1. Genome annotation

2. What we have GATCAATGATGATAGGAATTGAAAGTGTCTTAATTACAATCCCTGTGCAATTATTAATAACTTTTTTGTT CACCTGTTCCCAGAGGAAACCTCAAGCGGATCTAAAGGAGGTATCTCCTCAAAAGCATCCTCTAATGTCA GAAGCAAGTGAGCACTGGGAAGAATACTTGAGAAAGTGGCATGCTTACGAAACTGCTAAGGTGCACCCCA GGGAGGTTGCAAAACCTGCATCTAAAGGAAAGCCCAGGCTTCCAAAGGCTTCTCCTAAGGCAACCTCCAA ACCCAAGCACAGGCATAGGAAAGCACAAATCAAGACCCCGGAGACCCTCGGGCCAAATACAAATTCCAAT AACAACATAGAAGATGATCAGGATGTCCATTCCGAACAGCACCCTTCCCAAAAGGATCTCCAGCAGCTTA AGAAAAAGCCCCGGATCGTCCTACCTTGGTGGTGTGTTTATGTTGCATGGTTTTTGGTTTTTGCTACTTC TAGCATATCCTCATTCTTCATTGTATTTTATGGACTGACTTACGGCTATGACAAGTCAATAGAATGGCTC TTTGCATCTTTTTGTTCATTCTGTCAGTCAGTTCTTCTGGTGCAGCCATCTAAAATTATACTCCTGTCAG GCTTCAGAACGAATAAACCCAAGTATTGCAAAAACCTTTCATGGTCAACCAAGTATAAATATACTGAGAT CAGGTTGGATGGAATGCGTATGCATCCAGAAGAAATGCAGAGGATACATGACCAGATCGTCCGAATCCGA GGCACGAGGATGTACCAACCCCTTACAGAAGATGAAATCAGAATATTCAAAAGAAAGAAGAGGATCAAGA GAAGAGCACTCCTGTTTCTGAGTTACATTCTAACTCACTTTATCTTTCTAGCCCTTCTGTTGATCCTTAT CGTCTTACTACGTCACACTGACTGCTTTTACTATAACCAGTTTATTCGTGATCGGTTCTCTATGGATCTT GCTACTGTGACTAAGCTGGAAGACATCTATAGATGGCTAAACAGCGTGCTGTTGCCTTTGTTACACAATG ACCTGAATCCAACATTTCTTCCTGAAAGCTCGTCTAAAATCCTTGGCCTTCCATTGATGAGGCAAGTGAG AGCAAAATCTAGTGAAAAAATGTGTCTACCTGCCGAAAAGTTTGTGCAAAACAGCATCAGAAGAGAAATT CATTGTCACCCCAAATATGGCATTGACCCAGAAGACACAAAAAACTATTCTGGCTTTTGGAATGAAGTTG ATAAGCAGGCTATAGATGAGAGTACCAATGGATTTACTTATAAGCCTCAAGGAACGCAATGGCTATATTA TTCCTATGGACTACTACACACCTATGGATCTGGAGGATATGCACTCTATTTTTTTCCAGAACAGCAGCGG TTTAATTCCACACTGAGGCTCAAAGAACTTCAAGAAAGCAATTGGCTGGATGAGAAGACATGGGCTGTGG TTTTGGAATTAACAACTTTTAATCCAGATATAAATCTGTTCTGTAGCATTTCGGTCATATTTGAAGTCTC TCAGTTAGGAGTTGTCAACACAAGCATATCTCTGCACTCTTTTTCACTTGCTGATTTTGACAGAAAAGCT TCAGCAGAAATCTACTTGTATGTGGCCATTCTCATTTTTTTCTTAGCCTACGTTGTTGATGAGGGTTGTA TCATTATGCAAGAAAGAGCCTCCTATGTGAGAAGTGTGTATAATTTGCTCAACTTTGCTTTAAAGTGCAT ATTTACTGTGTTGATTGTGCTCTTTCTCAGGAAACATTTCCTGGCCACTGGCATAATTCGGTTTTACTTG TCGAACCCAGAAGACTTCATTCCCTTTCATGCAGTTTCTCAGGTAGATCACATTATGAGGATAATTTTGG GTTTCCTGTTATTTCTGACAATTTTGAAGACCCTCAGGTATTCCAGATTCTTCTACGATGTGCGCCTGGC TCAGAGGGCCATCCAGGCTGCCCTCCCTGGCATCTGCCACATGGCATTTGTTGTGTCCGTGTATTTCTTC GTATACATGGCTTTTGGTTACCTGGTGTTTGGTCAGCATGAATGGAACTACAGTAACTTGATTCATTCCA CTCAGACAGTATTTTCCTATTGTGTCTCAGCTTTCCAGAACACTGAATTTTCCAATAACAGGATTCTGGG GGTCCTGTTCCTCTCATCTTTCATGCTGGTGATGATCTGCGTCTTGATCAACTTATTTCAGGCTGTAATT

3. What we want: Annotated sequence GATCAATGATGATAGGAATTGAAAGTGTCTTAATTACAATCCCTGTGCAATTATTAATAACTTTTTTGTT CACCTGTTCCCAGAGGAAACCTCAAGCGGATCTAAAGGAGGTATCTCCTCAAAAGCATCCTCTAATGTCA GAAGCAAGTGAGCACTGGGAAGAATACTTGAGAAAGTGGCATGCTTACGAAACTGCTAAGGTGCACCCCA GGGAGGTTGCAAAACCTGCATCTAAAGGAAAGCCCAGGCTTCCAAAGGCTTCTCCTAAGGCAACCTCCAA ACCCAAGCACAGGCATAGGAAAGCACAAATCAAGACCCCGGAGACCCTCGGGCCAAATACAAATTCCAAT AACAACATAGAAGATGATCAGGATGTCCATTCCGAACAGCACCCTTCCCAAAAGGATCTCCAGCAGCTTA AGAAAAAGCCCCGGATCGTCCTACCTTGGTGGTGTGTTTATGTTGCATGGTTTTTGGTTTTTGCTACTTC TAGCATATCCTCATTCTTCATTGTATTTTATGGACTGACTTACGGCTATGACAAGTCAATAGAATGGCTC TTTGCATCTTTTTGTTCATTCTGTCAGTCAGTTCTTCTGGTGCAGCCATCTAAAATTATACTCCTGTCAG GCTTCAGAACGAATAAACCCAAGTATTGCAAAAACCTTTCATGGTCAACCAAGTATAAATATACTGAGAT CAGGTTGGATGGAATGCGTATGCATCCAGAAGAAATGCAGAGGATACATGACCAGATCGTCCGAATCCGA GGCACGAGGATGTACCAACCCCTTACAGAAGATGAAATCAGAATATTCAAAAGAAAGAAGAGGATCAAGA GAAGAGCACTCCTGTTTCTGAGTTACATTCTAACTCACTTTATCTTTCTAGCCCTTCTGTTGATCCTTAT CGTCTTACTACGTCACACTGACTGCTTTTACTATAACCAGTTTATTCGTGATCGGTTCTCTATGGATCTT GCTACTGTGACTAAGCTGGAAGACATCTATAGATGGCTAAACAGCGTGCTGTTGCCTTTGTTACACAATG ACCTGAATCCAACATTTCTTCCTGAAAGCTCGTCTAAAATCCTTGGCCTTCCATTGATGAGGCAAGTGAG AGCAAAATCTAGTGAAAAAATGTGTCTACCTGCCGAAAAGTTTGTGCAAAACAGCATCAGAAGAGAAATT CATTGTCACCCCAAATATGGCATTGACCCAGAAGACACAAAAAACTATTCTGGCTTTTGGAATGAAGTTG ATAAGCAGGCTATAGATGAGAGTACCAATGGATTTACTTATAAGCCTCAAGGAACGCAATGGCTATATTA TTCCTATGGACTACTACACACCTATGGATCTGGAGGATATGCACTCTATTTTTTTCCAGAACAGCAGCGG TTTAATTCCACACTGAGGCTCAAAGAACTTCAAGAAAGCAATTGGCTGGATGAGAAGACATGGGCTGTGG TTTTGGAATTAACAACTTTTAATCCAGATATAAATCTGTTCTGTAGCATTTCGGTCATATTTGAAGTCTC TCAGTTAGGAGTTGTCAACACAAGCATATCTCTGCACTCTTTTTCACTTGCTGATTTTGACAGAAAAGCT TCAGCAGAAATCTACTTGTATGTGGCCATTCTCATTTTTTTCTTAGCCTACGTTGTTGATGAGGGTTGTA TCATTATGCAAGAAAGAGCCTCCTATGTGAGAAGTGTGTATAATTTGCTCAACTTTGCTTTAAAGTGCAT ATTTACTGTGTTGATTGTGCTCTTTCTCAGGAAACATTTCCTGGCCACTGGCATAATTCGGTTTTACTTG TCGAACCCAGAAGACTTCATTCCCTTTCATGCAGTTTCTCAGGTAGATCACATTATGAGGATAATTTTGG GTTTCCTGTTATTTCTGACAATTTTGAAGACCCTCAGGTATTCCAGATTCTTCTACGATGTGCGCCTGGC TCAGAGGGCCATCCAGGCTGCCCTCCCTGGCATCTGCCACATGGCATTTGTTGTGTCCGTGTATTTCTTC GTATACATGGCTTTTGGTTACCTGGTGTTTGGTCAGCATGAATGGAACTACAGTAACTTGATTCATTCCA CTCAGACAGTATTTTCCTATTGTGTCTCAGCTTTCCAGAACACTGAATTTTCCAATAACAGGATTCTGGG GGTCCTGTTCCTCTCATCTTTCATGCTGGTGATGATCTGCGTCTTGATCAACTTATTTCAGGCTGTAATT Exon 1 Exon 2 Exon 3 Exon 4

4. Making sense of genomic seqs HMM analysis Compare genomes to each other Compare to other kind of supprting data –Which kinds of data can you think of?

5. Other kinds of data 1.mRNA sequences (and ESTs) 2.Protein sequences

6. -OMEs Genome Transcriptome Proteome Interactome Metabolome Phenome

7. -OMEs Technologies Genome Transcriptome Proteome Interactome Metabolome Phenome Sequencing Microarray Computer (ORFs), Mass-spec Y2H, Mass-spec Mass-spec Phenotype Biochemical Disease

8. Transcript databases RefSeq contains full length sequences of mRNAs, carefully reviewed –Currently 28.000 human sequences dbEST contains 5’ and 3’ reads of random cDNAs –Currently 5.9 mio. human seqs

9. What are ESTs?

11. UniGene UniGene: Merge (cluster) any two ESTs when >100 bp are identical 5 mio -> 107.014 clusters

12. ESTs UniGene: total # clusters 107.014 Cluster size Number of clusters 1 (singletons)8131 2 38169 3-4 23302 5-8 11989 9-16 5616 17-32 3733 33-64 3303 65-128 3799 129-256 4368 257-512 3029 513-1024 1079 1025-2048 343 2049-4096 106 4097-8192 33 8193-16384 16 16385-32768 2

13. Transcripts: what can we learn? Comparing genome sequences to transcripts allows: –Confirmation of gene predictions –Experimental identification of Exons/Introns, 5’ UTRs, 3’ UTRs –Alternative splicing Asses the relative abundance of transcripts: Digital differential display (DDD).

15. Annotation example

16. 18 exons 623 AA

17. Proteomics: What for? Disease targets Gene finding Secondary modifications Measuring expression levels Protein-protein interactions

18. Whats new? Mass spectrometry was invented turn of century (Thomson) Noble price to Aston 1930s MALDI-TOF (Henzel et al, 1993) Nano-electro-spray (Wilm, Mann 1996s) coupled to tandem mass spectrometer

24. 2-D electrophoresis