathy
MicroRNAs are now increasingly recognized as biomarkers of disease progression. Several quantitative real-time PCR (qPCR) platforms have been developed to determine the relative levels of microRNAs in biological fluids. We systematically compared the detection of cellular and circulating microRNA us...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4649912/ https://www.ncbi.nlm.nih.gov/pubmed/26035063 http://dx.doi.org/10.1038/srep10375 |
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author | Farr, Ryan J. Januszewski, Andrzej S. Joglekar, Mugdha V. Liang, Helena McAulley, Annie K. Hewitt, Alex W. Thomas, Helen E. Loudovaris, Tom Kay, Thomas W. H. Jenkins, Alicia Hardikar, Anandwardhan A. |
author_facet | Farr, Ryan J. Januszewski, Andrzej S. Joglekar, Mugdha V. Liang, Helena McAulley, Annie K. Hewitt, Alex W. Thomas, Helen E. Loudovaris, Tom Kay, Thomas W. H. Jenkins, Alicia Hardikar, Anandwardhan A. |
author_sort | Farr, Ryan J. |
collection | PubMed |
description | MicroRNAs are now increasingly recognized as biomarkers of disease progression. Several quantitative real-time PCR (qPCR) platforms have been developed to determine the relative levels of microRNAs in biological fluids. We systematically compared the detection of cellular and circulating microRNA using a standard 96-well platform, a high-content microfluidics platform and two ultra-high content platforms. We used extensive analytical tools to compute inter- and intra-run variability and concordance measured using fidelity scoring, coefficient of variation and cluster analysis. We carried out unprejudiced next generation sequencing to identify a microRNA signature for Diabetic Retinopathy (DR) and systematically assessed the validation of this signature on clinical samples using each of the above four qPCR platforms. The results indicate that sensitivity to measure low copy number microRNAs is inversely related to qPCR reaction volume and that the choice of platform for microRNA biomarker validation should be made based on the abundance of miRNAs of interest. |
format | Online Article Text |
id | pubmed-4649912 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-46499122015-11-24 A comparative analysis of high-throughput platforms for validation of a circulating microRNA signature in diabetic retinopathy Farr, Ryan J. Januszewski, Andrzej S. Joglekar, Mugdha V. Liang, Helena McAulley, Annie K. Hewitt, Alex W. Thomas, Helen E. Loudovaris, Tom Kay, Thomas W. H. Jenkins, Alicia Hardikar, Anandwardhan A. Sci Rep Article MicroRNAs are now increasingly recognized as biomarkers of disease progression. Several quantitative real-time PCR (qPCR) platforms have been developed to determine the relative levels of microRNAs in biological fluids. We systematically compared the detection of cellular and circulating microRNA using a standard 96-well platform, a high-content microfluidics platform and two ultra-high content platforms. We used extensive analytical tools to compute inter- and intra-run variability and concordance measured using fidelity scoring, coefficient of variation and cluster analysis. We carried out unprejudiced next generation sequencing to identify a microRNA signature for Diabetic Retinopathy (DR) and systematically assessed the validation of this signature on clinical samples using each of the above four qPCR platforms. The results indicate that sensitivity to measure low copy number microRNAs is inversely related to qPCR reaction volume and that the choice of platform for microRNA biomarker validation should be made based on the abundance of miRNAs of interest. Nature Publishing Group 2015-06-02 /pmc/articles/PMC4649912/ /pubmed/26035063 http://dx.doi.org/10.1038/srep10375 Text en Copyright © 2015, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Farr, Ryan J. Januszewski, Andrzej S. Joglekar, Mugdha V. Liang, Helena McAulley, Annie K. Hewitt, Alex W. Thomas, Helen E. Loudovaris, Tom Kay, Thomas W. H. Jenkins, Alicia Hardikar, Anandwardhan A. A comparative analysis of high-throughput platforms for validation of a circulating microRNA signature in diabetic retinopathy |
title | A comparative analysis of high-throughput platforms for validation of a circulating microRNA signature in diabetic retinopathy |
title_full | A comparative analysis of high-throughput platforms for validation of a circulating microRNA signature in diabetic retinopathy |
title_fullStr | A comparative analysis of high-throughput platforms for validation of a circulating microRNA signature in diabetic retinopathy |
title_full_unstemmed | A comparative analysis of high-throughput platforms for validation of a circulating microRNA signature in diabetic retinopathy |
title_short | A comparative analysis of high-throughput platforms for validation of a circulating microRNA signature in diabetic retinopathy |
title_sort | comparative analysis of high-throughput platforms for validation of a circulating microrna signature in diabetic retinopathy |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4649912/ https://www.ncbi.nlm.nih.gov/pubmed/26035063 http://dx.doi.org/10.1038/srep10375 |
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