BACKGROUND
the draft sequence of the chicken  genome has been recently obtained and an initial analysis completed  <cit> .
this genome sequence will be extremely valuable for vertebrate development, avian biology, and agriculture.
to reap these benefits, however, we must be able to determine with reasonable accuracy the amino acid sequences of the proteins encoded by this genome.
we therefore set out to adapt three leading gene prediction systems to the chicken genome sequence and to evaluate their predictions experimentally.
some features of the chicken genome facilitate gene prediction while others hinder it.
generally, gene prediction tends to be more accurate in more compact genomes than in the large mammalian genomes  <cit> .
the chicken genome is about 40% the size of the human genome, but about three times the size of the takifugu genome  <cit> .
this translates into a substantial reduction in repeats and pseudogenes.
interspersed repeats cover about 9% of the genome, far less than the 40–50% found in mammals  <cit> .
the small number of processed pseudogenes is beneficial to automated annotation, as this technology often misclassifies pseudogenes as functional.
de novo prediction methods need full open reading frame  mrnas to train their statistical models and homology-based methods rely on these sequences in order to predict a core set of high quality genes.
however, an abundant set of chicken full-length cdnas was not available at the start of this project, as only about  <dig>  putatively full-length cdnas and  <dig>  ests were deposited in genbank  <cit> .
we set out to determine how well the computational methods used for annotating protein-coding genes in the mouse and rat genomes  <cit>  would perform in this avian context, where transcriptome sequencing was much less advanced and where sequence divergence may be beyond the optimal distance.
an assessment of the computational methods was carried out by a large-scale experimental verification by rt-pcr.
the gene prediction tools tested were ensembl, sgp <dig> and twinscan.
ensembl is a homology-based method, which builds gene-models using species-specific known sequences and proteins from other species aligned to the genome  <cit> .
sgp <dig> and twinscan are de novo comparative gene predictors whose only inputs are the genome to be annotated and a second informant genome  <cit> .
in this case, the informant genome selected for comparison was human.
since ensembl relies on mapping known genes from chicken and other organisms to the chicken genome, we surmised that its prediction set would contain fewer false positives  and more accurate gene structures, as well as more false negatives  than the de novo methods.
conversely, sgp <dig> and twinscan should be effective in detecting bona fide genes missed by the ensembl pipeline.
in particular, we were able to verify gene structures simultaneously predicted by both de novo methods about 50% of the time.
in this respect, de novo comparative methods complement homology-based methods, which in general miss genes for which there is no pre-existing evidence of transcription.
to test and compare the performance of these prediction systems under the new conditions presented by the chicken genome, we tested a large number of predicted genes by rt-pcr and direct sequencing.
we sampled individually from the predictions for which either one or two of the three methods agreed, and the remainder did not.
we thus focused our tests on the most difficult genes to predict and on the differences between the various prediction systems.
we present here the largest experimental comparison of multiple gene-prediction programs to date as well as the first to use this kind of differential design.
we aimed to evaluate how de novo and homology-based gene finding methods perform in a newly sequenced genome for which a small number of gene sequences are known.
in particular we have  evaluated the three prediction methods,  investigated twinscan and sgp <dig> as possible effective methods to complement the ensembl prediction pipeline and  tested the overall specificity of the ensembl prediction set.
RESULTS
experimental evaluation of gene finding in chicken
we aimed to estimate the accuracy of each of the gene prediction sets, which consisted of  <dig>  sgp <dig>  and  <dig>  twinscan  gene predictions, with one transcript per gene, and  <dig>  ensembl  genes containing  <dig>  transcripts.
we classified the predictions according to the venn diagram defined by the three-way intersections of the sets and their complements .
the subsets were populated with intron assemblies , defined as a list of exons and introns contiguous in a predicted transcript , and can be classified into three types:  the orphan subsets, containing those elements that are in one set but not in any of the other two,  the two-way intersection subsets, containing those elements that are in two sets and not in the third, and  the triple intersection, containing those elements that are in all three sets.
subsequently we tested pairs of adjacent exons from each of the subsets.
complementing homology-based gene prediction with de novo methods
selected ias belonging to the three possible two-way intersections were experimentally tested.
the results are summarized in figure  <dig> and detailed in table  <dig>  after rt-pcr, gel purification, and direct sequencing, about 50% of the tested transcripts predicted by both sgp <dig> and twinscan, but not by ensembl yielded spliced alignments to the gene targeted .
this rate is higher than that reported for human using a combination of homology-based and single-genome predictors  <cit>  in spite of the lack of available known gene sequences for the chicken genome.
there is a total of  <dig>  ias in the ' not e' subset, corresponding to a total of  <dig>  exons.
projecting these results onto genes and using an average distribution of coding exons per gene from other vertebrates , we estimate that approximately  <dig> to  <dig> bona fide chicken genes that are not in the currently predicted ensembl set can be found by the de novo comparative methods followed by direct amplification and sequencing.
considering the set of ias unique to one prediction set , 39% of these have one single intron and 80% have  <dig> or  <dig> introns.
on the other hand, after testing experimentally  <dig> orphans from twinscan,  <dig> orphans from sgp <dig> and  <dig> orphans from ensembl, we found that about 77% of the ensembl orphans are real genes, compared to an average 18% for twinscan and sgp <dig> .
thus while ensembl orphans are more likely to be real genes not predicted by the other methods, orphan de novo predictions are more likely to be false positives.
extending homology-based gene predictions with de novo methods
as ensembl predictions often fail to correctly predict one or both ends of a gene  <cit> , we reasoned that de novo prediction methods could help in extending the homology-based predicted transcripts.
to test this hypothesis, we identified candidate 5' extensions: exons predicted by twinscan, sgp <dig> or both to the 5' side of ensembl genes on the same strand.
we found that  <dig>   ensembl genes have such candidate extensions.
however, not all these extensions were as likely to correspond to real exons.
from this total,  <dig>  genes had extensions suggested by de novo predictions that overlap the ensembl gene , and  <dig>  had extra exons from de novo predictions that did not overlap the ensembl gene .
as 99% of ensembl introns were no longer than  <dig> kb, we considered only exon extensions that were no further than  <dig> kb from the 5'-most ensembl exon.
interestingly, we found that 93% of the linked extensions were to multiexonic ensembl transcripts, the remainder being extensions to single-exon ensembl transcripts; however, for unlinked extensions, only 58% were to multiexonic ensembl transcripts.
we investigated experimentally  <dig> linked and  <dig> unlinked extensions by designing one primer in the 5'-most exon of the ensembl prediction and the second primer within one of the upstream exon suggested by twinscan and/or sgp <dig> to the 5' side.
the rt-pcr results  show that de novo methods-suggested linked extensions were correct in about 40% of the cases.
this rate dropped to a mere 7% for the unlinked extensions.
separating the extensions according to whether the extra exon was predicted either by sgp <dig> or by twinscan showed that both methods had a comparable contribution.
from the  <dig> linked tested extensions,  <dig> were predicted by sgp <dig> with  <dig>  rt-pcr positives,  <dig> were predicted by twinscan with  <dig>  positives, and  <dig> were predicted by both programs with  <dig>  positives.
on the other hand, from the  <dig> tested unlinked extensions  <dig> were predicted by sgp <dig>  with  <dig> positives, and  <dig> were predicted by twinscan, with  <dig> positive.
finally, there were  <dig> cases where both, sgp <dig> and twinscan, predicted the unlinked extra exon of which one was positive.
testing ensembl specificity
a randomly selected set of ensembl predictions was assayed to evaluate ensembl's specificity.
this test measured a false positive rate of 4% .
on the other hand, the tested exon-pairs for the two-way intersection sets that included ensembl  not t' and ' not s') had an average false positive rate of 19% and 35%, respectively .
the disparity is greater with the two-way intersection set that excludes ensembl  not e'), which shows a false positive rate of 53%.
one explanation for this difference is the observation that most of the ensembl predictions have exons predicted by both sgp <dig> and twinscan.
indeed,  <dig>   of the  <dig>  ensembl transcripts have at least one exon, which is also in the sgp <dig> and twinscan sets, and 82% of these transcripts have  <dig> or more exons in common with both de novo methods.
thus, ensembl predictions are most likely to fall within a triple intersection, resulting in an increased rate of true positives.
based on previous experiments  <cit> , we expected the triple intersection to give a yield close to 100% positive rate.
we tested  <dig> cases of triple intersection and found 85% positive rate .
moreover, 94% of these positive cases had the exon-intron boundaries correctly predicted .
we compared the accuracy of the human-based predictions with the accuracy of a fish-based set of predictions.
we predicted genes in chicken with sgp <dig> and twinscan using tetraodon nigroviridis as informant genome, and found that they are less accurate than the human-based ones .
additionally, we found that 85% and 98% of the tetraodon-based predictions from twinscan and sgp <dig>  respectively, overlap the corresponding human-based ones.
interestingly, 85% of the twinscan orphans overlap twinscan tetraodon-based predictions, and 80% of the sgp <dig> orphans overlap sgp <dig> tetraodon-based predictions.
on the other hand, 99% of the ias common to twinscan and sgp <dig> but not in ensembl, overlap twinscan or sgp <dig> tetraodon-based predictions.
CONCLUSIONS
in this paper we have evaluated how effective purely computational approaches for genome annotation can be, even in the absence of a large collection of previously known genes, by means of the largest attempt so far to experimentally compare several gene finders.
after testing the accuracy of ensembl, sgp <dig> and twinscan on the chicken genome we have shown that de novo comparative methods followed by experimental verification remain a successful approach in the annotation of newly sequenced genomes from which little is known.
we found that approximately 50% of predictions that were in twinscan and sgp <dig> but not in ensembl could be experimentally verified .
these experiments demonstrate that de novo comparative prediction methods are effective at complementing homology-based methods and confirm that a combination of methods can improve the prediction accuracy  <cit> .
moreover, in spite of the limited gene sequence data available for chicken, the combination of twinscan and sgp <dig> achieves better accuracy than previous attempts to verify by rt-pcr computational predictions that fall outside a set of annotations  <cit> .
on the other hand, looking at the intron assemblies unique to one prediction set, the proportion of positives is largely reduced for predictions not in ensembl.
the predictions unique to one of the de novo methods show an abundance of gene models with  <dig> and  <dig> exons, which may be artefacts due to genome misassemblies.
these results are in contrast with the high success rate  of the predictions unique to ensembl.
this is a reasonable observation considering that the ensembl prediction pipeline has access to genes that do not follow a 'standard' gene-grammar , but which may nevertheless be represented in the cdna/protein databases used.
the ensembl chicken gene set has been found to have a 96% positive rate, whereas the ias from the two-way intersections that include ensembl, ' not t' and ' not s', and the ensembl orphans, have a lower positive rate, 81%, 65% and 77%, respectively, which stems from the fact that most exons predicted by ensembl are also predicted by both sgp <dig> and twinscan.
additionally, de novo comparative methods are useful for extending partial predictions from homology-based methods.
ensembl may generate predictions based on protein fragments or on partial homology from other species, and twinscan and sgp <dig> predictions can add bona fide exons to the ensembl predictions they overlap with.
for the 5' end we show that 40% of the tested cases, where either twinscan or sgp <dig> predicted at least one additional exon, were verified .
to our knowledge, this is the first time that experimental evidence is provided for extensions to homology-based models produced by de novo methods.
we observed that the subsets containing sgp <dig> ias  not t)') have in general a higher proportion of rt-pcr positives than those containing twinscan ias  not s)') .
there are two factors that may contribute to this difference.
the first is an intrinsic difference between twinscan and sgp <dig> – sgp <dig> uses tblastx  alignments between human and chicken to reward exons overlapping aligned regions, whereas twinscan uses blastn  alignments to influence the scores of exons, splice sites, and translation initiation and termination sites.
human and chicken are sufficiently diverged that translated alignments may be more sensitive, whereas nucleotide alignments fail to cover many known exons.
the other factor is incidental to the way twinscan was trained and run to produce the predictions tested.
twinscan used  <dig> chicken refseqs to estimate parameters for its probability model.
this training set was probably too small to produce optimal parameter values.
sgp <dig>  on the other hand, was run with a combination of parameters estimated from the much larger set of known human genes  and parameters were hand tuned using the same  <dig> chicken genes .
although a larger fraction of sgp <dig> predictions yielded positive experimental results, we found that twinscan tends to be more accurate than sgp <dig> in the prediction of the intron boundaries .
this difference stems from the intron model used by twinscan, as opposed to sgp <dig>  which does not model introns explicitly.
twinscan was re-run after completion of the experiments with an improved intron-length model, yielding a prediction set that was substantially smaller and more accurate  than the set tested.
in spite these differences, comparing the gene predictions with a set of coding cdnas released after the completion of these analyses, we found that all three methods have similar sensitivity  , hence the de novo comparative methods cover a fraction of the transcriptome similar to homology-based methods with a minimal initial amount of genome-specific expression data.
the experimentally verified ias represent a fraction of the actual number of chicken genes that can be eventually found using our methods.
if we extrapolate the proportions of experimentally verified ias  to all the generated ias in the venn diagram  and using an average distribution of coding exons per gene from other vertebrates , we estimate a range of  <dig>  to  <dig>  experimentally verifiable chicken genes from our computational predictions.
in this paper we only analysed intron assemblies and deliberately left out a number of chicken protein-coding intronless predictions .
the triple intersection of these intronless genes contains  <dig> genes, which are worth investigating and for which techniques different from the ones applied here will be required.
considering all 2-way ias , one would need  <dig>  rt-pcr reactions to experimentally confirm about  <dig>   genes.
this number of experiments compares favourably to large-scale est projects with the added benefit of having almost no redundancy .
the biggest drawback to est sequencing is its large redundancy and extensive overlap.
the falling cost of primers and the increased flexibility of large-scale molecular biology centers make this approach of computational prediction followed by experimental verification cost effective and scalable  <cit> .
as rt-pcr primers can be designed with appropriate linker sites such an approach could also provide a physical resource of clonable fragments.
we conclude that de novo comparative gene predictions followed by experimental verification is an effective way to carry out the annotation of a newly sequenced genome for which little gene sequence information is known.
in particular, as our results show, performing rt-pcr and sequencing for all the predicted novel genes, starting with those predicted by multiple de novo methods, should enhance the quality of the annotation in forthcoming eukaryote genome sequencing projects.

 the draft sequence of the chicken genome has been recently obtained and an initial analysis completed. this genome sequence will be extremely valuable for vertebrate development, avian biology, and agriculture. to reap these benefits, however, we must be able to determine with reasonable accuracy the amino acid sequences of the proteins encoded by this genome. we therefore set out to adapt three leading gene prediction systems to the chicken genome sequence and to evaluate their predictions experimentally. some features of the chicken genome facilitate gene prediction while others hinder it. generally, gene prediction tends to be more accurate in more compact genomes than in the large mammalian genomes. the chicken genome is about 40% the size of the human genome, but about three times the size of the takifugu genome. this translates into a substantial reduction in repeats and pseudogenes. interspersed repeats cover about 9% of the genome, far less than the 40–50% found in mammals. the small number of processed pseudogenes is beneficial to automated annotation, as this technology often misclassifies pseudogenes as functional. de novo prediction methods need full open reading frame mrnas to train their statistical models and homology-based methods rely on these sequences in order to predict a core set of high quality genes. however, an abundant set of chicken full-length cdnas was not available at the start of this project, as only about putatively full-length cdnas and ests were deposited in genbank. we set out to determine how well the computational methods used for annotating protein-coding genes in the mouse and rat genomes would perform in this avian context, where transcriptome sequencing was much less advanced and where sequence divergence may be beyond the optimal distance. an assessment of the computational methods was carried out by a large-scale experimental verification by rt-pcr. the gene prediction tools tested were ensembl, sgp and twinscan. ensembl is a homology-based method, which builds gene-models using species-specific known sequences and proteins from other species aligned to the genome. sgp and twinscan are de novo comparative gene predictors whose only inputs are the genome to be annotated and a second informant genome. in this case, the informant genome selected for comparison was human. since ensembl relies on mapping known genes from chicken and other organisms to the chicken genome, we surmised that its prediction set would contain fewer false positives and more accurate gene structures, as well as more false negatives than the de novo methods. conversely, sgp and twinscan should be effective in detecting bona fide genes missed by the ensembl pipeline. in particular, we were able to verify gene structures simultaneously predicted by both de novo methods about 50% of the time. in this respect, de novo comparative methods complement homology-based methods, which in general miss genes for which there is no pre-existing evidence of transcription. to test and compare the performance of these prediction systems under the new conditions presented by the chicken genome, we tested a large number of predicted genes by rt-pcr and direct sequencing. we sampled individually from the predictions for which either one or two of the three methods agreed, and the remainder did not. we thus focused our tests on the most difficult genes to predict and on the differences between the various prediction systems. we present here the largest experimental comparison of multiple gene-prediction programs to date as well as the first to use this kind of differential design. we aimed to evaluate how de novo and homology-based gene finding methods perform in a newly sequenced genome for which a small number of gene sequences are known. in particular we have evaluated the three prediction methods, investigated twinscan and sgp as possible effective methods to complement the ensembl prediction pipeline and tested the overall specificity of the ensembl prediction set.  experimental evaluation of gene finding in chicken we aimed to estimate the accuracy of each of the gene prediction sets, which consisted of sgp and twinscan gene predictions, with one transcript per gene, and ensembl genes containing transcripts. we classified the predictions according to the venn diagram defined by the three-way intersections of the sets and their complements. the subsets were populated with intron assemblies, defined as a list of exons and introns contiguous in a predicted transcript, and can be classified into three types: the orphan subsets, containing those elements that are in one set but not in any of the other two, the two-way intersection subsets, containing those elements that are in two sets and not in the third, and the triple intersection, containing those elements that are in all three sets. subsequently we tested pairs of adjacent exons from each of the subsets. complementing homology-based gene prediction with de novo methods selected ias belonging to the three possible two-way intersections were experimentally tested. the results are summarized in figure and detailed in table after rt-pcr, gel purification, and direct sequencing, about 50% of the tested transcripts predicted by both sgp and twinscan, but not by ensembl yielded spliced alignments to the gene targeted. this rate is higher than that reported for human using a combination of homology-based and single-genome predictors in spite of the lack of available known gene sequences for the chicken genome. there is a total of ias in the' not e' subset, corresponding to a total of exons. projecting these results onto genes and using an average distribution of coding exons per gene from other vertebrates, we estimate that approximately to bona fide chicken genes that are not in the currently predicted ensembl set can be found by the de novo comparative methods followed by direct amplification and sequencing. considering the set of ias unique to one prediction set, 39% of these have one single intron and 80% have or introns. on the other hand, after testing experimentally orphans from twinscan, orphans from sgp and orphans from ensembl, we found that about 77% of the ensembl orphans are real genes, compared to an average 18% for twinscan and sgp. thus while ensembl orphans are more likely to be real genes not predicted by the other methods, orphan de novo predictions are more likely to be false positives. extending homology-based gene predictions with de novo methods as ensembl predictions often fail to correctly predict one or both ends of a gene, we reasoned that de novo prediction methods could help in extending the homology-based predicted transcripts. to test this hypothesis, we identified candidate 5' extensions: exons predicted by twinscan, sgp or both to the 5' side of ensembl genes on the same strand. we found that ensembl genes have such candidate extensions. however, not all these extensions were as likely to correspond to real exons. from this total, genes had extensions suggested by de novo predictions that overlap the ensembl gene, and had extra exons from de novo predictions that did not overlap the ensembl gene. as 99% of ensembl introns were no longer than kb, we considered only exon extensions that were no further than kb from the 5'-most ensembl exon. interestingly, we found that 93% of the linked extensions were to multiexonic ensembl transcripts, the remainder being extensions to single-exon ensembl transcripts; however, for unlinked extensions, only 58% were to multiexonic ensembl transcripts. we investigated experimentally linked and unlinked extensions by designing one primer in the 5'-most exon of the ensembl prediction and the second primer within one of the upstream exon suggested by twinscan and/or sgp to the 5' side. the rt-pcr results show that de novo methods-suggested linked extensions were correct in about 40% of the cases. this rate dropped to a mere 7% for the unlinked extensions. separating the extensions according to whether the extra exon was predicted either by sgp or by twinscan showed that both methods had a comparable contribution. from the linked tested extensions, were predicted by sgp with rt-pcr positives, were predicted by twinscan with positives, and were predicted by both programs with positives. on the other hand, from the tested unlinked extensions were predicted by sgp with positives, and were predicted by twinscan, with positive. finally, there were cases where both, sgp and twinscan, predicted the unlinked extra exon of which one was positive. testing ensembl specificity a randomly selected set of ensembl predictions was assayed to evaluate ensembl's specificity. this test measured a false positive rate of 4%. on the other hand, the tested exon-pairs for the two-way intersection sets that included ensembl not t' and' not s') had an average false positive rate of 19% and 35%, respectively. the disparity is greater with the two-way intersection set that excludes ensembl not e'), which shows a false positive rate of 53%. one explanation for this difference is the observation that most of the ensembl predictions have exons predicted by both sgp and twinscan. indeed, of the ensembl transcripts have at least one exon, which is also in the sgp and twinscan sets, and 82% of these transcripts have or more exons in common with both de novo methods. thus, ensembl predictions are most likely to fall within a triple intersection, resulting in an increased rate of true positives. based on previous experiments, we expected the triple intersection to give a yield close to 100% positive rate. we tested cases of triple intersection and found 85% positive rate. moreover, 94% of these positive cases had the exon-intron boundaries correctly predicted. we compared the accuracy of the human-based predictions with the accuracy of a fish-based set of predictions. we predicted genes in chicken with sgp and twinscan using tetraodon nigroviridis as informant genome, and found that they are less accurate than the human-based ones. additionally, we found that 85% and 98% of the tetraodon-based predictions from twinscan and sgp respectively, overlap the corresponding human-based ones. interestingly, 85% of the twinscan orphans overlap twinscan tetraodon-based predictions, and 80% of the sgp orphans overlap sgp tetraodon-based predictions. on the other hand, 99% of the ias common to twinscan and sgp but not in ensembl, overlap twinscan or sgp tetraodon-based predictions.  in this paper we have evaluated how effective purely computational approaches for genome annotation can be, even in the absence of a large collection of previously known genes, by means of the largest attempt so far to experimentally compare several gene finders. after testing the accuracy of ensembl, sgp and twinscan on the chicken genome we have shown that de novo comparative methods followed by experimental verification remain a successful approach in the annotation of newly sequenced genomes from which little is known. we found that approximately 50% of predictions that were in twinscan and sgp but not in ensembl could be experimentally verified. these experiments demonstrate that de novo comparative prediction methods are effective at complementing homology-based methods and confirm that a combination of methods can improve the prediction accuracy. moreover, in spite of the limited gene sequence data available for chicken, the combination of twinscan and sgp achieves better accuracy than previous attempts to verify by rt-pcr computational predictions that fall outside a set of annotations. on the other hand, looking at the intron assemblies unique to one prediction set, the proportion of positives is largely reduced for predictions not in ensembl. the predictions unique to one of the de novo methods show an abundance of gene models with and exons, which may be artefacts due to genome misassemblies. these results are in contrast with the high success rate of the predictions unique to ensembl. this is a reasonable observation considering that the ensembl prediction pipeline has access to genes that do not follow a'standard' gene-grammar, but which may nevertheless be represented in the cdna/protein databases used. the ensembl chicken gene set has been found to have a 96% positive rate, whereas the ias from the two-way intersections that include ensembl,' not t' and' not s', and the ensembl orphans, have a lower positive rate, 81%, 65% and 77%, respectively, which stems from the fact that most exons predicted by ensembl are also predicted by both sgp and twinscan. additionally, de novo comparative methods are useful for extending partial predictions from homology-based methods. ensembl may generate predictions based on protein fragments or on partial homology from other species, and twinscan and sgp predictions can add bona fide exons to the ensembl predictions they overlap with. for the 5' end we show that 40% of the tested cases, where either twinscan or sgp predicted at least one additional exon, were verified. to our knowledge, this is the first time that experimental evidence is provided for extensions to homology-based models produced by de novo methods. we observed that the subsets containing sgp ias not t)') have in general a higher proportion of rt-pcr positives than those containing twinscan ias not s)'). there are two factors that may contribute to this difference. the first is an intrinsic difference between twinscan and sgp – sgp uses tblastx alignments between human and chicken to reward exons overlapping aligned regions, whereas twinscan uses blastn alignments to influence the scores of exons, splice sites, and translation initiation and termination sites. human and chicken are sufficiently diverged that translated alignments may be more sensitive, whereas nucleotide alignments fail to cover many known exons. the other factor is incidental to the way twinscan was trained and run to produce the predictions tested. twinscan used chicken refseqs to estimate parameters for its probability model. this training set was probably too small to produce optimal parameter values. sgp on the other hand, was run with a combination of parameters estimated from the much larger set of known human genes and parameters were hand tuned using the same chicken genes. although a larger fraction of sgp predictions yielded positive experimental results, we found that twinscan tends to be more accurate than sgp in the prediction of the intron boundaries. this difference stems from the intron model used by twinscan, as opposed to sgp which does not model introns explicitly. twinscan was re-run after completion of the experiments with an improved intron-length model, yielding a prediction set that was substantially smaller and more accurate than the set tested. in spite these differences, comparing the gene predictions with a set of coding cdnas released after the completion of these analyses, we found that all three methods have similar sensitivity, hence the de novo comparative methods cover a fraction of the transcriptome similar to homology-based methods with a minimal initial amount of genome-specific expression data. the experimentally verified ias represent a fraction of the actual number of chicken genes that can be eventually found using our methods. if we extrapolate the proportions of experimentally verified ias to all the generated ias in the venn diagram and using an average distribution of coding exons per gene from other vertebrates, we estimate a range of to experimentally verifiable chicken genes from our computational predictions. in this paper we only analysed intron assemblies and deliberately left out a number of chicken protein-coding intronless predictions. the triple intersection of these intronless genes contains genes, which are worth investigating and for which techniques different from the ones applied here will be required. considering all 2-way ias, one would need rt-pcr reactions to experimentally confirm about genes. this number of experiments compares favourably to large-scale est projects with the added benefit of having almost no redundancy. the biggest drawback to est sequencing is its large redundancy and extensive overlap. the falling cost of primers and the increased flexibility of large-scale molecular biology centers make this approach of computational prediction followed by experimental verification cost effective and scalable. as rt-pcr primers can be designed with appropriate linker sites such an approach could also provide a physical resource of clonable fragments. we conclude that de novo comparative gene predictions followed by experimental verification is an effective way to carry out the annotation of a newly sequenced genome for which little gene sequence information is known. in particular, as our results show, performing rt-pcr and sequencing for all the predicted novel genes, starting with those predicted by multiple de novo methods, should enhance the quality of the annotation in forthcoming eukaryote genome sequencing projects. 
a venn diagram was computed and each component of it was evaluated. this is particularly true for genomes for which there is not a large collection of known gene sequences, such as the recently published chicken genome. we performed experimental evaluation by rt-pcr of three different computational gene finders, ensembl, sgp and twinscan, applied to the chicken genome. the results showed that de novo comparative methods can identify up to about chicken genes with no previous evidence of expression, and can correctly extend about 40% of homology-based predictions at the 5' end. despite the continuous production of genome sequence for a number of organisms, reliable, comprehensive, and cost effective gene prediction remains problematic. de novo comparative gene prediction followed by experimental verification is effective at enhancing the annotation of the newly sequenced genomes provided by standard homology-based methods.
 despite the continuous production of genome sequence for a number of organisms, reliable, comprehensive, and cost effective gene prediction remains problematic. this is particularly true for genomes for which there is not a large collection of known gene sequences, such as the recently published chicken genome. we used the chicken sequence to test comparative and homology-based gene-finding methods followed by experimental validation as an effective genome annotation method.  we performed experimental evaluation by rt-pcr of three different computational gene finders, ensembl, sgp and twinscan, applied to the chicken genome. a venn diagram was computed and each component of it was evaluated. the results showed that de novo comparative methods can identify up to about chicken genes with no previous evidence of expression, and can correctly extend about 40% of homology-based predictions at the 5' end.  de novo comparative gene prediction followed by experimental verification is effective at enhancing the annotation of the newly sequenced genomes provided by standard homology-based methods. 