You are here: Home / Research / Upcoming Seminars / Prof. Evan E. Eichler, Ph.D. - "Understanding the genetics of autism using next-generation sequencing"

Prof. Evan E. Eichler, Ph.D. - "Understanding the genetics of autism using next-generation sequencing"

(Howard Hughes Medical Institute and Department of Genome Sciences, University of Washington School of Medicine. Seattle USA)
When Nov 22, 2016
from 12:00 PM to 01:30 PM
Where Tigem, Auditorium "Vesuvius"
Contact Name
Contact Phone 08119230659
Add event to calendar vCal
iCal
The discovery that de novo gene-disruptive single-nucleotide (SNVs) and copy number variants (CNVs) contribute to ~30% of the genetic basis of simplex autism has significantly moved the field of autism research forward. Targeted sequencing of ~218 candidate genes from >12,000 patients and controls has identified 85 genes where there is an excess of de novo gene-disruptive mutations in patients with developmental delay and autism. We also find that the pattern and severity of de novo mutations differs significantly between probands and unaffected siblings. We have used this information to target clustered and recurrent severe mutations proving pathogenicity for genes and identifying specific clinical subtypes of disease. Building on our earlier observation that private, inherited truncating SNV mutations in conserved genes are preferentially inherited from mothers to their autistic sons (OR = 1.14, p = 0.0002) , we have begun to explore noncoding genetic variation in autism genomes where large CNVs and de novo gene-disruptive mutations were not found. We find that probands show a modest but significant enrichment of de novo and private, disruptive mutations within fetal CNS DNase I hypersensitive sites (i.e., putative regulatory regions). This effect was only observed around genes previously associated with autism risk, including genes where dosage sensitivity has already been established by recurrent disruptive de novo protein-coding mutations. Next-generation exome and genome sequencing data provide a powerful path forward for understanding the genetic architecture of these diseases but the heterogeneity demands an unprecedented level of global cooperation and networking.
Filed under: