The Journal of Heredity 2002:93(4)
© 2002 The American Genetic Association 93:254-259
Gene Flow Among Geographically Diverse Housefly Populations (Musca domestica L.): A Worldwide Survey of Mitochondrial Diversity
From the Department of Entomology, Iowa State University, Ames, IA 50011-3222.
Address correspondence to Dr. E. S. Krafsur at the address above, or e-mail: ekrafsur{at}iastate.edu.
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Abstract |
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Single-strand conformation polymorphisms at 16S2 and COII mitochondrial genes were surveyed in 111 housefly samples from North, Central, and South America, Europe, Asia, Africa, and the Western Pacific. Forty-eight phenotypes were detected, of which none were ubiquitous, and 21 (44%) were confined to a single zoogeographical region. Nei's gene diversity index (HS) was 0.27 and was heterogeneous among zoogeographical regions. Phenotypes were the most diverse in the Ethiopian region and least diverse in the Palearctic and Nearctic regions. Hierarchical partitioning of the total diversity among regions (Nei's GRT = 0.49) indicated only a small proportion was shared. The differentiation of populations within regions (GSR) was 0.32. All pairwise estimates of gene flow between zoogeographical regions were less than 0.31 reproducing females per generation (mean 0.19). We conclude that housefly populations are highly structured even though the flies are mobile and easily capable of passive transport by ship and air.
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Introduction |
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The housefly, Musca domestica L. (Diptera: Muscidae), is a cosmopolitan synanthropic insect of medical and veterinary importance (Greenberg 1971). This species exhibits great diversity both morphologically (Hulley 1979; Paterson 1967; Saccà 1967) and genetically (Krafsur et al. 1992; Milani 1967).
Morphological diversity among houseflies has led to the recognition of intraspecific taxonomic status to different forms. Saccà (1967) recognized three forms—calleva, vicina, and nebulo—as constituents of a geographic cline of M. d. sensu stricto, based on the ratio of frons to head width of males and on abdominal coloration. Paterson (1974), on the other hand, rejected Saccà's classification and proposed the subspecific taxon M. d. domestica for all houseflies outside the Ethiopian region. Currently two subspecies are recognized: M. d. calleva Walker (1849) and M. d. curviforceps Saccà and Rivosechi (1955). Both are endemic to the Ethiopian region (Saccà 1967) and have not been identified elsewhere.
There is much diversity in the mechanism of sex determination, including sex chromosome polymorphism, in houseflies (Çakir and Kence 2000; Dübendorfer et al. 1992). Its geographical components in nature are not understood.
Houseflies reproduce year-round in the tropics, but weather patterns, breeding substrates, and insecticide use vary greatly, and may set different selection patterns conducive to local adaptation. Environmental differences among geographically distant housefly populations may also cause genetic differentiation if the rate of gene flow is neutralized by the divergent forces of drift, selection, and mutation (Futuyma 1998). Thus the question follows naturally: How much gene flow exists among housefly populations? There are some data regarding this question.
Surveys of North American houseflies indicate that 53% of 73 allozyme loci are polymorphic with an average of 2.51 ± 1.9 alleles and mean gene diversity of 0.18 ± 0.30. Estimates of FST indicate unrestricted gene flow among Iowa and Minnesota populations (Krafsur et al. 1992). Houseflies do not diapause, but overwinter in closed livestock facilities where they breed slowly and experience abrupt reductions in population size (Krafsur 1985). These bottlenecks cause large fluctuations in gene frequencies because of drift that accrues over the November–April interval, in which breeding rate and population sizes are greatly reduced (Black and Krafsur 1986a,b). This ecological scenario is typical of temperate but not tropical latitudes.
Gene diversity was surveyed in British, African, and North American housefly populations at 17 allozyme and two mitochondrial loci (Krafsur et al. 2000). Fourteen allozyme loci (82%) were polymorphic, with an average of 3.1 alleles per locus. Only 17 of 47 allozyme alleles were shared between African and the two Holarctic samples. Differentiation between African and temperate populations was FST = 0.65, but there was no detectable differentiation between British and North American flies. Ten mitochondrial haplotypes were recorded and none were shared among the three populations.
The mitochondrial genome (mtDNA) in houseflies is a 16 kb circular DNA molecule encompassing genes for proteins, transfer RNAs, and ribosomal RNAs (Roehrdanz 1993). mtDNA is transmitted maternally (Avise 1991), lacks recombination, and evolves faster than nuclear genes (Brown et al. 1979). Variants are said to be selectively neutral. Therefore it is a useful molecular marker to study genetic variation and patterns of maternal gene flow. Here we investigate gene flow among 111 geographically diverse housefly populations by examining genetic variation at mitochondrial loci 16S2 and COII. We have grouped the housefly samples by Wallace's zoogeographical regions.
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Materials and Methods |
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Biological Material
Housefly collections from five continents and six zoogeographical regions (Figure 1) were obtained with the help of collaborators (Table 1). The samples consisted of ethanol-preserved flies, except those from Iowa, which were caught by using sweep nets, placed on ice, and later frozen at -80°C. Samples of 24 flies each were processed for this research.
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DNA Extraction, Primers, and Polymerase Chain Reaction (PCR)
Total DNA was extracted by using the CTAB (hexadecyl-trimethylammonium bromide) method of Boyce et al. (1989) modified by Shahjahan et al. (1995). The oligonucleotide primers N1-J-12585 (5'-GGT CCC TTA CGA ATT TGA ATA TAT CCT-3') and LR-N-12866 (5'-ACA TGA TCT GAG TTC AAA CCG G-3') were used to amplify a 300 bp fragment of the 16S ribosomal RNA (16S2) gene, and the primers C2-J-3279 (5'-GGT CAA ACA ATT GAG TCT ATT TGA AC-3') and C2-N-3494 (5'-GGT AAA ACT ACT CGA TTA TCA AC-3') were used for amplification of a 214 bp fragment of the cytochrome oxidase II (COII) gene (Simon et al. 1994).
DNA amplification was carried out in 25 µl reactions. These consisted of 10x PCR buffer, 0.4 mM dNTP, 1.5 mM MgCl2, 0.2 µg BSA, 0.5 µM each of forward and reverse primers, 0.5–1 µl template DNA, and 0.2 µl Taq DNA polymerase. The mixtures were overlaid with 30 µl of mineral oil. Thermocycling was in a PTC-100 (MJ Research, Woburn, MA) thermocycler with a profile of 30 cycles of 93°C for 30 sec, 50°C for 18 sec, and 72°C for 18 sec.
SSCP Methods and Scoring Gels
SSCP is based on the differential migration of single-strand DNA conformations electrophoresed in native polyacrylamide gels, after which the various conformations separate and occupy different, repeatable positions on the gel (Orita et al. 1989). We used methods suggested by Black and DuTeau (1997) with modifications.
Hoefer 600 vertical slab gels, 1.5 mm thick, were of 9% acrylamide in a 19 acrylamide:1 bis-acrylamide ratio, with 5% glycerol in 1x TBE. The gels were run at 2°C at 250 V for 1000 V-h. The use of thick gels obviated the need for bind silane. Gels were silver stained according to the protocol of Black and DuTeau (1997).
Phenotypes for 16S2 and COII were established by their banding patterns. Alleles at a locus were identified by their migration distances from the gel origin and by their relative migration with respect to the 200 bp fragment of the 
x174HinfI (Promega G1751) size marker (Figure 2).
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Data Analysis
Diversity was analyzed by using the methods of Nei (1987) and Weir (1996). Nei's (1987) method estimates population identity as JS =
pi2, and diversity as he = [n/(n - 1)](1 - pi2), where pi is the frequency of the ith haplotype, and n/(n - 1) corrects for sampling bias. Here he estimates HS, the population diversity, since there is complete linkage among mtDNA loci. JS is the probability that two flies from the same population have the same haplotype, and HS is the probability that ty have different haplotypes.
The diversity unshared between two populations is Dij = 2(Ji + Jj) - Jij, where Jij = pikpjk is the shared identity between populations i and j over k alleles. Dij can be interpreted as the minimum genetic distance between two populations.
The total gene diversity is HT = HS + DSR + DRT, the sum of the diversity within populations (HS), between populations within regions (DSR), and between regions (DRT). The magnitude of genetic differentiation among regions is GRT = DRTHT, and that of populations within regions is GST = DSRHT. The average number of reproducing migrants per generation (Nm) under the infinite allele model is Nm = (1 - GST)/2GST (Takahata and Palumbi 1985). The variance of haplotype frequencies was decomposed into within- and between-zoogeographical regions according to a nested random analysis of variance (ANOVA) model by using Arlequin 2.0 software (Schneider et al. 2000). Gene flow rates were also estimated from private haplotype frequencies (Slatkin 1985; Slatkin and Barton 1989). The average frequency of private haplotypes was taken over all haplotypes, p(1), and used to calculate a gene flow rate according to the relationship log Nm = log[(p[1] + 1.1)/-0.58].
Genotypic Analysis of SSCP Phenotypes
The DNA nucleotide sequences of all SSCP phenotypes were obtained. PCR amplifications were made from flies of each phenotype and locus. To estimate nucleotide diversity within gel phenotypes, two to four flies per phenotype were sequenced. Eight different 16S2 and 17 different COII phenotypes were sequenced. The nucleotide sequences were obtained by using the standard Sanger fluorescent dideoxy termination method in an ABI 377 automated DNA sequencing system.
Nucleotide diversities within and between phenotypes were estimated according to Nei and Kumar (2000, equation 12.56). The average number of nucleotide substitutions per site within phenotypes (
x) was estimated as 3ij[n(n - 1)/2]-1, where ij is the number of nucleotide differences between the ith and jth sequences of phenotype x, and n is the number of sequences compared. The average number of nucleotide substitutions per site between phenotypes (dxy) was estimated by 3dij[n(n - 1)/2]-1, where n is the number of phenotypes and dij is the number of substitutions per site between the ith and jth phenotypes. dij = [-3/4 loge(1 - 4/3pij)], where pij is the proportion of nucleotide differences between the ith and jth phenotypes. Sequences were edited, aligned, compared, and analyzed by using MEGA version 2.0 (Kumar et al. 2001) and DnaSP 3.14 software (Rozas and Rozas 2000).
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Results |
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Genotypic Analysis of SSCP Phenotypes
Of eight 16S2 gel phenotypes, sequencing showed that four actually consisted of at least two genotypes. Three of 20 COII gel phenotypes were found to have the same nucleotide sequences and the raw scores were adjusted accordingly. Four of the remaining 17 phenotypes each showed two or more genotypes. The overall mean was 1.9 genotypes per phenotype and the average resolution was 42% at COII and 67% at 16S2 (Table 2). Thus our data underestimate allelic diversity. The penalty was not great, however, because the average nucleotide diversity within phenotypes was only 4.5% of that between phenotypes.
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Mitochondrial Diversity
Forty-eight phenotypes were detected in 111 populations (Table 3). The overall phenotype frequency distribution was positively skewed (Figure 3). The most frequent three phenotypes accounted for 58% of the flies, but most phenotypes occurred in low frequencies. In fact, 13 (27%) of 48 phenotypes were singular (i.e., detected in one fly only) and a further 8 (17%) were confined to one population. Thus 27 phenotypes were shared among two or more zoogeographical regions.
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No haplotype was found in all samples within a region, but 38 monomorphic populations were detected (Table 3). The number of phenotypes in each zoogeographical region varied from 8 in the Australian region to 22 in the Palearctic region. Each region had one to five singular phenotypes. No private phenotypes were detected in the New World or Oriental regions. Gene diversity was heterogeneous among regions. The Ethiopian region showed the greatest diversity and the Nearctic region the least. Ewens–Watterson neutrality tests (Watterson 1986) indicated populations in each region were at mutation-drift equilibrium (data not shown). Most populations (66%) were polymorphic. Twenty-two of 46 Nearctic and Palearctic populations were monomorphic (48%), but only 3 of 22 populations from the Ethiopian and Neotropical regions were monomorphic (14%). Nevertheless, frequencies of monomorphic populations were homogeneous over zoogeographical regions. The overall distribution of population diversities (HS) was positively skewed (Figure 4).
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Mean diversity within populations was 0.27. Mean within region diversity (DSR) was 0.44 and the among-region diversity (DRT) was 0.68 (Table 4). Hierarchical partitioning of mitochondrial diversity thus indicated approximately 1.5 times more differentiation among than within regions. GST indicated that 19% of haplotype diversity lay in populations, GSR indicated that 32% lay within zoogeographical regions, and GRT showed that 49% of haplotype diversity lay among regions (Table 4).
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Pairwise unshared diversities (Dij) can be taken as estimates of minimum genetic distance and ranged from 0.51 to 0.81 (Table 5). Only 7% of haplotype diversity was shared among zoogeographical regions. No haplotype was ubiquitous. Only 4 phenotypes were shared over four regions, 5 over three regions, 11 over two regions, and 21 phenotypes were confined to a single zoogeographical region. Nine phenotypes were shared between the Palearctic and Nearctic (Table 5). Six Ethiopian phenotypes were shared with the Nearctic, but only two with the Neotropical region.
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ANOVA by the method of Weir and Cockerham (1984) showed that 50% of the variance in haplotype frequency was caused by differences among populations within regions (Table 6). Only 26% of the variance was attributed to regional differences, but 24% lay within populations. The mean correlation of phenotypes in populations relative to the regional totals was
SR = 0.67. RT, the correlation of phenotypes in zoogeographical regions relative to the correlation of phenotypes among all flies, was 0.26. ST = 0.76; it is analogous to FST, the correlation of phenotypes in populations relative to the correlation of phenotypes among all flies. Thus phenotypes were most strongly correlated within populations and much less correlated between regions than within regions, as would be expected under a hierarchical island model.
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Gene Flow
Pairwise zoogeographical differentiation and rates of gene flow are shown in Table 7. Populations within the Nearctic region were the most differentiated and Ethiopian populations were the least differentiated. Estimated rates of gene flow varied from 0.11 to 0.31, with a mean of 0.21 reproducing females per generation. The average level of gene flow among all populations by the private allele method estimated 0.39 migrants (equivalent to FST = 0.56) and
ST predicts 0.16 migrants. The differences are trivial when considering that both methods of estimating Nm are only approximately independent of selection and mutation (Slatkin 1985).
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Discussion |
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M. domestica is a colonizing species, closely associated with humans and their animals, and this accounts for its cosmopolitan distribution. Demographic research in Iowa has shown that, in the warm months, an average adult female at eclosion will generate 128 eggs in her lifetime, and that population doubling time is about 5 days (Krafsur 1985). Thus a single gravid female can invade a suitable patch and generate a flourishing population, only to disappear when resources are no longer available. This scenario can explain the rather high proportion (34%) of monomorphic samples even though 48 phenotypes were recorded.
Diversities were the least in Nearctic and Palearctic populations and greatest among Ethiopian populations. Annual overwintering population collapse in temperate regions is the most likely explanation for these low diversities (Black and Krafsur 1986a,b; Krafsur 1985). The observation is supported by comparatively large diversities among Neotropical houseflies, for they too are thought to have originated from Old World populations and one might expect low diversities accruing from founder effects. Instead, the haplotype data are consistent with multiple introductions in the New World. It is unknown where M. domestica originated, but Skidmore (1985) and Pont (1991) suggest the southern Palearctic region, particularly the Middle East, is a likely location.
Estimates of Population and Regional Differentiation
We detected a strong spatial component in the worldwide distribution of mtDNA phenotypes. The skewed distribution of haplotype frequencies and gene diversities, and the high proportion (21/48 = 44%) of regionally and local private phenotypes indicate restricted dispersal and gene flow of female houseflies. Differentiation between regions (GRT = 49%) was greater than differentiation within regions (GSR = 32%), also indicative of a high degree of structuring at all hierarchies. GST indicated only 19% lay within populations. The corresponding estimates by ANOVA were broadly similar, indicating that 24% of haplotype variation lay within populations, 26% in populations within zoogeographical regions, and 50% among regions.
Gene Flow Among Regions and Populations
Gene flow among zoogeographical regions estimated by Nei's index was 0.21 reproducing females per generation. Considering all populations, Slatkin's private allele method produced an estimate of 0.39 and Weir and Cockerham's ST predicted 0.16 migrants. In general, one reproducing migrant per generation is enough to prevent population differentiation at selectively neutral loci through genetic drift alone (Wright 1978).
There is much opportunity for assisted passages of houseflies via commercial transport. Indeed, early surveys showed that houseflies travel well and are the most commonly detected hitchhiking insect (West 1951). Dispersal by aircraft would seem to add greatly to the propensity of houseflies for long-distance travel. However, our data indicate that regional populations are probably at mutation-drift equilibrium, and it seems likely that only a tiny fraction of transported female houseflies actually reproduce in new environments. Polymorphic mechanisms of sex determination may be related to the low rates of gene flow, although evidence indicates the variation exists within populations (e.g., Çakir and Kence 2000). There does not seem to be any evidence bearing on the question of between-population variation in sex determination because most research was based on laboratory cultures. The phenotypic expression of sex determination polymorphism is sex ratio distortion.
Although our study provides only estimates of maternal gene flow rates, it indicates a considerable differentiation among housefly populations worldwide. Hale and Singh (1991) used restriction fragment length polymorphisms (RFLPs) to investigate mtDNA diversity in 114 Drosophila melanogaster isofemale laboratory populations originating from 18 locations worldwide. They found much differentiation among the 18 populations (GST = 0.66). Laboratory populations from the Euro-African region were the most diverse and those from the Western Hemisphere were the least diverse. Thus housefly population genetics seem to be similar to that of D. melanogaster, an unsurprising result in that both are colonizing species and both are commensals of man. The level of structuring observed in housefly populations is consistent with its colonizing strategy and boom and bust dynamics, which have both local and seasonal components. The origins and subsequent dispersal of M. domestica is unrecorded, but a scenario of worldwide dispersal largely by the agency of man is not contradicted by the data presented here.
It will be interesting to see if nuclear markers such as microsatellites afford a different picture of gene flow among housefly populations, for gene flow through migrant male flies may, in principle, be greater than estimated here for the females. That question can be answered, in principle, because highly polymorphic microsatellite loci have now been characterized in houseflies (Endsley et al. 2002).
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Acknowledgments |
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This is journal paper no. 19175 of the Iowa Agricultural and Home Economics Experiment Station, projects 3447 and 3457, contributing to regional project S-274 and supported in part by Hatch Act and State of Iowa funds. We thank the people listed in Table 1 for collecting and sending to us house flies.
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Footnotes |
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Corresponding Editor: Ross MacIntyre
Received January 20, 2002
Accepted June 10, 2002
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References |
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