10.6084/m9.figshare.7886671.v1
Friederike Ehrhart
Friederike
Ehrhart
Susan L. Coort
Susan
L. Coort
Lars Eijssen
Lars
Eijssen
Elisa Cirillo
Elisa
Cirillo
Eric E. Smeets
Eric E.
Smeets
Nasim Bahram Sangani
Nasim Bahram
Sangani
Chris T. Evelo
Chris
T. Evelo
Leopold M.G. Curfs
Leopold M.G.
Curfs
Integrated analysis of human transcriptome data for Rett syndrome finds a network of involved genes
Taylor & Francis Group
2019
Rett syndrome
rare diseases
neurological disorder
bioinformatics
pathway analysis
2019-03-25 10:02:10
Dataset
https://tandf.figshare.com/articles/dataset/Integrated_analysis_of_human_transcriptome_data_for_Rett_syndrome_finds_a_network_of_involved_genes/7886671
<p><b>Objectives:</b> Rett syndrome (RTT) is a rare disorder causing severe intellectual and physical disability. The cause is a mutation in the gene coding for the methyl-CpG binding protein 2 (MECP2), a multifunctional regulator protein. Purpose of the study was integration and investigation of multiple gene expression profiles in human cells with impaired <i>MECP2</i> gene to obtain a robust, data-driven insight in molecular disease mechanisms.</p> <p><b>Methods:</b> Information about changed gene expression was extracted from five previously published studies, integrated and the resulting differentially expressed genes were analysed using overrepresentation analysis of biological pathways and gene ontology, and network analysis.</p> <p><b>Results:</b> We identified a set of genes, which are significantly changed not in all but several transcriptomics datasets and were not mentioned in the context of RTT before. We found that these genes are involved in several processes and molecular pathways known to be affected in RTT. Integrating transcription factors we identified a possible link how MECP2 regulates cytoskeleton organisation via MEF2C and CAPG.</p> <p><b>Conclusions:</b> Integrative analysis of omics data and prior knowledge databases is a powerful approach to identify links between mutation and phenotype especially in rare disease research where little data is available.</p>