COMPUTATIONAL ANALYSIS OF KEY TRANSCRIPTION FACTOR BINDING MODULES IN ALZHEIMER’S DISEASE AND ITS ASSOCIATED GENES

Abstract

There is partial understanding of the molecular mechanism underlying Alzheimer’s disease (AD) pathogenesis and the genetic risk factors involved in it. Many approaches like genomics, proteomics and functional genomics have been taken in the recent years to identify new factors of AD etiology. Pathway or a particular disease-associated gene might have participated in multiple transcriptional co-regulation networks. The group of such gene can be identified either by literature survey or high throughput molecular techniques like protein interaction mapping or microarrays. The strategy that has been followed in the study includes in-silico promoter analysis to define regulatory networks and then locating important co regulated factors without a priori knowledge. Using a computational approach it was concluded that different AD related genes have common transcription factor binding site modules. A new bioinformatics workflow was established to identify other unknown co-regulated genes, which may potentially relate to AD. We have constructed some significant TF modules through Genomatix tool, composed of some important transcription factor families: CTCF, SP1F, and EGRF, which are thought to be genetically conserved in between human and mouse or rat APP promoter sequences. We found some new genes like cadherin 1, MRP, REEP5, EIF5 which can potentially regulate AD mechanism. After that to validate our result we have done Multiple Sequence Alignment (MSA) including our predicted genes and established a relation between our predicted genes and key AD causing genes.