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Genetics. Feb 2009; 181(2): 593–606.
PMCID: PMC2644949

Recombination and Speciation: Loci Near Centromeres Are More Differentiated Than Loci Near Telomeres Between Subspecies of the European Rabbit (Oryctolagus cuniculus)


Recent empirical and theoretical studies suggest that regions of restricted recombination play an important role in the formation of new species. To test this idea, we studied nucleotide variation in two parapatric subspecies of the European rabbit (Oryctolagus cuniculus). We surveyed five loci near centromeres, where recombination is expected to be suppressed, and five loci near telomeres, where recombination is expected to be higher. We analyzed this multilocus data set using a divergence-with-gene flow framework and we report three main findings. First, we estimated that these subspecies diverged ~1.8 MYA and maintained large effective population sizes (O. c. algirus Ne ≈ 1,600,000 and O. c. cuniculus Ne ≈ 780,000). Second, we rejected a strict allopatric model of divergence without gene flow; instead, high rates of gene flow were inferred in both directions. Third, we found different patterns between loci near centromeres and loci near telomeres. Loci near centromeres exhibited higher levels of linkage disequilibrium than loci near telomeres. In addition, while all loci near telomeres showed little differentiation between subspecies, three of five loci near centromeres showed strong differentiation. These results support a view of speciation in which regions of low recombination can facilitate species divergence in the presence of gene flow.

UNDERSTANDING the conditions that give rise to new species is an important topic in evolutionary biology. In the classic allopatric model of speciation, divergence occurs in geographic isolation, and, after secondary contact, gene flow is impeded (Mayr 1963). However, in the last few years a large body of literature focusing on patterns of gene flow via interspecific hybridization has demonstrated that introgression between young species can be quite common (Rieseberg et al. 1999; Machado et al. 2002; Saetre et al. 2003; Stump et al. 2005; Putnam et al. 2007; Yatabe et al. 2007; Teeter et al. 2008). One clear result to emerge from this work is that levels of differentiation vary across the genome. While some regions of the genome can cross species boundaries, others, despite hybridization, are preserved from introgression. The consequence is semipermeable species boundaries (Endler 1977; Caisse and Antonovics 1978; Barton 1979; Bengtsson 1979; Wu 2001), in which the movement of genomic regions between species depends on their fitness effects or the fitness effects of linked regions (Barton and Hewitt 1989; Harrison 1990).

Recent studies have demonstrated that genomic regions harboring chromosomal rearrangements show less admixture between species than colinear regions (e.g., Rieseberg et al. 1999; Machado et al. 2002, 2007; Feder et al. 2003; Noor et al. 2007). Moreover, genes involved in reproductive isolation sometimes map preferentially to rearranged regions (Noor et al. 2001). These observations led several authors to propose models of speciation where regions of low recombination represent islands of differentiation that facilitate or maintain species identity in the face of gene flow (Noor et al. 2001; Rieseberg 2001; Navarro and Barton 2003). Rieseberg's (2001) model is based on the combined effects of multiple isolation genes that are held together on a single haplotype, while the model of Noor et al. (2001) is based on the asymmetric nature of Dobzhansky–Muller incompatibilities and their potential to impede introgression when two loci with opposite asymmetries are located within a single nonrecombining region. The model of Navarro and Barton (2003), in contrast, is based on coadapted gene complexes held together by the absence of recombination (see also Kirkpatrick and Barton 2006). These models differ in many ways but share the common feature that the effects of genes involved in isolation are extended in regions with chromosomal rearrangements due to decreased recombination (reviewed in Butlin 2005). Besides structural rearrangements, the role of other regions of restricted recombination in speciation is far less clear. However, nonstructural chromosomal features, such as proximity to the centromere, where recombination is often suppressed, have also been associated with lower rates of gene flow (Stump et al. 2005). While both theoretical and empirical studies suggest that the higher differentiation in low-recombination regions might be caused by a higher density of genes contributing to reproductive isolation in such regions, greater differentiation in regions of low recombination could also arise because genes involved in reproductive isolation influence longer neutral regions of the genome in regions of reduced crossing over.

Surprisingly, with the exception of the house mouse (e.g., Boursot et al. 1993; Britton-Davidian et al. 2005) and to a lesser extent primates (Won and Hey 2005; Patterson et al. 2006), the genetics of speciation have received relatively little attention in mammals. The European rabbit (Oryctolagus cuniculus) is a good mammalian system for studying the genetic architecture of speciation under a model of divergence with gene flow. It is composed of two parapatric subspecies: O. cuniculus algirus, distributed in the southwestern part of the Iberian Peninsula, and O. cuniculus cuniculus in the northeastern part of the Iberian Peninsula (Figure 1). Although there are slight morphological differences between the two forms in craniometric measurements (Sharples et al. 1996) and body size (Villafuerte 2002), this intraspecific taxonomy is mainly based on patterns of genetic differentiation (e.g., Branco et al. 2000; Geraldes et al. 2006). Crosses between these subspecies produce viable hybrids, and the fertility of these hybrids is under investigation. Previous work showed contrasting patterns of differentiation across multiple markers, and the extensive sharing of genetic variation at some loci has been interpreted as evidence of gene flow following secondary contact (Geraldes et al. 2006, 2008; Ferrand and Branco 2007). In particular, Geraldes et al. (2006) described a striking contrast between two centromeric and two telomeric loci on the X chromosome. Levels of gene flow were low at the two loci near the centromere and high at the two loci near the telomere. These authors suggested that the centromeric region of the X chromosome may be involved in reproductive isolation between the two subspecies.

Figure 1.
Geographical location of the populations used in this study. Dark and light shading indicates the range of O. c. algirus and O. c. cuniculus, respectively. The putative hybrid zone separates both ranges (adapted from Geraldes et al. 2008). Numbers correspond ...

Here, we report the first large-scale survey of patterns of polymorphism and divergence at multiple autosomal regions in the European rabbit. To test the role of recombination on levels of differentiation we surveyed five loci near centromeres (hereafter “centromeric loci”), where recombination is expected to be lower (Choo 1998; Kong et al. 2002), and five loci near telomeres (hereafter “telomeric loci”), where recombination is expected to be higher. Additionally, using a divergence–population-genetics framework (Hey and Nielsen 2004, 2007), we estimated relevant demographic parameters that provide insight into the genetic architecture of speciation in this group. We address three main questions: (1) What are the levels and patterns of genetic variation on the autosomes in wild rabbit subspecies and what are the inferred effective population sizes?, (2) When did these subspecies start to diverge and can we reject a strict allopatric model without subsequent gene flow?, and (3) Does the physical location of loci (near centromeres vs. near telomeres) correlate with patterns of genetic differentiation, as predicted by recent speciation models?


Samples and sampling strategy:

We surveyed 10 individuals from each of eight populations, for a total of 80 individuals (Figure 1). Populations were divided into two major groups on the basis of the mtDNA phylogeographical division described by Branco et al. (2000): (1) the southwestern part of the Iberian Peninsula, corresponding to the subspecies O. c. algirus (n = 40), and (2) the northeastern part of the Iberian Peninsula, corresponding to the subspecies O. c. cuniculus (n = 40). One individual of Lepus granatensis was sampled to provide an outgroup. Genomic DNA was isolated from tissues, using a standard phenol-chloroform DNA extraction (Sambrook and Russell 2001).

Loci, DNA amplification, and sequencing:

We investigated patterns of genetic diversity in wild rabbits by resequencing 10 effectively unlinked autosomal loci. The loci consisted entirely of noncoding DNA, either intronic or 5′ flanking (Table 1). Five loci were selected near centromeres and five near telomeres (Figure 2) from genes mapped on the rabbit cytogenetic map (Chantry-Darmon et al. 2005).

Figure 2.
Chromosome locations of the 10 autosomal regions used in this study. Arrows indicate the position of the centromere for each chromosome. Modified from Chantry-Darmon et al. (2005).
Chromosome location, position in the gene, and length of the regions sequenced

Given the high levels of nucleotide diversity previously described for the European rabbit (Geraldes et al. 2006), there is a strong possibility of mutations occurring in priming sites, creating allelic dropout. To detect such situations we amplified two overlapping amplicons, one contained within the other, for each segment. The products were sequenced in both directions. We used additional primers for individuals heterozygous for multiple-indel polymorphisms and when instances of allele-specific PCR or allele-specific sequencing were detected. All PCR and sequencing primers were designed from the rabbit genomic sequence and are provided in supplemental Table 1. Sequences were edited, aligned, and assembled using phred/phrap/consed/polyphred (Nickerson et al. 1997; Ewing and Green 1998; Ewing et al. 1998; Gordon et al. 1998) together with auxiliary shell scripts and Perl programs kindly provided by August Woerner. Manual adjustments were further performed in some contigs, using Bioedit (Hall 1999). Individuals or positions with >15% of missing data were eliminated from the data set. Sequences have been deposited in GenBank under accession nos. FJ000560FJ001233.

Nucleotide variation, recombination, and neutrality tests:

Haplotypes were assigned by the computer program PHASE (Stephens et al. 2001; Stephens and Donnelly 2003). For each data set, we applied the algorithm five times with different seeds for the random number generator, and we checked for consistency of the results across independent runs.

Most standard population-genetic analyses were carried out using the program SITES (Hey and Wakeley 1997). All summary statistics were obtained for the global sample as well as for each subspecies independently. Indels were not included in the analyses. We estimated the neutral mutation parameter 4Neμ (where Ne is the effective population size and μ is the mutation rate per site per generation) by calculating Watterson's (1975) θw, the proportion of segregating sites in a sample, and π (Nei 1987), the average number of pairwise differences per sequence in a sample. Several descriptors of the amount of linkage disequilibrium (LD) were obtained. The population recombination parameter (R = 4Nec, where c is the recombination rate per generation) between adjacent sites was estimated using γ (Hey and Wakeley 1997) and ρ (Hudson 2001). γ is a maximum-likelihood estimator developed using a coalescent model for a sample of four DNA sequences with recombination. ρ is adapted to a finite-sites model and is estimated by means of a composite-likelihood method, as implemented in the LDhat 2.0 package (McVean et al. 2002). We also estimated the minimum number of recombination events (Rm) in the sample (Hudson and Kaplan 1985). Finally, we assessed the significance of LD through pairwise comparisons of polymorphic sites, using a chi-square test excluding individuals with missing data, using DnaSP 4.50.3 (Rozas et al. 2003).

We tested for deviations from neutrality in allele-frequency distributions, using Tajima's (1989) D and Fu and Li's (1993) D*. Significance of Tajima's D and Fu and Li's D* values was assessed by coalescent simulations, using DnaSP 4.50.3 (Rozas et al. 2003). We ran 104 coalescent simulations of the standard neutral model with the same number of chromosomes and base pairs as in the actual data and with the θW and population recombination rate equal to the estimated values. We also used the HKA test (Hudson et al. 1987) to evaluate heterogeneity in the ratio of polymorphism to divergence across loci under a neutral model. We compared ratios of polymorphism within rabbit to divergence between rabbit and Lepus. We performed three 10-locus tests, using polymorphism for both the two subspecies together and separately by means of the HKA software (http://lifesci.rutgers.edu/~heylab).

Genetic differentiation and gene flow:

We assessed genetic differentiation in several ways. We estimated the fixation index (FST) from which we inferred the number of migrants per generation (Nm), and we estimated the net nucleotide divergence (Da, Nei 1987) between O. c. algirus and O. c. cuniculus. In addition, we calculated the average pairwise differences (Dxy, Nei 1987) between all rabbit samples and L. granatensis. We also calculated fixation indexes within and between subspecies in an analysis of molecular variance (AMOVA) (Excoffier et al. 1992), using the Arlequin genetics package (Schneider et al. 2000). Another way of looking at differentiation between groups is from a genealogical perspective. Phylogenetic relationships among alleles for each locus were reconstructed with the neighbor-joining method (Saitou and Nei 1987), using the program MEGA4 (Tamura et al. 2007). Bootstrap values were obtained after 1000 replicates (Felsenstein 1985).

Patterns of shared variation (see results) may be explained by shared ancestral polymorphism or recent gene flow; to distinguish between these hypotheses we used the LD method developed by Machado et al. (2002). This test looks at the difference (x = DSS − DSX) between the amount of LD that is observed among pairs of shared polymorphisms (DSS) and the average estimate among pairs of sites where one is shared between species and the other is an exclusive polymorphism (DSX). If shared polymorphisms are due to postdivergence gene flow, x will tend to be positive because of the short time available for recombination to break down associations in the recipient species. This test was applied using D′ (Lewontin 1964) as a measure of LD. L. granatensis was used to polarize LD. Statistical significance of the observed values of x was obtained by simulating data sets using the program WH (Wang et al. 1997).

Divergence population genetics:

We investigated an isolation-with-migration (IM) model and estimated relevant demographic parameters using the programs IM and IMa (Nielsen and Wakeley 2001; Hey and Nielsen 2004, 2007). IM and IMa are based on Markov chain Monte Carlo simulations of genealogies and they estimate the posterior probability density function for six model parameters (the population-split time, effective population size for the ancestral and current populations, and migration rates in both directions). Although these six parameters may give a good approximation to the demographic history of two diverging populations, there are also several important population genetic assumptions underlying the method. First, the method assumes that there are no other unsampled populations exchanging genes with the populations under study or with the ancestral population. Second, it assumes selective neutrality. Third, the model assumes a particular mutational model (in this case, the infinite-sites model; Kimura 1969). Finally, it assumes free recombination between loci and no recombination or gene conversion within loci. Because of this last assumption, we used the program IMgc (Woerner et al. 2007) to obtain the longest region without four gametic types for each locus. We simulated the data three times to check for convergence. To facilitate mixing of the Markov chains we used Metropolis coupling. In this Metropolis-coupled version of the algorithm multiple linked chains are run simultaneously and disparate starting points and heating are used to improve sampling efficiency. For each simulation we ran 10 million steps, using 15 chains and a geometric heating scheme. Output from IM is expressed in units of 4Neμ and t0μ, where μ is the mutation rate per generation and t is the divergence time in generations. To estimate the effective population size in numbers of individuals for each subspecies (Ne) and the time since population split in years, we calculated μ for each locus, assuming that the divergence time for the Oryctolagus–Lepus comparison is 11.8 MYA (Matthee et al. 2004). We then estimated the neutral mutation rate as μ = D/2t1, where D is the estimated Da (Nei 1987) between Oryctolagus and Lepus for each locus. We assumed a generation time of 1 year and we calculated the geometric mean of the locus-specific mutation rates.


Multilocus patterns of polymorphism and recombination:

We collected polymorphism data in O. c. algirus and O. c. cuniculus for 10 autosomal regions. This data set contained ~12 kb of noncoding DNA sequence for 52–72 chromosomes in O. c. algirus and 56–80 chromosomes in O. c. cuniculus. The length of each aligned locus varied between 925 and 1488 bp. Outgroup sequence of L. granatensis was obtained for 9 of the 10 loci. We could not amplify UD14 in Lepus despite using multiple combinations of primers.

Levels of nucleotide variation were high both in the total sample and within each subspecies (Table 2). In the total sample, values of π (Nei 1987) ranged from 0.383 to 1.373% (average π = 0.836). The values of θw (Watterson 1975) were even higher, ranging from 1.074 to 2.264% (average θw = 1.227). Within subspecies, the genetic diversity was higher in O. c. algirus (average π = 0.746, average θw = 1.100) than in O. c. cuniculus (average π = 0.662, average θw = 0.848). This difference was significant for θw (Wilcoxon's signed rank test, P = 0.005) but not for π (Wilcoxon's signed rank test, P = 0.1141).

Analyses of polymorphism, frequency spectrum tests of neutrality, and recombination in O. c. algirus (alg) and O. c. cuniculus (cun)

A high proportion of rare polymorphisms was apparent at each locus, as reflected in the strongly negative Tajima's D (Tajima 1989) and Fu and Li's D* (Fu and Li 1993) (Table 2). This was observed both for the complete data set (average Tajima's D = −0.980, average Fu and Li's D* = −1.451) and for each subspecies separately (O. c. algirus, average Tajima's D = −0.996, average Fu and Li's D* = −1.000; O. c. cuniculus, average Tajima's D = −0.618, average Fu and Li's D* = −0.821). Significantly negative values of one or both statistics were observed at several individual loci (Table 2). We also observed significantly negative values of Tajima's D for each subspecies in multilocus tests (P < 0.0001 for O. c. algirus and P = 0.024 for O. c. cuniculus). A 10-locus HKA test (Hudson et al. 1987) indicated no significant heterogeneity in levels of polymorphism and divergence within subspecies as well as in the global data set (P > 0.10 for all three comparisons).

We found some evidence of recombination at each locus (Rm > 1 for each), although there was considerable variation among loci in estimates of the population recombination parameter (Table 2). O. c. algirus exhibited slightly but not significantly higher average values of the population recombination parameter than O. c. cuniculus for both γ and ρ (γ = 2.35% and ρ = 4.54% for O. c. algirus; γ = 2.10% and ρ = 1.48% for O. c. cuniculus; Wilcoxon's signed rank test, P > 0.05 for both). This trend is consistent with the higher values of nucleotide variation observed in O. c. algirus and may reflect a higher Ne in this subspecies. We also evaluated LD within each locus, using a chi-square test for independence between sites. In O. c. algirus, 1464 of 6771 pairwise comparisons (21.6%) between nonsingleton pairs of polymorphisms within loci showed statistically significant LD; with the Bonferroni correction for multiple comparisons, there were 529 (7.8%) significant associations. In O. c. cuniculus we found a higher percentage of within-locus nonrandom associations between pairs of polymorphic sites: 1609 of 5046 pairwise comparisons (31.9%) were significant, and 739 (14.6%) were significant with the Bonferroni correction.

The current genetic (Chantry-Darmon et al. 2006) and physical maps for the rabbit are not sufficiently detailed to estimate regional variation in the rate of crossing over. To test the hypothesis that recombination is suppressed near centromeres compared to telomeres in rabbits, as seen in other mammals (e.g., Kong et al. 2002), we compared the population recombination parameter for loci near centromeres and loci near telomeres. The mean values of both γ and ρ calculated for both subspecies together were significantly lower in centromeric loci (γ = 0.73%, ρ = 0.57%) than in telomeric loci (γ = 4.25%, ρ = 4.87%; Mann–Whitney U-test, P = 0.016 in both tests). Within O. c. algirus, both estimators were significantly lower in centromeric loci (γ = 0.63%, ρ = 0.69%) compared to telomeric loci (γ = 3.90%, ρ = 8.18%; Mann–Whitney U-test, P < 0.05 for each). Within O. c. cuniculus, γ was significantly lower in centromeric loci (γ = 0.49%) compared to telomeric loci (γ = 3.71%; Mann–Whitney U-test, P = 0.008) but the result was not significant for ρ (ρ centromeric = 0.48%, ρ telomeric = 2.47%; Mann–Whitney U-test, P = 0.095). Mean Rm values were also significantly lower at centromeric loci relative to telomeric loci in both O. c. algirus (Rm centromeric = 3.8, Rm telomeric = 10; Mann–Whitney U-test, P = 0.032) and O. c. cuniculus (Rm centromeric = 4.2, Rm telomeric = 8.2; Mann–Whitney U-test, P = 0.032), although these differences were not significant in the overall sample (Rm centromeric = 5.4, Rm telomeric = 10.4; Mann–Whitney U-test, P = 0.075).

Under neutrality, the ratio ρ/θ gives a measure of the relative contribution of recombination and mutation in a given locus (ρ/θ = 4Nec/4Neμ = c/μ). The mean values for centromeric loci (ρSitesw = 0.63) were significantly lower than those for telomeric loci (ρSitesw = 3.09; Mann–Whitney U-test, P = 0.016). The lower ratio at centromeric loci could, in principle, have two explanations: it could be due to either stronger LD or higher mutation rates close to the centromeres, or some combination of these factors. We estimated mutation rates (μ) per generation per site for centromeric loci (μ = 1.622 × 10−9) and for telomeric loci (μ = 1.662 × 10−9). The similarities of these estimates (Mann–Whitney U-test, P = 0.556) suggest that lower recombination, rather than higher mutation, is responsible for the patterns seen at centromeric loci.

We were also interested in evaluating the possibility that regions of low recombination might exhibit lower levels of polymorphism, as seen in other species (e.g., Begun and Aquadro 1992). To test this idea, we divided θw by divergence to Lepus (Dxy) to correct for possible mutation rate differences among regions and compared centromeric and telomeric loci. We did this using θw from the entire species as well as from the average within each subspecies. When θw was calculated from both subspecies together, the ratio θw/Dxy was slightly, but significantly lower at centromeric loci (0.26) compared to telomeric loci (0.31) (Mann–Whitney U-test, P = 0.016). When θw was calculated from the average within each subspecies, the ratio θw/Dxy was also significantly lower in centromeric loci compared to telomeric loci both in O. c. algirus (centromeric θw/Dxy = 0.23; telomeric θw/Dxy = 0.30; Mann–Whitney U-test, P = 0.016) and O. c. cuniculus (centromeric θw/Dxy = 0.18; telomeric θw/Dxy = 0.22; Mann–Whitney U-test, P = 0.016). Additionally, we tested the neutral prediction of equal ratios of polymorphism to divergence between centromeric loci and telomeric loci, using the HKA test. We could not reject a neutral model using either polymorphism within the entire species or that within either subspecies (P > 0.10 for each). These analyses suggest at most a modest reduction in levels of polymorphism at centromeric compared to telomeric loci. Finally, we compared values of Tajima's D and Fu and Li's D* among centromeric and telomeric loci. Both statistics were less negative at centromeric loci (Tajima's D = −0.877, Fu and Li's D* = −1.256) compared to telomeric loci (Tajima's D = −1.082, Fu and Li's D* = −1.646), although not significantly different (Mann–Whitney U-test, P > 0.5 for each).

Divergence and LD test of gene flow:

Patterns of differentiation were highly variable among loci (Table 3). None of the telomeric loci showed strong differentiation between subspecies. The centromeric loci, in contrast, were heterogeneous. Two centromeric loci (CYTC and PRL) showed little differentiation, while three centromeric loci (ATP12A, MGST3, and STAG1) showed high levels of differentiation. We note that these patterns are not associated with the allele-frequency distribution as measured by Tajima's D (Table 2). For example, we observed loci showing high levels of differentiation and loci showing low levels of differentiation among those showing no significant departures from a neutral equilibrium distribution (Tables 2 and and3).3). The mean FST for centromeric loci was 30.1% and the mean value for telomeric loci was 6.18%. In particular, FST-based inferences of Nm at three loci were <<1. All three of these loci are near centromeres (ATP12A, MGST3, and STAG1). In contrast, the inferred number of migrants per generation for all telomeric loci was >>1. Similarly, AMOVA analyses (Excoffier et al. 1992) showed that in centromeric genes a higher average proportion of the genetic variation is partitioned between subspecies (28.4%) while for all telomeric loci only a small amount (<9%) of the variation segregated between subspecies. The mean net divergence (Nei 1987) for centromeric loci (Da = 0.349%) was considerably but not significantly higher than that for telomeric loci (Da = 0.054%; Mann–Whitney U-test, P > 0.05).

Genetic differentiation and migration between O. c. algirus (alg) and O. c. cuniculus (cun) at 10 autosomal and 4 X-linked loci

Another way of examining differentiation is by looking at the phylogeny of alleles for each gene (Figure 3). Striking contrasts were observed among loci. While for two of the centromeric loci (STAG1 and MGST3) there was clear phylogenetic differentiation among subspecies, for the other eight genes there was little or no geographic pattern in the clustering of alleles.

Figure 3.
Haplotype variation illustrated as neighbor-joining trees for each of the 10 autosomal loci. Because recombination events were detected for all loci in our data set, the trees represent overall similarity between the haplotypes. Portions of each gene ...

The lack of concordance between phylogeny and geography in recently diverged taxa may be the consequence of either shared ancestral polymorphism or gene flow following species divergence. We evaluated a strict allopatric mode of speciation with no gene flow, using the test of Machado et al. (2002) based on patterns of intragenic LD as implemented in the program WH (Wang et al. 1997). The maximum input for WH is a total sample size of 32 chromosomes per locus; therefore, we generated three random data sets with the appropriate sample size, and three independent simulations were performed. Supplemental Table 2 shows the observed and simulated values of x for each locus, calculated using D′ (Lewontin 1964). Across the different runs the mean observed values of x were significantly elevated relative to simulated values for O. c. algirus. In O. c. cuniculus, the mean observed values of x were significantly elevated relative to simulated values for two of the three runs. For each locus separately, the observed values of x were consistently positive in the two subspecies and in a number of genes were significant in at least one of the independent runs (supplemental Table 2). This pattern can be visualized by looking at the genealogies in Figure 3 or the tables of polymorphism in supplemental Figure 1, where identical haplotypes are shared between subspecies. Taken together, these results suggest that gene flow has occurred in both directions with higher gene flow from O. c. cuniculus to O. c. algirus.

Estimates of ancestral demographic parameters using an isolation-with-migration model:

Using a divergence-with-gene-flow framework (Hey and Nielsen 2004, 2007), we obtained maximum-likelihood estimates (MLE) of effective population sizes for both extant and ancestral populations, migration rates in both directions, and time of divergence. We were able to achieve adequate mixing of the Markov chains, and independent runs converged on approximate marginal posterior probability distributions for all parameters incorporated in the model (Figure 4). Ne for O. c. algirus (1,598,056) and Ne for O. c. cuniculus (780,367) were estimated to be larger than Ne for the ancestral population (469,122) (Table 4). We estimated the time since divergence between the two subspecies to be ~1.8 MYA. Both migration rate parameters inferred from the model indicate moderate to high levels of gene flow. A model of strict allopatry with no gene flow was rejected when compared in a likelihood framework to a model allowing gene flow in both directions (P < 0.001). Inferred gene flow was higher from O. c. cuniculus to O. c. algirus (2Nm = 1.498) than in the opposite direction (2Nm = 0.762). One of the assumptions of this method is selective neutrality. To verify whether the results were affected by skews in the allele-frequency spectrum, we redid the IM analysis excluding those loci that showed significant deviations from neutral expectations. The results obtained were nearly identical (O. c. algirus Ne = 1,278,610; O. c. cuniculus Ne = 825,743; ancestral population Ne = 394,255; t = 1,943,816; O. c. algirus 2Nm = 2.040; O. c. cuniculus 2Nm = 0.660). We also estimated population migration rates for each locus in each direction (Table 3). Not all of these estimates were recovered with confidence either because the tails of the distributions did not reach zero or were relatively flat. Nonetheless, the estimates were remarkably consistent with inferences of gene flow from estimates of FST. Estimates of 2Nm were generally lower for loci near centromeres compared to loci near telomeres (Table 3). Remarkably, estimates of 2Nm were >1 for each telomeric locus in at least one direction.

Figure 4.
Marginal posterior probability distributions (y-axis) for model parameters (x-axis). (A) Effective population size of O. c. algirus, O. c. cuniculus, and the ancestral population in numbers of thousands of individuals. (B) Divergence time between the ...
ML estimates (MLE) and 90% posterior density intervals (HPD) of demographic parameters between O. c. algirus (alg) and O. c. cuniculus (cun)


We studied sequence variation at 10 autosomal loci in wild populations of the European rabbit (O. cuniculus) and found that (1) levels of nucleotide variation are high and reflect large effective population sizes, (2) these subspecies diverged ~1.8 MYA with subsequent high levels of gene flow in both directions, and (3) centromeric loci are generally more differentiated and show higher LD than telomeric loci. This pattern is in agreement with recent speciation models that propose that regions of reduced recombination facilitate divergence in the presence of gene flow.

Levels and patterns of genetic variation and LD at autosomal loci in the European rabbit:

This is the first large-scale survey of sequence polymorphism at multiple autosomal loci in the European rabbit. We observed surprisingly high levels of nucleotide diversity: π was 0.746% in O. c. algirus and 0.662% in O. c. cuniculus. Nucleotide diversity in humans is on the order of 0.1% (Aquadro et al. 2001). In mice nucleotide diversity is approximately twice that seen in humans (Baines and Harr 2007). Surprisingly, the values reported here for two rabbit subspecies are closer to observed levels of nucleotide diversity in Drosophila melanogaster (Moriyama and Powell 1996). In rabbits, estimates of Ne were 1,600,000 for O. c. algirus and 780,000 for O. c. cuniculus. These estimates are more than an order of magnitude higher than in humans (Takahata 1993) and several times higher than in mice (Salcedo et al. 2007). It is important to bear in mind that estimates of Ne depend on estimates of μ that should be considered approximate owing to the uncertainty of generation length and time of divergence between Lepus and Oryctolagus.

The higher Ne estimated for O. c. algirus compared to O. c. cuniculus is reflected in higher levels of heterozygosity in the former. Our results are consistent in this regard with previous studies using mtDNA (Branco et al. 2002) and X-linked sequences (Geraldes et al. 2006), as well as with studies using allozyme (Ferrand and Branco 2007) and microsatellite variation (Queney et al. 2001). Additionally, levels of intralocus LD in our data set are lower in O. c. algirus than in O. c. cuniculus. Since LD at neutral sites is governed by 1/(4Nec), this also suggests that Ne in O. c. algirus is larger.

We also estimated Ne of the extant subspecies to be much higher than Ne of the ancestral population. Consistent with this change in Ne, we observed a significant skew in the frequency distribution of polymorphisms toward rare variants compared to the standard neutral expectations. The pattern is observed across loci in both subspecies and is suggestive of a common history of population growth, congruent with the phylogeographical scenario of a postglacial range expansion of the European rabbit proposed by Branco et al. (2002).

Our experimental design allowed us to compare levels of polymorphism and LD between different chromosomal regions. Levels of LD were strongly associated with physical location, with centromeric loci showing higher levels of LD than telomeric loci. This suggests that recombination is most probably suppressed at centromeric loci relative to telomeric loci as observed for other species (e.g., Kong et al. 2002). Further support for suppressed recombination near centromeres derives from the ratio ρ/θ. Since ρ = 4Nec and θ = 4Neμ, this ratio controls for differences in effective population size between regions. The observed ratio ρ/θ for telomeric loci is 3.09 and is similar to estimates in other outcrossing species such as Drosophila (Haddrill et al. 2005) and wild Zea mays (Wright et al. 2005). Strikingly, the ratio ρ/θ is sharply reduced at centromeric loci (ρ/θ = 0.63) despite similar estimates of mutation rate for both centromeric and telomeric loci.

Selection at linked sites may lower nucleotide diversity in genomic regions that experience less recombination (Maynard Smith and Haigh 1974; Charlesworth et al. 1993). Consistent with this prediction we observed slightly lower polymorphism scaled to divergence in centromeric loci compared to telomeric loci. This adds to a growing body of literature in several other species that shows lower levels of genetic variation in regions of reduced recombination (e.g., Begun and Aquadro 1992; Nachman et al. 1998).

The history of divergence and gene flow between O. c. algirus and O. c. cuniculus:

By using multiple loci sampled across the genome it is possible to estimate parameters that provide insight into the history of diverging populations. Using an isolation-with-migration framework we date the initial split between the two rabbit subspecies to be ~1.8 MYA. This estimate is consistent with published mtDNA (Branco et al. 2000) and X chromosome data (Geraldes et al. 2006) that place the divergence between the two subspecies during the Quaternary glaciations (Branco et al. 2000; Geraldes et al. 2006). This age of separation mirrors several estimates involving other Iberian taxa (reviewed in Gómez and Lunt 2007) and probably results from the influence of common historical biogeographic events (e.g., glaciations) on Iberian biota (Hewitt 2001).

Although the estimated divergence between O. c. algirus and O. c. cuniculus is old, several lines of evidence point to the occurrence of gene flow between these groups. First, by fitting an isolation–migration model we estimated high levels of gene flow in both directions, and these estimates were significantly different from zero. Second, we found significantly elevated values of the LD statistic x (Machado et al. 2002), reflecting stronger LD than expected in both subspecies compared to an isolation model with no gene flow. Third, there is full haplotype sharing at a number of the surveyed regions (Figure 3 and supplemental Figure 1). Given the high levels of recombination observed at some of the loci, identical haplotypes are probably due to recent instances of gene flow. The IM analysis also suggests that gene flow is asymmetric. Interestingly, higher gene flow seems to occur from the smaller population, O. c. cuniculus, to the larger population, O. c. algirus. This could be explained by higher vagility in O. c. cuniculus, by an asymmetric mate preference between the two subspecies, or by intrinsic incompatibilities in which backcrosses may have higher fitness in one direction than the other.

Mosaic nature of the rabbit genome with respect to gene flow:

The most notable aspect of our data is the heterogeneity observed among loci in patterns of differentiation between the two subspecies. This heterogeneity demonstrates the semipermeable nature of the rabbit hybrid zone and supports the idea of a mosaic genome with respect to gene flow (Geraldes et al. 2008). In particular, we observe strong differentiation at three of five centromeric loci, which experience less recombination, and little differentiation at all telomeric loci, which experience greater recombination.

This observation fits the predictions of several recent speciation models that suggest that regions of low crossing over might harbor a disproportionate share of loci involved in isolation (Noor et al. 2001; Rieseberg 2001; Navarro and Barton 2003). For example, in the model of Noor et al. (2001), alleles contributing to isolation initially arise throughout the genome, but, following secondary contact, are purged more easily if they reside in recombining regions but less easily if they reside in regions where recombination is suppressed. This model was based on experiments in which genes contributing to isolation between D. persimilis and D. pseudoobscura were mapped to small chromosomal rearrangements that differed between these species. Consistent with this model, Machado et al. (2002, 2007) showed a reduction in introgression in rearranged regions (with little recombination) compared to colinear regions (which can recombine freely). In sunflowers, some studies have revealed that rates of introgression were significantly reduced in rearranged regions relative to colinear regions (Rieseberg et al. 1999), while other studies failed to find such a pattern (Strasburg and Rieseberg 2008). Additionally, studies of the M and S forms of Anopheles gambiae, where differentiation appears to be limited to a few regions of the genome (Turner et al. 2005), have shown that two of three areas of reduced introgression map close to centromeres and recombination has been shown to be suppressed in those regions (Stump et al. 2005; Slotman et al. 2006). We also see less introgression in regions with little recombination, and the data presented here are consistent with similar data from the rabbit X chromosome (Geraldes et al. 2006). Overall, our observations in rabbit are consistent with models suggesting that regions of reduced crossing over favor divergence in the face of gene flow (Noor et al. 2001; Rieseberg 2001; Navarro and Barton 2003). Importantly, however, not all centromeric regions show reduced introgression. Our results thus help identify particular genomic regions that may contribute to reproductive isolation (i.e., near the centromeres of chromosomes 8, 13, and 14).

A second potential explanation for the higher differentiation in low-recombination regions is the increased likelihood of these regions being in LD with alleles contributing to reproductive isolation (rather than an enrichment for “isolation genes” in such regions). In other words, if genes contributing to isolation are evenly distributed across the genome, but recombination rates vary, the likelihood of a nonrandom association with an isolation gene is greater in regions of lower crossing over. According to this model, isolation genes might occur throughout the genome, but their effects will extend over a greater genomic distance when they occur in regions of low recombination.

It should be possible to distinguish between these two models using introgression lines (e.g., consomic strains). If genes contributing to isolation are found only in low-recombination regions, then only those regions should cause isolation phenotypes when introgressed. In contrast, if genes contributing to isolation are found throughout the genome, some introgression lines containing high-recombination regions should show isolation phenotypes.

A third explanation for the higher differentiation in low-recombination regions is that rates of lineage sorting differ between centromeric and telomeric loci. We observed a slightly lower θ/Dxy ratio at centromeric loci compared to telomeric loci, and this may reflect a smaller effective population size for centromeric loci. This effect is modest and probably cannot account for all of the differences in patterns of differentiation among loci. For example, the IMa analysis shows that gene flow has occurred, and the IM analysis provides evidence of lower gene flow at centromeric loci compared to telomeric loci (Table 3). Although ancestral polymorphism may still segregate it cannot explain why some regions remain differentiated despite high levels of admixture.

Finally, although we do not know whether the studied regions are in LD with the centromeres, we note that the observation of increased differentiation near centromeres might also be consistent with recent models of centromere evolution (Henikoff et al. 2001; Malik and Henikoff 2002). These authors suggest that rapid evolution of centromeric sequences could lead to higher rates of chromosomal nondisjunction in hybrids and reduced fertility. This model makes a simple, testable prediction: rates of nondisjunction are expected to be higher in F1's from crosses between subspecies compared to crosses within subspecies. Experiments to test this prediction are currently underway.


We thank R. Villafuerte and M. Delibes-Mateos for providing rabbit samples, P. Tarroso for help with the map in Figure 1, members of the Nachman lab for valuable discussions, and David Rand and two anonymous reviewers for valuable comments on the manuscript. This work was partially supported by a Fundação para a Ciência e a Tecnologia Ph.D. grant to M.C. (SFRH/BD/23786/2005), by a Research Project to N.F. (PTDC/BIA-BDE/72304/2006), and by National Science Foundation and National Institutes of Health grants to M.W.N.


Sequence data from this article have been deposited with the EMBL/GenBank Data Libraries under accession nos. FJ000560FJ001233.


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