Reduced MHC and neutral variation in the Galápagos hawk, an island endemic
© Bollmer et al; licensee BioMed Central Ltd. 2011
Received: 3 January 2011
Accepted: 25 May 2011
Published: 25 May 2011
Genes at the major histocompatibility complex (MHC) are known for high levels of polymorphism maintained by balancing selection. In small or bottlenecked populations, however, genetic drift may be strong enough to overwhelm the effect of balancing selection, resulting in reduced MHC variability. In this study we investigated MHC evolution in two recently diverged bird species: the endemic Galápagos hawk (Buteo galapagoensis), which occurs in small, isolated island populations, and its widespread mainland relative, the Swainson's hawk (B. swainsoni).
We amplified at least two MHC class II B gene copies in each species. We recovered only three different sequences from 32 Galápagos hawks, while we amplified 20 unique sequences in 20 Swainson's hawks. Most of the sequences clustered into two groups in a phylogenetic network, with one group likely representing pseudogenes or nonclassical loci. Neutral genetic diversity at 17 microsatellite loci was also reduced in the Galápagos hawk compared to the Swainson's hawk.
The corresponding loss in neutral diversity suggests that the reduced variability present at Galápagos hawk MHC class II B genes compared to the Swainson's hawk is primarily due to a founder event followed by ongoing genetic drift in small populations. However, purifying selection could also explain the low number of MHC alleles present. This lack of variation at genes involved in the adaptive immune response could be cause for concern should novel diseases reach the archipelago.
Genes at the major histocompatibility complex (MHC) are known for their high levels of polymorphism , and for their importance in initiating the adaptive vertebrate immune response by binding to foreign peptides and presenting them to T cells . Class I MHC molecules primarily bind to peptides derived from intracellular pathogens, while class II molecules are associated with extracellular pathogens. MHC variability is maintained through balancing selection, with parasite-mediated natural selection and MHC-dependent sexual selection being the most likely mechanisms . A number of lines of evidence indicate that MHC genes are under selection , including an excess of nonsynonymous mutations at the peptide-binding region  and the long-term retention of allelic lineages post-speciation (trans-species polymorphism; ). Discrepancies between population genetic structure at selectively neutral and MHC loci also provide evidence of selection [6, 7], because both neutral and MHC loci are affected by neutral forces (gene flow, genetic drift), but only MHC loci should also be affected by selection.
Many natural populations studied have the high variability expected at MHC loci [8, 9]. While population bottlenecks are predicted to result in a loss of variability, balancing selection may counteract the effects of drift unless the effective population size becomes so low relative to the selection coefficient that genes under balancing selection behave in a neutral manner [10, 11]. A few studies have found relatively high variability at MHC genes in bottlenecked species with low neutral variability [12–14]. However, most studies of small island [15, 16] and mainland [17, 18] populations that have undergone severe bottlenecks have documented reduced MHC diversity and concluded that genetic drift had overwhelmed selection (reviewed in ).
Previous genetic work revealed low within-population variability and significant between-population differentiation at minisatellite and mitochondrial loci [21, 22], indicating little to no current gene flow among islands. In contrast, the migratory Swainson's hawk (; Figure 1), whose population size is unknown but likely numbers at least in the hundreds of thousands based on counts of migrants , shows limited population genetic structuring across its western North American breeding range . With their broader distribution and larger population sizes, Swainson's hawks are more variable than Galápagos hawks at minisatellite  and mitochondrial loci [22, 27]. Mitochondrial data suggest that these two species diverged recently relative to other avian taxa, approximately 125,000 years ago (95% CI: 51,000 - 254,000; ). Hull et al.  documented mitochondrial paraphyly of the Swainson's hawk relative to the Galápagos hawk, likely a result of incomplete lineage sorting subsequent to colonization.
Here we present the first characterization of MHC class II B genes in Galápagos and Swainson's hawks with the goal of comparing MHC variability in these two species. We predicted that variability would be lower in the Galápagos hawk due to a genetic bottleneck at foundation followed by ongoing genetic drift in these small populations. To better assess the role of genetic drift, we genotyped Galápagos hawks at nuclear microsatellite loci to compare neutral diversity with Swainson's hawks (data from ). Finally, we provide a preliminary assessment of MHC evolution in these two closely related species by characterizing the gene copies amplified.
From the Swainson's hawks, we recovered 20 different sequences, with each individual having three or four confirmed sequences. Fifth sequences were recovered from three of the individuals; however, we were unable to confirm these because in each case the fifth sequence amplified in only one reaction or did not sequence cleanly. So, every individual had at least two loci. In the 20 birds sampled, we found 18 different MHC genotypes (three birds had the same three sequences). The most common sequence (Busw*08) was recovered from 11 different birds, while 11 of the sequences were recovered from one or two birds. Four of the 20 sequences had a 3 bp deletion at the same codon as the two Galápagos hawk sequences. Of the 255 sites considered, 72 were variable (compared to 31 in Galápagos hawks), and sequences differed by an average of 26.0 ± 12.1 bp.
Phylogenetic relationships of class II B sequences
Sequence diversity within Galápagos (Buteo galapagoensis) and Swainson's (B. swainsoni) hawks at MHC class II B loci
No. polymorphic sites
B. galapagoensis (Grp 1)
B. galapagoensis (Grp 2)
B. swainsoni (Grp 1)
B. swainsoni (Grp 2)
Positive selection on exon 2
Comparison of non-synonymous (dN) and synonymous (dS) substitution rates at putative peptide-binding codons (PBCs) and non-PBCs
No. of sequences
dN ± SE
dS ± SE
dN ± SE
dS ± SE
Brown et al. 1993
0.272 ± 0.073
0.031 ± 0.019
0.069 ± 0.017
0.109 ± 0.037
0.268 ± 0.076
0.027 ± 0.017
0.073 ± 0.017
0.114 ± 0.042
0.072 ± 0.029
0.007 ± 0.007
0.014 ± 0.009
0.010 ± 0.010
0.299 ± 0.085
0.036 ± 0.025
0.045 ± 0.014
0.092 ± 0.034
Tong et al. 2006
0.573 ± 0.127
0.060 ± 0.034
0.057 ± 0.013
0.090 ± 0.030
0.566 ± 0.119
0.054 ± 0.033
0.060 ± 0.014
0.094 ± 0.032
0.123 ± 0.045
0.011 ± 0.011
0.009 ± 0.007
0.010 ± 0.011
0.607 ± 0.150
0.074 ± 0.044
0.036 ± 0.010
0.080 ± 0.029
Evidence of positive selection on Galápagos and Swainson's hawk MHC class II B exon 2 sequences
Positively selected sites
p = 0.775 (p1 = 0.225), ω = 0.071, ω1 = 1
p0 = 0.559, p1 = 0.379 (p2 = 0.062), ω0 = 0.078, ω1 = 1, ω2 = 9.80
3, 5, 29, 49, 62, 63, 78
89.9 (P < 0.001)
p = 0.145, q = 0.334
p0 = 0.938 (p1 = 0.062) p = 0.104, q = 0.117, ω = 10.11
3, 5, 29, 49, 62, 63, 78, 82
100.3 (P < 0.001)
p = 0.770 (p1 = 0.230), ω = 0.0, ω1 = 1
p0 = 0.884, p1 = 0.00 (p2 = 0.116), ω0 = 0.00, ω1 = 1, ω2 = 48.82
49, 63, 78, 82
33.6 (P < 0.001)
p = 0.005, q = 0.020
p0 = 0.884 (p1 = 0.116) p = 0.005, q = 16.87, ω = 48.82
3, 49, 63, 78, 82
33.7 (P < 0.001)
p = 0.683 (p1 = 0.317), ω = 0.054, ω1 = 1
p0 = 0.491, p1 = 0.432 (p2 = 0.077), ω0 = 0.00, ω1 = 1, ω2 = 16.66
5, 29, 63, 78
65.2 (P < 0.001)
p = 0.096, q = 0.149
p0 = 0.922 (p1 = 0.078) p = 0.023, q = 0.028, ω = 16.13
5, 29, 49, 62, 63, 78
70.1 (P < 0.001)
Galápagos hawks have low diversity at microsatellite loci as well. We found a total of 78 alleles across 17 loci in the 185 individuals genotyped. For the seven populations, mean allelic richness varied between 1.53 and 3.29. This low variability does not appear to be the result of a recent bottleneck. The program Bottleneck reported a significant excess of heterozygosity in only one (Pinta; P = 0.027) of the seven populations; however, sample sizes may have been too small to provide statistical resolution.
Population genetic parameters for Galápagos and Swainson's hawk populations estimated from microsatellite data
No. of loci
AR ± SD
Gene diversity ± SD
Ho ± SD
1.76 ± 1.20
0.13 ± 0.21
0.13 ± 0.23
1.53 ± 0.72
0.14 ± 0.23
0.13 ± 0.20
1.93 ± 1.17
0.24 ± 0.28
0.23 ± 0.26
1.84 ± 1.13
0.18 ± 0.25
0.20 ± 0.31
2.65 ± 1.77
0.32 ± 0.31
0.31 ± 0.31
3.29 ± 1.86
0.41 ± 0.29
0.40 ± 0.30
3.40 ± 2.21
0.41 ± 0.30
0.39 ± 0.30
4.92 ± 2.78
0.50 ± 0.29
0.34 ± 0.24
19.29 ± 9.75
0.87 ± 0.06
0.87 ± 0.06
While MHC peptide-binding genes typically display high variability, in some cases small or bottlenecked populations are reported to exhibit reduced variation. We had predicted that MHC class II B variability would be lower in the endemic Galápagos hawk than in the mainland Swainson's hawk due to a colonization event followed by ongoing genetic drift in the small island populations. We found that Galápagos hawks had fewer, less divergent sequences than Swainson's hawks. A corresponding low level of neutral microsatellite variability suggests that drift has played a strong role in shaping MHC variation in Galápagos hawks.
Low genetic diversity in the Galápagos hawk
Galápagos hawks exhibited low MHC class II B diversity, with all 32 individuals having Buga*01 (possibly a fixed locus) and one or both of Buga*02 and Buga*03 (possibly a second locus). Fixed loci have been reported in other species, including an island rat  and bottlenecked populations of the Eurasian beaver ; however, in those cases populations were fixed for different alleles. Likewise, other island populations have fewer MHC alleles compared to a mainland relative [9, 30, 31]. The reduced set of alleles found in the island populations of Eurasian kestrel  and Seychelles warbler  were just as divergent as alleles present in mainland populations. In contrast, Buga*02 and Buga*03 differ by only one base. Exon 2 alleles typically differ by a larger number of bases; for example, lesser kestrel sequences differ by an average of 22.7 bases . So, it is more likely that one of these Galápagos hawk alleles arose from the other through point mutation, than both being retained ancestral alleles. Similarly, the endangered Galápagos penguin has only three sequences (differing by 1-3 bp) at one locus, suggesting the penguins were once fixed for a single allele also . Interestingly, none of the Galápagos sequences was present among the Swainson's hawks sampled, which could be because those sequences were rare in the ancestral population or they mutated from ancestral sequences after colonization.
The low genetic diversity present at neutral markers provides strong evidence for the role of a founder event and ongoing genetic drift within the Galápagos hawk. Allelic richness and heterozygosity at microsatellite loci were lower in Galápagos populations than in the Swainson's hawk population. A similar pattern of low diversity occurs at minisatellite loci; individuals within populations share an average of 69-96% of their minisatellite alleles , while an average of 20-30% is more typical for outbred populations . At the mitochondrial control region, Galápagos hawks had five haplotypes that were on average less divergent than the 36 haplotypes in Swainson's hawks , and seven of eight populations appear fixed for single haplotypes at almost 3 kb of mitochondrial sequence .
The pattern of MHC variation in the Galápagos hawk is likely the result of a loss of ancestral variability at the time of colonization. The apparent fixation of Buga*01 and possible past fixation of Buga*02/03 is more consistent with an extreme bottleneck than ongoing drift. Also, Buga*01 is present on all eight islands; the other two sequences are each present on at least six islands, with at least four populations having both. Minisatellite and mitochondrial data indicate little current gene flow among populations [21, 22], so the geographic distribution of the sequences suggests that MHC variability was reduced at or soon after foundation and that the hawks carried the reduced set of alleles with them as they colonized the various islands. Minisatellite data also hint at an early reduction in genetic variability because of high background similarity across all populations , and four of the populations (Pinta, Marchena, Santiago, Santa Fe) are fixed for the same mitochondrial haplotype .
In addition to drift, low MHC variability in the Galápagos hawk could be attributed to relaxed selection or purifying selection. Parasite diversity on islands may be lower than on the mainland , so island populations may experience reduced selection pressure, resulting in less MHC variation being maintained . Island kestrels that experienced lower pathogen diversity and prevalence than mainland kestrels also had lower MHC variability . Galápagos hawks harbour five ectoparasite species and an undescribed Trypanosoma species [26, 35], but Swainson's hawks are likely exposed to a greater diversity of both endo- and ectoparasites. For example, Swainson's hawks carry five louse species , while Galápagos hawks carry three. Swainson's hawks are migratory and should encounter different sets of pathogens at their breeding and wintering grounds, which has been hypothesized to lead to greater selection for variability at the MHC . Alternatively, the lack of MHC variation could be explained by purifying selection for alleles advantageous against a current parasite or a past selective sweep . These alternatives do not explain the corresponding low variability at neutral markers, but they cannot be ruled out with our dataset and could be occurring in addition to drift.
While studies have demonstrated a relationship between MHC diversity and resistance to parasites [38, 39], the consequences of low MHC diversity remain unclear. Low MHC diversity has been implicated in the rapid spread of an infectious cancer that has caused declines in Tasmanian devil populations . However, other species appear to have experienced little negative impact, with some able to undergo population expansions [18, 41] and survive thousands of years . Radwan et al.  concluded that most bottlenecked populations do lose MHC variation, but data demonstrating an associated population decline or extinction are scarce, although they point out that studies are biased toward populations that have survived past bottlenecks. In some bottlenecked populations, the remaining alleles are divergent [17, 43], and it is possible that this variation is sufficient for survival under current environmental conditions. The introduction of novel diseases may pose the greatest threat, as genetically uniform species may be less capable of adapting. Whiteman et al.  found that smaller, more inbred (as measured at minisatellites) Galápagos hawk populations had higher loads of a coevolved body louse and, in general, lower and less variable natural antibody titres than the larger populations. This suggests that genetic variability may indeed affect this species' ability to mount an effective immune response.
Characterization of MHC genes
Class II B genes are prone to duplication and deletion events , and gene number may vary both within and between species [45, 46]. Among birds, it appears that two class II B genes were present before the major avian radiations , and existing bird taxa range in gene copy number from one or two [48, 49] to seven or more [50, 51]. The number of sequences we recovered from each hawk (≤ 4) suggests we amplified two loci, which is similar to the one to two loci amplified from other accipitrid species . However, we cannot be certain, so two loci is a minimum estimate; it is possible that the primer set we used did not amplify all exon 2 sequences or genes actually present. A more thorough investigation of the class II architecture of these species is needed to determine the true number of genes.
Assignment of alleles to particular MHC class II B genes based on exon 2 has proven difficult in birds, possibly because recent gene duplication or elevated rates of gene conversion have resulted in higher intergenic similarity [53, 54]. However, the hawk sequences exhibited substructuring, clustering into two groups that may represent separate genes. Group 1 was notable because of its low sequence divergence compared to sequences in Group 2. Other studies of avian MHC have also identified genes or clusters of sequences with low divergences, mostly in passerines  but also the Y complex in Galliformes . Some low variability genes appear to be nonfunctional pseudogenes, having mutations that prevent transcription [57, 58], while others are nonclassical with limited expression and specialized functions [56, 59].
Because we used genomic DNA, we cannot be certain that the hawk sequences we amplified are expressed. No frameshift mutations or stop codons were present within the region sequenced, and evolutionarily conserved amino acid residues occurred at 17 of the 19 sites thought to be functionally important for class II molecules (Figure 2; ). Also, an excess of nonsynonymous substitutions was present in both groups of sequences, which is evidence that selection has acted on these loci, although not necessarily recently , and Group 2 sequences had genetic distances similar to those of expressed sequences from classical MHC loci in other species. More sequence data and expression analyses are needed to better characterize these genes and to determine if the Group 1 sequences are from pseudogenes or specialized genes. The presence of a Group 1 sequence in the Old World common buzzard suggests that allelic lineage predates the divergences of these Buteo species.
Here, we documented low MHC variability in an island endemic, the Galápagos hawk, compared to its closest mainland relative, the Swainson's hawk. The corresponding loss of genetic diversity at neutral markers (microsatellite, minisatellite, and mitochondrial loci) suggests that a founder event at colonization followed by ongoing drift in small populations is the primary cause of low MHC diversity. However, purifying selection or a past selective sweep could also explain the low number of MHC alleles present. The Galápagos hawk's low genetic variability may affect its ability to mount an immune response  and could be cause for concern should novel diseases reach the archipelago.
Galápagos hawks (n = 189) were sampled from 1998 to 2003 on eight islands encompassing the entire breeding range of the species: Española, Santa Fe, Pinzón, Santiago, Isabela, Fernandina, Marchena, and Pinta. Overwintering Swainson's hawks (n = 20) were sampled in 2003 at a communal roost near Las Varillas, Córdoba province, Argentina. Both radio-tracking  and stable isotope  data show that Swainson's hawks from different breeding populations intermix on the Argentine wintering grounds. Therefore, it is likely that our sample is derived from more than one breeding population; however, our measure of Swainson's hawk variability is still an underestimate of the variability present in the species. We banded each hawk and took morphological measurements as well as two 50 μl blood samples for genetic analyses (see Bollmer et al.  and Whiteman et al.  for more details).
At the MHC, we genotyped four Galápagos hawks at class II B genes from each of the eight island populations (using unrelated adults from different territories) for a total of 32 individuals. With this sampling, we intended to gauge overall variability at the species level rather than evaluate the amount of variability within individual populations. The twenty Las Varillas Swainson's hawks were also genotyped at the MHC. Individuals that had been used in previous population genetic studies were preferentially chosen [21, 22]. We targeted exon 2, which codes for the peptide-binding region of the class II B molecule and has been shown to be under balancing selection . We first amplified a 307 bp fragment (primers included) using the primers Acc2FC and Acc2RC developed by Alcaide et al.  from other diurnal raptors. Acc2FC begins in intron 1 and extends 9 bp into exon 2, whereas Acc2RC comprises bases 9 through 27 of intron 2. This PCR amplification was carried out in 40 μl reactions using 1.25X buffer, 0.25 mM dNTPs, 2.5 mM MgCl2, 0.5 μM of each primer, 1 U Bioline Taq DNA polymerase, and 100 ng of genomic DNA. Reaction conditions were as follows: 94°C for 4 min, then 35 cycles of 94°C for 40 sec, 56°C for 40 sec, and 72°C for 1 min, and a final extension of 72°C for 5 min. We used QIAquick gel extraction kits (QIAGEN, Valencia, CA) to gel-purify the PCR products and then cloned them using the pGEM-T easy vector cloning kit (Promega, Madison, WI). Positive clones were sequenced on an ABI 3100 sequencer using BigDye chemistry (Life Technologies, Carlsbad, CA). Using sequences aligned from Galápagos and Swainson's hawks, we developed a new reverse primer ButeoR (5'-TTC TGG CAC RCA CTC ACC TC-3'), which overlaps the final 3 bp of exon 2 and extends into intron 2.
We employed denaturing gradient gel electrophoresis (DGGE) to genotype the 52 individuals. We screened eight of these individuals using cloning as well and confirmed that genotypes from DGGE and cloning were consistent. We amplified a 298 bp fragment (primers included) using the primers Acc2FC and ButeoR with a GC-clamp applied to the 5' end of ButeoR to facilitate separation of alleles on gels . Reaction conditions were the same as above, and PCR products were run on 8% 19:1 acrylamide/bisacrylamide gels using a 25 to 35% denaturing gradient of formamide and urea. We ran gels for 4.5 h at 160 V at a constant temperature of 60°C, stained them with SYBR© gold (Promega) and then visualized them on a Kodak IS440CF imaging system. In order to obtain the sequences of the alleles, we cut bands out of the gels, suspended them in 50 μl of dH2O, re-amplified them using the Acc2FC/ButeoR primer set, and then sequenced them using those same primers. All DGGE bands were cut out and sequenced at least once. Because spurious alleles may form when amplifying multiple sequences in one reaction , we considered sequences to be confirmed only if they were amplified in at least two independent reactions. Confirmed sequences are available online [GenBank:EU876805 - EU876827].
We genotyped 185 individual Galápagos hawks at 22 microsatellite loci (BswA110w, BswA204w, BswA302w, BswA303w, BswA312w, BswA317w, BswB111a2w, BswB220w, BswD107w, BswD122w, BswD123w, BswD127w, BswD210w, BswD220w, BswD223w, BswD234w, BswD235w, BswD310w, BswD312w, BswD313w, BswD324w, BswD330w) using the protocol described in Hull et al. . A subset of these loci have been previously used in an examination of Swainson's hawk populations . PCR fragments were size-separated on a 3730 DNA Analyzer (Applied Biosystems, Inc.), and alleles were scored with STRand version 2.3.89 . The 185 individuals represented seven of the eight island populations; our sample size from Pinzón was too small to include.
For the MHC data, we assembled and edited sequences using SeqMan Pro v. 7.1 (DNASTAR, Inc.) and aligned them in BioEdit . We recovered three or more sequences from most individuals, indicating that two or more gene duplications were amplified. This is consistent with previous data from other accipitrid species where one or two genes were recovered . Co-amplification of multiple genes is common in studies of avian MHC, as the high similarity of duplicated genes often makes it difficult to amplify them individually and to assign sequences to particular genes .
We calculated MHC sequence diversity measures using 255 bp of exon 2 (the bases within the primer region were excluded) both within and between species in the program DnaSP v. 4.50.3 . To evaluate relationships among sequences, we constructed a phylogenetic network using the program SplitsTree4 . We employed the Neighbor-Net method  using Jukes-Cantor distances. As opposed to traditional phylogenetic trees, phylogenetic networks permit visualization of conflicting signals from processes such as gene duplication and recombination . We tested for evidence of balancing selection on the peptide-binding region by calculating nonsynonymous (dN) and synonymous (dS) substitution rates. A dN/dS ratio of ω = 1 is expected under neutral evolution, ω < 1 under purifying selection, and ω > 1 under positive selection. First, we calculated the substitution rates using the Nei and Gojobori  method with the Jukes-Cantor correction in MEGA v. 4 . Rates were calculated separately for both putative peptide-binding and non-peptide-binding codons as assigned by Brown et al.  and Tong et al.  for human class II molecules, and Z-tests were used in MEGA to test for positive selection. We also tested for positive selection using the maximum likelihood method implemented in CODEML in the package PAML v. 4 [72, 73]. With this method we did not need to make a priori assumptions about which codons may be peptide-binding. We used a likelihood ratio test to compare model M1a, a neutral model with two site classes (ω0 < 1, ω1 = 1), and M2a which incorporates a third site class (ω2 > 1) allowing for positive selection . Similarly, we compared M7, a null model with a beta distribution (0 < ω < 1), and M8, which uses a beta distribution but also allows for positive selection . The models were compared using likelihood ratio tests. The test statistics were calculated as two times the difference between the likelihoods of the two models, and they were compared to the Chi-square distribution with degrees of freedom equal to the difference in the number of parameters for the two models (M1a and M7 each have 2 parameters; M2a and M8 have 4). M7 and M8 are the most robust to the effect of recombination, which may cause false positives . Positively selected codons with a ω > 1 were identified using the Bayes empirical Bayes approach .
For the microsatellite data, we tested for Hardy-Weinberg equilibrium by locus and population using a randomization test that employs the FIS statistic in FSTAT version 2.9.3 . We tested for linkage disequilibrium between all pairs of loci within each population via randomization tests employing the log-likelihood ratio G-statistic in FSTAT. We tested for the presence of null alleles in MICROCHECKER . Bonferroni tests were used to correct for multiple comparisons. Of the 22 loci, three had significant departures from Hardy-Weinberg equilibrium in at least one population (P < 0.0003, the adjusted critical value): BswA303w in Pinta, BswA312w in Fernandina, Isabela, and Pinta, and BswD234w in Española and Pinta. We found evidence of linkage for three pairs of loci (P < 0.00022, the adjusted critical value): BswD312w x BswD235w, BswA303w x BswD234w, and BswD123w x BswD223w. To eliminate Hardy-Weinberg and linkage issues, we removed BswA303w, BswA312w, BswD234w, BswD235w, and BswD223w from further analyses and used the remaining 17 loci. We found no evidence of null alleles among these 17 loci.
We calculated microsatellite allelic richness as the number of alleles per locus after controlling for differences in sample size using rarefaction analysis [78, 79] in FSTAT. Average gene diversity and observed heterozygosity were calculated using Arlequin v. 3.1 . We tested for evidence of a recent bottleneck (a significant excess of heterozygosity) in each of the Galápagos hawk island populations using the program BOTTLENECK [81, 82]. We used Wilcoxon signed-rank tests under the two-phase model (TPM) of microsatellite evolution with the stepwise mutation model (SMM) set at 70% and the infinite alleles model (IAM) at 30%. We checked the sensitivity of the data to the mutational model by running additional trials using multiple SMM/IAM combinations.
We are very grateful to M. Alcaide who generously provided us with unpublished primer sequences. The Charles Darwin Foundation, Galápagos National Park, Ea. La Independencia, and Agencia Córdoba Ambiente provided permission and support for fieldwork in Galápagos and Argentina. Tj. de Vries and J. Bednarz and their students, D. Santiago, and especially N. Whiteman helped in collecting samples. N. Whiteman also provided helpful comments on the manuscript. Funding was provided by the Field Research for Conservation Program at the Saint Louis Zoo and the E. Desmond Lee Collaborative in Zoological Studies. The Swainson's hawk distribution was provided by NatureServe in collaboration with R. Ridgely, J. Zook, The Nature Conservancy Migratory Bird Program, Conservation International (CABS), World Wildlife Fund (U.S.), and Environment Canada (WILDSPACE).
- Robinson J, Waller MJ, Parham P, de Groot N, Bontrop R, Kennedy LJ, Stoehr P, Marsh SGE: IMGT/HLA and IMGT/MHC: sequence databases for the study of the major histocompatibility complex. Nucleic Acids Res. 2003, 31: 311-314. 10.1093/nar/gkg070.View ArticlePubMedPubMed CentralGoogle Scholar
- Piertney SB, Oliver MK: The evolutionary ecology of the major histocompatibility complex. Heredity. 2006, 96: 7-21.PubMedGoogle Scholar
- Garrigan D, Hedrick PW: Perspective: Detecting adaptive molecular polymorphism: Lessons from the MHC. Evolution. 2003, 57: 1707-1722.View ArticlePubMedGoogle Scholar
- Hughes AL, Nei M: Nucleotide substitution at major histocompatibility complex class II loci - evidence for overdominant selection. Proc Natl Acad Sci USA. 1989, 86: 958-962. 10.1073/pnas.86.3.958.View ArticlePubMedPubMed CentralGoogle Scholar
- Klein J: Generation of diversity at MHC loci: implications for T-cell receptor repertoires. Immunology 80. Edited by: Fougereau M, Dausset J. 1980, London: Academic Press, 239-253.Google Scholar
- Westerdahl H, Hansson B, Bensch S, Hasselquist D: Between-year variation of MHC allele frequencies in great reed warblers: selection or drift?. J Evol Biol. 2004, 17: 485-492. 10.1111/j.1420-9101.2004.00711.x.View ArticlePubMedGoogle Scholar
- Ekblom R, Saether SA, Jacobsson P, Fiske P, Sahlman T, Grahn M, Kålås JA, Höglund J: Spatial pattern of MHC class II variation in the great snipe (Gallinago media). Mol Ecol. 2007, 16: 1439-1451. 10.1111/j.1365-294X.2007.03281.x.View ArticlePubMedGoogle Scholar
- Westerdahl H, Wittzell H, von Schantz T, Bensch S: MHC class I typing in a songbird with numerous loci and high polymorphism using motif-specific PCR and DGGE. Heredity. 2004, 92: 534-542. 10.1038/sj.hdy.6800450.View ArticlePubMedGoogle Scholar
- Alcaide M, Lemus JA, Blanco G, Tella JL, Serrano D, Negro JJ, Rodríguez A, García-Montijano M: MHC diversity and differential exposure to pathogens in kestrels (Aves: Falconidae). Mol Ecol. 2010, 19: 691-705. 10.1111/j.1365-294X.2009.04507.x.View ArticlePubMedGoogle Scholar
- Maruyama T, Nei M: Genetic variability maintained by mutation and overdominant selection in finite populations. Genetics. 1981, 98: 441-459.PubMedPubMed CentralGoogle Scholar
- Kimura M: The neutral theory of molecular evolution. 1983, Cambridge University PressView ArticleGoogle Scholar
- Hambuch TM, Lacey EA: Enhanced selection for MHC diversity in social tuco-tucos. Evolution. 2002, 56: 841-845.View ArticlePubMedGoogle Scholar
- Aguilar A, Roemer G, Debenham S, Binns M, Garcelon D, Wayne RK: High MHC diversity maintained by balancing selection in an otherwise genetically monomorphic mammal. Proc Natl Acad Sci USA. 2004, 101: 3490-3494. 10.1073/pnas.0306582101.View ArticlePubMedPubMed CentralGoogle Scholar
- van Oosterhout C, Joyce DA, Cummings SM, Blais J, Barson NJ, Ramnarine IW, Mohammed RS, Persad N, Cable J: Balancing selection, random genetic drift, and genetic variation at the major histocompatibility complex in two wild populations of guppies (Poecilia reticulata). Evolution. 2006, 60: 2562-2574.View ArticlePubMedGoogle Scholar
- Miller HC, Lambert DM: Genetic drift outweighs balancing selection in shaping post-bottleneck major histocompatibility complex variation in New Zealand robins (Petroicidae). Mol Ecol. 2004, 13: 3709-3721. 10.1111/j.1365-294X.2004.02368.x.View ArticlePubMedGoogle Scholar
- Bollmer JL, Vargas FH, Parker PG: Low MHC variation in the endangered Galápagos penguin (Spheniscus mendiculus). Immunogenetics. 2007, 59: 593-602. 10.1007/s00251-007-0221-y.View ArticlePubMedGoogle Scholar
- Hedrick PW, Parker KM, Gutierrez-Espeleta GA, Rattink A, Lievers K: Major histocompatibility complex variation in the Arabian oryx. Evolution. 2000, 54: 2145-2151.View ArticlePubMedGoogle Scholar
- Babik W, Durka W, Radwan J: Sequence diversity of the MHC DRB gene in the Eurasian beaver (Castor fiber). Mol Ecol. 2005, 14: 4249-4257. 10.1111/j.1365-294X.2005.02751.x.View ArticlePubMedGoogle Scholar
- Radwan J, Biedrzycka A, Babik W: Does reduced MHC diversity decrease viability of vertebrate populations?. Biol Conserv. 2010, 143: 537-544. 10.1016/j.biocon.2009.07.026.View ArticleGoogle Scholar
- Riesing MJ, Kruckenhauser L, Gamauf A, Haring E: Molecular phylogeny of the genus Buteo (Aves: Accipitridae) based on mitochondrial marker sequences. Mol Phylogenet Evol. 2003, 27: 328-342. 10.1016/S1055-7903(02)00450-5.View ArticlePubMedGoogle Scholar
- Bollmer JL, Whiteman NK, Cannon MD, Bednarz JC, De Vries T, Parker PG: Population genetics of the Galápagos Hawk (Buteo galapagoensis): Genetic monomorphism within isolated populations. Auk. 2005, 122: 1210-1224. 10.1642/0004-8038(2005)122[1210:PGOTGH]2.0.CO;2.View ArticleGoogle Scholar
- Bollmer JL, Kimball RT, Whiteman NK, Sarasola JH, Parker PG: Phylogeography of the Galápagos hawk (Buteo galapagoensis): A recent arrival to the Galápagos Islands. Mol Phylogenet Evol. 2006, 39: 237-247. 10.1016/j.ympev.2005.11.014.View ArticlePubMedGoogle Scholar
- Fuller MR, Seegar WS, Schueck LS: Routes and travel rates of migrating Peregrine Falcons Falco peregrinus and Swainson's Hawks Buteo swainsoni in the Western Hemisphere. J Avian Biol. 1998, 29: 433-440. 10.2307/3677162.View ArticleGoogle Scholar
- Bechard MJ, Houston CS, Sarasola JH, England AS: Swainson's Hawk (Buteo swainsoni). The Birds of North America Online. Edited by: Poole A. 2010, Ithaca: Cornell Lab of OrnithologyGoogle Scholar
- Hull JM, Anderson R, Bradbury M, Estep JA, Ernest HB: Population structure and genetic diversity in Swainson's Hawks (Buteo swainsoni): implications for conservation. Conserv Genet. 2008, 9: 305-316. 10.1007/s10592-007-9342-y.View ArticleGoogle Scholar
- Whiteman NK, Matson KD, Bollmer JL, Parker PG: Disease ecology in the Galápagos Hawk (Buteo galapagoensis): host genetic diversity, parasite load and natural antibodies. P Roy Soc Lond B Bio. 2006, 273: 797-804. 10.1098/rspb.2005.3396.View ArticleGoogle Scholar
- Hull JM, Savage WK, Bollmer JL, Kimball RT, Parker PG, Whiteman NK, Ernest HB: On the origin of the Galapagos hawk: an examination of phenotypic differentiation and mitochondrial paraphyly. Biol J Linn Soc. 2008, 95: 779-789. 10.1111/j.1095-8312.2008.01082.x.View ArticleGoogle Scholar
- Brown JH, Jardetzky TS, Gorga JC, Stern LJ, Urban RG, Strominger JL, Wiley DC: Three-dimensional structure of the human class II histocompatibility antigen HLA-DR1. Nature. 1993, 364: 33-39. 10.1038/364033a0.View ArticlePubMedGoogle Scholar
- Tong JC, Bramson J, Kanduc D, Chow S, Sinha AA, Ranganathan S: Modeling the bound conformation of Pemphigus vulgaris-associated peptides to MHC class II DR and DQ alleles. Immunome Res. 2006, 2: 1-10.1186/1745-7580-2-1.View ArticlePubMedPubMed CentralGoogle Scholar
- Seddon JM, Baverstock PR: Variation on islands: major histocompatibility complex (Mhc) polymorphism in populations of the Australian bush rat. Mol Ecol. 1999, 8: 2071-2079. 10.1046/j.1365-294x.1999.00822.x.View ArticlePubMedGoogle Scholar
- Richardson DS, Westerdahl H: MHC diversity in two Acrocephalus species: the outbred Great reed warbler and the inbred Seychelles warbler. Mol Ecol. 2003, 12: 3523-3529. 10.1046/j.1365-294X.2003.02005.x.View ArticlePubMedGoogle Scholar
- Parker Rabenold P, Rabenold KN, Piper WH, Decker MD, Haydock J: Using DNA fingerprinting to assess kinship and genetic structure in avian populations. Proceedings of the Fourth International Congress of Systematic and Evolutionary Biology. Edited by: Dudley EC. 1991, Portland, Oregon: Dioscorides Press, 611-620.Google Scholar
- Beadell JS, Atkins C, Cashion E, Jonker M, Fleischer RC: Immunological change in a parasite-impoverished environment: divergent signals from four island taxa. PLoS ONE. 2007, 2: e896-10.1371/journal.pone.0000896.View ArticlePubMedPubMed CentralGoogle Scholar
- Slade RW: Limited Mhc polymorphism in the southern elephant seal - implications for Mhc evolution and marine mammal population biology. P Roy Soc Lond B Bio. 1992, 249: 163-171. 10.1098/rspb.1992.0099.View ArticleGoogle Scholar
- Parker PG, Whiteman NK, Miller RE: Conservation medicine on the Galápagos islands: Partnerships among behavioral, population, and veterinary scientists. Auk. 2006, 123: 625-638. 10.1642/0004-8038(2006)123[625:CMOTGI]2.0.CO;2.View ArticleGoogle Scholar
- Price RD, Hellenthal R, Palma RL: World checklist of chewing lice with host associations and keys to families and genera. The chewing lice: World checklist and biology overview. Edited by: Price RD, Hellenthal RA, Palma RL, Johnson KP. 2003, Clayton DH: Illinois Natural History Survey Special Publication 24, 448-Google Scholar
- de Groot N, Heijmans CMC, de Groot N, Otting N, de Vos-Rouweler AJM, Remarque EJ, Bonhomme M, Doxiadis GGM, Crouau-Roy B, Bontrop R: Pinpointing a selective sweep to the chimpanzee MHC class I region by comparative genomics. Mol Ecol. 2008, 17: 2074-2088. 10.1111/j.1365-294X.2008.03716.x.View ArticlePubMedGoogle Scholar
- Meyer-Lucht Y, Otten C, Puttker T, Pardini R, Metzger JP, Sommer S: Variety matters: adaptive genetic divesity and parasite load in two mouse opossums from the Brazilian Atlantic forest. Conserv Genet. 2010, 11: 2001-2013. 10.1007/s10592-010-0093-9.View ArticleGoogle Scholar
- Wegner KM, Reusch TBH, Kalbe M: Multiple parasites are driving major histocompatibility complex polymorphism in the wild. J Evol Biol. 2003, 16: 224-232. 10.1046/j.1420-9101.2003.00519.x.View ArticlePubMedGoogle Scholar
- Siddle HV, Kreiss A, Eldridge MDB, Noonan E, Clarke CJ, Pyecroft S, Woods GM, Belov K: Transmission of a fatal clonal tumor by biting occurs due to depleted MHC diversity in a threatened carnivorous marsupial. Proc Natl Acad Sci USA. 2007, 104: 16221-16226. 10.1073/pnas.0704580104.View ArticlePubMedPubMed CentralGoogle Scholar
- Mikko S, Andersson L: Low major histocompatibility complex class II diversity in European and North American moose. Proc Natl Acad Sci USA. 1995, 92: 4259-4263. 10.1073/pnas.92.10.4259.View ArticlePubMedPubMed CentralGoogle Scholar
- Babik W, Pabijan M, Arntzen JW, Cogălniceanu D, Durka W, Radwan J: Long-term survival of a urodele amphibian despite depleted major histocompatibility complex variation. Mol Ecol. 2009, 18: 769-781. 10.1111/j.1365-294X.2008.04057.x.View ArticlePubMedGoogle Scholar
- Sommer S: The importance of immune gene variability (MHC) in evolutionary ecology and conservation. Front Zool. 2005, 2: 16-10.1186/1742-9994-2-16.View ArticlePubMedPubMed CentralGoogle Scholar
- Nei M, Gu X, Sitnikova T: Evolution by the birth-and-death process in multigene families of the vertebrate immune system. Proc Natl Acad Sci USA. 1997, 94: 7799-7806. 10.1073/pnas.94.15.7799.View ArticlePubMedPubMed CentralGoogle Scholar
- Doxiadis GGM, de Groot N, de Groot N, Rotmans G, de Vos-Rouweler AJM, Bontrop R: Extensive DRB region diversity in cynomolgus macaques: recombination as a driving force. Immunogenetics. 2010, 62: 137-147. 10.1007/s00251-010-0422-7.View ArticlePubMedPubMed CentralGoogle Scholar
- Kelley J, Walter L, Trowsdale J: Comparative genomics of major histocompatibility complexes. Immunogenetics. 2005, 56: 683-695. 10.1007/s00251-004-0717-7.View ArticlePubMedGoogle Scholar
- Burri R, Salamin N, Studer RA, Roulin A, Fumagalli L: Adaptive divergence of ancient gene duplicates in the avian MHC class II β. Mol Biol Evol. 2010, 27: 2360-2374. 10.1093/molbev/msq120.View ArticlePubMedGoogle Scholar
- Kikkawa E, Tsuda T, Sumiyama D, Naruse T, Fukuda M, Kurita M, Wilson R, LeMaho Y, Miller G, Tsuda M, Murata K, Kulski JK, Inoko H: Trans-species polymorphism of the Mhc class II DRB-like gene in banded penguins (genus Spheniscus). Immunogenetics. 2009, 61: 341-352. 10.1007/s00251-009-0363-1.View ArticlePubMedGoogle Scholar
- Miller MM, Bacon LD, Hala K, Hunt HD, Ewald SJ, Kaufman J, Zoorob R, Briles WE: 2004 Nomenclature for the chicken major histocompatibility (B and Y ) complex. Immunogenetics. 2004, 56: 261-279.PubMedGoogle Scholar
- Shiina T, Shimizu S, Hosomichi K, Kohara S, Watanabe S, Hanzawa K, Beck S, Kulski JK, Inoko H: Comparative genomic analysis of two avian (quail and chicken) MHC regions. J Immunol. 2004, 172: 6751-6763.View ArticlePubMedGoogle Scholar
- Balakrishnan CN, Ekblom R, Völker M, Westerdahl H, Godinez R, Kotkiewicz H, Burt DW, Graves T, Griffin DK, Warren WC, Edwards SV: Gene duplication and fragmentation in the zebra finch major histocompatibility complex. BMC Biol. 2010, 8: 29-10.1186/1741-7007-8-29.View ArticlePubMedPubMed CentralGoogle Scholar
- Alcaide M, Edwards SV, Negro JJ: Characterization, polymorphism, and evolution of MHC class IIB genes in birds of prey. J Mol Evol. 2007, 65: 541-554. 10.1007/s00239-007-9033-9.View ArticlePubMedGoogle Scholar
- Edwards SV, Hess CM, Gasper J, Garrigan D: Toward an evolutionary genomics of the avian Mhc. Immunol Rev. 1999, 167: 119-132. 10.1111/j.1600-065X.1999.tb01386.x.View ArticlePubMedGoogle Scholar
- Edwards SV, Wakeland EK, Potts WK: Contrasting histories of avian and mammalian Mhc genes revealed by class II B sequences from songbirds. Proc Natl Acad Sci USA. 1995, 92: 12200-12204. 10.1073/pnas.92.26.12200.View ArticlePubMedPubMed CentralGoogle Scholar
- Aguilar A, Edwards SV, Smith TB, Wayne RK: Patterns of variation in MHC class II beta loci of the little greenbul (Andropadus virens) with comments on MHC evolution in birds. J Hered. 2006, 97: 133-142. 10.1093/jhered/esj013.View ArticlePubMedGoogle Scholar
- Zoorob R, Bernot A, Renoir DM, Choukri F, Auffray C: Chicken major histocompatibility complex class II B genes: analysis of interallelic and interlocus sequence variance. Eur J Immunol. 1993, 23: 1139-1145. 10.1002/eji.1830230524.View ArticlePubMedGoogle Scholar
- Hess CM, Gasper J, Hoekstra HE, Hill CE, Edwards SV: MHC class II pseudogene and genomic signature of a 32-kb cosmid in the house finch (Carpodacus mexicanus). Genome Res. 2000, 10: 613-623. 10.1101/gr.10.5.613.View ArticlePubMedPubMed CentralGoogle Scholar
- Moon DA, Veniamin SM, Parks-Dely JA, Magor KE: The MHC of the duck (Anas platyrhynchos) contains five differentially expressed class I genes. J Immunol. 2005, 175: 6702-6712.View ArticlePubMedGoogle Scholar
- Kropshofer H, Vogt AB, Thery C, Armandola EA, Li BC, Moldenhauer G, Amigorena S, Hammerling GJ: A role for HLA-DO as a co-chaperone of HLA-DM in peptide loading of MHC class II molecules. EMBO J. 1998, 17: 2971-2981. 10.1093/emboj/17.11.2971.View ArticlePubMedPubMed CentralGoogle Scholar
- Kaufman J, Salomonsen J, Flajnik M: Evolutionary conservation of MHC class I and class II molecules - different yet the same. Sem Immunol. 1994, 6: 411-424. 10.1006/smim.1994.1050.View ArticleGoogle Scholar
- Sarasola JH, Negro JJ, Hobson KA, Bortolotti GR, Bildstein KL: Can a 'wintering area effect' explain population status of Swainson's hawks? A stable isotope approach. Divers Distrib. 2008, 14: 686-691. 10.1111/j.1472-4642.2008.00475.x.View ArticleGoogle Scholar
- Sheffield VC, Cox DR, Lerman LS, Myers RM: Attachment of a 40 base pair G+C-rich sequence (GC-clamp) to genomic DNA fragments by the polymerase chain-reaction results in improved detection of single-base changes. Proc Natl Acad Sci USA. 1989, 86: 232-236. 10.1073/pnas.86.1.232.View ArticlePubMedPubMed CentralGoogle Scholar
- Kanagawa T: Bias and artifacts in multitemplate polymerase chain reactions (PCR). J Biosci Bioeng. 2003, 96: 317-323.View ArticlePubMedGoogle Scholar
- Hull JM, Tufts D, Topinka JR, May B, Ernest HB: Development of 19 microsatellite loci for Swainson's hawks (Buteo swainsoni) and other buteos. Mol Ecol Notes. 2007, 7: 346-349.View ArticleGoogle Scholar
- Toonen RJ, Hughes S: Increased throughput for fragment analysis on an ABI PRISM (R) automated sequencer using a membrane comb and STRand software. Biotechniques. 2001, 31: 1320-1324.PubMedGoogle Scholar
- Hall TA: BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucleic Acid S. 1999, 41: 95-98.Google Scholar
- Rozas J, Sanchez-DelBarrio JC, Messeguer X, Rozas R: DnaSP, DNA polymorphism analsyes by the coalescent and other methods. Bioinformatics. 2003, 19: 2496-2497. 10.1093/bioinformatics/btg359.View ArticlePubMedGoogle Scholar
- Huson D: SplitsTree: a progam for analyzing and visualizing evolutionary data. Bioinformatics. 1998, 14: 68-73. 10.1093/bioinformatics/14.1.68.View ArticlePubMedGoogle Scholar
- Bryant D, Moulton V: Neighbor-Net: an agglomerative method for the construction of phylogenetic networks. Mol Biol Evol. 2004, 21: 255-265.View ArticlePubMedGoogle Scholar
- Nei M, Gojobori T: Simple methods for estimating the numbers of synonymous and nonsynonymous nucleotide substitutions. Mol Biol Evol. 1986, 3: 418-426.PubMedGoogle Scholar
- Tamura K, Dudley J, Nei M, Kumar S: MEGA4: Molecular evolutionary genetics analysis (MEGA) software version 4.0. Mol Biol Evol. 2007, 24: 1596-1599. 10.1093/molbev/msm092.View ArticlePubMedGoogle Scholar
- Yang Z, Nielsen R, Goldman N, Pedersen A-MK: Codon-substitution models for heterogeneous selection pressure at amino acid sites. Genetics. 2000, 155: 431-449.PubMedPubMed CentralGoogle Scholar
- Yang ZH, Wong WSW, Nielsen R: Bayes empirical Bayes inference of amino acid sites under positive selection. Mol Biol Evol. 2005, 22: 1107-1118. 10.1093/molbev/msi097.View ArticlePubMedGoogle Scholar
- Wong WSW, Yang Z, Goldman N, Nielsen R: Accuracy and power of statistical methods for detecting adaptive evolution in protein coding sequences and for identifying positively selected sites. Genetics. 2004, 168: 1041-1051. 10.1534/genetics.104.031153.View ArticlePubMedPubMed CentralGoogle Scholar
- Anisimova M, Nielsen R, Yang Z: Effect of recombination on the accuracy of the likelihood method for detecting positive selection at amino acid sites. Genetics. 2003, 164: 1229-1236.PubMedPubMed CentralGoogle Scholar
- Goudet J: FSTAT, a program to estimate and test gene diversities and fixation indices, version 2.9.3. 2001, Lausanne, Switzerland: Institut d'Écologie, Université de LausanneGoogle Scholar
- van Oosterhout C, Hutchinson WF, Wills DPM, Shipley P: MICRO-CHECKER: software for identifying and correcting genotyping errors in microsatellite data. Mol Ecol Notes. 2004, 4: 535-538. 10.1111/j.1471-8286.2004.00684.x.View ArticleGoogle Scholar
- El Mousadik A, Petit RJ: High level of genetic differentiation for allelic richness among populations of the argan tree [Argania spinosa (L.) Skeels] endemic to Morocco. Theor Appl Genet. 1996, 92: 832-839. 10.1007/BF00221895.View ArticlePubMedGoogle Scholar
- Petit RJ, El Mousadik A, Pons O: Identifying populations for conservation on the basis of genetic markers. Conserv Biol. 1998, 12: 844-855. 10.1046/j.1523-1739.1998.96489.x.View ArticleGoogle Scholar
- Excoffier L, Laval G, Schneider S: Arlequin ver. 3.0: An integrated software package for population genetics data analysis. Evol Bioinform Online. 2005, 1: 47-50.Google Scholar
- Cornuet JM, Luikart G: Description and power analysis of two tests for detecting recent population bottlenecks from allele frequency data. Genetics. 1996, 144: 2001-2014.PubMedPubMed CentralGoogle Scholar
- Piry S, Luikart G, Cornuet JM: BOTTLENECK: A computer program for detecting recent reductions in the effective population size using allele frequency data. J Hered. 1999, 90: 502-503. 10.1093/jhered/90.4.502.View ArticleGoogle Scholar
- Ridgely RS, Allnutt TF, Brooks T, McNicol DK, Mehlman DW, Young BE, Zook JR: Digital distribution maps of the birds of the Western Hemisphere, version 3.0. NatureServe, Arlington, Virginia, USA. 2007Google Scholar
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