Defining quantification methods and optimizing protocols for microarray hybridization of circulating microRNAs View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2017-12

AUTHORS

Anna Garcia-Elias, Leonor Alloza, Eulàlia Puigdecanet, Lara Nonell, Marta Tajes, Joao Curado, Cristina Enjuanes, Oscar Díaz, Jordi Bruguera, Julio Martí-Almor, Josep Comín-Colet, Begoña Benito

ABSTRACT

MicroRNAs (miRNAs) have emerged as promising biomarkers of disease. Their potential use in clinical practice requires standardized protocols with very low miRNA concentrations, particularly in plasma samples. Here we tested the most appropriate method for miRNA quantification and validated the performance of a hybridization platform using lower amounts of starting RNA. miRNAs isolated from human plasma and from a reference sample were quantified using four platforms and profiled with hybridization arrays and RNA sequencing (RNA-seq). Our results indicate that the Infinite® 200 PRO Nanoquant and Nanodrop 2000 spectrophotometers magnified the miRNA concentration by detecting contaminants, proteins, and other forms of RNA. The Agilent 2100 Bioanalyzer PicoChip and SmallChip gave valuable information on RNA profile but were not a reliable quantification method for plasma samples. The Qubit® 2.0 Fluorometer provided the most accurate quantification of miRNA content, although RNA-seq confirmed that only ~58% of small RNAs in plasma are true miRNAs. On the other hand, reducing the starting RNA to 70% of the recommended amount for miRNA profiling with arrays yielded results comparable to those obtained with the full amount, whereas a 50% reduction did not. These findings provide important clues for miRNA determination in human plasma samples. More... »

PAGES

7725

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41598-017-08134-3

DOI

http://dx.doi.org/10.1038/s41598-017-08134-3

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1091144880

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/28798363


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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1038/s41598-017-08134-3'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/s41598-017-08134-3'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/s41598-017-08134-3'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/s41598-017-08134-3'


 

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