An expanded repertoire of brain microexons is directly impacted by autism-associated genetic variation

By developing a machine learning model that predicts neuronally-spliced microexons from genome sequence, we have defined critical regulatory elements surrounding the expanded repertoire of microexons. Using this model, we identify rare and common variants that are predicted to alter microexon splicing patterns in approximately 30% of ASD-affected individuals, relative to their unaffected siblings, with rare variants having the strongest impact.

These variants are mostly detected in idiopathic individuals and converge on a subset of microexons concentrated in synaptic and additional ASD-linked genes, but also in genes not previously linked to autism. Our results collectively define an expanded repertoire of neuronal microexons, delineate their regulatory code, and pinpoint genetic variants that impact their splicing, with implications for the disruption of functions central to neuronal biology and brain disorders.