Biology subjects

Sukumaran, J.

Publications and source records attributed to Sukumaran, J..

8 recordsLinked to original sources

bioRxiv2025

The effects of post-divergence gene flow on simultaneous divergence time (SDT) testing

Estimating simultaneous divergence across multiple taxonomic groups from genetic data is a common approach in phylogeographical studies, providing insight into the historical and evolutionary factors shaping species diversification. However, the robustness of divergence time estimates across multiple co-distributed species or population pairs in the face of post-divergence gene flow is often left unaddressed. Here, we use a simulation-based approach to test the robustness of estimating simultaneous divergence within a full-likelihood Bayesian framework when the model assumptions of no gene flow are violated. We generated simulated datasets of multiple population pairs with varying migration rates and estimate shared divergence times with the software package Ecoevolity, comparing them with estimates from population pairs experiencing no migration. Our goal was to identify the threshold at which migration rates begin to bias divergence time estimates, providing insight into the robustness of full-likelihood Bayesian methods under more complex demographic scenarios. We found that simultaneous divergence is incorrectly supported across a broad range of parameters space when assumptions are violated. We suggest that future empirical studies that use simultaneous divergence testing explicitly test for gene flow, or at the very least, explicitly consider the presence, absence, and implications of gene flow in their systems as part of their investigations. We assert that this result--biased support for simultaneous divergence--is just a specific example of a general behavior when the statistical assumptions of the model are not met or there is insufficient power given the data. We additionally recommend that future studies reorient their research framework to focus on trying to demonstrate non-simultaneous divergence in systems. As such, support for simultaneous divergence between groups should be interpreted as failure to resolve non-simultaneous divergence rather than evidence of true simultaneous divergence.

evolutionary biology↗

bioRxiv2025

Thermal Dynamics of Ectotherm Behavioral Strategies: Insights from Agent-Based Simulations

Terrestrial ectotherms use dynamic behavioral thermoregulation strategies that typically rely on finding thermal refugia to avoid unfavorable conditions. Traditional analytic approaches rely on analysis of thermal indices to describe thermal conditions organisms may or may not choose, though computational simulations could potentially be used to analyze thermoregulatory behavior explicitly. Here, we leverage a novel simulation framework that integrates data from operative thermal models deployed in microhabitats available to ectotherms to showcase the trade-offs between two basic thermoregulatory strategies: maintaining a thermal optimum point or attempting to keep their body temperature within a preferred thermal range. We assess the output from simulations of these behavioral strategies to understand their influence on body temperature regulation and occupancy of thermal refugia, and then compare our findings from an empirical case study. Results from our analysis suggest that these two general strategies do not impact thermoregulation as strongly as previously assumed. We also found that occupancy of thermal refugia appeared to be driven by environmental conditions rather than the thermoregulation strategy. Although our case study showed promise in providing insights into predicting use of thermal refugia, understanding microhabitat occupancy from thermal data alone may require finer scale temporal data, or the integration of other factors such as foraging dynamics or predation avoidance. HighlightsO_LIAgent-Based simulation framework which explicitly models ectotherm behavioral thermoregulation. C_LIO_LIAnalysis shows minimal differences between varying thermoregulation strategies. C_LIO_LISimulations identify cathermal activity patterns regardless of behavioral strategy. C_LIO_LIResults show promise of empirical applications. C_LI

ecology↗

bioRxiv2024

Information theoretic inference of magnitude and direction of gene flow in metapopulation networks using nyemtaay, with potential for applications in metastasizing cancer clonal cell origin analysis

BackgroundWe introduce nyemtaay, a Python package for the calculation of classical population genetic statistics and inference of gene flow network connections and directionality in metapopulation networks using information theory. This genetic information flow network inference approach provided here is the only existing implementation of [1], and is applicable not only to ecological and evolutionary organism and landscape scale studies, but also has potential applications in, for example, cancer biology for analyzing clonal cell origins in metastasizing tumors. ResultsWe demonstrate this potential through simulations and an analysis of metastasizing cancer cell lineages, showcasing its ability to identify the tissue site of origin in cancer networks. This work highlights the importance of considering demographic history and founder effects in interpreting gene flow directionality, and the benefits of this understanding in allowing application of this approach to gene flow network modeling to reach a broader range of domains. Conclusionsnyemtaay is available under the MIT license from its public repository (https://github.com/aortizsax/nyemtaay), and can be installed locally using the Python package manager pip.

bioinformatics↗

bioRxiv2023

Uumarrty: Agent Based Simulation Model of Predator Prey Interactions with a Game Theoretical Framework

This paper introduces a new simulation framework for testing hypotheses relating to behavior strategies in predator-prey systems. To this end, we present two tools for simulating and analyzing behavioral trait dynamics: The Nash Score, a novel metric for evaluating evolutionary stability, and Uumarrty, an agent-based framework for simulating predator-prey interactions using game theory. These tools provide an approach for assessing the temporal co-evolution of behavioral traits within agent-based models, with a particular focus on predator-prey dynamics, though the framework is generalizable to other ecological interactions. The Nash Score functions as an analog to the Evolutionarily Stable Strategy (ESS) from classical game theory, offering a quantitative index to assess the relative stability and resilience of behavioral traits under selection. We demonstrate the utility of these tools through a case study on the microhabitat preferences of kangaroo rats and rattlesnakes. Specifically, we explore the emergence and stability of optimal strategies across scenarios with: (1) heterogeneous energy yields among microhabitats, (2) differential strike success rates by microhabitat, and (3) the presence of a specialist predator. Our results highlight how microhabitat specialist predators can drive other predators in the system to specialize due to outcompeting generalists at a given population frequency; leading to behavioral strategy stability in the system. Our case studies also show how behavioral trait dynamics can greatly vary depending on if you treat the trait as a pure strategy versus a mixed strategy. Collectively, this framework enhances our ability to explore ecological and evolutionary responses to environmental change, supporting more robust and comparable simulation-based research in eco-evolutionary dynamics.

evolutionary biology↗

bioRxiv2023

pikun: An Information Theoretic Toolkit for Analysis and Visualization of Species Delimitation Metric Space

BackgroundExisting software for comparison of species delimitation models do not provide a (true) metric or distance functions between species delimitation models, nor a way to compare these models in terms of relative clustering differences along a lattice of partitions. Resultspiikun is a Python package for analyzing and visualizing species delimitation models in an information theoretic framework that, in addition to classic measures of information such as the entropy and mutual information [1], provides for the calculation of the variation of information criterion [2], a true metric or distance function for species delimitation models that is aligned with the lattice of partitions. Conclusionspiikun is available under the MIT license from its public repository (https://github.com/jeetsukumaran/piikun), and can be installed locally using the Python package manager pip.

evolutionary biology↗

bioRxiv2022

AutoPhy: Automated phylogenetic identification of novel protein subfamilies

Phylogenetic analysis of protein sequences provides a powerful means of identifying novel protein functions and subfamilies, and for identifying and resolving annotation errors. However, automation of functional clustering based on phylogenetic trees has been challenging, and most of it is done manually. Clustering phylogenetic trees usually requires the delineation of tree-based thresholds (e.g., distances), leading to an ad hoc problem. We propose a new phylogenetic clustering approach that identifies clusters without using ad hoc distances or other pre-defined values. Our workflow combines uniform manifold approximation and projection (UMAP) with Gaussian mixture models as a k-means like procedure to automatically group sequences into clusters. We then apply a "second pass" clade identification algorithm to resolve non-monophyletic groups. We tested our approach with several well-curated protein families (outer membrane porins, acyltransferase, and dehydrogenases) and showed our automated methods recapitulated known subfamilies. We also applied our methods to a broad range of different protein families from multiple databases, including Pfam, PANTHER, and UNIPROT. Our results showed that AutoPhy rapidly generated monophyletic clusters (subfamilies) within phylogenetic trees evolving at very different rates both within and among phylogenies. The phylogenetic clusters generated by AutoPhy resolved misannotations, determined new protein functional groups, and detected novel viral strains.

bioinformatics↗

bioRxiv2021

An assembly-free method of phylogeny reconstruction using short-read sequences from pooled samples without barcodes

A current strategy for obtaining haplotype information from several individuals involves short-read sequencing of pooled amplicons, where fragments from each individual is identified by a unique DNA barcode. In this paper, we report a new method to recover the phylogeny of haplotypes from short-read sequences obtained using pooled amplicons from a mixture of individuals, without barcoding. The method, AFPhyloMix, accepts an alignment of the mixture of reads against a reference sequence, obtains the single-nucleotide-polymorphisms (SNP) patterns along the alignment, and constructs the phylogenetic tree according to the SNP patterns. AFPhyloMix adopts a Bayesian model of inference to estimates the phylogeny of the haplotypes and their relative frequencies, given that the number of haplotypes is known. In our simulations, AFPhyloMix achieved at least 80% accuracy at recovering the phylogenies and frequencies of the constituent haplotypes, for mixtures with up to 15 haplotypes. AFPhyloMix also worked well on a real data set of kangaroo mitochondrial DNA sequences.

bioinformatics↗

bioRxiv2021

SPART, a versatile and standardized data exchange format for species partition information

A wide range of data types can be used to delimit species and various computer-based tools dedicated to this task are now available. Although these formalized approaches have significantly contributed to increase the objectivity of SD under different assumptions, they are not routinely used by alpha-taxonomists. One obvious shortcoming is the lack of interoperability among the various independently developed SD programs. Given the frequent incongruences between species partitions inferred by different SD approaches, researchers applying these methods often seek to compare these alternative species partitions to evaluate the robustness of the species boundaries. This procedure is excessively time consuming at present, and the lack of a standard format for species partitions is a major obstacle. Here we propose a standardized format, SPART, to enable compatibility between different SD tools exporting or importing partitions. This format reports the partitions and describes, for each of them, the assignment of individuals to the "inferred species". The syntax also allows to optionally report support values, as well as original trees and the full command lines used in the respective SD analyses. Two variants of this format are proposed, overall using the same terminology but presenting the data either optimized for human readability (matricial SPART) or in a format in which each partition forms a separate block (SPART.XML). ABGD, DELINEATE, GMYC, PTP and TR2 have already been adapted to output SPART files and a new version of LIMES has been developed to import, export, merge and split them.

bioinformatics↗