New insights in Rett syndrome using pathway analysis for transcriptomics data

Friederike Ehrhart*, Susan Steinbusch - Coort, Elisa Cirillo, Eric Smeets, Chris T. Evelo, Leopold Curfs

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

4 Citations (Web of Science)

Abstract

The analysis of transcriptomics data is able to give an overview of cellular processes, but requires sophisticated bioinformatics tools and methods to identify the changes. Pathway analysis software, like PathVisio, captures the information about biological pathways from databases and brings this together with the experimental data to enable visualization and understanding of the underlying processes. Rett syndrome is a rare disease, but still one of the most abundant causes of intellectual disability in females. Cause of this neurological disorder is mutation of one single gene, the methyl-CpG-binding protein 2 (MECP2) gene. This gene is responsible for many steps in neuronal development and function. Although the genetic mutation and the clinical phenotype are well described, the molecular pathways linking them are not yet fully elucidated. In this study we demonstrate a workflow for the analysis of transcriptomics data to identify biological pathways and processes which are changed in a Mecp2 (-/y) mouse model.
Original languageEnglish
Pages (from-to)346-352
Number of pages7
JournalWiener Medizinische Wochenschrift
Volume166
Issue number11
DOIs
Publication statusPublished - Sep 2016

Keywords

  • Rett syndrome
  • Rare disease
  • Systems biology
  • Pathway analysis
  • Bioinformatics

Cite this