Biogeographic population structure of chimeric blades of porphyra in the northeast atlantic reveals southern rich gene pools, introgression and cryptic plasticity

The genus Porphyra sensu lato (Bangiaceae, Rhodophyta), an important seaweed grown in aquaculture, is the most genetically diverse group of the Class Bangiophyceae, but has poorly understood genetic variability linked to complex evolutionary processes. Genetic studies in the last decades have largely focused on resolving gene phylogenies; however, there is little information on historical population biogeography, structure and gene flow in the Bangiaceae, probably due to their cryptic nature, chimerism and polyploidy, which render analyses challenging. This study aims to understand biogeographic population structure in the two abundant Porphyra species in the Northeast Atlantic: Porphyra dioica (a dioecious annual) and Porphyra linearis (protandrous hermaphroditic winter annual), occupying distinct niches (seasonality and position on the shore). Here, we present a large-scale biogeographic genetic analysis across their distribution in the Northeast Atlantic, using 10 microsatellites and cpDNA as genetic markers and integrating chimerism and polyploidy, including simulations considering alleles derived from different ploidy levels and/or from different genotypes within the chimeric blade. For P. linearis, both markers revealed strong genetic differentiation of north-central eastern Atlantic populations (from Iceland to the Basque region of Northeast Iberia) vs. southern populations (Galicia in Northwest Iberia, and Portugal), with higher genetic diversity in the south vs. a northern homogenous low diversity. For. P. dioica, microsatellite analyses also revealed two genetic regions, but with weaker differentiation, and cpDNA revealed little structure with all the haplotypes mixed across its distribution. The southern cluster in P. linearis also included introgressed individuals with cpDNA from P. dioica and a winter form of P. dioica occurred spatially intermixed with P. linearis. This third entity had a similar morphology and seasonality as P. linearis but genomes (either nuclear or chloroplast) from P. dioica. We hypothesize a northward colonization from southern Europe (where the ancestral populations reside and host most of the gene pool of these species). In P. linearis recently established populations colonized the north resulting in homogeneous low diversity, whereas for P. dioica the signature of this colonization is not as obvious due to hypothetical higher gene flow among populations, possibly linked to its reproductive biology and annual life history.info:eu-repo/semantics/publishedVersio

Development of embodied capital: Diet composition, foraging skills, and botanical knowledge of forager children in the Congo Basin

The embodied capital theory states that the extended juvenile period has enabled human foragers to acquire the complex foraging skills and knowledge needed to obtain food. Yet we lack detailed data on how forager children develop these skills and knowledge. Here, we examine the seasonal diet composition, foraging behavior, and botanical knowledge of Mbendjele BaYaka forager children in the Republic of the Congo. Our data, acquired through long-term observations involving full-day focal follows, show a high level of seasonal fluctuation in diet and foraging activities of BaYaka children, in response to the seasonal availability of their food sources. BaYaka children foraged more than half of the time independent from adults, predominantly collecting and eating fruits, tubers, and seeds. For these most-consumed food types, we found an early onset of specialization of foraging skills in children, similar to the gendered division in foraging in adults. Specifically, children were more likely to eat fruit and seed species when there were more boys and men in the group, and girls were more likely than boys to collect tuber species. In a botanical knowledge test, children were more accurate at identifying plant food species with increasing age, and they used fruits and trunks for species identification, more so than using leaves and barks. These results show how the foraging activities of BaYaka children may facilitate the acquisition of foraging skills and botanical knowledge and provide insights into the development of embodied capital. Additionally, BaYaka children consumed agricultural foods more than forest foods, probably reflecting BaYaka’s transition into a horticultural lifestyle. This change in diet composition may have significant consequences for the cognitive development of BaYaka children

Data from: The trouble with isolation by distance

The genetic population structure of many species is characterised by a pattern of isolation by distance (IBD): due to limited dispersal, individuals that are geographically close tend to be genetically more similar than individuals that are far apart. Despite the ubiquity of IBD in nature, many commonly used statistical tests are based on a null model that is completely non-spatial, the Island model. Here, I argue that patterns of spatial autocorrelation deriving from IBD present a problem for such tests as it can severely bias their outcome. I use simulated data to illustrate this problem for two widely used types of tests: tests of hierarchical population structure and the detection of loci under selection. My results show that for both types of tests the presence of IBD can indeed lead to a large number of false positives. I therefore argue that all analyses in a study should take the spatial dependence in the data into account, unless it can be shown that there is no spatial autocorrelation in the allele frequency distribution that is under investigation. Thus, it is urgent to develop additional statistical approaches that are based on a spatially explicit null model instead of the non-spatial Island model

Analysis of Molecular Variance (AMOVA) for Autopolyploids

Autopolyploids present several challenges to researchers studying population genetics, since almost all population genetics theory, and the expectations derived from this theory, has been developed for haploids and diploids. Also many statistical tools for the analysis of genetic data, such as AMOVA and genome scans, are available only for haploids and diploids. In this paper, we show how the Analysis of Molecular Variance (AMOVA) framework can be extended to include autopolyploid data, which will allow calculating several genetic summary statistics for estimating the strength of genetic differentiation among autopolyploid populations (FST, φST, or RST). We show how this can be done by adjusting the equations for calculating the Sums of Squares, degrees of freedom and covariance components. The method can be applied to a dataset containing a single ploidy level, but also to datasets with a mixture of ploidy levels. In addition, we show how AMOVA can be used to estimate the summary statistic ρ, which was developed especially for polyploid data, but unfortunately has seen very little use. The ρ-statistic can be calculated in an AMOVA by first calculating a matrix of squared Euclidean distances for all pairs of individuals, based on the within-individual allele frequencies. The ρ-statistic is well suited for polyploid data since its expected value is independent of the ploidy level, the rate of double reduction, the frequency of polysomic inheritance, and the mating system. We tested the method using data simulated under a hierarchical island model: the results of the analyses of the simulated data closely matched the values derived from theoretical expectations. The problem of missing dosage information cannot be taken into account directly into the analysis, but can be remedied effectively by imputation of the allele frequencies. We hope that the development of AMOVA for autopolyploids will help to narrow the gap in availability of statistical tools for diploids and polyploids. We also hope that this research will increase the adoption of the ploidy-independent ρ-statistic, which has many qualities that makes it better suited for comparisons among species than the standard FST, both for diploids and for polyploids

Stift_et_al_used_R_code

This package contains the R-script used for simulating genetic data of two (or more) populations of a species with multiple ploidy levels. The script is extensively annotated using comments. The script will also perform several clustering analyses on the produced genetic data files. For this, the programs Structure, Admixture, and Instruct should be first downloaded from their respective websites, and placed in the R working directory. The package also contains the parameter files that are used for the Structure analysis; these should also be placed in the working directory

M arlin

Marlin is a software to create, run, analyse, and visualize spatially explicit population genetic simulations. It provides an intuitive user interface with which the geographical layout of a metapopulation can be drawn by hand or loaded from a map. Furthermore, the interface allows easy selection of the many different simulation settings. Marlin then uses the program QuantiNemo to run the simulation in the background. When simulations are finished, Marlin directly analyses and plots the results, thereby greatly simplifying the simulation workflow. This combination of simulation and analysis makes Marlin ideal for teaching and for scientists who are interested in doing simulations without having to learn command-line operations. Marlin is available for computers running Mac OS X and can be downloaded from: http://www.patrickmeirmans.com/software