Article

Chimpanzee polymorphisms

The draft sequence of the chimpanzee genome also facilitates genome-wide studies of genetic diversity among chimpanzees, extending recent work^{28, 29, 30, 31}. We sequenced and analysed sequence reads from the primary donor, four other West African and three central African chimpanzees (Pan troglodytes troglodytes) to discover polymorphic positions within and between these individuals (Supplementary Table S17).

A total of 1.66 million high-quality single-nucleotide polymorphisms (SNPs) were identified, of which 1.01 million are heterozygous within the primary donor, Clint. Heterozygosity rates were estimated to be 9.5 10^-4 for Clint, 8.0 10^-4 among West African chimpanzees and 17.6 10^-4 among central African chimpanzees, with the variation between West and central African chimpanzees being 19.0 10^-4. The diversity in West African chimpanzees is similar to that seen for human populations³², whereas the level for central African chimpanzees is roughly twice as high.

The observed heterozygosity in Clint is broadly consistent with West African origin, although there are a small number of regions of distinctly higher heterozygosity. These may reflect a small amount of central African ancestry, but more likely reflect undetected regions of segmental duplications present only in chimpanzees.

Nucleotide divergence

Best reciprocal nucleotide-level alignments of the chimpanzee and human genomes cover 2.4 gigabases (Gb) of high-quality sequence, including 89 Mb from chromosome X and 7.5 Mb from chromosome Y.

Genome-wide rates. We calculate the genome-wide nucleotide divergence between human and chimpanzee to be 1.23%, confirming recent results from more limited studies^{12, 33, 34}. The differences between one copy of the human genome and one copy of the chimpanzee genome include both the sites of fixed divergence between the species and some polymorphic sites within each species. By correcting for the estimated coalescence times in the human and chimpanzee populations (see Supplementary Information 'Genome evolution'), we estimate that polymorphism accounts for 14–22% of the observed divergence rate and thus that the fixed divergence is 1.06% or less.

Nucleotide divergence rates are not constant across the genome, as has been seen in comparisons of the human and murid genomes^{16, 17, 24, 35, 36}. The average divergence in 1-Mb segments fluctuates with a standard deviation of 0.25% (coefficient of variation = 0.20), which is much greater than the 0.02% expected assuming a uniform divergence rate (Fig. 1a; see also Supplementary Fig. S1).

Figure 1: Human-chimpanzee divergence in 1-Mb segments across the genome.

a, Distribution of divergence of the autosomes (blue), the X chromosome (red) and the Y chromosome (green). b, Distribution of variation by chromosome, shown as a box plot. The edges of the box correspond to quartiles; the notches to the standard error of the median; and the vertical bars to the range. The X and Y chromosomes are clear outliers, but there is also high local variation within each of the autosomes.

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Regional variation in divergence could reflect local variation in either mutation rate or other evolutionary forces. Among the latter, one important force is genetic drift, which can cause substantial differences in divergence time across loci when comparing closely related species, as the divergence time for orthologues is the sum of two terms: t₁, the time since speciation, and t₂, the coalescence time for orthologues within the common ancestral population³⁷. Whereas t₁ is constant across loci (6–7 million years³⁸), t₂ is a random variable that fluctuates across loci (with a mean that depends on population size and here may be on the order of 1–2 million years³⁹). However, because of historical recombination, the characteristic scale of such fluctuations will be on the order of tens of kilobases, which is too small to account for the variation observed for 1-Mb regions⁴⁰ (see Supplementary Information 'Genome evolution'). Other potential evolutionary forces are positive or negative selection. Although it is more difficult to quantify the expected contributions of selection in the ancestral population^{41, 42, 43}, it is clear that the effects would have to be very strong to explain the large-scale variation observed across mammalian genomes^{16, 44}. There is tentative evidence from in-depth analysis of divergence and diversity that natural selection is not the major contributor to the large-scale patterns of genetic variability in humans^{45, 46, 47}. For these reasons, we suggest that the large-scale variation in the human–chimpanzee divergence rate primarily reflects regional variation in mutation rate.

Chromosomal variation in divergence rate. Variation in divergence rate is evident even at the level of whole chromosomes (Fig. 1b). The most striking outliers are the sex chromosomes, with a mean divergence of 1.9% for chromosome Y and 0.94% for chromosome X. The likely explanation is a higher mutation rate in the male compared with female germ line⁴⁸. Indeed, the ratio of the male/female mutation rates (denoted ) can be estimated by comparing the divergence rates among the sex chromosomes and the autosomes and correcting for ancestral polymorphism as a function of population size of the most recent common ancestor (MRCA; see Supplementary Information 'Genome evolution'). Estimates for range from 3 to 6, depending on the chromosomes compared and the assumed ancestral population size (Supplementary Table S18). This is significantly higher than recent estimates of for the murids (1.9) (ref. ref. 17) and resolves a recent controversy based on smaller data sets^{12, 24, 49, 50}.

The higher mutation rate in the male germ line is generally attributed to the 5–6-fold higher number of cell divisions undergone by male germ cells⁴⁸. We reasoned that this would affect mutations resulting from DNA replication errors (the rate should scale with the number of cell divisions) but not mutations resulting from DNA damage such as deamination of methyl CpG to TpG (the rate should scale with time). Accordingly, we calculated separately for CpG sites, obtaining a value of 2 from the comparison of rates between autosomes and chromosome X. This intermediate value is a composite of the rates of CpG loss and gain, and is consistent with roughly equal rates of CpG to TpG transitions in the male and female germ line^{51, 52}.

Significant variation in divergence rates is also seen among autosomes (Fig. 1b; P < 3 10^-15, Kruskal–Wallis test over 1-Mb windows), confirming earlier observations based on low-coverage WGS sampling¹². Additional factors thus influence the rate of divergence between chimpanzee and human chromosomes. These factors are likely to act at length scales significantly shorter than a chromosome, because the standard deviation across autosomes (0.21%) is comparable to the standard deviation seen in 1-Mb windows across the genome (0.13–0.35%). We therefore sought to understand local factors that contribute to variation in divergence rate.

Contribution of CpG dinucleotides. Sites containing CpG dinucleotides in either species show a substantially elevated divergence rate of 15.2% per base; they account for 25.2% of all substitutions while constituting only 2.1% of all aligned bases. The divergence at CpG sites represents both the loss of ancestral CpGs and the creation of new CpGs. The former process is known to occur at a rapid rate per base due to frequent methylation of cytosines in a CpG context and their frequent deamination^{53, 54}, whereas the latter process probably proceeds at a rate more typical of other nucleotide substitutions. Assuming that loss and creation of CpG sites are close to equilibrium, the mutation rate for bases in a CpG dinucleotide must be 10–12-fold higher than for other bases (see Supplementary Information 'Genome evolution' and ref. 51).

Because of the high rate of CpG substitutions, regional divergence rates would be expected to correlate with regional CpG density. CpG density indeed varies across 1-Mb windows (mean = 2.1%, coefficient of variation = 0.44 compared with 0.0093 expected under a Poisson distribution), but only explains 4% of the divergence rate variance. In fact, regional CpG and non-CpG divergence is highly correlated (r = 0.88; Supplementary Fig. S2), suggesting that higher-order effects modulate the rates of two very different mutation processes (see also ref. 47).

Increased divergence in distal regions. The most striking regional pattern is a consistent increase in divergence towards the ends of most chromosomes (Fig. 2). The terminal 10 Mb of chromosomes (including distal regions and proximal regions of acrocentric chromosomes) averages 15% higher divergence than the rest of the genome (Mann–Whitney U-test; P < 10^-30), with a sharp increase towards the telomeres. The phenomenon correlates better with physical distance than relative position along the chromosomes and may partially explain why smaller chromosomes tend to have higher divergence (Supplementary Fig. S3; see also ref. 15). These observations suggest that large-scale chromosomal structure, directly or indirectly, influences regional divergence patterns. The cause of this effect is unclear, but these regions (15% of the genome) are notable in having high local recombination rate, high gene density and high G + C content.

Figure 2: Regional variation in divergence rates.

Human–chimpanzee divergence (blue), G + C content (green) and human recombination rates¹⁷³ (red) in sliding 1-Mb windows for human and chimpanzee chromosome 1. Divergence and G + C content are noticeably elevated near the 1p telomere, a trend that holds for most subtelomeric regions (see text). Internally on the chromosome, regions of low G + C content and high divergence often correspond to the dark G bands.

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Correlation with chromosome banding. Another interesting pattern is that divergence increases with the intensity of Giemsa staining in cytogenetically defined chromosome bands, with the regions corresponding to Giemsa dark bands (G bands) showing 10% higher divergence than the genome-wide average (Mann–Whitney U-test; P < 10^-14) (see Fig. 2). In contrast to terminal regions, these regions (17% of the genome) tend to be gene poor, (G + C)-poor and low in recombination^{55, 56}. The elevated divergence seen in two such different types of regions suggests that multiple mechanisms are at work, and that no single known factor, such as G + C content or recombination rate, is an adequate predictor of regional variation in the mammalian genome by itself (Fig. 3). Elucidation of the relative contributions of these and other mechanisms will be important for formulating accurate models for population genetics, natural selection, divergence times and the evolution of genome-wide sequence composition⁵⁷.

Figure 3: Divergence rates versus G + C content for 1-Mb segments across the autosomes.

Conditional on recombination rate, the relationship between divergence and G + C content varies. In regions with recombination rates less than 0.8 cM Mb^-1 (blue), there is an inverse relationship, where high divergence regions tend to be (G + C)-poor and low divergence regions tend to be (G + C)-rich. In regions with recombination rates greater than 2.0 cM Mb^-1, whether within 10 Mb (red) or proximal (green) of chromosome ends, both divergence and G + C content are uniformly high.

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Correlation with regional variation in the murid genome. Given that sequence divergence shows regional variation in both hominids (human–chimpanzee) and murids (mouse–rat), we asked whether the regional rates are positively correlated between orthologous regions. Such a correlation would suggest that the divergence rate is driven, in part, by factors that have been conserved over the 75 million years since rodents, humans and apes shared a common ancestor. Comparative analysis of the human and murid genomes has suggested such a correlation^{58, 59, 60}, but the chimpanzee sequence provides a direct opportunity to compare independent evolutionary processes between two mammalian clades.

We compared the local divergence rates in hominids and murids across major orthologous segments in the respective genomes (Fig. 4). For orthologous segments that are non-distal in both hominids and murids, there is a strong correlation between the divergence rates (r = 0.5, P < 10^-11). In contrast, orthologous segments that are centred within 10 Mb of a hominid telomere have disproportionately high divergence rates and G + C content relative to the murids (Mann–Whitney U-test; P < 10^-11 and P < 10^-4), implying that the elevation in these regions is, at least partially, lineage specific. The same general effect is observed (albeit less pronounced) if CpG dinucleotides are excluded (Supplementary Fig. S4). Increased divergence and G + C content might be explained by 'biased gene conversion'⁶¹ due to the high hominid recombination rates in these distal regions. Segments that are distal in murids do not show elevated divergence rates, which is consistent with this model, because the recombination rates of distal regions are not as elevated in mouse and rat⁶².

Figure 4: Disproportionately elevated divergence and G + C content near hominid telomeres.

Scatter plot of the ratio of human–chimpanzee divergence over mouse–rat divergence versus the ratio of human G + C content over mouse G + C content across 199 syntenic blocks for which more than 1 Mb of sequence could be aligned between all four species. Blocks for which the centre is within 10 Mb of a telomere in hominids only (green) or in hominids and murids (magenta), but not in murids only (light blue), show a significant trend towards higher ratios than internal blocks (dark blue). Blocks on the X chromosome (red) tend to show a lower divergence ratio than autosomal blocks, consistent with a smaller difference between autosomal and X divergence in murids than in hominids (lower ).

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Taken together, these observations suggest that sequence divergence rate is influenced by both conserved factors (stable across mammalian evolution) and lineage-specific factors (such as proximity to the telomere or recombination rate, which may change with chromosomal rearrangements).

Insertions and deletions

We next studied the indel events that have occurred in the human and chimpanzee lineages by aligning the genome sequences to identify length differences. We will refer below to all events as insertions relative to the other genome, although they may represent insertions or deletions relative to the genome of the common ancestor.

The observable insertions fall into two classes: (1) 'completely covered' insertions, occurring within continuous sequence in both species; and (2) 'incompletely covered' insertions, occurring within sequence containing one or more gaps in the chimpanzee, but revealed by a clear discrepancy between the species in sequence length. Different methods are needed for reliable identification of modest-sized insertions (1 base to 15 kb) and large insertions (> 15 kb), with the latter only being reliably identifiable in the human genome (see Supplementary Information 'Genome evolution').

The analysis of modest-sized insertions reveals 32 Mb of human-specific sequence and 35 Mb of chimpanzee-specific sequence, contained in 5 million events in each species (Supplementary Information 'Genome evolution' and Supplementary Fig. S5). Nearly all of the human insertions are completely covered, whereas only half of the chimpanzee insertions are completely covered. Analysis of the completely covered insertions shows that the vast majority are small (45% of events cover only 1 base pair (bp), 96% are <20 bp and 98.6% are <80 bp), but that the largest few contain most of the sequence (with the 70,000 indels larger than 80 bp comprising 73% of the affected base pairs) (Fig. 5). The latter indels >80 bp fall into three categories: (1) about one-quarter are newly inserted transposable elements; (2) more than one-third are due to microsatellite and satellite sequences; (3) and the remainder are assumed to be mostly deletions in the other genome.

Figure 5: Length distribution of small indel events, as determined using bounded sequence gaps.

Sequences present in chimpanzee but not in human (blue) or present in human but not in chimpanzee (red) are shown. The prominent spike around 300 nucleotides corresponds to SINE insertion events. Most of the indels are smaller than 20 bp, but larger indels account for the bulk of lineage-specific sequence in the two genomes.

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The analysis of larger insertions (> 15 kb) identified 163 human regions containing 8.3 Mb of human-specific sequence in total (Fig. 6). These cases include 34 regions that involve exons from known genes, which are discussed in a subsequent section. Although we have no direct measure of large insertions in the chimpanzee genome, it appears likely that the situation is similar.

Figure 6: Length distribution of large indel events (> 15 kb), as determined using paired-end sequences from chimpanzee mapped against the human genome.

Both the total number of candidate human insertions/chimpanzee deletions (blue) and the number of bases altered (red) are shown.

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On the basis of this analysis, we estimate that the human and chimpanzee genomes each contain 40–45 Mb of species-specific euchromatic sequence, and the indel differences between the genomes thus total 90 Mb. This difference corresponds to 3% of both genomes and dwarfs the 1.23% difference resulting from nucleotide substitutions; this confirms and extends several recent studies^{63, 64, 65, 66, 67}. Of course, the number of indel events is far fewer than the number of substitution events (5 million compared with 35 million, respectively).

Transposable element insertions

We next used the catalogue of lineage-specific transposable element copies to compare the activity of transposons in the human and chimpanzee lineages (Table 2).

Table 2: Transposable element activity in human and chimpanzee lineages

Full table

Endogenous retroviruses. Endogenous retroviruses (ERVs) have become all but extinct in the human lineage, with only a single retrovirus (human endogenous retrovirus K (HERV-K)) still active²⁴. HERV-K was found to be active in both lineages, with at least 73 human-specific insertions (7 full length and 66 solo long terminal repeats (LTRs)) and at least 45 chimpanzee-specific insertions (1 full length and 44 solo LTRs). A few other ERV classes persisted in the human genome beyond the human–chimpanzee split, leaving 9 human-specific insertions (all solo LTRs, including five HERV9 elements) before dying out.

Against this background, it was surprising to find that the chimpanzee genome has two active retroviral elements (PtERV1 and PtERV2) that are unlike any older elements in either genome; these must have been introduced by infection of the chimpanzee germ line. The smaller family (PtERV2) has only a few dozen copies, which nonetheless represent multiple (5–8) invasions, because the sequence differences among reconstructed subfamilies are too great (8%) to have arisen by mutation since divergence from human. It is closely related to a baboon endogenous retrovirus (BaEV, 88% ORF2 product identity) and a feline endogenous virus (ECE-1, 86% ORF2 product identity). The larger family (PtERV1) is more homogeneous and has over 200 copies. Whereas older ERVs, like HERV-K, are primarily represented by solo LTRs resulting from LTR–LTR recombination, more than half of the PtERV1 copies are still full length, probably reflecting the young age of the elements. PtERV1-like elements are present in the rhesus monkey, olive baboon and African great apes but not in human, orang-utan or gibbon, suggesting separate germline invasions in these species⁶⁸.

Higher Alu activity in humans. SINE (Alu) elements have been threefold more active in humans than chimpanzee (7,000 compared with 2,300 lineage-specific copies in the aligned portion), refining the rather broad range (2–7-fold) estimated in smaller studies^{13, 67, 69}. Most chimpanzee-specific elements belong to a subfamily (AluYc1) that is very similar to the source gene in the common ancestor. By contrast, most human-specific Alu elements belong to two new subfamilies (AluYa5 and AluYb8) that have evolved since the chimpanzee–human divergence and differ substantially from the ancestral source gene⁶⁹. It seems likely that the resurgence of Alu elements in humans is due to these potent new source genes. However, based on an examination of available finished sequence, the baboon shows a 1.6-fold higher Alu activity relative to human new insertions, suggesting that there may also have been a general decline in activity in the chimpanzee⁶⁷.

Some of the human-specific Alu elements are highly diverged (92 with >5% divergence), which would seem to suggest that they are much older than the human–chimpanzee split. Possible explanations include: gene conversion by nearby older elements; processed pseudogenes arising from a spurious transcription of an older element; precise excision from the chimpanzee genome; or high local mutation rate. In any case, the presence of such anomalies suggests that caution is warranted in the use of single-repeat elements as homoplasy-free phylogenetic markers.

New Alu elements target (A + T)-rich DNA in human and chimpanzee genomes. Older SINE elements are preferentially found in gene-rich, (G + C)-rich regions, whereas younger SINE elements are found in gene-poor, (A + T)-rich regions where long interspersed element (LINE)-1 (L1) copies also accumulate^{24, 70}. The latter distribution is consistent with the fact that Alu retrotransposition is mediated by L1 (ref. 71). Murid genomes revealed no change in SINE distribution with age¹⁷.

The human pattern might reflect either preferential retention of SINEs in (G + C)-rich regions, due to selection or mutation bias, or a recent change in Alu insertion preferences. With the availability of the chimpanzee genome, it is possible to classify the youngest Alu copies more accurately and thus begin to distinguish these possibilities.

Analysis shows that lineage-specific SINEs in both human and chimpanzee are biased towards (A + T)-rich regions, as opposed to even the most recent copies in the MRCA (Fig. 7). This indicates that SINEs are indeed preferentially retained in (G + C)-rich DNA, but comparison with a more distant primate is required to formally rule out the possibility that the insertion bias of SINEs did not change just before speciation.

Figure 7: Correlation of Alu age and distribution by G + C content.

Alu elements that inserted after human–chimpanzee divergence are densest in the (G + C)-poor regions of the genome (peaking at 36–40% G + C), whereas older copies, common to both genomes, crowd (G + C)-rich regions. The figure is similar to figure 23 of ref. 24, but the use of chimpanzee allows improved separation of young and old elements, leading to a sharper transition in the pattern.

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Equal activity of L1 in both species. The human and chimpanzee genomes both show 2,000 lineage-specific L1 elements, contrary to previous estimates based on small samples that L1 activity is 2–3-fold higher in chimpanzee⁷².

Transcription from L1 source genes can sometimes continue into 3' flanking regions, which can then be co-transposed^{73, 74}. Human–chimpanzee comparison revealed that 15% of the species-specific insertions appear to have carried with them at least 50 bp of flanking sequence (followed by a poly(A) tail and a target site duplication). In principle, incomplete reverse transcription could result in insertions of the flanking sequence only (without any L1 sequence), mobilizing gene elements such as exons, but we found no evidence of this.

Retrotransposed gene copies. The L1 machinery also mediates retrotransposition of host messenger RNAs, resulting in many intronless (processed) pseudogenes in the human genome^{75, 76, 77}. We identified 163 lineage-specific retrotransposed gene copies in human and 246 in chimpanzee (Supplementary Table S19). Correcting for incomplete sequence coverage of the chimpanzee genome, we estimate that there are 200 and 300 processed gene copies in human and chimpanzee, respectively. Processed genes thus appear to have arisen at a rate of 50 per million years since the divergence of human and chimpanzee; this is lower than the estimated rate for early primate evolution⁷⁵, perhaps reflecting the overall decrease in L1 activity. As expected⁷⁸, ribosomal protein genes constitute the largest class in both species. The second largest class in chimpanzee corresponds to zinc finger C2H2 genes, which are not a major class in the human genome.

The retrotransposon SVA and distribution of CpG islands by transposable elements. The third most active element since speciation has been SVA, which created about 1,000 copies in each lineage. SVA is a composite element (1.5–2.5 kb) consisting of two Alu fragments, a tandem repeat and a region apparently derived from the 3' end of a HERV-K transcript; it is probably mobilized by L1 (refs 79, 80). This element is of particular interest because each copy carries a sequence that satisfies the definition of a CpG island⁸¹ and contains potential transcription factor binding sites; the dispersion of 1,000 SVA copies could therefore be a source of regulatory differences between chimpanzee and human (Supplementary Table S20). At least three human genes contain SVA insertions near their promoters (Supplementary Table S21), one of which has been found to be differentially expressed between the two species^{82, 83}, but additional investigations will be required to determine whether the SVA insertion directly caused this difference.

Homologous recombination between interspersed repeats. Human–chimpanzee comparison also makes it possible to study homologous recombination between nearby repeat elements as a source of genomic deletions. We found 612 deletions (totalling 2 Mb) in the human genome that appear to have resulted from recombination between two nearby Alu elements present in the common ancestor; there are 914 such events in the chimpanzee genome. (The events are not biased to (A + T)-rich DNA and thus would not explain the preferential loss of Alu elements in such regions discussed above.) Similarly, we found 26 and 48 instances involving adjacent L1 copies and 8 and 22 instances involving retroviral LTRs in human and chimpanzee, respectively. None of the repeat-mediated deletions removed an orthologous exon of a known human gene in chimpanzee.

The genome comparison allows one to estimate the dependency of homologous recombination on divergence and distance. Homologous recombination seems to occur between quite (> 25%) diverged copies (Fig. 8), whereas the number of recombination events (n) varies inversely with the distance (d, in bases) between the copies (as n 6 10⁶ d^-1.7; r² = 0.9).

Figure 8: Dependency of homologous recombination between Alu elements on divergence and distance.

a, Whereas homologous recombination occurs between quite divergent (Smith–Waterman score <1,000), closely spaced copies, more distant recombination seems to favour a better match between the recombining repeats. b, The frequency of Alu–Alu-mediated recombination falls markedly as a function of distance between the recombining copies. The first three points (magenta) involve recombination between left or right arms of one Alu inserted into another. The high number of occurrences at a distance of 300–400 nucleotides is due to the preference of integration in the A-rich tail; exclusion of this point does not change the parameters of the equation.

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Large-scale rearrangements

Finally, we examined the chimpanzee genome sequence for information about large-scale genomic alterations. Cytogenetic studies have shown that human and chimpanzee chromosomes differ by one chromosomal fusion, at least nine pericentric inversions, and in the content of constitutive heterochromatin⁸⁴. Human chromosome 2 resulted from a fusion of two ancestral chromosomes that remained separate in the chimpanzee lineage (chromosomes 2A and 2B in the revised nomenclature¹⁸, formerly chimpanzee chromosomes 12 and 13); the precise fusion point has been mapped and its duplication structure described in detail^{85, 86}. In accord with this, alignment of the human and chimpanzee genome sequences shows a break in continuity at this point.

We searched the chimpanzee genome sequence for the precise locations of the 18 breakpoints corresponding to the 9 pericentric inversions (Supplementary Table S22). By mapping paired-end sequences from chimpanzee large insert clones to the human genome, we were able to identify 13 of the breakpoints within the assembly from discordant end alignments. The positions of five breakpoints (on chromosomes 4, 5 and 12) were tested by fluorescence in situ hybridization (FISH) analysis and all were confirmed. Also, the positions of three previously mapped inversion breakpoints (on chromosomes 15 and 18) matched closely those found in the assembly^{87, 88}. The paired-end analysis works well in regions of unique sequence, which constitute the bulk of the genome, but is less effective in regions of recent duplication owing to ambiguities in mapping of the paired-end sequences. Beyond the known inversions, we also found suggestive evidence of many additional smaller inversions, as well as older segmental duplications (< 98% identity; Supplementary Fig. S6). However, both smaller inversions and more recent segmental duplications will require further investigations.

Average rates of evolution

To assess the rate of evolution for each gene, we estimated K_A, the number of coding base substitutions that result in amino acid change as a fraction of all such possible sites (the non-synonymous substitution rate). Because the background mutation rate varies across the genome, it is crucial to normalize K_A for comparisons between genes. A striking illustration of this variation is the fact that the mean K_A is 37% higher in the rapidly diverging distal 10 Mb of chromosomes than in the more proximal regions. Classically, the background rate is estimated by K_S, the synonymous substitution rate (coding base substitutions that, because of codon redundancy, do not result in amino acid change). Because a typical gene has only a few synonymous changes between humans and chimpanzees, and not infrequently is zero, we exploited the genome sequence to estimate the local intergenic/intronic substitution rate, K_I, where appropriate. K_A and K_S were also estimated for each lineage separately using mouse and rat as outgroups (Fig. 9).

Figure 9: Human–chimpanzee–mouse–rat tree with branch-specific K_A/K_S () values.

a, Evolutionary tree. The branch lengths are proportional to the absolute rates of amino acid divergence. b, Maximum-likelihood estimates of the rates of evolution in protein-coding genes for humans, chimpanzees, mice and rats. In the text, _hominid is the K_A/K_S of the combined human and chimpanzee branches and _murid of the combined mouse and rat branches. The slight difference between _human and _chimpanzee is not statistically significant; masking of some heterozygous bases in the chimpanzee sequence may contribute to the observed difference (see Supplementary Information 'Gene evolution').

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The K_A/K_S ratio is a classical measure of the overall evolutionary constraint on a gene, where K_A/K_S1 indicates that a substantial proportion of amino acid changes must have been eliminated by purifying selection. Under the assumption that synonymous substitutions are neutral, K_A/K_S > 1 implies, but is not a necessary condition for, adaptive or positive selection. The K_A/K_I ratio has the same interpretation. The ratios will sometimes be denoted below by with an appropriate subscript (for example, _human) to indicate the branch of the evolutionary tree under study.

Evolutionary constraint on amino acid sites within the hominid lineage. Overall, human and chimpanzee genes are extremely similar, with the encoded proteins identical in the two species in 29% of cases. The median number of non-synonymous and synonymous substitutions per gene are two and three, respectively. About 5% of the proteins show in-frame indels, but these tend to be small (median = 1 codon) and to occur in regions of repeated sequence. The close similarity of human and chimpanzee genes necessarily limits the ability to make strong inferences about individual genes, but there is abundant data to study important sets of genes.

The K_A/K_S ratio for the human–chimpanzee lineage (_hominid) is 0.23. The value is much lower than some recent estimates based on limited sequence data (ranging as high as 0.63 (ref. 7)), but is consistent with an estimate (0.22) from random expressed-sequence-tag (EST) sequencing⁴⁵. Similarly, K_A/K_I was also estimated as 0.23.

Under the assumption that synonymous mutations are selectively neutral, the results imply that 77% of amino acid alterations in hominid genes are sufficiently deleterious as to be eliminated by natural selection. Because synonymous mutations are not entirely neutral (see below), the actual proportion of amino acid alterations with deleterious consequences may be higher. Consistent with previous studies⁸, we find that K_A/K_S of human polymorphisms with frequencies up to 15% is significantly higher than that of human–chimpanzee differences and more common polymorphisms (Table 3), implying that at least 25% of the deleterious amino acid alterations may often attain readily detectable frequencies and thus contribute significantly to the human genetic load.

Table 3: Comparison of K_A/K_S for divergence and human diversity

Full table

Evolutionary constraint on synonymous sites within hominid lineage. We next explored the evolutionary constraints on synonymous sites, specifically fourfold degenerate sites. Because such sites have no effect on the encoded protein, they are often considered to be selectively neutral in mammals.

We re-examined this assumption by comparing the divergence at fourfold degenerate sites with the divergence at nearby intronic sites. Although overall divergence rates are very similar at fourfold degenerate and intronic sites, direct comparison is misleading because the former have a higher frequency of the highly mutable CpG dinucleotides (9% compared with 2%). When CpG and non-CpG sites are considered separately, we find that both CpG sites and non-CpG sites show markedly lower divergence in exonic synonymous sites than in introns (50% and 30% lower, respectively). This result resolves recent conflicting reports based on limited data sets^{45, 89} by showing that such sites are indeed under constraint.

The constraint does not seem to result from selection on the usage of preferred codons, which has been detected in lower organisms⁹⁰ such as bacteria⁹¹, yeast⁹² and flies⁹³. In fact, divergence at fourfold degenerate sites increases slightly with codon usage bias (Kendall's = 0.097, P < 10^-14). Alternatively, the observed constraint at synonymous sites might reflect 'background selection'—that is, the indirect effect of purifying selection at amino acid sites causing reduced diversity and thereby reduced divergence at closely linked sites⁴². Given the low rate of recombination in hominid genomes (a 1 kb region experiences only 1 crossover per 100,000 generations or 2 million years), such background selection should extend beyond exons to include nearby intronic sites⁹⁴. However, when the divergence rate is plotted relative to exon–intron boundaries, we find that the rate jumps sharply within a short region of 7 bp at the boundary (Fig. 10). This pattern strongly suggests that the action of purifying selection at synonymous sites is direct rather than indirect, suggesting that other signals, for example those involved in splice site selection, may be embedded in the coding sequence and therefore constrain synonymous sites.

Figure 10: Purifying selection on synonymous sites.

Mean divergence around exon boundaries at non-CpG, exonic, fourfold degenerate sites and intronic sites, relative to the closest mRNA splice junction. The divergence rate at exonic, fourfold degenerate sites is significantly lower than at nearby intronic sites (Mann–Whitney U-test; P < 10^-27), suggesting that purifying selection limits the rate of synonymous codon substitutions.

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Comparison with murids. An accurate estimate of K_A/K_S makes it possible to study how evolutionary constraint varies across clades. It was predicted more than 30 years ago⁹⁵ that selection against deleterious mutations would depend on population size, with mutations being strongly selected only if they reduce fitness by s1/4N (where N is effective population size). This would predict that genes would be under stronger purifying selection in murids than hominids, owing to their presumed larger population size. Initial analyses (involving fewer than 50 genes⁹⁶) suggested a strong effect, but the wide variation in estimates of K_A/K_S in hominids^{7, 8, 97} and murids⁹⁸ has complicated this analysis⁴⁵.

Using the large collection of 7,043 orthologous quartets, we calculated mean K_A/K_S values for the various branches of the four-species evolutionary tree (human, chimpanzee, mouse and rat; Fig. 9). The K_A/K_S ratio for hominids is 0.20. (This is slightly lower than the value of 0.23 obtained with all human–chimpanzee orthologues, probably reflecting slightly greater constraint on the class of proteins with clear orthologues across hominids and murids.)

The K_A/K_S ratio is markedly lower for murids than for hominids (_murid 0.13 compared with _hominid 0.20) (Fig. 9). This implies that there is an 35% excess of the amino-acid-changing mutations in the two hominids, relative to the two murids. Excess amino acid divergence may be explained by either increased adaptive evolution or relaxation of evolutionary constraints. As shown in the next section, the latter seems to be the principal explanation.

Relaxed constraints in human evolution. The K_A/K_S ratio can be used to make inferences about the role of positive selection in human evolution^{99, 100}. Because alleles under positive selection spread rapidly through a population, they will be found less frequently as common human polymorphisms than as human–chimpanzee differences⁸. Positive selection can thus be detected by comparing the K_A/K_S ratio for common human polymorphisms with the K_A/K_S ratio for hominid divergence. These ratios have been estimated as _polymorphism 0.20 based on an initial collection of common SNPs in human genes and _divergence 0.34 based on comparison of human and Old World monkey genes⁸. Thus, the proportion of amino acid changes attributable to positive selection was inferred to be 35% (ref. ref. 8). This would imply a huge quantitative role for positive selection in human evolution.

With the availability of extensive data for both human polymorphism and human–chimpanzee divergence, we repeated this analysis (using the same set of genes for both estimates). We find that _polymorphism 0.21–0.23 and _divergence 0.23 are statistically indistinguishable (Table 3). Although some of the amino acid substitutions in human and chimpanzee evolution must surely reflect positive selection, the results indicate that the proportion of changes fixed by positive selection seems to be much lower than the previous estimate⁸. (Because the previous results involved comparison to Old World monkeys, it is possible that they reflect strong positive selection earlier in primate evolution; however, we suspect that they reflect the fact that relatively few genes were studied and that different genes were used to study polymorphism and divergence.)

Relaxed negative selection pressures thus primarily explain the excess amino acid divergence in hominid genes relative to murids. Moreover, because both _human and _chimpanzee are similarly elevated this explanation applies equally to both lineages.

We next sought to study variation in the evolutionary rate of genes within the hominid lineage by searching for unusually high or low levels of constraint for genes and sets of genes.

Rapid evolution in individual genes

We searched for individual genes that have accumulated amino acid substitutions faster than expected given the neutral substitution rate; we considered these genes as potentially being under strong positive selection. A total of 585 of the 13,454 human–chimpanzee orthologues (4.4%) have observed K_A/K_I > 1 (see Supplementary Information 'Gene evolution'). However, given the low divergence, the K_A/K_I statistic has large variance. Simulations show that estimates of K_A/K_I > 1 would be expected to occur simply by chance in at least 263 cases if purifying selection is allowed to act non-uniformly across genes (Supplementary Fig. S7).

Nonetheless, this set of 585 genes may be enriched for genes that are under positive selection. The most extreme outliers include glycophorin C, which mediates one of the Plasmodium falciparum invasion pathways in human erythrocytes¹⁰¹; granulysin, which mediates antimicrobial activity against intracellular pathogens such as Mycobacterium tuberculosis¹⁰²; as well as genes that have previously been shown to be undergoing adaptive evolution, such as the protamines and semenogelins involved in reproduction¹⁰³ and the Mas-related gene family involved in nociception¹⁰⁴. With similar follow-up studies on candidates from this list, one may be able to draw conclusions about positive selection on other individual genes. In subsequent sections, we examine the rate of divergence for sets of related genes with the aim of detecting subtler signals of accelerated evolution.

Variation in evolutionary rate across physically linked genes

We explored how the rate of evolution varies regionally across the genome. Several studies of mammalian gene evolution have noted that the rate of amino acid substitution shows local clustering, with proteins encoded by nearby genes evolving at correlated rates^{16, 105, 106, 107}.

Variation across chromosomes. On the basis of an analysis of 100 genes¹⁰⁸, it was recently reported that the normalized rate of protein evolution is greater on the nine chromosomes that underwent major structural rearrangement during human evolution (chromosomes 1, 2, 5, 9, 12, 15, 16, 17 and 18); it was suggested that such rearrangements led to reduced gene flow and accelerated adaptive evolution. A subsequent study of a collection of chimpanzee ESTs gave contradictory results^{109, 110}. With our larger data set, we re-examined this issue and found no evidence of accelerated evolution on chromosomes with major rearrangements, even if we considered each rearrangement separately (Supplementary Table S25).

Among all hominid chromosomes, the most extreme outlier is chromosome X with a mean K_A/K_I of 0.32. The higher mean seems to reflect a skewed distribution at both high and low values, with the median value (0.17) being more in line with other chromosomes (0.15). The excess of low values may reflect greater purifying selection at some genes, owing to the hemizygosity of chromosome X in males. The excess of high values may reflect increased adaptive selection also resulting from hemizygosity, if a considerable proportion of advantageous alleles are recessive¹¹¹. Interestingly, the higher K_A/K_I value on the X chromosome versus autosomes is largely restricted to genes expressed in testis⁸³.

Variation in local gene clusters. We next searched for genomic neighbourhoods with an unusually high density of rapidly evolving genes. Specifically, we calculated the median K_A/K_I for sliding windows of ten orthologues and identified extreme outliers (P < 0.001 compared to random ordering of genes; see Supplementary Information 'Gene evolution'). A total of 16 such neighbourhoods were found, which greatly exceeds random expectation (Table 4). Repeating the analysis with larger windows (25, 50 and 100 orthologues) did not identify additional rapidly diverging regions.

Table 4: Rapidly diverging gene clusters in human and chimpanzee

Full table

In nearly all cases, the regions contain local clusters of phylogenetically and functionally related genes. The rapid diversification of gene families, postulated by ref. 112, can thus be readily discerned even at the relatively close distance of human–chimpanzee divergence. Most of the clusters are associated with functional categories such as host defence and chemosensation (see below). Examples include the epidermal differentiation complex encoding proteins that help form the cornified layer of the skin barrier (Supplementary Fig. S8), the WAP-domain cluster encoding secreted protease inhibitors with antibacterial activity, and the Siglec cluster encoding CD33-related genes. Rapid evolution in these clusters does not seem to be unique to either human or chimpanzee^{113, 114}.

Variation in evolutionary rate across functionally related genes

We next studied variation in the evolutionary rate of functional categories of genes, based on the Gene Ontology (GO) classification¹¹⁵.

Rapidly and slowly evolving categories within the hominid lineage. We started by searching for sets of functionally related genes with exceptionally high or low constraint in humans and chimpanzees. For each of the 809 categories with at least 20 genes, K_A/K_S was calculated by concatenating the gene sequences. The category-specific ratios were compared to the average across all orthologues to identify extreme outliers using a metric based on the binomial test (Supplementary Information 'Gene evolution' and Supplementary Tables S26–S29). The numbers of observed outliers below a specific threshold (test statistic <0.001) were then compared to the expected distribution of outliers given randomly permuted annotations.

A total of 98 categories showed elevated K_A/K_S ratios at the specified threshold (Table 5). Only 30 would be expected by chance, indicating that most (but not all) of these categories undergo significantly accelerated evolution relative to the genome-wide average (P < 10^-4). The rapidly evolving categories within the hominid lineage are primarily related to immunity and host defence, reproduction, and olfaction, which are the same categories known to be undergoing rapid evolution within the broader mammalian lineage, as well as more distantly related species^{15, 16, 116}. Hominids thus seem to be typical of mammals in this respect (but see below).

Table 5: GO categories with the highest divergence rates in hominids

Full table

A total of 251 categories showed significantly low K_A/K_S ratios (compared with 32 expected by chance; P < 10^-4). These include a wide range of processes including intracellular signalling, metabolism, neurogenesis and synaptic transmission, which are evidently under stronger-than-average purifying selection. More generally, genes expressed in the brain show significantly stronger average constraint than genes expressed in other tissues⁸³.

Differences between hominid and murid lineages. Having found gene categories that show substantial variation in absolute evolutionary rate within hominids, we next examined variation in relative rates between murids and hominids. The K_A/K_S of each of the GO categories are highly correlated between the hominid and murid orthologue pairs, suggesting that the selective pressures acting on particular functional categories have been largely proportional in recent hominid and recent murid evolution (Fig. 11). However, there are several categories with significantly accelerated non-synonymous divergence on each of the lineages, which might represent functions that have undergone lineage-specific positive selection or a lineage-specific relaxation of constraint (Supplementary Information 'Gene evolution' and Supplementary Tables S30–S39).

Figure 11: Hominid and murid K_A/K_S () in GO categories with more than 20 analysed genes.

GO categories with putatively accelerated (test statistic <0.001; see Methods) non-synonymous divergence on the hominid lineages (red) and on the murid lineages (orange) are highlighted. Owing to the hierarchical nature of GO, the categories do not all represent independent data points. A non-redundant list of significant categories is provided in Table 8 and a complete list in Supplementary Table S30.

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A total of 59 categories (compared with 11 expected at random, P < 0.0003) show evidence of accelerated non-synonymous divergence in the murid lineage. These are dominated by functions and processes related to host defence, such as immune response and lymphocyte activation. Examples include genes encoding interleukins and various T-cell surface antigens (Cd4, Cd8, Cd80). Combined with the recent observation that genes involved in host defence have undergone gene family expansion in murids^{16, 17}, this suggests that the immune system has undergone extensive lineage-specific innovation in murids. Additional categories that also show relative acceleration in murids include chromatin-associated proteins and proteins involved in DNA repair. These categories may have similarly undergone stronger adaptive evolution in murids or, alternatively, they may contain fewer sites for mutations with slightly deleterious effects (with the result that the K_A/K_S ratios are less affected by the differences in population size^{96, 117}).

Another 58 categories (versus 14 expected at random, P < 0.0005) show evidence of accelerated evolution in hominids, with the set dominated by genes encoding proteins involved in transport (for example, ion transport), synaptic transmission, spermatogenesis and perception of sound (Table 6). Notably, some outliers include genes with brain-related functions, compatible with a recent finding¹¹⁸. Potential positive selection on spermatogenesis genes in the hominids was also recently noted¹¹⁹. However, as above, it is possible that these categories could have more sites for slightly deleterious mutations and thus be more affected by population size differences. Sequence information from more species and from individuals within species will be necessary to distinguish between the possible explanations.

Table 6: GO categories with accelerated divergence rates in hominids relative to murids

Full table

Differences between the human and chimpanzee lineage. One of the most interesting questions is perhaps whether certain categories have undergone accelerated evolution in humans relative to chimpanzees, because such genes might underlie unique aspects of human evolution.

As was done for hominids and murids above, we compared non-synonymous divergence for each category to search for relative acceleration in either lineage (Fig. 12). Seven categories show signs of accelerated evolution on the human lineage relative to chimpanzee, but this is only slightly more than the four expected at random (P < 0.22). Intriguingly, the single strongest outlier is 'transcription factor activity', with the 348 human genes studied having accumulated 47% more amino acid changes than their chimpanzee orthologues. Genes with accelerated divergence in human include homeotic, forkhead and other transcription factors that have key roles in early development. However, given the small number of changes involved, additional data will be required to confirm this trend. There was no excess of accelerated categories on the chimpanzee lineage.

Figure 12: Human and chimpanzee K_A/K_S () in GO categories with more than 20 analysed genes.

GO categories with putatively accelerated (test statistic <0.001; see Methods) non-synonymous divergence on the human lineage (red) and on the chimpanzee lineage (orange) are highlighted. The variance of these estimates is larger than that seen in the hominid–murid comparison owing to the small number of lineage-specific substitutions. Owing to the hierarchical nature of the GO ontology, the categories do not all represent independent data points. A complete list of categories is provided in Supplementary Table S30.

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We also compared human genes with and without disease associations, including mental retardation, for differences in mutation rate when compared to chimpanzee. Briefly, no significant differences were observed in either the background mutation rate or in the ratio of human-specific changes to chimpanzee-specific amino acid changes (see Supplementary Information 'Gene evolution' and Supplementary Tables S40 and S41).

We thus find minimal evidence of acceleration unique to either the human or chimpanzee lineage across broad functional categories. This is not simply due to general lack of power resulting from the small number of changes since the divergence of human and chimpanzee, because one can detect acceleration of categories in either hominid relative to either murid. For example, 29 accelerated categories versus 9 expected at random (P < 0.02) can be detected on the human lineage, and 40 categories versus 11 expected at random (P < 0.007) on the chimpanzee lineage, relative to mouse. But the outliers are largely the same for both human and chimpanzee, indicating that the fraction of amino acid mutations that have contributed to human- and chimpanzee-specific patterns of evolution must be small relative to the fraction that have contributed to a common hominid and, to a large extent, mammalian pattern of evolution.

It was recently reported¹⁰ that several functional categories are enriched for genes with evidence of positive selection in the human lineage or the chimpanzee lineage, and that these categories are largely different between the two lineages. These results and ours differ in ways that will require further investigation. With the potential exception of some developmental regulators, the categories that ref. 10 reported as showing the strongest enrichment of positive selection in one lineage (including cell adhesion, ion transport and perception of sound) are among those that we show as having accelerated divergence in both human and chimpanzee. This suggests that positive selection and relaxation of constraints may be correlated, or alternatively, that the results of ref. 10 may be enriched for false positives in categories that have experienced particularly strong relaxation of constraints in the hominids. Data from additional primates, as well as advances in analytical methods, will be necessary to distinguish between these alternatives. At present, strong evidence of positive selection unique to the human lineage is thus limited to a handful of genes¹²⁰.

Our analysis above largely omitted genes belonging to large gene families, because gene family expansion makes it difficult to define 1:1:1:1 orthologues across hominids and murids. One of the largest such families, the olfactory receptors, is known to be undergoing rapid divergence in primates. Directed study of these genes in the draft assembly has suggested that more than 100 functional human olfactory receptors are likely to be under no evolutionary constraint¹²¹. Our analysis also omitted the majority of very recently duplicated genes owing to their lower coverage in the current chimpanzee assembly. However, recent human-specific duplications can be readily identified from the finished human genome sequence, and have previously been shown to be highly enriched for the same categories found to have high absolute rates of evolution in 1:1 orthologues here; that is, olfaction, immunity and reproduction²³.

Gene disruptions in human and chimpanzee

Whereas most genes have undergone only subtle substitutions in their amino acid sequence, a few dozen have suffered more marked changes. We found a total of 53 known or predicted human genes that are either deleted entirely (36) or partially (17) in chimpanzee (Supplementary Table S42). We have so far tested and confirmed 15 of these cases by polymerase chain reaction (PCR) or Southern blotting. An additional eight genes have sustained large deletions (> 15 kb) entirely within an intron. Some genes may have been missed in this count owing to limitations of the draft genome sequence. In addition, some genes may have suffered chain termination mutations or altered reading frames in chimpanzee, but accurate identification of these will require higher-quality sequence. The sensitivity of the reciprocal analysis of genes disrupted in human is currently limited by the small number of independently predicted gene models for the chimpanzee. Some of the gene disruptions may be related to interesting biological differences between the species, as discussed below.

Genetic basis for human- and chimpanzee-specific biology

Given the substantial number of neutral mutations, only a small subset of the observed gene differences is likely to be responsible for the key phenotypic changes in morphology, physiology and behavioural complexity between humans and chimpanzees. Determining which differences are in this evolutionarily important subset and inferring their functional consequences will require additional types of evidence, including information from clinical observations and model systems¹²². We describe some novel examples of genetic changes for which plausible functional or physiological consequences can be suggested.

Apoptosis. Mouse and human are known to differ with respect to an important mediator of apoptosis, caspase-12 (refs 123–125). The protein triggers apoptosis in response to perturbed calcium homeostasis in mice, but humans seem to lack this activity owing to several mutations in the orthologous gene that together affect the protein produced by all known splice forms; the mutations include a premature stop codon and a disruption of the SHG box required for enzymatic activity of caspases. By contrast, the chimpanzee gene encodes an intact open reading frame and SHG box, indicating that the functional loss occurred in the human lineage. Intriguingly, loss-of-function mutations in mice confer increased resistance to amyloid-induced neuronal apoptosis without causing obvious developmental or behavioural defects¹²⁶. The loss of function in humans may contribute to the human-specific pathology of Alzheimer's disease, which involves amyloid-induced neurotoxicity and deranged calcium homeostasis.

Inflammatory response. Human and chimpanzee show a notable difference with respect to important mediators of immune and inflammatory responses. Three genes (IL1F7, IL1F8 and ICEBERG) that act in a common pathway involving the caspase-1 gene all appear to be deleted in chimpanzee. ICEBERG is thought to repress caspase-1-mediated generation of pro-inflammatory IL1 cytokines, and its absence in chimpanzee may point to species-specific modulation of the interferon-- and lipopolysaccharide-induced inflammatory response¹²⁷.

Parasite resistance. Similarly, we found that two members of the primate-specific APOL gene cluster (APOL1 and APOL4) have been deleted from the chimpanzee genome. The APOL1 protein is associated with the high-density lipoprotein fraction in serum and has recently been proposed to be the lytic factor responsible for resistance to certain subspecies of Trypanosoma brucei, the parasite that causes human sleeping sickness and the veterinary disease nagana¹²⁸. The loss of the APOL1 gene in chimpanzees could thus explain the observation that human, gorilla and baboon possess the trypanosome lytic factor, whereas the chimpanzee does not¹²⁹.

Sialic acid biology related proteins. Sialic acids are cell-surface sugars that mediate many biological functions¹³⁰. Of 54 genes involved in sialic acid biology, 47 were suitable for analysis. We confirmed and extended findings on several that have undergone human-specific changes, including disruptions, deletions and domain-specific functional changes^{113, 131, 132}. Human- and chimpanzee-specific changes were also found in otherwise evolutionarily conserved sialyl motifs in four sialyl transferases (ST6GAL1, ST6GALNAC3, ST6GALNAC4 and ST8SIA2), suggesting changes in donor and/or acceptor binding¹³⁰. Lineage-specific changes were found in a complement factor H (HF1) sialic acid binding domain associated with human disease¹³³. Human SIGLEC11 has undergone gene conversion with a nearby pseudogene, correlating with acquisition of human-specific brain expression and altered binding properties¹³⁴.

Human disease alleles

We next sought to identify putative functional differences between the species by searching for instances in which a human disease-causing allele appears to be the wild-type allele in the chimpanzee. Starting from 12,164 catalogued disease variants in 1,384 human genes, we identified 16 cases in which the altered sequence in a disease allele matched the chimpanzee sequence, and had plausible support in the literature (Table 7; see also Supplementary Table S43). Upon re-sequencing in seven chimpanzees, 15 cases were confirmed homozygous in all individuals, whereas one (PON1 I102V) appears to be a shared polymorphism (Supplementary Table S44).

Table 7: Candidate human disease variants found in chimpanzee

Full table

Six cases represent de novo human mutations associated with simple mendelian disorders. Similar cases have also been found in comparisons of more distantly related mammals¹³⁵, as well as between insects¹³⁶, and have been interpreted as a consequence of a relatively high rate of compensatory mutations. If compensatory mutations are more likely to be fixed by positive selection than by neutral drift¹³⁶, then the variants identified here might point towards adaptive differences between humans and chimpanzees. For example, the ancestral Thr 29 allele of cationic trypsinogen (PRSS1) causes autosomal dominant pancreatitis in humans¹³⁷, suggesting that the human-specific Asn 29 allele may represent a digestion-related molecular adaptation¹³⁸.

The remaining ten cases represent common human polymorphisms that have been reported to be associated with complex traits, including coronary artery disease and diabetes mellitus. In all of these cases we confirmed that the disease-associated allele in humans is indeed the ancestral allele by showing that it is carried not only by chimpanzee but also by outgroups such as the macaque. These ancestral alleles may thus have become human-specific risk factors due to changes in human physiology or environment, and the polymorphisms may represent ongoing adaptations. For example, PPARG Pro 12 is the wild-type allele in chimpanzee but has been clearly associated with increased risk of type 2 diabetes in human¹³⁹. It is tempting to speculate that this allele may represent an ancestral 'thrifty' genotype¹⁴⁰.

The current results must be interpreted with caution, because few complex disease associations have been firmly established. The fact that the human disease allele is the wild-type allele in chimpanzee may actually indicate that some of the putative associations are spurious and not causal. However, this approach can be expected to become increasingly fruitful as the quality and completeness of the disease mutation databases improve.

Ancestral and derived alleles

Of 7.2 million SNPs mapped to the human genome in the current public database, we could assign the alleles as ancestral or derived in 80% of the cases according to which allele agrees with the chimpanzee genome sequence¹⁴² (see Supplementary Information 'Human population genetics'). For the remaining cases, no assignment could be made because of the following: the orthologous chimpanzee base differed from both human alleles (1.2%); was polymorphic in the chimpanzee sequences obtained (0.4%); or could not be reliably identified with the current draft sequence of the chimpanzee (18.8%), with many of these occurring in repeated or segmentally duplicated sequence. The first two cases arise presumably because a second mutation occurred in the chimpanzee lineage. It should be possible to resolve most of these cases by examining a close outgroup such as gorilla or orang-utan.

Mutations in the chimpanzee may also lead to the erroneous assignment of human alleles as derived alleles. This error rate can be estimated as the probability of a second mutation resulting in the chimpanzee sequence matching the derived allele (see Supplementary Information 'Human population genetics'). The estimated error rate for typical SNPs is 0.5%, owing to the low nucleotide substitution rate. The exceptions are those SNPs for which the human alleles are CpG and TpG and the chimpanzee sequence is TpG. For these, a non-negligible fraction may have arisen by two independent deamination events within an ancestral CpG dinucleotide, which are well-known mutational hotspots⁵¹ (also see above). Human SNPs in a CpG context for which the orthologous chimpanzee sequence is TpG account for 12% of the total, and have an estimated error rate of 9.8%. Across all SNPs, the average error rate, , is thus estimated to be 1.6%.

We compared the distribution of allele frequencies for ancestral and derived alleles using a database of allele frequencies for