A geometric morphometric analysis of heterochrony in the cranium of chimpanzees and bonobos

Despite several decades of research, there remains a lack of consensus on the extent to which bonobos are paedomorphic (juvenilized) chimpanzees in terms of cranial morphology. This study reexamines the issue by comparing the ontogeny of cranial shape in cross-sectional samples of bonobos (Pan paniscus) and chimpanzees (Pan troglodytes) using both internal and external 3D landmarks digitized from CT scans. Geometric morphometric methods were used to quantify shape and size; dental-maturation criteria were used to estimate relative dental age. Heterochrony was evaluated using combined size-shape (allometry) and shape-age relationships for the entire cranium, the face, and the braincase. These analyses indicate that the bonobo skull is paedomorphic relative to the chimpanzee for the first principal component of size-related shape variation, most likely via a mechanism of postformation (paedomorphosis due to initial shape underdevelopment). However, the results also indicate that not all aspects of shape differences between the two species, particularly in the face, can be attributed to heterochronic transformation and that additional developmental differences must also have occurred during their evolution.     

A comparative study of the variety and complexity of object manipulation in captive chimpanzees (Pan troglodytes) and bonobos (Pan paniscus)

Four types of specific objects: wooden spoons, metal bowls, plastic boxes, and cotton towels were introduced in a similar setting to two captive groups of different species in the genusPan, the bonobo and the chimpanzee. In total, 582 unique manipulation forms were distinguished by a set of variables: types of objects, motor patterns, body-parts used, the number of objects manipulated, and types of orienting manipulation. In sum, chimpanzees and bonobos were not so different in the variety and the complexity of object manipulation forms. However, comparison of the two species revealed significant differences as follows: (1) chimpanzees preferred to use only one hand during manipulation of both single- and multiple-objects, whereas in the case of multiple-objects bonobos used both hands significantly more often; (2) chimpanzees performed more orienting manipulations in single-object manipulations than did bonobos, whereas the reverse was the case in multiple-object manipulations; and (3) chimpanzees' object manipulations were overall more substrate-oriented than were bonobos'. The factors producing these differences are discussed in relation to positional behaviors and habitual tool use in the two species.     

Divergence population genetic analysis of hybridization between rhesus and cynomolgus macaques

The geographic ranges of rhesus ( Macaca mulatta ) and cynomolgus ( M. fascicularis ) macaques adjoin in Indochina where they appear to hybridize. We used published and newly generated DNA sequences from 19 loci spanning ~20 kb to test whether introgression has occurred between these macaque species. We studied introgression at the level of nuclear DNA and distinguished between incomplete lineage sorting of ancestral polymorphisms or interspecific gene flow. We implemented a divergence population genetics approach by fitting our data to an isolation model implemented in the software IMa. The model that posits no gene flow from the rhesus into the cynomolgus macaque was rejected ( P  = 1.99 × 10⁻⁸). Gene flow in this direction was estimated as 2 Nm ~1.2, while gene flow in the reverse direction was nonsignificantly different from zero ( P  = 0.16). The divergence time between species was estimated as ~1.3 million years. Balancing selection, a special case of incomplete sorting, was taken into consideration, as well as potential crossbreeding in captivity. Parameter estimates varied between analyses of subsets of data, although we still rejected isolation models. Geographic sampling of the data, where samples of cynomolgus macaques derived from Indochina were excluded, revealed a lost signature of gene flow, indicating that interspecific gene flow is restricted to mainland Indochina. Our results, in conjunction with those by others, justify future detailed analyses into the genetics of reproductive barriers and reticulate evolution in these two genome-enabled primates. Future studies of the natural hybridization between rhesus and cynomolgus macaques would expand the repertoire of systems available for speciation studies in primates.     

Skeletal evidence of trauma in African apes, with special reference to the gombe chimpanzees

Incidence of cranial and postcranial skeletal trauma was investigated in samples of chimpanzees (Pan troglodytes troglodytes, P. troglodytes schweinfurthii), lowland gorillas (Gorilla gorilla gorilla), and bonobos (P. paniscus). The larger (adult) samples of chimpanzees (N=127 crania, 92 postcrania) and gorillas (N=136 crania, 62 postcrania) are curated at the Powell-Cotton Museum, Birchington, U.K. The bonobo collection (N=71 crania, 15 postcrania) is housed the Musée Royal de l'Afrique Centrale in Tervuren, Belgium. In addition, data were collected on the small but extremely well-documented skeletal sample from Gombe National Park (N=14 crania, 13 postcrania — including adults and adolescents). Cranial injuries, including healed fractures and bite wounds, were fairly frequent in the museum collection of chimpanzees (5.5% of individuals), but were twice as frequent in gorillas (11.0%). In the Gombe sample an even higher incidence was observed (28.6% of individuals). Bonobos, however, showed the lowest incidence of cranial trauma found among any of the African ape samples (1.4% of individuals). Postcranial trauma, documented most clearly by healed fractures, was seen in 21.7% of the Powell-Cotton chimpanzees, 30.8% of Gombe chimpanzees, 17.7% of gorillas, and in 13.3% of bonobos. Most of these lesions were found in the upper appendage. Nevertheless, highly debilitating healed fractures of the femur were also noted, most frequently and severe in female gorillas. The pattern of injuries suggests serious risks of falling in all free-ranging African apes, but also (in chimpanzees and gorillas) considerable risk from interindividual aggression, especially for males.     

A Continuous Method for Gene Flow

Most modern population genetics inference methods are based on the coalescence framework. Methods that allow estimating parameters of structured populations commonly insert migration events into the genealogies. For these methods the calculation of the coalescence probability density of a genealogy requires a product over all time periods between events. Data sets that contain populations with high rates of gene flow among them require an enormous number of calculations. A new method, transition probability-structured coalescence (TPSC), replaces the discrete migration events with probability statements. Because the speed of calculation is independent of the amount of gene flow, this method allows calculating the coalescence densities efficiently. The current implementation of TPSC uses an approximation simplifying the interaction among lineages. Simulations and coverage comparisons of TPSC vs. MIGRATE show that TPSC allows estimation of high migration rates more precisely, but because of the approximation the estimation of low migration rates is biased. The implementation of TPSC into programs that calculate quantities on phylogenetic tree structures is straightforward, so the TPSC approach will facilitate more general inferences in many computer programs.     

Bayesian phylogenetic model selection using reversible jump Markov chain Monte Carlo

A common problem in molecular phylogenetics is choosing a model of DNA substitution that does a good job of explaining the DNA sequence alignment without introducing superfluous parameters. A number of methods have been used to choose among a small set of candidate substitution models, such as the likelihood ratio test, the Akaike Information Criterion (AIC), the Bayesian Information Criterion (BIC), and Bayes factors. Current implementations of any of these criteria suffer from the limitation that only a small set of models are examined, or that the test does not allow easy comparison of non-nested models. In this article, we expand the pool of candidate substitution models to include all possible time-reversible models. This set includes seven models that have already been described. We show how Bayes factors can be calculated for these models using reversible jump Markov chain Monte Carlo, and apply the method to 16 DNA sequence alignments. For each data set, we compare the model with the best Bayes factor to the best models chosen using AIC and BIC. We find that the best model under any of these criteria is not necessarily the most complicated one; models with an intermediate number of substitution types typically do best. Moreover, almost all of the models that are chosen as best do not constrain a transition rate to be the same as a transversion rate, suggesting that it is the transition/transversion rate bias that plays the largest role in determining which models are selected. Importantly, the reversible jump Markov chain Monte Carlo algorithm described here allows estimation of phylogeny (and other phylogenetic model parameters) to be performed while accounting for uncertainty in the model of DNA substitution.     

Sympatric speciation as intrinsic property of the expanding population

Sympatric speciation is still debatable, though some well documented empirical data that support it already exist. Our computer modeling reveals that sympatric speciation is an intrinsic property of the expanding populations with differentiated inbreeding—higher at the edges and lower inside the territory. At the edges of expanding populations, the probability of forming deleterious phenotypes by placing two defective alleles in the corresponding loci is relatively high even with low genetic load. Thus, the winning strategy is to use rather the complementary haplotypes to form zygotes. This strategy leads to a very fast sympatric speciation and specific distribution of recombination activity along the chromosomes—higher at the subtelomeric regions (close to the ends of chromosomes) and lower in the middle of chromosomes, which is also observed in all human chromosomes (excluding Y).     

Sampling genotypes in large pedigrees with loops

Markov chain Monte Carlo (MCMC) methods have been proposed to overcome computational problems in linkage and segregation analyses. This approach involves sampling genotypes at the marker and trait loci. Scalar-Gibbs is easy to implement, and it is widely used in genetics. However, the Markov chain that corresponds to scalar-Gibbs may not be irreducible when the marker locus has more than two alleles, and even when the chain is irreducible, mixing has been observed to be slow. These problems do not arise if the genotypes are sampled jointly from the entire pedigree. This paper proposes a method to jointly sample genotypes. The method combines the Elston-Stewart algorithm and iterative peeling, and is called the ESIP sampler. For a hypothetical pedigree, genotype probabilities are estimated from samples obtained using ESIP and also scalar-Gibbs. Approximate probabilities were also obtained by iterative peeling. Comparisons of these with exact genotypic probabilities obtained by the Elston-Stewart algorithm showed that ESIP and iterative peeling yielded genotypic probabilities that were very close to the exact values. Nevertheless, estimated probabilities from scalar-Gibbs with a chain of length 235 000, including a burn-in of 200 000 steps, were less accurate than probabilities estimated using ESIP with a chain of length 10 000, with a burn-in of 5 000 steps. The effective chain size (ECS) was estimated from the last 25 000 elements of the chain of length 125 000. For one of the ESIP samplers, the ECS ranged from 21 579 to 22 741, while for the scalar-Gibbs sampler, the ECS ranged from 64 to 671. Genotype probabilities were also estimated for a large real pedigree consisting of 3 223 individuals. For this pedigree, it is not feasible to obtain exact genotype probabilities by the Elston-Stewart algorithm. ESIP and iterative peeling yielded very similar results. However, results from scalar-Gibbs were less accurate.     

Socioecological factors influencing population structure of gorillas and chimpanzees

Differences in distribution and density between gorillas and chimpanzees are reconsidered with special reference to population structure. Both ecological and social factors influencing population structure are compared between species and between habitats within species. Gorillas and chimpanzees respond differently to a decline in food quality, such as fruit scarcity: gorillas change diet and decrease range, while chimpanzees do not change diet but may expand range. These responses result in different effects on their grouping patterns. For gorillas the dispersed distribution and reduction of range size decreases the rate of inter-unit encounters and female transfer. The concentration of social units increases the rate of aggressive contact between units and stimulates female transfer. Social units of gorillas may crowd or disperse in order to attain the optimal density. This tendency may result in similar densities of gorillas across habitats. By contrast, the distribution patterns or range size may not affect inter-unit relationships of chimpanzees. Within a single unit-group, various reproductive strategies are adopted by both sexes. Independent travel of females and flexible grouping patterns enable them to survive at very low density in extraordinary large ranges. Density and inter-unit relationships are good criteria for a healthy population of gorillas, while the size of unit-group and inter-individual relationships are good criteria for chimpanzees. Conservation planners should consider these differences for sympatric and allopatric survival in these species.     

Folding small proteins via annealing stochastic approximation Monte Carlo

Recently, the stochastic approximation Monte Carlo algorithm has been proposed by Liang et al. (2007) as a general-purpose stochastic optimization and simulation algorithm. An annealing version of this algorithm was developed for real small protein folding problems. The numerical results indicate that it outperforms simulated annealing and conventional Monte Carlo algorithms as a stochastic optimization algorithm. We also propose one method for the use of secondary structures in protein folding. The predicted protein structures are rather close to the true structures.     

Bayesian phylogeny analysis via stochastic approximation Monte Carlo

Monte Carlo methods have received much attention in the recent literature of phylogeny analysis. However, the conventional Markov chain Monte Carlo algorithms, such as the Metropolis–Hastings algorithm, tend to get trapped in a local mode in simulating from the posterior distribution of phylogenetic trees, rendering the inference ineffective. In this paper, we apply an advanced Monte Carlo algorithm, the stochastic approximation Monte Carlo algorithm, to Bayesian phylogeny analysis. Our method is compared with two popular Bayesian phylogeny software, BAMBE and MrBayes, on simulated and real datasets. The numerical results indicate that our method outperforms BAMBE and MrBayes. Among the three methods, SAMC produces the consensus trees which have the highest similarity to the true trees, and the model parameter estimates which have the smallest mean square errors, but costs the least CPU time.     

Factors underlying party size differences between chimpanzees and bonobos: a review and hypotheses for future study

Differences in party size and cohesiveness among females have been primary topics in socio-ecological comparisons of chimpanzees (Pan troglodytes) and bonobos (Pan paniscus). This paper aims to review previous studies that attempted to explain these differences and propose some hypotheses to be tested in future studies. Comparisons of recent data show that relative party size (expressed as a percentage of total group size) is significantly larger for bonobos than chimpanzees. Although the prolonged estrus of females, close association between mother and adult sons, female social relationships including unique homosexual behavior, and high female social status might be related to the increased party size and female cohesiveness of bonobos, these social and behavioral factors alone do not appear to explain the differences between the two species. Differences in ecological factors, including fruit-patch size, density of terrestrial herbs, and the availability of scattered foods that animals forage as they travel between large fruit patches could also contribute to the differences between chimpanzees and bonobos. However, these factors cannot fully account for the increased party size and female cohesiveness of bonobos. The higher female cohesiveness in bonobos may be explained by socio-ecological systems that reduce the cost in feeding efficiency incurred by attending mixed-sex parties. These systems may include female initiatives for party ranging movements as well as the factors mentioned above. Because of their geographical isolation, the two species probably evolved different social systems. Chimpanzees, whose habitats became very dry during some periods in the Pleistocene, likely evolved more flexible fission–fusion social systems to cope with seasonal and annual variation in food availability. On the other hand, bonobos had a large refugia forest in the middle of their range even during the driest periods in the Pleistocene. Therefore bonobos, whose habitats had more abundant food and smaller variation in food availability, probably evolved systems that help females stay in mixed parties without incurring large costs from contest and scramble competition.     

Bayesian coalescent inference of past population dynamics from molecular sequences

We introduce the Bayesian skyline plot, a new method for estimating past population dynamics through time from a sample of molecular sequences without dependence on a prespecified parametric model of demographic history. We describe a Markov chain Monte Carlo sampling procedure that efficiently samples a variant of the generalized skyline plot, given sequence data, and combines these plots to generate a posterior distribution of effective population size through time. We apply the Bayesian skyline plot to simulated data sets and show that it correctly reconstructs demographic history under canonical scenarios. Finally, we compare the Bayesian skyline plot model to previous coalescent approaches by analyzing two real data sets (hepatitis C virus in Egypt and mitochondrial DNA of Beringian bison) that have been previously investigated using alternative coalescent methods. In the bison analysis, we detect a severe but previously unrecognized bottleneck, estimated to have occurred 10,000 radiocarbon years ago, which coincides with both the earliest undisputed record of large numbers of humans in Alaska and the megafaunal extinctions in North America at the beginning of the Holocene.