A Systematic approach to the LargeScale Analysis of GenotypePhenotype correlations

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A Systematic approach to the Large-Scale Analysis
of Genotype-Phenotype correlations
Paul Fisher Dr. Robert Stevens Prof. Andrew Brass
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Genotype

• The entire genetic identity of an individual that
  does not show any outward characteristics, e.g.
  Genes, mutations

Genes
DNA
Mutations
ACTGCACTGACTGTACGTATATCT ACTGCACTGTGTGTACGTATATCT
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Phenotype

• (harder to characterise)
• The observable expression of genes producing
  notable characteristics in an individual, e.g.
  Hair or eye colour, body mass, resistance to
  disease

vs.
Brown
White and Brown
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Genotype to Phenotype
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Current Methods
Genotype
Phenotype
200
?
What processes to investigate?
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Phenotype
Genotype
200
?
Metabolic pathways
Phenotypic response investigated using microarray
in form of expressed genes or evidence provided
through QTL mapping
Genes captured in microarray experiment and
present in QTL (Quantitative Trait Loci ) region
Microarray QTL
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Issues with current approaches
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Huge amounts of data
QTL region on chromosome
Microarray
1000 Genes
200 Genes
How do I look at ALL the genes systematically?
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Hypothesis-Driven Analyses
200 QTL genes
Pick the genes involved in immunological process
Case African Sleeping sickness - parasitic
infection - Known immune response
40 QTL genes
Pick the genes that I am most familiar with
2 QTL genes

• Result African Sleeping sickness
• Immune response
• Cholesterol control
• Cell death

Biased view
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Manual Methods of data analysis
No explicit methods
Tedious and repetitive
Human error
Navigating through hyperlinks
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Implicit methods
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Issues with current approaches

• Scale of analysis task
• User bias and premature filtering
• Hypothesis-Driven approach to data analysis
• Constant flux of data - problems with
  re-analysis of data
• Implicit methodologies (hyper-linking through web
  pages)
• Error proliferation from any of the listed issues
• Solution Automate through workflows

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The Two Ws

• Web Services
• Technology and standard for exposing code /
  database with an means that can be consumed by a
  third party remotely
• Describes how to interact with it
• Workflows
• General technique for describing and executing a
  process
• Describes what you want to do

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Hypothesis

• Utilising the capabilities of workflows and the
  pathway-driven approach, we are able to provide a
  more
• - systematic
• - efficient
• - scalable
• - un-biased
• - unambiguous
• the benefit will be that new biology results
  will be derived, increasing community knowledge
  of genotype and phenotype interactions.

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QTL mapping study
Microarray gene expression study
Statistical analysis
Identify genes in QTL regions
Identify differentially expressed genes
Genomic Resource
Annotate genes with biological pathways
Annotate genes with biological pathways
Pathway Resource
Workflow methods
Select common biological pathways
Hypothesis generation and verification
Wet Lab
Literature
Manual methods
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Replicated original chain of data analysis
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Trypanosomiasis in Africa
Steve Kemp
Andy Brass
many Others
http//www.genomics.liv.ac.uk/tryps/trypsindex.htm
l
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Preliminary Results

• A strong candidate gene was found for
  Trypanosomiasis resistance DAXX
• Daxx not found using manual investigation methods
• The gene was identified from analysis of
  biological pathway information
• Sequencing of the Daxx gene in Wet Lab showed
  mutations that changed the structure of the
  protein
• Mutation was published in scientific literature,
  noting its effect on the binding of Daxx protein
  to another protein other protein controls one
  of the phenotypes of Trypanosomiasis resistance
• FOUND NEW BIOLOGY !!!!

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Recycling, Reuse, Repurposing
Now the e-Science!

• Trypanosomiasis mouse workflow reused without
  change in Trichuris muris infection in mice
• Identified biological pathways involved in sex
  dependence
• Previous manual two year study of candidate genes
  had failed to do this.

- Social networking for scientists
Workflows now being run over Colitis/
Inflammatory Bowel Disease in Mice (without
change)
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What next?

• More use cases??
• Can be done, but not likely for my project
• Text Mining !!!
• Aid biologists in identifying novel links between
  pathways
• Link pathways to phenotype through literature

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To Sum Up .

• Need for Genotype-Phenotype correlations with
  respect to disease control
• High-throughput data can provide links between
  Genotype and Phenotype
• Highlighted issues with manually conducted in
  silico experiments
• Improved the methods of current microarray and
  QTL based investigations through systematic
  nature
• Increased reproducibility of our methods
• - workflows stored in XML based schema
• - explicit declaration of services, parameters,
  and methods of data analysis
• Shown workflows are capable of deriving new
  biologically significant results
• African Trypanosomiasis in the mouse
• Infection of mice with Trichuris muris
• The workflows require expansion to accommodate
  new analysis techniques text mining

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Many thanks to
including Joanne Pennock, EPSRC, OMII, myGrid,
and lots more people