Genomic and Post-Genomic Analysis of Human Chromosome 21 in Relation to the Pathogenesis of Trisomy 21 (Down Syndrome)

We performed an innovative systematic meta-analysis of gene expression profiles of whole normal human brain and heart to provide a quantitative transcriptome reference map of it, i.e. a typical reference value of expression for all the known, mapped and uncharacterized (unmapped) transcripts. For this reason, we used the software named TRAM (Transcriptome Mapper), which is able to generate transcriptome maps based on gene expression data from multiple sources. We also analyzed differential gene expression by comparing brain with human foetal brain, with a pool of non-brain tissues and with the three brain sub-region: cerebellum, cerebral cortex and hippocampus, the main regions severely affected with cognitive impairment, as seen in the case of trisomy 21. Data were downloaded from microarray databases, processed and analyzed using TRAM software and validated in vitro by assaying gene expression through several magnitude orders by "Real Time" reverse transcription polymerase chain reaction (RT-PCR). The excellent agreement between in silico and experimental data suggested that our transcriptome maps may be a useful quantitative reference benchmark for gene expression studies related to the human brain and heart. We also generated an integrated quantitative transcriptome map by systematic meta-analysis from all available gene expression profile datasets related to AMKL in paediatric age. The incidence of Acute Megakaryoblastic Leukemia (AMKL) is 500-fold higher in children with Down Syndrome (DS) compared with non-DS children. We present an integrated original model of the DS AMLK transcriptome, providing the identification of genes relevant for its pathophysiology which can potentially be new clinical markers. Finally, computational and molecular analysis of a highly restricted region of chromosome 21, which represents a strong candidate for typical DS features and is considered as intergenic, was performed. Northern Blot analysis and computational biology results show that HR-DSCR contain active loci bidirectionally transcribed.