Roser Corominas, Xinping Yang, Guan Ning Lin, Shuli Kang, Yun Shen, Lila Ghamsari, Martin Broly, Maria Rodriguez, Stanley Tam, Shelly A. Wanamaker, Changyu Fan, Song Yi, Murat Tasan, Irma Lemmens, Xingyan Kuang, Nan Zhao, Dheeraj Malhotra, Jacob J. Michaelson, Vladimir Vacic, Michael A. Calderwood, Frederick P. Roth, Jan Tavernier, Steve Horvath, Kourosh Salehi-Ashtiani, Dmitry Korkin, Jonathan Sebat, David E. Hill, Tong Hao, Marc Vidal, Lilia M. Iakoucheva

Increased risk for autism spectrum disorders (ASD) is attributed to hundreds of genetic loci. The convergence of ASD variants have been investigated using various approaches, including protein interactions extracted from the published literature. However, these datasets are frequently incomplete, carry biases and are limited to interactions of a single splicing isoform, which may not be expressed in the disease-relevant tissue. Here we introduce a new interactome mapping approach by experimentally identifying interactions between brain-expressed alternatively spliced variants of ASD risk factors. The Autism Spliceform Interaction Network reveals that almost half of the detected interactions and about 30% of the newly identified interacting partners represent contribution from splicing variants, emphasizing the importance of isoform networks. Isoform interactions greatly contribute to establishing direct physical connections between proteins from the de novo autism CNVs. Our findings demonstrate the critical role of spliceform networks for translating genetic knowledge into a better understanding of human diseases.