Integrating MicroRNA and MRNA Expression Profiles For Identification of Regulatory Networks

The discovery of microRNA as an additionalmicroarray was used. Expression of miRNA was
regulatory mechanism has been a revolution to theevaluated using miRNA microarrays (provided by LC
field of Developmental Biology. While early researchSciences). Both mRNA and miRNA expression was
has focused on the identification of miRNAs using avalidated using qRT-PCR.
combination of experimental and computationalBio-informatics analysis was then carried out on the
techniques, subsequent studies have focused ontwo data-sets to show the negative correlation
identification of miRNA-target mRNA pairs as abetween predicted mRNA targets and miRNA
means of identifying regulatory networks. It has beenexpression, indicating a gene expression regulatory
shown that the relationship between messenger RNAnetwork at work. The negative correlation found in
and microRNA (often an inverse relationship) plays athis study supports the theory that miRNAs play a
large role in cell functionality, especially in the earlylarger role in modulating the expression of genes
stages of cell development.which are essential for cortical neurogenesis. As
The identification of miRNAs, their target mRNAs,neuronal differentiation progresses, up-regulated
and the construction of their regulatory networks willmiRNA may down-regulate the expression of genes
provide new insights into complex biologicalwhich are no longer required.
procedures. There has been extensive computationalThe availability of mRNA and miRNA profiles from the
analysis of transcriptome and microRNAome data;same cell type represents a major limitation in the
however, many of the data-sets are derived fromnetwork analysis of genetic circuits. A platform
separate studies. There is a need for studiescapable of generating integrated data-sets, not only
encompassing both data-sets from cells within thefrom the same cell type, but from cells within the
same context for better understanding of miRNA -same context would be an important new tool for
target interaction. Access to both data-sets plus newanalysis of miRNA - target interaction. Such a tool
bio-informatics capabilities represents a powerful newmay provide a solution for:o Validation of
functional genomics tool for construction of cellcomputational methods of target predictiono
development networks/pathways and also forDiscovery of novel regulatory pathwayso Elucidating
unraveling the complex mechanism of action ofthe mechanism of action of miRNAso Providing
miRNA.datasets for the development of new pathway
In a recent study, researchers at the NIH usedanalysis algorithmso A diagnostic device for improving
microarray analysis to show the correlation betweenbio-molecular classification of human cancers
mRNA and miRNA in neuronal cortical development*.* Nielsen JA, Lau P, Maric D, Barker JL, Hudson LD.
Rat neuronal progenitors were obtained at days 11,(2009) Integrating microRNA and mRNA expression
12, and 13 and their total RNA extracted. To evaluateprofiles of neuronal progenitors to identify regulatory
the expression of mRNA a gene expression profilenetworks underlying the onset of cortical
using the Affymetrix Rat Expression 230 2.0neurogenesis. BMC Neurosci 10(1), 98.