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Science 329 (5990): 439-443

Copyright © 2010 by the American Association for the Advancement of Science

Integrative Modeling Defines the Nova Splicing-Regulatory Network and Its Combinatorial Controls

Chaolin Zhang,* Maria A. Frias, Aldo Mele, Matteo Ruggiu, Taesun Eom, Christina B. Marney, Huidong Wang, Donny D. Licatalosi, John J. Fak, Robert B. Darnell*

Abstract: 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 data sets 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.

Laboratory of Molecular Neuro-Oncology, Howard Hughes Medical Institute, The Rockefeller University, 1230 York Avenue, New York, NY 10021, USA.

* To whom correspondence should be addressed. E-mail: czhang{at}rockefeller.edu (C.Z.); darnelr{at}rockefeller.edu (R.B.D.)

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