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In silico cis -analysis

In silico cis -analysis. promoter analysis Promoters and cis -elements Searching for patterns Searching redundant patterns. What is a promoter?. and why care about it?. AAAAAAAA. CDS. A little about these. cis-elements - Transcription Factors (TF) often bind to them

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In silico cis -analysis

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  1. In silicocis-analysis promoter analysis Promoters and cis-elements Searching for patterns Searching redundant patterns

  2. What is a promoter? • and why care about it? AAAAAAAA CDS

  3. A little about these • cis-elements • - Transcription Factors (TF) often bind to them • - They are normally from 5-10 bp long • - They are often placed in the region from TSS and upstream • Often they come in clusters i.e. must be placed in some ‘syntax’ to be functional • We assume, they are shared by the promoters in a regulon • They are not always conserved 100%

  4. Sound hard to find? • it is hard

  5. Some tricks Kolmogorov-Smirnov, here test for deviations from a uniform distribution of patterns along a sorted list og promoters Pattern Occurrence Hypergeometric Statistic Takeout 6 balls Promoters ranked by e.g. p-value 10x 5x 1x 5x p=0.04 • makes it possible • Regulon (cluster) • Comparing promoters from a regulon to all other promoters i.e. using a negative set (all other promoters in species X) This allows us to use hypergeometric statistics • Ranked list of genes • The distribution of sequences with a given pattern along a rank i.e. is the pattern overrepresented in promoters with low (or high) p-values in a microarray experiment This allows us to use Kolmogorov-Smirnov

  6. A cis-element as it might be seen by a TF

  7. So, the elements may weight matrix Motif model (residue frequency x 100): POS A C G T Info 1 89 . . . 1.0 2 . . 92 . 2.0 3 . . . 94 1.2 4 . 92 . . 2.0 5 94 . . . 1.2 6 94 . . . 1.2 • not always be 100% conserved • If we only had a weight matrice to describe our pattern we could find less conserved patterns • With a Gibbs sampler we can work backwards • We give it promoters and it builds a weight matrix

  8. Try it! • Find the exercise on the course page • Exercise: in silicocis-analysis

  9. mRNAs OVEREXPRESSED IN mpk4 MUTANT ● ● ● ● ● ● ● ● ● ● ● ●

  10. Gibbs sample evaluation TTGACT monte carlo Gibbs sampling on 1000 random sampled sets of 17 Arabidopsis promoters, evaluated by information content.

  11. Gibbs sample evaluation GACTTTTC monte carlo Gibbs sampling on 1000 random sampled sets of 17 Arabidopsis promoters, evaluated by information content. Here for 8bp patterns

  12. Lebel et al. 1998 Arabidopsis PR1 promoter

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