Biology subjects

Dupuis, J. R.

Publications and source records attributed to Dupuis, J. R..

7 recordsLinked to original sources

bioRxiv2026

Fully integrative species delimitation with machine learning and diverse data types in delimSOM 2.0

Species delimitation increasingly relies on multiple sources of evidence, but most frameworks are still limited to genetics and morphology or analyze data types separately and compare results qualitatively. We present delimSOM 2.0, an R package that leverages unsupervised machine learning through multilayer self-organizing maps. Any kind of input data, including genomic, phenotypic, ecological, and spatial, is analyzed jointly, retaining each data type as a separate layer and balancing their contributions through layer-specific weighting. Our package provides functions for preprocessing, replicate training, multivariate clustering, hyperparameter optimization, model-quality assessment, and variable- and layer-importance analyses. We evaluated our approach using two simulation sets and eight empirical studies spanning diverse taxa and data types. Overall, performance was strongest with larger sample sizes (>10 individuals per lineage) and modest numbers of lineages (K < 5), but unlike most species delimitation methods, it can reliably infer K = 1. Across two-population demographic simulations of genetic data, our method performed similarly to the well-established DAPC across gene-flow and sampling regimes, was more conservative than STRUCTURE and sNMF in inferring K = 2 and showed mixed support for K = 1 and K = 2 at intermediate differentiation levels and with gene flow. Crucially, our method is robust to missing data and variation in hyperparameters. Empirical examples showed that genetic data were typically most influential, but phenotypic, ecological, and spatial layers often contributed substantial complementary information. By combining diverse data types into a single unsupervised analysis, delimSOM 2.0 enables fully integrative species delimitation, reduces over-splitting, and advances efforts toward more objective and standardized taxonomy and speciation biology.

evolutionary biology↗

bioRxiv2026

NicheDiv: A DAPC framework to quantify niche divergence across highly multivariate environmental space

Quantifying niche divergence is crucial to understanding the ecological and evolutionary processes underlying range limits, coexistence, speciation, biogeography, and macroevolution. Yet available approaches rely on low-dimensional climate summaries, are vulnerable to multiple biases, or struggle with high-dimensional collinear data. We introduce the R package NicheDiv, which adapts discriminant analysis of principal components (DAPC) to quantify pairwise niche divergence across any number of abiotic and biotic environmental variables associated with occurrence records. Our method first addresses correlations among environmental variables through principal component analysis. It then identifies a single discriminant axis that maximizes separation between predefined groups (species/lineages/populations), summarizing multivariate niche structure into one dimension. Significance is assessed by a permutation test that reshuffles group identities to mimic a shared niche. To characterize ecological differentiation, NicheDiv calculates Schoeners D as an overlap index and extends the niche divergence plane to multivariate space, providing metrics such as niche dissimilarity and exclusivity. Extracted variable contributions from the discriminant axis identify environmental variables that contribute most to divergence. Using simulations and empirical data together with a large set of environmental layers, we demonstrate that NicheDiv is computationally scalable, detects subtle divergence in high-dimensional space despite multicollinearity, distinguishes different forms of niche divergence (weighted, nested, soft, hard), and identifies the variables that potentially drive divergence. Compared with alternative divergence tests (PCA-env, hypervolumes, MVNH, PERMANOVA, PCA-space, and logistic regression), NicheDiv generally retains more variation, scales more consistently with increasing divergence, and returns more interpretable effect sizes. NicheDiv automatically extracts such environmental data from preconfigured and user-supplied GIS layers and implements a preprocessing pipeline that reduces known biases: delimiting accessible background space, spatially thinning occurrences, balancing sample sizes, filtering low-information variables, and screening predictors for between-group environmental analogy. We test our framework with empirical analyses of Hemileuca buck moths and demonstrate that their niches are structured by a range of seasonal abiotic and biotic variables rather than annual climatic averages. Overall, NicheDiv offers a robust framework for characterizing niche divergence across multiple environmental axes in support of species delimitation, local adaptation, community ecology, biogeography, and macroevolution.

ecology↗

bioRxiv2024

Whole-genome evaluation of genetic rescue: the case of a curiously isolated and endangered butterfly

Genetic rescue, or the translocation of individuals among populations to augment gene flow, can help ameliorate inbreeding depression and loss of adaptive potential in small and isolated populations. Genetic rescue is currently under consideration for an endangered butterfly in Canada, the half-moon hairstreak (Satyrium semiluna). A small, unique population persists in Waterton Lakes National Park, Alberta, isolated from other populations by >350km. However, whether genetic rescue would actually be helpful has not been evaluated. Here, we generate the first chromosome-level genome assembly and whole-genome resequence data for the species. We find that the Alberta populations genetic diversity is extremely low and very divergent from the nearest populations in British Columbia and Montana. Runs of homozygosity suggest this is due to a long history of inbreeding, and coalescent analyses show that the population has been small and isolated, yet stable for up to 40k years. When a population maintains its viability despite inbreeding and low genetic diversity, it has likely undergone purging of deleterious recessive alleles and could be threatened by their reintroduction via genetic rescue. Ecological niche modelling indicates that the Alberta population also exhibits environmental associations that are atypical of the species. Together, these results suggest that population crosses are likely to result in outbreeding depression. We infer that, in this case, genetic rescue has a relatively unique potential to be harmful rather than helpful at present. However, due to reduced adaptive potential, the Alberta may still benefit from future genetic rescue as climate conditions change. Proactive experimental population crosses should be completed to assess reproductive compatibility and offspring fitness.

ecology↗

bioRxiv2023

Toward transparent taxonomy: an interactive web-tool for evaluating competing taxonomic arrangements

1. Informative and consistent taxonomy above the species level is essential to communication about evolution, biodiversity, and conservation, and yet the practice of taxonomy is considered opaque and subjective by non-taxonomist scientists and the public alike. While various proposals have tried to make the basis for ranking and inclusiveness of taxa more transparent and objective, widespread adoption of these ideas has lagged. 2. Here, we present TaxonomR, an interactive online decision-support tool to evaluate alternative taxonomic classifications. This tool implements an approach that quantifies the criteria commonly used in taxonomic treatments and allows the user to interactively manipulate weightings for different criteria to compare scores for taxonomic groupings under those weights. 3. We use the butterfly taxon Argynnis to demonstrate how different weightings applied to common taxonomic criteria result in fundamentally different genus-level classifications that are predominantly used in different continents and geographic regions. These differences are objectively compared and quantified using TaxonomR to evaluate the kinds of criteria that have been emphasized in earlier classifications, and the nature of the support for current alternative taxonomic arrangements. 4. The main role of TaxonomR is to make taxonomic decisions transparent via an explicit prioritization scheme. TaxonomR is not a prescriptive application. Rather, it aims to be a tool for facilitating our understanding of alternative taxonomic classifications that can, in turn, potentially support global harmony in biodiversity assessments through evidence-based discussion and community-wide resolution of historically entrenched taxonomic tensions.

evolutionary biology↗

bioRxiv2021

Recombination of standing variation in a multi-hybrid swarm drove adaptive radiation in a fungal pathogen and gave rise to two pandemic plant diseases

Adaptive radiations fuel speciation and are characterized by rapid genetic diversification and expansion into new ecological niches. Historically, these processes were believed to be driven by selection on novel mutations but genomic analyses now indicate that standing variation and gene flow often have prominent roles. How "old" variation is combined, however, and its resulting genetic architecture within newly-adapted populations is not well understood. We reconstructed a recent radiation in the fungus, Pyricularia oryzae, that spawned a population pathogenic to eleven grass genera, and caused two new plant diseases: wheat blast - already a serious threat to global agriculture - and gray leaf spot of ryegrasses. We show that the new population evolved in a multi-hybrid swarm using only the standing variation that was present in seven individuals from five distinct, host-specialized lineages. Sexual and parasexual recombination within the swarm reassorted key host-specificity factors and generated more diversity in possibly just a few weeks than existing lineages had accumulated over hundreds to thousands of years. We suggest that the process was initiated by sexual opportunity arising when a fertile fungal strain was imported into Brazil on Urochloa introduced as forage for beef production; and we further contend that the host range expansion was largely fortuitous, with host selection playing little, if any, role in driving the process. Finally, we believe that our findings point to an overlooked role for happenstance in creating situations that allow organisms to skirt rules that would normally hold evolution in check. Commercial Endorsement DisclaimerMention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture. Equal Opportunity/Non-Discrimination StatementUSDA is an equal opportunity provider and employer.

evolutionary biology↗

bioRxiv2018

Would an RRS by any other name sound as RAD?

Sampling markers throughout a genome with restriction enzymes emerged in the 2000s as reduced representation shotgun sequencing (RRS). Rapid advances in sequencing technology have since spurred modifications of RRS, giving rise to many derivatives with unique names, such as RADseq. But naming conventions have often been more creative than consistent, with unclear criteria for recognition as a unique method resulting in a proliferation of names characterized by ambiguity. We conducted a literature review to assess methodological and etymological relationships among 36 restriction enzyme-based methods, as well as rates of correct referencing of commonly-used methods. We identify several instances of methodological convergence or misattribution in the literature, and note that many published derivatives have modified only minor elements of parent protocols. We urge greater restraint in naming derivative methods, to strike a better balance between clarity, recognition of scientific innovation, and correct attribution.

genomics↗

bioRxiv2017

HiMAP: robust Phylogenomics from Highly Multiplexed Amplicon sequencing

High-throughput sequencing has fundamentally changed how molecular phylogenetic datasets are assembled, and phylogenomic datasets commonly contain 50-100-fold more loci than those generated using traditional Sanger-based approaches. Here, we demonstrate a new approach for building phylogenomic datasets using single tube, highly multiplexed amplicon sequencing, which we name HiMAP (Highly Multiplexed Amplicon-based Phylogenomics), and present bioinformatic pipelines for locus selection based on genomic and transcriptomic data resources and post-sequencing consensus calling and alignment. This method is inexpensive and amenable to sequencing a large number (hundreds) of taxa simultaneously, requires minimal hands-on time at the bench (<1/2 day), and data analysis can be accomplished without the need for read mapping or assembly. We demonstrate this approach by sequencing 878 amplicons in single reactions for 82 species of tephritid fruit flies across seven genera (384 individuals), including some of the most economically-important agricultural insect pests. The resulting dataset (>150,000 bp concatenated alignment) contained >40,000 phylogenetically informative characters, and although some discordance was observed between analyses, it provided unparalleled resolution of many phylogenetic relationships in this group. Most notably, we found high support for the generic status of Zeugodacus and the sister relationship between Dacus and Zeugodacus. We discuss HiMAP, with regard to its molecular and bioinformatic strengths, and the insight the resulting dataset provides into relationships of this diverse insect group.

genomics↗