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27 results for “evolutionary simulation”
Simulation systems for: "Pore formation in complex biological membranes: torn between evolutionary needs"
<p>Simulation systems for the publication:</p> <div> <div> <div> <p>Leonhard J. Starke, Christoph Allolio, and Jochen S. Hub, <em>Pore formation in complex biological membranes: torn between evolutionary needs</em>, BioRxiv (2024), doi: <a href="https://doi.org/10.1101/2024.05.06.592649">10.1101/2024.05.06.592649</a></p> <p>Required software:<br>GROMACS Chain Coordinate, a modified GROMACS variant for pore formation across membranes or stalk formation between membranes: <a href="https://gitlab.com/cbjh/gromacs-chain-coordinate">https://gitlab.com/cbjh/gromacs-chain-coordinate</a></p> <p>See README_small.sh and README_large.sh files for instructions on how to run pulling simulations for inducing pores in the provided complex membrane models.</p> </div> </div> </div>
Data from: Methodological artefacts cause counter-intuitive evolutionary conclusions in a simulation study
<p>In their simulation study, Garcia-Costoya et al. (2023) conclude that evolutionary constraints might aid populations facing climate change. However, we are concerned that this conclusion is largely a consequence of the simulated temperature variation being too small, and, most importantly, that uneven limitations to standing variation disadvantage unconstrained populations.</p>
A Genome-Wide Evolutionary Simulation of the Transcription-Supercoiling Coupling: extended version
<p>Data set used for the Artificial Life journal paper <a href="https://direct.mit.edu/artl/article-abstract/28/4/440/112557/A-Genome-Wide-Evolutionary-Simulation-of-the"><em>A Genome-Wide Evolutionary Simulation of the Transcription-Supercoiling Coupling: extended version</em></a>. A preprint of the paper is also available <a href="https://hal.archives-ouvertes.fr/hal-03667822">here</a>.</p> <p>This data is also used in Chapter 4 of my <a href="https://gitlab.inria.fr/tgrohens/phd">PhD thesis</a>.</p>
Data from: Methodological artefacts cause counter-intuitive evolutionary conclusions in a simulation study
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Emergence of kinship structures and descent systems: multi-level evolutionary simulation and empirical data analyses
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Code for individual-based simulations in "Environmental fluctuations can promote evolutionary rescue in high-extinction-risk scenarios"
<p>Substantial environmental change can force a population onto a path towards extinction, but under some conditions, adaptation by natural selection can rescue the population and allow it to persist. This process, known as evolutionary rescue, is believed to be less likely to occur with greater magnitudes of random environmental fluctuations because environmental variation decreases expected population size, increases variance in population size, and increases evolutionary lag. However, previous studies of evolutionary rescue in fluctuating environments have only considered scenarios in which evolutionary rescue was likely to occur. We extend these studies to assess how baseline extinction risk (which we manipulated via changes in the initial population size, degree of environmental change, or mutation rate) influences the effects of environmental variation on evolutionary rescue following an abrupt environmental change. Using a combination of analytical models and stochastic simulations, we show that autocorrelated environmental variation hinders evolutionary rescue in low-extinction-risk scenarios but facilitates rescue in high-risk scenarios. In these high-risk cases, the chance of a run of good years counteracts the otherwise negative effects of environmental variation on evolutionary demography. These findings can inform the development of effective conservation practices that consider evolutionary responses to abrupt environmental changes.</p>
Molecular Dynamics Simulations and associated data for: Mechanistic and evolutionary insights into isoform-specific 'supercharging' in DCLK family kinases
<p>Catalytic signaling outputs of protein kinases are dynamically regulated by an array of structural mechanisms, including allosteric interactions mediated by intrinsically disordered segments flanking the conserved catalytic domain. The Doublecortin Like Kinases (DCLKs) are a family of microtubule-associated proteins characterized by a flexible C-terminal autoregulatory 'tail' segment that varies in length across the various human DCLK isoforms. However, the mechanism whereby these isoform-specific variations contribute to unique modes of autoregulation is not well understood. Here, we employ a combination of statistical sequence analysis, molecular dynamics simulations and in vitro mutational analysis to define hallmarks of DCLK family evolutionary divergence, including analysis of splice variants within the DCLK1 sub-family, which arise through alternative codon usage and serve to 'supercharge' the inhibitory potential of the DCLK1 C-tail. We identify co-conserved motifs that readily distinguish DCLKs from all other Calcium Calmodulin Kinases (CAMKs), and a 'Swiss-army' assembly of distinct motifs that tether the C-terminal tail to conserved ATP and substrate-binding regions of the catalytic domain to generate a scaffold for auto-regulation through C-tail dynamics. Consistently, deletions and mutations that alter C-terminal tail length or interfere with co-conserved interactions within the catalytic domain alter intrinsic protein stability, nucleotide/inhibitor-binding, and catalytic activity, suggesting isoform-specific regulation of activity through alternative splicing. Our studies provide a detailed framework for investigating kinome–wide regulation of catalytic output through cis-regulatory events mediated by intrinsically disordered segments, opening new avenues for the design of mechanistically-divergent DCLK1 modulators, stabilizers or degraders.</p>
Data from: Exploring the macroevolutionary impact of ecosystem engineers using an individual-based eco-evolutionary simulation
<p>Ecosystem engineers can radically reshape ecosystems by modulating the availability of resources to other organisms through modifying either physical or biological aspects of the environment. The introduction or removal of ecosystem engineers from otherwise stable ecosystems can impact the diversity of co-occurring species, such as driving local extinctions of native taxa. While these impacts are well established over ecological timescales for a wealth of taxa, the macroevolutionary implications of the onset of ecosystem engineering behaviours are less clear. Despite this uncertainty, ecosystem engineering has been implicated in several major transitions in Earth's history including the appearance of extensive bioturbation during the Cambrian substrate revolution and associated Ediacaran-Cambrian turnover and the Great Oxygenation Event. Whether ecosystem engineers are frequently associated with turnover and extinction in deep time is not known. Here we investigate this with an eco-evolutionary simulation framework in which we assign lineages the ability to impact the fitness of co-occurring taxa through phenotype-environment feedback. We explore numerous conditions, including how frequently these feedbacks occur, and whether ecosystem engineers modify or create niches. We show that there is no general expected outcome from the introduction of ecosystem engineers. In a minority of runs, ecosystem engineering lineages completely dominate, rendering all others extinct, but in others, they persist (but do not dominate), or die out. We suggest that ecosystem engineers have complex impacts but possess the capacity to profoundly shape diversity, and it is appropriate to consider them alongside other exogenous extinction drivers in deep time. </p>
Simulation scripts and data for the stochastic modelling of evolutionary rescue in resistance to pesticides
<p>Evolutionary rescue occurs when the genetic evolution of adaptation saves a population from extinction after environmental change. The evolution of resistance to pesticides is a special scenario of abrupt environmental change, where rescue occurs under strong selection for one or a few <em>de novo</em> resistance mutations of large effect. Here, we develop continuous-time approximations that accurately predict classic discrete-time dynamics in population genetics and population ecology in an integrated eco-evolutionary model of adaptive rescue through pesticide resistance. We derive analytical approximations for the key distributions and statistics that characterise the results, including the probability density function for the time to resistance and the probability of population extinction. The time to resistance shows a lag period, a narrow peak and a long tail, which implies that it can be difficult to predict when resistance will arise. The probability of population extinction shows a sharp transition, in that when extinction is possible, it is also highly likely, which can make eradication a theoretically achievable goal. Alongside these results contributing to the theory of evolutionary rescue, the methods have produced powerful approximations that lay the foundations of a flexible modelling framework for the applied study of eco-evolutionary dynamics to improve scientific resistance management.</p>
Simulated datasets analysed in Rota et al. study "A simple method for data partitioning based on relative evolutionary rates"
<p>Simulated datasets analysed in Rota et al. study "A simple method for data partitioning based on relative evolutionary rates". AS refers to datasets simulated on an asymmetrical trees and SS to those simulated on a symmetrical tree. The datasets are in phylip format. Having 'miss' in the name of a file refers to missing 25% of the data.</p>
Code for individual-based simulations in "Environmental fluctuations can promote evolutionary rescue in high-extinction-risk scenarios"
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Molecular Dynamics Simulations and associated data for: Mechanistic and evolutionary insights into isoform-specific 'supercharging' in DCLK family kinases
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Data from: Exploring the macroevolutionary impact of ecosystem engineers using an individual-based eco-evolutionary simulation
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PhyloJunction: a computational framework for simulating, developing, and teaching evolutionary models
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Simulation scripts and data for the stochastic modelling of evolutionary rescue in resistance to pesticides
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Stan code from: Simulation modeling reveals the evolutionary role of landscape shape and species dispersal on genetic variation within a metapopulation
Different shapes of landscape boundaries can affect the habitat networks within them and consequently the spatial genetic-patterns of a metapopulation. In this study, we used a mechanistic framework to evaluate the effects of landscape shape, through watershed elongation, on genetic divergence among populations at the metapopulation scale. Empirical genetic data from four, sympatric stream-macroinvertebrates having aerial adults were collected from streams in Japan to determine the roles of species-specific dispersal strategies on metapopulation genetics. Simulation results indicated that watershed elongation allows the formation of river networks with fewer branches and larger topographic constraints. This results in decreased interpopulation connectivity but a lower level of spatial isolation of distal populations (e.g., those found in headwaters) occurring in the landscapes examined. Distal populations had higher genetic divergence when their downstream-biased dispersal (relative to upstream- and/or overland-biased dispersal) was high. This underscores the importance of distal populations influencing genetic divergence at the metapopulation scale for species having downstream-biased dispersal. In turn, lower genetic divergence was observed under watershed elongation when the genetic isolation of distal populations was decreased in such species. This strong association between landscape shape and evolutionary processes highlights the importance of natural, spatial architecture in assessing the effectiveness of conservation and management strategies.
New Mass and Distance Estimates for Betelgeuse through Combined Evolutionary, Asteroseismic, and Hydrodynamical Simulations with MESA
<p>inlists for MESA version 11701 used to compute evolutionary tracks accompanying this manuscript on Betelgeuse</p>
Supplemental material for: Morphological phylogenetics evaluated using novel evolutionary simulations
<p></p><p>Evolutionary inferences require reliable phylogenies. Morphological data has traditionally been analysed using maximum parsimony, but recent simulation studies have suggested that Bayesian analyses yield more accurate trees. This debate is ongoing, in part, because of ambiguity over modes of morphological evolution and a lack of appropriate models. Here we investigate phylogenetic methods using two novel simulation models – one in which morphological characters evolve stochastically along lineages and another in which individuals undergo selection. Both models generate character data and lineage splitting simultaneously: the resulting trees are an emergent property, rather than a fixed parameter. Standard consensus methods for Bayesian searches (Mki) yield fewer incorrect nodes and quartets than the standard consensus trees recovered using equal weighting and implied weighting parsimony searches. Distances between the pool of derived trees (most parsimonious or posterior distribution) and the true trees – measured using Robinson-Foulds (RF), subtree prune and regraft (SPR), and tree bisection reconnection (TBR) metrics – demonstrate that this is related to the search strategy and consensus method of each technique. The amount and structure of homoplasy in character data differs between models. Morphological coherence, which has previously not been considered in this context, proves to be a more important factor for phylogenetic accuracy than homoplasy. Selection-based models exhibit relatively lower homoplasy, lower morphological coherence, and higher inaccuracy in inferred trees. Selection is a dominant driver of morphological evolution, but we demonstrate that it has a confounding effect on numerous character properties which are fundamental to phylogenetic inference. We suggest that the current debate should move beyond considerations of parsimony versus Bayesian, towards identifying modes of morphological evolution and using these to build models for probabilistic search methods.</p><p></p>
Molecular dynamics simulations for "Evolutionary Dynamics of RuBisCO: Emergence of the Small Subunit and its Impact Through Time"
<p>This repository contains the molecular dynamics simulation files for the extant and ancestral RuBisCOs, presented in Amritkar2024 et. al.</p> <p>There are two separate folders, one for the regular MD simulations and the other for MD simulations with gas trajectories.</p> <p>Both folders have the simulation trajectory `.dcd` files and the `.pdb` for their corresponding protein structures.</p> <p>The trajectory files are dried, i.e. water molecules have been removed from them.</p> <p>The data encompasses over 7 extant (pdb ids: 1BWV, 3ZXW, 6FTL, 6URA, 7SNV, 8RUC, 9RUB) and 8 ancestral (Anc-I/I', Anc-I', Anc-I, Anc-IAB, Anc-ICD, Anc-IA, Anc-IB, Anc-I-without-RbcS) RuBisCO complexes.</p> <p>This study performed three types of simulations: with water molecules (labeled as exp01), with water + CO2 molecules (labeled as exp02), and with water + O2 molecules (labeled as exp04).</p> <p>There are two replicates for the exp01 simulations and the simulation length for each is 250 ns.</p> <p>The <em>exp02</em> and <em>exp04</em> files are not present for the RbcS-less (Anc-I/I', Anc-I', Anc-I-without_RbcS, 6URA, and 9RUB) RuBisCOs. The simulation length for the gas simulations is 75 ns and one replicate.</p> <p>Each file is named "<em>RuBisCO-system"</em>."<em>simulation-type</em>".md"replicate-number".dry."<em>pdb or dcd</em>".</p> <p>The files are named with respect to each RuBisCO-id in small (No caps). Anc-I/I' is represented as "anciip" and Anc-I' is represented as "ancip".</p>
Evolutionary adaptation of trees and modelled future larch forest extent in Siberia. Code and simulation data
<p>Code and datset used for the publication: "Evolutionary adaptation of trees and modelled future larch forest extent in Siberia" 2023 Gloy et al.</p>
ScienceDex guides
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.