Distinguishing protein-coding and noncoding genes in the human genome Michele Clamp * , Ben Fry * , Mike Kamal * , Xiaohui Xie * , James Cuff * , Michael F. Lin , Manolis Kellis * , Kerstin Lindblad-Toh * , and Eric S. Lander * * Broad Institute of Massachusetts Institute of Technology and Harvard , 7 Cambridge Center , Cambridge , MA 02142 ; Department of Biology and Computer Science and Artificial Intelligence Laboratory , Massachusetts Institute of Technology , Cambridge , MA 02139 ; Whitehead Institute for Biomedical Research , 9 Cambridge Center , Cambridge , MA 02142 ; and Department of Systems Biology , Harvard Medical School , Boston , MA 02115 Contributed by Eric S. Lander , October 3 , 2007 -LRB- sent for review August 1 , 2007 -RRB- Although the Human Genome Project was completed 4 years ago , the catalog of human protein-coding genes remains a matter of controversy . Current catalogs list a total of 24,500 putative protein-coding genes . It is broadly suspected that a large fraction of these entries are functionally meaningless ORFs present by chance in RNA transcripts , because they show no evidence of evolutionary conservation with mouse or dog . However , there is currently no scientific justification for excluding ORFs simply because they fail to show evolutionary conservation : the alternative hypothesis is that most of these ORFs are actually valid human genes that reflect gene innovation in the primate lineage or gene loss in the other lineages . Here , we reject this hypothesis by carefully analyzing the nonconserved ORFs -- specifically , their properties in other primates . We show that the vast majority of these ORFs are random occurrences . The analysis yields , as a by-product , a major revision of the current human catalogs , cutting the number of protein-coding genes to 20,500 . Specifically , it suggests that nonconserved ORFs should be added to the human gene catalog only if there is clear evidence of an encoded protein . It also provides a principled methodology for evaluating future proposed additions to the human gene catalog . Finally , the results indicate that there has been relatively little true innovation in mammalian proteincoding genes . comparative genomics A n accurate catalog of the protein-coding genes encoded in the human genome is fundamental to the study of human biology and medicine . Yet , despite its importance , the human gene catalog has remained an elusive target . The twofold challenge is to ensure that the catalog includes all valid protein-coding genes and excludes putative entries that are not valid protein-coding genes . The latter issue has proven surprisingly difficult . It is the focus of this article . Putative protein-coding genes are identified based on computational analysis of genomic data -- typically , by the presence of an open-reading frame -LRB- ORF -RRB- exceeding 300 bp in a cDNA sequence . The underlying premise , however , is shaky . Recent studies have made clear that the human genome encodes an abundance of non-protein-coding transcripts -LRB- 1 3 -RRB- . Simply by chance , noncoding transcripts may contain long ORFs . This is particularly so because noncoding transcripts are often GC-rich , whereas stop codons are AT-rich . Indeed , a random GC-rich sequence -LRB- 50 % GC -RRB- of 2 kb has a 50 % chance of harboring an ORF 400 bases long -LSB- supporting information -LRB- SI -RRB- Fig. 4 -RSB- . Once a putative protein-coding gene has been entered into the human gene catalogs , there has been no principled way to remove it . Experimental evidence is of no utility in this regard . Although one can demonstrate the validity of protein-coding gene by direct mass-spectrometric evidence of the encoded protein , one can not prove the invalidity of a putative protein-coding gene by failing to detect the putative protein -LRB- which might be expressed at low abundance or in different tissues or at different developmental stages -RRB- . The lack of a reliable way to recognize valid protein-coding transcripts has created a serious problem , which is only growing as PNAS December 4 , 2007 vol . 104 no. 49 large-scale cDNA sequencing projects yield ever-larger numbers of transcripts -LRB- 2 -RRB- . The three most widely used human gene catalogs -LSB- Ensembl -LRB- 4 -RRB- , RefSeq -LRB- 5 -RRB- , and Vega -LRB- 6 -RRB- -RSB- together contain a total of 24,500 protein-coding genes . It is broadly suspected that a large fraction of these entries is simply spurious ORFs , because they show no evidence of evolutionary conservation . -LSB- Recent studies indicate that only 20,000 show evolutionary conservation with dog -LRB- 7 -RRB- . -RSB- However , there is currently no scientific justification for excluding ORFs simply because they fail to show evolutionary conservation ; the alternative hypothesis is that these ORFs are valid human genes that reflect gene innovation in the primate lineage or gene loss in other lineages . As a result , the human gene catalog has remained in considerable doubt . The resulting uncertainty hampers biomedical projects , such as systematic sequencing of all human genes to discover those involved in disease . The situation also complicates studies of comparative genomics and evolution . Current catalogs of protein-coding genes vary widely among mammals , with a recent analysis of the dog genome -LRB- 8 -RRB- reporting 19,000 genes and a recent article on the mouse genome -LRB- 2 -RRB- reporting at least 33,000 genes . The difference is attributable to nonconserved ORFs identified in cDNA sequencing projects . It is currently unclear whether it reflects meaningful evolutionary differences among species or simply varying numbers of spurious ORFs in species with more cDNAs in current databases . In addition , the confusion about protein-coding genes clearly complicates efforts to create accurate catalogs of non-protein-coding transcripts . The purpose of this article is to test whether the nonconserved human ORFs represent bona fide human protein-coding genes or whether they are simply spurious occurrences in cDNAs . Although it is broadly accepted that ORFs with strong cross-species conservation to mouse or dog are valid protein-coding genes -LRB- 7 -RRB- , no work has addressed the crucial issue of whether nonconserved human ORFs are invalid . Specifically , one must reject the alternative hypothesis that the nonconserved ORFs represent -LRB- i -RRB- ancestral genes that are present in our common mammalian ancestor but were lost in mouse and dog or -LRB- ii -RRB- novel genes that arose in the human lineage after divergence from mouse and dog . Here , we provide strong evidence to show that the vast majority of the nonconserved ORFs are spurious . The analysis begins with a thorough reevaluation of a current gene catalog to identify conserved protein-coding genes and eliminate many putative genes resulting from clear artifacts . We then study the remaining set of nonconserved ORFs . By studying their properties in primates , we Author contributions : M.C. and E.S.L. designed research ; M.C. , B.F. , M. Kamal , X.X. , J.C. , M.F.L. , M. Kellis , K.L.-T. , and E.S.L. performed research ; M.C. , B.F. , M. Kamal , X.X. , J.C. , M.F.L. , M. Kellis , K.L.-T. , and E.S.L. analyzed data ; and M.C. and E.S.L. wrote the paper . The authors declare no conflict of interest . To whom correspondence may be addressed . E-mail : mclamp@broad.mit.edu or lander@broad.mit.edu . This article contains supporting information online at www.pnas.org/cgi/content/full/ 0709013104/DC1 . 2007 by The National Academy of Sciences of the USA 19428 19433 www.pnas.org cgi doi 10.1073 pnas .0709013104 21,895 putative genes Invalid Retroposons/pseudogenes 1,551 59 1,177 1532 Retroposons / pseudogenes -LRB- 1,538 -RRB- 6 Valid Functional retroposons/pseudogenes 6 Miscellaneous artifacts Orphans Total invalid Cross-species orthologs -LRB- 18,752 -RRB- 18,752 Cross-species orthologs Cross-species paralogs 18,868 147 51 36 8 2,787 Cross-species paralogs -LRB- 155 -RRB- 147 3 14 Human-specific paralogs Pfam domains Human-specific paralogs -LRB- 68 -RRB- 51 Total valid 19,108 16 5 40 1,177 Pfam domains -LRB- 97 -RRB- 40 36 68 Orphans -LRB- 1,285 -RRB- Fig. 1 . Flowchart of the analysis . The central pipeline illustrates the computational analysis of 21,895 putative genes in the Ensembl catalog -LRB- v35 -RRB- . We then performed manual inspection of 1,178 cases to obtain the tables of likely valid and invalid genes . See text for details . show that the vast majority are neither -LRB- i -RRB- ancestral genes lost in mouse and dog nor -LRB- ii -RRB- novel genes that arose after divergence from mouse or dog . The results have three important consequences . First , the analysis yields as a by-product a major revision to the human gene catalog , cutting the number of genes from 24,500 to 20,500 . The revision eliminates few valid protein-coding genes while dramatically increasing specificity . Second , the analysis provides a scientifically valid methodology for evaluating future proposed additions to the human gene catalog . Third , the analysis implies that the mammalian protein-coding genes have been largely stable , with relatively little invention of truly novel genes . Results Identifying Orphans . Our analysis requires studying the properties of human ORFs that lack cross-species counterparts , which we term `` orphans . '' Such study requires carefully filtering the human gene catalogs , to identify genes with counterparts and to eliminate a wide range of artifacts that would interfere with analysis of the orphans . For this reason , we undertook a thorough reanalysis of the human gene catalogs . We focused on the Ensembl catalog -LRB- version 35 -RRB- , which lists 22,218 protein-coding genes with a total of 239,250 exons . Our analysis considered only the 21,895 genes on the human genome reference sequence of chromosomes 1 22 and X. -LRB- We thus omitted the mitochondrial chromosome , chromosome Y , and `` unplaced contigs , '' which involve special considerations ; see below . -RRB- We developed a computational protocol by which the putative genes are classified based on comparison with the human , mouse , and dog genomes -LRB- Fig. 1 ; see Materials and Methods -RRB- . The mouse and dog genomes were used , because high-quality genomic sequence is available -LRB- 7 , 8 -RRB- , and the extent of sequence divergence is well suited for gene identification . The nucleotide substitution rate relative to human is 0.50 per base for mouse and 0.35 for dog , with insertion and deletion -LRB- indel -RRB- events occurring at a frequency that is 10-fold lower -LRB- 8 , 9 -RRB- . These rates are low enough to allow reliable sequence alignment but high enough to reveal the differential mutation patterns expected in coding and noncoding regions . Clamp et al. . After the computational pipeline , we undertook visual inspection of 1,200 cases to detect instances misclassifications due to limitations of the algorithms or apparent errors in reported human gene annotations ; this process revised the classification of 417 cases . We briefly summarize the results . Class 0 : Transposons , pseudogenes , and other artifacts . Some of the putative genes consist of transposable elements or processed pseudogenes that slipped through the process used to construct the Ensembl catalog . Using a more stringent filter , we identified 1,538 such cases . These were 487 cases consisting of transposonderived sequence , 483 processed pseudogenes derived from a multiexon parent gene -LRB- recognizable because the introns had been eliminated by splicing -RRB- , and 568 processed pseudogenes derived from a single-exon parent gene -LRB- recognizable because the pseudogene sequence almost precisely interrupts the aligned orthologous sequence of human with mouse or dog -RRB- . Class 1 : Genes with cross-species orthologs . We next identified putative genes with a corresponding gene in the syntenic region of mouse or dog . We examined the orthologous DNA sequence in each species , checking whether an orthologous gene was already annotated in current gene catalogs for mouse or dog and , if not , whether we could identify an orthologous gene . Such cases are referred to as `` simple orthology '' -LRB- or 1:1 orthology -RRB- . We then expanded the search to a surrounding region of 1 Mb in mouse and dog to allow for cases of local gene family expansion . Such cases are referred to as `` complex orthology '' -LRB- or `` coorthology '' -RRB- . In both circumstances , the orthologous gene was required to have an ORF that aligns to a substantial portion -LRB- 80 % -RRB- of the human gene and have substantial peptide identity -LRB- 50 % for mouse , 60 % for dog -RRB- . Orthologous genes were identified for 18,752 of the putative human genes , with 16,210 involving simple orthology and 2,542 involving coorthology . Class 2 : Genes with cross-species paralogs . The pipeline then identified 155 cases of putative human genes that have a paralog within the human genome , that , in turn , has an ortholog in mouse or dog . These genes largely represent nonlocal duplications in the human lineage -LRB- three-quarters lie in segmental duplications -RRB- or possibly gene losses in the other lineages . Among these genes , close inspecPNAS December 4 , 2007 vol . 104 no. 49 19429 GENETICS tion revealed eight cases in which a small change to the human annotation allowed the identification of a clear human ortholog . Class 3 : Genes with human-only paralogs . The pipeline identified 68 cases of putative human genes that have one or more paralogs within the human genome , but with none of these paralogs having orthologs in mouse or dog . Close inspection eliminated 17 cases as additional retroposons or other artifacts -LRB- see SI Appendix -RRB- . The remaining 51 cases appear to be valid genes , with 15 belonging to three known families of primate-specific genes -LRB- DUF1220 , NPIP , and CDRT15 families -RRB- and the others occurring in smaller paralogous groups -LRB- two to eight members -RRB- that may also represent primate-specific families . Class 4 : Genes with Pfam domains . The pipeline identified 97 cases of putative genes with homology to a known protein domain in the Pfam collection -LRB- 10 -RRB- . Close inspection eliminated 21 cases as additional retroposons or other artifacts -LRB- see SI Appendix -RRB- and 40 cases in which a small change to the human annotation allowed the identification of a clear human ortholog . The remaining 36 genes appear to be valid genes , with 10 containing known primate-specific domains and 26 containing domains common to many species . Class 5 : Orphans . A total of 1,285 putative genes remained after the above procedure . Close inspection identified 40 cases that were clear artifacts -LRB- long tandem repeats that happen to lack a stop codon -RRB- and 68 cases in which a cross-species ortholog could be assigned after a small change correction to the human gene annotation . The remaining 1,177 cases were declared to be orphans , because they lack orthology , paralogy , or homology to known genes and are not obvious artifacts . We note that the careful review of the genes was essential to obtaining a `` clean '' set of orphans for subsequent analysis . Characterizing the Orphans . We characterized the properties of the orphans to see whether they resemble those seen for proteincoding genes or expected for randoms ORFs arising in noncoding transcripts . ORF lengths . The orphans have a GC content of 55 % , which is much higher than the average for the human genome -LRB- 39 % -RRB- and similar to that seen in protein-coding genes with cross-species counterparts -LRB- 53 % -RRB- . The high-GC content reflects the orphans ' tendency to occur in gene-rich regions . We examined the ORF lengths of the orphans , relative to their GC-content . The orphans have relatively small ORFs -LRB- median 393 bp -RRB- , and the distribution of ORF lengths closely resembles the mathematical expectation for the longest ORF that would arise by chance in a transcript-derived form human genomic DNA with the observed GC-content -LRB- SI Fig. 4 -RRB- . Conservation properties . We then focused on cross-species conservation properties . To assess the sensitivity of various measures , we examined a set of 5,985 `` well studied '' genes defined by the criterion that they are discussed in more than five published articles . For each well studied gene , we selected a matched random control sequence from the human genome , having a similar number of `` exons '' with similar lengths , a similar proportion of repeat sequence and a similar proportion of cross-species alignment , but not overlapping with any putative genes . The well studied genes and matched random controls differ with respect to all conservation properties studied -LRB- SI Fig. 5 and SI Table 1 -RRB- . The nucleotide identity and Ka/Ks ratio clearly differ , but the distributions are wide and have substantial overlap . The indel density has a tighter distribution : 97.3 % of well studied genes , but only 2.8 % of random controls , have an indel density of 10 per kb . The sharpest distinctions , however , were found for two measures that reflect the distinctive evolution of protein-coding genes : the reading frame conservation -LRB- RFC -RRB- score and the codon substitution frequency -LRB- CSF -RRB- score . Reading frame conservation . The RFC score reflects the percentage of nucleotides -LRB- ranging from 0 % to 100 % -RRB- whose reading frame is conserved across species -LRB- SI Fig. 6 -RRB- . The RFC score is determined 19430 www.pnas.org cgi doi 10.1073 pnas .0709013104 Ortholog vs. random Cumulative frequency Orphan vs. random Cumulative frequency a 1.0 0.8 0.6 0.4 0.2 0 30 40 50 60 70 80 RFC score 90 100 b 1.0 0.8 0.6 0.4 0.2 0 30 40 50 60 70 80 RFC score 90 100 JOINT -LRB- MOUSE , DOG -RRB- Cumulative frequency 0.8 0.6 0.4 0.2 0 30 40 50 60 70 80 RFC score 90 100 Cumulative frequency c 1.0 d 1.0 0.8 0.6 0.4 0.2 0 30 40 50 60 70 80 RFC score 90 100 MACAQUE Cumulative frequency e 1.0 0.8 0.6 0.4 0.2 0 30 40 50 60 70 80 RFC score 90 100 f Cumulative frequency 1.0 0.8 0.6 0.4 0.2 0 30 40 50 60 70 80 RFC score 90 100 CHIMP Fig. 2 . Cumulative distributions of RFC score . -LRB- Left -RRB- Human genes with cross-species orthologs -LRB- blue -RRB- versus matched random controls -LRB- black -RRB- . -LRB- Right -RRB- Human orphans -LRB- red -RRB- versus matched random controls -LRB- black -RRB- . RFC scores are calculated relative to mouse and dog together -LRB- Top -RRB- , macaque -LRB- Middle -RRB- and chimpanzee -LRB- Bottom -RRB- . In all cases , the orthologs are strikingly different from their matched random controls , whereas the orphans are essentially indistinguishable from their matched random controls . by aligning the human sequence to its cross-species ortholog and calculating the maximum percentage of nucleotides with conserved reading frame , across the three possible reading frames for the ortholog . The results are averaged across sliding windows of 100 bases to limit propagation of local effects due to errors in sequence alignment and gene boundary annotation . We calculated separate RFC scores relative to both the mouse and dog genomes and focused on a joint RFC score , defined as the larger of two scores . The RFC score was originally described in our work on yeast , but has been adapted to accommodate the frequent presence of introns in human sequence -LRB- see SI Appendix -RRB- . The RFC score shows virtually no overlap between the well studied genes and the random controls -LRB- SI Fig. 5 -RRB- . Only 1 % of the random controls exceed the threshold of RFC 90 , whereas 98.2 % of the well studied genes exceed this threshold . The situation is similar for the full set of 18,752 genes with crossspecies counterparts , with 97 % exceeding the threshold -LRB- Fig. 2a -RRB- . The RFC score is slightly lower for more rapidly evolving genes , but the RFC distribution for even the top 1 % of rapidly evolving genes is sharply separated from the random controls -LRB- SI Fig. 5 -RRB- . By contrast , the orphans show a completely different picture . They are essentially indistinguishable from matched random controls -LRB- Fig. 2b -RRB- and do not resemble even the most rapidly evolving subset of the 18,572 genes with cross-species counterparts . In short , the set of orphans shows no tendency whatsoever to conserve reading frame . Codon substitution frequency . The CSF score provides a complementary test of for the evolutionary pattern of protein-coding genes . Whereas the RFC score is based on indels , the CSF score is based on the different patterns of nucleotide substitution seen in proteincoding vs. random DNA . Recently developed for comparative genomic analysis of Drosophila species -LRB- 11 -RRB- , the method calculates a codon substitution frequency -LRB- CSF -RRB- score based on alignments Clamp et al. . across many species . We applied the CSF approach to alignments of human to nine mammalian species , consisting of high-coverage sequence -LRB- 7 -RRB- from mouse , dog , rat , cow , and opossum and low-coverage sequence -LRB- 2 -RRB- from rabbit , armadillo , elephant , and tenrec . The results again showed strong differentiation between genes with cross-species counterparts and orphans . Among 16,210 genes with simple orthology , 99.2 % yielded CSF scores consistent with the expected evolution of protein-coding genes . By contrast , the 1,177 orphans include only two cases whose codon evolution pattern indicated a valid gene . Upon inspection , these two cases were clear errors in the human gene annotation ; by translating the sequence in a different frame , a clear cross-species orthologs can be identified . Orphans Do Not Represent Protein-Coding Genes . The results above model as wholly implausible . We thus conclude that the vast majority of orphans are simply randomly occurring ORFs that do not represent protein-coding genes . Finally , we note that the careful filtering of the human gene catalog above was essential to the analysis above , because it eliminated pseudogenes and artifacts that would have prevented accurate analysis of the properties of the orphans . Experimental Evidence of Encoded Proteins . As an independent are consistent with the orphans being simply random ORFs , rather than valid human protein-coding genes . However , consistency does not constitute proof . Rather , we must rigorously reject the alternative hypothesis . Suppose the orphans represent valid human protein-coding genes that lack corresponding ORFs in mouse and dog . The orphans would fall into two classes : -LRB- i -RRB- some may predate the divergence from mouse and dog -- that is , they are ancestral genes that were lost in both mouse and dog , and -LRB- ii -RRB- some may postdate the divergence -- that is , they are novel genes that arose in the lineage leading to the human . How can we exclude these possibilities ? Our solution was to study two primate relatives : macaque and chimpanzee . We consider the alternatives in turn . 1 . Suppose that the orphans are ancestral mammalian genes that were lost in dog and mouse but are retained in the lineage leading to human . If so , they would still be present and functional in macaque and chimpanzee , except in the unlikely event that they also underwent independent loss events in both macaque and chimpanzee lineages . 2 . Suppose that the orphans are novel genes that arose in the lineage leading to the human , after the divergence from dog and mouse -LSB- 75 million years ago -LRB- Mya -RRB- -RSB- . Assuming that the generation of new genes is a steady process , the birthdates should be distributed across this period . If so , most of the birthdates will predate the divergence from macaque -LRB- 30 Mya -RRB- and nearly all will predate the divergence from chimpanzee -LRB- 6 Mya -RRB- -LRB- 12 -RRB- . Under either of the above scenarios , the vast majority of the orphans must correspond to functional protein-coding genes in macaque or chimpanzee . We therefore tested whether the orphans show any evidence of protein-coding conservation relative to either macaque or chimpanzee , using the RFC score . Strikingly , the distribution of RFC scores for the orphans is essentially identical to that for the random controls -LRB- Fig. 2 d and f -RRB- . The distribution for the orphans does not resemble that seen even for the top 1 % of most rapidly evolving genes with cross-species counterparts -LRB- SI Figs. 7 9 -RRB- . The set of orphans thus shows no evidence whatsoever of reading-frame conservation even in our closest primate relatives . -LRB- It is of course possible that the orphans include a few valid proteincoding genes , but the proportion must be small enough that it has no discernable effect on the overall RFC distribution . -RRB- We conclude that the vast majority of orphans do not correspond to functional protein-coding genes in macaque and chimpanzee , and thus are neither ancestral nor newly arising genes . If the orphans represent valid human protein-coding genes , we would have to conclude that the vast majority of the orphans were born after the divergence from chimpanzee . Such a model would require a prodigious rate of gene birth in mammalian lineages and a ferocious rate of gene death erasing the huge number of genes born before the divergence from chimpanzee . We reject such a Clamp et al. . check on our conclusion , we reviewed the scientific literature for published articles mentioning the orphans to determine whether there was experimental evidence for encoded proteins . Whereas the vast majority of the well studied genes have been directly shown to encode a protein , we found articles reporting experimental evidence of an encoded protein in vivo for only 12 of 1,177 orphans , and some of these reports are equivocal -LRB- SI Table 2 -RRB- . The experimental evidence is thus consistent with our conclusion that the vast majority of nonconserved ORFs are not protein-coding . In the handful of cases where experimental evidence exists or is found in the future , the genes can be restored to the catalog on a case-by-case basis . Revising the Human Gene Catalogs . With strong evidence that the vast majority of orphans are not protein-coding genes , it is possible to revise the human gene catalogs in a principled manner . Ensembl catalog . Our analysis of the Ensembl -LRB- v35 -RRB- catalog indicates that it contains 19,108 valid protein-coding genes on chromosomes 1 22 and X within the current genome assembly . The remaining 15 % of the entries are eliminated as retroposons , artifacts or orphans . Together with the mitochrondrial chromosome -LSB- well known to contain 13 protein-coding genes -LRB- 13 -RRB- -RSB- and chromosome Y -LSB- for which careful analysis indicates 78 protein-coding genes -LRB- 14 -RRB- -RSB- , the total reaches 19,199 . We extended the analysis to the Ensembl -LRB- v38 -RRB- catalog , in which 2,212 putative genes were added and many previous entries were revised or deleted . Our computational pipeline found 598 additional valid protein-coding genes based on cross-species counterparts , 1,135 retroposons , and 479 orphans . The RFC curves for the orphans again closely matched the expectation for random DNA . Other catalogs . We applied the same approach to the Vega -LRB- v34 -RRB- and RefSeq -LRB- March 2007 -RRB- catalog . Both catalogs contain a substantial proportion of entries that appear not to be valid protein-coding genes -LRB- 16 % and 10 % , respectively -RRB- , based on the lack of a crossspecies counterpart -LRB- see SI Fig. 10 and SI Appendix -RRB- . If we restrict the RefSeq entries to those with the highest confidence -LRB- with the caveat that this set contains many fewer genes -RRB- , only 1 % appear invalid . Together , these two catalogs add an additional 673 proteincoding genes . Combined analysis . Combining the analysis of the three major gene catalogs , we find that only 20,470 of the 24,551 entries appear to be valid protein-coding genes . Limitations on the Analysis . Our analysis of the current gene catalogs has certain limitations that should be noted . First , we eliminated all pseudogenes and orphans . We found six reported cases in which a processed pseudogene or transposon underwent exaptation to produce a functional gene -LRB- SI Tables 1 and 3 -RRB- and 12 reported cases of orphans with experimental evidence for an encoded protein . These 18 cases can be readily restored to the catalog -LRB- raising the count to 20,488 -RRB- . There are additional cases of potentially functional retroposons that are not present in the current gene catalogs -LRB- 15 -RRB- . If any are found to produce protein , they should also be included . Second , we have not considered the 197 putative genes that lie in the `` unmapped contigs . '' These regions are sequences that were omitted from the finished assembly of the human genome . They largely consist of segmental duplications , and most of the genes are highly similar to others in the assembly . Many of the sequence may PNAS December 4 , 2007 vol . 104 no. 49 19431 GENETICS Fig. 3 . An example gene report Gene type : simple ortholog ENST00000 222 304 RefSeq : NM_021175.2 427 bp -LRB- 255 bp coding -RRB- card for a small gene , HAMP , on 2.6 kb at Chromosome 19 : 40,465,250 40,467,886 Hugo : HAMP 3 Exons -LRB- 3 coding -RRB- chromosome 19 . Report cards for Protein family : HEPCIDIN PRECURSOR GC content : 60 % ENSG00000105 697 all 22,218 putative genes in EnProtein domains : Hepcidin Repeat : 0 % sembl v35 are available at www . Segmental duplication : Tandem repeat : 0 % Description : Hepcidin precursor -LRB- liver-expressed antimicrobial peptide -RRB- broad.mit.edu/mammals/alpheus . The report cards provide a visual framework for studying cross-speSynteny Exon Exon Exon Exon ExonExon 1 2 3 1 2 3 cies conservation and for spotting Human possible problems in the human gene annotation . Information at Mouse Chr 7 19,899,618 19,902,240 -LRB- 2622 bp -RRB- Dog Chr 1 119,490,967 119,492,937 -LRB- 1970 bp -RRB- the top shows chromosomal location ; alternative identifiers ; and Alignment detail summary information , such as DNA Protein length , number of exons , and reHuman Mouse peat content . Various panels below Dog provide graphical views of the alignment of the human gene to the mouse and dog genomes . `` Synteny '' shows the large-scale alignment of genomic sequence , indicating both aligned and unaligned segments . The human sequence is annotated with the exons in white and repetitive sequence in dark gray . `` Alignment detail '' shows the complete DNA sequence alignment and protein alignment . In the DNA alignment , the human sequence is given at the top , bases in the other species are marked as Frame alignment Exon 1 Exon 2 Exon 3 Codon Mouse matching -LRB- light gray -RRB- or nonmatchDog position 1 ing -LRB- dark gray -RRB- , exon boundaries Codon Mouse are marked by vertical lines , indels position 2 Dog Codon Mouse are marked by small triangles Dog position 3 above the sequence -LRB- vertex down for insertions , vertex up for deleIndels ; starts and stops tions , number indicating length in Mouse bases -RRB- , the annotated start codon is Dog in green , and the annotated stop codon is in purple . In the protein alignment , the human amino acid Intron 1 Intron 2 Splice sites sequence is given at the top , and Human the sequences in the other species Mouse are marked as matching -LRB- light Dog gray -RRB- , similar -LRB- pink -RRB- , or nonmatching -LRB- red -RRB- . `` Frame alignment '' Intron 1 Intron 2 Summary data shows the distribution of nucleotide mismatches found in each Indels/kb Donor Acceptor RFC Percent Local Nucleotide Peptide Ka/Ks Gene neighborhood FS Non-FS score present stops identity identity Sites Cons Sites Cons codon position , with excess muta0 .00 3.96 Mouse Chr 7 100.0 65 % 1 65 % 0.63 2 53 % 2 2 2 tions expected in the third position . Matching are shown in light 0.00 7.79 Dog Chr 1 100.0 80 % 1 80 % 69 % 0.61 2 2 2 2 gray , and mismatches are shown in dark gray . `` Indels , starts and stops '' provides an overview of key events . Indels are indicated by triangles -LRB- vertex down for insertions , vertex up for deletions -RRB- and marked as frameshifting -LRB- red -RRB- or frame-preserving -LRB- gray -RRB- . Start codons are marked in green and stop codons in purple . `` Splice sites '' shows sequence conservation around splice sites , with two-base donor and acceptor sites highlighted in gray and mismatching bases indicated in red . `` Summary data '' lists various conservation statistics relative to mouse and dog , including RFC score , nucleotide identity , number of conserved splice sites , frameshifting and nonframeshifting indel density/kb , and gene neighborhood . The gene neighborhood shows a dot for the three upstream and downstream genes , which is colored gray if synteny is preserved and red otherwise . represent alternative alleles or misassemblies of the genome . However , regions of segmental duplication are known to be nurseries of evolutionary innovation -LRB- 16 -RRB- and may contain some valid genes . They deserve focused attention . Third and most importantly , the nonconserved ORFs studied here were typically included in current gene catalogs because they have the potential to encode at least 100 amino acids . We thus do not know whether our conclusions would apply to much shorter ORFs . In principle , there exist many additional proteincoding genes that encode short proteins , such as peptide hormones , which are usually translated from much larger precursors and may evolve rapidly . It should be possible to investigate the 19432 www.pnas.org cgi doi 10.1073 pnas .0709013104 properties of smaller ORFs by using additional mammalian species beyond mouse and dog . Improving Gene Annotations . In the course of our work , we generated detailed graphical `` report cards '' for each of the 22,218 putative genes in Ensembl -LRB- v35 -RRB- . The report cards show the gene structure , sequence alignments , measures of evolutionary conservation , and our final classification -LRB- Fig. 3 -RRB- . The report cards are valuable for studying gene evolution and for refining gene annotation . By examining local anomalies by crossspecies comparison , we have identified 23 clear errors in gene annotation -LRB- including cases in which changing the reading frame or coding strand reveals unambiguous cross-species orthologs -RRB- and Clamp et al. . 332 cases in which cross-species conservation suggests altering the start or stop codon , eliminating an internal exon , or moving a splice site . Of these latter cases , most are likely to be errors in the human gene annotation , although some may represent true cross-species differences . The report cards , together with search tools and summary tables , are available at www.broad.mit.edu/mammals/ alpheus . Discussion The analysis here addresses an important challenge in genomics -- determining whether an ORF truly encodes a protein . We show that the vast majority of ORFs without cross-species counterparts are simply random occurrences . The exceptions appear to represent a sufficiently small fraction that the best course is would be consider such ORFs as noncoding in the absence of direct experimental evidence . We propose that it is time to undertake a thorough revision of the human gene catalogs by applying this principle to filter the entries . Specifically , we propose that nonconserved ORFs should be included in the human gene catalog if there is clear experimental evidence of an encoded protein . We report here an initial attempt to apply this principle , resulting in a catalog with 20,488 genes . Our focus has been on excluding putative genes from the human catalogs . We have not explored whether there are additional protein-coding genes that have not yet been included , although it is clear that cross-species analysis can be helpful in identifying such genes . Preliminary analysis from our own group and others suggests that there may be a few hundred additional protein-coding genes to be found but that the final total is likely to remain under 21,000 . The largest open question concerns very short peptides , which may still be seriously underestimated . One important biological implication of our results is that truly novel protein-coding genes -LRB- encoding at least 100 amino acids -RRB- arise only rarely in mammalian lineages . With the current gene catalogs , there are only 168 `` human-specific '' genes -LRB- 1 % of the total ; only 11 are manually reviewed entries in RefSeq ; see SI Table 4 -RRB- . These genes lack clear orthologs or paralogs in mouse and dog , but are recognizable because they belong to small paralogous families within the human genome -LRB- 2 to 9 members -RRB- or contain Pfam domains homologous to other proteins . These paralogous families shows a range of nucleotide identities , consistent with their having arisen over the course of 75 million years since the divergence 1 . Cheng J , Kapranov P , Drenkow J , Dike S , Brubaker S , Patel S , Long J , Stern D , Tammana H , Helt G , et al. -LRB- 2005 -RRB- Science 308:1149 1154 . 2 . Carninci P , Kasukawa T , Katayama S , Gough J , Frith MC , Maeda N , Oyama R , Ravasi T , Lenhard B , Wells C , et al. -LRB- 2005 -RRB- Science 309:1559 1563 . 3 . ENCODE Project Consortium -LRB- 2007 -RRB- Nature 447:799 816 . 4 . Hubbard TJ , Aken BL , Beal K , Ballester B , Caccamo M , Chen Y , Clarke L , Coates G , Cunningham F , Cutts T , et al. -LRB- 2007 -RRB- Nucleic Acids Res 35 : D610 D617 . 5 . Pruitt KD , Tatusova T , Maglott DR -LRB- 2007 -RRB- Nucleic Acids Res 35 : D61 D65 . 6 . Ashurst JL , Chen CK , Gilbert JG , Jekosch K , Keenan S , Meidl P , Searle SM , Stalker J , Storey R , Trevanion S , et al. -LRB- 2005 -RRB- Nucleic Acids Res 33 : D459 D465 . 7 . Goodstadt L , Ponting CP -LRB- 2006 -RRB- PLoS Comput Biol 2 : e133 : 1134 1150 . 8 . Lindblad-Toh K , Wade CM , Mikkelsen TS , Karlsson EK , Jaffe DB , Kamal M , Clamp M , Chang JL , Kulbokas EJ , III , Zody MC , et al. -LRB- 2005 -RRB- Nature 438:803 819 . 9 . Mouse Genome Sequencing Consortium -LRB- 2002 -RRB- Nature 420:520 562 . from the mouse lineage . In fact , many of these 168 genes are not entirely novel inventions : One-third show strong similarity to mouse or dog genes across at least 50 % of their length ; although this falls short of our threshold for declaring orthologs or paralogs -LRB- 80 % -RRB- , it is nonetheless substantial . Among the orphans , there are only 12 cases with reported experimental evidence of an encoded protein . These cases , which comprise 0.06 % of the gene catalog , have similar RFC and nucleotide identity scores to neutral sequence and have no similarity with any mouse or dog genes , suggesting these are truly novel inventions . We conclude that mammals thus share largely the same repertoire of protein-coding genes , modified primarily by gene family expansions and contractions . Finally , the creation of more rigorous catalogs of protein-coding genes for human , mouse , and dog will also aid in the creation of catalogs of noncoding transcripts . This should help propel understanding of these fascinating and potentially important RNAs . Materials and Methods All annotations were based on the NCBI35 -LRB- hg17 -RRB- assembly and all genome alignments were taken from the pairwise BLASTZ alignment to mouse assembly NCBI36 -LRB- mm4 -RRB- and dog Broad , Version 1.0 -LRB- canFam1 ; available from http://genome.ucsc.edu -RRB- . We identified retroposons , using the Ensembl annotation -LRB- www.ensembl . org -RRB- . We then eliminated pseudogenes by identifying transcripts with either retained introns or through interrupted synteny at the boundaries of the transcript . The set of well studied genes were found by using those transcripts whose RefSeq entry contained references to more than five articles . Orthologous genes were identified by using synteny -LRB- across 80 % of the gene -RRB- and peptide identity -LRB- 50 % for mouse and 60 % for dog -RRB- . The combined RFC score was the highest independent score -LRB- taking into account the length of the transcript -RRB- for alignments to both mouse and dog . For more details , see SI Appendix . We thank colleagues at the University of California , Santa Cruz , genome browser and the Ensembl genome browser for providing data -LRB- BLASTZ alignments , synteny nets , genes , and annotations -RRB- ; L. Gaffney for assistance in preparing the manuscript and figures ; S. Fryc and N. Anderson for resequencing data ; and a large collection of colleagues around the world for many helpful discussions over the past 3 years that have helped shape and improve this work . This work was supported by the National Institutes of Health National Human Genome Research Institute . 10 . Finn RD , Mistry J , Schuster-Bockler B , Griffiths-Jones S , Hollich V , Lassmann T , Moxon S , Marshall M , Khanna A , Durbin R , et al. -LRB- 2006 -RRB- Nucleic Acids Res 34 : D247 D251 . 11 . Lin MF , Carlson JW , Crosby MA , Matthews BB , Yu C , Park S , Wan KH , Schroeder AJ , Gramates LS , St. Pierre SE , et al. -LRB- 2007 -RRB- Genome Res , 10.1101 / gr .6679507 . 12 . Pilbeam D , Young N -LRB- 2004 -RRB- C R Palevol 3:305 321 . 13 . Anderson S , Bankier AT , Barrell BG , de Bruijn MH , Coulson AR , Drouin J , Eperon IC , Nierlich DP , Roe BA , Sanger F , et al. -LRB- 1981 -RRB- Nature 290:457 465 . 14 . Skaletsky H , Kuroda-Kawaguchi T , Minx PJ , Cordum HS , Hillier L , Brown LG , Repping S , Pyntikova T , Ali J , Bieri T , et al. -LRB- 2003 -RRB- Nature 423:825 837 . 15 . Vinckenbosch N , Dupanloup I , Kaessmann H -LRB- 2006 -RRB- Proc Natl Acad Sci USA 103:3220 3225 . 16 . Eichler EE -LRB- 2001 -RRB- Trends Genet 17:661 669 . Clamp et al. . PNAS December 4 , 2007 vol . 104 no. 49 19433 GENETICS

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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Vol 437 | 20 October 2005 | doi : 10.1038 / nature04240 LETTERS Natural selection on protein-coding genes in the human genome Carlos D. Bustamante1 , Adi Fledel-Alon1 , Scott Williamson1 , Rasmus Nielsen1 ,2 , Melissa Todd Hubisz1 , Stephen Glanowski3 , David M. Tanenbaum3 , Thomas J. White4 , John J. Sninsky4 , Ryan D. Hernandez1 , Daniel Civello4 , Mark D. Adams5 , Michele Cargill4 * & Andrew G. Clark6 * Comparisons of DNA polymorphism within species to divergence between species enables the discovery of molecular adaptation in evolutionarily constrained genes as well as the differentiation of weak from strong purifying selection1 4 . The extent to which weak negative and positive darwinian selection have driven the molecular evolution of different species varies greatly5 16 , with some species , such as Drosophila melanogaster , showing strong evidence of pervasive positive selection6 9 , and others , such as the selfing weed Arabidopsis thaliana , showing an excess of deleterious variation within local populations9 ,10 . Here we contrast patterns of coding sequence polymorphism identified by direct sequencing of 39 humans for over 11,000 genes to divergence between humans and chimpanzees , and find strong evidence that natural selection has shaped the recent molecular evolution of our species . Our analysis discovered 304 -LRB- 9.0 % -RRB- out of 3,377 potentially informative loci showing evidence of rapid amino acid evolution . Furthermore , 813 -LRB- 13.5 % -RRB- out of 6,033 potentially informative loci show a paucity of amino acid differences between humans and chimpanzees , indicating weak negative selection and/or balancing selection operating on mutations at these loci . We find that the distribution of negatively and positively selected genes varies greatly among biological processes and molecular functions , and that some classes , such as transcription factors , show an excess of rapidly evolving genes , whereas others , such as cytoskeletal proteins , show an excess of genes with extensive amino acid polymorphism within humans and yet little amino acid divergence between humans and chimpanzees . Of considerable interest to medical geneticists is the extent to which weak negative selection has shaped the human genome . Sensitivity to weak selection may be important in identifying candidate genes for association mapping studies , because weakly deleterious mutations can reach appreciable frequencies in local populations and , thus , may contribute significantly to genetic variance in disease susceptibility . A team at Celera Genomics sequenced by exon-specific polymerase chain reaction -LRB- PCR -RRB- amplification 20,362 loci in 20 European Americans , 19 African Americans and one male chimpanzee with the initial intention of finding novel nonsynonymous single nucleotide polymorphisms -LRB- SNPs -RRB- based on their 2001 build of the human genome . Here we analyse 11,624 genes with complementary DNA support , strong evidence of orthology between humans and chimpanzee , and location in non-repetitive elements of the genome . The distributions of the total number of synonymous and non-synonymous SNPs and fixed differences for these loci are presented in Fig. 1a . We found that 10,767 genes -LRB- 92.6 % -RRB- showed some form of coding nucleotide variability either within human subjects or between humans and a chimpanzee . A total of 34,099 fixed synonymous differences between all humans in our sample and the chimpanzee yield a genomic average synonymous divergence of dS 1:02 % . Correspondingly , we found 20,467 non-synonymous differences dN 0:242 % across 11.81 megabases -LRB- Mb -RRB- of aligned coding DNA . We also discovered 15,750 synonymous and 14,311 non-synonymous SNPs among the human subjects , yielding average synonymous and non-synonymous SNP densities of pS 0:470 % and pN 0:169 % . We note that the ratio of non-synonymous to synonymous differences -LRB- 23.76 % -RRB- is smaller than the ratio of nonsynonymous to synonymous polymorphisms -LRB- 38.42 % -RRB- , indicating a highly significant excess of amino acid variation relative to divergence -LRB- x 2 816.03 , P , 2 10216 -RRB- . This is consistent with previous studies of human polymorphism that suggest that a large proportion of amino acid variation in the human genome is slightly to moderately deleterious11 16 . In order to identify particular genes with evidence of non-neutral evolution , we applied a statistical approach that makes efficient use of comparative population genomic data4 ,7,9,17 . The method quantifies the extent and directionality of selection operating on a given gene in terms of the population genetic selection parameter g 2N e s -LRB- where N e is the effective population size and s is the selection coefficient in a Wright Fisher genic selection model -RRB- as estimated from contingency tables comparing polymorphism -LRB- P -RRB- versus divergence -LRB- D -RRB- at synonymous -LRB- S -RRB- versus non-synonymous -LRB- N -RRB- sites3 ,4 . The parameter is negative if a gene shows an excess of amino acid polymorphism -LRB- or paucity of amino acid divergence -RRB- and positive if a gene has an excess of amino acid divergence relative to the genomic average for synonymous sites . Invariant sites in an alignment do not affect the estimate of g , so it is independent of strong purifying selection operating at the locus . One consequence of this robustness is that genes with little or no variation contain little information regarding g . We therefore concentrate on two subsets of the data : the n 3,277 genes with at least four variable non-synonymous sites in the alignment -LRB- that is , P N D N $ 4 -RRB- , which are potentially informative about positive selection -LRB- IPS data -RRB- , and the set with at least two variable non-synonymous sites , which are potentially informative only about negative selection -LRB- INS data ; n 6,033 -RRB- . In order to classify genes , we use the posterior distribution of the selection coefficient to calculate a test statistic , such that P Pr -LCB- g . 0jData -RCB- is the posterior probability that a gene is subject to positive darwinian selection and P2 Pr -LCB- g , 0jData -RCB- is the posterior probability that a gene harbours excess amino acid variation . -LRB- Negative 1 Department of Biological Statistics and Computational Biology , 101 Biotechnology Building , Cornell University , Ithaca , New York 14853 , USA . 2Center for Bioinformatics , University of Copenhagen , Universitetsparken 15 , DK-2100 Copenhagen , Denmark . 3Applied Biosystems , 45 West Gude Drive , Rockville , Maryland 20850 , USA . 4Celera Diagnostics , 1401 Harbor Bay Parkway , Alameda , California 94502 , USA . 5Department of Genetics , Case Western Reserve University , 10900 Euclid Avenue , Cleveland , Ohio 44106 , USA . 6Department of Molecular Biology and Genetics , 227 Biotechnology Building , Cornell University , Ithaca , New York 14853 , USA . * These authors contributed equally to this work . 2005 Nature Publishing Group 1153 LETTERS NATURE | Vol 437 | 20 October 2005 Figure 1 | Summary distributions of McDonald Kreitman cell entries and mkprf analyses . a , Distributions of synonymous and non-synonymous SNPs and fixed differences across 11,624 genes . b , Distribution of the posterior probability that a gene is positively selected for simulated data under three neutral demographic scenarios and for the Celera data conditioning on a gene having at least four variable amino acid positions -LRB- IPS data -RRB- . c , Distribution of the estimated average selection coefficient for the 3,277 genes in the Celera IPS data set . d , Distribution of g for four molecular functions showing an excess of non-neutral loci . Bars represent 95 % CIs with blue and red denoting CIs completely above or below g 0 . Table 1 | Molecular functions and biological processes showing as an excess of positively or negatively selected genes Category P-value Number where CI . 0 Number where CI , 0 N Biological process Apoptosis Cell structure and motility Ectoderm development Gametogenesis General vesicle transport Intracellular protein traffic mRNA transcription Natural-killer-cell-mediated immunity Nucleoside , nucleotide and nucleic acid metabolism Sensory perception Molecular function Actin family cytoskeletal protein Cytoskeletal protein Defence/immunity protein Extracellular matrix Homeotic transcription factor Immunoglobulin receptor family member Kinase modulator KRAB box transcription factor Membrane traffic protein Microtubule-binding motor protein Microtubule family cytoskeletal protein Non-motor actin-binding protein Nuclear hormone receptor Protein kinase Receptor RNA helicase Transcription factor Voltage-gated potassium channel Zinc finger transcription factor 0.00336 0.00008 0.02805 0.03411 0.00016 0.01151 0.00002 0.03299 0.00467 0.04577 0.00008 0.00000 0.00965 0.01478 0.02586 0.04558 0.00538 0.00004 0.02701 0.03109 0.01373 0.01691 0.00143 0.04366 0.00211 0.03948 0.00000 0.03943 0.00074 12 4 1 5 0 8 29 1 38 9 4 7 10 3 2 7 0 17 2 1 2 3 3 6 31 0 39 0 20 10 -LRB- 5 -RRB- 27 -LRB- 8 -RRB- 12 -LRB- 7 -RRB- 4 -LRB- 1 -RRB- 14 -LRB- 4 -RRB- 32 -LRB- 10 -RRB- 34 -LRB- 17 -RRB- 3 -LRB- 2 -RRB- 65 -LRB- 28 -RRB- 9 -LRB- 4 -RRB- 23 -LRB- 10 -RRB- 36 -LRB- 12 -RRB- 12 -LRB- 5 -RRB- 15 -LRB- 11 -RRB- 2 -LRB- 0 -RRB- 3 -LRB- 1 -RRB- 9 -LRB- 3 -RRB- 10 -LRB- 5 -RRB- 17 -LRB- 6 -RRB- 7 -LRB- 1 -RRB- 9 -LRB- 1 -RRB- 12 -LRB- 3 -RRB- 0 -LRB- 0 -RRB- 4 -LRB- 1 -RRB- 37 -LRB- 18 -RRB- 8 -LRB- 4 -RRB- 41 -LRB- 19 -RRB- 5 -LRB- 2 -RRB- 19 -LRB- 9 -RRB- 99 -LRB- 53 -RRB- 176 -LRB- 101 -RRB- 98 -LRB- 61 -RRB- 41 -LRB- 23 -RRB- 40 -LRB- 20 -RRB- 159 -LRB- 83 -RRB- 333 -LRB- 185 -RRB- 19 -LRB- 9 -RRB- 568 -LRB- 311 -RRB- 101 -LRB- 56 -RRB- 104 -LRB- 60 -RRB- 205 -LRB- 118 -RRB- 89 -LRB- 54 -RRB- 103 -LRB- 78 -RRB- 28 -LRB- 8 -RRB- 36 -LRB- 27 -RRB- 28 -LRB- 14 -RRB- 168 -LRB- 108 -RRB- 70 -LRB- 32 -RRB- 31 -LRB- 19 -RRB- 52 -LRB- 34 -RRB- 58 -LRB- 27 -RRB- 10 -LRB- 7 -RRB- 94 -LRB- 36 -RRB- 343 -LRB- 207 -RRB- 33 -LRB- 18 -RRB- 428 -LRB- 240 -RRB- 23 -LRB- 11 -RRB- 229 -LRB- 141 -RRB- Classification is based on Panther classification . The P-value is the uncorrected value from the Mann Whitney U-test . A total of 139 different molecular functions and 133 biological processes were tested ; non-significant categories are listed in Supplementary Table 1 , as are significant categories with considerable overlap with those shown in the Table . Parentheses for all count data denote the IPS data set . Bold text indicates negatively selected genes ; non-bold text indicates positively selected genes . 1154 2005 Nature Publishing Group NATURE | Vol 437 | 20 October 2005 LETTERS selection on slightly deleterious mutations increases the proportion of non-synonymous polymorphisms relative to the proportion of non-synonymous fixed differences . -RRB- Figure 1b , c shows histograms of the distribution of P and g among genes in the IPS data . In order to assess how deviations from the assumptions of our model may influence our conclusions , we simulated 10,000 replicate data sets under each of three different demographic models -LRB- See Supplementary Data 1 for details -RRB- and plotted the distribution of P for the corresponding IPS data sets in these simulations . The Celera data have a clear excess of genes with high and low posterior probabilities -LRB- that is , there are too many genes in the ,1 % , 1 5 % and .99 % categories -RRB- regardless of which demographic model is used as the null hypothesis . The signature is particularly strong for weak negative selection . Figure 1c shows the distribution of g among genes in the IPS data set -LRB- estimated as the posterior mean of the selection parameter for each gene -RRB- and Fig. 1d shows the posterior mean and credibility intervals -LRB- CIs -RRB- for genes in four Panther classifications enriched for positively or negatively selected genes -LRB- see Table 1 and Supplementary Table 1 for details -RRB- . In Fig. 2 we present an amino acid selection map of the human genome with each locus mapped onto its genomic location and coloured according to the strength of evidence for positive or Figure 2 | A selection map of the human genome . Red bars indicate loci under negative selection and blue bars are loci under positive selection at 95 % credibility level . Loci with very strong evidence of selection -LRB- .99 % credibility -RRB- are denoted by their HUGO name , and within this category genes with a morbidity entry in the OMIM database are denoted by an asterisk . 1155 2005 Nature Publishing Group LETTERS NATURE | Vol 437 | 20 October 2005 negative selection . Although we find that most of the genes in the informative data sets -LRB- n 4,916 -RRB- show no evidence of selection according to our methods , we do classify 813 loci as significantly negatively selected and 304 as positively selected at a 5 % cutoff . Of the 50 loci identified by ref . 18 as rapidly evolving , 45 were informative about positive selection in our data set . Of these , 14 -LRB- 31.1 % -RRB- had more than 95 % of their posterior mass above g 0 , and 37 -LRB- 82.2 % -RRB- had a majority of their posterior mass above neutrality , indicating good agreement between population genetic and phylogenetic approaches for identifying rapidly evolving genes . There is a high degree of overlap in the types of genes classified as positively selected by both studies -LRB- see Table 1 and Supplementary Table 1 -RRB- , including defence/immunity proteins -LRB- P 0.00965 -RRB- , gametogenesis -LRB- P 0.03411 -RRB- , apoptosis -LRB- P 0.00336 -RRB- and sensory perception -LRB- P 0.04577 -RRB- . One interesting result of our analysis is that transcription factors as a group seem to be rapidly evolving -LRB- P , 0.0001 -RRB- , with 39 out of 240 in the informative data sets -LRB- 16.25 % -RRB- having P greater than 97.5 % as compared to 9.6 % of all loci in the IPS data set . Similarly , we find evidence that the categories of nuclear hormone receptors -LRB- P 0.00143 -RRB- and genes involved in nucleoside , nucleotide and nucleic acid metabolism -LRB- P 0.00467 -RRB- have an excess of rapidly evolving genes . We also used our approach to identify loci and classes of genes that show a paucity of amino acid divergence between humans and chimpanzees , yet have moderate to high levels of amino acid polymorphism , which we believe to harbour an excess of mildly deleterious variation . For example , loci involved in actin binding -LRB- P 0.00013 ; Supplementary Table 1 -RRB- and cytoskeletal formation -LRB- P , 0.00001 -RRB- contain an over-representation of negatively selected loci , with 36 out of 205 cytoskeletal proteins in the informative set -LRB- 17.6 % -RRB- having P 2 greater than 97.5 % -LRB- Table 1 -RRB- . For example , 6 out of the 9 myosin heavy chain loci exhibit a large excess of amino acid polymorphism , including non-muscle myosin -LRB- MYH9 , P 2 . 0.983 -RRB- , embryonic -LRB- MYH3 , P 2 . 0.999 -RRB- , perinatal -LRB- MYH8 , P 2 . 0.962 -RRB- and adult skeletal -LRB- MYH4 , P 2 . 0.946 ; MYH13 , P 2 . 0.957 -RRB- myosin as well as the smooth muscle -LRB- MYH11 , P 2 . 0.999 -RRB- form . Other cytoskeletal proteins with excess amino acid polymorphism within human populations include myomesin 2 and 3 -LRB- MYOM2 , MYOM3 -RRB- , dystrophin related protein 2 -LRB- DRP2 -RRB- , a - and b-adducin -LRB- ADD1 , ADD2 -RRB- , sarcospan -LRB- SSPN -RRB- and scinderin -LRB- SCIN -RRB- . These results are consistent with the fact that as a group , genes involved in cell structure and motility -LRB- Table 1 -RRB- show a signature of negative or purifying selection -LRB- P 0.00008 -RRB- , with 27 out 176 -LRB- 15.3 % -RRB- loci exhibiting excess amino acid polymorphism relative to divergence . Mutations in cytoskeletal protein-coding genes are known to cause a number of mendelian diseases and have been implicated in various complex disorders . For example , with the dystrophin gene many different types of mutation are known to cause both Duchenne and Becker types of muscular dystrophy -LRB- DMD , P 2 . 0.969 -RRB- . Also in this set is myosin VIIA -LRB- MYO7A , P 2 . 0.99 -RRB- , a gene implicated in Usher syndrome -LRB- 1B -RRB- , the most common cause of congenital deafness and blindness in developed countries . Similarly , the a - and b-adducin genes -LRB- P 2 . 0.99 for both -RRB- are associated with hypertension and cardiovascular disease , and one known causative variant -LRB- ADD1 G460W -LRB- refs 19 , 20 -RRB- -RRB- is found at moderate frequencies in both African Americans -LRB- 9.7 % -RRB- and European Americans -LRB- 28.9 % -RRB- in our sample . Another interesting group of genes that show excess amino acid polymorphism -LRB- P 0.02805 -RRB- are those involved in ectoderm development , with 12 loci out of 98 exhibiting significantly elevated levels of amino acid polymorphism relative to amino acid divergence -LRB- Table 1 -RRB- . These include three loci in which mutations are known to cause disease : GLI3 -LRB- polydactyly -RRB- , NOTCH3 -LRB- Drosophila homologue implicated in cerebral arteriopathy -RRB- and DCC -LRB- colorectal carcinoma -RRB- . Interestingly , all three of these genes are also involved in neurogenesis according to the Panther molecular function classification . Genes involved in general vesicle transport also show 1156 excess amino acid polymorphism as a class -LRB- P 0.00016 -RRB- . Sixteen loci have posterior distributions with more than 95 % and four with more than 99 % mass above g 0 -LRB- for example , COPE , HD , KIF4A , SEC31L1 and STX11 -RRB- . The most familiar of these is HD -- the gene that causes Huntington 's disease . To quantify the strength of association between non-neutral evolution and genetic disease more formally , we undertook two analyses . The first is a logistic regression of Online Mendelian Inheritance in Man -LRB- OMIM -RRB- morbidity status -LRB- 1 disease ; 0 non-disease -RRB- on the square-root of observed species nonpffiffiffiffiffiffi synonymous substitution rate dN for all loci in the IPS data contained in the OMIM database of disease and non-disease genes . This approach -LRB- which is independent of the Poisson random field -LRB- PRF -RRB- analysis and summarized in Fig. 3a -RRB- yields a highly significant negative association bpffiffiffiffi 27:6941 ; b0 20:4555 between rate dN of amino acid evolution and disease status for moderate to highly polymorphic loci -LRB- likelihood-ratio test LRT 14:8 ; Px2 1:1 1024 ; n 1,438 loci -RRB- , suggesting that mendelian dis1 orders may have discernable darwinian consequences . A second test of the same hypothesis , a Mann Whitney U-test comparing disease versus non-disease loci , also indicates a marginally significant excess of genes with high P 2 among genes contributing to mendelian disease -LRB- P 0.0374 ; see Fig. 3b -RRB- . The results of analysis of human polymorphism at this scale may help to guide our thinking about human evolution at a broad level , and they also help sharpen our targets for exploration of the genetic basis for medical conditions . Examination of Figs 1 and 2 shows that only a small minority of non-neutral genes are facing positive selection . In this group are genes that might be responsible for Figure 3 | Association between negative selection and disease . a , Results of a logistic regression analysis of OMIM status -LRB- disease versus non-disease -RRB- in the IPS data set as a function of the per site amino acid substitution rate . 95 % confidence intervals are found via non-parametric bootstrap re-sampling . b , Histograms for P 2 P r -LCB- g , 0jData -RCB- , the probability that non-lethal mutations at a gene are negatively selected , across disease -LRB- black bars -RRB- and control -LRB- non-disease ; grey bars -RRB- genes . 2005 Nature Publishing Group NATURE | Vol 437 | 20 October 2005 LETTERS adaptive differences between humans and chimpanzees , or for which molecular evolution might be driven by pathogen pressure . Each of these genes is a candidate for a deeper analysis of the evolutionary past of our species . Most genes in Fig. 2 show a signature of weak negative selection , a feature that is detected only if there are segregating variants that have deleterious consequences . This implies that this group constitutes a set of genes of keen interest in medical genetics . Notably , a substantial portion of these genes is also already known to be mutable to a mendelian disorder . These genes remain prime candidates in our quest for understanding the genetic basis for a diverse array of complex disorders that show weak familial tendencies . METHODS Sequencing and bioinformatics . Celera Genomics applied exon-specific PCR amplification to 20,362 loci in 39 humans and one male chimpanzee in order to obtain sequence variants in these regions -LRB- details are provided in the Supplementary Methods -RRB- . Of these , 14,032 genes shared at least 95 % sequence identity to a unique accession in the NM series of the NCBI Reference Sequence -LRB- RefSeq -RRB- 9.0 database -LRB- 3/1/2005 -RRB- and mapped onto build 34 of the human genome at the same genomic location as the accession -LRB- mapping was done using BLAT21 v. 29 -RRB- . The loci sequenced by Celera were aligned with the best hit in RefSeq . Regions of the alignment that were not in the RefSeq portion of the alignment were omitted from further analyses as were loci where the chimpanzee sequence had an internal stop codon . In order to exclude paralogous genes , we restricted our selection analysis to loci with d S , 0.1 . Of the remaining 11,624 genes , 8,292 had at least one non-synonymous SNP or fixed difference , and could thus be used for further study using the mkprf method -LRB- McDonald Kreitman analysis using Poisson random field ; http : / / cbsuapps.tc.cornell.edu/mkprf.aspx -RRB- . We also define two sets of informative loci -LRB- n 3,277 -RRB- with at least four variable non-synonymous sites in the alignment -LRB- that is , P N D N $ 4 ; IPS -RRB- as well as a set with at least two variable non-synonymous sites that are informative only about negative selection -LRB- n 6,033 ; INS -RRB- . Loci with less than four amino acid variable sites in the alignment can not be informative about positive selection , and loci with 0 or 1 amino acid variable sites can not inform a hypothesis regarding weak negative selection . The reason for this is that we make a conservative assumption that some -LRB- unknown -RRB- fraction of mutations are lethal . While inferences of selection based only on variable sites in the alignment reduces power , it does not require a priori assumptions about the distribution of selective effects among moderately to highly deleterious mutations . Statistics . To maximize our power to identify non-neutrally evolving loci , we pool genomic polymorphism and divergence data using the approach of ref . 9 who used a Poisson random field setting4 for bayesian population genetic inference of selection . The chief advantage of the mkprf method is an increase in power to detect selection without an increase in type I error as long as per locus mutation rates are low9 . One slight modification of the model used here is that we set a gaussian prior distribution for g i with mean 0 and an arbitrary standard deviation of 8 -LRB- as opposed to a hierarchical model as in ref . 9 -RRB- . This simplification is made so that the marginal posterior distributions of the selection coefficients are conditionally independent of one another and can be pooled for further analysis . Full details of the likelihood function used here can be found in Supplementary Data 1 . Briefly , our method estimates posterior distributions of genomic parameters such as the species divergence time between humans and chimpanzees -LRB- t number of generations/2N e , where N e is the effective population size of humans -RRB- using all synonymous SNPs and synonymous fixed differences in the sample . Conditional on genomic parameters , posterior distributions for individual gene parameters are informed only by the non-synonymous cell entries in a conventional McDonald Kreitman table -LRB- that is , P N and D N -RRB- . Evidence in our model for non-neutral evolution at a particular gene comes from the equal tail credibility intervals -LRB- a form of bayesian confidence intervals -RRB- on the selection parameter for the locus . That is , if the whole of the CI for g i is above 0 , there is strong evidence that the locus i has an excess of amino acid fixed differences given the observed level of amino acid variability within humans at the gene , and is therefore likely to be rapidly evolving due to positive darwinian selection . Similarly , if the whole of the CI for g i is below 0 , there are too few fixed amino acid differences in gene i ; this we interpret as evidence that the locus is subject to negative selection , and that many amino acid polymorphisms at the locus are weakly deleterious . An alternative explanation is that the locus is subject to strong balancing selection -LRB- or overdominance -RRB- that prevents fixation of non-lethal amino acid mutations between species . Recent analytical and simulation work22 ,23 suggests that over-dominance needs to be very strong for the McDonald Kreitman cell entries to deviate in the direction of excess amino acid variation relative to amino acid fixed differences -LRB- such as in self-incompatibility alleles24 -RRB- . In fact , under weak over-dominance , the McDonald Kreitman cell entries show the same deviation -LRB- that is , an excess of amino acid fixed differences relative to polymorphism -RRB- as under positive selection23 . Received 24 April ; accepted 14 September 2005 . 1 . 2 . 3 . 4 . 5 . 6 . 7 . Kimura , M . The Neutral Theory of Molecular Evolution -LRB- Cambridge Univ. . Press , Cambridge , 1983 -RRB- . Hudson , R. R. , Kreitman , M. & Aguade , M . A test of neutral molecular evolution based on nucleotide data . Genetics 116 , 153 -159 -LRB- 1987 -RRB- . McDonald , J. H. & Kreitman , M. Adaptive protein evolution at the Adh locus in Drosophila . Nature 351 , 652 -654 -LRB- 1991 -RRB- . Sawyer , S. A. & Hartl , D. L. Population genetics of polymorphism and divergence . Genetics 132 , 1161 -1176 -LRB- 1992 -RRB- . Eyre-Walker , A. & Keightley , P. D. High genomic deleterious mutation rates in hominids . Nature 397 , 344 -347 -LRB- 1999 -RRB- . Fay , J. C. , Wyckoff , G. J. & Wu , C. I. Testing the neutral theory of molecular evolution with genomic data from Drosophila . Nature 415 , 1024 -1026 -LRB- 2002 -RRB- . Sawyer , S. A. , Kulathinal , R. J. , Bustamante , C. D. & Hartl , D. L. Bayesian analysis suggests that most amino acid replacements in Drosophila are driven by positive selection . J. Mol . Evol . 57 -LRB- suppl . 1 -RRB- , S154 - S164 -LRB- 2003 -RRB- . Smith , N. G. & Eyre-Walker , A. Adaptive protein evolution in Drosophila . Nature 415 , 1022 -1024 -LRB- 2002 -RRB- . Bustamante , C. D. et al. . The cost of inbreeding in Arabidopsis . Nature 416 , 531 -534 -LRB- 2002 -RRB- . Nordborg , M. et al. . The pattern of polymorphism in Arabidopsis thaliana . PLoS Biol . 3 , e196 -LRB- 2005 -RRB- . Halushka , M. K. et al. . Patterns of single-nucleotide polymorphisms in candidate genes for blood-pressure homeostasis . Nature Genet . 22 , 239 -247 -LRB- 1999 -RRB- . Cargill , M. et al. . Characterization of single-nucleotide polymorphisms in coding regions of human genes . Nature Genet . 22 , 231 -238 -LRB- 1999 -RRB- . Stephens , J. C. et al. . Haplotype variation and linkage disequilibrium in 313 human genes . Science 293 , 489 -493 -LRB- 2001 -RRB- . Livingston , R. J. et al. . Pattern of sequence variation across 213 environmental response genes . Genome Res . 14 , 1821 -1831 -LRB- 2004 -RRB- . Sunyaev , S. et al. . Prediction of deleterious human alleles . Hum . Mol . Genet . 10 , 591 -597 -LRB- 2001 -RRB- . Williamson , S. et al. . Simultaneous inference of selection and population growth from patterns of variation in the human genome . Proc . Natl Acad . Sci . USA 102 , 7882 -7887 -LRB- 2005 -RRB- . Barrier , M. , Bustamante , C. D. , Yu , J. & Purugganan , M. D. Selection on rapidly evolving proteins in the Arabidopsis genome . Genetics 163 , 723 -733 -LRB- 2003 -RRB- . Nielsen , R. et al. . A scan for positively selected genes in the genomes of humans and chimpanzees . PLoS Biol . 6 , e170 -LRB- 2005 -RRB- . Manunta , P. et al. . Alpha-adducin polymorphisms and renal sodium handling in essential hypertensive patients . Kidney Int . 53 , 1471 -1478 -LRB- 1998 -RRB- . Morrison , A. C. , Bray , M. S. , Folsom , A. R. & Boerwinkle , E. ADD1 460W allele associated with cardiovascular disease in hypertensive individuals . Hypertension 39 , 1053 -1057 -LRB- 2002 -RRB- . Kent , W. J. BLAT - the BLAST-like alignment tool . Genome Res . 12 , 656 -664 -LRB- 2002 -RRB- . Weinreich , D. M. & Rand , D. M. Contrasting patterns of nonneutral evolution in proteins encoded in nuclear and mitochondrial genomes . Genetics 156 , 385 -399 -LRB- 2000 -RRB- . Williamson , S. , Fledel-Alon , A. & Bustamante , C. D. Population genetics of polymorphism and divergence for diploid selection models with arbitrary dominance . Genetics 168 , 463 -475 -LRB- 2004 -RRB- . Ioerger , T. R. , Clark , A. G. & Kao , T. H. Polymorphism at the self-incompatibility locus in Solanaceae predates speciation . Proc . Natl Acad . Sci . USA 87 , 9732 -9735 -LRB- 1990 -RRB- . 8 . 9 . 10 . 11 . 12 . 13 . 14 . 15 . 16 . 17 . 18 . 19 . 20 . 21 . 22 . 23 . 24 . Supplementary Information is linked to the online version of the paper at www.nature.com/nature . Acknowledgements We thank K. Thornton and B. Payseur for suggestions during the analysis . Some of the analysis was supported by NIH grants to C.D.B. , R.N. and A.G.C. . We also acknowledge the help of J. Pillardy and the Cornell University Theory Center Computational Biology Service Unit . Author Contributions S.G. , D.M.T. , D.C. , T.J.W. , J.J.S. , M.D.A. and M.C. conceived , designed and performed the experiments . C.D.B. , A.F.-A. , A.G.C. , S.W. , R.N. and M.J.H. analysed the data . Author Information Accession numbers for the SNP markers analysed in this study are dbSNP numbers ss48401226 ss48429818 and ss48429821 ss48431291 , submitted under the handle APPLERA_GI . Reprints and permissions information is available at npg.nature.com/reprintsandpermissions . The authors declare no competing financial interests . Correspondence and requests for materials should be addressed to C.D.B. -LRB- cdb28@cornell.edu -RRB- . 1157 2005 Nature Publishing Group

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O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O B O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

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