identification of circadian clock genes by datamining microarray data

Introduction Promotor Analysis Identifying genes: Methods Identifying genes: Results

The Identification of Circadian Clock GenesBy Data Mining Microarray Data

Atreyi Banerjee and Martin Hunt

The University of Leicester

June 27, 2008


Outline

• Introduction

• How to find circadian clock genes

• Promotor Analysis


What is circadian rhythm?

Circadian circa (about) + dies (a day) Circadian rhythm is theself-sustained cycle with 24 hour period that controls rest/activitytime awareness, photosynthesis, etc. Common among eukaryotes(Neurospora, Drosophila, Mammals) Reserved for living organisms(daily traffic congestions is not a circadian rhythm) Circannual 1year period(e.g. migration)


Circadian rhythm properties

Circadian rhythm properties are conserved across plant and animalkingdom Basic properties of circadian rhythm: Endogenous freerunning period of 24 hours Synchronization of stimuli Period isunchanged with temperature Advantage: learn from studyingsimple organisms (Drosophila, Neurospora, Mouse) Mechanismsare similar but the genes are different The main cycling genes:PER, TIM, CLK, CYC, BMAL


Drosophila

Affymetrix gene chip (Drosgenome 1) assay Identifying circadiangenes Clustering and Heatmap Promoter analysis


Drosophila circadian oscillator


Circadian clock control in Drosophila

ADD REFERENCE


Experimentations

Drosophila entrained in 12:12 hour light dark (LD) cycle Then leftin complete darkness and analysed every 4 hours The final datasetincluded replicas of 4 chips CT0, CT4, CT8, CT12, CT16 andCT20


Outline

• Introduction

• How to find circadian clock genes



Promoter analysis

To detect genes having same regulatory mechanism Extracting the5’ untranslated region of the genes Finding out the overrepresented motifs in the sequences Finding out the cis-regulatorymodules (combination of binding sites) in sets of co-expressed orcoregulated genes Getting the putative transcription factor bindingsites (TFBS) Functional analysis


Effects of clock mutations on enhancers regulatingcircadian gene expression

Stempfl, T. et al. Genetics 2002;160:571-593


TOUCAN software

An interactive java display Map genes onto the Sequence set spaceFlexibilty of using any identifier(Affy ID, EMBL, Refseq etc)Perform statistical tests for finding regulatory sequences, selectingparts of sequences, finding CpG islands in metazoan genome


Predict instances of known motifs with MotifScanner


The Significant motifs found in each cluster


Predict cis-regulatory modules with MotifSampler

The co-expression of Dorsal 2 and Myf showing


The cis-regulatory modules in each cluster


The cis-regulatory module in genes listed with p-values


Genscan output of cluster 1


List of unknown TFBS found in each cluster


de novo discovery of unknown TFBS

MotifSampler tool in TOUCAN used to find unknown motifs whichcould be novel transcription factors The 5’UTR sequences alsoextracted from Ensembl Biomart The over represented TFBS wereextracted from MATCH and OTFBS Dorsal 2 and Myf were overrepresented modules ARNT also found in cycle an important clockgene, was located Genscan predicted genes in each cluster


Outline

• Introduction

• Identifying circadian clock genes



Identifying circadian genes: an outline

Microarray experiment

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Data (spreadsheet)

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Process data in R

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Data analysis in R

?List of circadian genes


Identifying circadian genes: an outline

Four methods considered, all of which were implemented in R:

GeneCycle based

• The Fisher Method (Wichert et al. 2004)

• The Robust Method (Ahdesmaki et al. 2005)

“Sine wave” based

• The M&R Method (McDonald & Rosbash 2001)

• The Sine Method


The Fisher Method

Implemented by the R package GeneCycle, based on Fouriermethods and Fisher’s g test

Time Series:

CT0 = 1.2

CT4 = 4.9

CT8 = 9.5

CT12 = 0.4

CT16 = 1.5

CT20 = −42

- Fisher’s g test - p-value = 0.3213

Repeat this process for each time series


The Fisher Method: FDR

Oops! We’ve carried out over 6000 multiple tests.The solution: false discovery rate (FDR) control, implemented bythe R package fdrtool

Definition

The FDR value is the percentage of false-positives we expect to befound in our results

0.011, 0.021, 0.042, 0.045, 0.056, 0.065, 0.066, . . .


The Robust Method

Also implemented by the R package GeneCycle


The M&R Method

The M&R Method


The Sine Method

The Sine Method


Heatmap: The Fisher Method

heatmap of Fisher method


Heatmap: The Robust Method


The Numbers

How many in genes in common between methods etc


Fisher Vs Sine Methods

what’s so different about them?


Conclusions

• Why only use sine waves as a model?

• Is FDR really better than multiple testing?

• Why use GeneCycle?


Conclusions

• All methods find some circadian clock genes

• . . . and some false positives

• Best approach: use many methods

• There is always a new, better method around the corner . . .

identification of circadian clock genes by datamining microarray data

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