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DNA Sequence Variation and the Recombinational Landscape in Drosophila pseudoobscura: A Study of the Second Chromosome
Martha T. Hamblina and Charles F. Aquadroaa Section of Genetics and Development, Cornell University, Ithaca, New York 14853
Corresponding author: Martha T. Hamblin, Department of Human Genetics, University of Chicago, 924 E. 57th St., Chicago, IL 60637., mhamblin{at}genetics.uchicago.edu (E-mail)
Communicating editor: R. R. HUDSON
| ABSTRACT |
|---|
The relationship between rates of recombination and DNA sequence polymorphism was analyzed for the second chromosome of Drosophila pseudoobscura. We constructed integrated genetic and physical maps of this chromosome using molecular markers at 10 loci spanning most of its physical length. The total length of the map was 128.2 cM, almost twice that of the homologous chromosome arm (3R) in D. melanogaster. There appears to be very little centromeric suppression of recombination, and rates of recombination are quite uniform across most of the chromosome. Levels of sequence variation (
W, based on the number of segregating sites) at seven loci (tropomyosin 1, Rhodopsin 3, Rhodopsin 1, bicoid, Xanthine dehydrogenase, Myosin light chain 1, and ribosomal protein 49) varied from 0.0036 to 0.0167. Generally consistent with earlier studies, the average estimate of
W at total sites is 1.5-fold higher than that in D. melanogaster, while average
W at silent sites is almost 3-fold higher. These estimates of variation were analyzed in the context of a background selection model under the same parameters of mutation rate and selection as have been proposed for D. melanogaster. It is likely that a significant fraction of the higher level of sequence variation in D. pseudoobscura can be explained by differences in regional rates of recombination rather than a larger species-level effective population size. However, the distribution of variation among synonymous, nonsynonymous, and noncoding sites appears to be quite different between the species, making direct comparisons of neutral variation, and hence inferences about effective population size, difficult. Tajima's D statistics for 6 out of the 7 loci surveyed are negative, suggesting that D. pseudoobscura may have experienced a rapid population expansion in the recent past or, alternatively, that slightly deleterious mutations constitute an important component of standing variation in this species.
BOTH Drosophila melanogaster and D. pseudoobscura are important model species for population genetic and evolutionary studies. While they are fairly closely related (their estimated divergence time is 30 million years), their evolutionary history and ecology are apparently quite different. D. melanogaster originated in the tropics, became commensal with humans, and has spread worldwide in the recent past (![]()
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Levels of DNA sequence variation in these two species suggest that D. melanogaster has a smaller effective population size (Ne) than D. pseudoobscura. ![]()
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Another interesting issue concerns the relative contributions of adaptive vs. purifying selection to the observed relationship between recombination and variation in D. melanogaster. That relationship is driven by the local reduction of effective population size in regions linked to targets of both positive and negative selection (![]()
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One of the obstacles to this type of analysis is the requirement for integrated physical and genetic maps such as are currently available for D. melanogaster. In the case of D. pseudoobscura, however, this obstacle is not huge. The presence of polytene chromosomes allows physical localization, by in situ hybridization, of any cloned region or PCR product. Sequence conservation of coding regions between D. melanogaster and D. pseudoobscura facilitates PCR amplification of homologous loci. Conservation of the five major linkage groups (elements AE; ![]()
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| MATERIALS AND METHODS |
|---|
Fly stocks:
The population sample used for this study was obtained from a collection of isofemale lines of D. pseudoobscura from Goldendale, Washington established by M. Noor in summer of 1996. These lines were inbred by full-sib mating to facilitate sequencing and genetic analysis. Twenty-two lines were successfully inbred for 1115 generations. The D. miranda line, SP235 from Spray, Oregon, was obtained from W. Anderson.
DNA preparation:
DNAs for mapping were prepared from single flies arrayed in 96-well plates (![]()
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Construction of a genetic and physical map of the second chromosome:
GenBank sequences of D. pseudoobscura genes that are homologous to genes on 3R of D. melanogaster were identified. These sequences were examined for the presence of microsatellites or other repeated sequences that might provide highly polymorphic, easily scored markers. Such sequences were found in or near four genes: Glucose dehydrogenase (Gld), Rhodopsin 1 (Rh1), Myosin light chain 1 (Mlc1), and bicoid (bcd). PCR primers were designed to amplify small products containing these repeats. In gene regions where no repeated sequences were found, a survey of sequence variation at the locus was used to identify regions that were likely to show multiple alleles by single-strand conformation polymorphism (SSCP) analysis (![]()
In the case of tropomyosin 1 (trop1), no sequence data were previously available from D. pseudoobscura, but the physical location was known (B. CHARLESWORTH, personal communication). The D. pseudoobscura sequence of all of intron C and 713 nucleotides of intron D of the trop1 gene was obtained by PCR using primers based on conserved exon sequence from D. melanogaster (13581379F and 27302710R from GenBank accession no. K03277). D. melanogaster contains a (CT)n microsatellite (nucleotides 22952324) that we found to be conserved and variable in D. pseudoobscura. The D. pseudoobscura sequence of this region has been deposited in GenBank as accession nos. AF039273 and AF039274.
These markers and their physical locations, as well as an additional microsatellite marker, Dps2003, that had been genetically mapped to chromosome 2 by ![]()
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DNA was prepared from 192 F2 progeny for scoring each of the nine markers. An additional cross between lines 7 and 51 was set up in the same way to score the location of rp49. Inversion loops (presumably on the third chromosome, which is polymorphic for inversions in this population) were observed in F1 larvae of this cross, raising the possibility that crossing over on the second chromosome may have been somewhat elevated in this cross, due to the interchromosomal effect (![]()
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In situ hybridization:
Probes for Rh3 and bcd were prepared by biotinylation of the same PCR products used as sequencing templates. Hybridizations to polytene chromosome preparations were performed as described by ![]()
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DNA sequence variation:
Approximately 1 to 1.8-kb regions were sequenced in samples of 1012 inbred lines for seven loci whose physical and genetic locations were known. For five of these loci, one allele was also sequenced from D. miranda. The regions, which were chosen to include as much noncoding sequence as possible, are shown in Table 2. PCR products were sequenced directly using the Thermosequenase cycle sequencing system from Amersham (Arlington Heights, IL), after agarose gel purification using the Qiaex II system (Qiagen, Valencia, CA). Estimates of 4Neµ,
, and
W, were calculated according to ![]()
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W refers to Watterson's estimator.
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The background selection model:
Physical and genetic data generated in this study (Table 3) were used in Equation 15 of the background selection model of ![]()
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The ends of the chromosomes were treated two different ways. In the first treatment (Low, Table 5), which leads to lower estimates of f0, no additional recombination at the unmapped ends was included. Dps2003 was assumed to be at the centromere; rp49 was assumed to be at 19.5, with a most distal 0.5 section to the telomere having a recombination rate of zero.
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In the second treatment (High, Table 5), we assumed that the unmapped ends of the chromosomes had the same rates of recombination as the adjacent mapped intervals. Dps2003 was assumed to be at 0.5 sections from the centromere, and the most proximal 0.5 section was assumed to have the same genetic length as the interval from Dps2003 to trop1: 3.8 cM. As in the first analysis, rp49 was assumed to be at 19.5, but the most distal 0.5 section was assumed to have the same rate of recombination as the interval from Mlc1 to rp49, namely 3.5 cM/0.5 section.
| RESULTS |
|---|
Genetic map and rates of recombination:
Nine molecular markers across the second chromosome were developed based on published genomic sequence. Results of the population survey for these markers are shown in Table 1. The high level of variation at most loci made it possible to score eight of the nine markers, as well as microsatellite Dps2003, in F2 progeny of a single cross. The number of F2 progeny scored was in the range of 185192 for all markers except Rh1, for which 166 progeny were scored. The last marker, rp49, had only two alleles and was scored in a separate cross, 7 x 51. Because the physical order of the loci was already known, it was necessary to score only one other marker, Mlc1, in cross 7 x 51 to locate rp49 on the genetic map. Due to technical problems, fewer progeny were scored from this cross, and the estimate of genetic distance between Mlc1 and rp49 is based on only 79 progeny.
The genetic map is shown in Fig 1. The order of the markers is consistent with published cytological locations, except in the case of Rh3. ![]()
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The total length of our genetic map for this chromosome is >128 cM, as compared with the published length of 101 cM based on previously available visible and allozyme markers (![]()
Physical and genetic locations are shown in Table 3 and are presented graphically in Fig 2 with similar data from chromosome arm 3R of D. melanogaster (![]()
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Levels of DNA sequence variation in a population sample:
We surveyed DNA sequence variation at seven of the loci for which we had scored genetic map position; Table 4 summarizes the data. There is a fourfold difference in
W at silent sites between the least variable locus, trop1, and the most variable, Xdh. Estimates of
at silent sites vary about eightfold. For trop1, Rh1, Mlc1, Xdh, and rp49, one allele from D. miranda was sequenced to obtain an estimate of divergence (Table 4). None of these five loci shows a departure from the neutral expectation when compared to each other or to Adh (using the Apple Hill population sample; ![]()
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Estimates of
are lower than estimates of
W for all loci except bcd, as indicated by the negative Tajima's D (1989a) statistics (Table 4). Tajima's D's for Adh (![]()
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Prediction of the effects of background selection:
Given the recombinational map described above, we wanted to determine the expected impact of background selection on levels of neutral variation. In the absence of background selection, differences in
among loci are due only to differences in µ, since Ne is the same across all loci. Background selection, however, causes regional differences in Ne (![]()
We calculated values of f0 using the simplified model of ![]()
Using U = 1 and sh = 0.02, the same values used for D. melanogaster (![]()
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Expected values of f0 are related to expected values of
by the parameter
0 (the level of variation in the absence of background selection, i.e., 4Ne,0µ), so that f0 x
0 = E (
W). Fig 3 shows the expected values of
under the four sets of parameters, using an estimate of
0 based on silent (noncoding and synonymous) sites that gives the best fit of the observed data to the model (see below). The high variation observed at Xdh is not predicted by any of the models (but note that divergence at Xdh is 4.1%, more than twice that at other loci; Table 4). Otherwise, the shape of the curve is best predicted by the model with sh = 0.005 and assuming no recombination in the unmapped segments (fourth column of Table 5).
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The estimate of
0 was found by performing regression analysis of
W (for all loci except trop1 because of its significant Tajima's D) on the predictions of f0. Because E
= f0, the slope of the line
W = m x f0 is an estimate of
o. (We used the "no-intercept" option of Statview, which forces the regression line to pass through the origin.) Separate regressions were performed using
W at total sites, silent sites, or synonymous sites only. Xdh is an outlier in all three data sets, so we also performed the regressions without Xdh, which greatly improved the fit of the data to the model. The results of the analysis, using the model with sh = 0.005 and assuming no recombination in the unmapped segments, are presented in Table 6. For Fig 3, we chose an estimate of
0 based on
W at silent sites because it shows the highest correlation with f0 (r2 = 0.91 vs. r2 = 0.59 and r2 = 0.67 for total sites and synonymous sites, respectively).
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| DISCUSSION |
|---|
Genetic map of chromosome 2:
Our immediate purpose in constructing a genetic map was to relate rates of recombination to levels of DNA sequence variation in natural populations (as opposed to providing a framework for identifying genetic loci). It is therefore important to consider whether our map is likely to reflect average rates of recombination in the study population from which our estimates of variation were obtained. There is genetic variation for rates of recombination in D. pseudoobscura (![]()
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The temperature that a female D. pseudoobscura is likely to experience during meiosis in the wild is not known. Studies of daily activity found that flies are active at 10° to 31°, but are not usually found at baits during the hotter (>21°) parts of the day (![]()
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Our map of chromosome 2, based on two genotypes chosen at random from the population, is almost 30% longer than the published map of ![]()
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Levels of variation:
We analyzed levels of neutral variation at seven loci across the second chromosome of D. pseudoobscura, substantially increasing the number of estimates of sequence variation published for this species. Previous comparisons with sequence data from D. melanogaster have been problematic because estimates of 4Neµ from D. melanogaster come from many different kinds of samples (see ![]()
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W (i.e., an estimate of 4Neµ at all sites, coding and noncoding) on the basis of 4-cutter variation across regions 1.94.6 kb in length with an average of 46% coding sequence. This is quite similar to the average of 42% coding sequence in our surveys (Table 4).
Average levels of total variation in the Goldendale population of D. pseudoobscura are ~1.5-fold higher than in the Maryland population of D. melanogaster (Table 7). Most of this difference comes from the lower end of the range: the least variable locus in D. pseudoobscura is 1020-fold more variable than the least variable locus in D. melanogaster. The estimate of total
W at Adh in D. pseudoobscura was 0.015 in the most variable population sample, Gundlach-Bundshou (![]()
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For a comparison based on synonymous sites in coding sequence, we used estimates from 5 of the loci in this study (all except trop1 and Mlc1, which had 0 and 16.5 synonymous sites, respectively) plus the data for Adh and Adh-Dup in the Apple Hill population (![]()
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Analysis in the context of regional rates of recombination:
Increased overall recombination rate, a lack of substantial suppression of recombination near the centromere, and the reduced size of the linkage group (the acrocentric second chromosome of D. pseudoobscura contains only element E, while the metacentric third chromosome of D. melanogaster contains both elements D and E) all reduce the interaction of selection and linkage in D. pseudoobscura as compared with D. melanogaster (Table 5). The relative levels of silent DNA sequence variation observed for the second chromosome of D. pseudoobscura (20% of the genome) can be fairly well predicted using a background selection model assuming the same average mutational and selective forces as are thought to operate in a North American population of D. melanogaster (Fig 3).
Note that, although we used a model that is formulated to describe background selection against deleterious mutations, any positively selected mutations that have contributed to regional reductions in effective population size will affect the fit of the model to the data. It was not our goal to discriminate between the separate effects of background selection and selective sweeps. Rather, in using the same values for U and sh as were used by ![]()
The relatively uniform rates of recombination across the second chromosome of D. pseudoobscura make most of the chromosome fairly insensitive to changes in parameters. It was therefore difficult to discriminate between the alternative models presented in Fig 3, and our qualitative assessment of fit to the models became dependent on the ends of the chromosome where our data were less reliable. It was clear, however, that a stronger, rather than a weaker, effect of selection was needed to explain the reduction in variation observed at both ends of the chromosome. Therefore, unless we assume that the genomic rate of deleterious mutation (U) is higher in D. pseudoobscura, our analyses provide no support for the idea that hitchhiking events have played a larger role in the recent evolutionary history of North American D. melanogaster than D. pseudoobscura.
How likely is it that U for D. pseudoobscura is larger than for D. melanogaster? It is unlikely that replication-based errors occur at a different rate between such closely related species, though densities of transposable elements (TEs), which can contribute to the background selection effect (![]()
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It has been argued that U in D. melanogaster is considerably smaller, not larger, than 1 (![]()
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Species-level effective population size:
It has been inferred from a small number of restriction-enzyme and sequencing surveys (e.g., ![]()
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0, which directly reflects species-level effective population size, assuming similar neutral mutation rates in the two species.
For D. melanogaster, the estimate of
0 = 0.014 obtained by ![]()
0 at total sites in D. pseudoobscura is similar: 0.0100.013 (Table 6). However, a much larger fraction of total variation in D. melanogaster appears to be nonsynonymous or noncoding than in D. pseudoobscura (Table 7). This discrepancy suggests that differences in total variation between the two species may not be a simple function of effective population size (i.e., that a significant fraction of the variation may not be strictly neutral). We analyzed the relationship between recombination and variation for three classes of sites in D. pseudoobscura (Table 6) and found that estimates of silent variation (synonymous plus noncoding) showed the strongest relationship with the predicted effects of background selection, yielding an estimate of
0 = 0.0160.022 for silent sites, which is not much higher than
0 = 0.014 for total sites in D. melanogaster.
Synonymous sites are the most variable in both species and show the largest difference between the species (Table 7), so they are presumably most likely to accurately reflect differences in effective population size. Using data for seven loci on the third chromosome and the regression method described above (see RESULTS), we estimated
0 at synonymous sites in D. melanogaster to be 0.026, a bit lower than the estimate of 0.03 from ![]()
0 = 0.0200.031 for synonymous sites in D. pseudoobscura (Table 6) completely contains the range estimated for D. melanogaster. While these comparisons are very crude, the result is not unreasonable and suggests little difference in species-level effective population size between D. melanogaster and D. pseudoobscura. Note that we assumed U = 1 in both species. If U in D. pseudoobscura were actually <1 (see above), observed variation would be even closer to its maximal level, i.e., species-level effective population size would be smaller.
It is quite plausible that species-level effective population sizes of these two species in North America may be more similar than had been thought. While the ecology of neither species is well understood, there is no evidence from molecular data that D. melanogaster has experienced a severe bottleneck in establishing its North American populations from very large ancestral African populations. In addition, D. melanogaster's exploitation of abundant agricultural resources certainly provides the opportunity for high population densities.
While species-level effective population size (i.e., Ne,0) may be similar in the two species, molecular evolution at any particular locus will be a function of f0 Ne,0 at that locus, as described above. D. pseudoobscura's higher rates of recombination should allow for faster, more efficient response to selection. In this light, it is interesting that D. melanogaster, the species with a shorter genetic map than D. simulans and D. mauritiana as well as D. pseudoobscura (![]()
Excess of rare variants:
No difference in the amount of selection is required to explain patterns of variation in these two species, in spite of their seemingly very different evolutionary histories. This apparent similarity may be coincidental, obscuring important differences in several underlying parameters, or it may simply reflect the limited resolution of our data. However, it may also reflect an unexpected similarity in biology suggested by the frequency distributions of variation. Our data, together with previously published results (![]()
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The possibility that D. pseudoobscura is not at equilibrium has been raised before: ![]()
A significant change in population size would violate the equilibrium assumption of the background selection model and may affect our analysis in some unknown way. Nonetheless, this reservation probably also applies to North American populations of D. melanogaster, which are thought to be very recently established and may be far from mutation-drift equilibrium for base-pair polymorphisms.
Alternatively, the preponderance of negative Tajima's D's may be due to slightly deleterious variants being maintained at low frequencies throughout the D. pseudoobscura genome. At the five loci for which we have surveyed both coding and noncoding regions, there is a trend toward more negative Tajima's D's in noncoding regions than at synonymous sites. If this difference were significant in a larger sample, it would support this alternative hypothesis rather than the hypothesis of population expansion.
| CONCLUSIONS |
|---|
Patterns of molecular variation across the second chromosome of D. pseudoobscura are consistent with previously published models of the effects of background selection based on data from D. melanogaster. Using these models, the two- to threefold higher levels of silent variation in D. pseudoobscura compared to D. melanogaster appear to be explained by the former species' twofold longer genetic map and a similar species-level effective population size. Our confidence in this conclusion will be improved by mapping and polymorphism data for more loci and evaluation of how departures from a strictly neutral, equilibrium model of background selection affect parameter estimation. In addition, better estimates of the genomic deleterious mutation rate will permit more accurate inferences about species-level effective population size and the importance of positive selection in shaping genomic patterns of variation in these species.
| ACKNOWLEDGMENTS |
|---|
We thank M. Noor for providing flies, a microsatellite marker, and help with Mapmaker; W. Anderson for the D. miranda stock; M. Veuille, F. Depaulis, and members of the Aquadro lab for helpful discussions; and R. Hudson for comments on the manuscript. This work was supported by a grant from the National Institutes of Health to C.F.A. Some of the writing was done while M.T.H. was supported by a Chateaubriand Fellowship from the French government.
Manuscript received October 19, 1998; Accepted for publication July 1, 1999.
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