Optimal endogenous controls for microRNA analysis of visceral adipose tissue in the NAFLD mouse model.

Veronika Uhrova, Helena Parova, Zuzana Cervinkova, Otto Kucera, Vladimir Palicka
Author Information
  1. Veronika Uhrova: Department of Clinical Biochemistry and Diagnostics, Charles University, Faculty of Medicine in Hradec Kra��love�� and University Hospital Hradec Kra��love��, Hradec Kra��love��, Czech Republic.

Abstract

The selection of proper reference genes and materials is critical in the design of PCR experiments, especially for differential expression studies. In this study, we propose a method to identify robust endogenous control miRNAs in the visceral adipose tissue of C57BL/6J mice with non-alcoholic fatty liver disease induced by alternating Western and control diets. This study outlines a comprehensive methodology for the analysis of microRNA endogenous controls using microfluidic cards in conjunction with miRNA profiling through small RNA sequencing and subsequent validation by quantitative PCR and the RefFinder algorithm. Criteria included were fold change, p-value, reads per million, and gene stability assessment. A set of six putative endogenous microRNAs was identified (miR-331-3p, let-7a-5p, miR-1839-5p, miR-151a-5p, let-7d-5p, and let-7c-5p). Subsequent validation and analysis using the RefFinder algorithm assessed the stability of the selected genes, and a combination of the three most stable endogenous miRNA controls (miR-331-3p, let-7a- 5p, and miR-1839-5p) exhibiting consistent expression patterns with minimal variability was set. Given the absence of universal endogenous controls, individual evaluation of normalizers for each experiment is imperative for accurate miRNA expression measurements. This approach, which combines multiple techniques and assessments, provides a reliable strategy for identifying and validating endogenous controls in miRNA studies.

MeSH Term

Animals
MicroRNAs
Non-alcoholic Fatty Liver Disease
Mice
Intra-Abdominal Fat
Disease Models, Animal
Mice, Inbred C57BL
Gene Expression Profiling
Gene Expression Regulation
Male
Algorithms

Chemicals

MicroRNAs

Word Cloud

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