March 9, 2007 Bologna, February 2007 1
the complexity of human genes
The ENCODE Genes & Transcripts group
Roderic Guigó Centre de Regulació Genòmica, Barcelona
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genes and proteins
• One gene, one enzymeBeadle and Tatum
• The Central DogmaFrancis Crick
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from DNA to proteins
most of the transcriptional output of the human genome is localized in well defined genomic loci, which encode mRNAs that, when exported into the cytosol, are translated into proteins
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• 1% of the genome. 44 regions
• target selection. commitee to select sequence targets
– manual targets – a lot of information
– radom targets – stratified by non exonic conservation with mouse gene density
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m001
m002
m003
m004m005m007
m008
m009m010m011
m012m013
m014
r111
r112
r113
r114
r121
r122
r123
r131
r132
r133
r211
r212
r213
r221
r222
r223
r231
r232
r233r311
r312
r313
r321
r322
r323
r334
r324
m006
r331
r332
r333
12
3 4 5
6 987 10 1211
13 1514
2019
16
2221 Y
X
17 18
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Long-range regulatory elements(enhancers, repressors/silencers,
insulators)
Cis-regulatory elements(promoters, transcription factor binding
sites)
DNA Replication
DNase Hypersensitive
Sites
Genes and Transcripts
Epigenetic
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gencode: encyclopedia of
genes and gene variants
• Roderic Guigó, IMIM-UPF-CRG• Stylianos Antonarakis, Geneve
Alexandre Reymond• Ewan Birney, EBI• Michael Brent, WashU• Lior Pachter, Berkeley• Manolis Dermitzkakis, Sanger• Jennifer Ashurst, Tim Hubbard
identify all protein coding genes in the ENCODE regions:• identify one complete mRNA sequence for at least one splice isoform of each protein coding gene.
• eventually, identify a number of additional alternative splice forms.
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the gencode pipeline
1. mapping of known transcripts sequences (ESTs, cDNAs, proteins) into the human genome
2. manual curation to resolve conflicting evidence3. additional computational predictions4. experimental verification5. FINAL ANNOTATION
THE GENCODE PIPELINE
manual curation: havana (sanger)experimental verification:genevabioinformatics: imim
•2608 transcripts in 487 loci•137 transcripts in 53 non-coding loci•1097 coding transcripts and 1374 non-coding transcripts in 434 protein coding loci
most of protein coding loci encode a mixture of protein coding and non-coding transcripts
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one gene - many proteinsvery complex transcription units
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chimering tandem transcription / intergenic splicing
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KUA and UEV, Thomson et al., Genome Research 2000
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systematic search for functional chimeras in ENCODE:165 tandem pairs in the same orientation126 chimeric predictions obtained96 tested, at least 4 positve
Parra et al., Genome Research 2006Akiva et al., Genome Research 2006
Locus RP11-298J23.1 codes for pepsinogen C. The structure of pepsinogen C is 1htrA.
Isoform -003 is missing 80 residues with respect to pepsinogen C. Here the missing section of -003 is in light green.
The missing section in this isoform would remove the core from both subdomains of the structure. Both the N-terminal sub-domain (on the left) and the C-terminal sub-domain would have to refold.
This is the view from above looking down into the active cleft of the proteinase. Active site aspartates are shown in ball and chain. One of the two active site residues is in the missing section.
The symmetry apparent in this isoform suggests that although it will have to refold it may very well be able to reform into a single subdomain.
Structural Effects of Pepsinogen C Alternative Splice Variant
Michael Tress & Alfonso ValenciaCNB, Madrid
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ITGB4B
11 supporting ESTs
Adam FrankishSanger
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ALL EXONS
CODING EXONS
GENCODE vs OTHER
GENE SETS
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from the ENCODE Chromatin and Replication Group, John Stamatoyannopoulos
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EGASP’05• the complete annotation of 13 regions was
released in january 30. – The annotation of the remaining 31 regions was
being obtained, and it was withheld.
• gene prediction groups were asked to submit predictions by april 15 in the remaining 31 regions.– 18 groups participated, submiting 30 prediction
sets
• predictions were compared to the annoations in an NHGRI sponsored workshop at the Wellcome Trust Sanger Institute, on may 6 and 7.
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EGASP’05• two main goals:
1. to assess how automatic methods are able to reproduce the (costly) manual/computational/experimental gencode annotation
2. how complete is the gencode annotation. are there still genes consistenly predicted by computational methods
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accuracy measures
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accuracy at the coding exon level
evidence-baseddual genome“ab intio”
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accuracy at the exon level
evidence-baseddual genome“ab intio”
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programs are quite good at calling the protein coding exons (accuracy at 80%) Not as good at calling the transcribed exons), but the best of the programs
predict correctly only 40% of the complete transcripts (considering only the coding fraction)
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many novel exons predicted:
- 8,634 unique exons predicted in intergenic regions- we ranked the exons according to the accuracy of te predicted programs- tested 238 exon pairs by RT-PCR in 24 tissues- only 7 (less than 3%) were confirmed positive
PROGRAMGENEMARK.2 2802 2080Ecgene 2661 1545AUGUSTUS.7 2629 2580EXONHUNTER.3 1869 1373DOGFISH-CE.4 1857 1820Genscan 1233 900GENEZILLA.2 1217 849Acembly 1162 750TWINSCAN-MARS.4 796 388FGENESH++.1 546 452SAGA.4 504 390Geneid 500 331SGP 393 245ACEVIEW.3 377 301AUGUSTUS.2 372 214SPIDA.7 332 309AUGUSTUS.4 274 142N-SCAN.4 252 183N-SCAN.5 252 183Twinscan 232 67AUGUSTUS.1 215 94AUGUSTUS.3 206 94EXOGEAN.3 154 84PAIRAGON+N-SCAN.1 151 128PAIRAGON+N-SCAN.3 151 128J IGSAW.1 88 47ENSEMBL.3 86 54DOGFISH-CE.7 1 1
nbr of exons not overlapping
annotated exons
nbr of exons intergenic to annotations
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Long-range regulatory elements(enhancers, repressors/silencers,
insulators)
Cis-regulatory elements(promoters, transcription factor binding
sites)
DNA Replication
DNase Hypersensitive
Sites
Genes and Transcripts
Epigenetic
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TRANSCRIPTION OF PROCESSED POLY A+ RNA
based on a number of high throughput tecnologies
0.1%24,939Ditags*
14.7%2,355,238TOTAL UNIQUE
Transcribed Bases
0.5%151,149CAGE Tags*
9.3%1,278,588transfrag/tar
9.8%1,650,821Annotated exons
% nucleotides
covered
Nb of nucleotide
covered
Total # of nucleotides : 29,998,060
non repeat masked : 14,707,189
13618240(92.6%)
9767311(66.4%)
11763410(80.0%)
9496360(64.6%)
3545358(24.1%)
2163303(14.7%)
1369304(9.3%)
19629(0.1%)
116013(0.8%)
1447192(9.8%)
49.1470718929998060INTERROGATED
27325931(91.1%)
19658563(65.5%)
23318182(77.7%)
17758738(59.2%)
4826292(16.1%)
2519280(8.4%)
1369611(4.6%)
24939(0.1%)
151149(0.5%)
1776157(5.9%)
49.1470718929998060TOTAL(interrogated and uninterrogated)
Total Bases 12
(%)*
BasesbetweenPETs 11
(%)*
Baseswith5'RACE
10(%)*
BasesinExonsandIntrons 9
(%)*
Basesin PT(ESTsincluded) 8
(%)*
Total Basesin PT 7
(%)*
bp inTF 6
(%)*
bpinPET 5
(%)*
bp inCAGEtags 4
(%)*
bp inExons 3
(%)*%
TotalInterro-gatedBases 2
TotalBases 1
PRIMARY TRANSCRIPTSPROCESSED TRANSCRIPTS (PT)
Table 1: Summary of Transcriptional Coverage of ENCODE Regions.
13618240(92.6%)
9767311(66.4%)
11763410(80.0%)
9496360(64.6%)
3545358(24.1%)
2163303(14.7%)
1369304(9.3%)
19629(0.1%)
116013(0.8%)
1447192(9.8%)
49.1470718929998060INTERROGATED
27325931(91.1%)
19658563(65.5%)
23318182(77.7%)
17758738(59.2%)
4826292(16.1%)
2519280(8.4%)
1369611(4.6%)
24939(0.1%)
151149(0.5%)
1776157(5.9%)
49.1470718929998060TOTAL(interrogated and uninterrogated)
Total Bases 12
(%)*
BasesbetweenPETs 11
(%)*
Baseswith5'RACE
10(%)*
BasesinExonsandIntrons 9
(%)*
Basesin PT(ESTsincluded) 8
(%)*
Total Basesin PT 7
(%)*
bp inTF 6
(%)*
bpinPET 5
(%)*
bp inCAGEtags 4
(%)*
bp inExons 3
(%)*%
TotalInterro-gatedBases 2
TotalBases 1
PRIMARY TRANSCRIPTSPROCESSED TRANSCRIPTS (PT)
Table 1: Summary of Transcriptional Coverage of ENCODE Regions.
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tiling arrays reveal many novel sites of transcription
TRANSCRIPTION MAP of HL-60 DEVELOPMENTAL TIME COURSE (data by Tom Gingeras, affymerix)
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characteristics of unannotated transfrags
• short: 78bp on average compared with 121 for exonic transfrags
• very gc-rich: 56% vs 42% in the background of unannoated regions
• lack splice sites• no matches to protein or domain databases• lack of selective constraintsHOWEVER:• reproducible across cell lines• support by independent evidence of
transcription (mostly unspliced ESTs).• enriched for RNA structures.
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Denoeud et al., “Prominent use of distal 5’ transcription start sites and discovery of a large number of additional exons in ENCODE regions”, accepted for publication Genome Research
•5’ RACE on 12 tissues•primers in internal exons of 399 protein coding loci•RACE products hybridized into genome tiling arrays
–4573 race exons detected. 2324 novel
the RACE/array experiments
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Target gene
5’ RACE from TMEM15 Gene (region Enr232) identifies several tissue specific distal 5’ exons.
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distal RACEfrags are associated to independently predictes sites of transcription initiation
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cloning and sequencing of RACEarray products
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cloning and sequencing of RACEarray products
almost 30% of the sequenced products incorporate exons from upstream genes in chimeric structures
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RT-PCR/arrays, cloning and sequencing•136 novel transcripts (29 chimeric) in 69 loci•71 potential new CDS in 37 loci (14 chimeric)•225 novel exons
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CONCLUSIONS• there is substantial amount of transcription
which does not appear to be associated to protein coding loci
• only a fraction of the transcript diversity of protein coding loci appears to have been surveyed so far.– in particular, protein coding loci appear to have tissue
specific distal alternative transcriptional start sites
• ENCODE transcriptional landscape: network of overlapping coding and non-coding transcripts, resulting in a continuum of transcription (more than 90% of the ENCODE regions are transcribed in at least one strand)
ACKNOWLEDGEMNTSENCODE GT GROUP
Stilyanos Antonarakis (Geneva)Robert Baertsch (UCSC) Ian Bell (Affx)Ewan Birney (EBI)Robert Castelo (IMIM)Jill Cheng (Affx)Evelyn Cheung (Affx)Hiram Clawson (UCSC)France Denoeud (IMIM) Sujit Dike (Affymetrix)Jorg Drenkow (Affymetrix)Olof.Emanuelsson (Yale) Paul Flicek (Sanger)Mark Gerstein (Yale) Srinka Ghosh (Affx)Jenn Harrow (Sanger)Greg Helt (Afffx)Ivo Hofacker (U. Vienna)Tim Hubbard (Sanger)Phil Kapranov (Affx)Damian Keefe (EBI)
Jan Korbel (Yale)Julien Lagarde (IMIM)Jeff Long (Affx)Todd Lowe (UCSC) G. Madhavan (Affx)Anton Nekrutenko (Penn State) David Nix (Affx)Jakob Pedersen (UCSC)Alex Reymond Geneva)Joel Rozowsky (Yale)Yijun Runan (GIS)Albin Sandelin (RIKEN)Mike Snyder (Yale)Peter F. Stadler (U. Vienna)Kevin Struhl (Harvard)Hari Tammana (Affx)Scott Tennenbaun (SUNY, Albany) Chia Lin Wei (GIS)Matt Weirauch (UCSC)Deyou Zheng (Yale)Addam Frankish(Sanger)
Tom Gingeras (Affymetrix) Roderic Guigó (CRG)
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