Poster presented at ESHG in Nice, France in 2007.

1. Introduction:
Tissue specific gene expression can be regulated by tissue specific promoters,
enhancers, silencers, transcription factors, differential methylation, tissue
specific alternative splicing, as well as other transcriptional and post-
transcriptional factors. There are multiple methods used for studying the
regulatory elements, however, they are useful in cases where some information
about the promoters active in a given tissue is available. This information is
lacking for the regulation of gene expression in the tissues maturing after the
tooth development is complete is unclear.
Periodontal ligament tissue (PDL) is essential for structural support of the
teeth (attaches root to the bone) (Figure 1) while gingiva offers protection from
external factors.
Expression profiling data of the primary cell cultures of periodontal ligament
tissue and outer gum tissue (gingiva) was performed using Affymetrix HU133A
arrays. The analysis has identified 292 genes differentially regulated in these
tissues. This set of genes was then subjected to promoter analysis to identify
the CpG islands and promoter binding sites. We have used a number of
bioinformatic tools, such as Promoter-Express, PAINT, MScan, Clover, CpGProD,
and CpG plot to generate an overview of the promoters of the differentially
regulated genes. As a result we identified signature promoter features of these
differentially expressed genes.
Conclusions:
The CpG island analysis has identified a
number of genes with potential methylation
sites, these will be investigated further in
the current global scan using the biopsies of
the two tissues. It will be important to
confirm experimentally if these genes are
methylated in the tissues.
The identification of potential
transcription factors (TFs) involved in the
regulation of gene expression has indicated
that Elk-1 is a potential but not only
regulator of expression in the ligament. It
was clear from CLOVER analysis that there
are multiple sites for many TFs and this
information can now be used for
experimental analysis of the promoters.
Results:
Figure 3. Bar graph
of Gene Ontology
(GO) analysis using
DAVID software.
The two sets of
differentially regulated
genes were categorised in
Gene Ontology biological
process with DAVID
software.
Those processes with
P<0.05 are displayed in the
graph for the set of genes
up and down in human
periodontal ligament in
comparison to gingiva .
Methods:
CpGProD was employed to predict the presence of CpG islands associated with the promoter regions of each of
the genes . The region 2000 bp upstream from the transcription start site of each gene was first masked using
Repeat masker and then processed by CpGProd (Fig. 2). The fasta format of the regulatory regions was
extracted using PAINT program .
The functional groups were identified using DAVID software. The genelists of differentially expressed genes
consisting of Affymetrix probe ids were uploaded to the program to determine the biological processes they
might be involved in (Fig.3) with a p-value cut-off at 0.05.
Over expressed transcription factor binding site clusters were predicted by PAINT (Fig. 4) and CLOVER (Table
2, Fig 5 & 6) programs. Over represented clusters were predicted within the sequence 2000 base pairs upstream
from the transcription start site of each of the differentially regulated genes (P< 0.05). A comparison of
identified over expressed cluster (Elk-1) in genes up in periodontal was performed by the MSCAN software
(Table 1) using JASPAR Elk-1 position frequency matrices.
Figure 2. Computational prediction of the presence of CpG
islands using CpGProD. The the presence, location and size of CpG islands
within the region 2000 base pairs upstream from the transcription start site of
each of the genes was predicted using CpGProD. The same analysis has been
performed using CpG plot and the results were consistent across 80% of the
CpG islands identified.
Gene Name Predicted Elk-1 Cluster
PAINT MSCAN
CYP51A1
EGR1
HSPE1
KPNB1
MAGOH
MET
PAWR
PLCB4
PPP1CB
RNF5
SNRPD1
SNRPG
TAF11
TDG
GLG1
SIP1
FUBP3
ADAMTS1
KIAA0152
COX17
CDC42EP3
PDLIM5
PAPOLA
EBNA1BP2
U2AF2
DHRS7B
C14orf109
LSM3
TPRKB
C14orf111
MRPL35
LSM8
ENAH
C13orf10
YRDC
ZNF587
Figure 4. PAINT transcription factor binding site cluster
analysis of genes up-regulated in ligament. PAINT was employed to
predict transcription factor binding site clusters within the 2000 bp upstream of
transcription start site of genes down- and up-regulated in ligament. The same
analysis was also performed using various GO groupings from DAVID analysis to
identify if any of the biological processes are associated with particular sets of
TF binding sites.
Table 1. Comparision of PAINT
and MSCAN prediction for the
presence of ELK-1 transcription
factor binding sites.
Acknowledgments:
This work was supported by UQ Early Career Grant.
Elk-1
Legends:
Enamel
Gingival
epithelium
Gingiva
Cementum
Alveolar
bone
Periodontal
ligament
Root of
the tooth
References:
ALKEMA, W. B. et al (2004) Nucleic Acids Res, 32, W195 -8.
DENNIS, G., JR., et al (2003) Genome Biol, 4, P3.
PONGER, L. & MOUCHIROUD, D. (2002) Bioinformatics, 18 , 631-3.
VADIGEPALLI, R., et al (2003) Omics, 7, 235 -52.
FU, Y., et al (2004) Nucleic Acids Res, 32, W420 -3.
Total differentially expressed genes - 292
Genes with CpG islands – 121
Up in Ligament – 112 genesDown in Ligament – 180 genes
Genes with CpG islands – 70
GObiologicalprocessterms
Number of Genes
Prediction of Elk-1
Transcription factor
binding site clusters
in gene by both
PAINT and MSCAN
Prediction of Elk-1
Transcription factor
binding site clusters
in gene by PAINT only
Prediction of Elk-1
Transcription factor
binding site clusters
in gene by MSCAN
only
Biological processes of
genes up in periodontal
ligament
Biological processes of
genes down in
periodontal ligament
Table 2. CLOVER analysis
of promoters of genes
up-regulated in ligament
Transcription factor P-value
Broad complex 0
SRY 0.001
AP2 alpha 0.001
FREAC-7 0.002
ELK-1 0.002
DOF-3 0.003
UBX 0.006
bZIP911 0.006
PAX4 0.008
HMG-IV 0.01
HFH-1 0.01
Figure 5. ELK-1 and other TF sites in the 2000bp
upstream of the LSM3 gene. Analysis was performed using
CLOVER software. Only the TFs with p-value<0.05 are indicated.
In search of tissue specific regulators in periodontium
- a bioinformatic approach.
Agnieszka M. Lichanska and Nguyen Pham
Department of Oral Biology and Pathology, University of Queensland, St Lucia, Australia.
Figure 1. Structure of the
periodontium
Elk-1HMG-IV bZIP911
Elk-1
Elk-1 HMG-IV HMG-IV
SRY
PAX4
DOF3 AP2 alpha
Broad-
complex
1 2000