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Goal. Once we have the ability to examine gene expression (please keep in mind that this is mRNA abundance) at the genomic level –what are some of the questions we would ask? What transcription factors (TFs) are doing this What is the dynamic of TF binding and activation

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Presentation Transcript
Goal
Goal

  • Once we have the ability to examine gene expression (please keep in mind that this is mRNA abundance) at the genomic level –what are some of the questions we would ask?

    • What transcription factors (TFs) are doing this

    • What is the dynamic of TF binding and activation

    • How do TFs work together


Background
Background

  • TFs bind to promoters

  • Recruit other TFs, including chromatin-modifying proteins (histone acetylases, etc.)

  • A small sample of this analysis had been done either looking at expression of genes in TF mutants or Chromatin Immuno-precipitation


Goal
ChIP

  • Isolate chromatin with tagged TF

  • Reversible cross link of protein to DNA

  • Shear DNA

  • Immunoprecipitate protein-DNA complex

  • Reverse cross linker

  • Label DNA

  • Hybridize to intergenic DNA microarrays


Methods
Methods

  • Added myc tag to 141 transcription factors

  • Checked expression with PCR, protein with western blot (have myc antibody)

    • Could detect 106 of 124 by western blot!

  • 17 constructs couldn’t be recovered (mcy tag interfered significantly with their activity – these are essential proteins)


Assay
Assay

  • ChIP has many false positives

  • Did experiments in triplicate in YPD

  • Looked at ratio of IP-DNA to control DNA

  • Used Rosetta error model

  • Were concerned about errors: cell populations, DNA binding factors capable of binding specifically and non-specifically, and the expectation of noise.



Distribution of transcription factors
Distribution of transcription factors

37% bound by at least one

Average = 38


Network motifs
Network motifs


Results
Results

  • Found 10 autoregulated genes – suggests 10% of the genes are autoregulated

  • Found 3 multicomponent loops – could be bistable, i.e. have two alternative states

  • Found 39 regulators in 49 feed forward loops potentially controlling 240 genes


Ribosomal protein genes

Fkh1p forms a single-input regulatory motif

(look up recent Struhl paper about ribosomal proteins)

Also, multi-input involving Fkh1p

Ribosomal protein genes


Assembling motifs into network structures
Assembling motifs into network structures

  • Define G genes bound by S regulators with a P value threshold of .001

  • Look for other genes with similar expression patterns

  • Examine these genes to see if S regulators are bound to them


Go to the website for more discussion
Go to the website for more discussion

  • Could check more TFs

  • Could check other growth conditions

  • May be too rigorous in excluding false negatives