Regulation of eukaryotic transcription:

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Promoter definition by mass genome annotation data: in silico primer extension EMBNET course Bioinformatics of transcriptional regulation Jan 28 2008 Christoph Schmid Regulation of

1 Promoter definition by mass genome annotation data: in silico primer extension EMBNET course Bioinformatics of transcriptional regulation Jan Christoph Schmid Regulation of eukaryotic transcription: Levine, M. and R. Tjian (2003). "Transcription regulation and animal diversity." Nature 424(6945): with permission Nature Macmillan Publishers Ltd

2 Upstream promoter region defined by transcription start sites (TSS) conventional techniques: nuclease protection assay primer extension cdnas genomic DNA Core promoter TSS In Silico (Digital) versus in Vitro (Analog) Primer Extension cctcacccctttccttcccacaggtccctggccaaagatttatttctcttgacaacca

3 A job for Bioinformatics? Prediction based on sequence motifs does not (yet?) achieve satisfying results. (for review, see Ohler and Niemann, 2001) Large scale projects provide corresponding data: Genome projects cdna sequencing projects oligocapping method (Suzuki, Y. et al. 2002) MGC project (Strausberg, R.L. et al. 2002) Oligocapping method -> full-length libraries

DBTSS vs. conventional techniques # of 5 end of DBTSS transcripts 100 bp Genomic position Characterization of three optional promoters in the 5' region of the human aldolase A gene. Maire P.

4 DBTSS vs. conventional techniques # of 5 end of DBTSS transcripts 100 bp Genomic position Characterization of three optional promoters in the 5' region of the human aldolase A gene. Maire P. et al (1987) J. Mol. Biol. 197, TSS determined by modelling Gaussian distributions (MADAP) Frequency of full-length transcripts 45 bp 10 bp R R Genomic position MADAP, a flexible clustering tool for the interpretation of one-dimensional genome annotation data. Schmid CD, Sengstag T, Bucher P, Delorenzi M (2007) Nucleic Acids Res 35: W Webserver:

5 DATA INTERPRETATION WITH MADAP input: positions of 5'ends initial model: k normal distributions parameter fitting with EM eliminations of distributions? evaluation: data likelihood with this model no yes k=k-1 until k=1 output: best model = maximal likelihood

6 [-10;10] [-400;400] EPD RefSeq mrna Genome annot DBTSS Eponine Higher precision of in silico PE in silico primer ext. conv. methods Ohler-set RefSeq mrnas

Eukaryotic Promoter Database (EPD) ID HS_RPS19 standard; multiple; VRT. AC EP68002; DT 22-AUG-2001 (Rel. 68, created) DT 19-DEC-2003 (Rel. 77, Last annotation update). DE Ribosomal protein S19.

7 Eukaryotic Promoter Database (EPD) ID HS_RPS19 standard; multiple; VRT. AC EP68002; DT 22-AUG-2001 (Rel. 68, created) DT 19-DEC-2003 (Rel. 77, Last annotation update). DE Ribosomal protein S19. OS Homo sapiens (human). HG none. AP none. NP none. DR GENOME; NT_ ; NT_011109; [ , ]. DR CLEANEX; HS_RPS19. DR EMBL; AC ; [-21462, ]. DR EMBL; AF ; [-792, 1344]. DR SWISS-PROT; P39019; RS19_HUMAN. DR RefSeq; NM_ DR MIM; RN [1] RX MEDLINE; RA Suzuki Y., Yamashita R., Nakai K., Sugano S. RT DBTSS: database of human transcriptional start sites and RT full-length cdnas. RL Nucleic Acids Res. 30: (2002). RN [2] RX MEDLINE; RA Strausberg RL., Feingold EA., Klausner RD., Collins FS.; RT The mammalian gene collection; RL Science 286: (1999). ME NEDO full length human cdna sequencing project. ME Oligo-capping [1]. ME Mammalian gene collection (MGC) full-length cdna cloning [2]. SE tctcgcgagaccctacgcccgacttgtgcgcccgggaaaccccgtcgttccctttcccct FL DBTSS MGC : IF -3 G 1 IF -2 T 1 IF -1 T 4 IF 0 C IF +1 C IF +2 C 32 2 IF +3 T 2 2 : TX 6. Vertebrate promoters TX 6.1. Chromosomal genes TX Structural proteins TX RNA-binding proteins TX Ribosomal proteins KW Ribosomal protein, Disease mutation. FP Hs ribosomal p. S19 :+M EU:NC_ ; DO Experimental evidence: 11,12 DO Expression/Regulation: RF NAR30:328 Sci286:455 // GC-content around TSS Human promoter seq Drosophila

8 TATA is one of several signals Constraint (SSA-Cpr) (1830) (1664) (225) (47) Alternative sources of raw data to determine promoters: Sequencing: 5 SAGE (5 -end Serial Analysis of Gene Expression) CAGE (Cap Analysis Gene Expression) GIS-PET (Gene Identification Signature Paired-End ditag) Hybridization: Tiling array (probes for entire genome/chromosomes) ChIP-chip (Chromatin ImmunoPrecipitation on DNA chip)

9 CAGE Advantages: CAGE / 5 SAGE enriched for full-length 5 end of transcripts high throughput (lower cost) Disadvantages: no information on coding region relatively short tags with sequencing errors difficult to map

10 GIS-PET Advantages: GIS-PET Paired-End tags enhances mapping enriched for full-length 5 end of transcripts high throughput (lower cost) Disadvantages: no information on coding region

11 Advantages: ChIP-chip high resolution by overlapping probes (oligos) signal on entire genome/chromosomes Disadvantages: maps pre-initiation complex (not TSS) hybridization artifacts limited resolution repeat regions are excluded

virtual counts (2** log ratio)-1 New data sources for EPD ChIP-chip pre-initiation complexes Kim et al. (2005) Nature, 436, 876-880 GEO: GSE2672 (remapped!) ENSEMBL chro12: 6.8 6.

12 virtual counts (2** log ratio)-1 New data sources for EPD ChIP-chip pre-initiation complexes Kim et al. (2005) Nature, 436, GEO: GSE2672 (remapped!) ENSEMBL chro12: Mb ChIP-chip data with insufficient resolution FP Hs USP5 :+R EU:NC_ ; Frequency G enom ic position

PromSearch: A Hybrid Approach to Human Core-Promoter Prediction

PromSearch: A Hybrid Approach to Human Core-Promoter Prediction Byoung-Hee Kim, Seong-Bae Park, and Byoung-Tak Zhang Biointelligence Laboratory, School of Computer Science and Engineering Seoul National