Influence of spatial and temporal heterogeneities on the estimation of demographic parameters in a continuous population using individual microsatellite data

Drift and migration disequilibrium are very common in animal and plant populations. Yet their impact on methods of estimation of demographic parameters was rarely evaluated especially in complex realistic population models. The effect of such disequilibria on the estimation of demographic parameters depends on the population model, the statistics, and the genetic markers used. Here we considered the estimation of the product Dsigma2 from individual microsatellite data, where D is the density of adults and sigma2 the average squared axial parent-offspring distance in a continuous population evolving under isolation by distance. A coalescence-based simulation algorithm was used to study the effect on Dsigma2 estimation of temporal and spatial fluctuations of demographic parameters. Estimation of present-time Dsigma2 values was found to be robust to temporal changes in dispersal, to density reduction, and to spatial expansions with constant density, even for relatively recent changes (i.e., a few tens of generations ago). By contrast, density increase in the recent past gave Dsigma2 estimations biased largely toward past demographic parameters values. The method was also robust to spatial heterogeneity in density and estimated local demographic parameters when the density is homogenous around the sampling area (e.g., on a surface that equals four times the sampling area). Hence, in the limit of the situations studied in this article, and with the exception of the case of density increase, temporal and spatial fluctuations of demographic parameters appear to have a limited influence on the estimation of local and present-time demographic parameters with the method studied.     

Variogram analysis of the spatial genetic structure of continuous populations using multilocus microsatellite data

A geostatistical perspective on spatial genetic structure may explain methodological issues of quantifying spatial genetic structure and suggest new approaches to addressing them. We use a variogram approach to (i) derive a spatial partitioning of molecular variance, gene diversity, and genotypic diversity for microsatellite data under the infinite allele model (IAM) and the stepwise mutation model (SMM), (ii) develop a weighting of sampling units to reflect ploidy levels or multiple sampling of genets, and (iii) show how variograms summarize the spatial genetic structure within a population under isolation-by-distance. The methods are illustrated with data from a population of the epiphytic lichen Lobaria pulmonaria, using six microsatellite markers. Variogram-based analysis not only avoids bias due to the underestimation of population variance in the presence of spatial autocorrelation, but also provides estimates of population genetic diversity and the degree and extent of spatial genetic structure accounting for autocorrelation.     

New methods employing multilocus genotypes to select or exclude populations as origins of individuals

A new method for assigning individuals of unknown origin to populations, based on the genetic distance between individuals and populations, was compared to two existing methods based on the likelihood of multilocus genotypes. The distribution of the assignment criterion (genetic distance or genotype likelihood) for individuals of a given population was used to define the probability that an individual belongs to the population. Using this definition, it becomes possible to exclude a population as the origin of an individual, a useful extension of the currently available assignment methods. Using simulated data based on the coalescent process, the different methods were evaluated, varying the time of divergence of populations, the mutation model, the sample size, and the number of loci. Likelihood-based methods (especially the Bayesian method) always performed better than distance methods. Other things being equal, genetic markers were always more efficient when evolving under the infinite allele model than under the stepwise mutation model, even for equal values of the differentiation parameter F(st). Using the Bayesian method, a 100% correct assignment rate can be achieved by scoring ca. 10 microsatellite loci (H approximately 0.6) on 30-50 individuals from each of 10 populations when the F(st) is near 0.1.     

Dissimilarity of individual microsatellite profiles under different mutation models: Empirical approach

Microsatellites (simple sequence repeats, SSRs) still remain popular molecular markers for studying neutral genetic variation. Two alternative models outline how new microsatellite alleles evolve. Infinite alleles model (IAM) assumes that all possible alleles are equally likely to result from a mutation, while stepwise mutation model (SMM) describes microsatellite evolution as stepwise adding or subtracting single repeat units. Genetic relationships between individuals can be analyzed in higher precision when assuming the SMM scenario with allele size differences as a proxy of genetic distance. If population structure is not predetermined in advance, an empirical data analysis usually includes (a) estimating proximity between individual SSR profiles with a selected dissimilarity measure and (b) determining putative genetic structure of a given set of individuals using methods of clustering and/or ordination for the obtained dissimilarity matrix. We developed new dissimilarity indices between SSR profiles of haploid, diploid, or polyploid organisms assuming different mutation models and compared the performance of these indices for determining genetic structure with population data and with simulations. More specifically, we compared SMM with a constant or variable mutation rate at different SSR loci to IAM using data from natural populations of a freshwater bryozoan Cristatella mucedo (diploid), wheat leaf rust Puccinia triticina (dikaryon), and wheat powdery mildew Blumeria graminis (monokaryon). We show that inferences about population genetic structure are sensitive to the assumed mutation model. With simulations, we found that Bruvo's distance performs generally poorly, while the new metrics are capturing the differences in the genetic structure of the populations.     

Allele Frequencies at Microsatellite Loci: The Stepwise Mutation Model Revisited

We summarize available data on the frequencies of alleles at microsatellite loci in human populations and compare observed distributions of allele frequencies to those generated by a simulation of the stepwise mutation model. We show that observed frequency distributions at 108 loci are consistent with the results of the model under the assumption that mutations cause an increase or decrease in repeat number by one and under the condition that the product Nu, where N is the effective population size and u is the mutation rate, is larger than one. We show that the variance of the distribution of allele sizes is a useful estimator of Nu and performs much better than previously suggested estimators for the stepwise mutation model. In the data, there is no correlation between the mean and variance in allele size at a locus or between the number of alleles and mean allele size, which suggests that the mutation rate at these loci is independent of allele size.     

Simultaneous estimation of all the parameters of a stepwise mutation model.

Minisatellite and microsatellite are short tandemly repetitive sequences dispersed in eukaryotic genomes, many of which are highly polymorphic due to copy number variation of the repeats. Because mutation changes copy numbers of the repeat sequences in a generalized stepwise fashion, stepwise mutation models are widely used for studying the dynamics of these loci. We propose a minimum chi-square (MCS) method for simultaneous estimation of all the parameters in a stepwise mutation model and the ancestral allelic type of a sample. The MCS estimator requires knowing the mean number of alleles of a certain size in a sample, which can be estimated using Monte Carlo samples generated by a coalescent algorithm. The method is applied to samples of seven (CA)n repeat loci from eight human populations and one chimpanzee population. The estimated values of parameters suggest that there is a general tendency for microsatellite alleles to expand in size, because (1) each mutation has a slight tendency to cause size increase and (2) the mean size increase is larger than the mean size decrease for a mutation. Our estimates also suggest that most of these CA-repeat loci evolve according to multistep mutation models rather than single-step mutation models. We also introduced several quantities for measuring the quality of the estimation of ancestral allelic type, and it appears that the majority of the estimated ancestral allelic types are reasonably accurate. Implications of our analysis and potential extensions of the method are discussed.SINCE the discovery that a large number of loci with tandemly repeated sequences in human and many eukaryote species are highly polymorphic because of copy number variation of the repeats in different individuals (Jeffreys 1985; Litt and Luty 1989; Weber and May 1989), allele size data from such loci are rapidly becoming the dominant source of genetic markers for genome mapping, forensic testing, and population studies. Loci with repeat sequences longer than 5 bp are generally referred to as minisatellite or variable number tandem repeat loci, and those with repeat sequences between 2 to 5 bp are referred to as microsatellite or short tandem repeat loci (Tautz 1993). Because mutations change the copy number of such loci in a stepwise fashion, rapid accumulation of population samples from minisatellite and microsatellite loci has resurrected the interest of the stepwise mutation model (SMM), which was popular in the 1970s.     

Experimental estimation of mutation rates in a wheat population with a gene genealogy approach

Microsatellite markers are extensively used to evaluate genetic diversity in natural or experimental evolving populations. Their high degree of polymorphism reflects their high mutation rates. Estimates of the mutation rates are therefore necessary when characterizing diversity in populations. As a complement to the classical experimental designs, we propose to use experimental populations, where the initial state is entirely known and some intermediate states have been thoroughly surveyed, thus providing a short timescale estimation together with a large number of cumulated meioses. In this article, we derived four original gene genealogy-based methods to assess mutation rates with limited bias due to relevant model assumptions incorporating the initial state, the number of new alleles, and the genetic effective population size. We studied the evolution of genetic diversity at 21 microsatellite markers, after 15 generations in an experimental wheat population. Compared to the parents, 23 new alleles were found in generation 15 at 9 of the 21 loci studied. We provide evidence that they arose by mutation. Corresponding estimates of the mutation rates ranged from 0 to 4.97 x 10(-3) per generation (i.e., year). Sequences of several alleles revealed that length polymorphism was only due to variation in the core of the microsatellite. Among different microsatellite characteristics, both the motif repeat number and an independent estimation of the Nei diversity were correlated with the novel diversity. Despite a reduced genetic effective size, global diversity at microsatellite markers increased in this population, suggesting that microsatellite diversity should be used with caution as an indicator in biodiversity conservation issues.     

Microsatellite allele sizes: a simple test to assess their significance on genetic differentiation

The mutation process at microsatellite loci typically occurs at high rates and with stepwise changes in allele sizes, features that may introduce bias when using classical measures of population differentiation based on allele identity (e.g., F(ST), Nei's Ds genetic distance). Allele size-based measures of differentiation, assuming a stepwise mutation process [e.g., Slatkin's R(ST), Goldstein et al.'s (deltamu)(2)], may better reflect differentiation at microsatellite loci, but they suffer high sampling variance. The relative efficiency of allele size- vs. allele identity-based statistics depends on the relative contributions of mutations vs. drift to population differentiation. We present a simple test based on a randomization procedure of allele sizes to determine whether stepwise-like mutations contributed to genetic differentiation. This test can be applied to any microsatellite data set designed to assess population differentiation and can be interpreted as testing whether F(ST) = R(ST). Computer simulations show that the test efficiently identifies which of F(ST) or R(ST) estimates has the lowest mean square error. A significant test, implying that R(ST) performs better than F(ST), is obtained when the mutation rate, mu, for a stepwise mutation process is (a) >/= m in an island model (m being the migration rate among populations) or (b) >/= 1/t in the case of isolated populations (t being the number of generations since population divergence). The test also informs on the efficiency of other statistics used in phylogenetical reconstruction [e.g., Ds and (deltamu)(2)], a nonsignificant test meaning that allele identity-based statistics perform better than allele size-based ones. This test can also provide insights into the evolutionary history of populations, revealing, for example, phylogeographic patterns, as illustrated by applying it on three published data sets.     

Importance of a pilot study for non-invasive genetic sampling: genotyping errors and population size estimation in red deer

Population size information is critical for managing endangered or harvested populations. Population size can now be estimated from non-invasive genetic sampling. However, pitfalls remain such as genotyping errors (allele dropout and false alleles at microsatellite loci). To evaluate the feasibility of non-invasive sampling (e.g., for population size estimation), a pilot study is required. Here, we present a pilot study consisting of (i) a genetic step to test loci amplification and to estimate allele frequencies and genotyping error rates when using faecal DNA, and (ii) a simulation step to quantify and minimise the effects of errors on estimates of population size. The pilot study was conducted on a population of red deer in a fenced natural area of 5440 ha, in France. Twelve microsatellite loci were tested for amplification and genotyping errors. The genotyping error rates for microsatellite loci were 0–0.83 (mean=0.2) for allele dropout rates and 0–0.14 (mean=0.02) for false allele rates, comparable to rates encountered in other non-invasive studies. Simulation results suggest we must conduct 6 PCR amplifications per sample (per locus) to achieve approximately 97% correct genotypes. The 3% error rate appears to have little influence on the accuracy and precision of population size estimation. This paper illustrates the importance of conducting a pilot study (including genotyping and simulations) when using non-invasive sampling to study threatened or managed populations.     

Adult survival and microsatellite diversity in possums: effects of major histocompatibility complex-linked microsatellite diversity but not multilocus inbreeding estimators

Adult survival is perhaps the fitness parameter most important to population growth in long-lived species. Intrinsic and extrinsic covariates of survival are therefore likely to be important drivers of population dynamics. We used long-term mark-recapture data to identify genetic, individual and environmental covariates of local survival in a natural population of mountain brushtail possums (Trichosurus cunninghami). Rainfall and intra-individual diversity at microsatellite DNA markers were associated with increased local survival of adults and juveniles. We contrasted the performance of several microsatellite heterozygosity measures, including internal relatedness (IR), homozygosity by loci (HL) and the mean multilocus estimate of the squared difference in microsatellite allele sizes within an individual (mean d ²). However, the strongest effect on survival was not associated with multilocus microsatellite diversity (which would indicate a genome-wide inbreeding effect), but a subset of two loci. This included a major histocompatibility complex (MHC)-linked marker and a putatively neutral microsatellite locus. For both loci, diversity measures incorporating allele size information had stronger associations with survival than measures based on heterozygosity, whether or not allele frequency information was included (such as IR). Increased survival was apparent among heterozygotes at the MHC-linked locus, but the benefits of heterozygosity to survival were reduced in heterozygotes with larger differences in allele size. The effect of heterozygosity on fitness-related traits was supported by data on endoparasites in a subset of the individuals studied in this population. There was no apparent density dependence in survival, nor an effect of sex, age or immigrant status. Our findings suggest that in the apparent absence of inbreeding, variation at specific loci can generate strong associations between fitness and diversity at linked markers.     

Determination of the minimum number of microsatellite markers for individual genotyping in wild boar (Sus scrofa) using a test with close relatives

In the context of developing a noninvasive, practicable method for population size estimation in wild boar, we present a stepwise procedure to reduce the number of required microsatellite markers for individual genotyping. Step1: an initial marker set of 12 microsatellite loci was tested for species specificity with nontarget DNA and resulted in an exclusion of two markers. Step 2: a variability test regarding heterozygosity and deviations from Hardy–Weinberg equilibrium led to the rejection of two further markers. Step 3: the remaining eight markers were tested for transferability across populations with three separate wild boar sample sets. Step 4: on the basis of probability of identity values, a reduction from eight to five markers was possible. Step 5: a novel test using tissue samples from female wild boars and their embryos provided evidence that four variable microsatellite markers and one sex marker are sufficient for individual identification of close relatives. Step 6: feces samples were finally used to estimate PCR (PS) and genotyping success (GS). In conclusion, we recommend a specific four-marker combination with both PS and GS >50% for a reliable individual identification in noninvasive population size estimation of wild boar.     

Microsatellite analysis of genetic diversity in the Chinese alligator (<Emphasis Type="Italic">Alligator sinensis</Emphasis>) Changxing captive population

Chinese alligator (Alligator sinensis) is a critically endangered species endemic to China. In this study, the extent of genetic variation in the captive alligators of the Changxing Reserve Center was investigated using microsatellite markers derived from American alligators. Out of 22 loci employed, 21 were successfully amplified in the Chinese alligator. Sequence analysis showed loci in American alligators had a bigger average size than that of the Chinese alligators and the longest allele of an individual locus almost always existed in the species with longer stretch of repeat units. Eight of the 22 loci were found to be polymorphic with a total of 26 alleles present among 32 animals scored, yielding an average of 3.25 alleles per polymorphic locus. The expected heterozygosity (H _E) ranged at a moderate level from 0.4385 to 0.7163 in this population. Compared to that in the American alligators, a lower level of microsatellite diversity existed in the Changxing population as revealed by about 46% fewer alleles per locus and smaller H _E at the homologous loci. The average exclusion power and the ability to detect shared genotypes and multiple paternity were evaluated for those markers. Results suggested that when the polymorphic loci were combined, they could be sensitive markers in genetic diversity study and relatedness inference within the Chinese alligator populations. The level of genetic diversity present in the current Changxing population indicated an important resource to complement reintroductions based on the individuals from the other population. In addition, the microsatellite markers and their associated diversity characterized in this population could be utilized to further investigate the genetic status of this species.     

Genetics of recent habitat contraction and reduction in population size: does isolation by distance matter?

Fragmentation and loss of natural habitats are recognized as major threats to contemporary flora and fauna. Detecting past or current reductions in population size is therefore a major aim in conservation genetics. Statistical methods developed to this purpose have tended to ignore the effects of spatial population structure. However in many species, individual dispersal is restricted in space and fine-scale spatial structure such as isolation by distance (IBD) is commonly observed in continuous populations. Using a simulation-based approach, we investigated how comparative and single-point methods, traditionally used in a Wright-Fisher (WF) population context for detecting population size reduction, behave for IBD populations. We found that a complex 'quartet' of factors was acting that includes restricted dispersal, population size (i.e. habitat size), demographic history, and sampling scale. After habitat reduction, IBD populations were characterized by a stronger inertia in the loss of genetic diversity than WF populations. This inertia increases with the strength of IBD, and decreases when the sampling scale increases. Depending on the method used to detect a population size reduction, a local sampling can be more informative than a sample scaled to habitat size or vice versa. However, IBD structure led in numerous cases to incorrect inferences on population demographic history. The reanalysis of a real microsatellite data set of skink populations from fragmented and intact rainforest habitats confirmed most of our simulation results.     

gimlet: a computer program for analysing genetic individual identification data

Growing interest in microsatellite genotyping, combined with noninvasive genetic sampling has led to the increased production of data. New tools to analyse these data are required. gimlet is a user‐friendly software package designed to perform several simple tasks: (i) construction of consensus genotypes from repeated genotyping; (ii) estimation of genotyping error rates; (iii) identification of identical genotypes; (iv) comparison of new genotypes to a set of reference genotypes; (v) determination of the kinship; and (vi) estimation of several population parameters such as allele frequencies, heterozygosity, probability of identity, and population size.     

Assessing the genetic diversity in Argopecten nucleus (Bivalvia: Pectinidae), a functional hermaphrodite species with extremely low population density and self‐fertilization: Effect of null alleles

Argopecten nucleus is a functional hermaphroditic pectinid species that exhibits self‐fertilization, whose natural populations have usually very low densities. In the present study, the genetic diversity of a wild population from Neguanje Bay, Santa Marta (Colombia), was estimated using microsatellite markers, and the effect of the presence of null alleles on this estimation was assessed. A total of 8 microsatellite markers were developed, the first described for this species, and their amplification conditions were standardized. They were used to determine the genotype of 48 wild individuals from Naguanje Bay, and 1,010 individuals derived from the offspring of 38 directed crosses. For each locus, the frequencies of the identified alleles, including null alleles, were estimated using the statistical package Micro‐Checker, and the parental genotypes were confirmed using segregation analysis. Three to 8 alleles per locus with frequencies from 0.001 to 0.632 were detected. The frequencies of null alleles ranged from 0.10 to 0.45, with Ho from 0.0 to 0.79, and He from 0.53 to 0.80. All loci were in H‐W disequilibrium. The null allele frequencies values were high, with lower estimations using segregation analysis than estimated using Micro‐Checker. The present results show high levels of population genetic diversity and indicate that null alleles were not the only cause of deviation from H‐W equilibrium in all loci, suggesting that the wild population under study presents signs of inbreeding and Wahlund effect.     

Genetic variation and island biogreography: Microsatellite and mitochondrial DNA variation in island populations of the Australian bush rat, Rattus fuscipes greyii

To understand the impact of various factors on the maintenance of genetic variation in natural populations, we need to focus on situations where at least some of these factors are removed or controlled. In this study, we used highly variable, presumably neutral, microsatellite and mtDNA markers to assess the nature of genetic variation in 14 island and two mainland populations of the Australian bush rat, where there is no migration between islands. Thus we are controlling for selection and gene flow. Both marker sets revealed low levels of diversity within the small island populations and extreme differentiation between populations. For six microsatellite loci, all of the small island populations had less genetic variation than the mainland populations; reduction in allelic diversity was more pronounced than loss of heterozygosity. Kangaroo Island, the large island population, had similar levels of diversity to the mainland populations. A 442 base pair (bp) section of the mtDNA control region was screened for variation by outgroup heteroduplex analysis/temperature gradient gel electrophoresis (OHA/TGGE). Only three of the 13 small island populations showed haplotypic diversity: Gambier (2), Waldegrave (2), and Eyere (3). The level of haplotypic diversity in the small island populations was similar to that on the mainland, most likely reflecting a recent population bottleneck on the mainland. In contrast, Kangaroo Island had 9 mtDNA haplotypes. The dominant factor influencing genetic diversity on the islands was island size. No correlation was detected between genetic diversity and the time since isolation or distance form the mainland. The combination of genetic drift within and complete isolation among the small island populations has resulted in rapid and extreme population divergence. Population pair-wise comparisons of allele frequency distributions showed significant differences for all populations for all loci (F _st = 0.11–0.84, R _st = 0.07–0.99). For the mtDNA control region, 92.6% of variation was apportioned between populations; only the Pearson islands shared a haplotype. Mantel tests of pair-wise genetic distance with pair-wise geographic distance showed no significant geographical clustering of haplotypes. However, population substructuring was detected within populations where sampling was conducted over a broader geographical range, as indicated by departures from Hardy-Weinberg equilibrium. Thus substructuring in the ancestral population cannot be ruled out. The dominant evolutionary forces on the islands, after the initial founder event, are stochastic population processes such as genetic drift and mutation. This revised version was published online in July 2006 with corrections to the Cover Date.     

"Neighbourhood" size, dispersal and density estimates in the prickly forest skink (Gnypetoscincus queenslandiae) using individual genetic and demographic methods

Dispersal, or the amount of dispersion between an individual's birthplace and that of its offspring, is of great importance in population biology, behavioural ecology and conservation, however, obtaining direct estimates from field data on natural populations can be problematic. The prickly forest skink, Gnypetoscincus queenslandiae, is a rainforest endemic skink from the wet tropics of Australia. Because of its log-dwelling habits and lack of definite nesting sites, a demographic estimate of dispersal distance is difficult to obtain. Neighbourhood size, defined as 4piDsigma2 (where D is the population density and sigma2 the mean axial squared parent-offspring dispersal rate), dispersal and density were estimated directly and indirectly for this species using mark-recapture and microsatellite data, respectively, on lizards captured at a local geographical scale of 3 ha. Mark-recapture data gave a dispersal rate of 843 m2/generation (assuming a generation time of 6.5 years), a time-scaled density of 13 635 individuals * generation/km2 and, hence, a neighbourhood size of 144 individuals. A genetic method based on the multilocus (10 loci) microsatellite genotypes of individuals and their geographical location indicated that there is a significant isolation by distance pattern, and gave a neighbourhood size of 69 individuals, with a 95% confidence interval between 48 and 184. This translates into a dispersal rate of 404 m2/generation when using the mark-recapture density estimation, or an estimate of time-scaled population density of 6520 individuals * generation/km2 when using the mark-recapture dispersal rate estimate. The relationship between the two categories of neighbourhood size, dispersal and density estimates and reasons for any disparities are discussed.     

Migration and genetic structure of the grain aphid (Sitobion avenae) in Britain related to climate and clonal fluctuation as revealed using microsatellites

Genetic structuring of populations reflects the interaction of genetic drift, mutation, migration and selection, with influences from life history. Aphids are interesting in this regard as they have the potential for unusually high levels of dispersal and natural selection, which typically counter each other. In the present study, winged grain aphids Sitobion avenae (F.) were collected in four 12.2-m high suction traps along a north-south transect in Britain in order to eliminate sampling bias from plant hosts (cereals and grasses; Poaceae), it being known that these insects show host adaptation demonstrable using molecular markers. Samples were analysed at four polymorphic microsatellite loci over two consecutive years. Population allele frequencies were similar nationally during the two years, although clonal diversity varied greatly between sites and years. In the first sampling year following a harsh winter, diversity was found to display a latitudinal clinal trend: the proportion of unique clones (genotypes) increased with latitude. However, this pattern was less apparent the following year, after a milder winter. Nonetheless, overall FST analysis showed that there was little spatial genetic structuring in either sampling year. These data support the view that the insect is highly migratory and also support a theoretical model and previous data suggesting that the reproductive mode is clinal in S. avenae. This appears to be because natural selection (reduced reproductive success of asexual genotypes under cold conditions) is sufficiently powerful to overcome the homogenizing effects of strong migration. There was no clear evidence for isolation by distance for the genetic data obtained. The data are compared with similar data from other aphid species and other insects. Only by the collection of such data sets can an accurate picture be built up relating genetic variability to flight behaviour, including migratory ambit in this group of insects since, due to their small size and rapid dilution in the air, other marking approaches are impracticable over large geographical distances.     

Complex mutational patterns and size homoplasy at maize microsatellite loci

Microsatellite markers have become one of the most popular tools for germplasm characterization, population genetics and evolutionary studies. To investigate the mutational mechanisms of maize microsatellites, nucleotide sequence information was obtained for ten loci. In addition, Single-Strand Conformation Polymorphism (SSCP) analysis was conducted to assess the occurrence of size homoplasy. Sequence analysis of 54 alleles revealed a complex pattern of mutation at 8/10 loci, with only 2 loci showing allele variation strictly consistent with stepwise mutations. The overall allelic diversity resulted from changes in the number of repeat units, base substitutions, and indels within repetitive and non-repetitive segments. Thirty-one electromorphs sampled from six maize landraces were considered for SSCP analysis. The number of conformers per electromorph ranged from 1 to 7, with 74.2% of the electromorphs showing more than one conformer. Size homoplasy was apparent within landraces and populations. Variation in the amount of size homoplasy was observed within and between loci, although no differences were detected among populations. The results of the present study provide useful information on the interpretation of genetic data derived from microsatellite markers. Further efforts are still needed to determine the impact of these findings on the estimation of population parameters and on the inference of phylogenetic relationships in maize investigations. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Genetic variation of Pinus uncinata (Pinaceae) in the Pyrenees determined with cpSSR markers

The genetic variation within and between 13 populations (385 individuals) of Pinus uncinata was analyzed with ten chloroplast microsatellite markers. Both the infinite allele mutation and stepwise mutation model (SMM) have been applied to the analysis of the genetic structure and the geographical distribution of haplotypic variation. High level of genetic diversity and low but significant differentiation among compared population were found. Three marginal populations, Sierra de Cebollera, Margaride Mountains and Sierra de Gúdar are strongly differentiated from the rest. Mutations following SMM-like process contributed significantly to the regional differentiation. The pattern of genetic structure observed in mountain pine is common in conifers with a wide distribution range. Lack of significant genetic structuring may be a result of a recent fragmentation of a historically larger population and/or interspecific hybridization and introgression. The southernmost populations from the Sierra Cebollera and the Sierra de Gúdar are the most genetically distinct. This suggests a long period of spatial isolation and/or origin from different ancestral populations.