MicroRNAs (miRNAs) are emerging as key regulators of complex biological processes in several cardiovascular diseases, including atrial fibrillation (AF). Reverse transcription-quantitative polymerase chain reaction is a powerful technique to quantitatively assess miRNA expression profile, but reliable results depend on proper data normalization by suitable reference genes. Despite the increasing number of studies assessing miRNAs in cardiac disease, no consensus on the best reference genes has been reached. This work aims to assess reference genes stability in human cardiac tissue with a focus on AF investigation. We evaluated the stability of five reference genes (U6, SNORD48, SNORD44, miR-16, and 5S) in atrial tissue samples from eighteen cardiac-surgery patients in sinus rhythm and AF. Stability was quantified by combining BestKeeper, delta-Cq, GeNorm, and NormFinder statistical tools. All methods assessed SNORD48 as the best and U6 as the worst reference gene. Applications of different normalization strategies significantly impacted miRNA expression profiles in the study population. Our results point out the necessity of a consensus on data normalization in AF studies to avoid the emergence of divergent biological conclusions.

Selection of reference genes is critical for miRNA expression analysis in human cardiac tissue. A focus on atrial fibrillation

Masè, Michela;Grasso, Margherita;D'Amato, Elvira;Tessarolo, Francesco;Ravelli, Flavia
2017

Abstract

MicroRNAs (miRNAs) are emerging as key regulators of complex biological processes in several cardiovascular diseases, including atrial fibrillation (AF). Reverse transcription-quantitative polymerase chain reaction is a powerful technique to quantitatively assess miRNA expression profile, but reliable results depend on proper data normalization by suitable reference genes. Despite the increasing number of studies assessing miRNAs in cardiac disease, no consensus on the best reference genes has been reached. This work aims to assess reference genes stability in human cardiac tissue with a focus on AF investigation. We evaluated the stability of five reference genes (U6, SNORD48, SNORD44, miR-16, and 5S) in atrial tissue samples from eighteen cardiac-surgery patients in sinus rhythm and AF. Stability was quantified by combining BestKeeper, delta-Cq, GeNorm, and NormFinder statistical tools. All methods assessed SNORD48 as the best and U6 as the worst reference gene. Applications of different normalization strategies significantly impacted miRNA expression profiles in the study population. Our results point out the necessity of a consensus on data normalization in AF studies to avoid the emergence of divergent biological conclusions.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11582/308876
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