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.

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Genetics of gene expression primer

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

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