Download Tips for mining and integrating the Allen Mouse Brain Atlas data

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