An Integrated Analysis Method for miRNA, lncRNA and mRNA Profiles Based on Their Functional and Positional Relationships

Li Guo, Sheng Yang, Yang Zhao, Hui Zhang, Qian Wu, Feng Chen

Department of Epidemiology and Biostatistics and Ministry of Education Key Lab for Modern Toxicology, School of Public Health, Nanjing Medical University, Nanjing, China.
Department of Epidemiology and Biostatistics and Ministry of Education Key Lab for Modern Toxicology, School of Public Health, Nanjing Medical University, Nanjing, China.

DOI: 10.4236/eng.2013.510B008                

Abstract

ncRNAs have been identified as potential regulatory molecules and have multiple biological roles. Aberrant expression of specific ncRNAs contributes to multiple biological processes and many human diseases. Herein, we simultaneously profiled miRNA, lncRNA and mRNA in human HepG2 and L02 cells applying high-throughput sequencing and micro-array technologies. Abnormal miRNA, lncRNA and mRNA profiles were assessed through fold change filtering. A cross-platform integrated analysis method was developed to analyze differentially expressed miRNA, lncRNA and mRNA profiles. miRNA-mRNA interaction was analyzed according to their functional relationships. Target mRNAs of aberrantly expressed miRNAs were obtained from experimentally validated datasets or predicted using some programs. Generally, multiple target mRNAs were involved, and they have versatile roles by functional enrichment analysis. Ac-cording to actual expression datasets in the study, compared to deregulated miRNAs, these theoretical target mRNAs showed various expression patterns. The consistent or inconsistent expression was mainly derived from complex, mul-tiple, flexible and alternative regulatory relationships between miRNA and mRNA. Further, miRNA/mRNA and lncRNA were completely surveyed based on their location distributions on human chromosomes. Many miRNA-lncRNA and mRNA-lncRNA pairs always were located on the same strand or different strands in the specific genomic region. Due to the location distributions, they might have partly or completely overlapped regions or they could be reverse complementarily binding. These miRNA/mRNA-lncRNA pairs showed consistent or inconsistent expression pat-terns, although they might have functional relationships through reverse complementarily binding events. Moreover, we also detected and analyzed various isomiRs from a given miRNA locus, including those isomiRs with 3’ additional non-template nucleotides. These isomiRs, especially for those 5’ isomiRs with the new “seed sequences” through “seed shifting” events, maybe have potential biological roles as well as isomiR repertoire and their expression patterns. The integrative analysis provides potential functional relationships between miRNA, lncRNA and mRNA across different datasets. The complex and various expression patterns suggest a robust regulatory network across different regulatory molecules and their targets.

Keywords

ncRNA; mRNA; Profile; Integrative Analysis

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	D. P. Bartel, “MicroRNAs: Genomics, Biogenesis, Mechanism, and Function,” Cell, Vol. 116, 2004, pp. 281-297. http://dx.doi.org/10.1016/S0092-8674(04)00045-5
[2]	H. W. Hwang and J. T. Mendell, “MicroRNAs in Cell Proliferation, Cell Death, and Tumorigenesis,” British Journal of Cancer, vol. 94, 2006, pp. 776-780. http://dx.doi.org/10.1038/sj.bjc.6603023
[3]	A. Kozomara and S. Griffiths-Jones, “miRBase: Integrating microRNA Annotation and Deep-Sequencing Data,” Nu-cleic Acids Research, Vol. 39, 2011, pp. D152-D157. http://dx.doi.org/10.1093/nar/gkq1027
[4]	S. L. Fernandez-Valverde, R. J. Taft and J. S. Mattick, “Dynamic isomiR Regulation in Drosophila Development,” RNA—A Publication of the RNA Society, Vol. 16, 2010, pp. 1881-1888. http://dx.doi.org/10.1261/rna.2379610
[5]	L. W. Lee, S. Zhang, A. Etheridge, L. Ma, D. Martin, D. Galas and K. Wang, “Complexity of the microRNA Repertoire Revealed by Next Generation Sequencing,” RNA—A Publication of the RNA Society, Vol. 16, 2010, pp. 2170-2180. http://dx.doi.org/10.1261/rna.2225110
[6]	A. M. Burroughs, Y. Ando, M. J. L. de Hoon, Y. Tomaru, T. Nishibu, R. Ukekawa, T. Funakoshi, T. Kurokawa, H. Suzuki, Y. Hayashizaki and C. O. Daub, “A Comprehensive Survey of 3’ Animal miRNA Modification Events and a Possible Role for 3’ Adenylation in Modulating miRNA Targeting Effectiveness,” Genome Research, Vol. 20, 2010, pp. 1398-1410. http://dx.doi.org/10.1101/gr.106054.110
[7]	L. Guo, Q. Yang, J. Lu, H. Li, Q. Ge, W. Gu, Y. Bai and Z. Lu, “A Comprehensive Survey of miRNA Repertoire and 3’ Addition Events in the Placentas of Patients with Pre-eclampsia from High-Throughput Sequencing,” PLoS ONE, Vol. 6, 2011, Article ID: e21072. http://dx.doi.org/10.1371/journal.pone.0021072
[8]	S. D. Hsu, F. M. Lin, W. Y. Wu, C. Liang, W. C. Huang and W. L. Chan, “miRTarBase: A Database Curates Experimentally Validated microRNA-Target Interactions,” Nucleic Acids Research, Vol. 39, 2011, pp. D163-D169. http://dx.doi.org/10.1093/nar/gkq1107
[9]	B. P. Lewis, I. H. Shih, M. W. Jones-Rhoades, D. P. Bartel and C. B. Burge, “Prediction of Mammalian micro-RNA Targets,” Cell, Vol. 115, 2003, pp. 787-798. http://dx.doi.org/10.1016/S0092-8674(03)01018-3
[10]	L. Guo, H. Li, J. Lu, Q. Yang, Q. Ge, W. Gu, Y. Bai and Z. Lu, “Tracking miRNA Precursor Metabolic Products and Processing Sites through Completely Analyzing High-Throughput Sequencing Data,” Molecular Biology Reports, Vol. 39, 2012, pp. 2031-2038. http://dx.doi.org/10.1007/s11033-011-0950-8