Abstracts

Rationale: Epilepsy is a neurological disorder with complex etiologies and genetic architecture. There are no treatments to prevent epilepsy, and roughly 30% of epilepsies are intractable to current antiepileptic medications. Uncontrolled seizures also increase the risk of sudden unexpected death in epilepsy (SUDEP), a poorly understood fatal complication of epilepsy. New transformative treatments for epilepsy could be developed by understanding the genetic associations conferring risk or protective effects. Animal models have a critical role in understanding the pathophysiology of epilepsy. Most existing animal models of complex diseases such as epilepsy are limited because they do not reflect the high level of genetic diversity found in the human population. The Collaborative Cross (CC) population is a genetically diverse recombinant inbred panel derived from eight fully inbred strains that has ~42 million segregating genetic variants. In addition, whole-genome sequences have been established for each individual CC strain, and other genomic tools have been developed to enable the identification of genetic variants from mapping studies. The CC has been used to model complex traits such as behavior, cancer, and infectious disease susceptibility. Here, we took advantage of the immense genetic diversity available in the CC to study epilepsy. Methods: We first evaluated seizure-related phenotypes in a sampling of 35 CC inbred strains in addition to canonical seizure resistant (i.e. C57BL/6J) and susceptible (i.e. DBA/2J) inbred mice using the flurothyl-induced seizure and kindling paradigm. We then created a ~300 F2 population of extreme seizure susceptibility and performed QTL mapping to identify genomic regions associated with seizure sensitivity. To identify candidate genes by interrogating the allelic effects of genes within QTL, we performed gene expression analysis using RNA sequencing. Using whole-genome sequence from CC as well as the reference C57BL/6J sequence, we were able to identify founder haplotype and genetic variation in candidate genes. Results: We measured multiple epilepsy traits in 35 CC strains and identified new mouse models with extreme epileptic responses that include but are not limited to 1) CC strains with extreme seizure susceptibility/resistance; 2) two CC strains that exhibit resistance to seizure propagation; 3) CC strains with complete resistance to epileptogenesis as measured by a lack of kindling; 4) four CC strains that exhibit SUDEP (sudden unexpected death in epilepsy), likely through independent mechanisms. We then performed QTL mapping in the F2 intercrosses of seizure susceptible and resistant strains and identified one known and seven novel loci associated with seizure sensitivity. We combined whole-genome sequencing and hippocampal gene expression to pinpoint biologically plausible candidate genes (e.g. Gabra2) and variants associated with seizure sensitivity. Conclusions: We demonstrate a highly reliable and repeatable seizure induction paradigm, as well as the implementation and design of a genetic mapping population. We also show the power of our approach by using the CC and transcriptomic sequence resources to identify several QTL (both novel and previously identified), candidate genes, and candidate variants associated with seizure sensitivity. These resources provide a powerful toolbox for identifying new genes, and hence new therapeutic targets, linked to seizure susceptibility, seizure propagation, epileptogenesis, and SUDEP. Funding: Citizens United for Research in Epilepsy Taking Flight Award to Bin Gu