Functional genomics and molecular networks gene expression regulations in complex diseases: Down syndrome as a case study

Abstract

The goal of functional genomics is to understand the relationship between whole genomes and phenotypes through a dynamic approach. It requires high throughput technologies such as microarrays and data analysis. The power of this approach allowed to study complex biological functions as well as diseases. In this chapter, we introduce functional genomics and describe the statistical methods that are used to find differentially expressed genes. We analyze a large number of data sets produced on a complex disease, namely Down syndrome, in different models. We show that, whatever the model, genes that are in three copies are globally overexpressed. However, we failed to identify a set of two-copy genes that would be dysregulated in all studies. It either suggests that studies are incomplete, or that this set of genes does not exist and that overexpression of the three-copy genes impacts on the whole transcriptome in a stochastic way.