Discovery and validation of Barrett's esophagus microRNA transcriptome by next generation sequencing

利用新一代测序技术发现并验证巴雷特食管的microRNA转录组

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Abstract

OBJECTIVE: Barrett's esophagus (BE) is transition from squamous to columnar mucosa as a result of gastroesophageal reflux disease (GERD). The role of microRNA during this transition has not been systematically studied. DESIGN: For initial screening, total RNA from 5 GERD and 6 BE patients was size fractionated. RNA <70 nucleotides was subjected to SOLiD 3 library preparation and next generation sequencing (NGS). Bioinformatics analysis was performed using R package "DEseq". A p value<0.05 adjusted for a false discovery rate of 5% was considered significant. NGS-identified miRNA were validated using qRT-PCR in an independent group of 40 GERD and 27 BE patients. MicroRNA expression of human BE tissues was also compared with three BE cell lines. RESULTS: NGS detected 19.6 million raw reads per sample. 53.1% of filtered reads mapped to miRBase version 18. NGS analysis followed by qRT-PCR validation found 10 differentially expressed miRNA; several are novel (-708-5p, -944, -224-5p and -3065-5p). Up- or down- regulation predicted by NGS was matched by qRT-PCR in every case. Human BE tissues and BE cell lines showed a high degree of concordance (70-80%) in miRNA expression. Prediction analysis identified targets that mapped to developmental signaling pathways such as TGFβ and Notch and inflammatory pathways such as toll-like receptor signaling and TGFβ. Cluster analysis found similarly regulated (up or down) miRNA to share common targets suggesting coordination between miRNA. CONCLUSION: Using highly sensitive next-generation sequencing, we have performed a comprehensive genome wide analysis of microRNA in BE and GERD patients. Differentially expressed miRNA between BE and GERD have been further validated. Expression of miRNA between BE human tissues and BE cell lines are highly correlated. These miRNA should be studied in biological models to further understand BE development.

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