Engineering, 2013, 5, 38-41
http://dx.doi.org/10.4236/eng.2013.510B008 Published Online October 2013 (http://www.scirp.org/journal/eng)
Copyright © 2013 SciRes. ENG
An Integrated Analysis Method for miRN A, 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
Email: l guo@njmu.edu.cn, #fengchen@njmu.edu.cn
Received October 2012
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 sequen cing 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 mRN As 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 re-
verse 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, esp ecially for those 5isomiRs with the new seed sequencesthrough “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; mRN A ; Profile; Integrative Analysis
1. Introduction
As important players of gene regulation, non-coding
RNAs (ncRNAs), h ave attracted considerable interests in
many fields. Different lines of evidence suggest that
ncRNAs play an important role in multiple biological
processes and contribute to occurrence and development
of many human diseases, including microRNAs (miR-
NAs) and long non-coding RNAs (lncRNAs). miRNAs
contribute to biological processes by targeting mRNAs
through conserved complementarily to the seed (nucleo-
tides 2 - 8) of the miRNA [1]. Similarly, lncRNAs have a
broad range of biological roles in regulation of expres-
sion of genes and chromosomes. As potential regulators,
they contribute to various basic cellular functions, such
as cell proliferation, differentiation, death and tumorige-
nesis [2].
Concerning the potential relationships between differ-
ent molecules, especially for their contributions to com-
plex regulation network in multiple biological processes,
cross-platform analysis has been a new hot focus. How-
*The work was supported by National Natural Science
Foundation of
China (No. 81072389 and 81102182),
Jiangsu Planned Projects for
Postdoctoral Research Funds (No. 1201022B), and the Priority Aca-
demic Program Development of Jiangsu Higher Education Institutions
(PAPD).
#Correspondi ng author.
L. GUO ET AL.
Copyright © 2013 SciRes. ENG
39
ever, it is difficult to unveil the potential feedback loops
across different molecules in specific space and time in
regulatory network. Here, based on potential positional
and functional relationships between differ ent molecules,
we developed a method to integrative analyze datasets of
ncRNA-mRNA from different cells applying high-
through-put technologies. The sequence and potential
functional correlations and expression profiles of differ-
ent RNA molecules can provide more complex interac-
tion and biological roles across molecules in vivo. The
integrative analysis method will systematically rev eal the
complex relationships in regulatory network and contri-
butions in tumorigenesis.
2. Materials and Methods
High-throughput datasets of miRNA, lncRNA and
mRNA were obtained from HepG2 and L02 cells apply-
ing Solexa sequencing platform and microarray technol-
ogies, respectively. miRNAs were identified from the
raw miRNA datasets using Novoalign software (v2.07.11,
http://www.novocraft.com) based on the known human
miRNA precursors (pre-miRNAs) in the miRBase data-
base (Release 18.0, http://www.mirbase.org/ ) [3]. The
only one mismatch was allowed in the mapping analysis.
Specially, the multiple isomiRs [4-7] from a given
miRNA locus were also comprehensively surveyed and
analyzed. Those sequences that could match the pre-
miRNAs in the known mature miRNA or miRNA* re-
gion ± 4 nt were defaulted as isomiRs due to alternative
and imprecise cleavage of Drosha and Dicer through pre-
miRNA processing. These isomiRs may be detectedwith
3’ additional non-template nucleotide (3addition event).
LncRNA and mRNAs were obtained from array im-
ages using agilent Feature Extraction software (version
10.7.3.1) after quantile normalization of the raw data.
Fold change was calculated to obtain the differentially
expressed miRNA, lncRNA and mRNA profiles. Further,
isomiR profiles were also obtained based on potential
various sequences.
Herein, the integrated analysis method was developed
based on the potential functional and positional relation-
ships between ncRNAs and mRNAs (Figure 1). The
self-developed scripts were used to survey and obtain
potential relationships between mRNA -mi RN A, miRNA-
lncRNA and mRNA-lncRNA based on location distribu-
tions of aberrantly expressed ncRNA and mRNA profiles.
Expression patterns of these pairs were further analyzed
in HepG2 and L02 cells, especially for their deregulation
patterns in tumor cells. Functional enrichment analysis,
pathway and GO analysis were applied to define the po-
tential biological roles of these differentially expressed
functional mRNA molecules.
Figure 1. A flowchart indicates the integrative analysis of
ncRNA-mRNA based on their potential relationships.
3. Results and Discussion
Based on the original miRNA, lncRNA and mRNA pro-
files, the aberrantly expressed ncRNA and mRNA pro-
files were obtained in HepG2 cells according to fold
change filtering. Multiple isomiRs from a given miRNA
locus, including those isomiRs with 3additional non-
template nucleotides, were also obtained the abnormal
isomiR profiles. Firstly, according to the experimentally
validated target mRNAs in the miRTarBase d atabase [8],
all the targets of aberrantly expressed miRNA s were col-
lected. For those miRNAs that had no or less validated
mRNAs, we predicted their targets using the TargetScan
program [9]. IsomiRs might have various 5and/or 3
ends due to alternative cleav age of Drosha and Dicer
through pre-miRNA processing, especially 5’ isomiRs
will have the new seed sequenceswith seed shifting
events [7,10]. The new seed sequences might lead to the
shifting or change of their target mRNAs. Therefore, the
potential novel target mRNAs of dominantly expressed 5
isomiRs were also predicted and further analyzed. Al-
though these 5isomiRs and isomiRs with 3addition
always were not the abundant sequences from a given
miRNA locus, they might show unexpectedly higher
relative expression levels. The functional enrichment
analysis of their targets indicated that they have impor-
tant roles in multiple biological processes, including
some human diseases, such as cell cycle and Prostate
cancer (Table 1). Moreover, we also found inconsistent
isomiR repertoires and expression patterns in tumor and
control cells based on specific miRNA locus (data not
shown) [7]. The interesting phenomenon indicated po-
tential biological roles of isomiR repertoires in regulatory
network.
According to these abnormal miRNAs and isomiRs, a
series of target mRNAs (experimentally validated or pre -
dicted target mRNAs) were obtained. Theoretically,
L. GUO ET AL.
Copyright © 2013 SciRes. ENG
40
Table 1. An example of pathway enrichment analysis of mRNA targets of deregulated miRNAs.
Pathway No. P-value Target Genes
Cell cycle 18 3.01E30 ATM; CCNA2; CCND1; CCND2; CCNE1; CDC25A; CDK6; CDKN1A; CDKN1B;
CDKN2A; E2F1; E2F2; E2F3; EP300; RB1; RBL2; TP53; WEE1
Prostate cancer 15 3.74E26 AKT1; BCL2; CCND1; CCNE1; CDKN1A; CDKN1B; E2F1; E2F2; E2F3; EP300;
IGF1R; NFKB1; NRAS; RB1
Pancreatic cancer
; TP53
14 3.03E25 ACVR1C; AKT1; CCND1; CDC42; CDK6; CDKN2A; E2F1; E2 F2; E2F3; NFKB1;
RAC1; RB1
Melanoma
; TP53; VEGFA
13 3.21E23 AKT1; CCND1; CDK6; CDKN1A; CDKN2A; E2F1; E2F2; E2 F 3; IGF1R; MET;
NRAS; RB1; TP53
These target mRNAs are regulated by at least 2 abnormal miRNAs. mRNAs in bold type indicate up-regulated speci es, underlined mRNAs indicate down-regu-
lated species, and others indicate that they are sta bly e xpre ssed or not de te c ted.
these mRNAs might be targeted by these aberrant miR-
NA/isomiRs and lead to abnormal expression levels by
miRNA-mRNA interaction. Indeed, consistent or incon-
sistent expression patterns were detected from the actu al
aberrantly expressed mRNA profiles (Table 1). Although
miRNAs were down- or up-regulated in tumor cells, their
target mRNAs might be up- or down-regulated, or stably
expressed (Table 1). The pheno menon is mainly derived
from complex and multiple regulatory patterns between
miRNAs and mRNAs. Generally, on e miRNA can target
a great amount of mRNAs, whereas one mRNA can be
targeted by a series of miRNAs by miRNA-mRNA inte-
raction. The complex feedback loops contribute to the
whole flexible regulatory network.
Compared to miRNA, another non-coding regulatory
molecule, lncRNA, still remains mysterious. Herein, we
obtained the potential relationships between lncRNA-
mRNA and lncRNA-miRNA based on sequences and
location distr ib utio ns. Some miRNA-lncRNA and mRNA-
lncRNA pairs were surveyed based on their locations on
human chromosomes. They might be located on different
strands in the same genomic region, or located on the
same strand with the completely or partly over-lapped
regions. Based on the relationships of sequences or loca-
tions, miRNA/mRNA and lncRNA could have potential
functional relationships. The expression analysis indi-
cated that these pairs showed consistent or inconsistent
expression patterns, even though they could be reverse
complementarily binding (from the sense/antisense strands).
The results were similar to miRNA-mRNA interaction.
Although different RNA molecules may have functional
relationships, they might show various expressions as
well as consistent or inconsistent deregulated expression
patterns. Among of these, consistent expression patterns
between miRNA-lncRNA and mRN A-lncRNA were more
popular.
The genome-wide analysis of ncRNA-mRNA based
on their positional and functional relationships provides a
systematical integrative method to unveil potential rela-
tionships across different RNA molecules, including
ncRNAs (as regulatory RNA molecules) and mRNAs (as
functional RNA molecules). Here, based on aberrantly
expressed miRNA, lncRNA and mRNA profiles in tumor
cells, the integrative analysis suggested a robust regula-
tory network in tumorigenesis.
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