Genome Biology 2006, 7(Suppl 1):S4
GENCODE: producing a reference annotation for ENCODE
Jennifer Harrow*1, France Denoeud1†, Adam Frankish*1,
Alexandre Reymond1‡§, Chao-Kung Chen*, Jacqueline Chrast§,
Julien Lagarde‡, James GR Gilbert*, Roy Storey*, David Swarbreck*,
Colette Rossier‡, Catherine Ucla‡, Tim Hubbard†, Stylianos E Antonarakis‡
and Roderic Guigo†¶
Addresses: *Wellcome Trust Sanger Institute, Wellcome Trust Campus, Hinxton, Cambridge CB10 1SA, UK. †Grup de Recerca en Informatica
Biomedica, Institut Municipal d’Informatica Medica-Universitat Pompeu Fabra, Pg. Maritim de la Barceloneta, 08003 Barcelona, Catalonia,
Spain. ‡Department of Genetic Medicine and Development, University of Geneva Medical School and University Hospitals of Geneva,
Geneva, Switzerland. §Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland. ¶Centre de Regulacio Genomica, Pg.
Maritim de la Barceloneta, 08003 Barcelona, Catalonia, Spain. 1These authors contributed equally to this work.
Correspondence: Jennifer Harrow. Email: email@example.com
Published: 7 August 2006
Genome Biology 2006, 7(Suppl 1):S4
The electronic version of this article is the complete one and can be
found online at http://genomebiology.com/2006/7/S1/S4
© 2006 Harrow et al.; licensee BioMed Central Ltd.
This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which
permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background: The GENCODE consortium was formed to identify and map all protein-coding
genes within the ENCODE regions. This was achieved by a combination of initial manual
annotation by the HAVANA team, experimental validation by the GENCODE consortium and a
refinement of the annotation based on these experimental results.
Results: The GENCODE gene features are divided into eight different categories of which only
the first two (known and novel coding sequence) are confidently predicted to be protein-coding
genes. 5’ rapid amplification of cDNA ends (RACE) and RT-PCR were used to experimentally
verify the initial annotation. Of the 420 coding loci tested, 229 RACE products have been
sequenced. They supported 5’ extensions of 30 loci and new splice variants in 50 loci. In addition,
46 loci without evidence for a coding sequence were validated, consisting of 31 novel and 15
putative transcripts. We assessed the comprehensiveness of the GENCODE annotation by
attempting to validate all the predicted exon boundaries outside the GENCODE annotation. Out
of 1,215 tested in a subset of the ENCODE regions, 14 novel exon pairs were validated, only two
of them in intergenic regions.
Conclusions: In total, 487 loci, of which 434 are coding, have been annotated as part of the
GENCODE reference set available from the UCSC browser. Comparison of GENCODE
annotation with RefSeq and ENSEMBL show only 40% of GENCODE exons are contained within
the two sets, which is a reflection of the high number of alternative splice forms with unique
exons annotated. Over 50% of coding loci have been experimentally verified by 5’ RACE for
EGASP and the GENCODE collaboration is continuing to refine its annotation of 1% human
genome with the aid of experimental validation.
The complete sequence of the euchromatic region of the
human genome provides a new opportunity to establish the
complete catalogue of the human genes. Although auto-
mated gene prediction has improved greatly over the years
and the human gene count is thought to be between 20,000
and 25,000 protein-coding genes , defining a gene is not a
trivial issue. According to classic genetics, genes are inherit-
able units responsible for an associated phenotype. Although
in some cases this relationship derives from mutation of
non-coding DNA or regulatory elements, in most cases it is
synonymous with protein-coding genes. However, in the
past four years there has been an explosion in the discovery
of transcripts with no apparent coding potential (termed
non-coding RNAs) and there are indications these could play
as important a role in cellular function as proteins [2,3].
In an effort to investigate and understand all the functional
elements in the human genome, the ENCODE project
(Encyclopedia of DNA Elements)  was established. In this
pilot stage, the aim of the ENCODE project is to investigate
in great depth, computationally and experimentally, 44
regions totaling 30 Mb of sequence representing approxi-
mately 1% of the human genome. As part of this project, the
GENCODE consortium  was formed to identify and map
all protein-coding genes within the ENCODE regions. This is
achieved by a combination of initial manual annotation by
the HAVANA team , experimental validation by the
GENCODE consortium, and a refinement of the annotation
based on these experimental results (Figure 1).
This annotation is used as a reference set by all the ENCODE
consortium members. It also represents the standard to
which the automated prediction programs were assessed
during the ENCODE Genome Annotation Assessment Project
(E-GASP) 05 workshop (see  in this issue). This report
describes how the manual annotation and experimental
verification were performed. It also highlights some interest-
ing features in the GENCODE annotation and indicates the
weaknesses of the automated predictions compared to the
Results and discussion
Initial classification of loci
The HAVANA group divides gene features into different
categories of which only the first two (known and novel
coding sequence (CDS)) are confidently predicted to be
protein-coding genes. The common factor between all
annotated gene structures is that they must be supported by
transcriptional evidence, through homology to cDNA,
expressed sequence tags (ESTs) and/or protein sequences.
The following are the gene types first applied to the human
chromosome 20 annotation  and later expanded to fully
classify the annotation produced for the ENCODE project.
Known genes are identical to human cDNA or protein
sequences and identified by a GeneID in Entrez Gene .
Novel coding sequence
Novel coding sequences have an open reading frame (ORF)
and are identical, or have homology, to cDNAs or proteins
but do not fall into the above category; these mRNA
sequences are submitted to public databases, but they are
not yet represented in Entrez Gene or have not yet received
an official gene name from the nomenclature committee
. They can also be novel in the sense that they are not yet
represented by an mRNA sequence in the species concerned.
Novel transcripts are as above but no ORF can be
unambiguously assigned; these can be genuine non-coding
genes or they may be partial protein-coding genes supported
by limited evidence. They should be supported by at least
three ESTs from independent sources (not originating from
the same clone identifier).
Putative genes are identical, or have homology, to spliced
ESTs but lack a significant ORF and polyA features; these
are generally short two or three exon genes or gene
S4.2 Genome Biology 2006,Volume 7, Supplement 1, Article S4Harrow et al.http://genomebiology.com/2006/7/S1/S4
Genome Biology 2006, 7(Suppl 1):S4
The GENCODE pipeline. This schematic diagram shows the flow of data
between the three groups involved in the GENCODE consortium
(HAVANA, IMIM and Geneva) to produce an experimentally verified
annotation of the ENCODE region.
RT - PCR
Pseudogenes (assumes no expressed evidence) have
homology to proteins but generally suffer from a disrupted
CDS and an active homologous gene can be found at another
locus. This category can be further subdivided into proces-
sed or unprocessed pseudogenes. Sometimes these entries
have an intact CDS or an open but truncated ORF, in which
case there is other evidence used (for example genomic polyA
stretches at the 3’ end) to classify them as a pseudogene.
Transcribed pseudogenes are not currently given a separate
tag within GENCODE and are handled by creating a
pseudogene object and an overlapping transcript object with
the same locus name.
TEC (To be experimentally confirmed)
To be experimentally confirmed (TEC) is used for non-
spliced EST clusters that have polyA features. This category
has been specifically created for the ENCODE project to
highlight regions that could indicate the presence of novel
protein coding genes that require experimental validation,
either by 5’ rapid amplification of cDNA ends (RACE) or
RT-PCR to extend the transcripts or by confirming expres-
sion of the putatively encoded peptide with specific antibodies.
Artefact gene is used to tag mistakes in the public databases
(Ensembl/SwissProt/Trembl). Usually, these arise from
high-throughput cDNA sequencing projects, which submit
automatic annotation sometimes resulting in erroneous
CDSs that are, for example, 3’ untranslated regions (UTRs).
GENCODE annotation of the ENCODE regions
The first release of the annotation of the 44 ENCODE
regions was frozen on 29 April 2005 and was used in the E-
GASP workshop. It contained 416 known loci, 26 novel CDS
loci, 82 novel transcript loci, 78 putative loci, 104 processed
pseudogenes and 66 unprocessed pseudogenes. The current
version (release 02) was frozen on 14 October 2005. It
contains 411 known loci, 30 novel CDS loci, 81 novel
transcript loci, 83 putative loci, 104 processed pseudogenes
and 66 unprocessed pseudogenes. The gene content has
changed as a result of the experimental validation (see next
section). In total, 2.9% of the nucleotides in the ENCODE
regions (both strands considered separately) are covered by
annotated exons (1.2% by coding and 1.7% by UTRs and
non-coding), and 31% are transcribed (covered by annotated
exons or introns).
Multiple transcripts are annotated at any locus where
supporting evidence is available. Thus, the 487 compiled
GENCODE reference loci set (compiled from coding and
experimentally verified loci) corresponds to 2,608 trans-
cripts, of which 1,097 are coding. Of the coding loci (known
and novel CDS), 78% have alternative splice forms (86% of
the multi-exon gene loci), with an average of 5.7 variants per
locus. Of the coding variants, approximately 70% have a
complete CDS (the remainder are partial); 54% of the coding
loci have alternative CDS, indicating that diversity is lower at
the protein level than at the transcript level as a substantial
proportion of the alternative splice forms affect only the
UTRs. The RNPC2 (RNA-binding region (RNP1, RRM)
containing 2) gene has 37 variants, which is the highest
number in the ENCODE regions, of which only 6 are
annotated as coding.
Experimental verification of GENCODE annotation
The initial HAVANA annotation was submitted for experi-
mental verification (Figure 1). First, 5’ RACE in 12 different
tissues was employed to confirm that annotated coding
genes (within both known and novel CDS locus categories)
had been extended as far as possible towards the trans-
criptional start site, to exclude the possibility of additional
exons in their 5’ UTR and identify a representative full-
length transcript for each locus. Of the 420 coding loci
tested, 229 RACE products could be sequenced. They sup-
ported 5’ extensions of 30 loci (extension of the first exon in
two-thirds of the cases, new 5’ exons in one-third of the
cases) and new splice variants (not extending the 5’ end) in
Second, RT-PCR in 24 tissues was used for verifying trans-
cript (novel and putative) structures by checking the splice
junctions. All 360 splice junctions in the 161 novel and
putative transcript loci were tested. Of those tested, 47 loci
were validated, consisting of 31 novel and 15 putative trans-
cripts. As expected, the success rate of RT-PCR was higher
for the ‘novel transcripts’ (37%) than for the putative
transcripts (19%). Bidirectional RACE was carried out for
transcript loci with successfully validated splice junctions.
This supported seven loci over their full length but did not
Third, all annotated non-canonical sites (that is, all introns
not conforming to the AG-GT or AG-GC rule) were tested by
RT-PCR on 24 tissues. Of the annotated splice sites, 98% are
canonical GT-AG and an additional 0.9% are GC-AG. There
are 0.2% of AT-AC splice sites, most of them corresponding
to canonical U12 introns . Other non-canonical splice
sites occur in the remaining 0.9% of the introns. Among 90
non-canonical splice sites tested by RT-PCR in 24 tissues, 78
reactions were negative, 11 provided other canonical
junctions (most of them already annotated in other splice
forms), and only 1 was confirmed (CT-TG). The very low
level of success of the RT-PCRs on non-canonical splice sites
in 24 tissues suggests that these events may be artifactual.
As a control, we performed RT-PCR on 24 tissues (see
Materials and methods) on 96 randomly selected exon pairs
from within the GENCODE annotation. After sequencing of
the amplimer, the annotated exon pair was confirmed in 84
cases (87%) in at least one tissue. This is essentially the
Genome Biology 2006,Volume 7, Supplement 1, Article S4Harrow et al. S4.3
Genome Biology 2006, 7(Suppl 1):S4
expected result, given the fact that many alternative splice
forms in GENCODE are likely to have a restricted expression
pattern, and may not be represented in the 24 tissues tested.
Figure 2 summarizes the process of annotation, experi-
mental validation and reannotation that has occurred since
the original release of the GENCODE annotation in April
and its current update in October 2005.
Assessing completeness of the GENCODE annotation
To examine whether the manual annotation had missed any
coding loci, RT-PCR reactions in 24 tissues were also carried
out for splice junctions from all those gene objects predicted
by a panel of automated gene prediction algorithms before
the E-GASP workshop (Geneid , Genescan , Twinscan
, SGP , Fgenesh , Exonify , Acembly 
Ecgene , Ensembl EST ) that lie outside a HAVANA
annotated gene in 13 of the 44 ENCODE regions (corres-
ponding to the training regions for which the annotations
were released before the E-GASP predictions submission
deadline). Of the 1,215 exon pairs tested, only 14 (1.2%)
produced a positive result, 9 of which perfectly predicted
exon boundaries and 5 with displaced exon boundaries (8
other positive RT-PCRs were falling in 2 pseudogene loci).
Among the 14 positive validated junctions, 8 were new splice
forms internal to annotated loci, 4 were new splice forms
extending annotated loci, and only 2 were completely inter-
genic to any annotation. These results suggest that the
GENCODE gene set was relatively complete. It was then
updated to include the new splice forms/loci suggested by
To further assess the completeness of the GENCODE
annotation, we have compared it with other publicly
available and widely used human gene sets: RefSeq  and
ENSEMBL . These gene sets were downloaded from the
UCSC genome browser in November 2005. Table 1 shows
the overlap between these sets and GENCODE by at least
one bp: 99% of RefSeq, and 94% of ENSEMBL exons overlap
GENCODE exons. In contrast, only 80% and 84% of the
GENCODE exons overlap RefSeq and ENSEMBL exons,
S4.4 Genome Biology 2006, Volume 7, Supplement 1, Article S4Harrow et al. http://genomebiology.com/2006/7/S1/S4
Genome Biology 2006, 7(Suppl 1):S4
Experimental validation of HAVANA annotation. ‘Known’ and ‘Novel_CDS’ were submitted to 5’ RACE, and ‘Novel transcript’ and ‘Putative’ loci were
submitted to RT-PCR on all their exon junctions, followed by bi-directional RACE. Several steps of reannotation were performed during the process of
experimental verification: the figure shows the update of the annotation between the first release in April 2005 and the release from October 2005.
413 Known ; 26 novel CDS
2,378 transcripts (1061 coding)
83 Novel transcript ; 78 putative
47 loci validated
Several steps of
fusioned based on
exp validations and
Bidirectional RACEs on validated :
7 loci with ~full transcript structure confirmed
(4 were provided ORFs => novel CDS)
229 loci with RACE
product sequenced (54%):
7% (of 420) are extended in 5'
12% have new splice forms
(not extending the 5'end)
(October 2005 update)
411 Known ; 30 Novel CDS ;
31 Novel transcript ; 15 Putative
487 loci (434 coding)
2608 transcripts (1097 coding)
Havana-Gencode REFERENCE genes:
50 Novel transcript ;
68 Putative ; 18 TEC
156 transcripts (non coding)
Not yet validated
Figure 3 illustrates the comparisons at exact exon/intron
level. Although the exact agreement between GENCODE on
the one hand, and RefSeq and ENSEMBL on the other, is
lower than when considering one base overlap, the same
trend is observed: 84% (3,361/3,984) of RefSeq and 76%
(3,584/4,734) of ENSEMBL exons are included in the
GENCODE set, but only about 40% of the GENCODE exons
are included in RefSeq or ENSEMBL.
As illustrated by Figure 3, the exact agreement is larger for
exons than for introns, which suggests that the disagree-
ments are mostly found at the terminal exons, which is also
reflected in the fact that the agreement is also larger for the
subset of coding than for the set of all exons. In summary,
the comparison shows that GENCODE contains most of the
features from RefSeq and ENSEMBL but has more unique
exons than the two sets, which is reflected by its high
number of alternative splice forms.
Investigation of ENCODE regions that are
problematic for automatic annotation
The gene prediction algorithms that performed most
successfully in the E-GASP evaluation workshop when
compared to the manual annotation were the ones that used
alignments of expressed sequences to produce their gene
predictions (see  in this issue). However, even the most
successful methods of automated gene prediction achieved a
maximum sensitivity of 70% at the gene level (where at least
one coding transcript exon/intron structure was correctly
predicted) and 45% at the transcript level (where all alter-
natively spliced variants were correctly predicted). There are
several reasons for this. Some incidences of missed genes
could be explained by the lack of high identity transcript
evidence; for example, many of the olfactory receptor genes
in ENm009 (Figure 4f) lack good transcript and protein
support . Another example is the ANKRD43 locus in
ENr221, where partial coverage of the gene with human
mRNA produces truncated automated predictions. However,
cross-species evidence supports an extended protein-coding
gene (Figure 4c). In other cases, predictors fail to make a
correct prediction even though a full length transcript with
perfect sequence identity is present in the databases (for
example, Pairagon at the TRIM22 locus in ENm009;
Figure 4b). There are also examples where the predictions
differ from the manual annotation gene structure, even
though they use the same supporting evidence, because of
problems with automated alignment (for example, Ensembl
and Pairagon at the MAP3K1 locus in ENr221; Figure 4a). A
problem that appears to be associated with tandem
duplicated gene clusters is the linking together of adjacent
loci. The predicted transcript uses consecutive exons from
more than one locus, for example for a six exon gene taking
exons 1 and 2 from locus A, 3, 4 and 5 from locus B and 6
from locus C. Because the equivalent exons of the different
copies of the gene are very similar (often identical), the
resulting predicted transcript is an elongated structure
usually covering multiple loci (for example, AceView at the
HBG1/HBG2 loci in ENm009).
Another observation is that there are predictions that have
an identical intron/exon structure to the manual annotation
but have a different CDS. In such cases, the CDS has either a
5’ extension, that is, completely matches the GENCODE CDS
but uses an upstream translation initiation codon (most
often non-ATG; for example, AceView at the SEPT8 locus in
ENr221 and approximately 41% of AceView have a non-ATG
start), or has an entirely different CDS in a different frame.
The latter often results in unusual structures, with multi-
exon 5’ and/or 3’ UTRs that are at odds with rules governing
re-initiation  and nonsense mediated decay (NMD) 
(for example, Pairagon at the AC008937.5 locus in ENr221
and AceView at the IFNAR2 locus in ENm005; Figure 4e).
Many of the predictors suffer from reduced specificity as a
result of over-prediction of CDSs at loci where manual
annotation does not identify any CDS that can be confidently
assigned. These fall into two types; the first includes CDS
predicted at pseudogene loci, often where the pseudogene
suffers from small but significant disablements (for example,
Ensembl at the AC08730.14 locus in ENm009; Figure 4d);
and the second includes the ‘rule-breaking’ types of CDSs
described above (AceView at the AC008937.2 in ENr221).
Almost all the predictors (with AceView the notable
exception) under-predict coding (and non-coding) splice
variants, most predicting one transcript per gene.
GENCODE annotation uses only primary evidence; no
predictions or RefSeq entries are used to support gene
structures. This has the effect of reducing the risk of
propagating any errors that may be present in the databases.
The gene set annotated by GENCODE is supported using
evidence from all available sources, human and non-human
mRNAs, ESTs and proteins. The use of non-human evidence
is supported by our analysis of four exons not present in our
first pass annotation identified by the UNCOVER algorithm
Genome Biology 2006, Volume 7, Supplement 1, Article S4Harrow et al. S4.5
Genome Biology 2006, 7(Suppl 1):S4
Analysis of RefSeq and ENSEMBL ENCODE annotation
compared with GENCODE
No. (unique) exons 3,9844,734
No. transcripts 577738
No. exons overlapping GENCODE
5,118 (98.6%) 4,469 (94.4%)
No. transcripts overlapping
567 (98.3%)675 (91.5%)
No. GENCODE exons overlapped
(total = 8,865) (%)
7,084 (80.0%)7,450 (84.0%)
No. GENCODE transcripts
overlapped (total = 2,608) (%)
2,327 (89.2%)2,395 (91.8%)
S4.6 Genome Biology 2006, Volume 7, Supplement 1, Article S4Harrow et al. http://genomebiology.com/2006/7/S1/S4
Genome Biology 2006, 7(Suppl 1):S4
Comparison of GENCODE transcript annotation with RefSeq and ENSEMBL. The exact agreement between GENCODE and RefSeq and GENCODE and
ENSEMBL exons, introns, and nucleotides (NT) for the full transcripts or only the coding parts of the transcripts (CDS) is represented: in blue is the
fraction found only in GENCODE, in green the fraction common between GENCODE and the other set (RefSeq or ENSEMBL) and in red the fraction
found only in the other set (RefSeq or ENSEMBL) but not in GENCODE. The RefSeq set only contained the curated transcripts tagged with the NM prefix.
Genome Biology 2006, Volume 7, Supplement 1, Article S4 Harrow et al. S4.7
Genome Biology 2006, 7(Suppl 1):S4
Comparison of GENCODE annotation with automated gene prediction methods. Viewed in Fmap of Acedb. Panel A shows the MAPK1 gene in ENr221.
The GENCODE annotated gene structure is represented in green and red, the circled region highlights the different first exon identified by Pairagon
(dark pink/blue) and the expanded region shows tiny introns (indicated by arrows) predicted by Ensembl (orange/red). Panel B shows the TRIM22 locus
in ENm009. The structure predicted by Pairagon differs from the GENCODE structure and incorporates an unprocessed pseudogene as the final exon
(circled). Panel C shows the human ANKRD43 locus in ENr221 for which AceView (light pink/blue), Pairagon and Ensembl all predict a shorter CDS than
GENCODE. C ii shows the mouse ANKRD43 locus in which the upstream ATG is conserved. Panel D shows the GENCODE unprocessed pseudogene
locus AC087380.14 at which Ensembl predicts a coding gene. The arrow indicates a tiny intron introduced into the prediction to splice around an in-
frame premature stop codon. Panel E shows the IFNAR2 locus in ENm005 with GENCODE coding (red/green) and non-coding (all red) variants and
AceView predictions. The AceView CDSs differ from GENCODE in several respects; arrow ‘a’ indicates several transcripts that have their CDS
extended to the start of the prediction upstream of the GENCODE CDS start; arrow ‘b’ indicates a CDS starting in exon 5 despite the presence of an
upstream ATG, which would seem to preclude (re-)initiation from this site; and arrow ‘c’ indicates a predicted stop codon in the fourth from last exon,
which would be likely to make this transcript a target from Nonsense-mediated decay (NMD). GENCODE annotation incorporates all these variants but
keeps them as transcripts as CDSs cannot be assigned with certainty. Panel F shows part of the olfactory receptor (OR) cluster in ENm009. Here
Pairagon predicts a coding gene at the pseudogene locus OR52Z1P and a multi-exon gene that links separate OR loci (pseudogene locus OR51A1P,
coding loci OR52A1 and OR52A5), indicated by arrows.
, two of which are only supported by non-human EST
evidence. The identification of a rare splice variant in the
C16orf35 gene at the alpha globin locus is also facilitated
using mouse EST evidence (J Hughes, personal communi-
cation). Importantly, manual annotation allows context to be
taken into account when making a decision about difficult
gene regions, which includes consulting literature and
various web resources.
The E-GASP workshop as part of the ENCODE project has
highlighted the need for a high quality reference gene set
that can be used to improve and validate prediction algo-
rithms, as well as a scaffold for further experimentation. RT-
PCR and 5’ RACE of predicted exons outside the GENCODE
annotation has currently not revealed additional multi-exon
protein-coding genes. However, the experimental validation
continually adds evidence for more splice variants. In
addition, other technologies such as mapping RNA to tiling
arrays , cap analysis gene expression (CAGE) tags ,
and gene identification signature (GIS) ditags  indicate
there is transcriptional activity outside the regions currently
annotated by the GENCODE consortium. Therefore, the
annotation will be continually evolving to represent the
complete transcriptional landscape of the ENCODE regions.
Materials and methods
Annotation pipeline and software
Before the process of manual annotation begins, an
automated analysis pipeline for similarity searches and ab
initio predictions is run. The searches are run on a computer
farm and stored in an Ensembl MySQL database using a
modified Ensembl analysis pipeline system . All searches
and prediction algorithms, except CpG island prediction (see
cpgreport in the EMBOSS application suite ) are run on
repeat masked sequence. RepeatMasker  is used to mask
interspersed repeats, followed by Tandem repeats finder
 to mask tandem repeats. Nucleotide sequence data-
bases are searched with wuBLASTN , and significant
hits are re-aligned to the unmasked genomic sequence using
est2genome . The Uniprot protein database  is
searched with wuBLASTX, and the accession numbers of
significant hits are looked up in the Pfam database . The
hidden Markov models for Pfam protein domains are
aligned against the genomic sequence using Genewise 
to provide annotation of protein domains. We also run a
number of ab initio prediction algorithms: Genescan  and
Fgenesh  for genes, tRNAscan  to find tRNAgenes
and Eponine TSS , to predict transcription start sites.
Annotation assessed at the E-GASP workshop used data
from searches of the 24th August 2004 of dbEST, vertebrate
mRNA sequences from release 80 of the EMBL nucleotide
database and protein sequences from version 2.4 of Swiss-
Once the automated analysis is complete, the annotator uses
a Perl/Tk based graphical interface, called ‘otterlace’,
developed in-house to edit annotation data held in a separate
MySQL database system . The interface displays a rich,
interactive graphical view of the genomic region, showing
features like database matches, gene predictions, and
transcripts created by the annotators. Gapped alignments of
nucleotide and protein blast hits to the genomic sequence
are viewed and explored using the ‘Blixem’ alignment viewer
. Additionally, the ‘Dotter’ dot plot tool  is used for
showing the pair-wise alignments of unmasked sequence,
thus revealing the location of exons that are occasionally
missed by the automated blast searches because of their
small size and/or match to repeat-masked sequence. The
interface provides a number of tools that the annotator uses
to build genes and edit annotations: adding transcripts, exon
coordinates, translation regions, gene names and descrip-
tions, remarks and polyadenlyation signals and sites.
Rapid amplification of cDNA ends
Both 5’ and 3’ RACE were performed on 12 human poly(A)+
RNAs (brain, heart, kidney, spleen, liver, colon, small
intestine, muscle, lung, stomach, testis, placenta) using the
BD SMARTTMRACE cDNA amplification kit (BD BioScience-
Clontech Catalogue No.634914, Mountain View, CA 95043,
USA). Double-stranded cDNA synthesis and adaptor ligations
to the synthesized cDNA were done according to the manu-
facturer’s instructions. RACE fragments were separated on
agarose gels and one or two strong single bands per gene
purified and sequenced directly. Thus, successful RACE
reactions appearing as a smear on the agarose gel would be
discarded, therefore producing an approximate 54% success
Similar amounts of 24 human cDNAs (brain, heart, kidney,
spleen, liver, colon, small intestine, muscle, lung, stomach,
testis, placenta, skin, PBLs, bone marrow, fetal brain, fetal
liver, fetal kidney, fetal heart, fetal lung, thymus, pancreas,
mammary glands, prostate; final dilution 1,000×) were
mixed with JumpStart REDTaq ReadyMix (Sigma, St Louis,
MO, USA) and 4 ng/µl primers (Sigma-Genosys, St Louis,
MO, USA)) with a BioMek 2000 robot (Beckman, Fullerton,
CA, USA) as described and modified [43-45]. The 10 first
cycles of PCR amplification were performed with a
touchdown annealing temperature decreasing from 60°C to
50°C; the annealing temperature of the next 30 cycles was
50°C. Amplimers were separated on ‘Ready to Run’ precast
gels (Pfizer, New York, NY, USA) and sequenced. This
procedure was used to experimentally assay 1,215 exon-exon
junctions of human genes predicted by five ab initio and four
EST-based methods outside of HAVANA objects and 83
HAVANA novel and 78 putative transcripts (see Results and
discussion for details).
S4.8 Genome Biology 2006,Volume 7, Supplement 1, Article S4Harrow et al. http://genomebiology.com/2006/7/S1/S4
Genome Biology 2006, 7(Suppl 1):S4
Acknowledgments Download full-text
This work was supported by grants from the Childcare and Désirée and
Niels Yde Foundations, the European Union, the Swiss National Science
Foundation and the NCCR Frontiers in Genetics, from the NHGRI
ENCODE Project, and from the Spanish Ministry of Education and
This article has been published as part of Genome Biology Volume 7,
Supplement 1, 2006: EGASP ’05. The full contents of the supplement are
available online at http://genomebiology.com/supplements/7/S1.
1. International Human Genome Sequencing Consortium: Finishing
the euchromatic sequence of the human genome. Nature
2. Mattick JS: Non-coding RNAs: the architects of eukaryotic
complexity. EMBO Rep 2001, 2:986-991.
3. Bartel DP: MicroRNAs: genomics, biogenesis, mechanism,
and function. Cell 2004, 116:281-297.
4. ENCODE project consortium: The ENCODE (ENCyclopedia
Of DNA Elements) Project. Science 2004, 306:636-640.
GENCODE Consortium [http://genome.imim.es/gencode]
HAVANA Team [http://www.sanger.ac.uk/HGP/havana/]
7.Guigo R, Flicek P, Abril J, Reymond A, Lagarde J, Denoeud F,
Antonarakis S, Ashburner M, Bajic VB, Birney E, et al: EGASP. The
human ENCODE genome assessment project. Genome Biology
2006, 7(Suppl 1):S2
8. Deloukas P, Matthews LH, Ashurst J, Burton J, Gilbert JG, Jones M,
Stavrides G, Almeida JP, Babbage AK, Bagguley CL, et al.: The DNA
sequence and comparative analysis of human chromosome
20. Nature 2001, 414:865-871.
Entrez Gene [http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=gene]
HUGO Gene Nomenclature Committee [http://www.gene.ucl.
11. Will CL, Luhrmann R: Splicing of a rare class of introns by the
U12-dependent spliceosome. Biol Chem 2005, 386:713-724.
12.Parra G, Blanco E, Guigo R: GeneID in Drosophila. Genome Res
13.Burge C, Karlin S: Prediction of complete gene structures in
human genomic DNA. J Mol Biol 1997, 268:78-94.
14. Wang M, Buhler J, Brent MR: The effects of evolutionary dis-
tance on TWINSCAN, an algorithm for pair-wise compara-
tive gene prediction. Cold Spring Harb Symp Quant Biol 2003, 68:
15.Wiehe T, Gebauer-Jung S, Mitchell-Olds T, Guigo R: SGP-1: pre-
diction and validation of homologous genes based on
sequence alignments. Genome Res 2001, 11:1574-1583.
16. Salamov AA, Solovyev VV: Ab initio gene finding in Drosophila
genomic DNA. Genome Res 2000, 10:516-522.
17. Siepel A, Haussler D: Computational identification of evolu-
tionarily conserved exons.Proc. 8thAnnual Int’l Conf. on Research in
Computational Biology. pp 177-186, 2005 RECOMB’04, March 27-31,
2004, San Diego, California, USA.
19.Kim P, Kim N, Lee Y, Kim B, Shin Y, Lee S: ECgene: genome
annotation for alternative splicing. Nucleic Acids Res 2005, 33
20. Eyras E, Caccamo M, Curwen V, Clamp M: ESTGenes: alternative
splicing from ESTs in Ensembl. Genome Res 2004, 14:976-987.
21.Pruitt KD, Tatusova T, Maglott DR: NCBI Reference Sequence
(RefSeq): a curated non-redundant sequence database of
genomes, transcripts and proteins. Nucleic Acids Res 2005, 33
22. Birney E, Andrews TD, Bevan P, Caccamo M, Chen Y, Clarke L,
Coates G, Cuff J, Curwen V, Cutts T, et al.: An overview of
Ensembl. Genome Res 2004, 14:925-928.
23.UCSC genome browser [http://genome.cse.ucsc.edu/ENCODE]
24. Kozak M: Emerging links between initiation of translation
and human diseases. Mamm Genome 2002, 13:401-410.
25.Lewis BP, Green RE, Brenner SE: Evidence for the widespread
coupling of alternative splicing and nonsense-mediated mRNA
decay in humans. Proc Natl Acad Sci USA 2003, 100(1): 189-192.
26.Ohler U, Shomron N, Burge CB: Recognition of unknown con-
served alternatively spliced exons. PLoS Comput Biol 2005, 1:
27.Kapranov P, Drenkow J, Cheng J, Long J, Helt G, Dike S, Gingeras
TR: Examples of the complex architecture of the human
transcriptome revealed by RACE and high-density tiling
arrays. Genome Res 2005, 15:987-997.
Shiraki T, Kondo S, Katayama S, Waki K, Kasukawa T, Kawaji H,
Kodzius R, Watahiki A, Nakamura M, Arakawa T, et al.: Cap analy-
sis gene expression for high-throughput analysis of tran-
scriptional starting point and identification of promoter
usage. Proc Natl Acad Sci USA 2003, 100:15776-15781.
Ng P, Wei CL, Sung WK, Chiu KP, Lipovich L, Ang CC, Gupta S,
Shahab A, Ridwan A, Wong CH, et al.: Gene identification signa-
ture (GIS) analysis for transcriptome characterization and
genome annotation. Nat Methods 2005, 2:105-111.
Potter SC, Clarke L, Curwen V, Keenan S, Mongin E, Searle SM,
Stabenau A, Storey R, Clamp M: The Ensembl analysis pipeline.
Genome Res 2004, 14:934-941.
Rice P, Longden I, Bleasby A: EMBOSS: the European Molecular
Biology Open Software Suite. Trends Genet 2000, 16:276-277.
Benson G: Tandem repeats finder: a program to analyze
DNA sequences. Nucleic Acids Res 1999, 27:573-580.
Mott R: EST_GENOME: a program to align spliced DNA
sequences to unspliced genomic DNA. Comput Appl Biosci 1997,
Uniprot Protein Database [http://www.uniprot.org]
Bateman A, Coin L, Durbin R, Finn RD, Hollich V, Griffiths-Jones S,
Khanna A, Marshall M, Moxon S, Sonnhammer EL, et al.: The Pfam
protein families database. Nucleic Acids Res 2004, 32(Database
Birney E, Clamp M, Durbin R: GeneWise and Genomewise.
Genome Res 2004, 14:988-995.
Lowe TM, Eddy SR: tRNAscan-SE: a program for improved
detection of transfer RNA genes in genomic sequence.
Nucleic Acids Res 1997, 25:955-964.
Down TA, Hubbard TJ: Computational detection and location
of transcription start sites in mammalian genomic DNA.
Genome Res 2002, 12:458-461.
Searle SM, Gilbert J, Iyer V, Clamp M: The otter annotation
system. Genome Res 2004, 14:963-970.
Sonnhammer EL, Wootton JC: Integrated graphical analysis of
protein sequence features predicted from sequence compo-
sition. Proteins 2001, 45:262-273.
Reymond A, Friedli M, Henrichsen CN, Chapot F, Deutsch S, Ucla C,
Rossier C, Lyle R, Guipponi M, Antonarakis SE: From PREDs and
open reading frames to cDNA isolation: Revisiting the
human chromosome 21 transcription map. Genomics 2001,
Reymond A, Camargo AA, Deutsch S, Stevenson BJ, Parmigiani RB,
Ucla C, Bettoni F, Rossier C, Lyle R, Guipponi M, et al.: Nineteen
additional unpredicted transcripts from human chromo-
some 21. Genomics 2002, 79:824-832.
Guigo R, Dermitzakis ET, Agarwal P, Ponting CP, Parra G, Reymond
A, Abril JF, Keibler E, Lyle R, Ucla C, et al.: Comparison of mouse
and human genomes followed by experimental verification
yields an estimated 1,019 additional genes. Proc Natl Acad Sci
USA 2003, 100:1140-1145.
Genome Biology 2006,Volume 7, Supplement 1, Article S4Harrow et al. S4.9
Genome Biology 2006, 7(Suppl 1):S4