Xiaolei Liu1, Liang Zhang1, Ke Cheng1, Xiao Wang2, Gaoping Ren1, Peng Xie3. 1. Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Yuzhong District, Chongqing 400016, China; Chongqing Key Laboratory of Neurobiology, Chongqing, China; Institute of Neuroscience, Chongqing Medical University, Chongqing, China. 2. Chongqing Key Laboratory of Neurobiology, Chongqing, China; Institute of Neuroscience, Chongqing Medical University, Chongqing, China. 3. Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Yuzhong District, Chongqing 400016, China; Chongqing Key Laboratory of Neurobiology, Chongqing, China; Institute of Neuroscience, Chongqing Medical University, Chongqing, China. Electronic address: xiepeng@cqmu.edu.cn.
Abstract
BACKGROUND: Mounting evidence has demonstrated microRNA involvement in the set of diverse pathways associated with major depressive disorder (MDD). Reverse transcription quantitative real-time PCR (RT-qPCR) has been widely used in microRNA expression studies. To achieve accurate and reproducible microRNA RT-qPCR data, reference genes are required. The goal of this study is to systematically identify suitable reference genes for normalizing RT-qPCR assays of microRNA expression in the plasma of MDD patients. METHODS: Candidate reference genes were selected from plasma samples of both MDD and healthy controls by miRNA microarrays, in addition to a frequently used reference gene - U6 small nuclear RNA. Putative reference genes were thereafter validated by RT-qPCR in plasma samples, and analyzed by the four statistical algorithms geNorm, NormFinder, BestKeeper and the comparative delta-Ct method. Finally, the validity of the selected reference genes was assessed with two significantly decreased miRNAs identified by microarray. RESULTS: Five miRNAs (miR-320d, miR-101-3p, miR-106a-5p, miR-423-5p, miR-93-5p) based on microarray data and U6 were identified as putative reference genes. The results of the merged data from four statistical algorithms revealed that the most adequate microRNAs tested for normalization were miR-101-3p and miR-93-5p. Assessment of the validity of the selected reference genes confirms the suitability of applying the combination of miR-101-3p and miR-93-5p as optimal references genes. LIMITATIONS: Relatively small sample size; and lack of other disease groups. CONCLUSIONS: The normalization methods proposed here can contribute to improve studies on MDD biomarker identification and/or pathogenesis by providing more reliable and accurate expression measurements. Crown
BACKGROUND: Mounting evidence has demonstrated microRNA involvement in the set of diverse pathways associated with major depressive disorder (MDD). Reverse transcription quantitative real-time PCR (RT-qPCR) has been widely used in microRNA expression studies. To achieve accurate and reproducible microRNA RT-qPCR data, reference genes are required. The goal of this study is to systematically identify suitable reference genes for normalizing RT-qPCR assays of microRNA expression in the plasma of MDDpatients. METHODS: Candidate reference genes were selected from plasma samples of both MDD and healthy controls by miRNA microarrays, in addition to a frequently used reference gene - U6 small nuclear RNA. Putative reference genes were thereafter validated by RT-qPCR in plasma samples, and analyzed by the four statistical algorithms geNorm, NormFinder, BestKeeper and the comparative delta-Ct method. Finally, the validity of the selected reference genes was assessed with two significantly decreased miRNAs identified by microarray. RESULTS: Five miRNAs (miR-320d, miR-101-3p, miR-106a-5p, miR-423-5p, miR-93-5p) based on microarray data and U6 were identified as putative reference genes. The results of the merged data from four statistical algorithms revealed that the most adequate microRNAs tested for normalization were miR-101-3p and miR-93-5p. Assessment of the validity of the selected reference genes confirms the suitability of applying the combination of miR-101-3p and miR-93-5p as optimal references genes. LIMITATIONS: Relatively small sample size; and lack of other disease groups. CONCLUSIONS: The normalization methods proposed here can contribute to improve studies on MDD biomarker identification and/or pathogenesis by providing more reliable and accurate expression measurements. Crown
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