Estimates of gene flow, genetic substructure and population heterogeneity in bracken (Pteridium aquilinum)

Bracken [ Pteridium aquilinum (L.) Kuhn] is a cosmopolitan species and is a noxious weed in many areas. Because of its abundance, particularly in Britain, bracken affords an ideal system for investigating various aspects of population genetics and evolution. High mobility of dispersal units (spores) suggests that rates of gene flow among distant populations should be high. Gene flow is a major evolutionary force that influences the genetic structure of populations. To examine the effects of gene flow on population heterogeneity and population substructuring in bracken, starch gel electrophoresis of enzymes was used to provide the necessary genetic database. Allele frequency data at 21 loci were obtained for seven British populations, one Majorcan and one from the eastern United States. A model was employed to estimate the amount of gene flow ( Nm ) at several levels. Gene flow among British populations was extremely high ( Nm = 36.51), one of the highest estimates reported for plants. Among eight European populations gene flow was lower (but still considered high) at Nm = 2.47. Trans-Atlantic gene flow was low ( Nm = 0.0926).
F -statistics were used to assess population heterogeneity and substructuring. The data indicate that, compared with other species, there is very little genetic differentiation among British populations of bracken. Indeed, it appears that the whole island is behaving as a single randommating population. This result is consistent with high levels of gene flow. Only one population (on the Isle of Arran) showed statistically significant genetic substructuring. Habitat heterogeneity on the island and age structure are hypothesized as possible causes of this result.
The data reported here support previous studies demonstrating that bracken is genetically polymorphic and is an outcrossing species.     

Conflicts in maintaining biodiversity at multiple scales

Biodiversity consists of multiple scales, including functional diversity in ecological traits, species diversity and genetic diversity within species, and is declining across the globe, largely in response to human activities. While species extinctions are the most obvious aspect of this, there has also been a more insidious loss of genetic diversity within species. While a vast literature concerns each of these scales of biodiversity, less is known about how different scales affect one another. In particular, genetic and species diversity may influence each other in numerous ways, both positively and negatively. However, we know little about the mechanism behind these patterns. In this issue of Molecular Ecology, Nestmann et al. (2011) experimentally explore the effect of species and functional diversity and composition of grassland plant communities on the genetic structure of one of the component species. Increasing species richness led to greater changes in the genetic composition of the focal populations over 4 years, primarily because of genetic drift in smaller population sizes. However, there were also genetic changes in response to particular plant functional groups, indicating selective differences driven by plant community composition. These results suggest that different levels of biodiversity can trade-off in communities, which may prove a challenge for conservation biologists seeking to preserve all aspects of biodiversity.     

Can simple population genetic models reconcile partial match frequencies observed in large forensic databases?

A recent study of partial matches in the Arizona offender database of DNA profiles has revealed a large number of nine and ten locus matches. I use simple models that incorporate the product rule, population substructure, and relatedness to predict the expected number of matches in large databases. I find that there is a relatively narrow window of parameter values that can plausibly describe the Arizona results. Further research could help determine if the Arizona samples are congruent with some of the models presented here or whether fundamental assumptions for predicting these match frequencies requires adjustments.     

A C++ Template Library for Efficient Forward-Time Population Genetic Simulation of Large Populations

fwdpp is a C++ library of routines intended to facilitate the development of forward-time simulations under arbitrary mutation and fitness models. The library design provides a combination of speed, low memory overhead, and modeling flexibility not currently available from other forward simulation tools. The library is particularly useful when the simulation of large populations is required, as programs implemented using the library are much more efficient than other available forward simulation programs.     

Rapid microsatellite marker development in the endangered neotropical freshwater turtle Podocnemis lewyana (Testudines: Podocnemididae) using 454 sequencing

Using high throughput sequencing we obtained a large number of microsatellites from Podocnemis lewyana, an endemic turtle from northwestern South America. We used 454 Genome Sequence FLX platform of sheared genomic DNA from randomly sampling approximately 17% of the haploid genome. We identified 86,501 reads (8.1% of all reads) that contained our definition of microsatellite loci. AC and TC were the most abundant motifs in the P. lewyana genome. TGC and AAAC were most abundant tri and tetra-nucleotide motifs respectively. 72.7% of microsatellite reads had flanking sequence regions suitable for primer design and PCR amplification. We validated the identified potentially amplifiable loci (PAL) and tested for polymorphism by selecting 15 loci corresponding to tetranucleotides. Twelve loci showed polymorphism in eight individuals. These findings demonstrates that microsatellite detection using next-generation sequencing is an efficient way of getting a lot of loci for listed taxa and in turn will have a large impact on future genetic studies aiming to understand and implement conservation plans for this highly threatened freshwater turtle.     

Is there such a thing as landscape genetics?

For a scientific discipline to be interdisciplinary, it must satisfy two conditions; it must consist of contributions from at least two existing disciplines, and it must be able to provide insights, through this interaction, that neither progenitor discipline could address. In this study, I examine the complete body of peer‐reviewed literature self‐identified as landscape genetics (LG) using the statistical approaches of text mining and natural language processing. The goal here was to quantify the kinds of questions being addressed in LG studies, the ways in which questions are evaluated mechanistically, and how they are differentiated from the progenitor disciplines of landscape ecology and population genetics. I then circumscribe the main factions within published LG studies examining the extent to which emergent questions are being addressed and highlighting a deep bifurcation between existing individual‐ and population‐based approaches. I close by providing some suggestions on where theoretical and analytical work is needed if LGs is to serve as a real bridge connecting evolution and ecology sensu lato.     

A simple derivation and classification of common probability distributions based on information symmetry and measurement scale

Commonly observed patterns typically follow a few distinct families of probability distributions. Over one hundred years ago, Karl Pearson provided a systematic derivation and classification of the common continuous distributions. His approach was phenomenological: a differential equation that generated common distributions without any underlying conceptual basis for why common distributions have particular forms and what explains the familial relations. Pearson's system and its descendants remain the most popular systematic classification of probability distributions. Here, we unify the disparate forms of common distributions into a single system based on two meaningful and justifiable propositions. First, distributions follow maximum entropy subject to constraints, where maximum entropy is equivalent to minimum information. Second, different problems associate magnitude to information in different ways, an association we describe in terms of the relation between information invariance and measurement scale. Our framework relates the different continuous probability distributions through the variations in measurement scale that change each family of maximum entropy distributions into a distinct family. From our framework, future work in biology can consider the genesis of common patterns in a new and more general way. Particular biological processes set the relation between the information in observations and magnitude, the basis for information invariance, symmetry and measurement scale. The measurement scale, in turn, determines the most likely probability distributions and observed patterns associated with particular processes. This view presents a fundamentally derived alternative to the largely unproductive debates about neutrality in ecology and evolution.     

Using parentage analysis to examine gene flow and spatial genetic structure

Numerous approaches have been developed to examine recent and historical gene flow between populations, but few studies have used empirical data sets to compare different approaches. Some methods are expected to perform better under particular scenarios, such as high or low gene flow, but this, too, has rarely been tested. In this issue of Molecular Ecology , Saenz-Agudelo et   al . (2009 ) apply assignment tests and parentage analysis to microsatellite data from five geographically proximal (2–6 km) and one much more distant (1500 km) panda clownfish populations, showing that parentage analysis performed better in situations of high gene flow, while their assignment tests did better with low gene flow. This unusually complete data set is comprised of multiple exhaustively sampled populations, including nearly all adults and large numbers of juveniles, enabling the authors to ask questions that in many systems would be impossible to answer. Their results emphasize the importance of selecting the right analysis to use, based on the underlying model and how well its assumptions are met by the populations to be analysed.     

In defence of model‐based inference in phylogeography

Recent papers have promoted the view that model‐based methods in general, and those based on Approximate Bayesian Computation (ABC) in particular, are flawed in a number of ways, and are therefore inappropriate for the analysis of phylogeographic data. These papers further argue that Nested Clade Phylogeographic Analysis (NCPA) offers the best approach in statistical phylogeography. In order to remove the confusion and misconceptions introduced by these papers, we justify and explain the reasoning behind model‐based inference. We argue that ABC is a statistically valid approach, alongside other computational statistical techniques that have been successfully used to infer parameters and compare models in population genetics. We also examine the NCPA method and highlight numerous deficiencies, either when used with single or multiple loci. We further show that the ages of clades are carelessly used to infer ages of demographic events, that these ages are estimated under a simple model of panmixia and population stationarity but are then used under different and unspecified models to test hypotheses, a usage the invalidates these testing procedures. We conclude by encouraging researchers to study and use model‐based inference in population genetics.     

The effect of a population bottleneck on the evolution of genetic variance/covariance structure

It is well known that standard population genetic theory predicts decreased additive genetic variance (V(a) ) following a population bottleneck and that theoretical models including interallelic and intergenic interactions indicate such loss may be avoided. However, few empirical data from multicellular model systems are available, especially regarding variance/covariance (V/CV) relationships. Here, we compare the V/CV structure of seventeen traits related to body size and composition between control (60 mating pairs/generation) and bottlenecked (2 mating pairs/generation; average F = 0.39) strains of mice. Although results for individual traits vary considerably, multivariate analysis indicates that V(a) in the bottlenecked populations is greater than expected. Traits with patterns and amounts of epistasis predictive of enhanced V(a) also show the largest deviations from additive expectations. Finally, the correlation structure of weekly weights is not significantly different between control and experimental lines but correlations between necropsy traits do differ, especially those involving the heart, kidney and tail length.