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CS 374: Relating the Genetic Code to Gene Expression

CS 374: Relating the Genetic Code to Gene Expression. Sandeep Chinchali. Outline. Basic Gene Regulation Gene Regulation and Human Disease Measurement Technologies Papers Future Trends. 1. Basic Gene REGULATION. Human Genome. 3 billion bases – 2% coding, 5-10% regulatory

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CS 374: Relating the Genetic Code to Gene Expression

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  1. CS 374: Relating the Genetic Code to Gene Expression SandeepChinchali

  2. Outline • Basic Gene Regulation • Gene Regulation and Human Disease • Measurement Technologies • Papers • Future Trends

  3. 1. Basic Gene REGULATION

  4. Human Genome • 3 billion bases – 2% coding, 5-10% regulatory • Organism’s complexity NOT correlated with number of genes! • Human (20-25k genes) vs. Rice (51k genes) • 1 million Regulatory elements enable: • Precise control for turning genes on/off • Diverse cell types (lung, heart, skin)

  5. Regulatory Elements • ~ 20-25k genes • Expression Modulated by ~ 1 Million cis-reg elements • Enhancer, Promoters, Silencers

  6. Controlling Gene Expression • Transcription factors (TFs): • Proteins that recognize sequence motifs in enhancers, promoters • Combinatorial switches that turn genes on/off

  7. Modulating Gene Expression Expression Quantitative Trait Locus (eQTL): • Regions where different genotypes correlate with changes in gene expression

  8. Chromatin Remodelling http://www.cropscience.org.au/icsc2004/symposia/3/1/1957_dennise-5.gif

  9. 2. Gene regulation and disease

  10. Disease Implications SHH • MUTATIONS • Brain • Limb • Other Bejerano Lab

  11. Limb Enhancer 1Mb away from Gene limb SHH Bejerano Lab

  12. Enhancer Deletion limb SHH • DELETE • Limb Bejerano Lab

  13. Enhancer 1bp Substitution limb SHH • MUTATIONS • Limb Lettice et al. HMG 2003 12: 1725-35 Bejerano Lab

  14. Genome Wide Assocation Study (GWAS): 80% of GWAS SNPs are noncoding (many are eQTLs) Bejerano Lab

  15. From eQTL to Disease T Allele specific binding may alter gene expression

  16. Outline • Basic Gene Regulation • Gene Regulation and Human Disease • Measurement Technologies • Papers • Future Trends

  17. Measurement technologies

  18. eQTLs: Correlating Genotype with Expression RNA-seq, Microarray SNP Array, WGS GTEX

  19. Measuring Open Chromatin http://hmg.oxfordjournals.org

  20. Measuring open chromatin – DNaseSeq Sequence open chromatin – map enhancers, promoters … wikipedia

  21. Statistical Overview • Given: Genotype + Expression Matrix • Problem: Determine eQTLs • Possible Solutions: • Regress homozygous/het genotypes with expression • Key Problem: • Of many linked SNPs, what is the causal variant? Enhancer

  22. Outline • Basic Gene Regulation • Gene Regulation and Human Disease • Measurement Technologies • Papers • Future Trends

  23. Paper 1: dISSECTING THE REGULATORY ARCHITECTURE OF GENE EXPRESSION QTLs

  24. Overview • HapMap cells + 1000G genotypes • Bayesian Model • Uncertainty over functional SNP • Prior: Whether SNP hits a functional element (TFBS, promoter, etc) • Upweight effect of SNPs in functional regions • Results: • eQTLs often in TFBS, open chromatin, not specifically overrepresented in TATA box

  25. METHODS

  26. 1. Associate SNPs with Gene Expression

  27. 2. Functional Annotation

  28. 3. Adjust p-value based on annotation

  29. RESULTS

  30. eQTNs are enriched in enhancers, promoters Active Promoter/Enhancer Inactive

  31. eQTNs are enriched in enhancers, promoters (2) What is the distribution of eQTNs in regulatory sites?

  32. eQTNs enriched in TF binding sites What TF families show the highest eQTN enrichments?

  33. Paper 2: DNase1 SENSITIVITY QTLS are a major determinant of human expression variation

  34. Overview • If an allele is correlated with changes in open chromatin, how often does it actually modulate gene expression? • dsQTL – DNase sensitive QTL • dsQTLvseQTL • Functional link between changes in chromatin accessibility, gene expression

  35. DNase Hypersensitive Region http://hmg.oxfordjournals.org

  36. dsQTL– genotype correlates with extent of open chromatin How does a dsQTL look?

  37. RESULTS

  38. In what proximity of gene’s TSS do dsQTLs occur?

  39. Changes in open chromatin associated with gene expression levels How might a dsQTL be an eQTL?

  40. Mechanisms of dsQTLs In which conformations are dsQTLs also eQTLs?

  41. cONClusion

  42. Future Trends • Denser genotyping + more expression measurements in variety of cell lines • Better power to detect eQTLs with more people • eQTLs with small effect sizes that additively disrupt disease pathways • Common disease, common variant hypothesis • Better annotating + understanding genome enhances selection of causal eQTNs

  43. Extra slides

  44. Connections to GWAS Joe Pickrell,, Joint analysis of functional genomic data and genome-wide association studies of 18 human traits

  45. Joe Pickrell,, Joint analysis of functional genomic data and genome-wide association studies of 18 human traits

  46. References • 30: http://stanfordcehg.wordpress.com/2013/12/06/which-genetic-variants-determine-histone-marks/

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