Searching for new genetic variations in expression databases for the GABAergic and glutamatergic systems

Abstract

Changes in gene expression and genetic variations in coding regions have likely functional impact, potentially associated with complex diseases, such as neuropsychiatric conditions. A current need for high throughput analysis of genomic data is leading to the development and improvement of sophisticated bioinformatics approaches, which allows the processing of large amounts of sequence and gene expression data. In this study, we identified new potential genetic variations prioritizing genes related to glutamatergic and GABAergic systems, using different bioinformatics resources. The CLCbio Workbench Combined platform was initially used to build expressed sequence tags and mRNA files retrieved, respectively, from the Goldenpath and National Center for Biotechnology Information databases and latter to perform multiple batches of Smith-Waterman alignments. The PMUT software was used to increase an accurate association between potential variations and pathogenic predictions. The annotation revealed various classes of variations and most of them are deletions ranging from 1 to 7 bp. Bioinformatic pipelines seem to be useful approaches to help screening for genetic variations with potential impact in gene expression. Further analysis will foster this aim to provide celerity at the massive analysis of data currently generated in large scale high throughput experiments.