Neuronal activity regulates alternative exon usage

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.Projekt DEALPeer Reviewe

Genome-Wide Profiling of the Activity-Dependent Hippocampal Transcriptome

<div><p>Activity-dependent gene expression is central for sculpting neuronal connectivity in the brain. Despite the importance for synaptic plasticity, a comprehensive analysis of the temporal changes in the transcriptomic response to neuronal activity is lacking. In a genome wide survey we identified genes that were induced at 1, 4, 8, or 24 hours following neuronal activity in the hippocampus. According to their distinct expression kinetics we assigned these genes to five clusters, each containing approximately 200 genes. Using in situ hybridizations the regulated expression of 24 genes was validated. Apart from known activity-dependent genes our study reveals a large number of unknown induced genes with distinct expression kinetics. Among these we identified several genes with complex temporal expression patterns. Furthermore, our study provides examples for activity-induced exon switching in the coding region of genes and activity-induced alternative splicing of the 3′-UTR. One example is Zwint. In contrast to the constitutively expressed variant, the induced Zwint transcript harbors multiple regulatory elements in the 3′-UTR. Taken together, our study provides a comprehensive analysis of the transcriptomic response to neuronal activity and sheds new light on expression kinetics and alternative splicing events.</p></div

Genes used for <i>in situ</i> hybridizations, respective nucleotides of templates and accession numbers.

<p>Genes used for <i>in situ</i> hybridizations, respective nucleotides of templates and accession numbers.</p

Examples of the temporal and spatial expression of activity-regulated genes of cluster 4 (A) and cluster 5 (B).

<p>(Left) Plots of the time course and the ratio of induction based on the microarray analyses. Shown are expression profiles of genes represented by one or more microarray probe sets. A bold line indicates the microarray probe set that corresponds to the probe used in the corresponding <i>in situ</i> hybridization analysis. (Right) Autoradiograms of coronal sections of mouse brains at different time points following seizure. Radioactive <i>in situ</i> hybridizations of sections were conducted in parallel on one glass slide using gene specific antisense RNA probes.</p

Tumour necrosis factor α-converting enzyme mediates ectodomain shedding of Vps10p-domain receptor family members

Several transmembrane molecules are cleaved at juxtamembrane extracellular sites leading to shedding of ectodomains. We analysed shedding of members of the Vps10p-D (Vps10p domain; where Vps is vacuolar protein sorting) family of neuronal type-I receptors with partially overlapping functions, and additional proteolytic events initiated by the shedding. When transfected into CHO (Chinese-hamster ovary) cells (CHO-K1), sorCS1a–sorCS1c isoforms were shed at high rates (∼0.61%·min(−1)) that were increased approx. 3-fold upon stimulation with phorbol ester. sorCS1c identified in the cultured neuroblastoma cell line SH-SY5Y was shed similarly. In CHO-K1 transfectants, constitutive and stimulated shedding of sorCS3 also occurred at high rates (0.29% and 1.03%·min(−1)). By comparison, constitutive and stimulated shedding of sorLA occurred at somewhat lower rates (0.07% and 0.48%·min(−1)), whereas sorCS2 and sortilin were shed at very low rates even when stimulated (∼0.01%·min(−1)). Except for sorCS2, shedding of the receptors was dramatically reduced in mutant CHO cells (CHO-M2) devoid of active TACE (tumour necrosis factor α-converting enzyme), demonstrating that this enzyme accounts for most sheddase activity. The release of sorCS1 and sorLA ectodomains initiated rapid cleavage of the membrane-tethered C-terminal stubs that accumulated only in the presence of γ-secretase inhibitors. Purified shed sorLA bound several ligands similarly to the entire luminal domain of the receptor, including PDGF-BB (platelet-derived growth factor-BB) and amyloid-β precursor protein. In addition, PDGF-BB also bound to the luminal domains of sorCS1 and sorCS3. The results suggest that ectodomains shed from a subset of Vps10p-D receptors can function as carrier proteins

Gene expression profiles induced by neuronal activity and a functional categorization of identified genes.

<p><b>A,</b> Heat map providing an overview of different time courses of expression induced by neuronal activity. Transcripts were clustered into five groups according to their time course of expression. Red indicates upregulation, green indicates downregulation. <b>B,</b> Categorization of biological functions of the genes belonging to the identified clusters according to the Gene Ontology database. The fraction of genes of a classified function is shown in yellow.</p

Expression profiles of genes assigned to one cluster.

<p>Log ratios were normalized by the Eukledian distance to 0. Black lines show the average normalized log ration. Dark and light grey areas indicate one and two standard deviations, respectively. Genes used for validation experiments are highlighted in color. The 254 transcripts of cluster 1 showed strong induction 1</p

Correlation of activity induced genes.

<p><b>A,</b> Two-dimensional correlation plot of activity induced gene expression levels. Six independent experiments were conducted for the 0 h control time point and three independent experiments for the time points 1, 4, 8, and 24 h. Hippocampal RNA of one mouse was hybridized to one DNA microarray. The plot indicates the correlation of expression profiles of all induced genes compared in control animals and in animals at indicated time points after the onset of kainic acid induced seizures. Correlation coefficients range from 0.97 (bright yellow color code) to 0.99 (red color code). Arrays were clustered using average linkage cluster analysis with a correlation metric distance. <b>B</b>, Correlation of genes induced by seizure in mice of different genetic backgrounds. Hippocampal RNA from control mice and mice sacrificed 4 h after the onset of seizure was analyzed. RNA from one animal (n = 3) was hybridized to one microarray and genes induced 4 h after onset of seizures in C57Bl/6J and hybrid 129/Sv×C57Bl/6J mice were compared. Logarithmic fold changes (Log-FC) are shown. Correlation coefficient r = 0.6 is indicated.</p

Specific induction of a splice variant of Zwint.

<p><b>A,</b> Two alternative splice variants of Zwint are expressed in the mouse. Expression profiles of both variants observed by microarray analysis (left) and by <i>in situ</i> hybridization (right) are shown. The plots of the microarray probe sets corresponding to the fragment used for <i>in situ</i> hybridization are presented as bold lines. Autoradiograms of coronal sections of mice of different time points following seizure. Radioactive <i>in situ</i> hybridizations of sections were conducted in parallel on one glass slide using Zwint splice variant specific antisense RNA probes. <b>B,</b> Genomic organization of the Zwint gene. Shared exons are depicted as black boxes, alternatively used 3′-UTRs as white boxes. Stars indicate stop codons, black lines the RNA probes used for <i>in situ</i> hybridization (ish) and microarray probe sets. Exon sizes and distances are not to scale. <b>C, D,</b> Nucleotide sequence of the last exon of Zwint splice variant 1 <b>(C)</b> and splice variant 2 <b>(D)</b>. Putative regulatory elements are indicated. AU-rich elements (AUUUA) in red, U-rich motifs (UUUAAA) in black, K-boxes in green, UUGUUGG(G) motifs in yellow, polyadenylation signals in blue.</p