Microexon code flags autism-linked variants predicted to alter RNA splicing

Nature describes a study that used machine learning to model how DNA sequences guide neuronal microexon splicing. Rare and ultrarare variants had the strongest predicted effects. Researchers found a subset of variants predicted to disrupt splicing associated with autism status across family cohorts, and tests in cultured human neurons showed altered splicing for representative variants.