Bioinformatic screening of the binding transcription sites in the regulatory regions of genes up-regulated in response to oxidative stress

doi:10.4236/ojgen.2012.24B001

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Open Journal of Genetics, 2012, 2, 1-4 OJGen

Published Online December 2012 (h ttp://www.SciRP.org/journal/ojgen/)

Published Online March 2012 in SciRes. http://www.scirp.org/journal/ojgen

Bioinformatic screening of the binding transcription sites

in the regulatory regions of genes up-regulated in response

to oxidative stress

Shkurat TP, Ponomareva NS, Aleksandrova AA, Shkurat MA, Butenko AI, Panich AE

Southern Federal University, Rostov-on-Don, Russia

Email: [email protected]

Received 2012

ABSTRACT

This study focuses on bioinformatics search for new

regulatory structures in the non-coding DNA, located

around the patterns of gene expression levels

changed significantly in response to oxidative stress.

Hypothesized that all of the genes increase the ex-

pression in response to oxidative stress may have the

same motifs in non-coding DNA. To search for motifs

created an integrated collection database of tran-

scription binding sites - JASPAR, TRANSFAC, Ho-

comoco TF Homo sapiens, Uniprobe TF Mus mus-

culus. Two types of regulatory regions: the promoter

region and the sequence with the capture of potential

cis-regulatory modules. In the regulatory regions of

genes increase the expression in response to oxidative

stress, in contrast to the gene expression level did not

change, families of transcription factors identified

SOX (1-30) and HX (A, B, C, D).

Keywords: Gene Expression; DNA Microarrays;

Noncoding DNA; Oxidative Stress; Transcription Factor;

Sites of Transcription Factor Binding; DNA Motif

1. INTRODUCTION

Non-coding DNA sequences are considered to be a

new challenge for molecular genetics, genomics,

transcriptomics and proteomics. Studying them is

exceptionally important for full understanding of

biological processes under normal and pathological

conditions. According to the report published by the

international project ENCODE in September, 2012,

more than 80% of the non-coding DNA is represented

by different types RNA, regions responsible for histone

modifications, open chromatin regions and transcription

factor binding sites [1]. However, it is not yet fully

understood how the regulatory information is encoded in

DNA in order to define the positions of enhancers,

silencers and other distantly operating regulatory

elements (Noonan J.P., McCallion A.S., 2010;

Lindblad-Toh K, e.a., 2011). Systematic analysis of the

transcription profile provides us with the data on

regulatory mechanisms and screening for the linked

scenario of coding and non-coding DNA interactions

that are basically important for understanding of system

biology and molecular pathogenesis of a variety of

human diseases.

We chose oxidative stress as a model of non-specific

pathogenesis. It was previously shown that a single-time

treatment of newborn rats with high oxygen pressure

modifies intracellular metabolism and results in

formation of basically new ratio of pro- and antioxidant

activities in the organism. Moreover, this newly formed

ratio seems to be stable and may be observed in the first

generation progeny [2, 3]. Cells of newborn animals

appear to be better used to variable physiological

conditions compared to mature cells. It is suggested that

treatment of newborn animals with low dose hyperbaric

oxygenation will facilitate the formation of a wide

spectrum oxygen sensitivity of a neural network that, in

turn, will lead to increase in resistance of animals to

oxidative stress in further ontogenesis [4]. Full genomic

analysis of the transcribed sequences in the brain tissue

of these animals revealed that genes, which form at least

one expression genetic pattern and regulate six key

processes including oxidative metabolism, synaptic

transmission, intracellular transport, apoptosis and

proliferation, membrane permeability membrane

potentials and intercellular contact formation, are

involved into the early genetic mechanisms of

preadaptation to oxidative stress [7].

Objectives: The present study was aimed at

bioinfo rmatics screening of new regulatory structures in

the promoter and cis-regulatory regions of the

non-coding DNA, which participate in gene expression

in response to oxidative stress.

Shkurat TP et al. / Open Journal of Genetics 2 (2012) 1-4

2. MATERIALS AND METHODS

The object of the study were white outbreed rats

Rattus norvegicus treated with high oxygen pressure (0.2

MPa, 1 h). Animals were sacrificed in 3 h after the

treatment and gene expression was studied in the frontal

lobe. The results of full genomic transcriptome study

were previously described in [5].

To perform bioinformatic analysis two groups of

genes were formed. The first group involved genes

up-regulated in response to oxidative stress. The second

group consisted of genes with unchanged expression.

The first grouped was formed by genes

NM_017138:Lamr1, NM_053440:Stmn2,

NM_057207:Sv2b, NM_053339:Acox3, Scn7a, Trpc3,

Nid2:NM_213627, Herc1, Ssc1:BC085795,

Golph2:NM_023977, Actr1a, Crebzf, Pdk4:NM_053551,

Mrpl3, Api5, Zfhx1b, Snrpb:BC083694, Snrpb. The

second group included all genes of the chromosome 20

of R. norvegicus.

Regulatory regions of 264 genes available in

KnownGene with exception of the first and the last gene

were studied.

Two types of regulatory elements were studied in both

groups. These included the promoter regions (1000, 800

b. p. upstream the start point and 200 b. p. downstream

the termination point) and the sequences, overlapping

the potential cys-regulatory elements (5000, 4000 b. p.

upstream the start point and 1000 b. p. downstream the

termination point)

The bioinformatic screening was seeking DNA motifs

located near the first group genes. Here, the “recognition

motif” implies the way to describe a set of similar

oligonucleotides, which can be specifically recognized

and bound by a certain regulatory protein.

To search the motifs we created an integrative

collection of the binding transcription sites on the basis

of JASPAR, TRANSFAC, UCSC ENCODE, Нocomoco

TF Homo sapiens and Uniprobe TF Mus musculus

databases. The integrative collection Uniprobe included

272 motifs for transcription factors of M. musculus. The

collection Нocomoco TF H. sapiens, which was

obtained by means of integration of the data from

different sources, included 332 motives for 321

transcription factor. To perform bioinformatic analysis

we chose the release of R. norvegicus genome rn4

(Baylor 3.4/rn4)

[http :// genome. uc sc.e du/ c gi-bi n/h gGat e wa y].

The conception of homotypic transcription factor

binding site clusters, which were represented by a group

of transcription factor binding site, was used as a model

of a binding region. To assess the statistical confidence

of a binding site cluster the “r-scan” model with fixed

motive acceptance threshold was used (Papatsenko D.,

2007). The statistical confidence of the “r-scan” was

assessed as a probability to find at least the expected

number of transcription factor binding site clusters in a

sequence of certain length on account that at least 1

transcription factor binding site was already found, i.e.

one cluster contains at least one binding site.

In order to perform reliable assessment of the

presence of homotypic clusters they were counted in the

first and second group. We assessed the chance (p) to

choose such a gene, the regulatory region of which

would contain at least one cluster (for promoters) and a

cluster with a confidence of at least 0.0005 for

cis-regulatory elements.

The p value can be assessed using the binomial

distribution as a confidence of the fact that in the studied

sample the transcription factor binding site clusters

contain at least k number of regulatory regions, where k

corresponds to experimentally found number of

sequences which contain the transcription factor binding

site clusters (for promoters) / at least 0.0005 confident

transcription factor binding site clusters for

cis-regulatory elements.

3. RESULTS AND DISCUSSION

It was shown that transcription factor binding sites of

the SOX subfamily more often preceded the first group

of genes (Table 1). The SOX subfamily involves 30

transcription factors, which contain heptamerous

sequence (A/T) (A/T) CAA(A/T)G (Fig. 1) [5]. It is

considered to be one of the most important subfamilies,

which regulate development of both vertebrate and

invertebrate animals. Biological functions of these

proteins were investigated in a variety of mammalian

tissues and cells during embryogenesis and

postembryonic development. It is suggested that

differentiation of the proteins for groups is typically due

to specificity of their functioning in different tissues.

They initiate differentiation program and activate tissue

specific expression. The SOX subfamily is represented

by multifunctional proteins. Among multiple roles that

SOX proteins play in cells the transcription factors can

either induce or suppress a variety of cellular processes.

Moreover, it was shown that SOX proteins are involved

in DNA reparation processes.

HXA3, hepoxilin A3; in the absence of cytosol glu-

tathione peroxidase is transformed into 12S-hydroper-

oxyeicosatetraenoic acid on biologically active epoxides.

The process is catalyzed by lipoxygenase.

HLX is expressed in mesodermal tissues in embryo-

genesis. Especially high expression was observed in

Shkurat TP et al. / Open Journal of Genetic 2 (2012) 1-4

visceral mesenchyme, skeletal myoblasts and limb mes-

enchyme[6].

Gata 3 regulates the expression of genes, which are

involved in cell growth control, immune functions and

adipogenesis inhibition.

Table 1. Confident differences of transcription factor localization prior to the first group genes.

Collection

P <0.05

<0.05,r-skan >9

P <0.01

Рromoter_Hocomoc

o (s1000)

PAX6, ALX1, PITX2, OTX2, CRX, CDC5L,

PO3F2

FOXA1, CDX2

SOX5,

FOXO1,EVI1,

FOXO3

Рromoter_Uniprobe

(s1000)

GATA6, BARX2, HXB6, MEOX1, SH

SOX8, HXD3, HXA6, DLX1, ARI5A, PITX2,

HXA10, HXA7, DLX3, HXA9, BARH1, SOX15,

HXB7, HXC8, SOX13, HXA2, HDX, PDX1,

SP100, SOX30, GATA3, PO6F1, HXA1

TBP, TF7L1,

LMX1A

DLX2,

ARH2, DBX1

CRM_Hocomoco

(s5000)

SOX9, ARI3A, NFYA, ATF6A, CDX1, ZEP1,

SOX5, NFYB, SOX2

EVI1, MBD2,

MEF2C, MEF2A

CRM_Uniprobe

(s5000)

SOX15, SOX30, ZN187, HXD13, PROP1,

SOX18, RX, SRY, SOX7, SOX14,

HXD1,DLX4,PHX2B, PAX6,HXD10,HBP1,OTP

PO3F2, PO2F1,

SOX12

SOX5,

SOX13, SOX17,

DBX1, HLX-

Figure 1. Consensus sequences of the SOX transcription factors SOX [(A/T) (A/T) CAA(A/T)G[5].

SP100 is a multifunctional protein factor often found

in brain

Therefore, we have found out that primary treatment

with hyperbaric oxygenation (0.2 MPa, 1 h) results in

Shkurat TP et al. / Open Journal of Genetic 2 (2012) 1-4

up-regulation of a set of transcription factors, which are

associated with the studied genes and their promoters.

The obtained data support the idea of specific and

possibly cooperative interaction of transcription factors

in both promoters and cis-regulatory elements. The me-

chanism of simultaneous gene expression induced by

oxidative stress is not yet clear. It is suggested that the

neighbor sequences of non-coding DNA may be in-

volved in these processes. Our data allow us to conclude

that non-coding DNA somehow participates in

gene -gene interactions. The detailed study of all func-

tions of non-coding DNA is considered to be a challeng-

ing task for biological science.

4. ACKNOWLEDGEMENTS

This work was supported by the Federal Targeted Program by The

Ministry of education and science of Russian Federation, state contract

no. 14.740.11.0006

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