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This article is part of the supplement: Selected articles from the Tenth Asia Pacific Bioinformatics Conference (APBC 2012)

Open Access Proceedings

miRNA arm selection and isomiR distribution in gastric cancer

Sung-Chou Li12, Yu-Lun Liao3, Meng-Ru Ho1, Kuo-Wang Tsai4, Chun-Hung Lai3 and Wen-chang Lin23*

Author affiliations

1 Genomics Research Center, Academia Sinica, Taipei, Taiwan

2 Institute of Biomedical Informatics, National Yang-Ming University, Taipei, Taiwan

3 Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan

4 Department of Medical Education and Research, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan

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Citation and License

BMC Genomics 2012, 13(Suppl 1):S13  doi:10.1186/1471-2164-13-S1-S13

Published: 17 January 2012



MicroRNAs (miRNAs) are small non-protein-coding RNAs. miRNA genes need several biogenesis steps to form function miRNAs. However, the precise mechanism and biology involved in the mature miRNA molecules are not clearly investigated. In this study, we conducted in-depth analyses to examine the arm selection and isomiRs using NGS platform.


We sequenced small RNAs from one pair of normal and gastric tumor tissues with Solexa platform. By analyzing the NGS data, we quantified the expression profiles of miRNAs and isomiRs in gastric tissues. Then, we measured the expression ratios of 5p arm to 3p arm of the same pre-miRNAs. And, we used Kolmogorov-Smirnov (KS) test to examine isomiR pattern difference between tissues.


Our result showed the 5p arm and 3p arm miRNA derived from the same pre-miRNAs have different tissue expression preference, one preferred normal tissue and the other preferred tumor tissue, which strongly implied that there could be other mechanism controlling mature miRNA selection in addition to the known hydrogen-bonding selection rule. Furthermore, by using the KS test, we demonstrated that some isomiR types preferentially occur in normal gastric tissue but other types prefer tumor gastric tissue.


Arm selections and isomiR patterns are significantly varied in human cancers by using deep sequencing NGS data. Our results provided a novel research topic in miRNA regulation study. With advanced bioinformatics and molecular biology studies, more robust conclusions and insight into miRNA regulation can be achieved in the near future.