Coding and small non-coding transcriptional landscape of tuberous sclerosis complex cortical tubers: implications for pathophysiology and treatment

Abstract

Tuberous Sclerosis Complex (TSC) is a rare genetic disorder that results from a mutation in the TSC1 or TSC2 genes leading to constitutive activation of the mechanistic target of rapamycin complex 1 (mTORC1). TSC is associated with autism, intellectual disability and severe epilepsy. Cortical tubers are believed to represent the neuropathological substrates of these disabling manifestations in TSC. In the presented study we used high-throughput RNA sequencing in combination with systems-based computational approaches to investigate the complexity of the TSC molecular network. Overall we detected 438 differentially expressed genes and 991 differentially expressed small non-coding RNAs in cortical tubers compared to autopsy control brain tissue. We observed increased expression of genes associated with inflammatory, innate and adaptive immune responses. In contrast, we observed a down-regulation of genes associated with neurogenesis and glutamate receptor signaling. MicroRNAs represented the largest class of over-expressed small non-coding RNA species in tubers. In particular, our analysis revealed that the miR-34 family (including miR-34a, miR-34b and miR-34c) was significantly over-expressed. Functional studies demonstrated the ability of miR-34b to modulate neurite outgrowth in mouse primary hippocampal neuronal cultures. This study provides new insights into the TSC transcriptomic network along with the identification of potential new treatment targets.

Figure 1

The transcriptome of tuberous sclerosis complex (TSC) cortical tubers determined by using RNA-Seq data (a) Volcano plot showing differential expression of genes between TSC tubers (n = 12) and post-mortem control cortex (n = 10). A total of 269 mRNAs were found to be over-expressed and 169 under-expressed in TSC tubers compared to control cortex tissue (b) Ingenuity pathway analysis showing major pathways enriched for over-expressed genes in TSC tubers (c) Heat map showing genes of the complement system enriched in TSC tubers compared to control cortex. All p-values are BH adjusted.

Figure 2

Small RNA landscape of TSC cortical tubers determined by using small RNA-seq data. (a) Volcano plot showing differential expression of small RNAs between TSC tubers and post-mortem control cortex. A total of 932 small RNAs were found to be under-expressed and 59 over-expressed in TSC tubers compared to control cortex tissue (b) Distribution of various classes of small RNAs among the over- and under-expressed transcripts in TSC cortical tubers (c) Heat map showing the expression of the 48 over-expressed and top 10 under-expressed miRNAs in TSC tubers and control cortex.

Figure 3

Co-expression network modules and miRNA target predictions. (a) Unsupervised weighted gene co-expression network analysis (WGCNA) showing over-represented gene ontology terms in TSC patients. (b) Overlay of fold expression (log2 tranformed) of differentially expressed genes between TSC patients and controls on the gene co-expression network. Over-expressed genes predominantly overlap with the innate immune response and extracellular matrix organization modules whereas under-expressed genes overlap with neurogenesis and glutamate receptor signaling module. (c) Graphical representation of over- and under-expressed genes enriched within the over-represented co-expression network modules in TSC patients. Over-expressed genes are predominantly associated with the innate immune response and extracellular matrix organization modules whereas under-expressed genes are predominantly associated with neurogenesis and glutamate receptor signaling modules. Only modules that harboured significantly different genes are illustrated. (d) The miR-34 family (miR-34A, miR-34B and miR-34C) target multiple targets in the neurogenesis and glutamate receptor signaling modules.

Figure 4

In situ hybridization of miR-34a-5p and miR-34b-5p in Tuberous Sclerosis Complex (TSC) cortical tubers. Panels a-d: miR-34a-5p. Control cortex (a) shows moderate expression of miR-34a-5p in few neuronal cells (arrows); not detectable expression is observed in control white matter (c). Panels b and d (TSC) show strong expression of miR-34a-5p within the dysplastic region with several positive dysmorphic neurons (arrows in b) and glial cells (arrowheads in b,d); insert in b: miR-34b-5p in a NeuN positive cell; insert in d shows colocalization with GFAP. Expression of miR-34a-5p is also detected in giant cells within the tuber white matter (arrows in d). Panels e-h: miR-34b–5p. Control cortex (e) shows moderate expression of miR-34b-5p in neuronal cells (arrows); very low expression is observed in control white matter (g). Panels f and h (TSC) show expression of miR-34b-5p within the dysplastic region with several positive dysmorphic neurons [arrows; insert in f: miR-34b-5p in a NeuN positive cell] and glial cells [arrowheads in f and insert (a) in h; insert (b) in h shows colocalization with GFAP]; arrow in h shows a positive giant cell within the tuber white matter. Scale bar in a: (a–g), 80 µm; (h), 40 µm. [arrows in h and insert (a) in h, white matter]. Scale bar in a: (a,e,f): 160 µm; (b–d,g,h) 80 µm.

Figure 5

Neurite outgrowth modulated by transfection with miR-34b-5p in mouse hippocampal neurons (a,b) Representative images of mouse hippocampal dissociated neurons cotransfected with GFP vector and mimics for miR-34b-5p (miR-34b) or NC-1 (negative control; Scr); Scale bar, 100 µm. (c–f) Graphical representation of neurite outgrowth analysis using the NeuroMath software showing (c) total length of neurites (d) total number of neurites (e) cell area (f) longest neurite and (g) total number of branches. Student’s t-test: *p < 0.05; n = 3 experiments, 3 independent transfections each experiment.