Keizo Asami Laboratory (LIKA), Federal University of Pernambuco (UFPE), 50670901, Recife, Pernambuco, Brazil.
J Mol Neurosci. 2012 Sep;48(1):257-64. doi: 10.1007/s12031-012-9771-z. Epub 2012 Apr 22.
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.
基因表达的变化和编码区域的遗传变异可能具有功能影响,与神经精神疾病等复杂疾病有关。目前需要高通量分析基因组数据,这导致了复杂的生物信息学方法的发展和改进,这些方法允许处理大量的序列和基因表达数据。在这项研究中,我们使用不同的生物信息学资源,确定了与谷氨酸能和 GABA 能系统相关的新的潜在遗传变异。首先使用 CLCbio Workbench Combined 平台分别从 Goldenpath 和国家生物技术信息中心数据库中构建表达序列标签和 mRNA 文件,然后进行多批 Smith-Waterman 比对。PMUT 软件用于增加潜在变异与致病性预测之间的准确关联。注释揭示了各种类别的变异,其中大多数是从 1 到 7 bp 的缺失。生物信息学管道似乎是一种有用的方法,可以帮助筛选对基因表达具有潜在影响的遗传变异。进一步的分析将有助于这一目标,为目前在大规模高通量实验中生成的大量数据的快速分析提供支持。