DNA barcode analysis: a comparison of phylogenetic and statistical classification methods

<p>Abstract</p> <p>Background</p> <p>DNA barcoding aims to assign individuals to given species according to their sequence at a small locus, generally part of the CO1 mitochondrial gene. Amongst other issues, this raises the question of how to deal with within-species genetic variability and potential transpecific polymorphism. In this context, we examine several assignation methods belonging to two main categories: (i) phylogenetic methods (neighbour-joining and PhyML) that attempt to account for the genealogical framework of DNA evolution and (ii) supervised classification methods (k-nearest neighbour, CART, random forest and kernel methods). These methods range from basic to elaborate. We investigated the ability of each method to correctly classify query sequences drawn from samples of related species using both simulated and real data. Simulated data sets were generated using coalescent simulations in which we varied the genealogical history, mutation parameter, sample size and number of species.</p> <p>Results</p> <p>No method was found to be the best in all cases. The simplest method of all, "one nearest neighbour", was found to be the most reliable with respect to changes in the parameters of the data sets. The parameter most influencing the performance of the various methods was molecular diversity of the data. Addition of genetically independent loci - nuclear genes - improved the predictive performance of most methods.</p> <p>Conclusion</p> <p>The study implies that taxonomists can influence the quality of their analyses either by choosing a method best-adapted to the configuration of their sample, or, given a certain method, increasing the sample size or altering the amount of molecular diversity. This can be achieved either by sequencing more mtDNA or by sequencing additional nuclear genes. In the latter case, they may also have to modify their data analysis method.</p

Habitat continuity and geographic distance predict population genetic differentiation in giant kelp

Isolation by distance (IBD) models are widely used to predict levels of genetic connectivity as a function of Euclidean distance, and although recent studies have used GIS-landscape ecological approaches to improve the predictability of spatial genetic structure, few if any have addressed the effect of habitat continuity on gene flow. Landscape effects on genetic connectivity are even less understood in marine populations, where habitat mapping is particularly challenging. In this study, we model spatial genetic structure of a habitat-structuring species, the giant kelp Macrocystis pyrifera, using highly variable microsatellite markers. GIS mapping was used to characterize habitat continuity and distance between sampling sites along the mainland coast of the Santa Barbara Channel, and their roles as predictors of genetic differentiation were evaluated. Mean dispersal distance (σ) and effective population size (Ne) were estimated by comparing our IBD slope with those from simulations incorporating habitat continuity and spore dispersal characteristics of the study area. We found an allelic richness of 7–50 alleles/locus, which to our knowledge is the highest reported for macroalgae. The best regression model relating genetic distance to habitat variables included both geographic distance and habitat continuity, which were respectively, positively and negatively related to genetic distance. Our results provide strong support for a dependence of gene flow on both distance and habitat continuity and elucidate the combination of Ne and σ that explained genetic differentiation

Comparative population genetics of habitat-forming octocorals in two marine protected areas: eco-evolutionary and management implications

Current efforts to halt the decline of biodiversity are based primarily on protecting species richness. This narrow focus overlooks key components of biological diversity, particularly the infra-species genetic diversity, which is critical to consider with respect to genetic adaptation in changing environments. While comparative population genetics is recognized as a relevant approach to improve biodiversity management, it is still barely considered in practice. Here, a comparative population genetics study was conducted on two key habitat-forming octocoral species, Corallium rubrum and Paramuricea clavata, to contribute to management of two Marine Protected Areas (MPAs) in the northwestern Mediterranean. Contrasting patterns of genetic diversity and structure were observed in the two species, although they share many common biological features and live in similar habitats. Differential genetic drift effects induced by species-specific reproductive strategies and demographic histories most likely explain these differences. The translation of our results into management strategies supports the definition of four management units. We identified a coldspot of genetic diversity, with genetically isolated populations, and a hotspot of genetic diversity that has a central role in the system’s connectivity. Interestingly, they corresponded to the most recent and the oldest protected areas, respectively. This case study shows how moving from a “species pattern” perspective to an “eco-evolutionary processes” perspective can help assess and contribute to the effectiveness of biodiversity management plans.Open access funding provided by FCT|FCCN (b-on). JBL was funded by assistant researcher 2021.00855.CEECIND through national funds provided by FCT—Fundação para a Ciência e a Tecnologia. This research was supported by national funds through FCT within the scope of UIDB/04423/2020 and UIDP/04423/2020, by the MIMOSA project funded by the Foundation Prince Albert II Monaco. This work was supported by the European Union’s Horizon 2020 research and innovation program under grant agreement SEP-210597628 (FutureMARES). This study was also supported by the Spanish Government through the Smart project (CGL2012-32194) the HEATMED project (RTI2018-095346-B-I00, MCIU/AEI/FEDER, UE). RL was supported by the Agence Nationale de la Recherche (projects DISLAND ANR-20-CE32-00XXX, GENOSPACE ANR-16-CE02-0008 and INTROSPEC ANR-19-CE02-0011; and project PROLAG from the CeMEB LabEx;), and by recurrent funding from INRAe and CNRS. This research has been funded from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 869300 “FutureMARES”. SD is supported by the Fonds National de la Recherche Scientifique (FNRS, Belgium). JG and PL acknowledge the funding of the Spanish government through the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S). CL gratefully acknowledges the financial support by ICREA under the ICREA Academia program.Peer reviewe

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

Spatial heterogeneity in landscape structure influences dispersal and genetic structure: empirical evidence from a grasshopper in an agricultural landscape

Georeferenced abundance and microsatellite data and raw reads from the GS-FLX Roche sequencing have been posted on Dryad (doi:10.5061/dryad.88b12).Dispersal may be strongly influenced by landscape and habitat characteristics that could either enhance or restrict movements of organisms. Therefore, spatial heterogeneity in landscape structure could influence gene flow and the spatial structure of populations. In the past decades, agricultural intensification has led to the reduction in grassland surfaces, their fragmentation and intensification. As these changes are not homogeneously distributed in landscapes, they have resulted in spatial heterogeneity with generally less intensified hedged farmland areas remaining alongside streams and rivers. In this study, we assessed spatial pattern of abundance and population genetic structure of a flightless grasshopper species, Pezotettix giornae, based on the surveys of 363 grasslands in a 430-km(2) agricultural landscape of western France. Data were analysed using geostatistics and landscape genetics based on microsatellites markers and computer simulations. Results suggested that small-scale intense dispersal allows this species to survive in intensive agricultural landscapes. A complex spatial genetic structure related to landscape and habitat characteristics was also detected. Two P.giornae genetic clusters bisected by a linear hedged farmland were inferred from clustering analyses. This linear hedged farmland was characterized by high hedgerow and grassland density as well as higher grassland temporal stability that were suspected to slow down dispersal. Computer simulations demonstrated that a linear-shaped landscape feature limiting dispersal could be detected as a barrier to gene flow and generate the observed genetic pattern. This study illustrates the relevance of using computer simulations to test hypotheses in landscape genetics studies

A reassessment of explanations for discordant introgressions of mitochondrial and nuclear genomes

Hybridization is increasingly recognized as a significant evolutionary process, in particular because it can lead to introgression of genes from one species to another. A striking pattern of discordance in the amount of introgression between mitochondrial and nuclear markers exists such that substantial mitochondrial introgression is often found in combination with no or little nuclear introgression. Multiple mechanisms have been proposed to explain this discordance, including positive selection for introgressing mitochondrial variants, several types of sex-biases, drift, negative selection against introgression in the nuclear genome, and spatial expansion. Most of these hypotheses are verbal, and have not been quantitatively evaluated so far. We use individual-based, multilocus, computer simulations of secondary contact under a wide range of demographic and genetic scenarios to evaluate the ability of the different mechanisms to produce discordant introgression. Sex-biases and spatial expansions fail to produce substantial mito-nuclear discordance. Drift and nuclear selection can produce strong discordance, but only under a limited range of conditions. In contrast, selection on the mitochondrial genome produces strong discordance, particularly when dispersal rates are low. However, commonly used statistical tests have little power to detect this selection. Altogether, these results dismiss several popular hypotheses, and provide support for adaptive mitochondrial introgression

Measuring Genetic Differentiation from Pool-seq Data

International audienceThe advent of high throughput sequencing and genotyping technologies enables the comparison of patterns of polymorphisms at a very large number of markers. While the characterization of genetic structure from individual sequencing data remains expensive for many nonmodel species, it has been shown that sequencing pools of individual DNAs (Pool-seq) represents an attractive and cost-effective alternative. However, analyzing sequence read counts from a DNA pool instead of individual genotypes raises statistical challenges in deriving correct estimates of genetic differentiation. In this article, we provide a method-of-moments estimator of F-ST for Pool-seq data, based on an analysis-of-variance framework. We show, by means of simulations, that this new estimator is unbiased and outperforms previously proposed estimators. We evaluate the robustness of our estimator to model misspecification, such as sequencing errors and uneven contributions of individual DNAs to the pools. Finally, by reanalyzing published Pool-seq data of different ecotypes of the prickly sculpin Cottus asper, we show how the use of an unbiased F-ST estimator may question the interpretation of population structure inferred from previous analyses

New molecular data favour an anthropogenic introduction of the wood mouse (Apodemus sylvaticus) in North Africa

According to fossil data the wood mouse arrived in North Africa 7,500 ya, while it was present in Europe since early Pleistocene. Previous molecular studies suggested that its introduction in North Africa probably occurred via the Strait of Gibraltar more than 0.4 Mya ago. In this study, we widely sampled wood mice in order to get a better understanding of the geographic and demographic history of this species in North Africa, and possibly to help resolving the discrepancy between genetic and paleontological data. Specifically we wanted to answer the following questions: (1) when and how did the wood mouse arrive in North Africa? and (2) What is its demographic and geographic history in North Africa since its colonization? We collected in the field 438 new individuals and used both mtDNA and six microsatellite markers to answer these questions. Our results confirm that North African wood mice have a southwestern European origin and colonized the Maghreb through the Gibraltar strait probably during the Mesolithic or slightly after. They first colonized the Tingitane peninsula and then expanded throughout North Africa. Our genetic data suggest that the ancestral population size comprised numerous individuals reinforcing the idea that wood mice did not colonize Morocco accidentally through rafting of a few individuals, but via recurrent/multiple anthropogenic translocations. No spatial structuring of the genetic variability was recorded in North Africa, from Morocco to Tunisia