Previous Article |
Table of Contents
| Next Article
* Department of Organismal Biology and Anatomy, University of
Chicago, 1027 East 57th Street, Chicago, IL 60637-1508; and
Contributed by Eviatar Nevo, September 11, 2001
Substantial genetic differentiation, as great as among
species, exists between populations of Drosophila
melanogaster inhabiting opposite slopes of a small canyon.
Previous work has shown that prezygotic sexual isolation and numerous
differences in stress-related phenotypes have evolved between D.
melanogaster populations in "Evolution Canyon," Israel,
in which slopes 100-400 m apart differ dramatically in aridity, solar
radiation, and associated vegetation. Because the canyon's width is
well within flies' dispersal capabilities, we examined genetic changes
associated with local adaptation and incipient speciation in the
absence of geographical isolation. Here we report remarkable genetic
differentiation of microsatellites and divergence in the
regulatory region of hsp70Ba which encodes the major
inducible heat shock protein of Drosophila, in the two populations. Additionally, an analysis of microsatellites suggests a
limited exchange of migrants and lack of recent population bottlenecks. We hypothesize that adaptation to the contrasting microclimates overwhelms gene flow and is responsible for the genetic and phenotypic divergence between the populations.
thermotolerance|hsp70|P
element|genetic distance|premating isolation
A recurrent issue in
evolutionary biology is the amount of genetic isolation required for
incipient species to diverge from a common ancestor, with geographical
isolation and its impact on gene flow a prominent source of genetic
isolation (1-3). Indeed, Mayr (4, 5) has stressed repeatedly the role
of geographical separation of populations in the origin of species.
Although several evolutionary mechanisms may give rise to new species
in contiguous populations, in the absence of these mechanisms gene flow
would seem to exert a potent homogenizing force on incipient isolates (6, 7). Nonetheless, profound adaptive radiation of species can occur
without large scale geographical isolation, as in the >450 species of
haplochromine cichlids from Lake Malawi (8-11). Critics reasonably may
dispute that such cases are evidence for speciation without geographic
separation, because in Lake Malawi ( Accordingly, we have investigated "Evolution Canyon," Israel,
where Drosophila melanogaster occurs on north-
and south-facing slopes with greatly differing climatic regimes and in
the intervening region; the slopes are 400 m apart at the top and
100 m apart at the bottom (12-14). Although adult
Drosophila can traverse several kilometers in a single day
(15), populations on each slope have diverged in body size, heat and
desiccation tolerance, oviposition thermal preference, fluctuating
asymmetry, rates of mutation and recombination, and mate preference
(16-18). We thus ask: Have the populations likewise diverged
genetically according to microsatellite markers and a candidate gene
strongly linked to resistance to environmental stress? Is this
divergence consistent with genetic isolation despite the contiguity of
the D. melanogaster populations in the canyon? Finally, does
the divergence implicate any evolutionary mechanism(s) as its cause?
To address these questions, we analyzed both putatively neutral
(microsatellites) and non-neutral (hsp70Ba, a heat shock
gene) markers in D. melanogaster collected from the middle
elevation of each slope. Microsatellites, abundant repetitive DNA
sequences with motifs 2-6-nucleotides long, are ideal tools for the
study of population history. In particular, they can elucidate
migration rates between populations and detect recent population growth or decline (19-23). In D. melanogaster, hsp70Ba
is one of five genes encoding Hsp70, a heat-inducible molecular
chaperone that plays a crucial role in inducible thermotolerance and
resistance to other stresses (24). Because thermotolerance is related
to Hsp70 levels, nucleotide variation affecting Hsp70 levels can be a
target of selection. Such variation potentially occurs in the
hsp70Ba promoter, where D. melanogaster from
Evolution Canyon are polymorphic for a 1.2-kb P
element insertion that interrupts a regulatory region essential for
high hsp70 transcription. We report remarkable differences
in the frequencies of both microsatellites and the P
element-bearing hsp70Ba allele (henceforth
hsp70BaP) between D. melanogaster inhabiting the two slopes <400 m apart. These
differences are consistent with local adaptation to contrasting microclimates, overwhelming gene flow between the adjacent habitats.
Flies.
Flies were collected from the two midslope stations 90 m above sea
level on the opposite slopes of Evolution Canyon (Lower Nahal Oren, Mt.
Carmel, Israel) during August-September, 1997. First, isofemale lines
were established from the samples with 25 lines per slope. Next, 10 females and 10 males of each isofemale line were combined in population
cages to construct north-facing slope (NFS) and south-facing slope
(SFS) synthetic populations. The populations were maintained as mass
cultures with random mating for 50-55 generations on standard
cornmeal-sugar-yeast-agar medium in half-pint bottles at 24 ± 1°C and on a 12/12 light/dark cycle.
Microsatellite Detection.
We sampled 39 females from NFS and 39 females from SFS. DNA extracts
were prepared with a standard proteinase K protocol according to Gloor
et al. (25). PCR primers were designed for 15 loci according
to Schug et al. (26). Primer sequences and
amplification conditions are available also at
http://www.mbg.cornell.edu/aquadro/microsatellite.html. Primers were labeled with a carbocyanine dye (Cy-5) on the 5' end. Each
20-µl reaction mixture contained 2 µg of template DNA, 100 pmol/µl of each primer, 1.5-2.5 mM MgCl2, 2 mM
dNTPs, 2 µl of magnesium-free buffer and 0.1 µl of 500U
Taq polymerase (Sigma). The thermocycling profile was 45 cycles of 94°C for 30 s, 52-60°C for 75 s, and 72°C
for 6 min. PCR products were visualized by electrophoresis on
denaturing sequencing gels with an ALFexpress II DNA automated
sequencer and protocols of APBiotech (27). Samples were loaded with an
internal lane standard, usually PstI-cut lambda, and labeled
with ROX, a red fluorescent dye. Fragment sizes were determined with
ALFWIN FRAGMENT ANALYZER 1.03 software (APBiotech).
hsp70BaP Screening.
Single-fly DNA preparations were prepared from individual flies as
described above. The hsp70Ba promoter region was amplified from individual flies by adding 2 µl of template DNA to buffer [10
mM Tris·HCl (pH 9.0)/50 mM KCl/0.1% Triton X-100]
with 1.5-3.0 mM MgCl2, 0.2 mM each dNTP, 5 pmol of each
primer, and 1.25 units of Taq DNA polymerase (Promega) per
25-µl reaction. The primers were: upper, 5'-GCAAGCAATCATCATCCAAT-3',
and lower, 5'-ACTGTGTTTCTGGGGTTCAT-3'. These primers flank a
polymorphic P element insertion site. To determine
P element frequency, this amplification was performed on
individual males and females in conjunction with an additional PCR that
contained the same lower primer as described above and a P
element-specific upper primer (5'-GCCTTCTTTTATCTTTTCTGG-3'). For PCR
amplification of hsp70Ba promoters to be cloned and
sequenced, 1 µl of template DNA from individuals was added to buffer
[50 mM KCl/50 mM Tris·HCl (pH 8.3)] with 1.5 mM
MgCl2, 0.2 mM of each dNTP, 5 pmol of each primer (flanking
primers as described above), and 2.5 units MasterAmp Extra Long DNA
polymerase mix (Epicentre Technologies, Madison, WI) per 100-µl
reaction. Reaction conditions for all PCRs consisted of an initial 1.5 min at 94°C, 35 cycles of 92°C for 1 min, 54°C for 1 min, and
72°C for 2.5 min and a final step at 72°C for 5 min.
Evolution
Genetic evidence for adaptation-driven incipient speciation of
Drosophila melanogaster along a
microclimatic contrast in "Evolution Canyon," Israel
,
,
, and
,
Institute of Evolution, University of Haifa, Mount
Carmel, Haifa 31905, Israel
![]()
Abstract
Top
Abstract
Introduction
Methods
Results
Discussion
References
![]()
Introduction
Top
Abstract
Introduction
Methods
Results
Discussion
References
500-km long) and other such
instances, potential spatial and ecological separation are large
relative to the dispersal abilities of the speciating populations.
![]()
Methods
Top
Abstract
Introduction
Methods
Results
Discussion
References
Statistical Analysis of Microsatellites. Each locus was examined for gene diversity, heterozygosity, and genetic differentiation measured by Wright's F statistics (FST; ref. 28), by using POPGENE (http://www.ualberta.ca/~fyeh/index.htm) and GENEPOP (29). The significance of FST values was assessed with allelic permutations generated by FSTAT (5,000 resamplings; ref. 30). Because no direct sequence data for microsatellites were available in this study, we determined approximate (maximal) repeat numbers for each allele by dividing the PCR product size by the number of base pairs in a single repeat (according to ref. 26). We investigated the relationship between (i) gene diversity, (ii) heterozygosity, (iii) variance of the maximal repeat number, and (iv) number of alleles as dependent variables and (i) slope, (ii) marker chromosomal location, and (iii) recombination rate per chromosome physical unit length as independent variables. Whenever feasible, P values from exact as opposed to asymptotic or Monte Carlo methods are reported (31). These were computed mainly with STATXACT 4 (Cytel; http://www.cytel.com; ref. 32).
Because a bottleneck in one or both populations can affect the estimation of genetic distance (33), the program BOTTLENECK (http://www.ensam.inra.fr/URLB/bottleneck/pub.html; refs. 34 and 35) was used to assess whether studied populations were subject to a demographic decline. This program detects a deficiency in the number of alleles observed given the expected heterozygosity and the principle that under mutation-drift equilibrium allelic diversity is reduced faster than heterozygosity (36). Three significance tests (sign test, standardized differences test, and Wilcoxon sign-rank test) and three mutation models (infinite allele, two-phased, and stepwise mutation) were implemented. To obtain maximum likelihood estimates of migration rates between slopes and effective population sizes of NFS and SFS, we analyzed a coalescence/Monte Carlo Markov Chain process, generated by MIGRATE (http://evolution.genetics.washington.edu/lamarc/migrate.html; refs. 22, 37) and run on SunOS 5.6. The estimation process uses an expansion of the coalescent theory that includes migration and Metropolis-Hastings importance sampling. The following assumptions are made: populations have constant sizes through time such that they do not grow or decline, and the mutation rate µ is constant (but may vary across loci according to a gamma distribution). Additionally, suppositions of the coalescence theory (sensu Kingman, ref. 38) need to be valid. The parameters P to estimate using genealogies G with data D were
= 4Neµ and
= 4Nem, where
Ne is the effective population size
and m is migration rate per generation. The likelihood
formula is based on the product between the genealogy likelihood
(D|G) and the prior probability of the
coalescent genealogy
|
| |
Results |
|---|
|
|
|---|
Microsatellites.
Despite a small number of total alleles and low heterozygosity, many of
the alleles in both the NFS and SFS populations were private (Tables
1 and 2). Thus, because other allele
frequencies were also very different, Nei's (39) genetic distance
(D = 0.566) and the
FST statistic of genetic
differentiation between slopes are
remarkably high (Table 3). The two populations did not differ significantly in gene diversity (HST),
heterozygosity (H), variance in the maximal repeat number
(Var), or number of alleles (exact Mann-Whitney test,
P > 0.05 in each case).
Microsatellite variability depended on
chromosome location (Spearman rank correlation =
0.41, P < 0.025 for HST and
distance (in cM) to centromere, and Spearman rank correlation =
0.32, P < 0.1 for H and distance). The
number of alleles was correlated (Rs = 0.45, P < 0.02) with recombination rate per DNA unit
length (40). Although DMHSP82 (chromosome III, 63B9) was the most
variable locus, on average chromosome III did not vary more than
chromosomes X and II. Of the loci analyzed, DMPROSPER (III 86E1) is
located nearest the hsp70 clusters (III 87A7, 87C1), but its
allelic frequencies did not deviate significantly from the average.
|
|
|
|
are NFS (0.782 <
< 0.921) and SFS (0.818 <
< 0.943). For
the migration rate, 4Nem, the
0.95 HPD intervals are: from NFS into SFS (1.620 <
< 2.249) and from SFS into NFS (1.252 <
< 1.818). For a comparison, the average gene flow M estimated directly from
FST, M = (1/FST
1)/4 (41), was
0.835.
hsp70BaP Frequency.
Sequencing of the highly conserved transcribed region of the
hsp70Ba gene in the Evolution Canyon lines expectedly
revealed little polymorphism (not presented here, but see GenBank
accession nos. AF 385405-385408). By contrast, the lines were
polymorphic for a 1,222-bp insertion in the hsp70Ba
promoter. Sequencing identified this insertion as a nonautonomous
P element at position
184 relative to transcription start
(GenBank accession no. AF377341). This P element intervenes
between the second and third of the four heat shock elements (HSEs)
located in the hsp70Ba promoter. Ninety-six individuals from
NFS included five hsp70BaP homozygotes and
55 heterozygotes (an allelic frequency of 33.9%), and 124 SFS
individuals included three heterozygotes (a frequency of 1.2%). This
interslope difference in genotype frequencies is highly significant
(P < 0.0001 by using exact permutation test).
| |
Discussion |
|---|
|
|
|---|
Interslope Genetic Divergence. Our assay of microsatellite variability revealed striking genetic differentiation between populations derived from the opposite canyon slopes, with genetic distance (D = 0.566) as large as that between sibling Drosophila species (allozyme data, refs. 42-44). For example, D values obtained from allozyme data and ranging from 0.5 to 0.6 have been recorded for the D. melanogaster-Drosophila simulans species pair and Drosophila willistoni group [summarized by Coyne and Orr (43, 44)]. Clearly, comparisons between microsatellite- and allozyme-based distances should be taken with caution because of the higher microsatellite mutation rate (45). Nonetheless, to our knowledge this is the highest intraspecies genetic distance ever reported for Drosophila, approached only by a D of 0.44 between D. melanogaster populations 15 km apart from one another in the Brazzaville area of the Congo (46).
Similarly, the FST value for NFS and SFS populations was also high in comparison with other reports (Table 5), even when the relatively large standard error of the estimate is considered. If microsatellite size homoplasy, which may occur both among and within species, is taken into account, even higher coefficients of genetic divergence are expected (49, 50). Numerous private alleles and several near-private alleles in both populations strongly affect the D and FST values. Although other genetic distance measures have been developed specifically for microsatellite data, e.g., RST or
µ2 (33, 51, 52), we chose to use
D and FST for two reasons: (i) the ease of comparing our results with others' and
(ii) the behavior of other measures is not obvious when the
assumptions of the stepwise mutation model are violated. Indeed,
microsatellites may follow a complex nonstepwise mutation pattern (49).
|
Chromosome Ecology. In our data, intraslope genetic variation (HST) decreased with marker distance from the centromere, a strong suppressor of recombination. This may reflect a negative association between allelic variation and recombination, which is contrary to the trend in Drosophila (and other taxa) and potentially caused by background selection and selective sweeping (53). The association between allele number and distance from the centromere was negative but not significant (data not shown), whereas the correlation between allele number and recombination rate (40) was positive and significant at P < 0.02. This inconsistency resists simple explanation, but could be caused by high variation in recombination rate (54, 55) or background/sweeping selection and diversifying/balanced selection interacting with recombination in opposite ways (54, 56, 57).
hsp70Ba. The hsp70BaP allele was 28 times more frequent in NFS than in SFS. These large differences in microsatellite and hsp70BaP frequencies are consistent with low but nonzero gene flow between NFS and SFS populations. Estimated migrants from NFS into SFS and from SFS into NFS do not exceed three and two individuals per generation, respectively. Calculations of migration rate from microsatellite frequencies likely underestimate actual migration, because genetic methods describe only migration events resulting in gene pool changes. Whatever degree of sympatry Drosophila populations in Evolution Canyon represent, even a largely reduced gene flow is expected eventually to homogenize allele frequencies between populations (6-7). Yet, the interslope genetic distance we report is equivalent to those from allozyme data associated with complete reproductive isolation (43, 44). We hypothesize that divergent natural selection acting in the two microclimates overwhelmed the homogenizing effect of migration with a subsequent shift in mating preferences (18, 58), in turn yielding a correlated differentiation of genetic markers. Indeed, reproductive isolation is a frequent byproduct of adaptive response to different selection regimes (ref. 59 and references therein). Because reproductive isolation is an essential component of incipient speciation within the range of a common ancestor (60), we emphasize that Drosophila in Evolution Canyon prefer mates native to their own slope; although the different lines from the same slope did not deviate more than 1.3% from random mating, the deviation between lines from opposite slopes exceeded 15% (18, 58).
The between slope difference in hsp70BaP frequency is consistent with differential thermal selection. During and after heat shock, the heat shock transcription factor (HSF) trimerizes and binds to HSEs in the hsp70 promoter to release the paused transcriptional apparatus and induce transcription (61). Although HSEs 1 and 2 are sufficient for some transcriptional activation, the additional HSEs increase transcription. The P element insertion disrupts the hsp70Ba promoter, intervening between the proximal and distal HSE pairs, and may therefore alter cooperative binding and transcription. Indeed, strains with the P element insertion in the hsp70Ba promoter have lower inducible thermotolerance and lower Hsp70 protein levels than strains lacking the insertion (unpublished data). Thus, the difference in hsp70BaP allele frequency may result from stronger selection against the insertion in the SFS. Although neither our data nor prior work suggest such alternative explanations for the divergence in genetic markers, the divergence could have arisen via (re)colonization of the canyon by individuals from genetically distant ancestral populations, perhaps accompanied by a habitat preference, genetic drift, and/or evolution of the synthetic populations while in laboratory culture. Microsatellite frequencies indicate no bottlenecks, suggesting that genetic drift has not have played a major role in the diversification. Laboratory evolution seems unlikely because microsatellite frequencies in D. melanogaster change slowly in laboratory culture due to relatively low mutation rates (62, 63), and hsp70BaP allele frequency did not change with time. Our findings and hypotheses on the genetic and phenotypic divergence in D. melanogaster are consistent also with patterns both for other drosophilids and unrelated species in Evolution Canyon. Another drosophilid, D. simulans varies in thermotolerance in the same way as does D. melanogaster (17). In addition, their allozyme diversity indices significantly differ across the canyon (14). As with the P element in the hsp70Ba promoter, the frequency of a BARE-1 retrotransposon in the wild barley (Hordeum spontaneum; ref. 64) varies with the height and dryness of the slope on both slopes but especially on the drier SFS. In fact, a 3-fold difference in BARE-1 abundance significantly affects genome and cell size, thereby presumably leading to adaptive changes in the plants' growth rates. Recently, Nevo has hypothesized that incipient sympatric speciation may be ongoing in a soil fungus (Sordaria fimicola) and other taxa (Nostoc, Lotus, etc.) inhabiting Evolution Canyon (see ref. 65 and references therein). The D. melanogaster case presented here, however, is unique not only in detecting massive fine scale genetic differentiation in a very mobile organism but in revealing genetic changes associated with incipient sympatric or near sympatric speciation driven by adaptation to local environments.| |
Acknowledgements |
|---|
We thank Jerry A. Coyne and the four reviewers for constructive
criticism, Kostas Iliadi and Eugenia Rashkovetsky for help during
preparation of this manuscript, Katarzyna Michalak for PCR, Peter
Beerli for computing, and Tomá
Pavli
ek for field assistance. We acknowledge Margaret G. Kidwell, Francisco J. Ayala, Hampton L. Carson, and James F. Crow for constructive comments that
improved the paper. The work was supported by Israel Science Foundation
Grant 02198, United States-Israel Binational Science Foundation Grant
4556, National Science Foundation Grants DGE-0072944, IBN99-72678, and
99-86158, Foundation for Polish Science Grant KBN 6 PO4F 011 16, and
the Ancell-Teicher Research Foundation for Molecular Genetics and Evolution.
| |
Abbreviations |
|---|
NFS, north-facing slope; SFS, south-facing slope; HSE, heat shock element.
| |
Footnotes |
|---|
To whom reprint requests should be addressed.
E-mail: nevo{at}research.haifa.ac.il.
| |
References |
|---|
|
|
|---|
| 1. | Kondrashov, A. S. (1986) Theor. Popul. Biol. 29, 1-15. |
| 2. | Coyne, J. A. & Orr, H. A. (1998) Philos. Trans. R. Soc. London B 28, 287-305. |
| 3. | Kondrashov, A. S. & Kondrashov, F. A. (1999) Nature (London) 6742, 351-354. |
| 4. | Mayr, E. (1963) Animal Species and Evolution (Harvard Univ. Press, Cambridge, MA). |
| 5. | Mayr, E. (1982) in Mechanisms of Speciation, ed. Barigozzi, C. (Liss, New York), pp. 1-19. |
| 6. | Crow, J. F. & Kimura, M. (1970) An Introduction to Population Genetics Theory (Harper & Row, New York). |
| 7. | King, R. B. (1993) Evolution (Lawrence, Kans.) 47, 1819-1833. |
| 8. | Meyer, A. (1993) Trends Ecol. Evol. 8, 279-284. |
| 9. | van Oppen, M. H. L. , Duetsch, J. C. , Turner, G. F. , Rico, C. , Ibrahim, K. M. , Robinson, R. L. & Hewitt, G. M. (1997) Proc. R. Soc. London Ser. B 264, 1803-1812. |
| 10. | Markert, J. A. , Arnegard, M. E. , Danley, P. D. & Kocher, T. D. (1999) Mol. Ecol. 8, 1013-1026. |
| 11. | Danley, P. D. , Markert, J. A. , Arnegard, M. E. & Kocher, T. D. (2000) Evolution (Lawrence, Kans.) 54, 1725-1737. |
| 12. | Nevo, E. (1995) Proc. R. Soc. London Ser. B 262, 149-155. |
| 13. | Nevo, E. (1997) Theor. Popul. Biol. 52, 231-243. |
| 14. | Harry, M. , Rashkovetsky, E. , Pavlicek, T. , Baker, S. , Derzhavets, E. M. , Capy, P. , Cariou, M.-L. , Lachaise, D. , Asada, N. & Nevo, E. (1999) Biologia (Bratisl.) 54, 685-705. |
| 15. | Coyne, J. A. & Milstead, B. (1987) Am. Nat. 130, 70-82. |
| 16. | Rashkovetsky, E. , Korol, A. B. , Pavlicek, T. & Nevo, E. (1997) Drosoph. Inf. Serv. 80, 83-85. |
| 17. | Nevo, E. , Rashkovetsky, E. , Pavlicek, T. & Korol, A. (1998) Heredity 80, 9-16. |
| 18. | Korol, A. , Rashkovetsky, E. , Iliadi, K. , Michalak, P. , Ronin, Y. & Nevo, E. (2000) Proc. Natl. Acad. Sci. USA 97, 12637-12642. (First Published October 24, 2000; 10.1073/pnas.220041397) |
| 19. | Kimmel, M. R. , Chakraborty, R. , King, J. P. , Bamshad, M. , Watkins, W. S. , Watkins, W. S. & Jorde, L. B. (1998) Genetics 148, 1921-1930. |
| 20. | Wilson, I. J. & Balding, D. J. (1998) Genetics 150, 499-510. |
| 21. | Beaumont, M. A. (1999) Genetics 153, 2013-2029. |
| 22. | Beerli, P. & Felsenstein, J. (1999) Genetics 152, 763-773. |
| 23. | Gonser, R. , Donnelly, P. , Nicholson, G. & Di Rienzo, A. (2000) Genetics 154, 1793-1807. |
| 24. | Feder, M. E. & Hofmann, G. E. (1999) Annu. Rev. Physiol. 61, 243-282. |
| 25. | Gloor, G. B. , Preston, C. R. , Johnson-Schlitz, D. M. , Nassif, N. A. , Phillips, R. W. , Benz, W. K. , Robertson, H. M. & Engels, W. R. (1993) Genetics 135, 81-95. |
| 26. | Schug, M. D. , Wetterstrand, K. A. , Gaudette, M. S. , Lim, R. H. & Hutter, C. M. (1998) Mol. Ecol. 7, 57-70. |
| 27. | Amersham Pharmacia. (1998) ALFWINTM FRAGMENT ANALYSER 1.03, User Manual (Amersham Pharmacia, UK, Uppsala, Sweden). |
| 28. | Weir, B. S. & Cockerham, C. C. (1984) Evolution (Lawrence, Kans.) 38, 1358-1370. |
| 29. | Raymond, M. & Rousset, F. (1995) J. Hered. 86, 248-249. |
| 30. | Goudet, J. (1995) J. Hered. 86, 485-486. |
| 31. | Weerahandi, S. (1995) Exact Statistical Methods for Data Analysis (Springer, New York). |
| 32. | Cytel software Corp.. (2000) STATXACT, User Manual (Cambridge, MA). |
| 33. | Hedrick, P. (1999) Evolution (Lawrence, Kans.) 53, 313-318. |
| 34. | Cornuet, J. M. & Luikart, G. (1996) Genetics 144, 2001-2014. |
| 35. | Piry, S. G. , Luikart, G. & Cornuet, J. M. (1996) BOTTLENECK, A Program for Detecting Recent Effective Population Size Reductions from Allele Data Frequencies (INRA, Montpellier, France). |
| 36. | Maruyama, T. & Fuerst, P. A. (1985) Genetics 111, 675-689. |
| 37. | Beerli, P. (1997-2000) MIGRATE, Documentation and Program, part of LAMARC 0.9 (University of Washington, Seattle). |
| 38. | Kingman, J. (1982) Stochastic Proc. Appl. 13, 235-248. |
| 39. | Nei, M. (1978) Genetics 89, 583-590. |
| 40. | Kliman, R. M. & Hey, J. (1993) Mol. Biol. Evol. 10, 1239-1258. |
| 41. | Slatkin, M. (1993) Evolution (Lawrence, Kans.) 47, 264-279. |
| 42. | Ayala, F. J. (1975) Evol. Biol. 8, 1-78. |
| 43. | Coyne, J. A. & Orr, H. A. (1989) Evolution (Lawrence, Kans.) 43, 362-381. |
| 44. | Coyne, J. A. & Orr, H. A. (1997) Evolution (Lawrence, Kans.) 51, 295-303. |
| 45. | Balloux, F. , Brünner, H. , Lugon-Moulin, N. , Hausser, J. & Goudet, J. (2000) Evolution (Lawrence, Kans.) 54, 1414-1422. |
| 46. | Capy, P. , Veuille, M. , Paillette, M. , Jallon, J.-M. , Vouidibio, J. & David, J. R. (2000) Heredity 84, 468-475. |
| 47. | Irvin, S. D. , Wetterstrand, K. A. , Hutter, C. M. & Aquadro, C. F. (1998) Genetics 150, 777-790. |
| 48. | Noor, M. A. F. , Schug, M. D. & Aquadro, C. F. (2000) Genet. Res. 75, 25-35. |
| 49. | Colson, I. & Goldstein, D. B. (1999) Genetics 152, 617-627. |
| 50. | van Oppen, M. J. H. , Rico, C. , Turner, G. F. & Hewitt, G. M. (2000) Mol. Biol. Evol. 17, 489-498. |
| 51. | Slatkin, M. (1995) Genetics 139, 457-462. |
| 52. | Goldstein, D. B. , Linares, A. R. , Cavalli-Sforza, L. & Feldman, M. V. (1995) Proc. Natl. Acad. Sci. USA 92, 11549-11552. |
| 53. | Charlesworth, B. (1996) Genet. Res. 68, 131-149. |
| 54. | Korol, A. B. , Preygel, I. A. & Preygel, S. I. (1994) Recombination Variability and Evolution (Chapman & Hall, London). |
| 55. | Andolfatto, P. & Przeworski, M. (2000) Genetics 156, 257-268. |
| 56. | Stephan, W. , Xing, L. , Kirby, D. A. & Braverman, J. M. (1998) Proc. Natl. Acad. Sci. USA 95, 5649-5654. |
| 57. | Kelly, J. K. & Wade, M. J. (2000) J. Theor. Biol. 204, 83-101. |
| 58. | Iliadi, K., Iliadi, N., Rashkovetsky, E., Minkov, I., Nevo, E. & Korol, A. (2001) Proc. R. Soc. London Ser. B, in press. |
| 59. | Powell, J. R. (1997) Progress and Prospects in Evolutionary Biology: The Drosophila Model (Oxford Univ. Press, London). |
| 60. | Howard, D. J. , Marshall, J. L. , Braswell, W. E. & Coyne, J. A. (2001) Science 291, 1853. |
| 61. | Fernandes, M. , O'Brien, T. & Lis, J. T. (1994) in The Biology of Heat Shock Proteins and Molecular Chaperons, eds. Morimoto, R. I., Tissieres, A. & Georgopoulos, C. (Cold Spring Harbor Lab. Press, Plainview, NY). |
| 62. | Schug, M. D. , Mackay, T. F. C. & Aquadro, C. F. (1997) Nat. Genet. 15, 99-102. |
| 63. | Schug, M. D. , Hutter, C. M. , Noor, M. A. F. & Aquadro, C. F. (1998) Genetica 103, 359-367. |
| 64. | Kalender, R. , Tanskanen, J. , Immonen, S. , Nevo, E. & Schulman, A. H. (2000) Proc. Natl. Acad. Sci. USA 97, 6603-6607. (First Published May 23, 2000; 10.1073/pnas.110587497) |
| 65. | Nevo, E. (2001) Proc. Natl. Acad. Sci. USA 98, 6233-6240. |
This article has been cited by other articles in HighWire Press-hosted journals:
![]() |
A. Korol, E. Rashkovetsky, K. Iliadi, and E. Nevo Drosophila flies in "Evolution Canyon" as a model for incipient sympatric speciation PNAS, November 28, 2006; 103(48): 18184 - 18189. [Abstract] [Full Text] [PDF] |
||||
![]() |
T. K. Ezov, E. Boger-Nadjar, Z. Frenkel, I. Katsperovski, S. Kemeny, E. Nevo, A. Korol, and Y. Kashi Molecular-Genetic Biodiversity in a Natural Population of the Yeast Saccharomyces cerevisiae From "Evolution Canyon": Microsatellite Polymorphism, Ploidy and Controversial Sexual Status Genetics, November 1, 2006; 174(3): 1455 - 1468. [Abstract] [Full Text] [PDF] |
||||
![]() |
D. G. Folk, P. Zwollo, D. M. Rand, and G. W. Gilchrist Selection on knockdown performance in Drosophila melanogaster impacts thermotolerance and heat-shock response differently in females and males J. Exp. Biol., October 15, 2006; 209(20): 3964 - 3973. [Abstract] [Full Text] [PDF] |
||||
![]() |
N. A. Fangue, M. Hofmeister, and P. M. Schulte Intraspecific variation in thermal tolerance and heat shock protein gene expression in common killifish, Fundulus heteroclitus J. Exp. Biol., August 1, 2006; 209(15): 2859 - 2872. [Abstract] [Full Text] [PDF] |
||||
![]() |
V. Y. Shilova, D. G. Garbuz, E. N. Myasyankina, B. Chen, M. B. Evgen'ev, M. E. Feder, and O. G. Zatsepina Remarkable Site Specificity of Local Transposition Into the Hsp70 Promoter of Drosophila melanogaster Genetics, June 1, 2006; 173(2): 809 - 820. [Abstract] [Full Text] [PDF] |
||||
![]() |
J. P. Pollinger, C. D. Bustamante, A. Fledel-Alon, S. Schmutz, M. M. Gray, and R. K. Wayne Selective sweep mapping of genes with large phenotypic effects Genome Res., December 1, 2005; 15(12): 1809 - 1819. [Abstract] [Full Text] [PDF] |
||||
![]() |
J. Sikorski and E. Nevo Adaptation and incipient sympatric speciation of Bacillus simplex under microclimatic contrast at "Evolution Canyons" I and II, Israel PNAS, November 1, 2005; 102(44): 15924 - 15929. [Abstract] [Full Text] [PDF] |
||||
![]() |
J. de Meaux, U. Goebel, A. Pop, and T. Mitchell-Olds Allele-Specific Assay Reveals Functional Variation in the Chalcone Synthase Promoter of Arabidopsis thaliana That Is Compatible with Neutral Evolution PLANT CELL, March 1, 2005; 17(3): 676 - 690. [Abstract] [Full Text] [PDF] |
||||
![]() |
D. N. Lerman and M. E. Feder Naturally Occurring Transposable Elements Disrupt hsp70 Promoter Function in Drosophila melanogaster Mol. Biol. Evol., March 1, 2005; 22(3): 776 - 783. [Abstract] [Full Text] [PDF] |
||||
![]() |
A. Lupu, A. Pechkovskaya, E. Rashkovetsky, E. Nevo, and A. Korol DNA repair efficiency and thermotolerance in Drosophila melanogaster from 'Evolution Canyon' Mutagenesis, September 1, 2004; 19(5): 383 - 390. [Abstract] [Full Text] [PDF] |
||||
![]() |
D. Garbuz, M. B. Evgenev, M. E. Feder, and O. G. Zatsepina Evolution of thermotolerance and the heat-shock response: evidence from inter/intraspecific comparison and interspecific hybridization in the virilis species group of Drosophila. I. Thermal phenotype J. Exp. Biol., July 15, 2003; 206(14): 2399 - 2408. [Abstract] [Full Text] [PDF] |
||||
![]() |
T. Lehmann, M. Licht, N. Elissa, B. T. A. Maega, J. M. Chimumbwa, F. T. Watsenga, C. S. Wondji, F. Simard, and W. A. Hawley Population Structure of Anopheles gambiae in Africa J. Hered., March 1, 2003; 94(2): 133 - 147. [Abstract] [Full Text] [PDF] |
||||
![]() |
D. N. Lerman, P. Michalak, A. B. Helin, B. R. Bettencourt, and M. E. Feder Modification of Heat-Shock Gene Expression in Drosophila melanogaster Populations via Transposable Elements Mol. Biol. Evol., January 1, 2003; 20(1): 135 - 144. [Abstract] [Full Text] [PDF] |
||||
![]() |
W. Wang, F. G. Brunet, E. Nevo, and M. Long Origin of sphinx, a young chimeric RNA gene in Drosophilamelanogaster PNAS, April 2, 2002; 99(7): 4448 - 4453. [Abstract] [Full Text] [PDF] |
||||
![]() |
C. Schlotterer and M. Agis Microsatellite Analysis of Drosophila melanogaster Populations Along a Microclimatic Contrast at Lower Nahel Oren Canyon, Mount Carmel, Israel Mol. Biol. Evol., April 1, 2002; 19(4): 563 - 568. [Abstract] [Full Text] [PDF] |
||||
![]() |
W. Wang, F. G. Brunet, E. Nevo, and M. Long Origin of sphinx, a young chimeric RNA gene in Drosophilamelanogaster PNAS, April 2, 2002; 99(7): 4448 - 4453. [Abstract] [Full Text] [PDF] |
||||
| |||||||||||||||||||||||||||||||||