Pathological priming causes developmental gene network heterochronicity in autistic subject-derived neurons

Nature Neuroscience

Volumn 22, Issue 2, 2019, Pages 243-255

  Schafer, Simon T ^a   Paquola, Apua C M ^a,b,c   Stern, Shani ^a   Gosselin, David ^d   Ku, Manching ^a,e   Pena, Monique ^a   Kuret, Thomas J M ^a   Liyanage, Marvin ^a   Mansour, Abed AlFatah ^a   Jaeger, Baptiste N ^a,f   Marchetto, Maria C ^a   Glass, Christopher K ^g   Mertens, Jerome ^a,h   Gage, Fred H ^a  

^a SALK INSTITUTE FOR BIOLOGICAL STUDIES   (United States)

^b LIEBER INSTITUTE FOR BRAIN DEVELOPMENT   (United States)

^c JOHNS HOPKINS UNIVERSITY SCHOOL OF MEDICINE   (United States)

^d UNIVERSITÉ LAVAL   (Canada)

^e UNIVERSITY OF FREIBURG   (Germany)

^f UNIVERSITY OF ZURICH   (Switzerland)

^g UNIVERSITY OF CALIFORNIA   (United States)

^h UNIVERSITY OF INNSBRUCK   (Austria)

Author keywords

[No Author keywords available]

Indexed keywords

CD15 ANTIGEN; CD24 ANTIGEN; CHEMOKINE RECEPTOR CXCR4; ENHANCED GREEN FLUORESCENT PROTEIN; F BOX PROTEIN; HERMES ANTIGEN; NERVE CELL ADHESION MOLECULE; NEUROGENIN 2; NEUROTROPHIN RECEPTOR P75; RNA;

ANTIGEN EXPRESSION; ARTICLE; AUTISM; BRAIN DEVELOPMENT; CELL MATURATION; CELL STRUCTURE; CELL TRANSDIFFERENTIATION; CHROMATIN; CLINICAL ARTICLE; CLINICAL FEATURE; COHORT ANALYSIS; CONTROLLED STUDY; DEVELOPMENTAL GENE; DISEASE ASSOCIATION; FLUORESCENCE ACTIVATED CELL SORTING; GENE EXPRESSION; GENETIC VARIATION; HUMAN; HUMAN CELL; INDUCED PLURIPOTENT STEM CELL; MACROCEPHALY; NERVE CELL; NERVE CELL DIFFERENTIATION; NERVE CELL NETWORK; NERVE PROJECTION; NERVOUS SYSTEM DEVELOPMENT; NEURAL STEM CELL; PHENOTYPE; PRIORITY JOURNAL; PROTEIN EXPRESSION; RNA SEQUENCE; GENE REGULATORY NETWORK; GENETICS; INHIBITORY POSTSYNAPTIC POTENTIAL; PATHOLOGY; PATHOPHYSIOLOGY; PHYSIOLOGY;

AUTISM SPECTRUM DISORDER; GENE REGULATORY NETWORKS; HUMANS; INDUCED PLURIPOTENT STEM CELLS; INHIBITORY POSTSYNAPTIC POTENTIALS; NERVE NET; NEURAL STEM CELLS; NEURONS;

EID: 85059695852     PISSN: 10976256     EISSN: 15461726     Source Type: Journal    
DOI: 10.1038/s41593-018-0295-x     Document Type: Article

References (71)

1. de la Torre-Ubieta, L., Won, H., Stein, J. L. & Geschwind, D. H. Advancing the understanding of autism disease mechanisms through genetics. Nat. Med. 22, 345–361 (2016)
2. Parikshak, N. N., Gandal, M. J. & Geschwind, D. H. Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders. Nat. Rev. Genet. 16, 441–458 (2015)
3. Parikshak, N. N. et al. Integrative functional genomic analyses implicate specific molecular pathways and circuits in autism. Cell 155, 1008–1021 (2013)
4. Willsey, A. J. et al. Coexpression networks implicate human midfetal deep cortical projection neurons in the pathogenesis of autism. Cell 155, 997–1007 (2013)
5. Courchesne, E., Carper, R. & Akshoomoff, N. Evidence of brain overgrowth in the first year of life in autism. J. Am. Med. Assoc. 290, 337–344 (2003)
6. Courchesne, E. et al. Mapping early brain development in autism. Neuron 56, 399–413 (2007)
7. Emerson, R. W. et al. Functional neuroimaging of high-risk 6-month-old infants predicts a diagnosis of autism at 24 months of age. Sci. Transl. Med. 9, eaag2882 (2017)
8. Hazlett, H. C. et al. Early brain development in infants at high risk for autism spectrum disorder. Nature 542, 348–351 (2017)
9. Marchetto, M. C. et al. Altered proliferation and networks in neural cells derived from idiopathic autistic individuals. Mol. Psychiatry 22, 820–835 (2017)
10. Mariani, J. et al. FOXG1-dependent dysregulation of GABA/glutamate neuron differentiation in autism spectrum disorders. Cell 162, 375–390 (2015)
11. Shcheglovitov, A. et al. SHANK3 and IGF1 restore synaptic deficits in neurons from 22q13 deletion syndrome patients. Nature 503, 267–271 (2013)
12. Stein, J. L. et al. A quantitative framework to evaluate modeling of cortical development by neural stem cells. Neuron 83, 69–86 (2014)
13. Allan Institute for Brain Science. Atlas of the developing human brain BrainSpan http://www.brainspan.org/ (2016)
14. Yuan, S. H. et al. Cell-surface marker signatures for the isolation of neural stem cells, glia and neurons derived from human pluripotent stem cells. PLoS One 6, e17540 (2011)
15. Zhang, B. & Horvath, S. A general framework for weighted gene co-expression network analysis. Stat. Appl. Genet. Mol. Biol. 4, e17 (2005)
16. Langfelder, P. & Horvath, S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics 9, 559 (2008)
17. Sakoe, H. Dynamic programming algorithm optimization for spoken word recognition. IEEE Trans. Acoust. Speech Signal Process. 26, 43–49 (1978)
18. Velichko, V. M. & Zagoruyko, N. G. Automatic recognition of 200 words. Int. J. Man. Mach. Stud. 2, 223–234 (1970)
19. Basu, S. N., Kollu, R. & Banerjee-Basu, S. AutDB: a gene reference resource for autism research. Nucleic Acids Res. 37, D832–D836 (2009)
20. Voineagu, I. et al. Transcriptomic analysis of autistic brain reveals convergent molecular pathology. Nature 474, 380–384 (2011)
21. Parikshak, N. N. et al. Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism. Nature 540, 423–427 (2016)
22. Iossifov, I. et al. The contribution of de novo coding mutations to autism spectrum disorder. Nature 515, 216–221 (2014)
23. Lancaster, M. A. et al. Cerebral organoids model human brain development and microcephaly. Nature 501, 373–379 (2013)
24. Qian, X. et al. Brain-region-specific organoids using mini-bioreactors for modeling ZIKV exposure. Cell 165, 1238–1254 (2016)
25. Molyneaux, B. J., Arlotta, P., Menezes, J. R. L. & Macklis, J. D. Neuronal subtype specification in the cerebral cortex. Nat. Rev. Neurosci. 8, 427–437 (2007)
26. Toma, K., Wang, T.-C. & Hanashima, C. Encoding and decoding time in neural development. Dev. Growth Differ. 58, 59–72 (2016)
27. Erhardt, J. A. et al. A novel F box protein, NFB42, is highly enriched in neurons and induces growth arrest. J. Biol. Chem. 273, 35222–35227 (1998)
28. Atkin, G. et al. Loss of F-box only protein 2 (Fbxo2) disrupts levels and localization of select NMDA receptor subunits, and promotes aberrant synaptic connectivity. J. Neurosci. 35, 6165–6178 (2015)
29. Vitucci, D. et al. Rasd2 modulates prefronto-striatal phenotypes in humans and ‘schizophrenia-like behaviors’ in mice. Neuropsychopharmacology 41, 916–927 (2016)
30. Abudureyimu, S. et al. Essential role of Linx/Islr2 in the development of the forebrain anterior commissure. Sci. Rep. 8, 7292 (2018)
31. Mandai, K., Reimert, D. V. & Ginty, D. D. Linx mediates interaxonal interactions and formation of the internal capsule. Neuron 83, 93–103 (2014)
32. Zhang, Y. et al. Rapid single-step induction of functional neurons from human pluripotent stem cells. Neuron 78, 785–798 (2013)
33. Kundaje, A. et al. Integrative analysis of 111 reference human epigenomes. Nature 518, 317–330 (2015)
34. Wilczynski, B., Liu, Y.-H., Yeo, Z. X. & Furlong, E. E. M. Predicting spatial and temporal gene expression using an integrative model of transcription factor occupancy and chromatin state. PLoS. Comput. Biol. 8, e1002798 (2012)
35. Jin, F. et al. A high-resolution map of the three-dimensional chromatin interactome in human cells. Nature 503, 290–294 (2013)
36. Chow, M. L. et al. Age-dependent brain gene expression and copy number anomalies in autism suggest distinct pathological processes at young versus mature ages. PLoS. Genet. 8, e1002592 (2012)
37. Gupta, S. et al. Transcriptome analysis reveals dysregulation of innate immune response genes and neuronal activity-dependent genes in autism. Nat. Commun. 5, 5748 (2014)
38. Sun, W. et al. Histone acetylome-wide association study of autism spectrum disorder. Cell 167, 1385–1397 (2016)
39. Lim, E. T. et al. Rates, distribution and implications of postzygotic mosaic mutations in autism spectrum disorder. Nat. Neurosci. 20, 1217–1224 (2017)
40. Hazlett, H. C. et al. Early brain overgrowth in autism associated with an increase in cortical surface area before age 2 years. Arch. Gen. Psychiatry 68, 467–476 (2011)
41. Schumann, C. M. et al. Longitudinal magnetic resonance imaging study of cortical development through early childhood in autism. J. Neurosci. 30, 4419–4427 (2010)
42. Bauman, M. L. & Kemper, T. L. Neuroanatomic observations of the brain in autism: a review and future directions. Int. J. Dev. Neurosci. 23, 183–187 (2005)
43. Belmonte, M. K. et al. Autism and abnormal development of brain connectivity. J. Neurosci. 24, 9228–9231 (2004)
44. Carper, R. A. & Courchesne, E. Localized enlargement of the frontal cortex in early autism. Biol. Psychiatry 57, 126–133 (2005)
45. Casanova, M. F., Buxhoeveden, D. P., Switala, A. E. & Roy, E. Minicolumnar pathology in autism. Neurology 58, 428–432 (2002)
46. Casanova, M. F. et al. Abnormalities of cortical minicolumnar organization in the prefrontal lobes of autistic patients. Clin. Neurosci. Res. 6, 127–133 (2006)
47. Weir, R. K., Bauman, M. D., Jacobs, B. & Schumann, C. M. Protracted dendritic growth in the typically developing human amygdala and increased spine density in young ASD brains. J. Comp. Neurol. 526, 262–274 (2018)
48. Chomiak, T., Karnik, V., Block, E. & Hu, B. Altering the trajectory of early postnatal cortical development can lead to structural and behavioural features of autism. BMC Neurosci. 11, 102 (2010)
49. Chomiak, T. et al. Auditory-cued sensorimotor task reveals disengagement deficits in rats exposed to the autism-associated teratogen valproic acid. Neuroscience 268, 212–220 (2014)
50. Vierbuchen, T. et al. Direct conversion of fibroblasts to functional neurons by defined factors. Nature 463, 1035–1041 (2010)
51. Fishman, V. S. et al. Cell divisions are not essential for the direct conversion of fibroblasts into neuronal cells. Cell Cycle 14, 1188–1196 (2015)
52. Briggs, J. A. et al. Mouse embryonic stem cells can differentiate via multiple paths to the same state. eLife 6, e26945 (2017)
53. Heger, A., Webber, C., Goodson, M., Ponting, C. P. & Lunter, G. GAT: a simulation framework for testing the association of genomic intervals. Bioinformatics 29, 2046–2048 (2013)
54. Takahashi, K. et al. Induction of pluripotent stem cells from adult human fibroblasts by defined factors. Cell 131, 861–872 (2007)
55. Marchetto, M. C. N. et al. A model for neural development and treatment of Rett syndrome using human induced pluripotent stem cells. Cell 143, 527–539 (2010)
56. Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014)
57. Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013)
58. Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014)
59. Yip, A. M. & Horvath, S. Gene network interconnectedness and the generalized topological overlap measure. BMC Bioinformatics 8, 22 (2007)
60. Langfelder, P., Zhang, B. & Horvath, S. Defining clusters from a hierarchical cluster tree: the Dynamic Tree Cut package for R. Bioinformatics 24, 719–720 (2008)
61. Aach, J. & Church, G. M. Aligning gene expression time series with time warping algorithms. Bioinformatics 17, 495–508 (2001)
62. Giorgino, T. Computing and visualizing dynamic time warping alignments in R: the dtw package. J. Stat. Softw. 31, 1–24 (2009)
63. Shannon, P. et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 13, 2498–2504 (2003)
64. Huang, W., Sherman, B. T. & Lempicki, R. A. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat. Protoc. 4, 44–57 (2009)
65. Ashburner, M.et al. The Gene Ontology Consortium. Gene ontology: tool for the unification of biology. Nat. Genet. 25, 25–29 (2000)
66. Hosack, D. A., Dennis, G. Jr., Sherman, B. T., Lane, H. C. & Lempicki, R. A. Identifying biological themes within lists of genes with EASE. Genome Biol. 4, R70 (2003)
67. Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012)
68. Ramírez, F. et al. deepTools2: a next generation web server for deep-sequencing data analysis. Nucleic Acids Res. 44, W160–W165 (2016)
69. Ross-Innes, C. S. et al. Differential oestrogen receptor binding is associated with clinical outcome in breast cancer. Nature 481, 389–393 (2012)
70. Hahne, F. & Ivanek, R. Visualizing genomic data using Gviz and Bioconductor. Methods Mol. Biol. 1418, 335–351 (2016)
71. Heinz, S. et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol. Cell 38, 576–589 (2010)