Comparison of Two MicroRNA Quantification Methods for Assaying MicroRNA Expression Profiles in Wheat(Triticum aestivum L.)  

作　　者：HAN Ran YAN Yan ZHOU Peng ZHAO Hui-xian 

机构地区：[1]State Key Laboratory of Crop Stress Biology for Arid Areas/College of Life Sciences,Northwest A&F University

出　　处：《Journal of Integrative Agriculture》2014年第4期733-740,共8页农业科学学报（英文版）

基　　金：the National Natural Science Foundation of China(30871578)

摘　　要：Two microRNA （miRNA） quantification methods, namely, poly（A） reverse transcription （RT）-quantitative real-time polymerase chain reaction （qPCR） and stem-loop RT-qPCR, have been developed for quantifying miRNA expression. In the present study, five miRNAs, including miR166, miR167, miR168, miR159, and miR396, with different sequence frequencies, were selected as targets to compare their expression profiles in five wheat tissues by applying the two methods and deep sequencing. The study aimed to determine a simple, reliable and high-throughput method for detecting miRNA expressions in wheat tissues. Results showed that the miRNA expression profiles determined by poly（A） RT-qPCR were more consistent with those obtained by deep sequencing. Further analysis indicated that the correlation coefficients of the data obtained by poly（A） RT-qPCR and deep sequencing （0.739, P≤0.01） were higher than those obtained by stem-loop RT-qPCR and deep sequencing （0.535, P≤0.01）. The protocol used for poly（A） RT-qPCR is simpler than that for stem-loop RT-qPCR. Thus, poly（A） RT-qPCR was a more suitable high-throughput assay for detecting miRNA expression profiles. To the best of our knowledge, this study was the first to compare these two miRNA quantification methods. We also provided useful information for quantifying miRNA in wheat or other plant species.Two microRNA （miRNA） quantification methods, namely, poly（A） reverse transcription （RT）-quantitative real-time polymerase chain reaction （qPCR） and stem-loop RT-qPCR, have been developed for quantifying miRNA expression. In the present study, five miRNAs, including miR166, miR167, miR168, miR159, and miR396, with different sequence frequencies, were selected as targets to compare their expression profiles in five wheat tissues by applying the two methods and deep sequencing. The study aimed to determine a simple, reliable and high-throughput method for detecting miRNA expressions in wheat tissues. Results showed that the miRNA expression profiles determined by poly（A） RT-qPCR were more consistent with those obtained by deep sequencing. Further analysis indicated that the correlation coefficients of the data obtained by poly（A） RT-qPCR and deep sequencing （0.739, P≤0.01） were higher than those obtained by stem-loop RT-qPCR and deep sequencing （0.535, P≤0.01）. The protocol used for poly（A） RT-qPCR is simpler than that for stem-loop RT-qPCR. Thus, poly（A） RT-qPCR was a more suitable high-throughput assay for detecting miRNA expression profiles. To the best of our knowledge, this study was the first to compare these two miRNA quantification methods. We also provided useful information for quantifying miRNA in wheat or other plant species.

关 键 词：Triticum aestivum L. MICRORNA deep sequencing poly（A） RT-qPCR stem-loop RT-qPCR 

分 类 号：S512.1[农业科学—作物学]