Laboratory of Molecular Neuro-Oncology, Howard Hughes Medical Institute, The Rockefeller University, 1230 York Avenue, New York, NY 10021, USA.
Science. 2010 Jul 23;329(5990):439-43. doi: 10.1126/science.1191150. Epub 2010 Jun 17.
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 approximately 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 可变剪接的调控对于产生生物多样性至关重要。尽管新兴的全基因组技术可用于研究 RNA 的复杂性，但尚未定义可靠和全面的 RNA 调控网络。在这里，我们使用贝叶斯网络来概率建模各种数据集，并预测特定调节剂的靶网络。我们应用此策略鉴定了大约 700 个在小鼠脑中由神经元特异性因子 Nova 直接调控的可变剪接事件，整合了 RNA 结合数据、剪接微阵列数据、Nova 结合基序和进化特征。由此产生的综合网络揭示了 Nova 和神经元剪接因子 Fox 的组合调控、磷酸化和剪接之间的相互作用，以及与神经疾病的潜在联系。因此，我们开发了一种全面的方法来理解哺乳动物 RNA 在系统水平上的调控。
