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150 results for “Evolutionary modelling”
Individual-based eco-evolutionary models for understanding adaptation in changing seas
<p>As climate change threatens species' persistence, predicting the potential for species to adapt to rapidly changing environments is imperative for the development of effective conservation strategies. Eco-evolutionary individual-based models (IBMs) can be useful tools for achieving this objective. We performed a literature review to identify studies that apply these tools in marine systems. Our survey suggested that this is an emerging area of research fueled in part by developments in modeling frameworks that allow simulation of increasingly complex ecological, genetic, and demographic processes. The studies we identified illustrate the promise of this approach and advance our understanding of the capacity for adaptation to outpace climate change. These studies also identify limitations of current models and opportunities for further development. We discuss three main topics that emerged across studies: 1) effects of genetic architecture and non-genetic responses on adaptive potential; 2) capacity for gene flow to facilitate rapid adaptation; and 3) impacts of multiple stressors on persistence. Finally, we perform a set of simple simulations to demonstrate the approach and provide a framework for users to explore eco-evolutionary IBMs as tools for understanding adaptation in changing seas.</p>
Data from: Compensatory adaptation and diversification subsequent to evolutionary rescue in a model adaptive radiation
<p>Biological populations may survive lethal environmental stress through evolutionary rescue. The rescued populations typically suffer a reduction in growth performance and harbour very low genetic diversity compared with their parental populations. The present study addresses how population size and within-population diversity may recover through compensatory evolution, using the experimental adaptive radiation of bacterium <i>Pseudomonas fluorescens</i>. We exposed bacterial populations to an antibiotic treatment; and then imposed a one-individual-size population bottleneck on those surviving the antibiotic stress. During the subsequent compensatory evolution, population size increased and leveled off very rapidly. The increase of diversity was of slower paces and persisted longer. In the very early stage of compensatory evolution, populations of large sizes had a greater chance to diversify; however, this productivity-diversification relationship was not observed in later stages. Population size and diversity from the end of the compensatory evolution was not contingent on initial population growth performance. We discussed the possibility that our results be explained by the emergence of a "holey" fitness landscape under the antibiotic stress.</p>
Evolutionary models demonstrate rapid and adaptive diversification of Australo-Papuan pythons
<p>Lineages may diversify when they encounter available ecological niches. Adaptive divergence by ecological opportunity often appears to follow the invasion of a new environment with open ecological space. This evolutionary process is hypothesized to explain the explosive diversification of numerous Australian vertebrate groups following the collision of the Eurasian and Australian plates 25 million years ago. One of these groups is the pythons, which demonstrate their greatest phenotypic and ecological diversity in Australo-Papua (Australia and New Guinea). Here, using an updated and near complete time-calibrated phylogenomic hypothesis of the group, we show that following invasion of this region, pythons experienced a sudden burst of speciation rates coupled with multiple instances of accelerated phenotypic evolution in head and body shape and body size. These results are consistent with adaptive radiation theory with an initial rapid niche filling phase and later slow-down approaching niche saturation. We discuss these findings in the context of other Australo-Papuan adaptive radiations and the importance of incorporating adaptive diversification systems that are not extraordinarily species-rich but ecomorphologically diverse to understand how biodiversity is generated.</p>
The developmental and evolutionary characteristics of transcription factor binding site clustered regions based on an explainable machine learning model
<p>## Identification of transcription factor binding sites clustered regions</p> <p>First, the TFBSs were identified from ATAC-seq peaks by FIMO. The position-specific weight matrices (PWMs) of transcription factors were downloaded from CIS-BP databases. The genomic sequences under the open chromatin regions were used as inputs for FIMO with a custom library of all motifs for each species to scan for motif instances at a p-value threshold of 1e-5. </p> <p>Then, an established method was used to identify TFCRs by performing the Gaussian kernel density estimations across the genome (with a bandwidth of 300bp centered on each TFBS). Each peak in density profile was considered a TFCR. To determine the complexity of each TFCR, the Gaussian kernelized distances from each peak that contributed at least 0.1 to its strength were determined. The complexity of each TFCR was determined by the quantity and proximity of the contributing TFBS. We combined motif instances based on the TF family information from CIS-BP to calculate the complexity of TFCR. The window for each TFCR was determined by finding the maximum distance (in bp) from the TFCR to a contributing TF and then adding 150 bp (one-half of the bandwidth). Each window was centered on the TFCR. The identified TFCR was grouped into 10 groups based on their complexity from low to high. </p> <p>usage: <br>indir="Human_fimo" # the directory where you put the output files of FIMO <br>motifMap="Homo_sapiens_2020_0920/TF_Information_all_motifs_plus.txt" # the mapping relationship of TF and its TF family from CIS-BP <br>cd Codes/TFCR_embryo <br>perl d-motif_combine.pl $indir TFfamily $motifMap <br>perl e-tfpos_combine.pl TFfamily <br>perl f1-tf_bed-new-c.pl TFfamily <br>perl 0-merge-TFCR.pl $indir TFfamily </p>
Spectral ANalog of Dwarfs (SAND) model atmospheres and Evolutionary Extension to SAND (SANDee) evolutionary models for low-mass stars and brown dwarfs
<p>Spectral ANalog of Dwarfs (SAND) is a new grid of model atmospheres for low-mass stars and brown dwarfs at a variety of chemical compositions, characteristic of various components of the Milky Way, including the galactic halo and globular clusters. The models were calculated using <strong>PHOENIX 15</strong></p> <p>A detailed description of SAND is available in RNAAS 2024 by Alvarado, Gerasimov, Burgasser, Brooks, Aganze and Theissen <a href="https://ui.adsabs.harvard.edu/abs/2024RNAAS...8..134A/abstract">[ADS]</a></p> <p>Evolutionary Extension to SAND (SANDee) is a new grid of evolutionary models that uses the SAND models for synthetic photometry and as atmosphere boundary conditions. SANDee is the first set of models that can reproduce the observed star/brown dwarf transition in globular clusters. SANDee models were calculated using <strong>MESA 23.05.1</strong></p> <p>A detailed description of SANDee is available in ApJ 2024 by Gerasimov, Bedin, Burgasser, Apai, Nardiello, Alvarado and Anderson <a href="https://ui.adsabs.harvard.edu/abs/2024arXiv240501634G/abstract">[ADS]</a></p> <p> </p> <p><strong>Directory structure:</strong></p> <pre><code>SAND.zip : SAND model atmospheres recommended : Subset of SAND atmospheres whose synthetic photometry maintains continuity as a function of temperature rest : The rest of SAND models (see notes on convergence below) SANDee.zip : SANDee evolutionary models BC : MESA atmosphere boundary condition tables for tau=100 at each chemistry MESA : MESA evolutionary models, organized first by chemistry, then by initial mass isogen.zip : Python script to generate model isochrones from SANDee and SAND models isogen.py : The script itself demo.ipynb : Jupyter notebook that demonstrates how the script can be used vega_bohlin_2004.dat : Standard spectrum of Vega for VEGAMAG photometry<br> Other *.dat : Transmission profiles for JWST filters used by the demo notebook custom.patch : Patch with author's changes to the MESA codebase HBL.mrt : Estimated true hydrogen-burning limits for each SAND/SANDee chemistry</code></pre>
Dataset S4-6: Leveraging co-evolutionary insights and AI-based structural modeling to unravel receptor-peptide ligand-binding mechanisms
<h3>Significance statement:</h3> <p>This study presents proof-of-concept for a rapid and inexpensive alternative to classical structure-based approaches for resolving ligand-receptor binding mechanisms. It relies on a multilayered bioinformatic approach that leverages genomic data across diverse species in combination with AI-based structural modeling to identify true ligand and receptor homologues, and subsequently predict their binding mechanisms. <em>In silico </em>findings were validated by multiple experimental approaches, which investigated the effect of amino acid changes in the proposed binding pockets on ligand-binding, complex formation with a co-receptor essential for downstream signaling, and activation of downstream signaling. Our analysis combining evolutionary insights, <em>in silico</em> modeling and functional validation provides a framework for structure-function analysis of other peptide-receptor pairs, which could be easily implemented by most laboratories.</p> <h3><span>Zip file contains:</span></h3> <p><span>Dataset S4:</span><span> </span><strong><span>Plasmid maps of constructs used in this study.</span></strong></p> <p><span>Dataset S5:</span><span> </span><strong><span>AFM and AF3 predicted structures (.pdb) and AFM confidence metrics (.pae)</span></strong></p> <p><span>Dataset S6:</span><span> </span><strong><span>Unedited files (.tiff) of co-IP and western blotting.</span></strong></p>
Fig. 3 in A molecular phylogeny of nephilid spiders: Evolutionary history of a model lineage
Fig. 3. Tree shapes for seven genes obtained with ML (best tree out of 100 replicates) with ingroup in green and outgroups in red. Note that for the two nuclear ribosomal genes (18S and 28S) the ingroup branch lengths are disproportionately long. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Fig. 6 in A molecular phylogeny of nephilid spiders: Evolutionary history of a model lineage
Fig. 6. Typical web architectures of the six nephilid genera mirroring the phylogenetic results: (a) Nephila (N. pilipes); (b) Nephilingis (N. n. sp. from Seychelles); (c) ''Nephila'' (N. inaurata); (d) Herennia (H. multipuncta); (e) Nephilengys (N. papuana); (f) Clitaetra (C. episinoides).
Fig. 5. A in A molecular phylogeny of nephilid spiders: Evolutionary history of a model lineage
Fig. 5. A summary nephilid phylogeny based on the Bayesian tree in Fig. 2 with squares at terminals color coded according to biogeographical regions (see right map inset). Branches are also color coded for geography, with the ancestral values inferred using parsimony optimization. Although the tree is not ultrametric (all terminals are in fact contemporary) the roughly estimated main clade ages are labeled according to the scheme A in Fig. 4. The nephilid ancestral age is thus between 40 and 60 million years when the Gondwanan continents were already largely split (see left map inset).
Fig. 2 in A molecular phylogeny of nephilid spiders: Evolutionary history of a model lineage
Fig. 2. Summary results from the analyses of the molecular matrices. The topology is from the Bayesian analysis of the full matrix partitioned by gene, with posterior probability values above 95% labeled with green dots at nodes. The nine squares on branches summarize the results of the alternative analyses using maximum likelihood (ML), maximum parsimony (MP) and Bayesian inference (BI) on different matrices and partition schemes (key in upper part of legend). Bar colors are indicative of clade support (key in lower part of legend) with solid squares indicating high support, gray squares indicating low support, and empty squares indicating a clade not recovered. Terminal legend as in Fig. 1, but with additional families (from top: MIC = Micropholcommatidae, NIC = Nicodamidae, MYS = Mysmenidae, MIM = Mimetidae, CYA = Cyatholipidae, MAL = Malkaridae, ANA = Anapidae, HOL = Holarchaeidae, SYM = Symphytognathidae, SYN = Synotaxidae). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Fig. 4 in A molecular phylogeny of nephilid spiders: Evolutionary history of a model lineage
Fig. 4. Chronograms obtained under three different calibration schemes: (a) the fossil Nephila jurassica treated as stem orbicularian (red); (b) N. jurassica treated as stem nephilid (green); (c) N. jurassica treated as stem Nephila sensu stricto as implied by the original description (black). Inset plot shows posterior distribution of the ucld.mean parameter for each calibration scheme (color codes as in trees). The arrow and the dotted area in the plot indicate the mean and 95% interval of the ucld.mean estimated by Bidegaray-Batista and Arnedo (2011). Only the scheme shown in a falls roughly within the expected mitochondrial substitution rates. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Fig. 1. A in A molecular phylogeny of nephilid spiders: Evolutionary history of a model lineage
Fig. 1. A pictorial summary of nephilid phenotypic diversity (right, a–h), and a strict consensus of 36 trees resulting from parsimony analyses combining molecular markers (full matrix) with morphology (left). The three sets of squares on branches represent node supports from alternative analyses, as follows: the left set corresponds to the parsimony jackknife support for the full (above branch) and Gblocked (Gb, below) matrices, respectively. The middle bar shows maximum likelihood (ML) bootstrap support of the full matrix under the full codon partition scheme. The right set indicates the Bremer supports for the different partitions (PBS) on the reference tree: above branches, from left to right, values for morphology + behavior, followed by the Bremer support values for the nuclear genes and below branches for the mitochondrial genes. See legend for support thresholds.Terminals have the first three letters of current taxonomic familial placement (from bottom:NEP = Nephilidae, ARA = Araneidae, TET = Tetragnathidae, NES = Nesticidae, THE = Theridiidae, THS = Theridiosomatidae, PIM = Pimoidae, LIN = Linyphiidae, DEI = Deinopidae, ULO = Uloboridae). The ingroup, nephilid part of the tree is colored in green and the ingroup terminals are colored according to the accepted nomenclature prior to the classification changes in the current study. Terminals with original molecular data end with specimen codes (as in Table 1), those with data from GenBank end with GB, and those for which only morphological (and behavioral) data were used are labeled M.
Evolutionary models for R Coronae Borealis stars
<p>MESA input files associated with Schwab (2019). Run with MESA r11701. See included README.org files for explanation.</p>
Fig. 2 in Description of a new syllid species as a model for evolutionary research of reproduction and regeneration in annelids
Fig. 2 SEM images of Typosyllis antoni n. sp. a Anterior end, dorsal view. b Anterior end, ventral view. c Detail of anterior end, dorsal view. d Anterior end, lateral view. e Midbody segments, ventral view. f Midbody parapodia, lateral view
Fig. 6 in Description of a new syllid species as a model for evolutionary research of reproduction and regeneration in annelids
Fig. 6 Confocal maximum projections of Typosyllis antoni n. sp. Phalloidin–rhodamine (gray) and serotonin labeling (red) of cross sections (a–c) and the proventricle (d, e) of adult specimens. Dorsal is up in a–c. Anterior is up in d and right in e. a Cross section of the midbody region, the prominent longitudinal muscle bundles are colored in yellow. The insert shows a detailed view of the parapodium, and major muscle bundles are color coded— parapodial retractor muscle in brown, acicular protractor muscle in green, acicular flexor muscle in violet, chaetal flexor muscle in pink, cirral muscle bundle in blue. b Cross section showing the distinct proventricle (pr) filling almost the whole body cavity. The longitudinal muscle bundles are color coded in yellow. c The proventricle (pr) and the ventral nerve cord (vn) show distinct serotonergic immunoreactivity. d The separated proventricle (pr) exhibits radial honeycomb-like muscle bundles (rb, dotted circle) and prominent circular muscle fibers (cf) surrounding the whole structure. e The separated proventricle (pr) is represented by an anterior circular muscle bundle (am) and suspending muscles (sm) terminating at the border between the anterior circular muscle bundle (am) and the radial muscle bundles (rb). am anterior circular muscle bundle, cf circular muscle fiber, dc dorsal cirrus, dv dorsoventral muscle fibers, in intestine, mm median muscle bundle, pa parapodium, pr proventricle, rb radial muscle bundle, sm suspending muscle fiber, vn ventral nerve cord. Scale bar=100 μm (color figure online)
Fig. 10 in Description of a new syllid species as a model for evolutionary research of reproduction and regeneration in annelids
Fig. 10 Most parsimonius tree. Jacknife support values above nodes. Syllis and Typosyllis species as they were described. Drawings from up to down: chaetae of Syllis benbeliahue (after Aguado and San Martín 2006),
Fig. 8 in Description of a new syllid species as a model for evolutionary research of reproduction and regeneration in annelids
Fig. 8 Light microscopy pictures of regenerating specimens of Typosyllis antoni n. sp. All pictures are dorsal views except d2 (ventral view). a, c, e anterior end, b, d1, d2, f posterior end. The dotted white line indicates the site of dissection. a At 4 days after dissection, the re-developing prostomium (ps), as well as the first two segments (1, 2) are visible (in other specimens also three segments were observed). The prostomium shows palps (pl), antenna (la, ma) and two pairs of eyes (ey). Dorsal tentacular cirri (dt) of the first segment occur. b After 4 days, the pygidium (py) with the anal cirri (ac) and the median papillae (mp) are regenerated. c At 6 days, all in a described anterior structures have grown. Pharynx (ph) is re-developed, connecting the mouth opening (not visible) with the
Fig. 4 in Description of a new syllid species as a model for evolutionary research of reproduction and regeneration in annelids
Fig. 4 Light microscopy pictures of Typosyllis antoni n. sp. a Anterior chaetae, most dorsal ones and medially located in the fascicle. b Anterior chaetae, most dorsal ones. c Anterior chaetae, medially and most ventral ones. d. Anterior aciculae. e Midbody chaetae, most dorsal ones and medially located in the fascicle. f Midbody chaeta, most dorsal one. g Dorsal simple chaeta, posterior parapodium. h Ventral simple chaeta,
Magnetic braking with MESA evolutionary models in the single star and LMXB regimes (Gossage et al. 2023) - Inlists, source code, history files
<p>Associated MESA (r11701) inlists, source files (run_star_extras.f90 and run_binary_extras.f), and outputs (history files for single star models --but the same for binary star models is available upon request) used in producing models featured in <a href="https://ui.adsabs.harvard.edu/abs/2022arXiv221212037G/abstract">Gossage et al. 2023 - Magnetic braking with MESA evolutionary models in the single star and LMXB regimes</a>). README files are included, and please contact to alert me of any issues.</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
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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.