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Genetics of gene expression primer

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Broad Institute/MPG primer lecture given 2008-12-11. Thanks to Alkes Price and Steve McCarroll for contributing slides.

Broad Institute/MPG primer lecture given 2008-12-11. Thanks to Alkes Price and Steve McCarroll for contributing slides.

Published in: Technology, Health & Medicine

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  • 1. Genetics of Gene Expression
      • Chris Cotsapas
      • [email_address]
  • 2. Outline
    • Background
      • Significance
      • Experimental design
      • Definitions
    • Basic findings
    • Tissue specificity
    • Population differences
    • Biological insight (?)‏
    • Last thoughts
  • 3. In the beginning...
    • King and Wilson, Science 1975
    • Chimp – human coding sequence differences don't match phenotypic distance
    • Gene regulation responsible for rest?
    • Basis for evo-devo, GGE
  • 4. Genetics of gene expression
    • Find genetic variation that (partially) controls levels of RNA
    • If RNA levels are different, maybe protein levels are also different
    • If protein concentration is different, maybe there is a phenotype?
  • 5. Experimental design
    • Protein measurements
      • 2D gels; quantitation hard; resolution?
    • RNA measurements
      • Expression chips ca. 1995 (Schena et al , Science)‏
  • 6. Experimental design - methods
    • Allelic discrimination
      • SBE
      • Pyrosequencing
      • SNP arrays
    • Whole-genome expression assays
    • Genotypes?
  • 7. Experimental design - samples
    • Pedigrees – multiplex/trios
      • HapMap
    • Population samples
    • Inbred strain panels
      • genotypes
    • New crosses
    • Inter-specific hybrids
  • 8. Definitions Cis Trans
  • 9. Outline
    • Background
    • Basic findings
    • Tissue specificity
    • Population differences
    • Biological insight (?)‏
    • Last thoughts
  • 10. First forays
    • Damerval et al 1994
    • Protein levels are different in 42/72 maize gene products
    • 2D electrophoresis, eyeball spot quantitation
    • Problems:
      • genome coverage
      • quantitation
      • post-translational modifications
  • 11. Cowles et al 2002
    • F1 mice
    • 69 genes in three tissues
    • 4 variant; 2 only in liver
  • 12. Yeast WG approaches
    • Brem et al Science 2002
    • Linkage in 40 offspring of lab x wild strain cross
    • 1528/6215 DE between parents
    • 570 map in cross
      • multiple QTLs
      • 32% of 570 have cis linkage
    • 262 not DE in parents also map
  • 13. Trans hotspots Brem et al Science 2002
  • 14. Yvert et al Nat Genet 2003
  • 15. Mammals I
    • F2 mice on atherogenic diet
    • Expression arrays; WG linkage
    Schadt et al Nature 2003
  • 16. Mammals II Chesler et al Nat Genet 2005 10% !!
  • 17. Mammals III
    • No major trans loci in humans
      • Cheung et al Nature 2003
      • Monks et al AJHG 2004
      • Stranger et al PLoS Genet 2005, Science 2007
      • Further scans (WT, Cheung, Schadt etc)‏
  • 18. What's the deal with trans ?
    • Artefacts
      • Normalization robustness
      • Replication?
      • Clusters of correlated genes
    • Power
      • trans often weak effects
      • Small sample sizes
  • 19. Outline
    • Background
    • Basic findings
    • Tissue specificity
    • Population differences
    • Biological insight (?)‏
    • Last thoughts
  • 20.
    • trans -acting factors may be tissue specific
      • TFs, signalling molecules, etc etc
    • cis regulatory sequences may be used by TS factors
    • So, shouldn't genetic effects on GE be tissue specific?
    Logic
  • 21. Examples
    • Chesler vs Bystrykh (Nat Genet 2005)‏
      • 39/101 (39%) forebrain cis in HSC
      • 297/1218 (24%) HSC cis in forebrain
    • Hubner (Nat Genet 2005)‏
      • 311/4297 (7%) shared between fat and kidney
    • Campbell et al (Gen Res 2008)‏
      • 12% of ~100 genes vary in at least one of three tissues
  • 22. Correlation networks persist across tissues
  • 23. Outline
    • Background
    • Basic findings
    • Tissue specificity
    • Population differences
    • Biological insight (?)‏
    • Last thoughts
  • 24. Slide courtesy Alkes Price
  • 25. Population differences could have non-genetic basis • Differences due to environment? (Idaghdour et al. 2008)‏ • Differences in cell line preparation? (Stranger et al. 2007)‏ • Differences due to batch effects? (Akey et al. 2007)‏ (Reviewed in Gilad et al. 2008)‏ Slide courtesy Alkes Price
  • 26. Gene expression experiment Does gene expression in 60 CEU + 60 YRI vary with ancestry? Does gene expression in 89 AA vary with % Eur ancestry? 60 CEU + 60 YRI from HapMap, 89 AA from Coriell HD100AA Gene expression measurements at 4,197 genes obtained using Affymetrix Focus array c Slide courtesy Alkes Price
  • 27. Gene expression differences in African Americans validate CEU-YRI differences c = 0.43 (± 0.02)‏ ( P -value < 10 -25 )‏ 12% ± 3% in cis Slide courtesy Alkes Price
  • 28. Outline
    • Background
    • Basic findings
    • Tissue specificity
    • Population differences
    • Biological insight
    • Last thoughts
  • 29. Does GGE matter?
    • Where is the phenotype?
      • Case/control differences?
    • Does it translate to protein?
    • Can we reconstruct networks/pathways?
  • 30. Insight
    • Mechanism?
    • trans – coregulated groups?
      • pathways
    • Model QTs
    • Molecular variation snapshots
      • What does it mean?
    • Ancillary information
  • 31. IRGM harbors a 20-kilobase deletion polymorphism immediately upstream IRGM Individuals Position on chr5 Slide courtesy Steve McCarroll McCarroll et al., Nature Genetics , Sept. 2008 rs13361189 (strongest Crohn’s-associated SNP)‏
  • 32. IRGM structural haplotypes have altered expression Slide adapted, courtesy Steve McCarroll McCarroll et al., Nature Genetics , Sept. 2008
  • 33. IRGM expression levels influence the efficacy of autophagy McCarroll et al., Nature Genetics , Sept. 2008 Slide adapted, courtesy Steve McCarroll
  • 34. Outline
    • Background
    • Basic findings
    • Tissue specificity
    • Population differences
    • Biological insight (?)‏
    • Last thoughts
  • 35. Success?
    • Baseline variation - tricky
    • Perturbations and phenotypes
      • mouse obesity crosses (Schadt et al )‏
      • Drug screening (Choi, Yelensky et al )‏
      • Crohn's disease (McCarroll et al )‏
  • 36. Stuff we haven't covered
    • Coregulated sets
    • Disease context
    • Annotation/pathway analysis
    • Modelling QTLs
    • Regression
    • WGAS
    • Multiple data sets/types
    • Post-transcriptional event variation
  • 37.  
  • 38.  

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