The Worldwide Invasion of Drosophila suzukii Is Accompanied by a Large Increase of Transposable Element Load and a Small Number of Putatively Adaptive Insertions.

Transposable elements (TEs) are ubiquitous and mobile repeated sequences. They are major determinants of host fitness. Here, we characterized the TE content of the spotted wing fly Drosophila suzukii. Using a recently improved genome assembly, we reconstructed TE sequences de novo and found that TEs occupy 47% of the genome and are mostly located in gene-poor regions. The majority of TE insertions segregate at low frequencies, indicating a recent and probably ongoing TE activity. To explore TE dynamics in the context of biological invasions, we studied the variation of TE abundance in genomic data from 16 invasive and six native populations of D. suzukii. We found a large increase of the TE load in invasive populations correlated with a reduced Watterson estimate of genetic diversity θw^ a proxy of effective population size. We did not find any correlation between TE contents and bioclimatic variables, indicating a minor effect of environmentally induced TE activity. A genome-wide association study revealed that ca. 2,000 genomic regions are associated with TE abundance. We did not find, however, any evidence in such regions of an enrichment for genes known to interact with TE activity (e.g., transcription factor encoding genes or genes of the piRNA pathway). Finally, the study of TE insertion frequencies revealed 15 putatively adaptive TE insertions, six of them being likely associated with the recent invasion history of the species.

A Whole-Genome Scan for Association with Invasion Success in the Fruit Fly Drosophila suzukii Using Contrasts of Allele Frequencies Corrected for Population Structure.

Evidence is accumulating that evolutionary changes are not only common during biological invasions but may also contribute directly to invasion success. The genomic basis of such changes is still largely unexplored. Yet, understanding the genomic response to invasion may help to predict the conditions under which invasiveness can be enhanced or suppressed. Here, we characterized the genome response of the spotted wing drosophila Drosophila suzukii during the worldwide invasion of this pest insect species, by conducting a genome-wide association study to identify genes involved in adaptive processes during invasion. Genomic data from 22 population samples were analyzed to detect genetic variants associated with the status (invasive versus native) of the sampled populations based on a newly developed statistic, we called C2, that contrasts allele frequencies corrected for population structure. We evaluated this new statistical framework using simulated data sets and implemented it in an upgraded version of the program BayPass. We identified a relatively small set of single-nucleotide polymorphisms that show a highly significant association with the invasive status of D. suzukii populations. In particular, two genes, RhoGEF64C and cpo, contained single-nucleotide polymorphisms significantly associated with the invasive status in the two separate main invasion routes of D. suzukii. Our methodological approaches can be applied to any other invasive species, and more generally to any evolutionary model for species characterized by nonequilibrium demographic conditions for which binary covariables of interest can be defined at the population level.

Adaptation and correlated fitness responses over two time scales in Drosophila suzukii populations evolving in different environments.

The process of local adaptation involves differential changes in fitness over time across different environments. Although experimental evolution studies have extensively tested for patterns of local adaptation at a single time point, there is relatively little research that examines fitness more than once during the time course of adaptation. We allowed replicate populations of the fruit pest Drosophila suzukii to evolve in one of eight different fruit media. After five generations, populations with the highest initial levels of maladaptation had mostly gone extinct, whereas experimental populations evolving on cherry, strawberry and cranberry media had survived. We measured the fitness of each surviving population in each of the three fruit media after five and after 26 generations of evolution. After five generations, adaptation to each medium was associated with increased fitness in the two other media. This was also true after 26 generations, except when populations that evolved on cranberry medium developed on cherry medium. These results suggest that, in the theoretical framework of a fitness landscape, the fitness optima of cherry and cranberry media are the furthest apart. Our results show that studying how fitness changes across several environments and across multiple generations provides insights into the dynamics of local adaptation that would not be evident if fitness were analysed at a single point in time. By allowing a qualitative mapping of an experimental fitness landscape, our approach will improve our understanding of the ecological factors that drive the evolution of local adaptation in D. suzukii.

ABC random forests for Bayesian parameter inference.

MOTIVATION: Approximate Bayesian computation (ABC) has grown into a standard methodology that manages Bayesian inference for models associated with intractable likelihood functions. Most ABC implementations require the preliminary selection of a vector of informative statistics summarizing raw data. Furthermore, in almost all existing implementations, the tolerance level that separates acceptance from rejection of simulated parameter values needs to be calibrated. RESULTS: We propose to conduct likelihood-free Bayesian inferences about parameters with no prior selection of the relevant components of the summary statistics and bypassing the derivation of the associated tolerance level. The approach relies on the random forest (RF) methodology of Breiman (2001) applied in a (non-parametric) regression setting. We advocate the derivation of a new RF for each component of the parameter vector of interest. When compared with earlier ABC solutions, this method offers significant gains in terms of robustness to the choice of the summary statistics, does not depend on any type of tolerance level, and is a good trade-off in term of quality of point estimator precision and credible interval estimations for a given computing time. We illustrate the performance of our methodological proposal and compare it with earlier ABC methods on a Normal toy example and a population genetics example dealing with human population evolution. AVAILABILITY AND IMPLEMENTATION: All methods designed here have been incorporated in the R package abcrf (version 1.7.1) available on CRAN. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A young age of subspecific divergence in the desert locust inferred by ABC random forest.

Dating population divergence within species from molecular data and relating such dating to climatic and biogeographic changes is not trivial. Yet it can help formulating evolutionary hypotheses regarding local adaptation and future responses to changing environments. Key issues include statistical selection of a demographic and historical scenario among a set of possible scenarios, and estimation of the parameter(s) of interest under the chosen scenario. Such inferences greatly benefit from (a) independent information on evolutionary rate and pattern at genetic markers; and (b) new statistical approaches, such as approximate Bayesian computation-random forest (ABC-RF), which provides reliable inference at a low computational cost and the possibility to measure prediction quality at the exact position of the observed data set. Here, we show full potential of the ABC-RF approach including prior knowledge on microsatellite genetic markers to decipher the evolutionary history of the African arid-adapted pest locust, Schistocerca gregaria, with support for a southern colonization of Africa, from a low number of founders of northern origin, dating back 2.6 Ky (90% CI: 0.9-6.6 Ky). We verify that this divergence time estimate accurately reflected true divergence time values by computing accuracy at a local posterior scale from simulated pseudo-observed data sets. The inferred divergence history is better explained by the peculiar biology of S. gregaria, which involves a density-dependent swarming phase with some exceptional spectacular migrations, rather than a continuous colonization resulting from the continental expansion of open vegetation habitats during more ancient Quaternary glacial climatic episodes.

Deciphering the Routes of invasion of Drosophila suzukii by Means of ABC Random Forest.

Deciphering invasion routes from molecular data is crucial to understanding biological invasions, including identifying bottlenecks in population size and admixture among distinct populations. Here, we unravel the invasion routes of the invasive pest Drosophila suzukii using a multi-locus microsatellite dataset (25 loci on 23 worldwide sampling locations). To do this, we use approximate Bayesian computation (ABC), which has improved the reconstruction of invasion routes, but can be computationally expensive. We use our study to illustrate the use of a new, more efficient, ABC method, ABC random forest (ABC-RF) and compare it to a standard ABC method (ABC-LDA). We find that Japan emerges as the most probable source of the earliest recorded invasion into Hawaii. Southeast China and Hawaii together are the most probable sources of populations in western North America, which then in turn served as sources for those in eastern North America. European populations are genetically more homogeneous than North American populations, and their most probable source is northeast China, with evidence of limited gene flow from the eastern US as well. All introduced populations passed through bottlenecks, and analyses reveal five distinct admixture events. These findings can inform hypotheses concerning how this species evolved between different and independent source and invasive populations. Methodological comparisons indicate that ABC-RF and ABC-LDA show concordant results if ABC-LDA is based on a large number of simulated datasets but that ABC-RF out-performs ABC-LDA when using a comparable and more manageable number of simulated datasets, especially when analyzing complex introduction scenarios.

Reliable ABC model choice via random forests.

MOTIVATION: Approximate Bayesian computation (ABC) methods provide an elaborate approach to Bayesian inference on complex models, including model choice. Both theoretical arguments and simulation experiments indicate, however, that model posterior probabilities may be poorly evaluated by standard ABC techniques. RESULTS: We propose a novel approach based on a machine learning tool named random forests (RF) to conduct selection among the highly complex models covered by ABC algorithms. We thus modify the way Bayesian model selection is both understood and operated, in that we rephrase the inferential goal as a classification problem, first predicting the model that best fits the data with RF and postponing the approximation of the posterior probability of the selected model for a second stage also relying on RF. Compared with earlier implementations of ABC model choice, the ABC RF approach offers several potential improvements: (i) it often has a larger discriminative power among the competing models, (ii) it is more robust against the number and choice of statistics summarizing the data, (iii) the computing effort is drastically reduced (with a gain in computation efficiency of at least 50) and (iv) it includes an approximation of the posterior probability of the selected model. The call to RF will undoubtedly extend the range of size of datasets and complexity of models that ABC can handle. We illustrate the power of this novel methodology by analyzing controlled experiments as well as genuine population genetics datasets. AVAILABILITY AND IMPLEMENTATION: The proposed methodology is implemented in the R package abcrf available on the CRAN. CONTACT: jean-michel.marin@umontpellier.fr SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

DIYABC v2.0: a software to make approximate Bayesian computation inferences about population history using single nucleotide polymorphism, DNA sequence and microsatellite data.

MOTIVATION: DIYABC is a software package for a comprehensive analysis of population history using approximate Bayesian computation on DNA polymorphism data. Version 2.0 implements a number of new features and analytical methods. It allows (i) the analysis of single nucleotide polymorphism data at large number of loci, apart from microsatellite and DNA sequence data, (ii) efficient Bayesian model choice using linear discriminant analysis on summary statistics and (iii) the serial launching of multiple post-processing analyses. DIYABC v2.0 also includes a user-friendly graphical interface with various new options. It can be run on three operating systems: GNU/Linux, Microsoft Windows and Apple Os X. AVAILABILITY: Freely available with a detailed notice document and example projects to academic users at http://www1.montpellier.inra.fr/CBGP/diyabc CONTACT: estoup@supagro.inra.fr Supplementary information: Supplementary data are available at Bioinformatics online.

Cannibalism in invasive, native and biocontrol populations of the harlequin ladybird.

BACKGROUND: Cannibalism is widespread in both vertebrates and invertebrates but its extent is variable between and within species. Cannibalism depends on population density and nutritional conditions, and could be beneficial during colonisation of new environments. Empirical studies are needed to determine whether this trait might facilitate invasion of a new area in natural systems. We investigated whether the propensity for cannibalism in H. axyridis differs both between native and invasive populations and between invasive populations from the core and from the front of the invasive area in Western Europe. We also compared the propensity for cannibalism of these natural populations with that of laboratory-reared biocontrol populations. We measured the cannibalism rates of eggs by first instar larvae and adult females at two different individual densities of ladybirds from three types of population (invasive, native and biocontrol), in laboratory-controlled conditions. RESULTS: Cannibalism was significantly greater in larvae from invasive populations compared to native or biocontrol populations, but there was no difference in cannibalism rates between populations from the core or front of the invaded range. Cannibalism was significantly lower in larvae from biocontrol populations compared to wild (invasive and native) populations. No differences in cannibalism rates of adult females were found between any populations. While high population density significantly increased cannibalism in both larvae and adults, the norm of reaction of cannibalism to individual density did not change significantly during the invasion and/or laboratory rearing processes. CONCLUSION: This study is the first to provide evidence for a higher propensity for cannibalism in invasive populations compared to native ones. Our experiments also shed light on the difference in cannibalism evolution with respect to life stages. However, we are still at an early stage in understanding the underlying mechanisms and several different research perspectives are needed to determine whether the higher propensity for cannibalism is a general feature of the invasion process.

Complementarity of statistical treatments to reconstruct worldwide routes of invasion: the case of the Asian ladybird Harmonia axyridis.

Inferences about introduction histories of invasive species remain challenging because of the stochastic demographic processes involved. Approximate Bayesian computation (ABC) can help to overcome these problems, but such method requires a prior understanding of population structure over the study area, necessitating the use of alternative methods and an intense sampling design. In this study, we made inferences about the worldwide invasion history of the ladybird Harmonia axyridis by various population genetics statistical methods, using a large set of sampling sites distributed over most of the species' native and invaded areas. We evaluated the complementarity of the statistical methods and the consequences of using different sets of site samples for ABC inferences. We found that the H. axyridis invasion has involved two bridgehead invasive populations in North America, which have served as the source populations for at least six independent introductions into other continents. We also identified several situations of genetic admixture between differentiated sources. Our results highlight the importance of coupling ABC methods with more traditional statistical approaches. We found that the choice of site samples could affect the conclusions of ABC analyses comparing possible scenarios. Approaches involving independent ABC analyses on several sample sets constitute a sensible solution, complementary to standard quality controls based on the analysis of pseudo-observed data sets, to minimize erroneous conclusions. This study provides biologists without expertise in this area with detailed methodological and conceptual guidelines for making inferences about invasion routes when dealing with a large number of sampling sites and complex population genetic structures.

Androgenesis is a maternal trait in the invasive ant Wasmannia auropunctata.

Androgenesis is the production of an offspring containing exclusively the nuclear genome of the fathering male via the maternal eggs. This unusual mating system is generally considered a male trait, giving to androgenetic males a substantial fitness advantage over their sexually reproducing relatives. We here provide the first empirical study of the evolutionary outcomes of androgenesis in a haplo-diploid organism: the invasive ant Wasmannia auropunctata. Some of the populations of this species have a classical haplo-diploid sexual mating system. In other populations, females and males are produced through parthenogenesis and androgenesis, respectively, whereas workers are produced sexually. We conducted laboratory reciprocal-cross experiments with reproductive individuals from both types of populations and analysed their progenies with genetic markers, to determine the respective contribution of males and females to the production of androgenetic males. We found that androgenesis was a parthenogenetic female trait. A population genetic study conducted in natura confirmed the parthenogenetic female origin of androgenesis, with the identification of introgression events of sexual male genotypes into androgenetic/parthenogenetic lineages. We argue that by producing males via androgenesis, parthenogenetic queen lineages may increase and/or maintain their adaptive potential, while maintaining the integrity of their own genome, by occasionally acquiring new male genetic material and avoiding inbreeding depression within the sexually produced worker cast.

The effect of RAD allele dropout on the estimation of genetic variation within and between populations.

Inexpensive short-read sequencing technologies applied to reduced representation genomes is revolutionizing genetic research, especially population genetics analysis, by allowing the genotyping of massive numbers of single-nucleotide polymorphisms (SNP) for large numbers of individuals and populations. Restriction site-associated DNA (RAD) sequencing is a recent technique based on the characterization of genomic regions flanking restriction sites. One of its potential drawbacks is the presence of polymorphism within the restriction site, which makes it impossible to observe the associated SNP allele (i.e. allele dropout, ADO). To investigate the effect of ADO on genetic variation estimated from RAD markers, we first mathematically derived measures of the effect of ADO on allele frequencies as a function of different parameters within a single population. We then used RAD data sets simulated using a coalescence model to investigate the magnitude of biases induced by ADO on the estimation of expected heterozygosity and F(ST) under a simple demographic model of divergence between two populations. We found that ADO tends to overestimate genetic variation both within and between populations. Assuming a mutation rate per nucleotide between 10(-9) and 10(-8), this bias remained low for most studied combinations of divergence time and effective population size, except for large effective population sizes. Averaging F(ST) values over multiple SNPs, for example, by sliding window analysis, did not correct ADO biases. We briefly discuss possible solutions to filter the most problematic cases of ADO using read coverage to detect markers with a large excess of null alleles.

Invasion genetics of the introduced black rat (Rattus rattus) in Senegal, West Africa.

An understanding of the evolutionary history and dynamics of invasive species is required for the construction of predictive models of future spread and the design of biological management measures. The black rat (Rattus rattus) is a major vertebrate invader with a worldwide distribution. Despite the severe ecological, economic and health impacts of this species, its evolutionary history has been little studied. We carried out extensive specimen sampling in Senegal, West Africa, and used microsatellite markers to describe the pattern and processes of invasion in this large continental area. The genetic data obtained were combined with historical knowledge concerning the presence of this species in Senegal. Data were analysed by a combination of Bayesian clustering and approximate Bayesian computation methods. The invasion pathways closely paralleled the history of human trade routes in Senegal. In several places, we detected the occurrence of multiple introductions from genetically different sources. Long-distance migration between towns and villages was also observed. Our findings suggest that genetic bottlenecks and admixture have played a major role in shaping the genetics of invasive black rats. These two processes may generate genetic novelty and favour rapid evolution along the invasion pathways.

Estimation of population allele frequencies from next-generation sequencing data: pool-versus individual-based genotyping.

Molecular markers produced by next-generation sequencing (NGS) technologies are revolutionizing genetic research. However, the costs of analysing large numbers of individual genomes remain prohibitive for most population genetics studies. Here, we present results based on mathematical derivations showing that, under many realistic experimental designs, NGS of DNA pools from diploid individuals allows to estimate the allele frequencies at single nucleotide polymorphisms (SNPs) with at least the same accuracy as individual-based analyses, for considerably lower library construction and sequencing efforts. These findings remain true when taking into account the possibility of substantially unequal contributions of each individual to the final pool of sequence reads. We propose the intuitive notion of effective pool size to account for unequal pooling and derive a Bayesian hierarchical model to estimate this parameter directly from the data. We provide a user-friendly application assessing the accuracy of allele frequency estimation from both pool- and individual-based NGS population data under various sampling, sequencing depth and experimental error designs. We illustrate our findings with theoretical examples and real data sets corresponding to SNP loci obtained using restriction site-associated DNA (RAD) sequencing in pool- and individual-based experiments carried out on the same population of the pine processionary moth (Thaumetopoea pityocampa). NGS of DNA pools might not be optimal for all types of studies but provides a cost-effective approach for estimating allele frequencies for very large numbers of SNPs. It thus allows comparison of genome-wide patterns of genetic variation for large numbers of individuals in multiple populations.

Where do adaptive shifts occur during invasion? A multidisciplinary approach to unravelling cold adaptation in a tropical ant species invading the Mediterranean area.

Evolution may improve the invasiveness of populations, but it often remains unclear whether key adaptation events occur after introduction into the recipient habitat (i.e. post-introduction adaptation scenario), or before introduction within the native range (i.e. prior-adaptation scenario) or at a primary site of invasion (i.e. bridgehead scenario). We used a multidisciplinary approach to determine which of these three scenarios underlies the invasion of the tropical ant Wasmannia auropunctata in a Mediterranean region (i.e. Israel). Species distribution models (SDM), phylogeographical analyses at a broad geographical scale and laboratory experiments on appropriate native and invasive populations indicated that Israeli populations followed an invasion scenario in which adaptation to cold occurred at the southern limit of the native range before dispersal to Israel. We discuss the usefulness of combining SDM, genetic and experimental approaches for unambiguous determination of eco-evolutionary invasion scenarios.

Meiotic recombination dramatically decreased in thelytokous queens of the little fire ant and their sexually produced workers.

The little fire ant, Wasmannia auropunctata, displays a peculiar breeding system polymorphism. Classical haplo-diploid sexual reproduction between reproductive individuals occurs in some populations, whereas, in others, queens and males reproduce clonally. Workers are produced sexually and are sterile in both clonal and sexual populations. The evolutionary fate of the clonal lineages depends strongly on the underlying mechanisms allowing reproductive individuals to transmit their genomes to subsequent generations. We used several queen-offspring data sets to estimate the rate of transition from heterozygosity to homozygosity associated with recombination events at 33 microsatellite loci in thelytokous parthenogenetic queen lineages and compared these rates with theoretical expectations under various parthenogenesis mechanisms. We then used sexually produced worker families to define linkage groups for these 33 loci and to compare meiotic recombination rates in sexual and parthenogenetic queens. Our results demonstrate that queens from clonal populations reproduce by automictic parthenogenesis with central fusion. These same parthenogenetic queens produce normally segregating meiotic oocytes for workers, which display much lower rates of recombination (by a factor of 45) than workers produced by sexual queens. These low recombination rates also concern the parthenogenetic production of queen offspring, as indicated by the very low rates of transition from heterozygosity to homozygosity observed (from 0% to 2.8%). We suggest that the combination of automixis with central fusion and a major decrease in recombination rates allows clonal queens to benefit from thelytoky while avoiding the potential inbreeding depression resulting from the loss of heterozygosity during automixis. In sterile workers, the strong decrease of recombination rates may also facilitate the conservation over time of some coadapted allelic interactions within chromosomes that might confer an adaptive advantage in habitats disturbed by human activity, where clonal populations of W. auropunctata are mostly found.

f-Statistics estimation and admixture graph construction with Pool-Seq or allele count data using the R package poolfstat.

By capturing various patterns of the structuring of genetic variation across populations, f -statistics have proved highly effective for the inference of demographic history. Such statistics are defined as covariances of SNP allele frequency differences among sets of populations without requiring haplotype information and are hence particularly relevant for the analysis of pooled sequencing (Pool-Seq) data. We here propose a reinterpretation of the F (and D ) parameters in terms of probability of gene identity and derive from this unified definition unbiased estimators for both Pool-Seq data and standard allele count data obtained from individual genotypes. We implemented these estimators in a new version of the R package poolfstat, which now includes a wide range of inference methods: (i) three-population test of admixture; (ii) four-population test of treeness; (iii) F 4 -ratio estimation of admixture rates; and (iv) fitting, visualization and (semi-automatic) construction of admixture graphs. A comprehensive evaluation of the methods implemented in poolfstat on both simulated Pool-Seq (with various sequencing coverages and error rates) and allele count data confirmed the accuracy of these approaches, even for the most cost-effective Pool-Seq design involving relatively low sequencing coverages. We further analysed a real Pool-Seq data made of 14 populations of the invasive species Drosophila suzukii, which allowed refining both the demographic history of native populations and the invasion routes followed by this emblematic pest. Our new package poolfstat provides the community with a user-friendly and efficient all-in-one tool to unravel complex population genetic histories from large-size Pool-Seq or allele count SNP data.

Rapid and transient evolution of local adaptation to seasonal host fruits in an invasive pest fly.

Both local adaptation and adaptive phenotypic plasticity can influence the match between phenotypic traits and local environmental conditions. Theory predicts that environments stable for multiple generations promote local adaptation, whereas highly heterogeneous environments favor adaptive phenotypic plasticity. However, when environments have periods of stability mixed with heterogeneity, the relative importance of local adaptation and adaptive phenotypic plasticity is unclear. Here, we used Drosophila suzukii as a model system to evaluate the relative influence of genetic and plastic effects on the match of populations to environments with periods of stability from three to four generations. This invasive pest insect can develop within different fruits, and persists throughout the year in a given location on a succession of distinct host fruits, each one being available for only a few generations. Using reciprocal common environment experiments of natural D. suzukii populations collected from cherry, strawberry, and blackberry, we found that both oviposition preference and offspring performance were higher on medium made with the fruit from which the population originated than on media made with alternative fruits. This pattern, which remained after two generations in the laboratory, was analyzed using a statistical method we developed to quantify the contributions of local adaptation and adaptive plasticity in determining fitness. Altogether, we found that genetic effects (local adaptation) dominate over plastic effects (adaptive phenotypic plasticity). Our study demonstrates that spatially and temporally variable selection does not prevent the rapid evolution of local adaptation in natural populations. The speed and strength of adaptation may be facilitated by several mechanisms including a large effective population size and strong selective pressures imposed by host plants.

Clonal reproduction by males and females in the little fire ant.

Sexual reproduction can lead to major conflicts between sexes and within genomes. Here we report an extreme case of such conflicts in the little fire ant Wasmannia auropunctata. We found that sterile workers are produced by normal sexual reproduction, whereas daughter queens are invariably clonally produced. Because males usually develop from unfertilized maternal eggs in ants and other haplodiploid species, they normally achieve direct fitness only through diploid female offspring. Hence, although the clonal production of queens increases the queen's relatedness to reproductive daughters, it potentially reduces male reproductive success to zero. In an apparent response to this conflict between sexes, genetic analyses reveal that males reproduce clonally, most likely by eliminating the maternal half of the genome in diploid eggs. As a result, all sons have nuclear genomes identical to those of their father. The obligate clonal production of males and queens from individuals of the same sex effectively results in a complete separation of the male and female gene pools. These findings show that the haplodiploid sex-determination system provides grounds for the evolution of extraordinary genetic systems and new types of sexual conflict.

Extending approximate Bayesian computation with supervised machine learning to infer demographic history from genetic polymorphisms using DIYABC Random Forest.

Simulation-based methods such as approximate Bayesian computation (ABC) are well-adapted to the analysis of complex scenarios of populations and species genetic history. In this context, supervised machine learning (SML) methods provide attractive statistical solutions to conduct efficient inferences about scenario choice and parameter estimation. The Random Forest methodology (RF) is a powerful ensemble of SML algorithms used for classification or regression problems. Random Forest allows conducting inferences at a low computational cost, without preliminary selection of the relevant components of the ABC summary statistics, and bypassing the derivation of ABC tolerance levels. We have implemented a set of RF algorithms to process inferences using simulated data sets generated from an extended version of the population genetic simulator implemented in DIYABC v2.1.0. The resulting computer package, named DIYABC Random Forest v1.0, integrates two functionalities into a user-friendly interface: the simulation under custom evolutionary scenarios of different types of molecular data (microsatellites, DNA sequences or SNPs) and RF treatments including statistical tools to evaluate the power and accuracy of inferences. We illustrate the functionalities of DIYABC Random Forest v1.0 for both scenario choice and parameter estimation through the analysis of pseudo-observed and real data sets corresponding to pool-sequencing and individual-sequencing SNP data sets. Because of the properties inherent to the implemented RF methods and the large feature vector (including various summary statistics and their linear combinations) available for SNP data, DIYABC Random Forest v1.0 can efficiently contribute to the analysis of large SNP data sets to make inferences about complex population genetic histories.