Identification of shared transcriptional profiles with three high-confidence autism mouse models
- Awarded: 2016
- Award Type: Research
- Award #: 393316
Genetic risks for autism are diverse and encompass mutations and copy number variations in hundreds of genes. However, autism is diagnosed through the evaluation of a shared set of symptoms that include social interaction deficits and repetitive or restrictive behaviors. Transcriptional studies suggest autism can also be defined by a shared molecular pathology1,2. This pathology includes reduced expression of genes involved in synaptic transmission and elevated expression of microglial genes. Other shared phenotypes in individuals with autism include cortical overgrowth and increased dendritic spine density. These clinical findings raise the possibility that molecular, cellular and behavioral phenotypes might be shared across mouse models of autism. However, animal models harboring high-confidence autism gene mutations have yet to be examined, largely because such risk variants have only recently been discovered.
In unpublished work, Mark Zylka and his colleagues generated genetically precise mouse models, mimicking loss-of-function or missense mutations found in the high-confidence autism candidate genes CHD8, CUL3 and UBE3A. This collection of autism mouse models will be studied in parallel, under equivalent experimental conditions. The researchers hypothesize that these mice can be used to identify shared transcriptional phenotypes, as well as phenotypes that are unique to each line. They will explore this hypothesis by applying the methods of RNA-seq and Drop-seq to different brain areas of these mouse models. This research will advance these three mouse lines as autism models and may help to discover novel drug targets for common phenotypes.