Transcript Document

Transcriptomics
Area Chair:
Martin Vingron
Max-Planck-Institute for
Molecular Genetics, Berlin,
Germany
Presentation:
Thomas Lengauer
Max-Planck-Institute for
Informatics, Saarbücken,
Germany
Transcriptomics = Study of
transcriptional products
• Determination of mRNA levels, i.e.
expression profiling
• Gene structure, alternative splicing
• Utilization of expression profiles for study
of biological mechanisms, disease
mechanisms
• Application of DNA arrays in chromatin
immuno precipitation – gene regulation
Technologies I
• Tagging the mRNA: ESTs, SAGE
• Quantitative PCR
Technologies II: Array based
• cDNA arrays, long oligo arrays: immobilize a
piece of DNA per gene. These are (usually) 2color arrays, i.e. two samples are labeled with
different dyes and hybridized
• Short oligo arrays (Affymetrix): immobilize
several short oligonucleotides per gene. These are
1-color arrays, i.e. one sample is hybridized at a
time
• Tiling arrays: spots do not correspond to genes.
Instead representative sequences for whole
genomic regions are spotted
Questions I
• Experimental design: How to get the most
information out of the least number of
hybridizations?
- Paper by Woo et al: Experimental Design for
Three-Color and Four-Color Gene Expression
Microarrays
Questions II
• What is the product of transcription?
– Gene structure and alternative splicing: Paper by Cline
et al: A Statistical Method for Detecting Splice Variants from
Expression Data
– Tiling arrays: Originally used for unbiased detection of
transcription. Now being used for identifying
transcription factor binding sites, see paper by Li et al:
A Hidden Markov Model for Analyzing ChIP-chip
Experiments on Genome Tiling Arrays and its Application to
p53 Binding Sequences
Questions III
• Use expression profiles to characterize, e.g.,
– Developmental states
– Disease states
– Leads to classification problem: Paper by
Soukup et al: Robust Classification Modeling on
Microarray Data Using Misclassification Penalized
Posterior
Questions IV
• Common change – common regulation?
– Clustering, coexpression: Paper by by Dueck et
al: Multi-way clustering of Microarray Data using
Probabilistic Sparse Matrix Factorization
– Is coexpression mediated by the same
transcription factor? Compare also paper on
regulation by Li et al