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Identification of pathways and genetic drivers for childhood epileptic encephalopathies by integrating whole-exome sequencing and gene network approaches
Identification of pathways and genetic drivers for.. (IGENEE)
Identification of pathways and genetic drivers for childhood epileptic encephalopathies by integrating whole-exome sequencing and gene network approaches
(IGENEE)
Date du début: 1 sept. 2014,
Date de fin: 31 août 2016
PROJET
TERMINÉ
The objective of the iGENEE project (Integrated Genetic Networks for Epileptic Encephalopathies) is the identification of pathways and genetic drivers for childhood epileptic encephalopathies (EE) by integrating whole-exome sequencing and gene network approaches. It will be supervised by Dr Petretto, Head of the Integrative Genomics and Medicine Group at the MRC Institute of Clinical Sciences, and co-supervised by Dr Johnson, Deputy Head of the Centre for Clinical Translation of Brain Sciences and member of the Epi4K Consortium, both at Imperial College London. I will analyse exome-sequence data generated by the Epi4K/EPGP Consortium in patients with classical EE (n=264 probands) and their parents. Initial analyses identified Sanger-confirmed de novo Single Nucleotide Variants (SNV) in 9.5% of EE probands (Epi4K Consortium et al. Nature, 2013), but further analyses indicated that an additional 90 EE genes are present among the remaining 304 Sanger confirmed de novo SNVs in this patient cohort. To identify these causal mutations and the underlying convergent pathways for EE, I will utilize an integrated systems-level network approach as follows: (1) build gene co-expression networks from human and rodent brain transcriptomes to identify differentially expressed networks from various brain regions and at different stages of brain development; (2) connect gene networks to EE, by testing for enrichment of mutations using the Epi4K exome-sequence data; (3) investigate candidate networks enriched for EE susceptibility variants, by testing if the mutations disrupt the network at a protein-protein interaction level; (4) map key regulatory genes of the EE-associated co-expression networks, using Bayesian methods developed in Dr Petretto’s lab and (5) perform functional validation experiments of the regulatory genes identified. This project will provide an innovative, highly integrated approach to facilitate novel drug development for these devastating conditions.
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