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Tips for mining and integrating the Allen Mouse Brain Atlas data Allen Institute Hackathon, 2012 Leon French Pavlidis Lab University of British Columbia Vancouver, Canada Neuroanatomical Connectivity Axonal projections, synapses Pathways of information flow Wiring of the brain Key to understanding brain function Beyond local Macro or mesoscale Brain regions (~1,000), modules 25,000 – 100,000 connections “Connectome” Determine global organizational principals Interpret functional imaging results The “connectome” The anatomical “wiring diagram” of the brain Large scale structure determined during development Obvious implications for disease Hagmann P, Kurant M, Gigandet X, Thiran P, Wedeen VJ, et al. (2007) Mapping Human Whole-Brain Structural Networks with Diffusion MRI. PLoS ONE 2(7): e597. Changes in Wiring in Schizophrenia? Karlsgodt et al. (2008). Diffusion tensor imaging of the superior longitudinal fasciculs and working memory in recent-onset schizophrenia. Biol Psychiatry. 63:512-518. Understanding the Brain Connectivity data is difficult to obtain Relatively few connections have been linked functions such as vision, pain and stress Abnormal connectivity is observed in many devastating brain disorders Disconnection leading to dysfunction Limited understanding of the connectome prevents discovery of causes and cures Data at cellular and molecular levels may help elucidate brain structure and function Expression Data: Allen Brain Atlas Non-expression genes removed Natural logarithm of expression energy Each image series set treated independently 22,771 image series 17,530 genes 207 regions ~3% missing Lein ES, Hawrylycz MJ, Ao N et al. Genome-wide atlas of gene expression in the adult mouse brain, Nature 2007;445:168-176. Brain Regions vary in expression patterns • Most genes are expressed in the brain • Many genes show patterns of expression that are regionally-specific • Many patterns are not clearly explained Brain Regions Brain Regions Coronal Set Genes that had marked regional expression patterns in the sagittal plane 4,261 image series 3,976 genes Used in AGEA Ng L, Bernard A, Lau C, Overly CC, Dong HW, Kuan C, Pathak S, Sunkin SM, Dang C, Bohland JW, Bokil H, Mitra PP, Puelles L, Hohmann J, Anderson DJ, Lein ES, Jones AR, Hawrylycz M. An anatomic gene expression atlas of the adult mouse brain. Nature Neuroscience 2009 Mar;12(3):356-62. My Projects Does gene expression carry information about connectivity at the brain region level? Characterization of anti-correlated patterns Global Mantel test analysis Can neuroanatomical connectivity information be automatically extracted from biomedical literature? Camk2a Pvalb Example anti-correlated gene pair ..with Patrick Tan Example anti-correlated gene pair Front (anterior) Back (posterior) ..withPatrick PatrickTan Tan ..with Principal Component Analysis 456 most anti-correlated gene pairs represent only 102 genes Pattern OE Genes Pattern NE Brain Regions Thoughts on PCA Hard to interpret Weighted gene list Signals can be spread across components Good for visualization of global patterns Interesting genes Pattern NE calcium/calmodulin-dependent protein kinase II alpha calbindin-28K Pattern OE carbonic anhydrase II S100b glutamine synthetase neurofilament high molecular weight None of the ABA regions used are white matter tracts (most are small nuclei) Pattern OE Pattern NE Cell-type specific expression *p-value < 0.05 **p-value < 0.005 Cahoy JD, Emery B, Kaushal A, Foo LC, Zamanian JL, Christopherson KS, Xing Y, Lubischer JL, Krieg PA, Krupenko SA, Thompson WJ, Barres BA. A transcriptome database for astrocytes, neurons, and oligodendrocytes: a new resource for understanding brain development and function. J Neurosci. 2008 Jan 2;28(1):264-78. Connectivity Data: Brain Architecture Management System Manually curated from tract tracing experiments in rat 961 brain regions 7,308 neuroanatomical connections Cerebellum Cerebrum Hindbrain Interbrain Midbrain Bota, M., H.W. Dong, and L.W. Swanson, Brain architecture management system. Neuroinformatics, 2005. 3(1): p. 15-48. Correlation with connectedness Evolution Only three pattern NE genes had a homolog in yeast, worm, or fly genomes 7.5%, p=0.00023 Pattern OE group had 23 (37%) 32% all coronal genes have yeast, worm, or fly homologs Expected amounts in human genome Can we do the same analysis at the brain region level? Pattern NE Pattern OE Neuron specific Functions linked to learning Anterior expression Expressed highly in regions with many connections Evolutionary recent Oligodendrocyte specific Functions linked to ion homeostasis, metabolism Posterior expression Expressed highly in regions with few connections My Projects Does gene expression carry information about connectivity at the brain region level? Characterization of anti-correlated patterns Global Mantel test analysis Can neuroanatomical connectivity information be automatically extracted from biomedical literature? Is there a relationship between gene expression patterns and connectivity? We might expect this if: Genes have to be expressed in patterns relevant to function that is “connection-specific” Adult patterns of expression “echo” patterns used during development to lay down connectivity Gene expression has a continued role in modulating connectivity Example - Dopaminergic neurons project to regions expressing dopamine receptors Two major sources of dopamine – VTA and substantia nigra Anders Björklund and Stephen B. Dunnett, Dopamine neuron systems in the brain: an update. Trends in Neurosciences. Volume 30, Issue 5, May 2007, Pages 194-202 Direct scope Hypothesis: Expression profiles of connected brain region pairs are more correlated than disconnected pairs Expression correlation versus connectivity Correlation of expression profiles p-value < 0.0001 Hypothesis: There is a statistical relationship between the connections and gene expression levels of individual brain regions. Inspiration Caenorhabditis Elegans Complete neuron level connectivity map Expression information for hundreds of genes at cellular level Varadan et al. 2006, Computational inference of the molecular logic for synaptic connectivity in C. elegans “Ultimately, we expect our approach to provide important clues for universal mechanisms of neural interconnectivity.” Kaufman et al. 2006, Gene Expression of Caenorhabditis elegans Neurons Carries Information on Their Synaptic Connectivity Identified a list of putative genes for predicting neural connectivity How to compare two brain regions? Comparing by distance Comparing by connectedness (No connection, or unknown connectivity) Shared connections Gene expression similarity correlation × 22,000 × 22,000 How to compare two brain regions? Expression processing Expression energy summarized to brain regions No cortex data Kept imageseries independent 22,771 rows All sagittal and coronal series Removed list of non-expressing genes Mantel test All brain region pairs Expression Data Connection Data Brain regions Brain regions Brain regions Brain regions Correlate matrices Comparing comparisons Brain regions Brain regions Brain regions Brain regions Wiring patterns resemble expression patterns We applied the Mantel test to assess the similarity of the gene expression and connectivity profiles 142 regions 2.5M gene expression values 100,000 connection values Correlation: 0.23 p-value < 0.001 Summary of results Distance 0.49 Gene Expression 0.32 0.23 p < 0.001 Shared Connections Spatial correction Distance 0 Gene Expression 0 0.13 p = 0.001 Shared Connections Connectivity and Expression relationships Greedy feature (gene) reduction Purkinje cell protein 2 How could it contain information about connectivity? Santiago Ramón y Cajal, 1899; Instituto Santiago Ramón y Cajal, Madrid, Spain. Single gene perspective, prediction? Functionally Enriched Gene Sets Primarily genes linked to development Axon guidance and genesis Cell migration Concordant with previous findings Genes that repress such functions Steroid hormone signaling Outgoing connectivity had more functional enrichment Clustered heatmap of top outgoing gene list Brain Regions Genes Semaphorin Axon Guidance Genes Linked to connectivity in our results Guide axon growth cones in combination with plexin receptors Continue to play roles in Axon regeneration Plasticity Enrichment of Autism candidate genes Human orthologs in AUTS1 locus (7q) Noticed from manual inspection Enrichment of genes from a autism research database 17 matched genes of 163 p < 0.0005 Increasing confidence Filtered top ranked gene sets for genes that are in the top ranked list more than once Chrm3, Vamp2, Nrtn, Tacr1, Trhr, Hs6st2, Gpc3... 5 of 30 have been linked in neurological disorders L1Cam (partial agenesis of the corpus callosum) Snca and Uchl1 (Parkinson’s disease) Cadps2 and Btg3 (autism disorder) Summary Expression patterns of neurodevelopmental genes carry information about connectivity Some of these genes play roles in maintenance or tuning of connectivity at finer scales Extracted patterns may be residue of a developmental process that is no longer active The patterns may be functionally relevant with respect to connectivity An interesting link between autism candidate genes and connectivity Conclusions Integration of large neuroinformatics resources provides new insight into the brain There are statistical relationships between gene expression and connectivity May be relevant to understanding plasticity in the adult nervous system or providing insights into development and disorders