Abstract

MicroRNA (miRNA) expression profiling has proven useful in diagnosing and understanding the development and progression of several diseases. Microarray is the standard method for analyzing miRNA expression profiles; however, it has several disadvantages, including its limited detection of miRNAs. In recent years, advances in genome sequencing have led to the development of next-generation sequencing (NGS) technologies, which significantly advance genome sequencing speed and discovery. In this study, we compared the expression profiles obtained by next generation sequencing (NGS) with the profiles created using microarray to assess if NGS could produce a more accurate and complete miRNA profile. Total RNA from 14 hepatocellular carcinoma tumors (HCC) and 6 matched non-tumor control tissues were sequenced with Illumina MiSeq 50-bp single-end reads. Micro RNA expression profiles were estimated using miRDeep2 software. As a comparison, miRNA expression profiles for 11 out of 14 HCCs were also established by microarray (Agilent human microRNA microarray). The average total sequencing exceeded 2.2 million reads per sample and of those reads, approximately 57% mapped to the human genome. The average correlation for miRNA expression between microarray and NGS and subtraction were 0.613 and 0.587, respectively, while miRNA expression between technical replicates was 0.976. The diagnostic accuracy of HCC, p-value, and AUC were 90.0%, 7.22×10−4, and 0.92, respectively. In summary, NGS created an miRNA expression profile that was reproducible and comparable to that produced by microarray. Moreover, NGS discovered novel miRNAs that were otherwise undetectable by microarray. We believe that miRNA expression profiling by NGS can be a useful diagnostic tool applicable to multiple fields of medicine.

Highlights

  • MicroRNAs are an abundant class of small (19– 24 nt) and highly conserved, non-coding RNA. They act as posttranscriptional regulators of gene expression, altering mRNA transcription and translation by hybridizing to the untranslated regions (UTRs) of certain subsets of mRNAs [1] [2]

  • We have demonstrated that quantifying miRNA using next-generation sequencing (NGS) gives results similar to those obtained by microarray, and that miRNA expression measured by NGS can discriminate Hepatocellular carcinoma (HCC) from non-tumorous tissue

  • We have shown in this study that miRNA expression profiles obtained from NGS analysis are reproducible and are concordant with that obtained by the standard microarray procedure

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Summary

Introduction

MicroRNAs (miRNAs) are an abundant class of small (19– 24 nt) and highly conserved, non-coding RNA They act as posttranscriptional regulators of gene expression, altering mRNA transcription and translation by hybridizing to the untranslated regions (UTRs) of certain subsets of mRNAs [1] [2]. Since their initial discovery in Caenorhabditis elegans in 1993 [3], researchers have gained much insight into the prevalence of miRNAs in other species. Hepatocellular carcinoma (HCC) is a common cause of cancerrelated deaths worldwide. There are more than 250,000 new HCC cases and an estimated 500,000–600,000 HCC deaths annually [4] [5]. Recent advances in functional genomics provide a deeper understanding of viral associated hepatocarcinogenesis (review in [6]), the molecular pathogenesis of HCC remains unclear

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