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1 M2 BIM - Génomes, Génétique et Evolution Anatomie et annotations des génomes Mardi 20 octobre Cours de 9h a 12h salle M2 BIM Génétique Génome et Evolution 13 octobre 2010 Definitions: Genome sizes: The C-value paradox 1) Genome: the genome is the entire DNA content of a cell - chromosomes - plasmids - mitochondrial DNA - chloroplastic DNA 2) Gene: A gene is an informative DNA sequence composed of a transcribed region and a regulatory sequence 3) ORF (open reading frame): a DNA sequence betweeen two STOP codons. It is presumed to be the sequence of a protein coding gene 4) CDS (coding sequence): a DNA sequence betweeen a START and a STOP codon 5) Intron: a RNA sequence spliced from the pre-mature RNA Exon: the coding part of the protein encoded genes 1

2 Gene content: The G-value paradox Number of chromosomes/haploid genome: Estimated gene number: S. pombe n = 3 Arabidopsis : n = 5 S. cerevisiae : n = 16 Human : n = 23 Tobacco : n = 36 Kiwi : n = 98 Fern: n > 500 ~ 20,000 Homo sapiens Drosophila melanogaster ~ 13,000 Arabidopsis thaliana ~ 25,000 Caenorhabditis elegans ~ 19,000 ~ 40,000 Paramecium tetraurelia Saccharomyces cerevisiae ~ 6,000 Escherichia coli (Mbp) Genome content : I) no correlation between complexity: genome size number of genes number of chromosomes 2 - Gene duplications Most eukaryotic genomes contain high proportion of duplicated sequences Unique sequences - protein encoding genes S. c. A. t. C. e. D. m. H. s. s. - RNA genes (RNAseP, TelC1, ) II) Repeated sequences - transposable elements - ADN satellite Duplicated Genes 43% 65% 49% 40% duplication 50% 25-60% du génome des vertebrés environ 50% du génome humain Jusqu à 80% du génome des plantes ou des amphibiens. - protein encoding genes - RNA genes (tdna, rdna, etc) Pseudogenization Neofunctionalization Most frequent fate: 278 in yeast Gain of a new function (Lafontaine et al. 2004) Conservation Gene dosage increase Genetic robustness Degeneration Complementation Specialization of the 2 copies 2

3 Homologs, orthologs (co-orthologs), paralogs (in-paralogs, out-paralogs) ancestor A ancestor ancestor A B Duplication DUPLICATION LOSS Speciation Speciation Speciation Duplication A B A1 A2 species 1 species 2 orthologs A1 B1 A2 B2 species 1 species 2 out-paralogs out-paralogs orthologs A B C species 1 species 2 in-paralogs orthologs Duplication ancestor Organisation et structure des gènes «protéiques» chez les eucaryotes Duplication A B C Speciation Loss of B1 A1 B1 C1 A2 C2 B2.1 B2.2 Loss of A2 Loss of C2 Duplication A1 C1 B2.1 B2.2 species 1 species 2 3

4 Organisation et structure des gènes «protéiques» chez les eucaryotes LesamoureodcbighdccohcheuxzhvbzdcizqhcokqsikeiutrzevuzeidcvbCIferventse tlessavantsausfxqghklmpotèresjqsiaiobcsbcoiohsodjsqjjxchcqyxnldsqshsnchgdq qsoqqpcqpcccdgjlcjsjpaimentégalemqshxhxqxioxiient,dansleurmûrebcjqoqp chhizpps,xqioqsogjydsguipgvaddixixxioisqisaison,fsdfrttykylibvqleshsduzis klxlxhjhchghgchhchchatspuissansks,ndoidopezpsmsktsetdoux,orggcq qxucvvvv vxwdtyhsvueilcjqpcjjcqoccccdelamacokqsikeiuzjqsiaioison,qddzaztrykjkloljtvq uicommeeuxccqscqvfg,hk;bscqfjiilopjsdsontfhhjdcizeodcbighdcrileuxetcommee uxqsqsazdzsédentaires.gdjqqspqqsiqsopqpscqpjdiksoaoqjknsndshvsdfsdfsdfshh gloqksdgzsauaqnwnwsschediokcjcjcdsdfgfhkcohchqhbcsbcoiohsodjsqjjxchcqyf xqhgdqqsoqqpcqpcccdgjlcjsjpdsdvsdvezbnj,uiyterrogjydsguipgvaddiqshxhxq xigdjqqspqqsiqsopqpscqpjdiksoaoqjknsndshvsdfsfsdfshhgloqkauaqnwndfgfhkh hjdcizeodcbighdccohchqhcokqsikeiuergzaqcqvzjqsiaiobcsbcoiohsodjswsschedio kcjcjcdsdfgfhkhhjdcizeodcbighdccohchqhcokqsikeiuzjqsiaiobcsbcoiohsodjsqjjx chcqyfxqqpcqpcccdgjlcjsjpvgrgtjykililloleergrrergrrrgerqqqqogjydsguipgvad diqshxhxqxibcoiohsodjsqjjxchcqyfxqhgdqqsoqqpcqpccsodjsqjjxchcqyfxqhgdq qsokqsikeiuzjqsiaiobcsbcoiohsodaiobcsbcoiohsodjsaqnwnwsschediokcjcjcdsdfgf hkhhjdcizeodckeiuzjqsiapgvaddiqshxhxqxioxiixgfhkhhjdcizeodcbighdccohchq AmisdelascienceetdeqqpCqdsdfgfhkhccohchqhcolavoluptéhcokqsikeiuzjqsiaiob Organisation et structure des gènes «protéiques» chez les eucaryotes LesamoureodcbighdccohcheuxzhvbzdcizqhcokqsikeiutrzevuzeidcvbCIferventse tlessavantsausfxqghklmpotèresjqsiaiobcsbcoiohsodjsqjjxchcqyxnldsqshsnchgdq qsoqqpcqpcccdgjlcjsjpaimentégalemqshxhxqxioxiient,dansleurmûrebcjqoqp chhizpps,xqioqsogjydsguipgvaddixixxioisqisaison,fsdfrttykylibvqleshsduzis klxlxhjhchghgchhchchatspuissansks,ndoidopezpsmsktsetdoux,orggcq qxucvvvv vxwdtyhsvueilcjqpcjjcqoccccdelamacokqsikeiuzjqsiaioison,qddzaztrykjkloljtvq uicommeeuxccqscqvfg,hk;bscqfjiilopjsdsontfhhjdcizeodcbighdcrileuxetcommee uxqsqsazdzsédentaires.gdjqqspqqsiqsopqpscqpjdiksoaoqjknsndshvsdfsdfsdfshh gloqksdgzsauaqnwnwsschediokcjcjcdsdfgfhkcohchqhbcsbcoiohsodjsqjjxchcqyf xqhgdqqsoqqpcqpcccdgjlcjsjpdsdvsdvezbnj,uiyterrogjydsguipgvaddiqshxhxq xigdjqqspqqsiqsopqpscqpjdiksoaoqjknsndshvsdfsfsdfshhgloqkauaqnwndfgfhkh hjdcizeodcbighdccohchqhcokqsikeiuergzaqcqvzjqsiaiobcsbcoiohsodjswsschedio kcjcjcdsdfgfhkhhjdcizeodcbighdccohchqhcokqsikeiuzjqsiaiobcsbcoiohsodjsqjjx chcqyfxqqpcqpcccdgjlcjsjpvgrgtjykililloleergrrergrrrgerqqqqogjydsguipgvad diqshxhxqxibcoiohsodjsqjjxchcqyfxqhgdqqsoqqpcqpccsodjsqjjxchcqyfxqhgdq qsokqsikeiuzjqsiaiobcsbcoiohsodaiobcsbcoiohsodjsaqnwnwsschediokcjcjcdsdfgf hkhhjdcizeodckeiuzjqsiapgvaddiqshxhxqxioxiixgfhkhhjdcizeodcbighdccohchq AmisdelascienceetdeqqpCqdsdfgfhkhccohchqhcolavoluptéhcokqsikeiuzjqsiaiob Les amoureux fervents et les savants austères Aiment également, dans leur mûre saison, Les chats puissants et doux, orgueil de la maison, Qui comme eux sont frileux et comme eux sédentaires. Amis de la science et de la volupté, / Structure of Eukaryotic coding genes: Eukaryotic mrnas are modified at their 5ʼ and 3ʼ ends -5ʼ cap -poly-a tail at 3ʼ end Eukaryotic genes give rise to multiple protein products -alternative splicing -alternative promoters -alternative terminators multiple promoters alternatively spliced introns multiple terminators Ch. Beaudelaire, «Les chats» alternative promoters alternative terminators alternative splicing correlation between complexity and protein diversity? About prot in human 4

5 Chaque chromosome humain contient des dizaines de millions de paires de bases Chaque chromosome humain contient des dizaines de millions de paires de bases TCGCGCGTTTCGGTGATGACGGTGAAAACCTCTGACACATGCAGCTCCCGGAGACGGTCACAGCTTGTCTGTAAGCGGATGCCGGGAGCAGACAAGCCCGTCAGGGCGCGTCAGCGGGTGTTGGCGGGTGTCGGGGCTGG CTTAACTATGCGGCATCAGAGCAGATTGTACTGAGAGTGCACCATATGCGGTGTGAAATACCGCACAGATGCGTAAGGAGAAAATACCGCATCAGGCGCCATTCGCCATTCAGGCTGCGCAACTGTTGGGAAGGGCGATC GGTGCGGGCCTCTTCGCTATTACGCCAGCTGGCGAAAGGGGGATGTGCTGCAAGGCGATTAAGTTGGGTAACGCCAGGGTTTTCCCAGTCACGACGTTGTAAAACGACGGCCAGTGAATTCGAGCTCGGTACCCGGGGAT CCTCTAGAGTCGACCTGCAGGCATGCAAGCTTGGCGTAATCATGGTCATAGCTGTTTCCTGTGTGAAATTGTTATCCGCTCACAATTCCACACAACATACGAGCCGGAAGCATAAAGTGTAAAGCCTGGGGTGCCTAATG AGTGAGCTAACTCACATTAATTGCGTTGCGCTCACTGCCCGCTTTCCAGTCGGGAAACCTGTCGTGCCAGCAGATCTGAATTAATTCGGTCGAAAAAAGAAAAGGAGAGGGCCAAGAGGGAGGGCATTGGTGACTATTGA GCACGTGAGTATATATACCGTGATTAAGCACACAAAGGCAGCTTGGAGTATGTCTGTTATTAATTTCACAGGTAGTTCTGGTCCATTGGTGAAAGTTTGCGGCTTGCAGAGCACAGAGGCCGCAGAATGTGCTCTAGATT CCGATGCTGACTTGCTGGGTATTATATGTGTGCCCAATAGAAAGAGAACAATTGACCCGGTTATTGCAAGGAAAATTTCAAGTCTTGTAAAAGCATATAAAAATAGTTCAGGCACTCCGAAATACTTGGTTGGCGTGTTT CGTAATCAACCTAAGGAGGATGTTTTGGCTCTGGTCAATGATTACGGCATTGATATCGTCCAACTGCATGGAGATGAGTCGTGGCAAGAATACCAAGAGTTCCTCGGTTTGCCAGTTATTAAAAGACTCGTATTTCCAAA AGACTGCAACATACTACTCAGTGCAGCTTCACAGAAACCTCATTCGTTTATTCCCTTGTTTGATTCAGAAGCAGGTGGGACAGGTGAACTTTTGGATTGGAACTCGATTTCTGACTGGGTTGGAAGGCAAGAGAGCCCCG AAAGTTTACATTTTATGTTAGCTGGTGGACTGACGCCAGAAAATGTTGGTGATGCGCTTAGATTAAATGGCGTTATTGGTGTTGATGTAAGCGGAGGTGTGGAGACAAATGGTGTAAAAGACTCTAACAAAATAGCAAAT TTCGTCAAAAATGCTAAGAAATAGGTTATTACTGAGTAGTATTTATTTAAGTATTGTTTGTGCACTTGCCCAGATCTGCTGCATTAATGAATCGGCCAACGCGCGGGGAGAGGCGGTTTGCGTATTGGGCGCTCTTCCGC TTCCTCGCTCACTGACTCGCTGCGCTCGGTCGTTCGGCTGCGGCGAGCGGTATCAGCATCGATGCTCACTCAAAGGTCGGTAATACGGTTATCCACAGAATCAGGGGATAACGCAGGAAAGAACATGTGAGCAAAAGGCC AGCAAAAGGCCAGGAACCGTAAAAAGGCCGCGTTGCTGGCGTTTTTCCATAGGCTCCGCCCCCCTGACGAGCATCACAAAAATCGACGCTCAAGTCAGAGGTGGCGAAACCCGACAGGACTATAAAGATACCAGGCGTTT CCCCCTGGAAGCTCCCTCGTGCGCTCTCCTGTTCCGACCCTGCCGCTTACCGGATACCTGTCCGCCTTTCTCCCTTCGGGAAGCGTGGCGCTTTCTCATAGCTCACGCTGTAGGTATCTCAGTTCGGTGTAGGTCGTTCG CTCCAAGCTGGGCTGTGTGCACGAACCCCCCGTTCAGCCCGACCGCTGCGCCTTATCCGGTAACTATCGTCTTGAGTCCAACCCGGTAAGACACGACTTATCGCCACTGGCAGCAGCCACTGGTAACAGGATTAGCAGAG CGAGGTATGTAGGCGGTGCTACAGAGTTCTTGAAGTGGTGGCCTAACTACGGCTACACTAGAAGGACAGTATTTGGTATCTGCGCTCTGCTGAAGCCAGTTACCTTCGGAAAAAGAGTTGGTAGCTCTTGATCCGGCAAA CAAACCACCGCTGGTAGCGGTGGTTTTTTTGTTTGCAAGCAGCAGATTACGCGCAGAAAAAAAGGATCTCAAGAAGACCTTTGATCTTTTCTACGGGGTCTGACGCTCAGTGGAACGAAAACTCACGTTAAGGGATTTTG GTCATGAGATTATCAAAAAGGATCTTCACCTAGATCCTTTTAAATTAAAAATGAAGTTTTAAATCAATCTAAAGTATATATGAGTAAACTTGGTCTGACAGTTACCAATGCTTAATCAGTGAGGCACCTATCTCAGCGAT CTGTCTATTTCGTTCATCCATAGTTGCCTGACTCCCCGTCGTGTAGATAACTACGATACGGGAGGGCTTACCATCTGGCCCCAGTGCTGCAATGATACCGCGAGACCCACGCTCACCGGCTCCAGATTTATCAGCAATAA ACCAGCCAGCCGGAAGGGCCGAGCGCAGAAGTGGTCCTGCAACTTTATCCGCCTCCATCCAGTCTATTAATTGTTGCCGGGAAGCTAGAGTAAGTAGTTCGCCAGTTAATAGTTTGCGCAACGTTGTTGCCATTGCTACA GGATCGTGGTGTCACGCTCGTCGTTTGGTATGGCTTCATTCAGCTCCGGTTCCCAACGATCAAGGCGAGTTACATGATCCCCCATGTTGTGCAAAAAAGCGGTTAGCTCCTTCGGTCCTCCGATCGTTGTCAGAAGTAAG TTGGCCGCAGTGTTATCATCGCGCGTTTCGGTGATGACGGTGAAAACCTCTGACACATGCAGCTCCCGGAGACGGTCACAGCTTGTCTGTAAGCGGATGCCGGGAGCAGACAAGCCCGTCAGGGCGCGTCAGCGGGTGTT GGCGGGTGTCGGGGCTGGCTTAACTATGCGGCATCAGAGCAGATTGTACTGAGAGTGCACCATATGCGGTGTGAAATACCGCACAGATGCGTAAGGAGAAAATACCGCATCAGGCGCCATTCGCCATTCAGGCTGCGCAA CTGTTGGGAAGGGCGATCGGTGCGGGCCTCTTCGCTATTACGCCAGCTGGCGAAAGGGGGATGTGCTGCAAGGCGATTAAGTTGGGTAACGCCAGGGTTTTCCCAGTCACGACGTTGTAAAACGACGGCCAGTGAATTCG AGCTCGGTACCCGGGGATCCTCTAGAGTCGACCTGCAGGCATGCAAGCTTGGCGTAATCATGGTCATAGCTGTTTCCTGTGTGAAATTGTTATCCGCTCACAATTCCACACAACATACGAGCCGGAAGCATAAAGTGTAA AGCCTGGGGTGCCTAATGAGTGAGCTAACTCACATTAATTGCGTTGCGCTCACTGCCCGCTTTCCAGTCGGGAAACCTGTCGTGCCAGCAGATCTGAATTAATTCGGTCGAAAAAAGAAAAGGAGAGGGCCAAGAGGGAG GGCATTGGTGACTATTGAGCACGTGAGTATATATACCGTGATTAAGCACACAAAGGCAGCTTGGAGTATGTCTGTTATTAATTTCACAGGTAGTTCTGGTCCATTGGTGAAAGTTTGCGGCTTGCAGAGCACAGAGGCCG CAGAATGTGCTCTAGATTCCGATGCTGACTTGCTGGGTATTATATGTGTGCCCAATAGAAAGAGAACAATTGACCCGGTTATTGCAAGGAAAATTTCAAGTCTTGTAAAAGCATATAAAAATAGTTCAGGCACTCCGAAA TACTTGGTTGGCGTGTTTCGTAATCAACCTAAGGAGGATGTTTTGGCTCTGGTCAATGATTACGGCATTGATATCGTCCAACTGCATGGAGATGAGTCGTGGCAAGAATACCAAGAGTTCCTCGGTTTGCCAGTTATTAA AAGACTCGTATTTCCAAAAGACTGCAACATACTACTCAGTGCAGCTTCACAGAAACCTCATTCGTTTATTCCCTTGTTTGATTCAGAAGCAGGTGGGACAGGTGAACTTTTGGATTGGAACTCGATTTCTGACTGGGTTG GAAGGCAAGAGAGCCCCGAAAGTTTACATTTTATGTTAGCTGGTGGACTGACGCCAGAAAATGTTGGGAAGGCAAGAGAGCCCCGAAAGTTTACATTTTATGTTAGCTGGTGGACTGACGCCAGAAAATGTTGGGAAGGC subtélomère télomère (TTAGGG)n centromere subtélomère télomère (TTAGGG)n Prix Nobel de médecine 2009: Blackburn, Greider et Szostak Protein/RNA complex -> RNA is template, protein is reverse transcriptase 1) RNA anneals to leading strand 2) Forms template to make more leading strand Comment séquencer l ADN? 3) Translocates 6 bp & repeats 4) Once have enough unpaired leading strand lagging strand is replicated in usual way. -> add back piece that got left off 5

6 Sequençage méthode didéoxy (Fred Sanger, Nobel 1980) 8 years, 120 labs, 633 people Sequençage méthode didéoxy (Fred Sanger, Nobel 1980) The S. cerevisiae genome sequence Comparative genomics Life with 6000 genes; Goffeau et al., Science, French laboratories, Genoscope Genopole Institut Pasteur Library construction Saccharomyces c erevisiae Candida glabrata Zygosaccharo myces rouxii Library construction => DNA extraction => manual sequencing Sanger method Lachancea kluyveri DNA extraction (WashU seq center Lachancea M. Jonhston) thermotolerans Kluyveromy ces lactis Debaryomyces hansenii Yarrowia lipolytica Génolevures I Exploration of 13 species Génolevures II 55% 17% 15% 7% 4% 2% ~ 100 europeen laboratories Sanger centre, Cambridge Washington University, Saint Louis Stanford University Mc Gill University, Montréal Institut RIKEN, Japon 2004 automatic sequencing Complete genome 4 species Génolevures III 2009 Complete genome 3 species 6

7 New sequencing technologies 454 / Roche Genome Sequence FLX Illumina / Solexa Genetic Analyzer Applied Biosystems ABI 3730XL Roche / 454 Genome Sequencer FLX Applied Biosystems SOLiD Ce qui change : La quantité et le type des données générées - Le coût La qualité des données (erreurs) 454 / Roche Genome Sequence FLX 454 / Roche Genome Sequence FLX 7

8 454 / Roche Genome Sequence FLX Illumina / Solexa Genetic Analyzer 1G Illumina / Solexa Genetic Analyzer 1G 1 fragment -> 1 bille 1 bille -> 1 lecture Illumina / Solexa Genetic Analyzer 1G Illumina / Solexa Genetic Analyzer 1G 8

9 Illumina / Solexa Genetic Analyzer 1G Illumina / Solexa Genetic Analyzer 1G Applied Biosystems SOLiD (Sequencing by Oligo Ligation and Detection) Applied Biosystems SOLiD (Sequencing by Oligo Ligation and Detection) Applied Biosystems SOLiD 9

10 Résumé : Séquençage manuel => 1 Kb / réaction X : Séquençage automatique => 100 Kb /réaction X : Nouvelles technologies => 1 Gb / réaction? Comment trouver les gènes? TCGCGCGTTTCGGTGATGACGGTGAAAACCTCTGACACATGCAGCTCCCGGAGACGGTCACAGCTTGTCTGTAAGCGGATGCCGGGAGCAGACAAGCCCGTCAGGGCGCGTC AGCGGGTGTTGGCGGGTGTCGGGGCTGGCTTAACTATGCGGCATCAGAGCAGATTGTACTGAGAGTGCACCATATGCGGTGTGAAATACCGCACAGATGCGTAAGGAGAAAA TACCGCATCAGGCGCCATTCGCCATTCAGGCTGCGCAACTGTTGGGAAGGGCGATCGGTGCGGGCCTCTTCGCTATTACGCCAGCTGGCGAAAGGGGGATGTGCTGCAAGGC GATTAAGTTGGGTAACGCCAGGGTTTTCCCAGTCACGACGTTGTAAAACGACGGCCAGTGAATTCGAGCTCGGTACCCGGGGATCCTCTAGAGTCGACCTGCAGGCATGCAA GCTTGGCGTAATCATGGTCATAGCTGTTTCCTGTGTGAAATTGTTATCCGCTCACAATTCCACACAACATACGAGCCGGAAGCATAAAGTGTAAAGCCTGGGGTGCCTAATG AGTGAGCTAACTCACATTAATTGCGTTGCGCTCACTGCCCGCTTTCCAGTCGGGAAACCTGTCGTGCCAGCAGATCTGAATTAATTCGGTCGAAAAAAGAAAAGGAGAGGGC CAAGAGGGAGGGCATTGGTGACTATTGAGCACGTGAGTATATATACCGTGATTAAGCACACAAAGGCAGCTTGGAGTATGTCTGTTATTAATTTCACAGGTAGTTCTGGTCC ATTGGTGAAAGTTTGCGGCTTGCAGAGCACAGAGGCCGCAGAATGTGCTCTAGATTCCGATGCTGACTTGCTGGGTATTATATGTGTGCCCAATAGAAAGAGAACAATTGAC CCGGTTATTGCAAGGAAAATTTCAAGTCTTGTAAAAGCATATAAAAATAGTTCAGGCACTCCGAAATACTTGGTTGGCGTGTTTCGTAATCAACCTAAGGAGGATGTTTTGG CTCTGGTCAATGATTACGGCATTGATATCGTCCAACTGCATGGAGATGAGTCGTGGCAAGAATACCAAGAGTTCCTCGGTTTGCCAGTTATTAAAAGACTCGTATTTCCAAA AGACTGCAACATACTACTCAGTGCAGCTTCACAGAAACCTCATTCGTTTATTCCCTTGTTTGATTCAGAAGCAGGTGGGACAGGTGAACTTTTGGATTGGAACTCGATTTCT GACTGGGTTGGAAGGCAAGAGAGCCCCGAAAGTTTACATTTTATGTTAGCTGGTGGACTGACGCCAGAAAATGTTGGTGATGCGCTTAGATTAAATGGCGTTATTGGTGTTG ATGTAAGCGGAGGTGTGGAGACAAATGGTGTAAAAGACTCTAACAAAATAGCAAATTTCGTCAAAAATGCTAAGAAATAGGTTATTACTGAGTAGTATTTATTTAAGTATTG TTTGTGCACTTGCCCAGATCTGCTGCATTAATGAATCGGCCAACGCGCGGGGAGAGGCGGTTTGCGTATTGGGCGCTCTTCCGCTTCCTCGCTCACTGACTCGCTGCGCTCG GTCGTTCGGCTGCGGCGAGCGGTATCAGCATCGATGCTCACTCAAAGGTCGGTAATACGGTTATCCACAGAATCAGGGGATAACGCAGGAAAGAACATGTGAGCAAAAGGCC AGCAAAAGGCCAGGAACCGTAAAAAGGCCGCGTTGCTGGCGTTTTTCCATAGGCTCCGCCCCCCTGACGAGCATCACAAAAATCGACGCTCAAGTCAGAGGTGGCGAAACCC GACAGGACTATAAAGATACCAGGCGTTTCCCCCTGGAAGCTCCCTCGTGCGCTCTCCTGTTCCGACCCTGCCGCTTACCGGATACCTGTCCGCCTTTCTCCCTTCGGGAAGC GTGGCGCTTTCTCATAGCTCACGCTGTAGGTATCTCAGTTCGGTGTAGGTCGTTCGCTCCAAGCTGGGCTGTGTGCACGAACCCCCCGTTCAGCCCGACCGCTGCGCCTTAT CCGGTAACTATCGTCTTGAGTCCAACCCGGTAAGACACGACTTATCGCCACTGGCAGCAGCCACTGGTAACAGGATTAGCAGAGCGAGGTATGTAGGCGGTGCTACAGAGTT CTTGAAGTGGTGGCCTAACTACGGCTACACTAGAAGGACAGTATTTGGTATCTGCGCTCTGCTGAAGCCAGTTACCTTCGGAAAAAGAGTTGGTAGCTCTTGATCCGGCAAA CAAACCACCGCTGGTAGCGGTGGTTTTTTTGTTTGCAAGCAGCAGATTACGCGCAGAAAAAAAGGATCTCAAGAAGACCTTTGATCTTTTCTACGGGGTCTGACGCTCAGTG GAACGAAAACTCACGTTAAGGGATTTTGGTCATGAGATTATCAAAAAGGATCTTCACCTAGATCCTTTTAAATTAAAAATGAAGTTTTAAATCAATCTAAAGTATATATGAG TAAACTTGGTCTGACAGTTACCAATGCTTAATCAGTGAGGCACCTATCTCAGCGATCTGTCTATTTCGTTCATCCATAGTTGCCTGACTCCCCGTCGTGTAGATAACTACGA TACGGGAGGGCTTACCATCTGGCCCCAGTGCTGCAATGATACCGCGAGACCCACGCTCACCGGCTCCAGATTTATCAGCAATAAACCAGCCAGCCGGAAGGGCCGAGCGCAG AAGTGGTCCTGCAACTTTATCCGCCTCCATCCAGTCTATTAATTGTTGCCGGGAAGCTAGAGTAAGTAGTTCGCCAGTTAATAGTTTGCGCAACGTTGTTGCCATTGCTACA GGATCGTGGTGTCACGCTCGTCGTTTGGTATGGCTTCATTCAGCTCCGGTTCCCAACGATCAAGGCGAGTTACATGATCCCCCATGTTGTGCAAAAAAGCGGTTAGCTCCTT CGGTCCTCCGATCGTTGTCAGAAGTAAGTTGGCCGCAGTGTTATCATCGCGCGTTTCGGTGATGACGGTGAAAACCTCTGACACATGCAGCTCCCGGAGACGGTCACAGCTT GTCTGTAAGCGGATGCCGGGAGCAGACAAGCCCGTCAGGGCGCGTCAGCGGGTGTTGGCGGGTGTCGGGGCTGGCTTAACTATGCGGCATCAGAGCAGATTGTACTGAGAGT GCACCATATGCGGTGTGAAATACCGCACAGATGCGTAAGGAGAAAATACCGCATCAGGCGCCATTCGCCATTCAGGCTGCGCAACTGTTGGGAAGGGCGATCGGTGCGGGCC TCTTCGCTATTACGCCAGCTGGCGAAAGGGGGATGTGCTGCAAGGCGATTAAGTTGGGTAACGCCAGGGTTTTCCCAGTCACGACGTTGTAAAACGACGGCCAGTGAATTCG AGCTCGGTACCCGGGGATCCTCTAGAGTCGACCTGCAGGCATGCAAGCTTGGCGTAATCATGGTCATAGCTGTTTCCTGTGTGAAATTGTTATCCGCTCACAATTCCACACA ACATACGAGCCGGAAGCATAAAGTGTAAAGCCTGGGGTGCCTAATGAGTGAGCTAACTCACATTAATTGCGTTGCGCTCACTGCCCGCTTTCCAGTCGGGAAACCTGTCGTG CCAGCAGATCTGAATTAATTCGGTCGAAAAAAGAAAAGGAGAGGGCCAAGAGGGAGGGCATTGGTGACTATTGAGCACGTGAGTATATATACCGTGATTAAGCACACAAAGG CAGCTTGGAGTATGTCTGTTATTAATTTCACAGGTAGTTCTGGTCCATTGGTGAAAGTTTGCGGCTTGCAGAGCACAGAGGCCGCAGAATGTGCTCTAGATTCCGATGCTGA CTTGCTGGGTATTATATGTGTGCCCAATAGAAAGAGAACAATTGACCCGGTTATTGCAAGGAAAATTTCAAGTCTTGTAAAAGCATATAAAAATAGTTCAGGCACTCCGAAA TACTTGGTTGGCGTGTTTCGTAATCAACCTAAGGAGGATGTTTTGGCTCTGGTCAATGATTACGGCATTGATATCGTCCAACTGCATGGAGATGAGTCGTGGCAAGAATACC AAGAGTTCCTCGGTTTGCCAGTTATTAAAAGACTCGTATTTCCAAAAGACTGCAACATACTACTCAGTGCAGCTTCACAGAAACCTCATTCGTTTATTCCCTTGTTTGAT 10

11 Strategies to find genes: Predictive methods: frames Stop codons (in the appropriate genetic code) * AUG codons (translation initiator) Predictive methods Interpretation of the DNA sequence into genes according to rules Watson strand 3> 3> 2> 2> 1> 1> Comparative methods Interpretation of the DNA sequence into genes according to similarities with other sequences Crick strand <1 <1 <2 <2 <3 < Experimental methods Interpretation of the DNA sequence into genes according to experimental results Genetics, mutations, mapping cdna libraries Expression data on microarrays RNA seq ORF (open reading frame): a DNA sequence betweeen two STOP codons. It is presumed to be the sequence of a protein coding gene CDS (coding sequence): a DNA sequence betweeen a START and a STOP codon Predictive methods: CAI = mesurement of the bias in codon usage (Sharp and Li, 1987) TTT phe F 2.7 TCT ser S 2.3 TAT tyr Y 1.9 TGT cys C 0.8 TTC phe F 1.8 TCC ser S 1.4 TAC tyr Y 1.4 TGC cys C 0.5 TTA leu L 2.7 TCA ser S 1.9 TAA OCH * TGA OPA * TTG leu L 2.7 TCG ser S 0.9 TAG AMB * TGG trp W 1.0 CTT leu L 1.2 CCT pro P 1.3 CAT his H 1.4 CGT arg R 0.6 Discrepency of the genetic code > synonymous codons Bias due to the different translational efficiencies of codons Reference table of relative synonymous codon usage values (RSCU) from highly expressed genes: CTC leu L 0.5 CCC pro P 0.7 CAC his H 0.8 CGC arg R 0.3 CTA leu L 1.4 CCA pro P 1.8 CAA gln Q 2.7 CGA arg R 0.3 CTG leu L 1.1 CCG pro P 0.5 CAG gln Q 1.2 CGG arg R 0.2 ATT ile I 3.0 ACT thr T 2.0 AAT asn N 3.6 AGT ser S 1.5 ATC ile I 1.7 ACC thr T 1.2 AAC asn N 2.5 AGC ser S 1.0 ATA ile I 1.8 ACA thr T 1.8 AAA lys K 4.3 AGA arg R 2.1 RSCU Phe UUU UUC ATG met M 2.1 ACG thr T 0.8 AAG lys K 3.1 AGG arg R 1.0 GTT val V 2.2 GCT ala A 2.0 GAT asp D 3.8 GGT gly G 2.3 GTC val V 1.1 GCC ala A 1.2 GAC asp D 2.0 GGC gly G 1.0 GTA val V 1.2 GCA ala A 1.6 GAA glu E 4.6 GGA gly G 1.1 GTG val V 1.1 GCG ala A 0.6 GAG glu E 2.0 GGG gly G 0.6 Ile AUU AUC AUA RSCU = freq obs freq exp 11

12 CAI = mesurement of the bias in codon usage Mirror effects CAI = CAI obs / CAI max YPR080w (TEF1) translation elongation factor EF-1 alpha with CAI obs = ( II L RSCU k ) 1/L K=1 CAI max = (II RSCU kmax ) 1/L L 3> 3> 2> 2> 1> 1> <1 <1 <2 <2 <3 <3 and K=1 RSCU = relative synonymous codon usage disregarded ORF Comparative methods: FTI1: RAD52 inhibitor One homolog (Pichia sorbitophila) YKR035wa > 3> 2> 2> 1> 1> <1 <1 <2 <2 <3 < YKR035c No homolog Frames A segment of the S. cerevisiae genome delta trna Ala YKL121w YKL120w PMT1 Entirely included ORFs were disregarded YKL119c VPH2 YKL117w YKL116c YKL114c APN1 Partially overlapping ORFs were considered Proportion gènes/génome : 75% du genome de S. cerevisiae 1,5% du génome humain (40% including introns) 0,05% du génome de certaines plantes

13 S. cerevisiae genome: - 12 Megabases - 16 chromosomes I II III IV V VI VII VIII IX X XI XII XIII XIV XV XVI mt small ORFs Basrai et al. (1997) Genome Research, 7, «Small ORFs: Beautiful needles in the haystack» protein-coding genes 140 rrna genes 274 trna genes - only 4% of intron-containing genes - 40% of the genes belong to families -ORFs occupy 72% of the genome! ORFs < 100 codons 299 sorfs (Functional genomics of genes with small open reading frames (sorfs) in S. cerevisiae Kastenmayer et al, Genome Research, 2006) HRA1 antisens to DRS2: DRS2 GOLGI-membrane located transport protein phenotype involved in maturation of 18S rrna? A novel type of genetic elements: CUTs (cryptic unstable transcripts) Two forms of the exosome in S. cerevisiae Ski3 Degradation of mrnas HRA1 Ski2 Ski8 Rrp4 Rrp41 Rrp44 Exosome = 3' 5' exonucleases mrna 5'UTR 3'UTR AAAAAAAAAA Responsible for the rrna processing phenotype Samanta et al., PNAS (2006); Global identification of noncoding RNAs in S. cerevisiae Cytoplasm Nucleus Rrp4 Rrp41 Rrp44 Rrp6 Rrp47 Maturation/degradation of rrnas, snrnas, snornas and trnas ncrna Wyers et al. Cell,

14 A novel type of genetic elements: CUTs (cryptic unstable transcripts) A novel type of genetic elements: CUTs (cryptic unstable transcripts) Neil et al., Nature 2009 Neil et al., Nature 2009 Eukaryotic promoters are intrinsically bidirectional!!! Repression of serine biosynthesis SRG1 SER3 Activation of serine catabolism CAT1 14

15 CONCLUSIONS : -séquencer des génomes n est plus vraiment limitant - Annotation aisée des gènes codant pour des protéines et pour quelques types de gènes d ARN - La fraction ARN informative des génomes est vraisemblablement très sous-estimée et très difficile à annoter - Trouver TOUS les gènes d un organisme reste un véritable chalenge 15