Neuronal activity-regulated gene transcription underlies plasticity-dependent changes in the molecular composition and structure of neurons. A large number of genes regulated by different neuronal plasticity inducing pathways have been identified, but altered gene expression levels represent only part of the complexity of the activity-regulated transcriptional program. Alternative splicing, the differential inclusion and exclusion of exonic sequence in mRNA, is an additional mechanism that is thought to define the activity-dependent transcriptome. Here, we present a genome wide microarray-based survey to identify exons with increased expression levels at 1, 4 or 8 h following neuronal activity in the murine hippocampus provoked by generalized seizures. We used two different bioinformatics approaches to identify alternative activity-induced exon usage and to predict alternative splicing, ANOSVA (ANalysis Of Splicing VAriation) which we here adjusted to accommodate data from different time points and FIRMA (Finding Isoforms using Robust Multichip Analysis). RNA sequencing, in situ hybridization and reverse transcription PCR validate selected activity-dependent splicing events of previously described and so far undescribed activity-regulated transcripts, including Homer1a, Homer1d, Ania3, Errfi1, Inhba, Dclk1, Rcan1, Cda, Tpm1 and Krt75. Taken together, our survey significantly adds to the comprehensive understanding of the complex activity-dependent neuronal transcriptomic signature. In addition, we provide data sets that will serve as rich resources for future comparative expression analyses.

中文翻译：

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神经元活动调节替代外显子使用

神经元活动调节的基因转录是神经元分子组成和结构的可塑性依赖性变化的基础。已经鉴定了大量由不同神经元可塑性诱导途径调节的基因，但改变的基因表达水平仅代表活性调节转录程序的复杂性的一部分。选择性剪接，即 mRNA 中外显子序列的差异包含和排除，是另一种被认为定义活性依赖性转录组的机制。在这里，我们提出了一项基于全基因组微阵列的调查，以确定在全身性癫痫发作引起的小鼠海马神经元活动后 1、4 或 8 小时表达水平增加的外显子。我们使用了两种不同的生物信息学方法来识别替代活性诱导的外显子使用并预测替代剪接，ANOSVA（剪接变异分析）我们在这里调整以适应来自不同时间点的数据和 FIRMA（使用稳健多芯片分析寻找同种型）。RNA 测序、原位杂交和逆转录 PCR 验证了先前描述的和迄今为止未描述的活性调节转录本的选定活性依赖性剪接事件，包括 Homer1a、Homer1d、Ania3、Errfi1、Inhba、Dclk1、Rcan1、Cda、Tpm1 和 Krt75。总之，我们的调查显着增加了对复杂的活动依赖性神经元转录组特征的全面理解。此外，我们提供的数据集将作为未来比较表达分析的丰富资源。