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  1. Biology of transcription factors Lecture5 Dec 2012 Regulatory Genomics Weizmann Institute Prof. Yitzhak Pilpel

  2. First home-assignmentRead this paper: Proc Natl Acad Sci U S A. 2006 Oct 3;103(40):14724-31. Epub 2006 Sep 26.

  3. Necessity Sufficiency Hierarchy TF-TF interaction Ho et al. Nature. 2002 Deduced network Properties - 1 - 0 . 5 . Correlation 0 0 . 5 G 2 G 1 1 M bp 1 M C B M S E Ndt80 U R S 1 Ume6 S C B Swi4 M C M 1 ' M C M 1 ' S F F ' Fkh1 0 . 2 0 . 4 Expression Coherence 0 . 6 0 . 8

  4. Detect the effect of mutations in a motif

  5. Foxp2 TF: a human regulator involved in speech • In humans, mutations of FOXP2 cause a severe speech and language disorder. • Positive selection for variability in human compared to other vertebrates.

  6. Some typical expression patterns

  7. A Bayesian approach (conditional probability) • Xi could be“1” to denote denot: • The presences of motif m • Its distance from TSS is < N • Its on the coding strand • It neighbors another motif m’ • Or “0” otherwise ei = being expressed in pattern i

  8. Example: two rRNA processing motifs The two motifs Work together The two motifs’ orientation matters

  9. The procedure • Given that P(N|D)=P(N)*P(D|N) / P(D): • Search in the space of possible Ns to look for a network that maximizes the above probability • Impossible to enumerate all possible networks, thus needs an optimization algorithm • Use cross validation: partition the data into 5 gene sets, learn the rules based on all but one and test based on the left-out, each time.

  10. For example: what does it take to belong to expression patter (4)? • Need to have RRPE and PAC • If PAC is not within 140 bps from ATG , but RRPE is within 240 bps then the probability of pattern 4 is 22% • If PAC is within 140 and RRPE is within 240 bp then 100% chance

  11. Regulation of basal transcription in the promoter of IL-18 binding protein (Hurgin V, Novick D, Rubinstein M, PNAS 2002 ) L R Luc (1.0) ‚  pGL3( 1 272) ƒ ƒ Luc ‚ pGL3(1272 mGAS) ƒ ƒ Luc ƒ ƒ  Luc pGL3(1272 mIRF-E) ‚ ƒ  pGL3(1272 mC/EBP-E1) Luc pGL3(1272 mC/EBP-E2) ƒ ‚  Luc ‚  Luc pGL3(122) -1500 -1000 -500 -1 0 10 20 30 40 bp Basal expression For basal expression (1 AND 2) AND ((3L AND 3R) OR (NOT3L and NOT3R))

  12. Inferring various logical conditions (“gates”) on motif combinations

  13. The Bayesian network predicts very accurately expression profiles

  14. Can make useful predictions in worm

  15. Motif discovery from evolutionary conservation data

  16. S. Cerevisiae S. mikatae, S. kudriavzevii, S. bayanus). S. castellii S. Kluyveri Their intergenicsequences spanned 40 to 67% identity

  17. Nucleotide conservation in promoters is highest close to the TSS TATA-containing genes All genes

  18. A set of discovered motifs

  19. Expression coherence score, intuition 1 2 * * EC1=0 EC2=0.66 * * * * * * * * * 3 4 * * * * * * * * * * * * * * EC3=0.2 EC4=0.2 * * * * * * Threshold distance, D

  20. ? ? ? ? ?

  21. NATURE | VOL 434 | 17 MARCH 2005

  22. The data • Examined intergenic regions of human mouse rate and dog • ~18,000 genes • “Promoters”: 4kb centered on TSS • 3’UTRs based on RNA annotations • 64 Mb, and 15 Mb in total respectively for promoters and 3’ UTRs • Negative control: Introns of ~120 Mb • % of alignable sequence: • promoters: 51% (44% upstream and 58% downstream of the TSS), • 3’ UTR: 73%, • Introns:34%, • Entire genome: 28%

  23. The phylogenetic trees • Questions: • How would addition of species affect analyses? • What if the sequences were not only mammalian?

  24. An example: a known binding site of Err-a in the GABPA promoter • Questions: • What is the “meaning” of the other conserved positions?

  25. Discovery of new motifs: exhaustive enumeration of all 6-mers

  26. Discovery of new motifs: exhaustive enumeration of all 6-mers

  27. Targets of new motifs showed defined expression patterns

  28. Motifs often show clear positional bias – close to TSS

  29. Same methods to look for motifs in 3’ UTRs reveals strand-specific motifs

  30. Nat Rev Genet. 2009 Apr;10(4):252-63

  31. The most studied human TFs: a sever bias towards disease-related regulators

  32. The most TF-regulated biological process: most knowledge comes from model organisms

  33. A few structural families account for most human TFs From motif to TF fold? Structure function relationship: homeodomain-containing TFs are often associated with developmental processes, and those in the interferon regulatory factor family are generally associated with triggering immune responses against viral infections

  34. TFs expression across tissues: TFs are always more lowly expressed compared to other genes in the same tissue. Why?

  35. Most TFs are either tissue specific or very ubiquitous. What types of combinations between TFs do we expect here?

  36. First home-assignmentRead this paper: Proc Natl Acad Sci U S A. 2006 Oct 3;103(40):14724-31. Epub 2006 Sep 26.

  37. A hierarchy of regulators

  38. The phylogenetic profiles of human TFs For example: 13% of the human TFs are primate specific, while only 2% of our metabolic enzymes are primate specific

  39. The chromosomal arrangement of the human TFs High TF density Hox TFs