Journal of Heredity Advance Access published online on October 30, 2008
Journal of Heredity, doi:10.1093/jhered/esn093
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Assessing Natural Introgression in 2 Biomedical Model Species, the Rhesus Macaque (Macaca mulatta) and the Long-Tailed Macaque (Macaca fascicularis)
From the Université Paul Sabatier, Laboratoire Evolution et Diversité Biologique, UMR CNRS 5174, Toulouse cedex 9, France (Bonhomme, Cuartero, and Crouau-roy); and the Laboratoire d'Immunogénétique Moléculaire, Faculté de Médecine de Rangueil, Université Paul Sabatier, Toulouse III, France (Blancher)
Address correspondence to B. Crouau-Roy at the address above, or e-mail: bcrouau{at}cict.fr.
Rhesus macaque (Macaca mulatta) and long-tailed macaque (Macaca fascicularis) are the 2 most commonly used primate model species in biomedical sciences. Although morphological studies have revealed a weak hybridization at the interspecific contact zone, in the north of Indochina, a molecular study has suggested an ancient introgression from rhesus to long-tailed macaque into the Indo-Chinese peninsula. However, the gene flow between these 2 taxa has never been quantified using genetic data and theoretical models. In this study, we have examined genetic variation within and between the parapatric Chinese rhesus macaque and Indo-Chinese long-tailed macaque populations, using 13 autosomal, 5 sex-linked microsatellite loci and mitochondrial DNA sequence data. From these data, we assessed genetic structure and estimated gene flow using a Bayesian clustering approach and the "Isolation with Migration" model. Our results reveal a weak interspecific genetic differentiation at both autosomal and sex-linked loci, suggesting large population sizes and/or gene flow between populations. According to the Bayesian clustering, Chinese rhesus macaque is a highly homogeneous gene pool that contributes strongly to the current Indo-Chinese long-tailed macaque genetic makeup, whether or not current admixture is assumed. Coalescent simulations, which integrated the characteristics of the loci, pointed out 1) a higher effective population size in rhesus macaque, 2) no mitochondrial gene flow, and 3) unilateral and male-mediated nuclear gene flow of 
10 migrants per generation from rhesus to long-tailed macaque. These patterns of genetic structure and gene flow suggest extensive ancient introgression from Chinese rhesus macaque into the Indo-Chinese long-tailed macaque population.
Natural successful interspecific mating, known as hybridization, has received much attention in the recent years because it can have evolutionary consequences such as genetic enrichment by introgression, reinforcement of reproductive barriers, and the formation of new species (Barton and Hewitt 1985, 1989; Arnold 2006). It has been documented on several organisms, and population genetic studies have often focused on the contact zones with presence or absence of the introgressing or parental populations (see for example: Gottelli et al. 1994; Roy et al. 1994; Beaumont et al. 2001; Coyer et al. 2007).
Morphological analyses and comparative phylogenetics of mitochondrial DNA (mtDNA) and nuclear genes have shown that hybridization is of major relevance in the evolution and conservation of primate species (see Arnold and Meyer 2006, for a review; Jolly 2001; Detwiler et al. 2005). It is frequent in cercopithecine genera such as Papio (Alberts and Altmann 2001; Newman et al. 2004) and Macaca in which it has been detected in 15 out of the 19 species (Hayasaka et al. 1996; Bynum et al. 1997; Morales and Melnick 1998; Evans et al. 2001; Bynum 2002; Tosi et al. 2002, 2003; Kawamoto 2005; Smith and McDonough 2005).
Macaca fascicularis (long-tailed macaque or cynomolgus macaque) and Macaca mulatta (rhesus macaque) are 2 closely related parapatric macaque species living in southeast Asia (Fooden 1980, 1982). The ability of these 2 species to hybridize has been evidenced by natural hybrids forms described in the Dawna Range of the Indo-Chinese peninsula (hereafter named "Indochina"), with, however, a currently limited spatial pattern of hybridization (Fooden 1964, 1997), and by crosses in captivity (Bernstein and Gordon 1980). Moreover, a molecular study suggests ancient and strong introgression from rhesus to long-tailed macaque, based on the comparison of Y chromosome and mtDNA sequences (Tosi et al. 2002). In this study, the mtDNA monophyly in both species emphasizes the philopatric behavior of female macaques—a common phenomenon in primate species from the Cercopithecidae family (Pusey and Packer 1987)—whereas the long-tailed macaque Y chromosome paraphyly clearly shows that males have hybridized after dispersal. More recently, the study of blood group distribution in free-ranging long-tailed and rhesus macaques in Thailand also supported the introgression hypothesis (Malaivijitnond et al. 2008).
The probable hybrid nature of the current Indo-Chinese long-tailed macaque may have evolutionary consequences. For instance, a signature of introgression in its genome would definitely beg the question of the relevance of its current taxonomic status (Fooden 1964, 1997; Tosi et al. 2002). On the one hand, such introgression would tend to cause the breaking of coadapted genes and then a lower population fitness. On the other hand, it could favor the transfer of genes underlying adaptive traits and then a possibility for the introgressed form to establish in novel habitats, if the hybrids have a higher fitness—heterosis—(for review, see Arnold 2006). A more practical implication of the putative hybrid nature of long-tailed macaque in Indochina could be unexpected and/or biased outcomes in biomedical experiments involving individuals of this species, as an alternative to the rhesus macaque (Schmidt et al. 1977; Borie et al. 2002; Kita et al. 2005; Lawler et al. 2006; O'Connor 2006; Wieczorek et al. 2006; Sato et al. 2008).
An issue that has not been addressed is whether such introgression, if confirmed, can be quantified from nuclear and mitochondrial genetic data, namely to estimate the proportion of rhesus macaque genes present in the Indo-Chinese long-tailed macaque genome. To identify putative hybrid genotypes, we used a Bayesian clustering method. Then, in order to infer migration events after the speciation, we used a method that relies on the fitting of the "Isolation with Migration" (IM) model—originally designed for population studies—to the species studied. This Markov chain Monte Carlo (MCMC) method yields estimates of the posterior probability distribution for demographic parameters, such as the migration rates, the effective population sizes of 2 current populations and their ancestral population, and the divergence time (Nielsen and Wakeley 2001; Hey and Nielsen 2004; Hey 2006). In primates, this method has been applied to human for inferring the peopling of the Americas (Hey 2005) and to Great Apes for quantifying migration between subspecies using multilocus sequence data (Pan troglodytes ssp.: Won and Hey [2005]; Gorilla gorilla: Thalmann et al. [2007]; both species: Becquet and Przeworski [2007]). Here, we applied this method for quantifying gene flow (introgression) between 2 common macaque species: the rhesus and the long-tailed macaques.
To test the introgression hypothesis, we studied intraspecific and interspecific genetic variation in samples from the 2 contiguous populations of rhesus (China) and long-tailed (Indochina) macaque. To this end, we performed analyses using a data set combining tetranucleotide microsatellites scattered throughout the autosomes (13 on different autosomes) and the sex chromosomes (4 on the X chromosome and 1 on the Y chromosome), with additional mtDNA D-loop sequence data from both species. We first evaluated the proportion of hybrid genotypes in both populations, based on microsatellite genotypes, using a Bayesian clustering method. Then, using the population-based IM model, we attempted to estimate the amount, the direction (symmetric or asymmetric), and the potentially sex-biased pattern of gene flow/introgression and to evaluate the timescale of this phenomenon.
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Sampling and Microsatellites Genotyping
The samples consisted of 70 unrelated long-tailed macaques from Indochina and 50 rhesus macaques from China. Long-tailed macaque individuals were F1 derived from breeders from various locations in Indochina, except in the contact zones (for location of the contact zones see Figure 2, Fooden 2006), hosted by the animal breeding company Nafovanny (Long Thanh, VietNam). Rhesus macaque individuals were F1 imported from a Chinese breeding center (South-China Primate Research Development Center, Jiufu center, country of Guangzhou, China) to the Bioprim quarantine center (Bioprim, Baziège, France). All genomic DNA samples were extracted from peripheral blood using either QIAamp Blood Kit (Qiagen, Courtaboeuf, France) or a classical phenol–chloroform method. The bulk of Indo-Chinese long-tailed macaque and Chinese rhesus macaque individuals investigated were previously sequenced for the mtDNA D-loop—68 and 22 individuals, respectively (Blancher et al. 2008). This study definitely confirmed that the individuals sampled in Indochina indeed belonged to the long-tailed macaque cluster. This data set was investigated here in addition to nuclear microsatellite data, using the IM model.
We amplified 18 human-derived microsatellites: 13 unlinked autosomal tetranucleotides, 4 X-linked microsatellites (2 tetranucleotides and 2 dinucleotides), and 1 Y-linked tetranucleotide. D1S548, D3S1768, D7S2204, D8S1106, D10S1432, D4S243, D5S820, DXS571, DXS6810, DXS6799, and DXS8043 were amplified as described in Bonhomme et al. (2005). The multiplex polymerase chain reaction (PCRs) of the other markers were slightly modified from Bonhomme et al. (2005), with specific annealing temperatures of 56 °C (D5S1457, D14S306) and 52 °C (D1S550, D4S2365, D5S1470, D7S794, DYS391), and primer concentrations 0.2, 0.2, 0.6, 0.15, 0.5, 0.15, and 0.2 µM, respectively. PCR products were separated on a 5% polyacrylamide gel on an ABI 377 genetic analyzer and genotypes scored using the software Genotyper 3.6 (ABI Prism).
Statistical Analyses
Genetic diversity was measured using the number of alleles (nA), the expected and observed heterozygosity (He and Ho). Departures from Hardy–Weinberg equilibrium within samples was measured with Fis using the GENETIX software v 4.05 (Belkhir et al. 2004) and significance tests were done using 10 000 permutations. The software MICRO-CHECKER 2.2.3 (van Oosterhout et al. 2004) was used to pinpoint loci with potential null alleles. We computed 2 genetic differentiation estimates between the long-tailed and rhesus macaque samples: Fst (
of Weir and Cockerham 1984) and Rst (
of Slatkin 1995). Fst was calculated using GENETIX and the significance was tested using 10 000 permutations. Rst uses information about the mutation process by estimating a distance between alleles at a microsatellite locus, in addition to allelic frequency variations. It was calculated using the Rst Calc software (Goodman 1997). Significance was assessed using 10 000 permutations. Linkage disequilibrium (LD) was tested on the autosomal and X chromosome microsatellite data sets in both species, using the likelihood ratio test implemented in ARLEQUIN V.2.000 software (Schneider et al. 2000), in order to check for independence between loci for subsequent multilocus data analysis.
To evaluate whether present-day Chinese rhesus macaque and Indo-Chinese long-tailed macaque populations consist of hybrid genotypes, we used the software STRUCTURE v2.2 (Pritchard et al. 2000), which implements a Bayesian algorithm to identify K user-defined clusters of genetically homogeneous individuals. We analyzed the data with K = 2 up to 6. The analysis with STRUCTURE produced for each individual a probability value of assignment to each cluster (proportion of membership). We used both the "admixture" and "no admixture" models. Allelic frequencies were set to correlate among populations. All analyses were replicated 10 times to ensure proper convergence of the MCMC with a burn-in of 1 000 000 steps and a MCMC length of 2 000 000 after burn-in.
We used the IM program—5 March 2007 release (Nielsen and Wakeley 2001; Hey and Nielsen 2004; Hey 2006)—for the MCMC estimation of posterior probability distributions of m1 (=m1/µ), m2 (=m2/µ), q1 (=1 = 4N1µ), q2 (=2 = 4N2µ), qA (=A = 4NAµ), and t (=tµ) corresponding to the migration rate within Chinese rhesus macaque and within Indo-Chinese long-tailed macaque, respectively, the current effective population size of rhesus and long-tailed macaque, respectively, the ancestral population size and the divergence time. The parameter µ is the mean mutation rate of microsatellite loci. The underlying assumptions of the model are 1) no selection, 2) panmixia and no population substructure 3) a stepwise mutation model for microsatellite data and a Hasegawa-Kishino-Yano substitution model for sequence data, and 4) potential population growth with a variable contribution of the ancestral population to the 2 divergent populations. The Felsenstein equation shows how a data set and the model parameters are linked via integration over the different genealogies (Felsenstein 1988; Beerli and Felsenstein 1999; Hey and Nielsen 2007):
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The MCMC (Nielsen and Wakeley 2001) allows sampling from the posterior distribution of the parameter given the data (Pr(Parameters/Data)), that is linked to the likelihood function (Pr(Data/Parameters)) via a constant. We then obtain marginal posterior distributions for each parameter of the model. We ran the MCMC 3 times with a combined data set of all microsatellite loci (autosomes, X, and Y chromosomes), excluding loci showing signs of null alleles and for D-loop mtDNA sequences independently. Each chain consisted of 20 000 000 steps and the burn-in was 1 000 000. The effective population sizes, the divergence time, and the migration rate parameters are scaled by the mean mutation rate in the simulations. To obtain demographic parameters, we assumed a mutation rate of 5 x 10–4 per generation for microsatellite loci (Weber and Wong 1993; Estoup and Angers 1998; Schlötterer 2001; Whittaker et al. 2003). We used the mtDNA D-loop sequence data set mainly to estimate the migration rate parameter from the female-inherited genome and to compare it with the one inferred from nuclear microsatellite data. Although the generation time is a fluctuating component of macaques life history and population dynamics, it was given a minimum value of 5 years, for both species, which corresponds to the mean age of sexual maturity for both sexes (Harvey et al. 1987). The value of the generation time parameter only affects the divergence time estimated in years, in a linear way. Thus, for instance, doubling the generation time would double accordingly the divergence time estimated in years. Prior distributions were uniform and their bounds were set to [0–800] for q1, q2, and qA and [0–5] for m1 and m2. For the parameter t, the uncertainty on the timescale of the divergence time between long-tailed and rhesus macaque are such that we allowed a wide range of values [0–250]: This set up a maximum divergence time at 3 Ma, corresponding to the age of the oldest macaque fossil in Asia (Macaca palaeindica—Szalay and Delson 1979). Finally, the parameter s, the percentage of lineages from the ancestral population sorting into the 2 divergent populations, was given the largest bounds ([0–1]). Hence, we assumed no prior knowledge of the contribution of the ancestral population to the 2 divergent populations. More generally, we allowed a large spectrum of possible values—no prior knowledge—for each parameter when applying the IM model to our data.
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Average genetic diversity was high and similar in Chinese rhesus macaque and Indo-Chinese long-tailed macaque at autosomal loci (He: 0.80 and 0.80, nA: 9.8 and 10.8), X chromosome loci (He: 0.81 and 0.80, nA: 10.5 and 8.8), and the Y chromosome locus (He: 0.79 and 0.85, nA: 6 and 9) (see Table 1).
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None of the pairs of autosomal loci were in LD in Chinese rhesus macaque, whereas only 3% showed significant LD (P < 0.01) in Indo-Chinese long-tailed macaque. In addition, no LD was observed among X chromosome microsatellites in both species, except for the pair of loci DXS571–DXS8043 (P = 0.03), in long-tailed macaque. The lack of LD between X chromosome markers was not surprising given the distances separating the loci: DXS6810, DXS6799, DXS571, and DXS8043 are located approximately at positions 41, 97, 107, and 143 Mb, respectively (see http://www.ncbi.nlm.nih.gov/mapview/map_search.cgi?taxid=9544—rhesus macaque map viewer), allowing recombination events. Overall autosomal and X chromosome microsatellites could then be considered as independent and be treated as such in subsequent multilocus analyses.
Mean Fis for rhesus and long-tailed macaques were low at autosomal loci (0.07 and 0.09, respectively) but significant (P < 0.001). Two loci (D1S550 and D5S1457) in long-tailed macaque had high Fis values (0.31 and 0.24) most probably due to the presence of null alleles (MICRO-CHECKER analysis). When removing these 2 loci, mean autosomal Fis values decreased at 0.067 and 0.056 for rhesus and long-tailed macaque, respectively. For X chromosome loci, mean Fis was 0.20 for long-tailed macaque and 0.01 for rhesus macaque, but 2 loci were responsible for the former value in long-tailed macaque: DXS571 (Fis = 0.43) and DXS8043 (Fis = 0.21). These 2 loci also showed null alleles with high Fis values compared with the 2 other X chromosome loci (0.1 and 0.07). Therefore, when removing loci showing null allele signs, there was no evidence for strong population substructure in the nuclear genomes of our samples of Chinese rhesus macaque and Indo-Chinese long-tailed macaque. As a consequence, loci D1S550, D5S1457, DXS571, and DXS8043 were removed from the STRUCTURE and IM analysis.
Genetic differentiation was low but significant for autosomal (Fst = 0.02), X chromosome (Fst = 0.05), and Y chromosome (Fst = 0.11) loci (Table 2). Rst values were slightly higher than Fst values. One exception was the Rst value for the Y chromosome microsatellite (Rst = 0.62), which was very strong but probably attributable to the high sampling variance of this statistic (Slatkin 1995), due to only one locus capturing the Y chromosome variability. Thus, the nuclear genetic differentiation between Chinese rhesus macaque and Indo-Chinese long-tailed macaque is low.
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The analyses with STRUCTURE produced informative partitions only for runs performed with K = 2, thus matching a 2-species division. Results are therefore presented for K = 2. The analyses indicated no major differences among runs and between the admixture and no admixture models (Figure 1). The Chinese rhesus macaque sample represented an homogeneous genetic cluster, with an average proportion of membership in cluster 2% of 93% that increased up to 95% when removing 2 individuals (numbers 36 and 37) that showed q values of 58% and 28% (Figure 1). By contrast, the Indo-Chinese long-tailed macaque sample was nonhomogeneous, with an average proportion of membership to cluster 1 of 81%. At least 14% of the individuals (10 out of 70) bore mostly hybrid genotypes, having q values superior or equal to 50%. More precisely, 19% and 24% of the individuals showed q values superior or equal to 40% and 25%, respectively. Thus, cluster 2 (the rhesus macaque gene pool) strongly contributed to the current Indo-Chinese long-tailed macaque genetic makeup.
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The IM program was run 3 times with a combined data set of 14 fully independent microsatellite loci and independently with mtDNA D-loop sequences. The 2 sets of 3 IM runs revealed highly similar marginal posterior distributions of the parameters; thus, we present results from one run for each data set. The outputs from the nuclear microsatellite data set showed marginal posterior distributions with narrow ranges and relatively high maximum likelihood (ML) values (Figure 2). The ML effective population size for Chinese rhesus macaque, Indo-Chinese long-tailed macaque, and their ancestral population were 24 600 (90% highest posterior density [HPD] interval: 17 000–46 600), 11 800 (6600–17 400), and 2200 (200–5400) in number, respectively, assuming a microsatellite mutation rate of 5 x 10–4 (Table 3). Posterior distributions of the effective population size estimated from mtDNA data had similar shapes as those estimated from nuclear microsatellite data but showed higher absolute theta values (Table 3, Figure 3). The marginal posterior distribution of the divergence time parameter estimated from microsatellite data revealed a peak at 4.35 units with a narrow distribution (Table 3, Figure 2). When converted to years, the divergence time between Chinese rhesus and Indo-Chinese long-tailed macaques was estimated at 43 500 years (90% HPD interval: 23 500–68 500 years). By contrast, the distribution of the divergence time estimated from mtDNA data was not informative (Table 3, Figure 3). The migration rate distributions estimated from microsatellite data suggested a ML migration rate close to zero from Indo-Chinese long-tailed macaque to Chinese rhesus macaque (m1 = 0.0025), whereas gene flow from Chinese rhesus macaque to Indo-Chinese long-tailed macaque was, by contrast, relevant (m2 = 0.8975) (Table 3, Figure 2). Therefore, the ML effective number of migrants per generation becomes 2N1m1 = 0.0615 and 2N2m2 = 10.59, respectively. Interestingly, from mtDNA data, the ML migration rate was close to 0 for both species (Figure 3). To get a better insight on gene flow from one species to another, we recorded the number of migration events that occurred in the simulations for each locus and the mean time of migration events (Table 4). From long-tailed to rhesus macaque, the modal number of migration events per locus was 0 for each locus. From rhesus to long-tailed macaque, the modal number of migration events over microsatellite loci was 26. More precisely, the modal number of migration events was 28.7 over autosomal microsatellite loci, 21 over X-linked loci, 6 for the only Y-linked loci, and 0 for the mtDNA D-loop, indicating the occurrence of nuclear gene flow but not mitochondrial gene flow. These values suggest that gene flow is male mediated. Finally, the mean time of migration rates was 0.34—with a negligible variance—corresponding to 3400 years when converted by using a mutation rate of 5 x 10–4 (Table 4).
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The rhesus macaque (M. mulatta) and the long-tailed macaque (M. fascicularis) are among the 2 most common and widely distributed primate species besides human (Fooden 1980). During the last 20 years, both represented the main primate models for biomedical research with applications to human genetics, diseases, surgery, and medicine (Schmidt et al. 1977; Borie et al. 2002; Kita et al. 2005; Lawler et al. 2006; O'Connor 2006; Wieczorek et al. 2006; Sato et al. 2008). It is thus of utmost importance to have a good knowledge of the genetic variability and structure within and between these 2 species, so as to properly investigate the genetic basis of phenotypic differences and also common characteristics. The female-inherited mtDNA diversity is high and species specific (monophyletic) in rhesus and long-tailed macaques (see Figure 2 in Hayasaka et al. 1996; Morales and Melnick 1998; Tosi et al. 2002, 2003; Blancher et al. 2008). In addition, the biochemical and nuclear gene diversities also appear to be high in macaque species (Nozawa et al. 1977; Melnick and Kidd 1985; Deinard and Smith 2001). Recently, the study of neutral markers such as single nucleotide polymorphisms (SNPs) and microsatellites revealed high levels of genetic diversity in populations of both species (Bonhomme et al. 2007, 2008; Hernandez et al. 2007).
Factors Affecting Demographic Parameter Estimates
After divergence, gene flow slows the rate at which 2 populations become genetically distinctive. Thus, because lineages are exchanged between populations, methods that assume no gene flow after divergence will tend to underestimate the divergence time (Rosenberg and Feldman 2002). Similarly, population growth decreases genetic differentiation between populations, thus if not taken into account, divergence time may also be underestimated. The IM model allows gene flow to occur and assumes that the 2 populations could increase after the divergence, from a proportion s of the ancestral population. Therefore, divergence/introgression time estimates are not a priori expected to be underestimated from the IM analysis performed in this study.
Subdivision within populations (or species), with low gene flow among demes, tends to increase the effective population size of each population, thus decreasing genetic divergence between population (Wright 1931; Wakeley 2000). Therefore, if population subdivision is not accounted for, like in the IM model, isolation between populations (or speciation) will seem more recent and migration rates among populations higher. It should be noted, however, that in our study, population subdivision within the Chinese rhesus macaque sample is limited (Fis = 0.07; see also the STRUCTURE analysis) and its impact on the migration rate estimate between species may not be as serious as the one generated, for instance, by microsatellite homoplasy.
Microsatellite loci show a substantial level of homoplasy because of a high mutation rate and recurrent reverse mutations characteristics of the mutation model; this characteristic often leads to underestimate population genetic diversity, structure, and time estimates when these are actually substantial (Balloux and Lugon-Moulin 2002; Estoup et al. 2002). Thus, microsatellite homoplasy is the phenomenon most likely to affect demographic parameters estimated from genetic data of the 2 macaque species, independently of the demographic model. Therefore, we want to emphasize that the population size and divergence/introgression time estimates given hereafter should be considered as lower bounds and migration rate estimates as upper bounds.
Effective Population Sizes
We reported high levels of heterozygosity in the nuclear autosomal genome of these 2 taxa (He = 0.80) as well as on the X (0.80 and 0.81) and the Y (0.80 and 0.79) chromosomes. Such values imply high effective population sizes. Indeed, the effective population size was estimated at 24 600 Chinese rhesus macaque individuals and 11 800 Indo-Chinese long-tailed macaque individuals. However, in a recent study, the Chinese rhesus macaque population was estimated at 240 000 individuals based on 1467 SNPs genotyped on 9 individuals from 3 distant locations in China (Hernandez et al. 2007). The sampling scheme and the large amount of SNPs could explain this difference. Nonetheless, estimating precisely effective population size beyond thousands of individuals from genetic data is difficult because of the decreasing impact of genetic drift. Overall, the high genetic diversity found in the nuclear genome of rhesus and long-tailed macaques is in agreement with a high mtDNA polymorphism previously found in these species (Tosi et al. 2002, 2003; Smith and McDonough 2005; Smith et al. 2007; Blancher et al. 2008). Despite the effect of microsatellite homoplasy, the high genetic diversity and effective population sizes estimated in this study indicate that both Chinese rhesus macaque and Indo-Chinese long-tailed macaque show large and increasing populations, the Chinese rhesus macaque population being the larger.
Genetic Structure and Gene Flow: Characteristics and Consequences
The interspecific genetic differentiation between Chinese rhesus macaque and Indo-Chinese long-tailed macaque was lower (Fst = 0.02, Rst = 0.07) than that estimated between different long-tailed macaque populations using the same microsatellite markers (Fst and Rst > 0.10, Bonhomme et al. 2007, 2008) and thus not representative of the pattern to be expected from an interspecific comparison. Although weak, this genetic differentiation was significant, due to allelic frequency differences.
The STRUCTURE analysis from microsatellite data specified the genetic structure estimated from F and R statistics. The Chinese rhesus macaque conforms to a highly homogeneous gene pool that contributes substantially to the current Indo-Chinese long-tailed macaque genetic makeup, indicating that Chinese rhesus macaque has introgressed Indo-Chinese long-tailed macaque. Thus, it appears that the Indo-Chinese long-tailed macaque is mainly a hybrid population with a variable proportion of membership across individuals. In addition, Chinese rhesus macaque contributes equally to the genetic makeup of Indo-Chinese long-tailed macaque whether or not admixture between the 2 groups is assumed to still occur. This pattern clearly suggests that the hypothesis of a strictly contemporary introgression is unlikely, contrary to a more ancient introgression.
Unidirectional and male-specific gene flow from the Chinese rhesus macaque to the Indo-Chinese long-tailed macaque was inferred from the IM model coalescent simulations, without samples from the contact zones. This introgression seems to occur at a maximum rate of 10 effective migrants per generation, taking into account microsatellite homoplasy. However, most probably it was not constant since the divergence of the 2 species, but concentrated during a short period of time as suggested by the weak variance across loci of the mean time of migration rate (see last section). The actual number of migrants at each generation is probably higher because this value was estimated from genetic data (i.e., migrant individuals effectively reproducing in the hosting population that receives them).
These results are in agreement with the sex-biased dispersal of macaques (Pusey and Packer 1987) and with the first molecular evidence of male-mediated introgression between these species (Tosi et al. 2002). Furthermore, the pattern of genetic structure and the unidirectional gene flow inferred reflect an extensive, while probably not constant, past genetic exchange between the 2 taxa. As a consequence, nuclear genes from rhesus macaque currently contribute significantly to most of the Indo-Chinese long-tailed macaque gene pool. The admixture between these species may have several consequences.
The first consequence is related to the taxonomy of Indo-Chinese long-tailed macaque. We showed that rhesus macaque nuclear genes are introgressing far beyond the current contact zones of the 2 species, thus spreading over the Indo-Chinese long-tailed macaque population. Morphological variants, however, seem restricted to the contact zone (Fooden 1964, 1997). No such variants may be detected in animals living beyond these contact zones because of repeated recombination that fragments the polygenic complex required for their phenotypic expression (Tosi et al. 2002). Another issue is the overall pattern of allele sharing between long-tailed macaque and rhesus macaque. Street et al. (2007) revealed SNPs sharing between regional long-tailed macaque and rhesus macaque populations sometimes geographically distant (i.e., Indian rhesus macaque and Indonesian long-tailed macaque). This pattern is most likely due to ancestral polymorphism and/or differential lineage sorting at nuclear genes. Some studies have attempted to resolve phylogenetic relationships among Asian macaque species and found several incongruences explained by these phenomena (Deinard and Smith 2001; Tosi et al. 2003). Such phenomena may obscure a pattern of low genetic structure due to gene flow. Therefore, a survey of shared nuclear SNPs would be complementary to microsatellite data in order to disentangle allele sharing due to ancestral polymorphism/incomplete lineage sorting and allele sharing due to gene flow. Such an approach would help to define a true "hybrid" status for the Indo-Chinese long-tailed macaque. Genetic data from Tosi et al. (2002) and our study suggest that long-tailed macaque living throughout Indochina—north of the Kra Isthmus (peninsular Thailand)—could receive a new taxonomic designation reflecting its current genetically admixed status. Nevertheless, such a taxonomic revision it is contingent on future results of morphological and other genetic analyses.
Introgression also has evolutionary consequences. Introgression from one species to another may favor the breaking of coadapted genes by recombination, leading to a lower fitness of the introgressed taxon (here, the Indo-Chinese long-tailed macaque population) for particular phenotypic traits. We have previously observed that the Indo-Chinese long-tailed macaque population is the only one in this species to show a complete lack of LD between microsatellite markers of the major histocompatibility complex (MHC), a genomic region involved in the immune response against pathogens (Bonhomme et al. 2007). Such a lack of linkage between genes of the same chromosomic region can be explained by ancient recombination between 2 series of haplotypes belonging to 2 population (or species) stocks (Allendorf et al. 2001). Consequently, a very recent introgression between the 2 species could also be excluded from patterns of LD. Anyhow, the breaking of MHC allelic combinations (haplotypes) could have important consequences on the fitness of long-tailed macaque individuals originating from the Indochina, regarding endemic pathogens. Conversely, if genetic differences between species are limited, introgression may increase the fitness of the hybrids (heterosis effect). Whether the breaking of coadapted gene systems or the heterosis effect could be favored by this introgression remains an issue to be addressed in the future.
Finally, nonnegligible consequences might be expected from a biomedical point of view. Because Indo-Chinese long-tailed macaque shares genes with Chinese rhesus macaque, the phenotypic responses of individuals of the 2 taxa to specific biomedical experiments might be correlated. Thus, experimental designs should take into account putative interspecific phenotypic similarities due to gene sharing by introgression.
Divergence and Introgression Time Estimates
The IM model, run with the microsatellite data set, showed highly informative and unambiguous marginal posterior distributions of the demographic parameters, especially the distribution of the divergence time. Using a widely accepted mutation rate of 5 x 10–4 for microsatellite loci, the ML divergence time between rhesus and long-tailed macaque was estimated at 43 500 years (87 000 years assuming a maximum generation time of 10 years). Due to homoplasy in microsatellite loci, this value can be taken as a sort of lower bound for the divergence time between the 2 species. In the same way, a higher bound estimated from sequence data could be between 1.6 and 2.5 Ma (Purvis 1995; Hayasaka et al. 1996; Tosi et al. 2003; Raaum et al. 2005; Steiper and Young 2006). Despite the effect of homoplasy, our divergence time estimate takes into account variation in the ancestral population, which is more reliable than the commonly used estimate of the average time of the ancestral sequence from pairs of sequences. For chimpanzee species and using the IM model with sequence data, Won and Hey (2005) also found more recent divergence times, namely half the one generally estimated using sequence data. Here, we used microsatellite markers as opposed to studies that attempted to infer divergence times with sequence data (Purvis 1995; Hayasaka et al. 1996; Tosi et al. 2003; Raaum et al. 2005; Steiper and Young 2006). The bigger difference we obtained thus suggests the use of sequence data with the IM model, though the actual divergence time is expected to be somewhere in between.
Considering the same mutation rate for microsatellite data, the mean time of migration rates becomes 3400 years (6800 years assuming a maximum generation time of 10 years). For the same reason as mentioned above, the true time at which most of the introgression occurred might in fact be more ancient. A period of forest regression, from the last glacial maximum 18 000 years BP to interglacials around 6000 years BP, might have been propitious to the hybridization of dispersing male rhesus macaques, that moved southward from China, with female long-tailed macaques in Indo-Chinese tropical forest refugia such as Dawna Range (Burma, Thailand) and the Annamitic cordillera in Vietnam (Eudey 1980; Kershaw et al. 2001; Pickett et al. 2004). Indeed, some rhesus macaque populations may have found more favorable habitat conditions in such refugia, despite the fact that they can be found in a variety of habitats such as temperate semideserts, dry, mixed deciduous, and temperate forests (Fooden 2000). By contrast, Indo-Chinese long-tailed macaque, more adapted to tropical rainforest, river, and mangrove systems (Fittinghoff and Lindburg 1980; Wheatley 1980), might have densely aggregated around such refugia.
Although SNPs data show less homoplasy than microsatellite data, they potentially retain more ancestral polymorphism and are subjected to incomplete lineage sorting. Therefore, a multilocus approach combining SNPs and microsatellite data would be helpful to provide more precise estimates of demographic parameters in the frame of the IM model. Especially, such an approach would help to refine the estimation of the contribution of Chinese rhesus macaque to the Indo-Chinese long-tailed macaque gene pool.
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Funding |
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European Commission, QLRI-CT-2002-01325 INPRIMAT (Research Infrastructure to Promote Molecular Biology) to this research and M.B.; French Ministry of Research grant (contract EA3034) to A.B.; the Université Paul Sabatier (Action Spécifique de l'UPS - funds).
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Acknowledgments |
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We thank Stéphanie Despiau and Béatrice Atlan for their excellent technical assistance and Virginie Vervoort and Juli Broggi for editing the manuscript.
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Footnotes |
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Corresponding Editor: William Murphy
Received April 22, 2008
Revised September 26, 2008
Accepted September 26, 2008
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