Search

Two African apes are the closest living relatives of humans: the chimpanzee (Pan troglodytes) and the bonobo (Pan paniscus). Although they are similar in many respects, bonobos and chimpanzees differ strikingly in key social and sexual behaviours, and for some of these traits they show more similarity with humans than with each other. Here we report the sequencing and assembly of the bonobo genome to study its evolutionary relationship with the chimpanzee and human genomes. We find that more than three per cent of the human genome is more closely related to either the bonobo or the chimpanzee genome than these are to each other. These regions allow various aspects of the ancestry of the two ape species to be reconstructed. In addition, many of the regions that overlap genes may eventually help us understand the genetic basis of phenotypes that humans share with one of the two apes to the exclusion of the other.

To gain insight into the patterns of genetic variation and evolutionary relationships within and between bonobos and chimpanzees, we sequenced 150,000 base pairs of nuclear DNA divided among 15 autosomal regions as well as the complete mitochondrial genomes from 20 bonobos and 58 chimpanzees. Except for western chimpanzees, we found poor genetic separation of chimpanzees based on sample locality. In contrast, bonobos consistently cluster together but fall as a group within the variation of chimpanzees for many of the regions. Thus, while chimpanzees retain genomic variation that predates bonobo-chimpanzee speciation, extensive lineage sorting has occurred within bonobos such that much of their genome traces its ancestry back to a single common ancestor that postdates their origin as a group separate from chimpanzees.

A previous polymorphism survey of the type 2 diabetes gene CAPN10 identified a segment showing an excess of polymorphism levels in all population samples, coinciding with localized breakdown of linkage disequilibrium (LD) in a sample of Hausa from Cameroon, but not in non-African samples. This raised the possibility that a recombination hotspot is present in all populations and we had insufficient power to detect it in the non-African data. To test this possibility, we estimated the crossover rate by sperm typing in five non-African men; these estimates were consistent with the LD decay in the non-African, but not in the Hausa data. Moreover, resequencing the orthologous region in a sample of Western chimpanzees did not show either an excess of polymorphism level or rapid LD decay, suggesting that the processes underlying the patterns observed in humans operated only on the human lineage. These results suggest that a hotspot of recombination has recently arisen in humans and has reached higher frequency in the Hausa than in non-Africans, or that there is no elevation in crossover rate in any human population, and the observed variation results from long-standing balancing selection.

Neanderthals are the extinct hominid group most closely related to contemporary humans, so their genome offers a unique opportunity to identify genetic changes specific to anatomically fully modern humans. We have identified a 38,000-year-old Neanderthal fossil that is exceptionally free of contamination from modern human DNA. Direct high-throughput sequencing of a DNA extract from this fossil has thus far yielded over one million base pairs of hominoid nuclear DNA sequences. Comparison with the human and chimpanzee genomes reveals that modern human and Neanderthal DNA sequences diverged on average about 500,000 years ago. Existing technology and fossil resources are now sufficient to initiate a Neanderthal genome-sequencing effort.

Levels of diversity vary across the human genome. This variation is caused by two forces: differences in mutation rates and the differential impact of natural selection. Pertinent to the question of the relative importance of these two forces is the observation that both diversity within species and interspecies divergence increase with recombination rates. This suggests that mutation and recombination are either directly coupled or linked through some third factor. Here, we test these possibilities using the recently generated sequence of the chimpanzee genome and new estimates of human diversity. We find that measures of GC and CpG content, simple-repeat structures, as well as the distance from the centromeres and the telomeres predict diversity as well as divergence. After controlling for these factors, large-scale recombination rates measured from pedigrees are still significant predictors of human diversity and human-chimpanzee divergence. Furthermore, the correlation between human diversity and recombination remains significant even after controlling for human-chimpanzee divergence. Two plausible and non-mutually exclusive explanations are, first, that natural selection has shaped the patterns of diversity seen in humans and, second, that recombination rates across the genome have changed since humans and chimpanzees shared a common ancestor, so that current recombination rates are a better predictor of diversity than of divergence. Because there are indications that recombination rates may have changed rapidly during human evolution, we favor the latter explanation.

Recombination rates seem to vary extensively along the human genome. Pedigree analysis suggests that rates vary by an order of magnitude when measured at the megabase scale, and at a finer scale, sperm typing studies point to the existence of recombination hotspots. These are short regions (1-2 kb) in which recombination rates are 10-1,000 times higher than the background rate. Less is known about how recombination rates change over time. Here we determined to what degree recombination rates are conserved among closely related species by estimating recombination rates from 14 Mb of linkage disequilibrium data in central chimpanzee and human populations. The results suggest that recombination hotspots are not conserved between the two species and that recombination rates in larger (50 kb) genomic regions are only weakly conserved. Therefore, the recombination landscape has changed markedly between the two species.

Recent experiments using sperm typing have demonstrated that, in several regions of the human genome, recombination does not occur uniformly but instead is concentrated in "hotspots" of 1-2 kb. Moreover, the crossover asymmetry observed in a subset of these has led to the suggestion that hotspots may be short-lived on an evolutionary time scale. To test this possibility, we focused on a region known to contain a recombination hotspot in humans, TAP2, and asked whether chimpanzees, the closest living evolutionary relatives of humans, harbor a hotspot in a similar location. Specifically, we used a new statistical approach to estimate recombination rate variation from patterns of linkage disequilibrium in a sample of 24 western chimpanzees (Pan troglodytes verus). This method has been shown to produce reliable results on simulated data and on human data from the TAP2 region. Strikingly, however, it finds very little support for recombination rate variation at TAP2 in the western chimpanzee data. Moreover, simulations suggest that there should be stronger support if there were a hotspot similar to the one characterized in humans. Thus, it appears that the human TAP2 recombination hotspot is not shared by western chimpanzees. These findings demonstrate that fine-scale recombination rates can change between very closely related species and raise the possibility that rates differ among human populations, with important implications for linkage-disequilibrium based association studies., Competing Interests: The authors have declared that no conflicts of interest exist.

An ability to predict levels of linkage disequilibrium (LD) between linked markers would facilitate the design of association studies and help to distinguish between evolutionary models. Unfortunately, levels of LD depend crucially on the rate of recombination, a parameter that is difficult to measure. In humans, rates of genetic exchange between markers megabases apart can be estimated from a comparison of genetic and physical maps; these large-scale estimates can then be interpolated to predict LD at smaller ("local") scales. However, if there is extensive small-scale heterogeneity, as has been recently proposed, local rates of recombination could differ substantially from those averaged over much larger distances. We test this hypothesis by estimating local recombination rates indirectly from patterns of LD in 84 genomic regions surveyed by the SeattleSNPs project in a sample of individuals of European descent and of African-Americans. We find that LD-based estimates are significantly positively correlated with map-based estimates. This implies that large-scale, average rates are informative about local rates of recombination. Conversely, although LD-based estimates are based on a number of simplifying assumptions, it appears that they capture considerable information about the underlying recombination rate or at least about the ordering of regions by recombination rate. Using LD-based estimators, we also find evidence for homologous gene conversion in patterns of polymorphism. However, as we demonstrate by simulation, inferences about gene conversion are unreliable, even with extensive data from homogeneous regions of the genome, and are confounded by genotyping error.

One of the most striking findings to emerge from the study of genomic patterns of variation is that regions with lower recombination rates tend to have lower levels of intraspecific diversity but not of interspecies divergence. This uncoupling of variation within and between species has been widely interpreted as evidence that natural selection shapes patterns of genetic variability genomewide. We revisited the relationship between diversity, divergence, and recombination in humans, using data from closely related species and better estimates of recombination rates than previously available. We show that regions that experience less recombination have reduced divergence to chimpanzee and to baboon, as well as lower levels of diversity. This observation suggests that mutation and recombination are associated processes in humans, so that the positive correlation between diversity and recombination may have a purely neutral explanation. Consistent with this hypothesis, diversity levels no longer increase significantly with recombination rates after correction for divergence to chimpanzee.

Studies of "dead-on-arrival" transposable elements in Drosophila melanogaster found that deletions outnumber insertions approximately 8:1 with a median size for deletions of approximately 10 bp. These results are consistent with the deletion and insertion profiles found in most other Drosophila pseudogenes. In contrast, a recent study of D. melanogaster introns found a deletion/insertion ratio of 1.35:1, with 84% of deletions being shorter than 10 bp. This discrepancy could be explained if deletions, especially long deletions, are more frequently strongly deleterious than insertions and are eliminated disproportionately from intron sequences. To test this possibility, we use analysis and simulations to examine how deletions and insertions of different lengths affect different components of splicing and determine the distribution of deletions and insertions that preserve the original exons. We find that, consistent with our predictions, longer deletions affect splicing at a much higher rate compared to insertions and short deletions. We also explore other potential constraints in introns and show that most of these also disproportionately affect large deletions. Altogether we demonstrate that constraints in introns may explain much of the difference in the pattern of deletions and insertions observed in Drosophila introns and pseudogenes.

Although many studies have reported human polymorphism data, there has been no analysis of the effect of sampling design on the patterns of variability recovered. Here, we consider which factors affect a summary of the allele-frequency spectrum. The most important variable to emerge from our analysis is the number of ethnicities sampled: studies that sequence individuals from more ethnicities recover more rare alleles. These observations are consistent with fine-scale geographic differentiation as well as population growth. They suggest that the geographic sampling strategy should be considered carefully, especially when the aim is to infer the demographic history of humans.