Computational strategies to investigate transcriptional effects of the upregulation of genes mapping to chromosome 21

Down Syndrome (DS) is the most frequent autosomal aneuploidy compatible with post-natal life. Few meta-analyses of DS gene expression data have been conducted to date even though comprehensive comparative studies would be pivotal to understand genetic hallmarks of DS and molecular mechanisms responsible for DS phenotypes. For this reason, aim of this study was to provide new insights into the transcriptional changes influencing the molecular mechanisms associated with DS using computational strategies. We first performed a comprehensive computational analysis of expression feature-level extraction output (FLEO) files from transcriptome studies on different tissues from human DS subjects, with Affymetrix microarray technology. The non-biological experimental variation was adjusted with a recently developed algorithm, called ComBat. Comparative analysis of 44 DS samples versus 40 controls from 9 experiments identified 178 genes consistently dysregulated in DS. Functional class scoring of these genes revealed that Gene Ontology categories related to cellular morphogenesis, development, defects in synapsis and apoptosis were enriched among dysregulated genes. Hsa21 genes were globally upregulated and the pathway of PGC-1?, a key regulator of mitochondrial biogenesis, was altered. A second computational strategy was applied to identify Hsa21 genes likely responsible for 2 specific traits of DS, highlighted by a previous experiment of expression profiling performed on heart tissues from DS subjects, i.e. the downregulation of nuclear encoded mitochondrial genes (NEMGs), and the upregulation of genes encoding extracellular matrix (ECM) proteins. We speculated that most of the under-expressed NEMGs might be under the same regulatory control, as well as the overexpressed ECM genes and that these controls might be affected by the trisomy of Hsa21. Therefore, to investigate whether the overexpression of individual Hsa21 genes might alter either NEMG or ECM gene expression, we analyzed expression data, retrieved from public repositories. With this strategy we identified NRIP1, a repressor of PGC-1? activity, as a good candidate gene for NEMG downregulation, and RUNX1 for the upregulation of ECM genes. These predictions agree with the result of our comprehensive meta-analysis and are supported by literature and by the analysis of the promoter regions of the NEMGs and ECM genes dysregulated in DS. Finally, we successfully validated the predicted NRIP1 repressive role on both NEMG regulation and mitochondrial function, by modulating its expression in human fibroblasts from DS fetuses.