De novo structural variants in autism spectrum disorder disrupt distal regulatory interactions of neuronal genes

Computational prediction of the effect of structural variants on three-dimensional chromatin folding and on contacts between promoters and distal regulatory elements.

Three-dimensional genome organization drives gene regulation, and its disruption by a structural variant can separate a gene from its distal regulatory elements, for instance when topologically associating domains merge after a boundary deletion. Because experimentally testing large numbers of structural variants is prohibitive in time and cost, the authors propose a computational approach that predicts their impact on genome folding in order to prioritise causal hypotheses. They develop a weighted scoring method measuring chromatin contact changes specifically at regions of interest, promoters or regulatory elements, implemented in the SuPreMo-Akita software. Applied to hundreds of de novo structural variants from autism spectrum disorder individuals and their unaffected siblings, the method shows that putative cis-regulatory element interactions are more disrupted in probands than in siblings. The top-ranked locus was validated in isogenic excitatory neurons with and without the de novo variant, confirming the predicted disruption of chromatin contacts.

Synthesis written by Geno'X. For the full original abstract, please refer to the source publication.

The practical value here is triage: a non-coding structural variant is almost always left as a variant of uncertain significance, for lack of any criterion to rank candidates. Ranking by predicted disruption of promoter-to-regulatory-element contacts, then validating the top hit in isogenic neurons, is a scheme that transfers to other tissues. The signal is nonetheless demonstrated at the level of a proband group compared with their siblings, not at the level of an individual patient: the tool points to a functional hypothesis to test, it does not classify a variant on its own.

Analysis by Dr Thibaut Benquey