Biology subjects

Mussmann, S. M.

Publications and source records attributed to Mussmann, S. M..

5 recordsLinked to original sources

bioRxiv2023

autoStreamTree: Genomic variant data fitted to geospatial networks

SummaryLandscape genetics is a statistical framework that parses genetic variation within the context of spatial covariates, but current analytical methods typically fail to accommodate the unique topologies and autocorrelations inherent to network-configured habitats (e.g., streams or rivers). autoStreamTree analyzes and visualizes genome-wide variation across dendritic networks (i.e., riverscapes). Availability and ImplementationautoStreamTree is an open source workflow (https://github.com/tkchafin/autostreamtree) that automatically extracts a minimal graph representation of a geospatial network from a provided shapefile, then fits the components of genetic variation using a least-squares algorithm. To facilitate downstream population genomic analyses, genomic variation can be represented per-locus, per-SNP, or via microhaplotypes (i.e., phased data). We demonstrate the workflow by quantifying genetic variation in Speckled Dace (Rhinichthys osculus) versus environmental covariates, with putative adaptive variants subsequently identified. Contacttyler.chafin@bioss.ac.uk

bioinformatics↗

bioRxiv2021

Quantifying diversity, connectivity, and environmental resistance in dendritic ecological networks

O_LIA central theme in landscape ecology is the translation of individual movements within a population by deconstructing/interpreting the components of its topographical environment. Most such endeavors rely heavily on the concept of landscape resistance - a composite of an arbitrary number of features/covariates that, when identified/compiled, yield a surface inversely related to net movement. However, the statistical methodologies underlying this compilation have limited applicability when applied to dendritic ecological networks (DENs), including riverscapes. C_LIO_LIHerein we provide an analytical framework (ResistNet) that more appropriately annotates DEN segments by first aligning individual genetic distances with environmental covariates within a graph structure, then employing a genetic algorithm to optimise a composite model. C_LIO_LIWe evaluated the efficacy of our method by first testing it in silico across an array of sampling designs, spatial trajectories, and levels of complexity, then applying it in an empirical case study involving 13,218 ddRAD loci from N=762 Speckled Dace (Leuciscidae: Rhinichthys osculus), sampled across N=78 Colorado River localities. By doing so, we underscored the utility of ResistNet within a large-scale conservation study, as well as identified prerequisites for its appropriate application. C_LIO_LIOur contemporary framework not only allows an interpretation of meta-population/meta-community structure across DENs, but also highlights several innovative applications. These are: (a) Expanding an ongoing study design, and thus its hypotheses, into yet unsampled temporal and/or spatial arenas, and; (b) Promoting multi-species management through comparative analyses that extend across species and/or drainages. C_LI

ecology↗

bioRxiv2020

ADMIXPIPE: Population analyses in ADMIXTURE for non-model organisms

Background: Research on the molecular ecology of non-model organisms, while previously constrained, has now been greatly facilitated by the advent of reduced-representation sequencing protocols. However, tools that allow these large datasets to be efficiently parsed are often lacking, or if indeed available, then limited by the necessity of a comparable reference genome as an adjunct. This, of course, can be difficult when working with non-model organisms. Fortunately, pipelines are currently available that avoid this prerequisite, thus allowing data to be a priori parsed. An oft-used molecular ecology program (i.e., STRUCTURE), for example, is facilitated by such pipelines, yet they are surprisingly absent for a second program that is similarly popular and computationally more efficient (i.e., ADMIXTURE). The two programs differ in that ADMIXTURE employs a maximum-likelihood framework whereas STRUCTURE uses a Bayesian approach, yet both produce similar results. Given these issues, there is an overriding (and recognized) need among researchers in molecular ecology for bioinformatic software that will not only condense output from replicated ADMIXTURE runs, but also infer from these data the optimal number of population clusters (K). Results: Here we provide such a program (i.e., ADMIXPIPE) that (a) filters SNPs to allow the delineation of population structure in ADMIXTURE, then (b) parses the output for summarization and graphical representation via CLUMPAK. Our benchmarks effectively demonstrate how efficient the pipeline is for processing large, non-model datasets generated via double digest restriction-site associated DNA sequencing (ddRAD). Outputs not only parallel those from STRUCTURE, but also visualize the variation among individual ADMIXTURE runs, so as to facilitate selection of the most appropriate K-value. Conclusions: ADMIXPIPE successfully integrates ADMIXTURE analysis with popular variant call format (VCF) filtering software to yield file types readily analyzed by CLUMPAK. Large population genomic datasets derived from non-model organisms are efficiently analyzed via the parallel-processing capabilities of ADMIXTURE. ADMIXPIPE is distributed under the GNU Public License and freely available for Mac OSX and Linux platforms at: https://github.com/stevemussmann/admixturePipeline.Competing Interest StatementThe authors have declared no competing interest.View Full Text

bioinformatics↗

bioRxiv2020

Defining Relictual Biodiversity: Conservation Units in Speckled Dace (Cyprinidae: Rhinichthys osculus) of the Greater Death Valley Ecosystem

The tips in the tree of life serve as foci for conservation and management, yet clear delimitations are masked by inherent variance at the species-population interface. Analyses using thousands of nuclear loci can potentially sort inconsistencies, yet standard categories applied to this parsing are themselves potentially conflicting and/or subjective [e.g., DPS (distinct population segments); DUs (Diagnosable Units-Canada); MUs (management units); SSP (subspecies); Evolutionarily Significant Units (ESUs)]. One potential solution for consistent categorization is to create a comparative framework by accumulating statistical results from independent studies and evaluating congruence among data sets. Our study illustrates this approach in speckled dace (Cyprinidae: Rhinichthys osculus) endemic to two basins (Owens and Amargosa) in the Death Valley ecosystem (DVE). These fish persist in the Mojave Desert as isolated Pleistocene-relicts and are of conservation concern, but lack formal taxonomic descriptions/designations. Double-digest RAD (ddRAD) methods identified 14,355 SNP loci across 10 populations (N=140). Species delimitation analyses [multispecies coalescent (MSC) and unsupervised machine learning (UML)] delineated four putative ESUs. FST outlier loci (N=106) were juxtaposed to uncover the potential for localized adaptations. We detected one hybrid population that resulted from upstream reconnection of habitat following contemporary pluvial periods, whereas remaining populations represent relics of ancient tectonism within geographically-isolated springs and groundwater-fed streams. Our study offers three salient conclusions: A blueprint for a multi-faceted delimitation of conservation units; a proposed mechanism by which criteria for intraspecific biodiversity can be potentially standardized; and a strong argument for the proactive management of critically-endangered DVE fishes.

genetics↗

bioRxiv2019

Taxonomic Uncertainty and Phylogenomics: Rescuing a Contentious Species Complex from the Anomaly Zone

Species is an indisputable unit for biodiversity conservation, yet their delimitation is fraught with both conceptual and methodological difficulties. A classic example is the taxonomic controversy surrounding the Gila robusta complex in the lower Colorado River of southwestern North America. Nominal species designations were originally defined according to weakly diagnostic morphological differences that conflicted with traditional genetic analyses. Consequently, the complex was re-defined as a single polytypic unit, with the proposed threatened status of two being withdrawn at the federal level. Here, we utilized dense spatial and genomic sampling (N=387 and >22k loci) to re-evaluate the status of the complex, based on SNP-based coalescent and polymorphism-aware phylogenetic models. In doing so, all three species were supported as evolutionarily independent lineages, despite widespread phylogenetic discordance. To understand this discrepancy with past studies, we categorized evolutionary mechanisms driving discordance. We tested (and subsequently rejected) prior hypotheses suggesting that phylogenetic discord in the complex was hybridization-driven. Instead, we found the G. robusta complex to have diverged within the anomaly zone of tree space and, as such, have accumulated inconsistent patterns of diversity which have confounded prior studies. After extending these analyses with phylogeographic modeling, we propose that this is reflective of a rapid radiation promoted by Plio-Pleistocene tectonism. Our results not only support resurrection of the three species as distinct entities, but also offer an empirical example of how phylogenetic discordance can be categorized in other recalcitrant taxa where variation is primarily partitioned at the species-level.

evolutionary biology↗