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Data visualization in the post-genomics era Carol Morita Genentech, Inc.
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Data visualization in the post-genomics era Carol Morita Genentech, Inc.

Dec 20, 2015

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Page 1: Data visualization in the post-genomics era Carol Morita Genentech, Inc.

Data visualization in the post-genomics era

Carol MoritaGenentech, Inc.

Page 2: Data visualization in the post-genomics era Carol Morita Genentech, Inc.

Pre-Genomics: assembling the pieces

Genome project initiated

GenBank

Page 3: Data visualization in the post-genomics era Carol Morita Genentech, Inc.

Where we are today

Organism Size (bp) # genes

E.coli (bacteria) 4.67 million 3,237

Arabidopsis (plant) 100 million 25,000

C. elegans (worm) 97 million 19,099

Drosophila (fly) 136 million 13,061

Mouse 3 billion ~40,000

Human 3 billion ~40,000

Page 4: Data visualization in the post-genomics era Carol Morita Genentech, Inc.

American view of the genome

Entrez Genome Browser

National Center for Biotechnology InformationNational Institutes of Health

http://www.ncbi.nlm.nih.gov:80/PMGifs/Genomes/euk_g.html

Page 5: Data visualization in the post-genomics era Carol Morita Genentech, Inc.
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Page 8: Data visualization in the post-genomics era Carol Morita Genentech, Inc.

European view of the genome

Ensembl Genome Browser

European Molecular Biology Laboratoryhttp://www.ensembl.org/

Page 9: Data visualization in the post-genomics era Carol Morita Genentech, Inc.
Page 10: Data visualization in the post-genomics era Carol Morita Genentech, Inc.
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Page 13: Data visualization in the post-genomics era Carol Morita Genentech, Inc.

What the genomes of model organisms tell us

Maturation 10 days 9 weeks 20-25 years

Genome 165 million bp 3 billion bp 3 billion bp

Genes 13,600 ~40,000 ~40,000

Almost every human gene has a counterpart in the mouse and some blocks of DNA are proving impossible to tell apart

Page 14: Data visualization in the post-genomics era Carol Morita Genentech, Inc.

If we are so similar genetically,why are we so different?

Human genes mapped onto mouse chromosomes

Page 15: Data visualization in the post-genomics era Carol Morita Genentech, Inc.

Proteomics: the real work begins

Definition: Description and functional characterization of the full complement of an organism’s proteins

what’s at play…

– Multiple proteins can be derived from one gene

– Protein interactions can be complex and are poorly understood

– ‘Plasticity’ of the genome

– Spatial and temporal regulation

Page 16: Data visualization in the post-genomics era Carol Morita Genentech, Inc.

Increased diversity due to alternative splicing

gene A

Page 17: Data visualization in the post-genomics era Carol Morita Genentech, Inc.

Alternative splicing

• Plays an important role in:– expanding protein diversity– generating proteins with subtle or opposing

functional roles– enabling an organism to respond to

environmental pressures

• >35% of human genes undergo alternate splicing; probably higher

Page 18: Data visualization in the post-genomics era Carol Morita Genentech, Inc.

Complexity due to protein interactions

Death Receptor Signaling pathway

Page 19: Data visualization in the post-genomics era Carol Morita Genentech, Inc.

DNA Microarrays

Microarray chips may contain 50,000

known DNA fragments on a single slide

Page 20: Data visualization in the post-genomics era Carol Morita Genentech, Inc.

Visualizing microarray data

Source: Silicon Genetics: GeneSpring

Page 21: Data visualization in the post-genomics era Carol Morita Genentech, Inc.

Limitations of DNA microarrays

• ‘snapshots’ of the DNA activity in a cell -- prefer movies!

• Many important biological events cannot be detected because transcription of DNA is not involved

• Protein array technology is still in its infancy

Page 22: Data visualization in the post-genomics era Carol Morita Genentech, Inc.

Source: Klausner, 2002 Cancer Cell1, p. 3-10

The curse of dimensionality