Integrative modeling defines the Nova splicing-regulatory network and its combinatorial controls: Exon array data

The control of RNA alternative splicing is critical for generating biological diversity. Despite emerging genome-wide technologies to study RNA complexity, reliable and comprehensive RNA-regulatory networks have not been defined. Here we used Bayesian networks to probabilistically model diverse datasets and predict the target networks of specific regulators. We applied this strategy to identify ~700 alternative splicing events directly regulated by the neuron-specific factor Nova in the mouse brain, integrating RNA-binding data, splicing microarray data, Nova-binding motifs, and evolutionary signatures. The resulting integrative network revealed combinatorial regulation by Nova and the neuronal splicing factor Fox, interplay between phosphorylation and splicing, and potential links to neurologic disease. Thus we have developed a general approach to understanding mammalian RNA regulation at the systems level. RNA from the whole brain or spinal cord of 4 wild type and 4 Nova1/2 double KO (dKO) E18.5 CD1 mice. One array per biological replicate.