Computational Approaches to Transcriptome Signatures in the Human … · · 2016-09-04Computational Approaches to Transcriptome Signatures in the Human Brain Mike Hawrylycz,

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Computational Approaches to Transcriptome

Signatures in the Human Brain

Mike Hawrylycz, Ph.D.

February 18, 2016

Agilent Technologies eSeminar

| For Research Use Only. Not for use in diagnostic procedures.

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ALLEN Adult Human Atlas – Online tools

For Research Use Only. Not for use in diagnostic procedures.

| For Research Use Only. Not for use in diagnostic procedures.

An Anatomic Transcriptional Atlas of Glioblastoma

Puchalski, Shah, Miller, et al, submitted

Science

Ivy-Allen Glioblastoma atlas project http://glioblastoma.alleninstitute.org/

Only large data set to profile distinct anatomical structures of GBM using RNA-Seq and ISH, and machine learning annotation providing an invaluable resource.

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tum

or

Leadin

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dge

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seudopalis

adin

g c

ells

aro

und n

ecro

sis

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rovascula

r

pro

lifera

tion

“Proliferation” and “migratory” classes of stem cell markers correspond to two GBM subtypes: “classical” and “proneural.”

Our GBM atlas allows for computational assessment of anatomical composition of any bulk GBM samples.

CD44 EZH2

This novel finding is a potential simplification from current understanding.

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Allen Human Brain Atlas Platform

Hawrylycz, Lein, et

al, Nature, 2012

Lein, Hawrylycz,

Nature, 2014


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Allen Human Brain Atlas Platform


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Microarray Data Generation

Agilent 8x60K array, custom-designed by Beckman Coulter Genomics in conjunction

with the Allen Institute, was used to generate microarray data.

The array design included the existing 4x44K Agilent Whole Human Genome probe set

supplemented with an additional 16,000 probes.

At least two different probes were available for 93% of genes with EntrezGeneIDs

(21,245 genes). Probes were located on different exons as much as possible when

multiple probes were available for a gene. Other probes on the microarray were for

transcripts with UCSC IDs (1,852 transcripts) and Agilent IDs (1,268 transcripts).

An additional set of probes were included to overlap with the 1,000- and 60-gene sets

that were characterized by ISH for the 1,000 Gene Survey in Cortex and the Subcortex

Study, respectively, both of which are integrated into the Allen Human Brain Atlas

Total RNA in the amount of 50 ng per sample was sent to Beckman Coulter Genomics

for processing on Agilent 8x60K gene expression arrays.

RNA-Sequencing (RNA-Seq) data were generated for a selected set of 240 samples

(120 from each brain) representing 29 cortical and subcortical regions matched across

two brains (H0351.2001 and H0351.2002), using aliquots of the same total RNA

isolates used to generate microarray data.


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Spatial genomic landscape of gene classes


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Spatial Topography of the Neocortex Microarray and RNA-seq

Miller et al., BMC Genomics, 2014 For Research Use Only. Not for use in diagnostic procedures.

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Reproducible Differential Gene Expression: Six Brains

• Genes DE between

structures in at least 5 brains

• 96 regions

• Same direction

• FC > 3

• B&H p-value < 0.01


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The Genetic Geography of the Brain http://casestudies.brain-map.org/ggb

Tim Dolbeare For Research Use Only. Not for use in diagnostic procedures.

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The Genetic Geography of the Brain: Vignette

Tim Dolbeare

Anil Jegga, CCHMC For Research Use Only. Not for use in diagnostic procedures.

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Protocadherin 8 (PCDH8) Gene Expression in

Six Brains

Consistent expression pattern of an exemplary gene, PCDH8, across 96 brain regions for the six brains

(numbered 1-6). CTX: cortex; HP: hippocampus; AMG: amygdala; STR: striatum; HY: hypothalamus;

TH: thalamus; CB: cerebellum; P: pons; MB: midbrain; WM: white matter. Structures shown are a

subset of those in (A) with cortex reduced to its major lobes (FL: frontal lobe, OL: occipital lobe, TL:

temporal lobe, PL: parietal lobe).


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Differential Stability and the Brain

DS as average

Kendall Tau

DS versus mean

expression level and

variability

DS versus average

Pearson based metric

C


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Parvalbumin (PVALB), DS = 0.806 The most stable gene in human brain in this dataset.

Consistent expression pattern of an exemplary gene, across 96 brain regions for the six brains (numbered 1-6). CTX: cortex;

HP: hippocampus; AMG: amygdala; STR: striatum; HY: hypothalamus; TH: thalamus; CB: cerebellum; P: pons; MB:

midbrain; WM: white matter. Structures shown are a subset of those in (A) with cortex reduced to its major lobes (FL: frontal

lobe, OL: occipital lobe, TL: temporal lobe, PL: parietal lobe).

CKS2 (CDC28 Protein Kinase Regulatory

Subunit) DS = 0.245

Differential Stability and the Brain


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High DS Genes and the Brain Top 5th Percentile, n=864 genes


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Consistent patterning of Potassium channels

• Most stable gene

class, p<3.19e-12

• Span a broad

distribution of

anatomic patterns

and structural

markers.

• Can we classify or

describe these

patterns?


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Consensus Co-expression Patterns in Adult Brain


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Anatomic Architecture of 29 Modules


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Potassium Channels span Module types


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Modules span expression patterns of the brain

Maximum module correlation and DS

ρ>0.4 , 85.6% (14,856/17,349)

5 brains predicts module in 6th brain


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Genetic markers for eight

cortical cell types in postnatal

mouse were identified based

on differential expression of

RNA-seq derived

transcriptomes

Zhang Y, Chen K, Sloan S a, et al.

An RNA-Sequencing Transcriptome

and Splicing Database of Glia,

Neurons, and Vascular Cells of the

Cerebral Cortex. J Neurosci.

2014;34(36):11929–47.


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Canonical Genetic Signatures of the Adult Human Brain:

(M1-M16)


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Module Annotation: Anatomy, ontology, drug, disease


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Canonical Genetic Signatures of the Adult Human Brain:

(M1-M16)


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Module Annotation: Anatomy, ontology, drug, disease


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Module interaction: ontology, pathways, drug

targets, cancer gene sets


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Unique anatomical patterning of 48 high DS genes.

GNB4

PRSS23

TES

265 high DS genes uncorrelated with major patterns


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Module preservation from

human to mouse.

(A) Mouse-human module preservation index measuring

average within-module gene correlation in an anatomy-

independent fashion, showing highest preservation of the

most neuronal modules (M1, M2, M4).

(B) Conservation of anatomical patterning, defined as the

proportion of mouse genes correlated at > 0.4 to the

corresponding human module eigengene (green bars). A

subset of genes in each module are both poorly correlated to

the human eigengene (gray bars), but instead very highly

correlated to a different human module eigengene (> 0.8).

(C-H) Correspondence of module eigengene anatomical

patterning between human and mouse. Histogram

representation of ME pattern in human (blue) and mouse

(red), with overlap in green, demonstrating highly conserved

patterns for M4, M10, M12 and M19.


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Human Connectome Project

www.humanconnectome.org

Van Essen et al., 2013; Smith et al., 2013 For Research Use Only. Not for use in diagnostic procedures.

http://www.humanconnectome.org/

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Cortex DS and Functional Connectivity

Vilas Menon For Research Use Only. Not for use in diagnostic procedures.

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Taxonomies of Neocortical Cell Types

Anatomical/Morphology Transcriptomic

Data-driven taxonomy of neocortical neuron types

Large-scale quantitative phenotyping of single neurons in adult neocortex

Physiological


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Cell Types and Hierarchical Organization


Glia

GABA

Glutamatergic

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Genetics of Cell Type based on Cre Lines


Tasic, Menon et al.,

Nat. Neuroscience,

2016

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We wish to thank the Allen Institute founders, Paul

G. Allen and Jody Allen, for their vision,

encouragement, and support.

Acknowledgments External Collaborators

• Anil G. Jegga, Bruce J. Aronow,

Kenneth A. Berman, Cincinnati

Children’s Hospital Medical Center

• Matthew F. Glasser, Donna L.

Dierker, David C. Van Essen,

Washington University

• Pascal Grange, Xi’an Jiaotong-

Liverpool University

• Albert-László Barabási, Jörge

Menche, Northeastern University,

Central European University

• Jay Schulkin, Georgetown

University

• David R. Haynor, Lance Stewart,

University of Washington


Documents

Computational Approaches to Transcriptome Signatures in the Human … · · 2016-09-04Computational Approaches to Transcriptome Signatures in the Human Brain Mike Hawrylycz,