
van Slegtenhorst, M. et al. Identification of the tuberous sclerosis gene TSC1 on chromosome 9q34. Science
277, 805–808 (1997).
Curatolo, P., Bombardieri, R. & Jozwiak, S. Tuberous sclerosis. Lancet
372, 657–668, doi:10.1016/S0140-6736(08)61279-9 (2008).
Curatolo, P., Verdecchia, M. & Bombardieri, R. Tuberous sclerosis complex: a review of neurological aspects. European Journal of Paediatric Neurology
6, 15–23 (2002).
Bolton, P. F. Neuroepileptic correlates of autistic symptomatology in tuberous sclerosis. Mental Retardation & Developmental Disabilities Research Reviews
10, 126–131 (2004).
Curatolo, P., Moavero, R. & de Vries, P. J. Neurological and neuropsychiatric aspects of tuberous sclerosis complex. Lancet Neurol
14, 733–745, doi:10.1016/S1474-4422(15)00069-1 (2015).
Koh, S. et al. Epilepsy surgery in children with tuberous sclerosis complex: presurgical evaluation and outcome. Epilepsia
41, 1206–1213 (2000).
Weiner, H. L. et al. Epilepsy surgery in young children with tuberous sclerosis: results of a novel approach. Pediatrics
117, 1494–1502 (2006).
Bollo, R. J. et al. Epilepsy surgery and tuberous sclerosis complex: special considerations. Neurosurgical Focus
25, E13 (2008).
Curatolo, P. et al. The Role of mTOR Inhibitors in the Treatment of Patients with Tuberous Sclerosis Complex: Evidence-based and Expert Opinions. Drugs
76, 551–565, doi:10.1007/s40265-016-0552-9 (2016).
French, J. A. et al. Adjunctive everolimus therapy for treatment-resistant focal-onset seizures associated with tuberous sclerosis (EXIST-3): a phase 3, randomised, double-blind, placebo-controlled study. Lancet
388, 2153–2163, doi:10.1016/S0140-6736(16)31419-2 (2016).
Sahin, M. et al. Advances and Future Directions for Tuberous Sclerosis Complex Research: Recommendations From the 2015 Strategic Planning Conference. Pediatric Neurology
60, 1–12, doi:10.1016/j.pediatrneurol.2016.03.015 (2016).
White, R. et al. Selective alterations in glutamate and GABA receptor subunit mRNA expression in dysplastic neurons and giant cells of cortical tubers. Annals of Neurology
49, 67–78 (2001).
Kyin, R. et al. Differential cellular expression of neurotrophins in cortical tubers of the tuberous sclerosis complex. Am J Pathol
159, 1541–1554 (2001).
Boer, K. et al. Gene expression analysis of tuberous sclerosis complex cortical tubers reveals increased expression of adhesion and inflammatory factors. Brain Pathol
20, 704–719, doi:10.1111/j.1750-3639.2009.00341.x (2010).
Dombkowski, A. A. et al. Cortical Tubers: Windows into Dysregulation of Epilepsy Risk and Synaptic Signaling Genes by MicroRNAs. Cerebral Cortex
26, 1059–1071, doi:10.1093/cercor/bhu276 (2016).
Hitzemann, R. et al. Introduction to Sequencing the Brain Transcriptome. Brain Transcriptome
116, 1–19, doi:10.1016/B978-0-12-801105-8.00001-1 (2014).
Soon, W. W., Hariharan, M. & Snyder, M. P. High-throughput sequencing for biology and medicine. Molecular Systems Biology
9, doi:10.1038/msb.2012.61 (2013).
Parikshak, N. N., Gandal, M. J. & Geschwind, D. H. Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders. Nature Reviews Genetics
16, 441–458, doi:10.1038/nrg3934 (2015).
Gokoolparsadh, A. et al. Searching for convergent pathways in autism spectrum disorders: insights from human brain transcriptome studies. Cellular and Molecular Life Sciences
73, 4517–4530, doi:10.1007/s00018-016-2304-0 (2016).
Afonso-Grunz, F. & Muller, S. Principles of miRNA-mRNA interactions: beyond sequence complementarity. Cellular and Molecular Life Sciences
72, 3127–3141, doi:10.1007/s00018-015-1922-2 (2015).
Martens-Uzunova, E. S., Olvedy, M. & Jenster, G. Beyond microRNA – Novel RNAs derived from small non-coding RNA and their implication in cancer. Cancer Letters
340, 201–211, doi:10.1016/j.canlet.2012.11.058 (2013).
Veneziano, D., Nigita, G. & Ferro, A. Computational Approaches for the Analysis of ncRNA through Deep Sequencing Techniques. Front Bioeng Biotechnol
3, 77 (2015).
Darmanis, S. et al. A survey of human brain transcriptome diversity at the single cell level. Proc Natl Acad Sci USA
112, 7285–7290, doi:10.1073/pnas.1507125112 (2015).
Dombkowski, A. A. et al. Cortical Tubers: Windows into Dysregulation of Epilepsy Risk and Synaptic Signaling Genes by MicroRNAs. Cereb Cortex
26, 1059–1071, doi:10.1093/cercor/bhu276 (2016).
Somel, M. et al. MicroRNA-driven developmental remodeling in the brain distinguishes humans from other primates. PLoS Biol
9, e1001214, doi:10.1371/journal.pbio.1001214 (2011).
Boon, R. A. et al. MicroRNA-34a regulates cardiac ageing and function. Nature
495, 107–110, doi:10.1038/nature11919 (2013).
Maetschke, S. R., Madhamshettiwar, P. B., Davis, M. J. & Ragan, M. A. Supervised, semi-supervised and unsupervised inference of gene regulatory networks. Brief Bioinform
15, 195–211, doi:10.1093/bib/bbt034 (2014).
Zhao, W. et al. Weighted gene coexpression network analysis: state of the art. J Biopharm Stat
20, 281–300, doi:10.1080/10543400903572753 (2010).
Lee, Y. J., Kim, V., Muth, D. C. & Witwer, K. W. Validated MicroRNA Target Databases: An Evaluation. Drug Develop Res
76, 389–396, doi:10.1002/ddr.21278 (2015).
Boer, K. et al. Inflammatory processes in cortical tubers and subependymal giant cell tumors of tuberous sclerosis complex. Epilepsy Res
78, 7–21, doi:10.1016/j.eplepsyres.2007.10.002 (2008).
Zurolo, E. et al. Activation of Toll-like receptor, RAGE and HMGB1 signalling in malformations of cortical development. Brain: a journal of neurology
134, 1015–1032, doi:10.1093/brain/awr032 (2011).
Vezzani, A., French, J., Bartfai, T. & Baram, T. Z. The role of inflammation in epilepsy. Nature reviews. Neurology
7, 31–40, doi:10.1038/nrneurol.2010.178 (2011).
Aronica, E., Ravizza, T., Zurolo, E. & Vezzani, A. Astrocyte immune responses in epilepsy. Glia
60, 1258–1268, doi:10.1002/glia.22312 (2012).
Vezzani, A., Friedman, A. & Dingledine, R. J. The role of inflammation in epileptogenesis. Neuropharmacology
69, 16–24, doi:10.1016/j.neuropharm.2012.04.004 (2013).
Vezzani, A., Aronica, E., Mazarati, A. & Pittman, Q. J. Epilepsy and brain inflammation. Exp Neurol
244, 11–21, doi:10.1016/j.expneurol.2011.09.033 (2013).
Vezzani, A., Lang, B. & Aronica, E. Immunity and Inflammation in Epilepsy. Cold Spring Harb Perspect Med
6, a022699, doi:10.1101/cshperspect.a022699 (2016).
Aronica, E. et al. Complement activation in experimental and human temporal lobe epilepsy. Neurobiology of Disease
26, 497–511 (2007).
Aronica, E. et al. Gene expression profile analysis of epilepsy-associated gangliogliomas. Neuroscience
151, 272–292, doi:10.1016/j.neuroscience.2007.10.036 (2008).
Pelham, C. J. & Agrawal, D. K. Emerging roles for triggering receptor expressed on myeloid cells receptor family signaling in inflammatory diseases. Expert Rev Clin Immu
10, 243–256, doi:10.1586/1744666x.2014.866519 (2014).
Roe, K., Gibot, S. & Verma, S. Triggering receptor expressed on myeloid cells-1 (TREM-1) a new player in antiviral immunity? Front Microbiol
5, doi:10.3389/fmicb.2014.00627 (2014).
Maroso, M. et al. Toll-like receptor 4 and high-mobility group box-1 are involved in ictogenesis and can be targeted to reduce seizures. Nat Med
16, 413–419, doi:10.1038/nm.2127 (2010).
Iori, V. et al. Blockade of the IL-1R1/TLR4 pathway mediates disease-modification therapeutic effects in a model of acquired epilepsy. Neurobiology of Disease (2016).
Prabowo, A. S. et al. Fetal brain lesions in tuberous sclerosis complex: TORC1 activation and inflammation. Brain pathology
23, 45–59, doi:10.1111/j.1750-3639.2012.00616.x (2013).
Araki, K., Ellebedy, A. H. & Ahmed, R. TOR in the immune system. Curr Opin Cell Biol
23, 707–715, doi:10.1016/j.ceb.2011.08.006 (2011).
Saleiro, D. & Platanias, L. C. Intersection of mTOR and STAT signaling in immunity. Trends Immunol
36, 21–29, doi:10.1016/j.it.2014.10.006 (2015).
Weichhart, T., Hengstschlager, M. & Linke, M. Regulation of innate immune cell function by mTOR. Nat Rev Immunol
15, 599–614, doi:10.1038/nri3901 (2015).
Zhang, B., Zou, J., Rensing, N. R., Yang, M. & Wong, M. Inflammatory mechanisms contribute to the neurological manifestations of tuberous sclerosis complex. Neurobiol Dis
80, 70–79, doi:10.1016/j.nbd.2015.04.016 (2015).
Cunningham, C. Microglia and neurodegeneration: the role of systemic inflammation. Glia
61, 71–90, doi:10.1002/glia.22350 (2013).
Mayo, L. et al. Regulation of astrocyte activation by glycolipids drives chronic CNS inflammation. Nat Med
20, 1147–1156, doi:10.1038/nm.3681 (2014).
Weber, M. J. Mammalian small nucleolar RNAs are mobile genetic elements. Plos Genet
2, 1984–1997, doi:10.1371/journal.pgen.0020205 (2006).
Mattick, J. S. The central role of RNA in human development and cognition. Febs Lett
585, 1600–1616, doi:10.1016/j.febslet.2011.05.001 (2011).
Lui, L. R. & Lowe, T. Small nucleolar RNAs and RNA-guided post-transcriptional modification. Essays Biochem
54, 53–77, doi:10.1042/Bse0540053 (2013).
Bratkovic, T. & Rogelj, B. The many faces of small nucleolar RNAs. Bba-Gene Regul Mech
1839, 438–443, doi:10.1016/j.bbagrm.2014.04.009 (2014).
Falaleeva, M. et al. Dual function of C/D box small nucleolar RNAs in rRNA modification and alternative pre-mRNA splicing. P Natl Acad Sci USA
113, E1625–E1634, doi:10.1073/pnas.1519292113 (2016).
Darzacq, X. et al. Cajal body-specific small nuclear RNAs: a novel class of 2 ‘-O-methylation and pseudouridylation guide RNAs. Embo J
21, 2746–2756, doi:10.1093/emboj/21.11.2746 (2002).
Deryusheva, S. & Gall, J. G. Novel small Cajal-body-specific RNAs identified in Drosophila: probing guide RNA function. Rna
19, 1802–1814, doi:10.1261/rna.042028.113 (2013).
Ander, B. P., Barger, N., Stamova, B., Sharp, F. R. & Schumann, C. M. Atypical miRNA expression in temporal cortex associated with dysregulation of immune, cell cycle, and other pathways in autism spectrum disorders. Mol Autism
6, 37, doi:10.1186/s13229-015-0029-9 (2015).
Galiveti, C. R., Raabe, C. A., Konthur, Z. & Rozhdestvensky, T. S. Differential regulation of non-protein coding RNAs from Prader-Willi Syndrome locus. Sci Rep
4, 6445, doi:10.1038/srep06445 (2014).
Kristensen, V. N. et al. Principles and methods of integrative genomic analyses in cancer. Nat Rev Cancer
14, 299–313, doi:10.1038/nrc3721 (2014).
Eisch, A. J. & Petrik, D. Depression and hippocampal neurogenesis: a road to remission? Science
338, 72–75, doi:10.1126/science.1222941 (2012).
Christian, K. M., Song, H. & Ming, G. L. Functions and dysfunctions of adult hippocampal neurogenesis. Annu Rev Neurosci
37, 243–262, doi:10.1146/annurev-neuro-071013-014134 (2014).
Glass, M. & Dragunow, M. Neurochemical and morphological changes associated with human epilepsy. Brain Res Brain Res Rev
21, 29–41 (1995).
Moon, J. et al. Unique behavioral characteristics and microRNA signatures in a drug resistant epilepsy model. PLoS One
9, e85617, doi:10.1371/journal.pone.0085617 (2014).
Rasgado, L. A., Reyes, G. C. & Diaz, F. V. Modulation of brain glutamate dehydrogenase as a tool for controlling seizures. Acta Pharm
65, 443–452, doi:10.1515/acph-2015-0033 (2015).
Wong, M. Y. W., Yu, Y., Walsh, W. R. & Yang, J. L. microRNA-34 family and treatment of cancers with mutant or wild-type p53 (Review). Int J Oncol
38, 1189–1195, doi:10.3892/ijo.2011.970 (2011).
Agostini, M. & Knight, R. A. miR-34: from bench to bedside. Oncotarget
5, 872–881 (2014).
de Antonellis, P. et al. MiR-34a Targeting of Notch Ligand Delta-Like 1 Impairs CD15(+)/CD133(+) Tumor-Propagating Cells and Supports Neural Differentiation in Medulloblastoma. Plos One
6, doi:10.1371/journal.pone.0024584 (2011).
Bernardo, B. C. et al. Therapeutic inhibition of the miR-34 family attenuates pathological cardiac remodeling and improves heart function. P Natl Acad Sci USA
109, 17615–17620, doi:10.1073/pnas.1206432109 (2012).
Bae, Y. J. et al. miRNA-34c regulates Notch signaling during bone development. Hum Mol Genet
21, 2991–3000, doi:10.1093/hmg/dds129 (2012).
Kim, N. H. et al. p53 and MicroRNA-34 Are Suppressors of Canonical Wnt Signaling. Sci Signal
4, doi:10.1126/scisignal.2001744 (2011).
Cha, Y. H. et al. miRNA-34 intrinsically links p53 tumor suppressor and Wnt signaling. Cell Cycle
11, 1273–1281, doi:10.4161/cc.11.7.19618 (2012).
Tarantino, C. et al. miRNA 34a, 100, and 137 modulate differentiation of mouse embryonic stem cells. Faseb J
24, 3255–3263, doi:10.1096/fj.09-152207 (2010).
Aranha, M. M. et al. Apoptosis-associated microRNAs are modulated in mouse, rat and human neural differentiation. Bmc Genomics
11, doi:10.1186/1471-2164-11-514 (2010).
Agostini, M. et al. Neuronal differentiation by TAp73 is mediated by microRNA-34a regulation of synaptic protein targets. P Natl Acad Sci USA
108, 21093–21098, doi:10.1073/pnas.1112061109 (2011).
Agostini, M. et al. microRNA-34a regulates neurite outgrowth, spinal morphology, and function. P Natl Acad Sci USA
108, 21099–21104, doi:10.1073/pnas.1112063108 (2011).
Aranha, M. M., Santos, D. M., Sola, S., Steer, C. J. & Rodrigues, C. M. P. miR-34a Regulates Mouse Neural Stem Cell Differentiation. Plos One
6, doi:10.1371/journal.pone.0021396 (2011).
Morgado, A. L. et al. MicroRNA-34a Modulates Neural Stem Cell Differentiation by Regulating Expression of Synaptic and Autophagic Proteins. Mol Neurobiol
51, 1168–1183, doi:10.1007/s12035-014-8794-6 (2015).
Fededa, J. P. et al. MicroRNA-34/449 controls mitotic spindle orientation during mammalian cortex development. Embo J
35, 2386–2398, doi:10.15252/embj.201694056 (2016).
Gomez, M., Sampson, J. & Whittemore, V. The Tuberous Sclerosis Complex (Oxford University Press., 1999).
Northrup, H. & Krueger, D. A. & International Tuberous Sclerosis Complex Consensus, G. Tuberous sclerosis complex diagnostic criteria update: recommendations of the 2012 Iinternational Tuberous Sclerosis Complex Consensus Conference. Pediatr Neurol
49, 243–254, doi:10.1016/j.pediatrneurol.2013.08.001 (2013).
Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics
30, 2114–2120, doi:10.1093/bioinformatics/btu170 (2014).
Kim, D. et al. TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biol
14, doi:10.1186/gb-2013-14-4-r36 (2013).
Trapnell, C. et al. Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nature Protocols
7, 562–578, doi:10.1038/nprot.2012.016 (2012).
Harrow, J. et al. GENCODE: The reference human genome annotation for The ENCODE Project. Genome Res
22, 1760–1774, doi:10.1101/gr.135350.111 (2012).
Smyth, G. K. In Bioinformatics and Computational Biology Solutions using R and Bioconductor (eds C. V.J. G. R., W. H., I. R.A., D. S., Eds (Springer, 2005)) 397–420 (2005).
Benjamini, Y. & Hochberg, Y. Controlling the False Discovery Rate – a Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society Series B-Methodological
57, 289–300 (1995).
Shannon, P. T., Grimes, M., Kutlu, B., Bot, J. J. & Galas, D. J. RCytoscape: tools for exploratory network analysis. Bmc Bioinformatics
14, doi:10.1186/1471-2105-14-217 (2013).
Scicluna, B. P., van Lieshout, M. H., Blok, D. C., Florquin, S. & van der Poll, T. Modular Transcriptional Networks of the Host Pulmonary Response during Early and Late Pneumococcal Pneumonia. Molecular Medicine
21, 430–441, doi:10.2119/molmed.2014.00263 (2015).
Bulgakov, V. P. & Tsitsiashvili, G. S. Bioinformatics analysis of protein interaction networks: Statistics, topologies, and meeting the standards of experimental biologists. Biochemistry-Moscow
78, 1098–1103, doi:10.1134/S0006297913100039 (2013).
Dong, J. & Horvath, S. Understanding network concepts in modules. Bmc Systems Biology
1, doi:10.1186/1752-0509-1-24 (2007).
Song, L., Langfelder, P. & Horvath, S. Comparison of co-expression measures: mutual information, correlation, and model based indices. Bmc Bioinformatics
13, doi:10.1186/1471-2105-13-328 (2012).
Dweep, H., Sticht, C., Pandey, P. & Gretz, N. miRWalk – Database: Prediction of possible miRNA binding sites by “walking” the genes of three genomes. Journal of Biomedical Informatics
44, 839–847, doi:10.1016/j.jbi.2011.05.002 (2011).
Darmanis, S. et al. A survey of human brain transcriptome diversity at the single cell level. P Natl Acad Sci USA
112, 7285–7290, doi:10.1073/pnas.1507125112 (2015).
Liao, Y., Smyth, G. K. & Shi, W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics
30, 923–930, doi:10.1093/bioinformatics/btt656 (2014).
Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol
15, doi:10.1186/s13059-014-0550-8 (2014).
Hoogeveen-Westerveld, M. et al. Functional Assessment of Variants in the TSC1 and TSC2 Genes Identified in Individuals with Tuberous Sclerosis Complex. Human Mutation
32, 424–435, doi:10.1002/humu.21451 (2011).
Prabowo, A. S. et al. Differential expression and clinical significance of three inflammation-related microRNAs in gangliogliomas. J Neuroinflammation
12, 97, doi:10.1186/s12974-015-0315-7 (2015).
van Scheppingen, J. et al. Expression of microRNAs miR21, miR146a and miR155 in tuberous sclerosis complex cortical tubers and their regulation in human astrocytes and SEGA-derived cell cultures. Glia in press (2016).
Ramakers, C., Ruijter, J. M., Deprez, R. H. & Moorman, A. F. Assumption-free analysis of quantitative real-time polymerase chain reaction (PCR) data. Neuroscience Letters
339, 62–66 (2003).
Ruijter, J. M. et al. Amplification efficiency: linking baseline and bias in the analysis of quantitative PCR data. Nucleic acids research
37, e45, doi:10.1093/nar/gkp045 (2009).