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Talk: Genetic variation in gene regulation (34 min)

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X Navigable Slide Index
  1. Introduction
  2. Much of the basis of complex traits is noncoding
  3. GWAS hits due to non-synonymous variants
  4. eQTLs: expression Quantitative Trait Loci
  5. How do genetic variants influence expression?
  6. How do SNPs impact gene regulation?
  7. One major source of eQTL data is from GTEx
  8. HapMap cell lines as a model system
  9. RNA-seq studies identified thousand cis-eQTLs
  10. Example cis-eQTL from HapMap samples
  11. Some eQTLs affect individual exons only
  12. What is the molecular basis for cis-eQTLs?
  13. Genotype correlates with steady state expression
  14. Which site is causal
  15. Most eQTLs lie inside or very near target genes
  16. eQTLs affect regulators of chromatin function
  17. DNaseI sequencing
  18. DNase-seq in 70 HapMap cell lines
  19. Example dsQTL
  20. dsQTL due to disruption of an NF-KB binding site
  21. Binding is virtually eliminated from one haplotype
  22. dsQTL SNPs function
  23. Promoter SNP at SNX7 drives chromatin changes
  24. DNaseI sensitivity at dsQTLs and TF occupancy
  25. DNaseI sensitivity and nucleosome occupancy
  26. Causal links from DNA to chromatin function
  27. Disrupting transcription factor binding sequences
  28. Do TF affects histones?
  29. Histone marks
  30. PWM changes and allele-specific mark changes
  31. Model: closed and open configurations
  32. How do dsQTLs affect promoters and expression?
  33. How a SNP in SLFN5 affects DNaseI sensitivity
  34. This dsQTL also impacts expression of SLFN5
  35. dsQTLs drive remote chromatin activation
  36. SNPs, chromatin architecture and mRNA levels
  37. eQTLs and their effects on proteins
  38. Ribosomal profiling and mass spec
  39. Most eQTLs are preserved at protein level
  40. The effect sizes are smaller on protein
  41. Protein-specific QTLs act post-translationally
  42. Summary
  43. Acknowledgments
  44. END
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DETAILED SLIDE INDEX

  1. 1. Introduction
  2. 2. Much of the basis of complex traits is noncoding
  3. 3. GWAS hits due to non-synonymous variants
  4. 4. eQTLs: expression Quantitative Trait Loci
  5. 5. How do genetic variants influence expression?
  6. 6. How do SNPs impact gene regulation?
  7. 7. One major source of eQTL data is from GTEx
  8. 8. HapMap cell lines as a model system
  9. 9. RNA-seq studies identified thousand cis-eQTLs
  10. 10. Example cis-eQTL from HapMap samples
  11. 11. Some eQTLs affect individual exons only
  12. 12. What is the molecular basis for cis-eQTLs?
  13. 13. Genotype correlates with steady state expression
  14. 14. Which site is causal
  15. 15. Most eQTLs lie inside or very near target genes
  16. 16. eQTLs affect regulators of chromatin function
  17. 17. DNaseI sequencing
  18. 18. DNase-seq in 70 HapMap cell lines
  19. 19. Example dsQTL
  20. 20. dsQTL due to disruption of an NF-KB binding site
  21. 21. Binding is virtually eliminated from one haplotype
  22. 22. dsQTL SNPs function
  23. 23. Promoter SNP at SNX7 drives chromatin changes
  24. 24. DNaseI sensitivity at dsQTLs and TF occupancy
  25. 25. DNaseI sensitivity and nucleosome occupancy
  26. 26. Causal links from DNA to chromatin function
  27. 27. Disrupting transcription factor binding sequences
  28. 28. Do TF affects histones?
  29. 29. Histone marks
  30. 30. PWM changes and allele-specific mark changes
  31. 31. Model: closed and open configurations
  32. 32. How do dsQTLs affect promoters and expression?
  33. 33. How a SNP in SLFN5 affects DNaseI sensitivity
  34. 34. This dsQTL also impacts expression of SLFN5
  35. 35. dsQTLs drive remote chromatin activation
  36. 36. SNPs, chromatin architecture and mRNA levels
  37. 37. eQTLs and their effects on proteins
  38. 38. Ribosomal profiling and mass spec
  39. 39. Most eQTLs are preserved at protein level
  40. 40. The effect sizes are smaller on protein
  41. 41. Protein-specific QTLs act post-translationally
  42. 42. Summary
  43. 43. Acknowledgments
  44. 44. END

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TALK'S CITATION

Pritchard, J. (2015), "Genetic variation in gene regulation", in Rosenberg, N. and Nielsen, R. (eds), Human Population Genetics II, The Biomedical & Life Sciences Collection, Henry Stewart Talks Ltd, London (online at http://hstalks.com/?t=BL1963921)

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ABOUT THIS TALK

Speaker(s)

Prof. Jonathan Pritchard Show Biography

SPEAKER BIOGRAPHY

Prof. Jonathan Pritchard – Stanford University, USA

Jonathan Pritchard's lab at Stanford University works in population genetics and genomics, with a particular focus on understanding how genetic variation drives variation in gene regulation, and the implications for understanding disease and evolution. He received his undergraduate training in Biology and Mathematics at Penn State University, his PhD in Biology at Stanford, and completed a postdoc at the University of Oxford. He joined Stanford University in 2013 after 12 years on the faculty at the University of Chicago.

Publication Date

April, 2015

Topics Covered

Expression Quantitative Trait Loci: linking genetic variation to changes in gene regulation... more

TOPICS COVERED IN THIS TALK

  • Expression Quantitative Trait Loci: linking genetic variation to changes in gene regulation
  • How do SNPs impact gene regulation
  • HapMap cell lines as a model system for studying expression variation
  • eQTL analysis
  • dsQTL
  • Histone marks
  • Protein-specific QTLs

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