In silico cis analysis
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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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In silico cis analysis

In silicocis-analysis

promoter analysis

Promoters and cis-elements

Searching for patterns

Searching redundant patterns


What is a promoter

What is a promoter?

  • and why care about it?

AAAAAAAA

CDS


A little about these

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%


Sound hard to find

Sound hard to find?

  • it is hard


Some tricks

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


A cis element

A cis-element

as it might be seen by a TF


So the elements may

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


Try it

Try it!

  • Find the exercise on the course page

  • Exercise: in silicocis-analysis


Mrnas overexpressed in mpk4 mutant

mRNAs OVEREXPRESSED IN mpk4 MUTANT


Gibbs sample evaluation

Gibbs sample evaluation

TTGACT

monte carlo

Gibbs sampling on 1000 random sampled sets of 17 Arabidopsis promoters, evaluated by information content.


Gibbs sample evaluation1

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


Lebel et al 1998

Lebel et al. 1998

Arabidopsis PR1 promoter


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