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

doi:10.4236/eng.2013.510B008

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Engineering, 2013, 5, 38-41

http://dx.doi.org/10.4236/eng.2013.510B008 Published Online October 2013 (http://www.scirp.org/journal/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 [email protected], #[email protected]

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 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; 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.

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 (3’ addition 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 3’ additional 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 5’ and/or 3’

ends due to alternative cleav age of Drosha and Dicer

through pre-miRNA processing, especially 5’ isomiRs

will have the new “seed sequences” with “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 5’ isomiRs and isomiRs with 3’ addition

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.

Table 1. An example of pathway enrichment analysis of mRNA targets of deregulated miRNAs.

Pathway No. P-value Target Genes

Cell cycle 18 3.01E−30 ATM; CCNA2; CCND1; CCND2; CCNE1; CDC25A; CDK6; CDKN1A; CDKN1B;

CDKN2A; E2F1; E2F2; E2F3; EP300; RB1; RBL2; TP53; WEE1

Prostate cancer 15 3.74E−26 AKT1; BCL2; CCND1; CCNE1; CDKN1A; CDKN1B; E2F1; E2F2; E2F3; EP300;

IGF1R; NFKB1; NRAS; RB1

Pancreatic cancer

; TP53

14 3.03E−25 ACVR1C; AKT1; CCND1; CDC42; CDK6; CDKN2A; E2F1; E2 F2; E2F3; NFKB1;

RAC1; RB1

Melanoma

; TP53; VEGFA

13 3.21E−23 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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