Integrative Genomics

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Integrative Genomics
Analysis and Functional Explanation
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Cost of Disease

• Most research in the bioscience is motivated by
  hope of disease intervention.

• Major WHO projects have tried to tabulate the
  costs of different diseases

Alan D Lopez, Colin D Mathers, Majid Ezzati, Dean
T Jamison, Christopher J L Murray Global and
regional burden of disease and risk factors,
2001 systematic analysis of population health
data Lancet 2006 367 174757

• Genetic Diseases are diseases where there is
  genetic variation in the susceptibility.

• Even small improvements would save many billions

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What is a bacteria? A human being?
From wikipedia
Central Dogma
DNA
RNA
Protein
Metabolism Cell Structure
Organism
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The Central Dogma Data
DNA
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Structure of Integrative Genomics
Concepts
Models Networks
Hidden Structures/ Processes
Evolution
Data Models Inference
Analysis
Functional Explanation
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G Genomes
Key challenge Making a single molecule
observable!!
Classical Solution (70s) Many
De Novo Sequencing Halted extensions or
degradation
80s From one to many PCR Polymerase Chain
Reaction
00s Re-sequencing Hybridisation to complete
genomes
Future Solution One is enough!!
Observing the behavior of the polymerase
Passing DNA through millipores registering
changes in current
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G Assembly and Hybridisation
Contigs and Contig Sizes as function of Genome
Size (G), Read Size (L) and overlap (Ø)
Lander Waterman, 1988 Statistical Analysis of
Random Clone Fingerprinting
Complementary or almost complementary strings
allow interrogation.
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E - Epigenomics
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T - Transcriptomics
Classical Expression Experiment
Measures transcript levels averaging of a set of
cells.
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T - Transcriptomics
Advantages - Discoveries
More quantitative in evaluating expression levels
More precise in positioning
Much more is transcribed than expected.
Wang, Gerstein and Snyder (2009) RNA-Seq a
revolutionary tool for Transcriptomics NATURE
REVIEwS genetics VOLUME 10.57-64
Transcription of genes very imprecise
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M - Metabonomics
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Concepts
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G?F

• Mechanistically predicting relationships
  between different data types is very difficult

• Empirical mappings are important

• Functions from Genome to Phenotype stands out
  in importance
• G is the most abundant data form -
  heritable and precise. F is of greatest interest.

Zero-knowledge mapping dominance, recessive,
interactions, penetrance, QTL,.
Mapping with knowledge weighting interactions
according to co-occurence in pathways.
Model based mapping genome?system?phenotype
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The General Problem is Enormous
Set of Genotypes

• In 1 individual, 3 107 positions could
  segregate.
• In the complete human population 5108 might
  segregate.
• Thus there could be 2500.000.00 possible
  genotypes

Partial Solution Only consider functions
dependent on few positions
Classical Definitions

• Multiple Loci

Epistasis The effect of one locus depends on the
state of another
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Genotype and Phenotype Covariation Gene Mapping
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Pedigree Analysis Association Mapping
Adapted from McVean and others
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Heritability Inheritance in bags, not strings.
The Phenotype is the sum of a series of factors,
simplest independently genetic and environmental
factors F G E
Relatives share a calculatable fraction of
factors, the rest is drawn from the background
population.
This allows calculation of relative effect of
genetics and environment
Visscher, Hill and Wray (2008) Heritability in
the genomics era concepts and misconceptions
nATurE rEvIEWS genetics volumE 9.255-66
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Heritability
Examples of heritability
Rzhetsky et al. (2006) Probing genetic overlap
among complex human phenotypes PNAS vol. 104
no. 28 1169411699
Visscher, Hill and Wray (2008) Heritability in
the genomics era concepts and misconceptions
nATurE rEvIEWS genetics volumE 9.255-66
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Protein Interaction Network based model of
Interactions
The path from genotype to genotype could go
through a network and this knowledge can be
exploited
Rhzetsky et al. (2008) Network Properties of
genes harboring inherited disease mutations PNAS.
105.11.4323-28
Groups of connected genes can be grouped in a
supergene and disease dominance assumed a
mutation in any allele will cause the disease.
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PIN based model of Interactions Emily et al, 2009
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Summary of this lecture
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P Proteomics
Cox and Mann (2007) Is Proteomics the New
Genomics? Cell 130,395-99
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P Proteomics
Hoog and Mann (2004) Proteomics Annu. Rev.
Genomics Hum. Genet. 52679
P uses Mass Spectrometry and 2D gel
electrophoresis of degraded peptides and Protein
Arrays using immuno-recognition of complete
proteins
http//www.hupo.org/