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Inferring Transcriptional Regulation Using Transctiptomics Carsten O. Daub September 1 st, 2014 StratCan Summer School 2014 Vår Gård, Saltsjöbaden.

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Presentation on theme: "Inferring Transcriptional Regulation Using Transctiptomics Carsten O. Daub September 1 st, 2014 StratCan Summer School 2014 Vår Gård, Saltsjöbaden."— Presentation transcript:

1 Inferring Transcriptional Regulation Using Transctiptomics Carsten O. Daub September 1 st, 2014 StratCan Summer School 2014 Vår Gård, Saltsjöbaden

2 Overview – Levels of Regulation Genome –SNP –DNA modifications (e.g. methylation) –structural alterations (e.g. genomic rearrangements) Transcriptome –Transcription factors, enhancers/ insulators –Promoter –RNA splicing –miRNA –Posttranscriptional modifications (e.g. RNA editing) –3D structure of the genome Protein –Translation –Posttranslational modifications Metabolites

3 Central Dogma of Molecular Biology DNA RNA Protein Francis Crick, 1958 Transcription Translation Non coding RNA

4 What is the transcriptome? The ensemble of all expressed RNA Protein coding genes Non-protein coding genes

5 How is the Transcriptome regulated? Via Promoter –Transcription factors –enhancers –insulators RNA splicing miRNA Posttranscriptional modifications (e.g. RNA editing) 3D structure of the genome

6 Regulation via the Promoter

7 Transcription The principle: DNA is copied into RNA by the RNA polymerase (Pol) 5’5’3’3’ Pol Transcription initiation is more complex in eukaryotes than in prokaryotes In eukaryotes several different factors are necessary for the transcription of an RNA polymerase II promoter.RNA polymerase II

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9 Initiation –Promoter clearance –Pol2 stalling Elongation Termination Figures from

10 Transcription Model 5’5’3’3’ Pol AAAAAAAAAAA Transcription Capping ( ) Splicing Polyadenylation mRNA Pre-mRNA (precursor)

11 Transcription Factor (TF) Binding TFs bind to specific sites in the DNA Sets of TFs can function as cis- regulatory modules (CRM) Nature Reviews Genetics 5, (April 2004)

12 Specific TF Binding Transcription factors bind to specific DNA sequences Databases of TF binding sequence motifs –JASPAR, TRANSFAC DNA IRF8 IRF8 binding motif

13 Promoter Region Transcription start site (TSS) Core promoter [-34, -1] Proximal promoter [-250, -34] Distal promoter [-10k, -250]

14 Promoter Region Core promoter – the minimal portion of the promoter required to properly initiate transcription –Transcription Start Site (TSS) –Approximately -34 –A binding site for RNA polymeraseRNA polymerase –General transcription factor binding sites Proximal promoter – the proximal sequence upstream of the gene that tends to contain primary regulatory elements –Approximately -250 –Specific transcription factor binding sites Distal promoter – the distal sequence upstream of the gene that may contain additional regulatory elements, often with a weaker influence than the proximal promoter –Anything further upstream (but not an enhancer or other regulatory region whose influence is positional/orientation independent) –Specific transcription factor binding sites

15 Transcription in eukaryotes In eukaryotes, several different factors are necessary for the transcription of an RNA polymerase II promoter.RNA polymerase II

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17 Identifying the TF regulators How much is a TF binding site used –Observed expression of all genes –Predicted site count Motif Activity Response Analysis (MARA)

18 FANTOM4 – A Systems Approach Illumina (47K probes) 10 time points RIKEN1 RIKEN3 RIKEN5 RIKEN6 Microarray check Replicates Not good Deep CAGE TF qRT-PCR miRNA microarray Monoblast-like PMA Monocyte-like Monoblast-like THP-1 cells were stimulated by PMA to differentiate them into monocyte-like cells. 10 time point samples were collected during differentiation hour

19 Cap Analysis of Gene Expression (CAGE) 1 Carninci, P. et al. Genome-wide analysis of mammalian promoter architecture and evolution. Nature genetics 38, 626–35 (2006) Figure based on [1] CAGE library preparation CAGE data digital processing Sequencing Tag cluster (TC)

20 CAGE identifies the active set of promoters HeLa Promoter THP-1 Promoter Kanamori-Katayama, Itoh, Kawaji et al Genome Research. “Unamplified cap analysis of gene expression on a single-molecule sequencer” Alternative promoter usage for PTPN6 Slide modified from Alistair Forrest.

21 Transcriptional Regulation A. TFBS prediction B. Co-expression Gene B TF A Gene C Gene D 0h 96h × × × × × ×× ■ ■ ■ ■ ■ ■ ■ ◆ ◆ ◆ ◆ ◆ ◆ ◆ ● ● ● ● ● ● ● A: basis: TFBS prediction B: co-expression TFBS prediction TF A  promoter B TF A  promoter C TF A  promoter D × Co-expression High Low = Total score High Low ×: Average expression CAGE Promoter No of CAGE tags In each promoter CAGE tags

22 THP-1 cells are a monoblastic leukemia cell line which upon PMA treatment can differentiate into an adherent monocyte like cell (CD14 +, CSF1R + ) e ps Suzuki, Forrest, van Nimwegen et al. Nature Genetics 2009, 41:5 Genome m1 m2m3 Promoter1 m1m4 Promoter2 ・・・・ m1m5 PromoterX Reaction efficiency Number of possible binding sites Degree of conservation of the motif Chromatin status Effective concentration Expression Motif Activity Response Analysis – MARA

23 Motif Activity Response Analysis How much is a binding site used –Observed expression of all promoters over time –Predicted site count Suzuki, Forrest, van Nimwegen et al. Nature Genetics 2009, 41:5

24 Nat Genet May;41(5):

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26 Enhancers Enhancers are sequence motifs They bind factors (proteins) that are participating in the transcription initiation complex Enhancers can be many kb away from the TSS Insulators are acting in a similar way, but repressing expression Is an enhancer a gene?

27 Enhancer RNA ENCODE reported (Nature, 489(7414), 101–108) –Enhancers identified by co-occurrence of H3K27ac and H3K4me1 ChIP-Seq data, centred on P300 binding sites, in HeLa cells Enhancers make non-coding RNA Nature 465, 173–174 (2010). Widespread transcription at neuronal activity-regulated enhancers. (Kim, T. K. et al. Widespread transcription at neuronal activity- regulated enhancers. Nature 465, 182–187 (2010).)

28 Djebali, S., Davis, C. A., Merkel, A., Dobin, A., Lassmann, T., Mortazavi, A., et al. (2012). Landscape of transcription in human cells. Nature, 489(7414), 101– 108. doi: /nature11233

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30 RNA splicing in cancer

31 Example: Melanoma Transcriptome discovery of aberrations that contribute to carcinogenesis characterize the spectrum of cancer- associated mRNA alterations through integration of transcriptomic and structural genomic data –11 novel melanoma gene fusions produced by underlying genomic rearrangements –12 novel readthrough transcripts Genome Res Apr;20(4):413-27

32 Melanoma Transcriptome: Gene Fusion Connecting genes located on different chromosomes!

33 Melanoma Transcriptome: Gene Read-through

34 Genes fusions are ‘private’ –The same gene fusion was not observed in two melanoma patients (10 samples total) Gene fusions in melanoma might not be the cancer causing events but consequences

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36 Chromosome Structure Ref:

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38 Mouse ES cells Dixon, J. R., Selvaraj, S., Yue, F., Kim, A., Li, Y., Shen, Y., et al. (2012). Topological domains in mammalian genomes identified by analysis of chromatin interactions. Nature. doi: /nature11082

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40 Remote ER-a chromatin biding sites are anchored at gene promoters through long-range chromatin interactions suggesting that ER-a functions by extensive chromatin looping to bring genes together for coordinated transcriptional regulation Nature Nov 5;462(7269):58-64

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42 Polymerase II Stalling stalled active Nature Genetics 39, (2007) No binding Pol II ChIP-chip in drosophila embryos Stalled genes are highly enriched in developmental control genes

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44 Transcriptional Regulation in Cancer

45 From observations to mechanisms Observations => Biomarkers


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