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Understanding the dispersal and genetic structure of invasive insects across islands is …

Biology Articles » Biomathematics » Genetic variation in the invasive avian parasite, Philornis downsi (Diptera, Muscidae) on the Galápagos archipelago » Methods

- Genetic variation in the invasive avian parasite, Philornis downsi (Diptera, Muscidae) on the Galápagos archipelago

Study species

Philornis downsi (family Muscidae; subfamily Azeliinae; tribe Reinwardtiini) is a semi-haematophagous obligate avian parasite in its three larval stages, whereas adult flies are non-parasitic and feed on organic matter [13]. Adults lay eggs inside the nares of newly hatched nestlings (usually at one to three days old), which hatch into first instar larvae [17,24]. Second and third instar larvae attach externally and feed on nestling blood and tissues over four to six days [13]. Most larvae of P. downsi appear to reach their third instar phase at the time of host fledging. The larvae pupariate at the base of the nesting material and remain for approximately two weeks before emerging as adult flies [13,25].

Study area and sample collection

Philornis downsi were collected from three islands of the Galápagos: Santa Cruz (986 km2; 0° 37'S, 90° 21'W), Floreana (173 km2, 1° 28'S, 90° 48'W), and Isabela (4588 km2, 0° 58'S, 90° 58'W). Fly samples were collected from nests during the January to March finch breeding season in 2004, 2005 and 2006 from two contrasting habitats, the arid lowlands (0–100 m asl) and the humid highlands (300–600 m asl) (Table 1) [see also [26,27]]. The lowlands are characterised by low rainfall, and are dominated by the trees Acacia macracantha, Bursera graveolens, Croton scouleri, Opuntia spp., Pisonia floribunda, and Zanthoxylum fagara [12]. In contrast, the highlands have much higher rainfall [28,29], abundant moss and lichen, and are dominated by the endemic tree Scalesia pedunculata, or S. cordata (Asteraceae) on Isabela Island.

Table 1. Sample sizes of bird nests and P. downsi individuals.

We sampled from one site in each habitat on both Floreana (lowlands, adjacent to the town of Puerto Velasco Ibarra: 1° 16'S, 90° 29'W; highlands, base of Cerro Pajas: 1° 17'S, 090° 27'W) (Figure 1) and Isabela (lowlands: adjacent to town of Puerto Villamil: 0° 57'S, 91° 00'W; highlands: 0° 50'S, 91° 01'W), while on Santa Cruz we sampled from three sites in the lowlands: (1) Garrapatero: 0° 39'S, 90° 28'W; (2) Itabaca: 0° 29'S, 90° 17'W; (3) Punta Estrada, near Puerto Ayora: 0 ° 45'S, 90° 18'W, and one site in the highlands (Los Gemelos: 0° 37'S, 90° 22'W) (Figure 1). All sample sites were approximately 2000–4000 m2, except for the highland site on Isabela, where our sample site was only 100 m2 because habitat fragmentation has reduced the Scalesia forest to small remnant patches. The distance between highland and lowland sites was much shorter on Floreana (3–5 km) than on Santa Cruz and Isabela (both 15–25 km), while on Santa Cruz, the distance between all four sites (1 highland, 3 lowland) varied between 15 and 27 km. Data were obtained from all three islands in 2004, from just Floreana in 2005, and from Santa Cruz and Floreana in 2006 (Table 1).

Figure 1. Map of Santa Cruz, Floreana, and Isabela Islands with sampling locations. Sampling sites on Santa Cruz: S1 = highlands; S2 = lowlands, Punta Estrada; S3 = lowlands, Garrapatero; S4 = lowlands, Itabaca. On Floreana and Isabela, one site each in the lowlands (L) and highlands (H) are indicated.

For the purpose of our study, larvae, puparia and puparia cases were sampled from 64 bird nests of five Darwin finch species (Geospiza fuliginosa, n = 25, Geospiza fortis, n = 15, Camarhynchus parvulus, n = 3, Camarhynchus pauper, n = 4; Cactospiza pallida, n = 1), while one nest was opportunistically sampled from each of the Galápagos mockingbird (Nesomimus parvulus) and the yellow warbler (Dendroica petechia aureola). Fourteen recently fledged nests were sampled for P. downsi where the finch species was unknown. GPS coordinates were recorded at each nest location. Inactive nests were collected and sealed in individual plastic bags and later dismantled for counting of P. downsi individuals. All flies were immediately preserved in 95% ethanol.

DNA extraction and microsatellite typing

DNA extraction was carried out using the salting out procedure described in [30] with the exception that all samples (3 mm2 tissue from each individual) were homogenised and washed three times in 10 mm TRIS prior to digestion with Proteinase K to remove traces of ethanol, excess lipids, and other potential contaminants. Across all three islands, 1012 P. downsi individuals (larvae and pupae) were genotyped (Table 1) using eight microsatellite markers [31]: Pd1 [GenBank: EF608562] Pd2 [EF608556], Pd4 [EF608557], Pd6 [EF608564], Pd7 [EF608558], Pd8 [EF608555], Pd9 [EF608561], Pd10 [EF608563]. Multiplex PCR conditions were followed as described in Dudaniec et al. [31]. Samples were genotyped on an ABI 3730 capillary electrophoresis DNA analyser (Applied Biosystems). A fluorescently labeled size standard (GS500 (-250) LIZ) was run with the samples and alleles were scored using GENEMAPPER version 3.7 (Applied Biosystems). To minimise and estimate genotyping error, each run of the DNA analyser contained eight repeated samples and a control sample run each time. In total, this resulted in 70 individual samples (14.5% of all samples genotyped) being re-amplified and genotyped at least once.

Mitochondrial DNA sequencing

An 822-bp region of the 3' end of the CO1 gene was amplified in five P. downsi individuals collected from Santa Cruz (1 highlands), Floreana (1 highlands, 1 lowlands), and Isabela (1 highlands, 1 lowlands). Samples were amplified using primers M202 (forwards, C1-J-1751 [32]) and M70 (reverse, UEA10 [33]). Amplifications were performed in 10× TaqGold buffer, 25 mM MgCl2, 10 mM total dNTP's, 200 nM each primer, 0.2 U TaqGold polymerase, and 10–50 ng DNA. Amplification conditions were an initial denaturation at 94°C for 9 min, followed by 34 cycles of 94°C for 45 s, 55°C for 45 s, 72°C for 1 min, with a final extension of 72°C for 6 min. Sequencing was performed using the ABI Prism™ Big Dye Terminator Cycle sequencing kit (Applied Biosystems) according to the manufacturer's instructions. Products were sequenced on ABI 3700 (version 3.7) automated DNA sequencers. SeqEd (version 1.0.3) (Applied Biosystems) was used to edit chromatogram files to determine bi-directional consensus sequences and to manually align sequences across samples.

Allele frequencies and data set construction

We calculated allele frequencies using RELATEDNESS 5.0.8 [34] by randomly selecting one individual per sample (n = 64) to eliminate the possibility of including related individuals (a sample is defined as all P. downsi individuals collected from a single bird's nest). Exact tests were performed for each microsatellite locus to test deviation from Hardy-Weinberg equilibrium using GENEPOP[35]. All loci were in Hardy Weinberg equilibrium after sequential Bonferroni correction [36] and these allele frequencies were used for all further analyses. Genetic relatedness among P. downsi offspring within nests of Darwin's finches is low, and the individuals found within each nest are produced by up to approximately five ovipositing females that have each mated with between one and five males (as found by sib-ship reconstruction analysis by Dudaniec et al. in review). To eliminate the effect of sibs in the data, we selected unrelated individuals that were identified using the sib-ship reconstruction method implemented in the program COLONY 1.2 [37]. Each sample of P. downsi individuals taken from an independent bird nest was run in COLONY 1.2, which uses a maximum likelihood method that partitions individuals into pure full-sib families (i.e. monogamous female parent), or full-sib families nested within half-sib families (i.e. polyandrous female parent) using progeny genotypes without known parental genotypes [37,38]. Three runs were performed per sample with different random seed numbers (12, 80, and 243) to ensure data convergence, and a conservative error rate of 5% was implemented based on evidence from the re-genotyping of 70 individuals, in which genotyping error ranged from 0–5% across loci.

We selected one individual per reconstructed maternal family (i.e. one family = the offspring assigned to one putative female parent). In nested-half sib families (i.e. one mother, multiple fathers), individuals were only selected from full sib families with the largest number of members that had the highest posterior probability. Only individuals genotyped at all eight loci were included in the analysis and individuals were not sampled from families that contained Class I or Class II typing errors (identified by COLONY 1.2) [37]. These criteria resulted in a sample size of 158 individuals sampled from 63 bird nests (with between one and six unrelated individuals per sample) (Table 1).

To examine the probability that two randomly selected individuals from the same population will have the same multi-locus genotype, a Probability of Identity (PI) analysis was performed using GIMLET[39]. The output is a cumulative multi-locus PI value, estimated both with and without sample size correction. PI values were calculated for the dataset of 158 individuals using equations of unbiased PI, which assumes that individuals are unrelated, and PI for sibs, which assumes that all individuals are siblings [39].

Inter-island genetic differentiation

Heterozygosity, and pairwise Fst [40] was calculated to examine genetic differentiation between islands (Santa Cruz, Floreana, Isabela) using MICROSATELLITE ANALYSER (MSA) 4.05 [41]. Genotypic differentiation was tested between islands using option 3 with 10 0000 Markov chain iterations in GENEPOP[35]. P-values for multiple tests were adjusted using sequential Bonferroni correction [36]. The AMOVA method [42] was conducted in GENALEX version 6 [43] to partition the total genetic variation into three levels: among islands, among individuals, and within individuals using the Codom-genotypic distance calculation and 9999 permutations.

Population bottleneck analysis

Recently colonised species may experience a population bottleneck, resulting in a reduction in the number of alleles and expected heterozygosity at polymorphic loci. However, alleles may be lost at a faster rate than the loss of heterozygosity, so observed heterozygosity is higher than the expected heterozygosity at equilibrium [44]. The program BOTTLENECK version 1.2.02 [45] was used to test for the presence of a recent population bottleneck for P. downsi by analysing within-population heterozygosity and allele frequency using the constructed dataset of individuals sampled from all islands. Both the stepwise mutation model (SMM) and two-phase model of mutation (TPM) were used, with the latter model being considered the most appropriate for microsatellites. The variance for the TPM was set at 5% and the proportion of SMM in TPM was set at 95% [46]. To determine differences in gene diversity across loci, the Wilcoxin sign-rank test was used as recommended for data sets with less than 20 loci (with 10 000 permutations) [45]. We also examined the allele frequency distribution in order to see whether it is approximately L-shaped (as expected under mutation-drift equilibrium) or not (indicating that a recent bottleneck has provoked a mode shift) as described in [47].

Genetic structure among islands

For inferring genetic structure among the three sampled islands, we conducted two complementary individual-based Bayesian clustering analyses using STRUCTURE 2.1 [48] and the landscape genetics program GENELAND[49] without a priori knowledge of population units and limits. Both software packages implement a Bayesian clustering method that uses a MCMC technique to define the number of populations in a sample that are at Hardy Weinberg Equilibrium. The methods implemented in these two programs differ in that GENELAND determines the optimal number of populations or 'clusters' and then allocates individuals (probabilistically) to these clusters using geographic coordinates, whereas STRUCTURE carries out the allocation sequentially for different numbers of clusters, and then flags the number of clusters with the highest likelihood [50]. In STRUCTURE, the following run parameters were used: admixture without population information used, correlated allele frequency model, a burn-in period of 100 000 simulations followed by a run length of 1 million Markov Chain Monte Carlo (MCMC) simulations and three iterations for each number of potential clusters (defined as k = 1–5) to check for consistency of results. Estimation of k was taken to be the values of k with the highest Pr (X|k).

In contrast to STRUCTURE, the algorithm implemented in GENELAND[49] is considered to be a powerful clustering method under conditions of low genetic differentiation among populations [51,52]. The model infers genetic discontinuities between populations in space from multilocus genotypes obtained from geo-referenced individuals [49,53]. All individuals from the same sample (i.e. same bird nest) were allocated the same GPS coordinates. GPS coordinates were available for 57/63 nests (Santa Cruz: n = 18; Floreana: n = 36; Isabela: n = 3) (138 individuals in total). Samples for which GPS coordinates were missing were excluded from the analysis. To firstly infer the number of genetic clusters (k) in our data set, we used the Dirichlet model, which assumes independent allele frequencies with the following parameters: 1000 000 MCMC iterations, uncertainty attached to spatial coordinates = 0, variable number of populations = TRUE, minimum k = 1, maximum k = 5, and spatial information included in the model = TRUE. This procedure was performed three times to establish consistency of k across runs. The established k was then run five times to check the consistency of individual assignment to the inferred populations across runs. The same parameters were used but k was fixed at the modal number found in the first analyses. These five runs were post-processed (with a burn-in of 1000 × 100 iterations) to obtain posterior probabilities of population membership for each individual. Consistency of results across the five runs was checked visually.

Inferred populations were further examined for heterozygosity, allelic richness (corrected for sample size), observed (Ho) and expected (He) heterozygosity, inbreeding coefficients (Fis), and genetic differentiation (estimated using Fst) using FSTAT v. 2.9.3 [54].

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