Array of plenty results from a 4 base resolution yeast genome tiling array
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array of plenty - results from a 4 base resolution yeast genome tiling array. Wolfgang Huber European Molecular Biology Laboratory EBI. Bioinformatics and Computational Biology Solutions Using R and Bioconductor, R. Gentleman, V. Carey, W. Huber, R. Irizarry, S. Dudoit. Springer (Aug. 2005).

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Array of plenty results from a 4 base resolution yeast genome tiling array

array of plenty - results from a 4 base resolution yeast genome tiling array

Wolfgang Huber

European Molecular Biology Laboratory

EBI


Array of plenty results from a 4 base resolution yeast genome tiling array

Bioinformatics and Computational Biology Solutions Using R and Bioconductor, R. Gentleman, V. Carey, W. Huber, R. Irizarry, S. Dudoit. Springer (Aug. 2005)

Topics:

microarray analysis

(meta)data integration

machine learning

graphs: for data, knowledge, & models


Bioconductor

Bioconductor

Core design: Robert Gentleman, Rafael Irizarry, Vince Carey, WH.

Release 1.6 contained 124 packages, current number is 140

Ca. 15,000 downloads from main website after each release. June 2005: 9009 unique visitors

User poll by Affymetrix: Bioconductor is 2nd-most popular third-party software… after MS-Excel.


Array of plenty results from a 4 base resolution yeast genome tiling array

Genechip S. cerevisiae Tiling Array

4 bp tiling path over complete genome

(12 Mio basepairs, 16 chromosomes)

Sense and Antisense strands

6.5·106 oligonucleotides

5 mm feature size

Chips manufactured by Affymetrix

Application + analysis by L. Steinmetz (EMBL/Stanford Genome Center) and W. Huber (EMBL/EBI)


Samples

Samples

Genomic DNA

Poly-A RNA (double enriched) from exponential growth in rich media

Total RNA from exponential growth in rich media

3 replicates each


Array of plenty results from a 4 base resolution yeast genome tiling array

RNA Hybridization


Array of plenty results from a 4 base resolution yeast genome tiling array

before

Probe specific response normalization

after


Array of plenty results from a 4 base resolution yeast genome tiling array

Probe specific response normali-zation

remove ‘dead’ probes


Segmentation

Segmentation

Two obvious options:

Smoothing and thresholding: simple, but estimates of transcript boundaries will be biasedand depend on expression level

Hidden Markov Model (HMM): but our “states” come from a continuum! Fiddly.

Our solution:

Fit a piecewise constant function

change point


The model

The model

t1,…, tS: change points

Y: normalized intensities

x: genomic coordinates

mk: level of k-th segment


Model fitting

Model fitting

Minimize

t1,…, tS: change points

J: number of replicate arrays

Complexity O(n2) through dynamical programming algorithm.

F. Picard et al., BMC Bioinformatics 6 (2005)

Bai+Perron, Journal of Applied Econometrics (2003)


Array of plenty results from a 4 base resolution yeast genome tiling array

Splicing


Array of plenty results from a 4 base resolution yeast genome tiling array

Unexpected Transcript Structure


Array of plenty results from a 4 base resolution yeast genome tiling array

Novel Transcripts


Array of plenty results from a 4 base resolution yeast genome tiling array

Novel Transcripts

Potential antisense regulator


Expressed features

Expressed Features

5646 ORFs with ≥ 7 probes

5306 (94%) above background in poly-A RNA

5192 (92%) in total RNA (FDR=0.001)

untranscribed: meiosis, sporulation

poly-A RNA: 9356k of 11360k (82.4%)

total RNA:8786k (77.2%)

Both: 9612k (84.3%)

… of which not annotated: 1559k (13.7%)

annotated total: 8997k of 12071k (74.5%)

Fraction of transcribed basepairs


Novel transcripts

Novel transcripts

Basis: multiple alignment of 4 yeast genomes: S.cerevisiae, S.bayanus, S.mikatae, S.paradoxus. Kellis et al. Nature (2003)

Conservation analysis: fraction of segments for which there is a multiple alignment; total tree length

Codon signature: 3-periodicity of mutation frequencies

novel transcribed segments

 untranscribed

<< annotated transcripts.

with Lee Bofkin, Nick Goldman


Antisense transcripts

Antisense transcripts

  • microtubule-mediated nuclear migration

  • cell separation during cytokinesis

  • cell wall

  • single-stranded RNA binding (all 5: NAB2, NAB3, NPL3, PAB1, SGN1)

  • (p<2x10-16)


Antisense transcripts nab2

Antisense transcripts: NAB2


Antisense transcripts nab3

Antisense transcripts: NAB3


Antisense transcripts pab1

Antisense transcripts: PAB1


Array of plenty results from a 4 base resolution yeast genome tiling array

Mapping of UTRs:


Utr lengths

UTR lengths


Conclusions

Conclusions

o Conventional microarrays: measure transcript levels

o High resolution tiling arrays: also transcript structure

introns, exons,

alternative transcription start sites

partial degradation

novel transcripts

new annotation

o Probe-response normalization: make signal comparable across probes – and hence across genes!

o Simple segmentation algorithm: well-developed theory, accurate estimation of change-points, including confidence intervals

o Software - from Bioconductor (also: CEL file import, normalization, further statistical testing)


Acknowledgements

Acknowledgements

Group

Oleg Sklyar

Jörn Tödling

Matt Ritchie Florian Hahne

Raeka Aiyar Ligia Bras

Tiling Array Project

Lars Steinmetz, Lior David, Marina Granovskaia, Lee Bofkin, Nick Goldman, Jörn Tödling

Joint Projects

Lars Steinmetz, EMBL HD, yeast transcriptomics & high-density tiling array

Michael Boutros, DKFZ, genetic interactions & HT-RNAi

Robert Gentleman, FHCRC Seattle, Bioconductor

Silke Sperling, MPI MG Berlin, heart development and ChIP-chip

Eileen Furlong, EMBL HD, muscle development and ChIP-chip

Alvis Brazma, EMBL EBI, microarray quality metrics

Funding

HFSP, EU, MRC, LGC / DTI,

NGFN / BMBF


Array of plenty results from a 4 base resolution yeast genome tiling array

Probe-specific response normalization

si probe-sequence specific response factor. Estimation: geometric mean of intensities from DNA hybridization

bi =b(si ) probe-sequence specific background. Estimation: for strata of probes with similar si, estimate b through location estimator of distribution of intergenic probes, then interpolate to obtain continuous b(s)


Array of plenty results from a 4 base resolution yeast genome tiling array

Defining Expressed Transcripts

Segments not overlapping any annotated features

Segments overlapping annotated features

Normal distribution


Array of plenty results from a 4 base resolution yeast genome tiling array

Model selection criteria

model family has just one parameter: no. of segments


Confidence intervals

Confidence Intervals

Di level difference

Qino. data points / unit t

Wi error variance (allowing serial correlations)

true and estimated change points

Vi(s)appropriately scaled and shifted Wiener process

(Brownian motion)

Bai and Perron, J. Appl. Econometrics 18 (2003)


Array of plenty results from a 4 base resolution yeast genome tiling array

Segments Statistics

Annotated 100% overlap

Annotated >50% overlap

Novel isolated - filtered

Novel isolated - unassigned

Novel antisense - filtered

Novel antisense - unassigned

length

level


Antisense transcripts npl3

Antisense transcripts: NPL3 (?)


Antisense transcripts sgn1

Antisense transcripts: SGN1 (?)


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