Signification evolutive du polygenotypisme des populations na- turelles, L'annee. L'analyse genetique des populations naturelles, in Reunion Internationale de. Examen de populations de Sphaeroma serratum, sur le cotes dela peninsule. ´ ne ´tique des populations BIO 3519 Ge (3,0,0) 3 cr. Description du cours Combinaison de l’observation et de la th´eorie pour comprendre les changements g´en´etiques qui prennent place ` a l’int´erieur et entre les populations.
Populations studied and number of successfully genotyped samples from each population ( n). Measures of genetic variation based on 16 microsatellite loci: Na: number of alleles, AR: average allelic richness, He: expected heterozygosity, Ho: observed heterozygosity, P: polymorphism.
Island size is shown in hectares and island isolation was calculated as nearest shore-to-shore distances from all other islands (km). Island location was assigned as central (c) or peripheral (p) based on the position of the island within the species range of M. Island age is shown in million years. (i) Contemporary samplesBlood samples were collected on filter paper after a small puncture of the wing vein of live birds.
Extraction and PCR were performed using previously published methods. Concentrations of DNA extracts were standardized at 20 ng µl −1 (Quant-iT PicoGreen dsDNA Quantitation, Invitrogen) and the following 17 microsatellite loci were amplified: MpAAT26, Nes01, Nes03, Nes04, Nes06, Nes10, Nes12, Nes13, Nes14, Nes15, Nes16, Nes17, Nes18, Nes19, Nes20, Nes22 and Nes23.
Except for MpAAT26 which was developed in Mimus polyglottos by, all microsatellite loci were previously designed in our laboratory with the aim of obtaining short microsatellite products (less than 200 bp) for amplification in highly fragmented, low quality DNA. Microsatellites were amplified in four independent multiplex reactions as described in.
MpAAT26 was amplified separately under the same conditions as markers in multiplex reactions B and C. Fragment analyses were performed on a 3730 DNA Analyser using Gene-Scan-500 LIZ size standard (ABI) and G enemapper v. 4 software (ABI) followed by manual proofreading of genotypes.
To estimate the frequency of genotyping error rates, six per cent of the contemporary samples were amplified and genotyped a second time at each locus. (ii) Historic samplesSmall toe pad samples (approx. 4 mm 2 in size) were collected from the historic specimens and half of each sample was used for DNA extraction using QIAamp DNA Micro kit (QIAGEN) following the manufacturer's tissue protocol. Negative controls were included and all work with historic samples was carried out in a dedicated historic DNA laboratory where no contemporary mockingbird DNA had ever been present.
The laboratory had an independent air-handling system, was under positive air displacement and was irradiated with UV light to destroy DNA following each laboratory session. The DNA concentration in the historic samples was measured through quantitative PCR (QPCR) using SYBR Green I detection format (Roche Diagnostics, Switzerland) by amplifying part of the 7 intron of the fibrinogen gene β-subunit. Using the FIB-BI7U and FIB-BI7L primers developed by, we sequenced M. Trifasciatus DNA to design two new primers for QPCR, NesFib7F (5′-CTGGATGCAATAGTCAGAGACTG-3′) and NesFib7R (5′-CCTGCCTCTTTCTTCAGGAC-3′), in order to reduce the amplicon length to 104 bp.
The ABI 7500 Fast Real-Time PCR System (Applied Biosystems) was used for QPCR amplification and detection. Negative controls were included in the experimental runs and 1–2 replicates were done for each historic sample. QPCR was prepared in a 20 µl reaction volume containing 10 µl of FastStart Universal SYBR Green Master (ROX), 300 nM of each primer and 2 µl template DNA following the operator's manual for PCR conditions. DNA concentrations were determined using a standard curve consisting of 11 dilutions (of modern M. Trifasciatus DNA) ranging from 0.005 to 20 ng µl −1.PCR amplification of the 17 microsatellites was carried out as described in with the exception that the total reaction volume of 5 µl contained 2.5 µl Multiplex PCR Master Mix (QIAGEN) and 2 µl of template historic DNA. Negative controls were included to monitor potential contamination. PCR conditions were changed slightly from the protocol described in, with an initial denaturation step of only 12 min followed by 38 cycles of amplification at 59°C for all four panels.
To assure reliable genotyping of the historic samples, PCR amplification was replicated four times for each sample at each locus. This should be sufficient as 2–3 replicates have previously been shown to accurately score the genotype in 99 per cent of sample- and locus-combinations in museum samples containing reasonable amounts of DNA. Fragment analyses and genotyping were done as described above. The software G imlet was used to determine dropout and genotyping error rates per locus as well as consensus genotypes for each sample based on the four replicates. (c) Diversity within populationsDeviations from Hardy–Weinberg equilibrium (HWE) for each locus were tested with allele randomizations within samples (1000 permutations per test) and overall samples (10 000 permutations) using FS tat 2.9.3.1 package and Bonferroni corrections. Genotypic equilibrium between all pairs of loci in each population was tested using G-statistics with Bonferroni corrections (FS tat; 84 000 permutations).
To describe within-population genetic diversity, we calculated standard parameters such as mean number of alleles (Na), allelic richness (AR, standardized to the smallest sample size), observed (Ho) and expected heterozygosity (He) and polymorphism (P) in FS tat and G enetix v 4.05. (i) Contemporary populationsWe tested for the predicted positive correlation between genetic diversity and population size using He, AR and P as estimators of genetic diversity. Because no empirical information on current population sizes was available except for the two M. Trifasciatus populations, we used island size as a surrogate for population size. In a multiple regression analysis, we entered island size as an explanatory variable and the within-population indices of genetic diversity as dependent variables in separate analyses. As more isolated islands are less likely to receive gene flow than islands situated at the centre of the archipelago and older island populations might have lost more genetic diversity due to drift and reduced gene flow, we entered island isolation and island age as further explanatory variables. Average isolation for each island was calculated by adding up nearest shore-to-shore distances to all other islands and dividing the sum by the total number of islands minus one.
For island age, we used the youngest age estimate for each island (D. Geist 2005–2008, unpublished data). The three explanatory variables (island size, isolation and age) were not correlated (all r 2. (ii) Temporal change within populationsWe performed a Wilcoxon signed-rank test with the variables He, AR and P to test whether these within-population indices of genetic diversity changed significantly over the last century. Based on the assumption that genetic drift is stronger in smaller and more isolated populations, we also investigated whether change in genetic diversity was dependent on island size or isolation. To this end, we performed a multiple regression analysis using size and isolation as explanatory variables and the relative change in He, AR and P between the historic and contemporary populations as dependent variables (i.e. 1−He Contemporary/He CAS, etc).
To quantify the change in gene frequencies within each island since 1906 (i.e. Temporal differentiation), we calculated estimator τ for Wright's F ST (G enepop on the web v.
3.4; ) for each CAS-contemporary population pair (called ‘temporal F ST’ below) and related it to island size or isolation, respectively, in a linear regression analysis. We chose F ST to estimate temporal differentiation within islands because of the relatively small time scale involved (approx. 25 generations assuming a generation time of 4 years; ). Over such short time scales drift is the dominant process creating local differentiation and the effects of mutation are minimal. (iii) Effective population sizeIn the absence of migration, selection and mutation, effective population size can be estimated using temporal changes in allele frequencies. We used our temporal dataset and the Bayesian coalescent-based method implemented in the program C oN e to calculate the variance effective population size (Ne) for each island population, setting the time between the two sampling periods to 25 generations, the likelihood range for Ne between 2 and 20 000 in steps of 5, and using 1000 Monte Carlo replications. (i) Pair-wise population differentiationDifferentiation over all loci for all contemporary population pairs was estimated using Nei's standard genetic distance Ds calculated in P opulations v.
We chose Ds because it allows for mutation and increases more linearly with time than F ST when considering large time scales and, hence, is a more accurate estimator when estimating evolutionary times. Furthermore, Ds does not assume a specific mutation model and has been shown to perform well with microsatellite data (e.g.;; ). F ST was calculated for comparison. Including only populations of M. Parvulus to avoid species bias, we also tested whether overall differentiation between peripheral islands was higher than between centrally located islands in the archipelago. We tested for isolation-by-distance by contrasting geographical distances and multi-locus Ds-values between all contemporary population pairs of M.
Parvulus and, separately, also between all populations of all four species, using a series of Mantel tests (1000 permutations; ). Geographical distance was measured as the logarithm of each island's nearest shore-to-shore distance from the other islands in the archipelago (; G oogle E arth v 5.0, Google Inc.). (ii) Genetic affinities among species and populationsGenetic affinities among contemporary species and populations were described with a factorial correspondence analysis (FCA) on multilocus genotypes using G enetix v 4.05. FCA displays the genetic differences among populations in a two-dimensional graphical space. Genetic distances among populations were also assessed by building an evolutionary tree based on Nei's Ds using UPGMA and performing 1000 bootstrap resamplings among loci with P opulations v. 1.2.30.All statistical analyses were done using JMP v.
8 (SAS Institute Inc., Cary, NC). (a) GenotypingAmplification and genotyping of the contemporary samples was very successful reaching nearly 100 per cent, with only one locus not amplifying in a single individual. Genotyping error and dropout rates in the contemporary samples were below 0.1 per cent. Not surprisingly, amplification success for the historic samples was lower, most probably due to the much lower DNA concentrations (0.01–254 pg µl −1 with an average of 28 pg µl −1) and lower DNA quality of historic samples in general.
On average, 78 per cent of the PCR reactions with the historic samples resulted in successful amplification (across individuals and loci) and the combined allelic dropout and false allele rates of all four replicates of the historic samples were seven per cent (s.d. = 0.08) and 2.8 per cent (s.d.
= 0.04), respectively. Consensus genotypes were cross-checked for reliability by hand. Additionally, blank negative controls confirmed that cross-contamination was negligible. Forty-two individuals from the CAS collection amplified successfully for less than 10 loci and were therefore excluded from all further analyses. (i) Contemporary populationsAll measures of genetic diversity were significantly related to island size (He: F 1,14 = 15.9, b = 0.03 ± 0.01, p = 0.001; AR: F 1,14 = 33.4, b = 0.14 ± 0.05, p. ( a) Temporal F ST between contemporary and historic populations as a function of island size (in ha; log scale).
Differentiation clearly increased more strongly in smaller populations as shown by the dotted regression line ( F ST = −0.899–0.354. log(island size)). Overlapping data points from islands with similar size were slightly modified to improve visual representation. ( b) Estimates of effective population size (Ne) with lower and, where available, upper estimation limits plotted against island size (in ha; log scale). The dotted line shows the linear regression line (Ne = −507.07 + 148.94.
log(island size)). A strong positive linear correlation was also found when both Ne and island size were ln-transformed ( r 2 = 0.92, p.
(iii) Effective population sizeWe were able to estimate effective population size for all 12 populations for which we had temporal samples. The lowest maximum likelihood Ne estimate was 43 individuals for Champion, and the highest was 1591 individuals for Isabela, reflecting the smallest and largest islands investigated (see the electronic supplementary material). In six cases no upper confidence interval could be calculated, resulting in an infinite upper support limit. Ne estimates were strongly positively correlated with island size ( r 2 = 0.88, p. (i) Pair-wise population differentiationPair-wise differentiation (Ds) between all contemporary populations and species from different islands ranged from 0.004 to 1.988 (see the electronic supplementary material). Pair-wise Ds and F ST correlated strongly ( r 2 = 0.75, p.
(ii) Genetic affinities among species and populationsGenetic differences among contemporary populations based on an FCA analysis revealed three main clusters, with M. Trifasciatus most clearly differentiated from the other species , all populations of M. Parvulus forming a second cluster and M. Macdonaldi and M.
Melanotis together forming a third cluster. Similar population relationships were found in the UPGMA tree, which showed all populations of M. Parvulus separated from the other three species, populations of M. Macdonaldi most closely together with M. Melanotis and M. Trifasciatus forming a separate branch. As we were unable to root our tree due to the lack of microsatellite data from a related species, we cannot show the evolutionary position of the clusters.