Divergence of human and mouse brain transcriptome highlights Alzheimer disease pathways

Because mouse models play a crucial role in biomedical research related to the human nervous system, understanding the similarities and differences between mouse and human brain is of fundamental importance. Studies comparing transcription in human and mouse have come to varied conclusions, in part because of their relatively small sample sizes or underpowered methodologies. To better characterize gene expression differences between mouse and human, we took a systems-biology approach by using weighted gene coexpression network analysis on more than 1,000 microarrays from brain. We find that global network properties of the brain transcriptome are highly preserved between species. Furthermore, all modules of highly coexpressed genes identified in mouse were identified in human, with those related to conserved cellular functions showing the strongest between-species preservation. Modules corresponding to glial and neuronal cells were sufficiently preserved between mouse and human to permit identification of cross species cell-class marker genes. We also identify several robust human-specific modules, including one strongly correlated with measures of Alzheimer disease progression across multiple data sets, whose hubs are poorly-characterized genes likely involved in Alzheimer disease. We present multiple lines of evidence suggesting links between neurodegenerative disease and glial cell types in human, including human-specific correlation of presenilin-1 with oligodendrocyte markers, and significant enrichment for known neurodegenerative disease genes in microglial modules. Together, this work identifies convergent and divergent pathways in mouse and human, and provides a systematic framework that will be useful for understanding the applicability of mouse models for human brain disorders.

[1]  Kyoko Takahashi,et al.  Epigenetic Regulation of TLR4 Gene Expression in Intestinal Epithelial Cells for the Maintenance of Intestinal Homeostasis1 , 2009, The Journal of Immunology.

[2]  D. Geschwind,et al.  Human-Specific Transcriptional Regulation of CNS Development Genes by FOXP2 , 2009, Nature.

[3]  D. Geschwind,et al.  Genetic advances in autism: heterogeneity and convergence on shared pathways. , 2009, Current opinion in genetics & development.

[4]  D. Stephan,et al.  Genetic control of human brain transcript expression in Alzheimer disease. , 2009, American journal of human genetics.

[5]  S. Horvath,et al.  WGCNA: an R package for weighted correlation network analysis , 2008, BMC Bioinformatics.

[6]  Sandhya Rani,et al.  Human Protein Reference Database—2009 update , 2008, Nucleic Acids Res..

[7]  S. Horvath,et al.  Functional organization of the transcriptome in human brain , 2008, Nature Neuroscience.

[8]  Carl W. Cotman,et al.  Gene expression changes in the course of normal brain aging are sexually dimorphic , 2008, Proceedings of the National Academy of Sciences.

[9]  Jun Dong,et al.  Geometric Interpretation of Gene Coexpression Network Analysis , 2008, PLoS Comput. Biol..

[10]  R. Fields,et al.  White matter in learning, cognition and psychiatric disorders , 2008, Trends in Neurosciences.

[11]  Rosario M. Piro,et al.  Prediction of Human Disease Genes by Human-Mouse Conserved Coexpression Analysis , 2008, PLoS Comput. Biol..

[12]  Bin Zhang,et al.  Defining clusters from a hierarchical cluster tree: the Dynamic Tree Cut package for R , 2008, Bioinform..

[13]  D. Geschwind,et al.  A Systems Level Analysis of Transcriptional Changes in Alzheimer's Disease and Normal Aging , 2008, The Journal of Neuroscience.

[14]  Y. Xing,et al.  A Transcriptome Database for Astrocytes, Neurons, and Oligodendrocytes: A New Resource for Understanding Brain Development and Function , 2008, The Journal of Neuroscience.

[15]  Judith A. Blake,et al.  The Mouse Genome Database (MGD): mouse biology and model systems , 2007, Nucleic Acids Res..

[16]  Peter Langfelder,et al.  Eigengene networks for studying the relationships between co-expression modules , 2007, BMC Systems Biology.

[17]  Jing Chen,et al.  Improved human disease candidate gene prioritization using mouse phenotype , 2007, BMC Bioinformatics.

[18]  Stanley J. Watson,et al.  Methodological considerations for gene expression profiling of human brain , 2007, Journal of Neuroscience Methods.

[19]  George Bartzokis,et al.  Diffusion tensor imaging in preclinical and presymptomatic carriers of familial Alzheimer's disease mutations. , 2007, Brain : a journal of neurology.

[20]  S. Nelson,et al.  Celsius: a community resource for Affymetrix microarray data , 2007, Genome Biology.

[21]  Y. Xing,et al.  Assessing the conservation of mammalian gene expression using high-density exon arrays. , 2007, Molecular biology and evolution.

[22]  J. Olson,et al.  Conservation of Regional Gene Expression in Mouse and Human Brain , 2007, PLoS genetics.

[23]  Allan R. Jones,et al.  Genome-wide atlas of gene expression in the adult mouse brain , 2007, Nature.

[24]  S. Horvath,et al.  Conservation and evolution of gene coexpression networks in human and chimpanzee brains , 2006, Proceedings of the National Academy of Sciences.

[25]  S. Goldman,et al.  Astrocytic complexity distinguishes the human brain , 2006, Trends in Neurosciences.

[26]  Michael Lachmann,et al.  Evolution of primate gene expression , 2006, Nature Reviews Genetics.

[27]  Win-Li Lin,et al.  In silico identification and comparative analysis of differentially expressed genes in human and mouse tissues , 2006, BMC Genomics.

[28]  Johannes Berg,et al.  Cross-species analysis of biological networks by Bayesian alignment. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

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

[30]  F. González-Scarano,et al.  Microarray analysis of activated mixed glial (microglia) and monocyte-derived macrophage gene expression , 2004, Journal of Neuroimmunology.

[31]  I. Yanai,et al.  Incongruent expression profiles between human and mouse orthologous genes suggest widespread neutral evolution of transcription control. , 2004, Omics : a journal of integrative biology.

[32]  M. Owen,et al.  TBP, a polyglutamine tract containing protein, accumulates in Alzheimer's disease. , 2004, Brain research. Molecular brain research.

[33]  Homin K. Lee,et al.  Coexpression analysis of human genes across many microarray data sets. , 2004, Genome research.

[34]  S. Batalov,et al.  A gene atlas of the mouse and human protein-encoding transcriptomes. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[35]  L. Gan,et al.  Identification of Cathepsin B as a Mediator of Neuronal Death Induced by Aβ-activated Microglial Cells Using a Functional Genomics Approach* , 2004, Journal of Biological Chemistry.

[36]  G. Bartzokis Age-related myelin breakdown: a developmental model of cognitive decline and Alzheimer’s disease , 2004, Neurobiology of Aging.

[37]  S. Bergmann,et al.  Similarities and Differences in Genome-Wide Expression Data of Six Organisms , 2003, PLoS biology.

[38]  D. Geschwind Tau Phosphorylation, Tangles, and Neurodegeneration The Chicken or the Egg? , 2003, Neuron.

[39]  Joshua M. Stuart,et al.  A Gene-Coexpression Network for Global Discovery of Conserved Genetic Modules , 2003, Science.

[40]  M. Mattson,et al.  Triple-Transgenic Model of Alzheimer's Disease with Plaques and Tangles Intracellular Aβ and Synaptic Dysfunction , 2003, Neuron.

[41]  A. Barabasi,et al.  Hierarchical Organization of Modularity in Metabolic Networks , 2002, Science.

[42]  G. Church,et al.  Correlation between transcriptome and interactome mapping data from Saccharomyces cerevisiae , 2001, Nature Genetics.

[43]  R. Albin,et al.  Neurological abnormalities in a knock-in mouse model of Huntington's disease. , 2001, Human molecular genetics.

[44]  M. King,et al.  Evolution at two levels in humans and chimpanzees. , 1975, Science.

[45]  D. Blacker,et al.  Systematic meta-analyses of Alzheimer disease genetic association studies: the AlzGene database , 2007, Nature Genetics.

[46]  E. Koonin,et al.  - 1-Supplementary Information for : Global similarity and local divergence in human and mouse gene co-expression networks , 2006 .

[47]  Y. Leea,et al.  Analysis of oncogenic signaling networks in glioblastoma identifies ASPM as a molecular target , 2006 .

[48]  BMC Bioinformatics Methodology article , 2004 .

[49]  Alex E. Lash,et al.  Gene Expression Omnibus: NCBI gene expression and hybridization array data repository , 2002, Nucleic Acids Res..

[50]  J. Trojanowski,et al.  Neurodegenerative tauopathies. , 2001, Annual review of neuroscience.

[51]  D. Ferrari,et al.  Activation of microglial cells by beta-amyloid protein and interferon-gamma. , 1995, Nature.

[52]  Steve Horvath,et al.  Molecular Systems Biology 5; Article number 291; doi:10.1038/msb.2009.46 Citation: Molecular Systems Biology 5:291 , 2022 .