Differential variability and correlation of gene expression identifies key genes involved in neuronal differentiation

BackgroundUnderstanding the dynamics of stem cell differentiation processes at the molecular level is a central challenge in developmental biology and regenerative medicine. Although the dynamic behaviors of differentiation regulators have been partially characterized, the architecture regulating the underlying molecular systems remains unclear.ResultSystem-level analysis of transcriptional data was performed to characterize the dynamics of molecular networks in neural differentiation of stem cells. Expression of a network module of genes tightly co-expressed in mouse embryonic stem (ES) cells fluctuated greatly among cell populations before differentiation, but became stable following neural differentiation. During the neural differentiation process, genes exhibiting both differential variance and differential correlation between undifferentiated and differentiating states were related to developmental functions such as body axis development, neuronal movement, and transcriptional regulation. Furthermore, these genes were genetically associated with neuronal differentiation, providing support for the idea they are not only differentiation markers but could also play important roles in neural differentiation. Comparisons with transcriptional data from human induced pluripotent stem (iPS) cells revealed that the system of genes dynamically regulated during neural differentiation is conserved between mouse and human.ConclusionsThe results of this study provide a systematic analytical framework for identifying key genes involved in neural differentiation by detecting their dynamical behaviors, as well as a basis for understanding the dynamic molecular mechanisms underlying the processes of neural differentiation.

[1]  David J. Price,et al.  Regulation of cerebral cortical neurogenesis by the Pax6 transcription factor , 2015, Front. Cell. Neurosci..

[2]  K. Schenke-Layland,et al.  Mapping the first stages of mesoderm commitment during differentiation of human embryonic stem cells , 2010, Proceedings of the National Academy of Sciences.

[3]  Xiufen Zou,et al.  Deciphering deterioration mechanisms of complex diseases based on the construction of dynamic networks and systems analysis , 2015, Scientific Reports.

[4]  Daniel H. Geschwind,et al.  Neuroscience in the era of functional genomics and systems biology , 2009, Nature.

[5]  Avi Ma’ayan,et al.  Systems biology of stem cell fate and cellular reprogramming , 2009, Nature Reviews Molecular Cell Biology.

[6]  Kazuyuki Aihara,et al.  Identifying critical transitions of complex diseases based on a single sample , 2014, Bioinform..

[7]  N. Corbi,et al.  Developmental-specific activity of the FGF-4 enhancer requires the synergistic action of Sox2 and Oct-3. , 1995, Genes & development.

[8]  Guillaume Blin,et al.  Hes1 Desynchronizes Differentiation of Pluripotent Cells by Modulating STAT3 Activity , 2013, Stem cells.

[9]  Sue Povey,et al.  HCOP: The HGNC comparison of orthology predictions search tool , 2005, Mammalian Genome.

[10]  S. Carpenter,et al.  Anticipating Critical Transitions , 2012, Science.

[11]  S. Horvath,et al.  A General Framework for Weighted Gene Co-Expression Network Analysis , 2005, Statistical applications in genetics and molecular biology.

[12]  Wei Hsu,et al.  Gpr177/mouse Wntless is essential for Wnt‐mediated craniofacial and brain development , 2011, Developmental dynamics : an official publication of the American Association of Anatomists.

[13]  Ju-Young Kim,et al.  Secreted frizzled-related protein 3 regulates activity-dependent adult hippocampal neurogenesis. , 2013, Cell stem cell.

[14]  Ryoichiro Kageyama,et al.  The cyclic gene Hes1 contributes to diverse differentiation responses of embryonic stem cells. , 2009, Genes & development.

[15]  Xiangtian Yu,et al.  Unravelling personalized dysfunctional gene network of complex diseases based on differential network model , 2015, Journal of Translational Medicine.

[16]  Ryoichiro Kageyama,et al.  Persistent and high levels of Hes1 expression regulate boundary formation in the developing central nervous system , 2006, Development.

[17]  Michael B. Elowitz,et al.  Dynamic Heterogeneity and DNA Methylation in Embryonic Stem Cells , 2014, Molecular cell.

[18]  S. Carpenter,et al.  Early-warning signals for critical transitions , 2009, Nature.

[19]  Aviv Regev,et al.  Deconstructing transcriptional heterogeneity in pluripotent stem cells , 2014, Nature.

[20]  Joaquín Dopazo,et al.  Large-scale transcriptional profiling and functional assays reveal important roles for Rho-GTPase signalling and SCL during haematopoietic differentiation of human embryonic stem cells. , 2011, Human molecular genetics.

[21]  K. Aihara,et al.  Early Diagnosis of Complex Diseases by Molecular Biomarkers, Network Biomarkers, and Dynamical Network Biomarkers , 2014, Medicinal research reviews.

[22]  G. Lahav,et al.  Encoding and Decoding Cellular Information through Signaling Dynamics , 2013, Cell.

[23]  Tannishtha Reya,et al.  The elements of stem cell self-renewal: a genetic perspective. , 2003, BioTechniques.

[24]  Patrick S. Stumpf,et al.  Nanog-dependent feedback loops regulate murine embryonic stem cell heterogeneity , 2012, Nature Cell Biology.

[25]  P. Shannon,et al.  Cytoscape: a software environment for integrated models of biomolecular interaction networks. , 2003, Genome research.

[26]  A. Depaoli-Roach,et al.  Cyclin G2 Associates with Protein Phosphatase 2A Catalytic and Regulatory B′ Subunits in Active Complexes and Induces Nuclear Aberrations and a G1/S Phase Cell Cycle Arrest* , 2002, The Journal of Biological Chemistry.

[27]  T. Ohtsuka,et al.  Oscillations in notch signaling regulate maintenance of neural progenitors , 2008, International Journal of Developmental Neuroscience.

[28]  Jean YH Yang,et al.  Bioconductor: open software development for computational biology and bioinformatics , 2004, Genome Biology.

[29]  M. Elowitz,et al.  Functional roles for noise in genetic circuits , 2010, Nature.

[30]  박찬영.  Using iPSC-derived neurons to uncover cellular phenotypes associated with Timothy syndrome , 2012 .

[31]  Ryoichiro Kageyama,et al.  The Hes gene family: repressors and oscillators that orchestrate embryogenesis , 2007, Development.

[32]  Nicoletta Kessaris,et al.  SOX1 links the function of neural patterning and Notch signalling in the ventral spinal cord during the neuron-glial fate switch. , 2009, Biochemical and biophysical research communications.

[33]  Kazuyuki Aihara,et al.  Identifying critical transitions and their leading biomolecular networks in complex diseases , 2012, Scientific Reports.

[34]  Judith A. Blake,et al.  The Mouse Genome Database: integration of and access to knowledge about the laboratory mouse , 2013, Nucleic Acids Res..

[35]  T. Ideker,et al.  Differential network biology , 2012, Molecular systems biology.

[36]  L. Tran,et al.  Integrated Systems Approach Identifies Genetic Nodes and Networks in Late-Onset Alzheimer’s Disease , 2013, Cell.

[37]  Boris Greber,et al.  Rapid and efficient generation of neurons from human pluripotent stem cells in a multititre plate format. , 2013, Journal of visualized experiments : JoVE.

[38]  Jeroen L A Pennings,et al.  Time-response evaluation by transcriptomics of methylmercury effects on neural differentiation of murine embryonic stem cells. , 2011, Toxicological sciences : an official journal of the Society of Toxicology.

[39]  Li-Ru Zhao,et al.  Sox1 acts through multiple independent pathways to promote neurogenesis. , 2004, Developmental biology.

[40]  Omar Khalid,et al.  Discovery of Consensus Gene Signature and Intermodular Connectivity Defining Self‐Renewal of Human Embryonic Stem Cells , 2014, Stem cells.

[41]  Kazuyuki Aihara,et al.  Detecting early-warning signals for sudden deterioration of complex diseases by dynamical network biomarkers , 2012, Scientific Reports.

[42]  Guoping Fan,et al.  Functional modules distinguish human induced pluripotent stem cells from embryonic stem cells. , 2011, Stem cells and development.

[43]  Ryoichiro Kageyama,et al.  Oscillatory Control of Factors Determining Multipotency and Fate in Mouse Neural Progenitors , 2013, Science.

[44]  Radu Dobrin,et al.  Dissecting self-renewal in stem cells with RNA interference , 2006, Nature.

[45]  Sui Huang.  Non-genetic heterogeneity of cells in development: more than just noise , 2009, Development.

[46]  Y. Benjamini,et al.  More powerful procedures for multiple significance testing. , 1990, Statistics in medicine.