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Poster SSBP 2019 Birmingham - The pathways of Rett syndrome revealed by different methods for pathway and network analysis

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Version 2 2019-09-09, 14:04
Version 1 2019-09-09, 14:03
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posted on 2019-09-09, 14:04 authored by Friederike EhrhartFriederike Ehrhart, Martina KutmonMartina Kutmon, Egon WillighagenEgon Willighagen
Background: Rett syndrome is a rare genetic disorder caused by a loss of function mutation in MECP2, an important regulator of gene expression especially, but not only, in neurons. Due to the multi-functionality of MECP2 there are many downstream pathways which are interesting for understanding the pathophysiology of Rett syndrome, and allowing a search for drug targets. Using omics data and analysing it in terms of biological pathways and networks allows a holistic view of the influence of MECP2. In the past years several methods have been developed, which we will demonstrate here.
Methods: Transcriptomics microarray data was collected from several previously published studies of which differentially expressed gene lists were extracted. Overrepresentation analysis of biological pathways was done in PathVisio software using the pathway database WikiPathways (including Reactome pathways). For active module analysis, first, the whole WikiPathways database was used to construct one large network and, second, active modules based on differently expressed genes were identified using the Cytoscape app jActiveModules. For comparison, gene ontology analysis was performed using GO_Elite software.
Results: The integrative approach, using different pathway and network analysis methods to analyse transcriptomics datasets, revealed several downstream pathways of Rett syndrome. The different methods showed a clear overlap in ability to identify disease affected processes in inflammation, neuronal development, neuronal function, and translation. Pathway analysis was less effective to show affected processes in translation, which were identified clearly by gene ontology and active modules analysis. This is possibly due to a limited number of available pathways focussing on translation related processes.
Conclusion: Although the details of identified pathways and active modules in the networks differed in each method used, the different methods showed a significant overlap in identification of pathways and processes which are clearly linked to the Rett syndrome phenotype.

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