Cross disease analysis of co-functional microRNA pairs on a reconstructed network of disease-gene-microRNA tripartite.
BACKGROUND
MicroRNAs always function cooperatively in their regulation of gene expression. Dysfunctions of these co-functional microRNAs can play significant roles in disease development. We are interested in those multi-disease associated co-functional microRNAs that regulate their common dysfunctional target genes cooperatively in the development of multiple diseases. The research is potentially useful for human disease studies at the transcriptional level and for the study of multi-purpose microRNA therapeutics.


RESULTS
We designed a computational method to detect multi-disease associated co-functional microRNA pairs and conducted cross disease analysis on a reconstructed disease-gene-microRNA (DGR) tripartite network. The construction of the DGR tripartite network is by the integration of newly predicted disease-microRNA associations with those relationships of diseases, microRNAs and genes maintained by existing databases. The prediction method uses a set of reliable negative samples of disease-microRNA association and a pre-computed kernel matrix instead of kernel functions. From this reconstructed DGR tripartite network, multi-disease associated co-functional microRNA pairs are detected together with their common dysfunctional target genes and ranked by a novel scoring method. We also conducted proof-of-concept case studies on cancer-related co-functional microRNA pairs as well as on non-cancer disease-related microRNA pairs.


CONCLUSIONS
With the prioritization of the co-functional microRNAs that relate to a series of diseases, we found that the co-function phenomenon is not unusual. We also confirmed that the regulation of the microRNAs for the development of cancers is more complex and have more unique properties than those of non-cancer diseases.
Advanced Analytics Institute, University of Technology Sydney, PO Box 123, Broadway, 2007, NSW, Australia.
Hui
H
Peng
Advanced Analytics Institute, University of Technology Sydney, PO Box 123, Broadway, 2007, NSW, Australia.
Chaowang
C
Lan
Advanced Analytics Institute, University of Technology Sydney, PO Box 123, Broadway, 2007, NSW, Australia.
Yi
Y
Zheng
Centre for Health Technologies, University of Technology Sydney, PO Box 123, Broadway, 2007, NSW, Australia.
Gyorgy
G
Hutvagner
School of Information Technologies and the Faculty of Engineering and Information Technologies, University of Sydney, J12/318 Cleveland St, Darlington, 2008, NSW, Australia.
Dacheng
D
Tao
Advanced Analytics Institute, University of Technology Sydney, PO Box 123, Broadway, 2007, NSW, Australia. Jinyan.Li@uts.edu.au.
Jinyan
J
Li
D019295:Computational Biology / Q000379:methods*; D006801:Humans; D035683:MicroRNAs / Q000235:genetics*
D035683:MicroRNAs
Co-functional microRNA pair; Cross-disease analysis; Disease-microRNA associations prediction