Searching for functional regions (coding or non-coding) Searching for functional regions (coding or non-coding) in mammalian genomes in mammalian genomes

Organization of the human genome Human genome project: present status Human sequence data in GenBank/EMBL Prediction of functional elements by computer analysis of

genomic sequences State of the art Success and pitfalls of different approaches

Prediction of function by homology Orthology/paralogy

Functional elements in the human genomeFunctional elements in the human genome

3.4 109 nt 50,000-100,000 protein-coding genes

81% no known function43%38%introns4%12%protein-coding regions

centromeres, telomeres,

RNA2%intergenic

Untranslated RNAs: Xist, H19, His-1, bic, etc.

Regulatory elements: promoters, enhancers, etc.

Repeated sequences (SINES, LINES, HERV, etc.) : 40% of the human genome

Repeat SequencesRepeat Sequences

Tandem repeats

motif bloc size % human genome satellite: 2-2000 nt up to 10 Mb 10% minisatellite: 2-64 nt 100-20,000 bp ? microsatellite: 1-6 nt 10-100 bp 2%

Interspersed repeats

SINE (non-autonomous retroelement) LINE (retrotransposon) Endogenous Retrovirus (HERV, LTR- retrotransposon) DNA transposons

Fréquence des éléments transposables Fréquence des éléments transposables dans le génome humaindans le génome humain

Total = 42% (Smit 1999)

0%4%8%12%AluLINE1MIRLINE2LTR elementsDNAtranposon

RetropseudogènesRetropseudogènes

23,000 à 33,000 retropseudogènes dans le génome humain (6-10 copies / Mb)

Les gènes qui génèrent des retropseudogènes sont généralement de type housekeeping

Gonçalves et al. 2000

Structure of human protein genesStructure of human protein genes

1396 complete human genes (exons + introns) from GenBank Average size (25%, 75%)

Gene 15 kb ± 23 kb (4, 16) (10% > 35 kb) CDS 1300 nt ± 1200 (600, 1500) Exon (coding) 200 nt ± 180 (110, 200) Intron 1800 nt ± 3000 (500, 2000) 5'UTR 210 nt (Pesole et al. 1999) 3'UTR 740 nt (Pesole et al. 1999)

Intron/exon Number of introns: 6 ±3 introns / kb CDS Introns / (introns + CDS): 80% 5' introns in 15% of genes (more ?), 3 ’introns very rare

Alternative splicing in more than 30% of human genes (Hanke et al. 1999)

Structure of human protein genesStructure of human protein genes GenBank: bias towards short genes 1396 complete human genes (exons + introns)

≤949596979899Publication date48121620Gene size (coding exons+introns) kb

5101520253035≤949596979899Publication dateGene size (coding exons+introns) kb

Structure of human protein genesStructure of human protein genes GenBank: bias towards short genes 1396 complete human genes (exons + introns) 9268 complete human mRNA

Sequence:cDNA

complete gene (exons+introns)

400800120016002000889092949698Average CDS size (nt)Publication date

Isochore organization of the human genomeIsochore organization of the human genome

Insertion of repeated sequences (A. Smit 1996) Recombination frequency (Eyre-Walker 1993) Chromosome banding (Saccone, 1993) Replication timing (Bernardi, 1998) Gene density (Mouchiroud, 1991) Gene expression ?? -> No Gene structure (Duret, 1995)

isochore %C+G % total genomic DNA

L1+L2 : 33%-44% 62 %

H1+H2 : 44%-51% 31%

H3 : 51%-60% 3-5%

H1+H2L1+L2H3H1+H2L1+L2L1+L2>300 kbBernardi et al. 1985

Isochores and insertion of repeat sequencesIsochores and insertion of repeat sequences

4%8%12%16%20%AluLINE-1LTR-

elements

Density in repeat sequencesG+C content of genomic sequence:G+C < 39%G+C > 47%G+C 39%-47%

4419 human genomic sequences > 50 kb4419 human genomic sequences > 50 kb

Isochores and gene densityIsochores and gene density

MHC locus (3.6 Mb) MHC locus (3.6 Mb) (The MHC sequencing consortium 1999)(The MHC sequencing consortium 1999)

Class I, class II (H1-H2 isochores): 20 genes/Mb, many pseudogenesClass I, class II (H1-H2 isochores): 20 genes/Mb, many pseudogenesClass III (H3 isochore): 84 genes/Mb, no pseudogeneClass III (H3 isochore): 84 genes/Mb, no pseudogene

Class II boundaries correlate with switching of replication timingClass II boundaries correlate with switching of replication timing

isochore % total genomic DNA %total genes

L1+L2 : 62 % 31%

H1+H2 : 31% 39%

H3 : 3-5% 30%

2060100140Number of genes / MbL1+L2H1+H2H3Mouchiroud et al. 1991

Isochores and introns lengthIsochores and introns length

760 complete human genes L1L2: intron G+C content < 46% H1H2: intron G+C content 46-54% H3: intron G+C content >54%

Average intron length (bp)Gene compaction (intron length/coding region length)40080012001600200024681012L1L2H1H2H3L1L2H1H2H3

Duret, Mouchiroud and Gautier, 1995

Sequencing Projects :Sequencing Projects :Genome / TranscriptomeGenome / Transcriptome

gene (DNA)messenger RNA (mRNA)proteinexonintrontranscription, maturationtranslationchromosome (DNA)AAAAAAAA50-250 106 nt5-50 103 nt1-10 103 ntGenomeprojectsTranscriptomeprojects (ESTs)

Expressed Sequence TagsExpressed Sequence Tags (ESTs) (ESTs)

Inventory of all mRNAs expressed by an organism, in different tissues, development stages, pathologies, …

Single pass sequences: high error rate (>1%), partial mRNA sequences Usually derived from poly-dT-primed cDNA -> bad coverage of 5' regions of long mRNAs 60-80% of human genes represented in public EST database, but only 25-50% of the total

coding part of the genome

Homo sapiens 2,461,893 Mus musculus (mouse) 1,661,949 Rattus sp. (rat) 188,736

Number of ESTs (Sep. 2000)Number of ESTs (Sep. 2000)

large insert DNA library (BAC): 150-250 kbgenomesmall insert library (M13)sequencingcontig assemblyfinished sequencecloningsub-cloningfinishing (filling gaps)Phase 0 single-few pass reads of a single clone (not contigs).Phase 1 Unfinished, may be unordered, unoriented contigs, with gaps.Phase 2 Unfinished, ordered, oriented contigs, with or without gaps. Phase 3 Finished, no gaps (with or without annotations)

GenBank/EMBL divisionPhase 0

Phase 1

Phase 2

Phase 3

HTG PRI (nr)GenBank/EMBL HTG division : High Troughput Genome sequences

Genomic SequencesGenomic Sequences

(draft)(draft)

Exponential growth of sequence dataExponential growth of sequence data

Doubling time: 13 mounths

-500

0

500

1000

1500

2000

2500

3000

3500

82 86 90 94 98Date

0.1

1

10

100

1000

10000

82 86 90 94 98Date

Publicly available sequences (Mb)

Human Genome Sequence DataHuman Genome Sequence Data Traditional sequences: correspond to biologically

characterized genes, annotated by reearchers or database curators, usually relatively short (<20,000).

Finished genome sequences: long contiguous sequences, correspond to clones (cosmid, BAC, PAC); partly automatically generated annotations covers repetitive elements, kown and predicted genes, EST matches

Unfinished genome sequences (draft): large sequence entries consisting of unordered pieces separated by runs of N's, correspond to clones, contain minimal annotation.

Genome survey sequences: low-quality, single pass sequences from a variety of different projects (BAC end sequencing, polymorphism studies, CpG islands, etc.), minimal annotation.

Different types of nucleotide sequences in current databasesDifferent types of nucleotide sequences in current databases

StandardHigh throughput genome (HTG)

Genome survey sequence (GSS)

Expressed sequence tags (EST)

Contents

biologically characterized genes and RNAs, finished clones from genome projects

unfinished clones from genome projects

single pass sequences from random genomic clones

single pass sequences from random cDNA clones

Length variable >20,000 bp <1,000 bp <1,000 bp

Accuracy medium-high high low low

Annotation

medium to high, rich biological annotation

technically use- ful, biologically poor

technically use- ful, biologically poor

technically use- ful, biologically poor

GenBank release 119 (September 28, 2000)GenBank release 119 (September 28, 2000)

Division Entries Nucleotides % nt

EST 5,843,794 2,337,244,350 23%

HTG 77,960 4,373,497,668 44%

GSS 1,724,845 951,450,849 9%

PRI 135,144 1,073,472,484 11%

Other 882,631 1,296,473,741 13%

Total 8,664,374 10,032,139,092 100%

Human 3,518,824 6,253,704,359 62%

The human genome sequencing projectThe human genome sequencing projectWhere are we today (July 17 2000) ?Where are we today (July 17 2000) ?

According to Phillip Bucher (SIB, Lausanne) statistics and genome coverage estimates (see also EBI's statistics: http://www.ebi.ac.uk/~sterk/ genome-MOT)

Estimated size of human genome 3260 MB 100.00%

EMBL sequences in HUM division: 770 MB 23.60%(7858 entries, ave. Size: 101.3 kb)

Human sequences in HTG division: 3629 MB 111.30%(23681 entries, ave. Size: 153.3 kb)

Total: 4399 MB 134.90%

Estimated redundancy (35%) -1540 MB -47.70%

Corrected total: 2859 MB 87.90%

Next steps in genome projectsNext steps in genome projects

Identify genes and other functional elements within genomic sequence (where are the genes ?)

Determine the function of genes (what do they do ?)

Prediction of functional elements (1)Prediction of functional elements (1) Ab initio methods

Ruled-based or statistical methods e.g.: protein genes prediction, promoter prediction, … Very useful but ...

Limits in sensibility/specificity No method available for many functional elements (non-coding RNA

genes, regulatory elements, …)

Prédiction Prédiction ab initioab initio de gènes eucaryotes de gènes eucaryotes

Prédiction d ’exons codants Recherche de phases ouvertes de lecture (ORF: open reading frame)

– Taille moyenne des exons: ± 150 nt Statistiques sur les nucléotides, usage des codons

– Périodicité d'ordre 3, fréquence d ’hexamères– Modèles de Markov cachés

Signaux d ’épissage– Profils, modèles de Markov cachés, réseau neuronaux

Construction d ’un modèle de gène protéique Combinaison d ’exons de phases compatibles (pondération en fonction des scores de chaque exon

potentiel) Recherche de limites de gènes

– Exons terminaux (5 ’, 3 ’)– Promoteur– Signal de polyadénylation

Epissage alternatif ?? Exons non codants ?? Gène transcrits non codants (Xist, …) ??

Prédiction de gènes eucaryotes: Prédiction de gènes eucaryotes: qualité de la prédictionqualité de la prédiction

Comparaison des différents logiciels: sensibilité/spécificité Sn: sensibilité Sp: spécificité par exon (sn_e, sp_e) ou par nucéotide (sn_e, sp_e)

Jeu de données Burset-Guigo (1996): 570 gènes de vertébrés

Jeu de données Salamov et al (1998): 660 gènes humains

Sn_e Sp_e Sn_n Sp_nGenScan 0.78 0.81 0.93 0.93FGENES 1.6 0.83 0.82 0.92 0.93Grail2 0.36 0.43 0.72 0.87

Sn_e Sp_e Sn_n Sp_nGenScan 0.70 0.71 0.92 0.90FGENES 1.6 0.77 0.77 0.90 0.91

Prédiction de gènes eucaryotes: Prédiction de gènes eucaryotes: qualité de la prédictionqualité de la prédiction

Comparaison des différents logiciels: sensibilité/spécificité Sn: sensibilité Sp: spécificité par exon (sn_e, sp_e) ou par nucéotide (sn_e, sp_e)

Locus BRCA2 (1.4 Mb, chrom. 13q) (Sanger Centre 1999): région "difficile" pour les logiciels de prédiction. 159 exons

Sn_e Sp_e Sn_n Sp_nGenScan 0.66 0.36 0.81 0.44FGENES 1.6 0.69 0.57 0.79 0.66FGENES 1.6 masked 0.69 0.65 0.79 0.74GenScan+FGENES 0.61 0.82 0.67 0.90

Prédiction de gènes protéiques completsPrédiction de gènes protéiques complets C. elegans: la plupart des ‘ gènes ’ annotés sont seulement des prédictions Peut-on utiliser ces méthodes pour annoter les séquences génomique humaines ?

+ les faux positifs !

00.20.40.60.8113579111315Sensibilité par exon:90%80%

Probabilité de détecter tous les exons d’un gènesNombre d’exons du gène

Un peu d ’optimismeUn peu d ’optimisme Fraction de la longueur des gènes correctement prédits:

70-80%

Probabilité que deux exons potentiels consécutifs soient réels (et donc positifs en RT-PCR)

0.5

Prediction of functional elements (2)Prediction of functional elements (2)

Large scale transcriptome projects: ESTs, full-length cDNA Identification of transcribed genes (protein or non-coding RNA) Information on alternative splicing, polyadenylation (Hanke et al.

1999, Gautheret et al. 1998), expression pattern SIM4: align a cDNA to genomic DNA Very useful but ...

Problems with genes expressed at low level, narrow tissue distribution, stage-specific expression, …

Limited tissue sampling Artifacts in ESTs (introns, partially matured RNA, …) Limited to polyadenylated RNA

Prediction of functional elements (3)Prediction of functional elements (3) Comparative sequence analysis (phylogenetic footprinting)

Function => selective pressure

Corollary Sequence conservation = selective pressure = function

provided the number of aligned homologous sequences represents enough evolutionary time for the accumulation of mutations at the less constrained (presumably selectively neutral)

base positions.

Evolutionary rate in non-functional DNA: ~ 0.3% / My (± 0.069)

Man/Mouse: ~ 80 Myrs 46-58% identity

Mammals/Birds: ~ 300 Myr 26-28% identity

Random sequences 25% identity

Analyse comparative des gènes de Analyse comparative des gènes de -actine de l'homme et de la carpe-actine de l'homme et de la carpe

CarpeHomme5’UTR 3’UTR site polyA échelle de similarité: pas de similarité significative70 - 80% identité80 - 90% identitérégions codantes: éléments régulateurs:introns:ATGcodon stop

Phylogenetic footprintingPhylogenetic footprinting Advantages

Works for all kinds of functional elements (transcribed or not, coding or not) as far as the information is in the primary sequence

Does not require any a priori knowledge of the functional elements

Limits Absence of evolutionary conservation does not mean absence of function No efficient method to detect unknown conserved secondary structure in RNA Function, but what function ? Depends on the sequencing status of other genomes

Human, mouse, fugu, C. elegans, drosophila, yeast, A. thaliana Number of sequences to compare : > 200 Myrs of evolution

Mammals/birds: 310 Myrs Human + mouse + bovine : 240 Myrs

Prédiction de gènes eucaryotes (suite)Prédiction de gènes eucaryotes (suite)

Approche comparative Comparaison d ’une séquence génomique avec des gènes déjà caractérisés

dans d ’autres espèces (WISE2: alignement ADN/protéine avec épissage) Comparaison de séquences génomiques (non-annotées) homologues

– Locus mnd2 (homme souris) (Jang et al. 1999): >80 kb– Prédiction d ’exons internes basée sur la conservation de séquence

ORF ≥ 80 nt

Séquence protéique ≥ 70% similarité

Séquence ADN ≥50% identité

GT AG conservés

=> détection de tous les exons internes du gène D6Mm5e

– Généralisation de la méthode (Guigo 2000). Sensibilité ? Spécificité ?

Next steps in genome projectsNext steps in genome projects

Identify genes and other functional elements within genomic sequence (where are the genes ?)

Determine the function of genes (what do they do ?)

Prédiction de fonction par homologie ?Prédiction de fonction par homologie ? Similarité entre séquences homologie Homologie structure conservée Structure conservée fonction conservée

Oui, mais … Fonction: concept flou

– activité biochimique identique ? e.g. même ligand pour un récepteur, même substrat pour une enzyme, même gènes cibles pour un facteur de transcription.

– distribution tissulaire ? (isoformes tissu-spécifiques).– compartimentalisation cellulaire: cytoplasme, mitochondrie, etc.

Protéines homologues de fonction différentes – Protéines homologues ligands (activateur/répresseur) d ’un même récepteur– Recrutement pour une fonction totalement différente: -cristalline / -énolase

Orthologie/paralogie

Évolution modulaire

Prédiction de fonction par homologie ?Prédiction de fonction par homologie ?

MZEORFG: 1 ILNSPDRACNLAKQAFDEAISELDSLGEESYKDSTLIMQLLXDNLTLWTSDTNEDGGDE 59

I N+P++AC LAKQAFD+AI+ELD+L E+SYKDSTLIMQLL DNLTLWTSD ++ E

BOV1433P: 186 IQNAPEQACLLAKQAFDDAIAELDTLNEDSYKDSTLIMQLLRDNLTLWTSDQQDEEAGE 244

Score = 87.4 bits (213), Expect = 1e-17

Identities = 41/59 (69%), Positives = 50/59 (84%)

LOCUS BOV1433P 1696 bp mRNA MAM 26-APR-1993

DEFINITION Bovine brain-specific 14-3-3 protein eta chain mRNA, complete cds.

ACCESSION J03868

LOCUS MZEORFG 187 bp mRNA PLN 31-MAY-1994

DEFINITION Zea mays putative brain specific 14-3-3 protein, tau protein

homolog mRNA, partial cds.

Orthologie/paralogieOrthologie/paralogiespéciationduplicationPrimatesRongeursHommeRatGène ancestral

de l’insulineSourisRatSourisINSINS1INS1INS1INS2INS2INS2Homologie: deux gènes sont homologues si ils ont un ancêtre commun

Orthologie: deux gènes sont orthologues si ils ont divergé à la suite d’un évènement de spéciation

Paralogie: deux gènes sont paralogues si ils ont divergé à la suite d’un évènement de duplication

Orthologie ≠ équivalence fonctionnelle

!

Approche phylogénétique pour la prédiction de fonction

1) Identifier les homologues

2) Aligner les séquences

3) Calculer l’arbre phylogénétique

2A3A1A1B2B3B2A3A1A1B2B3B2A3A1A1B2B3B2A3A1A1B2B3B2ADuplication de gènes4) Placer les fonctions connues sur l’arbre

5) Inférer la fonction probable des gènes

Evolution modulaire

ABC

Prédiction de régions régulatricesPrédiction de régions régulatrices

Méthodes ab initio

Prédiction de promoteurs Îlots CpG

Approche comparative

Large scale phylogenetic Large scale phylogenetic footprintingfootprinting

Non-coding sequences : 325,247 sequences 145 Mb

everything except protein-coding regions and structural RNA genes (rRNA, tRNA, snRNA, scRNA)

Introns, 5' and 3' untranslated regions, intergenic sequences

Filtering of microsatellite repeats and cloning vectors: XBLAST

Similarity search: BLASTN + LFASTA

Vertebrates, insects, nematode

Metazoan Genome ProjectsMetazoan Genome ProjectsMillion yearsPorifera (sponge)Nematodes (C. elegans)Arthropods (Drosophila)EchinodermsUrochordataCephalochordata (amphioxus)Jawless fisheschondrichthyes (ray, shark)actinopterygii (bony fishes)amphibians mammals birds reptiles600400200800VertebratesSequencing effort: 9 to 100 Mb 0.8 to 2.4 Mb less than 0.2 Mb

Sequence SimilaritiesSequence Similarities1- Identification of new genes

protein-genes, RNA-genes: intronic snoRNA genes

2- Retroviral elements, retrotransposons

3- Low complexity sequences:

GC-rich, AT-rich, cryptic microsatellites

4- Artefacts:

annotation errors, sample contamination (sponge insulin, ascidian RNA, chicken TGFB1)

5- 326 highly conserved regions (HCRs)

- do not code for proteins

- do not correspond to any known structural RNA

326 Highly Conserved 326 Highly Conserved Regions (HCRs)Regions (HCRs)

• > 70% identity over 50 to 2000 nt after more than 300 Myrs

• Unique sequences

• Generally specific of only one gene

• Longest HCR:

84% identity over 1930 nt after 300 Myrs

3’UTR deltaEF1 transcription factor

• Oldest HCRs: 500 to 600 Myrs

• No HCR between vertebrates and insects or nematode

Oldest HCRsOldest HCRsMillion yearsPorifera (sponge)Nematodes (C. elegans)Arthropods (Drosophila)EchinodermsUrochordataCephalochordata (amphioxus)Jawless fisheschondrichthyes (ray, shark)actinopterygii (bony fishes)amphibians mammals birds reptiles600400200800Sequencing effort: 9 to 100 Mb 0.8 to 2.4 Mb less than 0.2 MbHistone 3’UTR- actin3’UTR

3 5’HOX UTRVertebrates

Conservation pattern in Conservation pattern in 3’UTRs3’UTRs

position relative to the stop codon (nt)10005000150020002400c-fosTransferrin receptorbirdmammalEndoplasmic-reticulum Ca2+ ATPase birdmammalbirdmammalsimilarity: <60% ≥60% ≥70% ≥80%

Distribution of HCRs within Distribution of HCRs within genesgenes3'-non-coding5'-non-codingintrons0%10%20%30%40%mammals / birdsmammals / amphibiansmammals / bony fishes2841917296512563812 Frequency of orthologous

genes containing HCRs

HCRs and multigenic familiesHCRs and multigenic familiesHistone replacement variant H3.3A0400600100014001800AAAAAAAAUGStopAUGStopAAAAAAAHistone replacement variant H3.3BHistone replacement variant H3.3A and H3.3B, Calmodulinsnt• several genes coding for a same protein

• non-coding sequences are distinct, and conserved

Function of 3’HCRs: Function of 3’HCRs: mRNA stability, translationmRNA stability, translationA+U-rich element: stability, translationposition relative to the stop codon (nt)10005000150020002400c-fosTransferrin receptorbirdmammalbirdmammalsimilarity: <60% ≥60% ≥70% ≥80%IRE : Iron Responsive Element

IRP : Iron Regulatory Protein

CCAGUGN5'3'

Function of 3’HCRs:Function of 3’HCRs:mRNA subcellular localizationmRNA subcellular localization

Myosin heavy chain, c-myc, vimentin, -actin

chickencarp (bony fish)site poly(A)site poly(A)0200400600800position relative to the stop codon (nt)localization signalssimilarity: <60% ≥60% ≥70% ≥80%- 3’actin UTR