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. 2015 Oct 1;9:351.
doi: 10.3389/fnins.2015.00351. eCollection 2015.

Dynamic Expression of Long Noncoding RNAs and Repeat Elements in Synaptic Plasticity

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Free PMC article

Dynamic Expression of Long Noncoding RNAs and Repeat Elements in Synaptic Plasticity

Jesper L V Maag et al. Front Neurosci. .
Free PMC article

Erratum in

Abstract

Long-term potentiation (LTP) of synaptic transmission is recognized as a cellular mechanism for learning and memory storage. Although de novo gene transcription is known to be required in the formation of stable LTP, the molecular mechanisms underlying synaptic plasticity remain elusive. Noncoding RNAs have emerged as major regulatory molecules that are abundantly and specifically expressed in the mammalian brain. By combining RNA-seq analysis with LTP induction in the dentate gyrus of live rats, we provide the first global transcriptomic analysis of synaptic plasticity in the adult brain. Expression profiles of mRNAs and long noncoding RNAs (lncRNAs) were obtained at 30 min, 2 and 5 h after high-frequency stimulation of the perforant pathway. The temporal analysis revealed dynamic expression profiles of lncRNAs with many positively, and highly, correlated to protein-coding genes with known roles in synaptic plasticity, suggesting their possible involvement in LTP. In light of observations suggesting a role for retrotransposons in brain function, we examined the expression of various classes of repeat elements. Our analysis identifies dynamic regulation of LINE1 and SINE retrotransposons, and extensive regulation of tRNA. These experiments reveal a hitherto unknown complexity of gene expression in long-term synaptic plasticity involving the dynamic regulation of lncRNAs and repeat elements. These findings provide a broader foundation for elucidating the transcriptional and epigenetic regulation of synaptic plasticity in both the healthy brain and in neurodegenerative and neuropsychiatric disorders.

Keywords: LTP (long term potentiation); long noncoding RNA (lncRNA); rat brain; repeat elements; retrotransposons; synaptic plasticity (LTP/LTD); time-series data.

Figures

Figure 1
Figure 1
Time dependent high frequency stimulation is the main driver of variation between dentate gyrus samples in vivo. (A) (top) Location of the hippocampus in both hemispheres of the brain. (bottom) Transverse section of the rat brain showing the hippocampal trisynaptic circuitry and the position of the stimulation electrode at the medial performant path and the registration electrode in the middle molecular layer of the dentate gyrus. (B) (I–III) Time course plot showing changes in the medial performant path-evoked fEPSP slope expressed as percentage of baseline. Experimental groups received HFS alone, HFS in the presence of NMDA receptor antagonist CPP, or only baseline test stimuli (BTS). CPP was injected IP at the dose of 10 mg/ml, 90 min prior to HFS. Dentate gyrus tissue was collected at the indicated time points post-HFS (I) 30min-HFS (II) 2h-HFS, 2h-CPP + HFS, 2h-BTS (III) 5h-HFS. Values are means (±s.e.m.) (IV) Quantitative PCR was used to validate the expression of the IEG Arc mRNA in the dentate gyrus (treated/control). PCR was performed in triplicate and normalized to the geometric mean of three housekeeping genes. Values are means (±s.e.m.), n = 5 in all groups except BLS and 30 min-HFS n = 4, * denotes p < 0.05, **denotes p < 0.01; students paired t-test. (C) PCA plot showing the difference between the samples for the first two compartments with the amount of variation explained in the axis. Circles represent the stimulated dentate gyrus (LDG) while triangles represent the unstimulated contralateral side (RDG). The color of each time point is matched for ipsilateral (light) and contralateral (dark) side of the HFS hippocampus.
Figure 2
Figure 2
RNA-seq reveals time dependent increase in transcription after high frequency stimulation. (A) (Top) The number of differentially expressed genes comparing the experimental (LDG) and the contralateral side (RDG) of the dentate gyrus as either upregulated (positive) or downregulated (negative) with number of differentially expressed genes in each bar (|log2 FC|>1 and FDR < 0.05). (Bottom) Representation of Ensembl classes for each differentially expressed Ensemble gene. Classes were taken from the Ensembl gtf file. (B) Intersection of differentially expressed genes between the different time points, upregulated (left), and downregulated (right). Expression of Ensembl genes (C) and transcription factors (D) with greatest fold-change (|log2FC|>4 for genes and |log2FC|>2 for TFs) at any time point between the experimental (LDG) and control (RDG). Left key (blue/yellow/red) describes the fold-change value (log2 LDG/RDG), middle key (white/pink) denotes the expression values (log2 cpm), right key (green/white) represents the significance of the differential expression (FDR, n = 3).
Figure 3
Figure 3
De novo transcriptome assembly identifies novel differentially-expressed lncRNAs after high frequency stimulation. (A) (Top left) Frequency of differentially expressed lncRNAs and direction of change post-stimulation with positive values indicating upregulated lncRNAs and negative indicating downregulated lncRNAs. (bottom) Class of lncRNAs that display differential expression for each time point. (top right) Intersection of differentially expressed lncRNA between each time point. (B) Conservation of the novel differentially expressed lncRNAs (blue) compared to Ensembl miRNA (red), protein-coding genes (green). (random 71 genes taken from each group). (C) Temporal expression of novel lncRNAs between the brain hemispheres. Left key (blue/yellow/red) describes the log2FC value, middle key (white/pink) denotes the expression values (log2 cpm), right key (green/white) represents the significance of the differential expression (FDR, n = 3). (D) K-means clustering of the temporal profile for the differentially expressed lncRNAs divided into four individual clusters.
Figure 4
Figure 4
Expression correlation analysis of lncRNAs with Ensembl genes. (A) Correlation matrix between all differentially expressed lncRNAs (y-axis divided into their respective class) and differentially expressed Ensembl genes (x-axis). Pearson correlation was used to determine degree of correlation. (B) Classification of all differentially expressed novel lncRNA with a coding potential less than zero (Antisense: overlapping a protein-coding gene on the antisense, Bidirectional: < 1 kb from the TSS of the protein-coding gene on the opposite strand, Intergenic: >1 kb from the nearest protein-coding gene). (C) Frequencies of classes of differentially expressed lncRNAs that had highly correlated expression with a protein-coding neighbor (p < 0.05). (D) Examples of neighboring lncRNA-mRNA pairs (blue, red respectively) that had highly correlated expression. Pearson correlation coefficients (R) are indicated.
Figure 5
Figure 5
Novel rat lncRNAs correlated to highly differentially expressed Ensembl genes and Arc mRNA. The Ensembl genes chosen were those with the lowest FDR value for 2 and 5 h (no lncRNAs were identified at 30 min that showed high correlation to any Ensembl genes), and Arc. LncRNA with a neighboring Ensembl gene (from Figure 4C) were excluded from this analysis. The top 5 correlated lncRNAs with a p < 0.05 were plotted. Pearson correlation values are shown to the right of each line. Ensembl genes are colored brown and assigned a Pearson correlation value of 1, while the lncRNA are color-coded in each graph.
Figure 6
Figure 6
Expression profiling of repeat elements reveals differentially expressed repeat types after high frequency stimulation. (A) Frequency of significantly differentially expressed (FDR < 0.05) repeat types aggregated to their respective repeat class between LDG and RDG for naïve rats and for each time point. (B) Differential expression of different repeat types (excluding simple repeats, tRNA and low complexity repeat types) between each time point with significantly differentially expressed (FDR < 0.05) repeats colored red. (C) Expression correlation of Arc, Dbc1, Pim1, and Pmepa1 with different repeat types as in Figure 5, excluding simple repeats, tRNA, and low complexity repeat types.

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