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:

EnamelGingival epithelium

Gingiva

Cementum

Alveolar bone

Periodontal ligamentRoot 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

GO b

iolo

gica

l pro

cess

ter

ms

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-valueBroad complex 0SRY 0.001AP2 alpha 0.001FREAC-7 0.002ELK-1 0.002DOF-3 0.003UBX 0.006bZIP911 0.006PAX4 0.008HMG-IV 0.01HFH-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