Abstract
Purpose: :
Tumor necrosis factor alpha (TNFα) is an important mediator of the therapeutic effects of laser trabeculoplasty on glaucoma. Trabecular meshwork (TM) cells respond to TNFα treatment by increasing matrix metalloproteinases (MMPs), enzymes that initiate turnover the extracellular matrix (ECM). To further understand ECM remodeling and its effects on aqueous humor outflow resistance, studies were conducted to identify de-novo transcription factor binding sites in TM cell gene express response to TNFα treatment.
Methods: :
Primary porcine TM cells were treated with recombinant human TNFα (10 ng/ml). At 12, 24, and 48 hrs after treatment, 9 μg of total purified RNA was collected for gene expression profiling. Three independent experiments were conducted at all 3 time points. After normalization, the Significance Analysis of Microarrays was employed to identify differentially expressed genes for each time point separately with the statistical significance defined as a q-value less than 5%. TightClust cluster analysis was performed on genes which showed significant changes at one or more time points; this grouped these genes by similar temporal expression patterns. DNA sequences for all genes in the top 50 clusters were extracted using Ensembl Genome Browser. Masked sequences were extracted in order to remove regions of interspersed repeats or areas of low complexity for 5K bp upstream with 2K bp downstream. The extracted sequences were analyzed by CisModule to identify putative cis-regulatory motifs and modules of transcription factors and their binding sites. The consensus sequences of the motif binding sites predicted by CisModule were identified by TRANSFAC Professional database against known cis-regulatory motifs.
Results: :
There were distinctly different patterns between up-regulated and down-regulated clusters. Several transcription factors were common and present in several clusters, notably Churchill, ETF, MOVO-B, and WT1. Other transcription factors were spread throughout the groups with less clear patterns. A few were only present in one time group. Despite a significant increase of information in the TRANSFAC Professional database, CisModule still predicted numerous de-novo regulatory motifs.
Conclusions: :
Transcription factors play a crucial role in regulating gene expression patterns. Transcription factor binding sites can be identified by database searches of known transcription factor binding sites or by using statistical models. These streamlined methods were effective in identifying common known and potentially new motifs of co-expressed genes after mRNA microarrays experiment. Further validation studies will be required to confirm the functionality of these de-novo motifs.
Keywords: gene microarray • transcription factors • trabecular meshwork