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477 results for “Evolution: molecular”
Data from: Diversity and molecular evolution of non-visual opsin genes across environmental, developmental, and morphological adaptations in frogs
<p>Dataset for the article Diversity and molecular evolution of non-visual opsin genes across environmental, developmental, and morphological adaptations in frogs. Includes non-visual opsin coding sequences from frogs, sequence alingments, phylogenetics trees, and raw PAML results files.</p>
Comparative analysis of phenotypic plasticity sheds light on the evolution and molecular underpinnings of locust phase polyphenism
<p>Locusts exhibit one of nature's most spectacular examples of complex phenotypic plasticity, in which changes in density cause solitary and cryptic individuals to transform into gregarious and conspicuous locusts forming large migrating swarms. We investigated how these coordinated alternative phenotypes might have evolved by studying the Central American locust and three closely related non-swarming grasshoppers in a comparative framework. By experimentally isolating and crowding during nymphal development, we induced density-dependent phenotypic plasticity and quantified the resulting behavioural, morphological, and molecular reaction norms. All four species exhibited clear plasticity, but the individual reaction norms varied among species and showed different magnitudes. Transcriptomic responses were species-specific, but density-responsive genes were functionally similar across species. There were modules of co-expressed genes that were highly correlated with plastic reaction norms, revealing a potential molecular basis of density-dependent phenotypic plasticity. These findings collectively highlight the importance of studying multiple reaction norms from a comparative perspective.</p>
Molecular Phylogenetics and Trait Evolution in Stigmatodon (Bromeliaceae, Tillandsioideae), an Endemic Genus to Brazilian Rocky Outcrops
<p><strong><em>Abstract</em></strong>—The genus <em>Stigmatodon</em> occurs in steep granite slopes, typical of the inselbergs from the Brazilian Atlantic Forest. Here, we present the first broad phylogenetic analysis focused on <em>Stigmatodon</em>, sampling a total of 83 terminals, including 16 of the 20 species of the genus and the morphologically similar species of <em>Vriesea</em>. We conducted a phylogenetic analysis using two plastid markers (<em>matK </em>and <em>rps16-trnK</em>) and the nuclear gene <em>PHYC</em> to infer phylogenetic relationships and reconstruct ancestral states for ecological and morphological characters. Our results suggest the monophyly of <em>Stigmatodon</em> as originally circumscribed is only possible with the inclusion of morphologically and ecologically similar <em>Vriesea</em> species. In addition, the morphological and anatomical traits led us to propose a new circumscription for the genus, combining eight species of <em>Vriesea </em>to <em>Stigmatodon</em>. The stomata positioned above the ordinary epidermal cells, the adaxial water-storage parenchyma with axially elongated cells, the stamens positioned in two groups of three on each side of the corolla and the tubo-laciniate stigma are exclusive to <em>Stigmatodon</em> in its new circumscription. This new morphological and phylogenetic results constitute a relevant contribution to the taxonomy and evolution of Bromeliaceae, one of the most diverse and ecologically important families of flowering plants of the Neotropics.</p>
Molecular evolution and depth-related adaptations of rhodopsin in the adaptive radiation of cichlid fishes in Lake Tanganyika
<p><span>The visual sensory system is essential for animals to perceive their environment and is thus under strong selection. In aquatic environments, light intensity and spectrum differ primarily along a depth gradient. Rhodopsin (RH1) is the only opsin responsible for dim-light vision in vertebrates and has been shown to evolve in response to the respective light conditions, including along a water depth gradient in fishes. In this study, we examined the diversity and sequence evolution of RH1 in the virtually entire adaptive radiation of cichlid fishes in Lake Tanganyika, focusing on adaptations to the achromatic environment with respect to depth. We show that Tanganyikan cichlid genomes contain a single copy of RH1. The 76 variable amino acid sites detected in RH1 across the radiation were not uniformly distributed along the protein sequence, and 31 of these variable sites show signals of positive selection. Moreover, the amino acid substitutions at 15 positively selected sites appeared to be depth-related, including three key tuning sites that directly mediate shifts in the peak spectral sensitivity, one site involved in protein stability, and 11 sites that may be functionally important on the basis of their </span><span>physicochemical properties. Among the strongest candidate sites for deep-water adaptations are two known key tuning sites (positions 292 and 299) and three newly identified variable sites (37, 104 and 290). Our study, which is th first compralehensive analysis of RH1 evolution in a massive adaptive radiation of cichlid fishes, provides novel insights into the evolution of RH1 in a freshwater environment.</span></p>
Supplementary Materials from the article Characterization and molecular evolution analysis of Periploca forrestii inferred from its complete chloroplast genome sequence
<p>Table S1. Base composition of chloroplast genome in <em>P. forrestii</em>, Table S2. The lengths of introns and exons for the splitting genes, Table S3. The GC content of the codons from <em>P. forrestii </em>chloroplast genome, Table S4. Preferred codons in chloroplast genome of <em>P. forrestii</em>, Table S5. Long repeat sequences in the <em>P. forrestii </em>chloroplast genome, Figure S1. Codon bias analysis of P. forrestii chloroplast genome. (A) Neutrality plot analysis; (B) Analysis of PR2 bias plot; (C) Analysis on ENC and GC3 relationship.</p>
Impact of host demography and evolutionary history on endosymbiont molecular evolution: a test in carpenter ants (Genus Camponotus) and their Blochmannia endosymbionts
Obligate endosymbioses are tight associations between symbionts and the hosts they live inside. Hosts and their associated obligate endosymbionts generally exhibit codiversification, which has been documented in taxonomically diverse insect lineages. Host demography (e.g., effective population sizes) may impact the demography of endosymbionts, which may lead to an association between host demography and the patterns and processes of endosymbiont molecular evolution. Here, we used whole-genome sequencing data for carpenter ants (Genus Camponotus; subgenera Camponotus and Tanaemyrmex) and their Blochmannia endosymbionts as our study system to address whether Camponotus demography shapes Blochmannia molecular evolution. Using whole-genome phylogenomics, we confirmed previous work identifying codiversification between carpenter ants and their Blochmannia endosymbionts. We found that Blochmannia genes have evolved at a pace ~30× faster than that of their hosts' molecular evolution and that these rates are positively associated with host rates of molecular evolution. Using multiple tests for selection in Blochmannia genes, we found signatures of positive selection and shifts in selection strength across the phylogeny. Host demography was associated with Blochmannia shifts toward increased selection strengths, but not associated with Blochmannia selection relaxation, positive selection, genetic drift rates, or genome size evolution. Mixed support for relationships between host effective population sizes and Blochmannia molecular evolution suggests weak or uncoupled relationships between host demography and Blochmannia population genomic processes. Finally, we found that Blochmannia genome size evolution was associated with genome-wide estimates of genetic drift and number of genes with relaxed selection pressures. --
Data supplementing the article "Avoiding quantification bias in metabarcoding: application of a cell biovolume correction factor in diatom molecular biomonitoring" V. Vasselon, A. Bouchez, F. Rimet, S. Jacquet, R. Trobajo, M. Corniquel, K. Tapolczai, I. Domaizon submitted to Methods in Ecology and Evolution journal
<p>These data supplement the article "Avoiding quantification bias in metabarcoding: application of a cell biovolume correction factor in diatom molecular biomonitoring" V. Vasselon, A. Bouchez, F. Rimet, S. Jacquet, R. Trobajo, M. Corniquel, K. Tapolczai, I. Domaizon submitted to Methods in Ecology and Evolution journal</p> <p>The directory contains the following files:</p> <p>1<strong>5 fastq files raw reads (5 mock communities, 3 replicates)</strong><strong>.rar </strong>- contains the 15 fastq files provided by the sequencing platform with demultiplexed DNA reads (raw data prior any bioinformatics treatments).</p> <p><strong>15 fastq files information.xlsx</strong> :</p> <p>- contains the information relative to the 15 fastq files corresponding to the PGM raw data of the 5 mock communities (sequenced with 3 replicates), including: the ID of the fastq files, the mock community name, the replicate number, the final sample Id and the number of raw reads per fastq file.</p> <p>- contains the information of the proportion of the 8 diatoms species (%) used to create the 5 mock communities (estimated from microscopy).</p>
Data from "Allostery and evolution: a molecular journey throught the structural and dynamical landscape of an enzyme super family."
<p>This data accompanies the paper entitled Allostery and evolution: a molecular journey throught the structural and dynamical landscape of an enzyme super family.</p> <p>The zip archive contains: </p> <p>1- Starting configurations of the proteins after equilibration in PDB format and trajectories of unrestrained molecular dynamics simulations with the positions of the proteins every 100 ps in XTC gromacs format are provided for all systems. </p> <p>2- The free energy profiles and histograms are provided for all umbrella sampling simulations and the scripts used to run it with gromacs.</p>
Fig. 1 in Evolution and systematics of Green Bush-crickets (Orthoptera: Tettigoniidae: Tettigonia) in the Western Palaearctic: testing concordance between molecular, acoustic, and morphological data
Fig. 1 Map showing the sampling sites for Tettigonia
Data supplementing the article "Diatom DNA metabarcoding for biomonitoring : strategies to avoid major taxonomical and bioinformatical biases limiting molecular indices capacities" K. Tapolczai, F. Keck, A. Bouchez, F. Rimet, M. Kahlert and V. Vasselon submitted to "Frontiers in Ecology and Evolution" journal
<p>These data supplement the article "Diatom DNA metabarcoding for biomonitoring : strategies to avoid major taxonomical and bioinformatical biases limiting molecular indices capacities" K. Tapolczai, F. Keck, A. Bouchez, F. Rimet, M. Kahlert and V. Vasselon submitted to "Frontiers in Ecology and Evolution" journal.</p> <p>The directory contains the following files:</p> <p><strong>464_samples_fastq_files_(mothur).rar </strong>- contains the 464 fastq files proceed together during the Mothur bioinformatics treatments to produce the OTUs and ISUs tables. As the contig and the demultiplexing steps were performed by the sequencing platform, there is 1 fastq file per sample. From this 464 samples OTU/ISU tables, only information regarding 76 samples were used in this study and are listed in the "<strong>76_samples_list_(mothur).xlsx" </strong>file<strong>.</strong></p> <p><strong>76_samples_list_(mothur).xlsx </strong>- contains the information regarding the 76 samples used to create the OTUs and ISUs tables presented in the paper.</p> <p><strong>76_samples_R1_R2_fastq_files(DADA2).rar - </strong>contains the raw demultiplexed fastq files (R1.fastq and R2.fastq) for each of the 76 samples used in this study to produce the ESVs table using the DADA2 bioinformatics pipeline.</p>
Processed data supporting the manuscript "Cutting the sap: first molecular phylogeny of twig-girdler longhorn beetles (Coleoptera: Cerambycidae: Lamiinae: Onciderini) suggests shifts in host plant attack behaviors contributed to morphological evolution"
<div><strong>Processed data supporting the manuscript: </strong>Cutting the sap: first molecular phylogeny of twig-girdler longhorn beetles (Coleoptera: Cerambycidae: Lamiinae: Onciderini) suggests shifts in host plant attack behaviors contributed to morphological evolution</div> <div> </div> <div><strong>By:</strong> Diego de S. Souza 1, 2, Rowan L. K. French 3, José O. Silva Júnior 4, Eugenio H. Nearns 5, Luciane Marinoni 4, Ian P. Swift 6, Kelly B. Miller 7, Felix A. H. Sperling 2 & Marcela L. Monné 1</div> <div> </div> <div>1 Department of Entomology, National Museum, Federal University of Rio de Janeiro, Rio de Janeiro, Rio de Janeiro, Brazil.</div> <div>2 Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada.</div> <div>3 Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, Ontario, Canada.</div> <div>4 Department of Zoology, Federal University of Paraná, Curitiba, Paraná, Brazil.</div> <div>5 National Museum of Natural History, Smithsonian Institution, Washington, DC, USA.</div> <div>6 California State Collection of Arthropods, Sacramento, California, USA.</div> <div>7 Department of Biology and Museum of Southwestern Biology, University of New Mexico, Albuquerque, New Mexico, USA.</div> <div> </div> <div>Corresponding author: Diego de S. Souza, dsouza@fieldmuseum.org. Current affiliation: Field Museum of Natural History, Chicago, Illinois, USA.</div> <div> </div> <div> </div> <div><strong>List of Contents: </strong></div> <div> </div> <div><strong>Onciderini_concat_matrix.phy</strong></div> <div>Concatenated matrix (cox1, Wg and CPS) used for the phylogenetic analyses of Onciderini (Coleoptera: Cerambycidae: Lamiinae: Onciderini). </div> <div> </div> <div><strong>PartitionFinder_AICc_best_scheme.txt</strong></div> <div>Results from PartitionFinder v2.1.1, containing the best partitioning scheme for the concatenated matrix of Onciderini, identified using the corrected Akaike Information Criterion (AICc), with model definitions for use in the phylogenetic analyses.</div> <div> </div> <div><strong>RAxML_Onciderini_concat_matrix (zip file)</strong></div> <div>- Onciderini_concat_matrix.phy: concatenated matrix (cox1, Wg and CPS) used in the RAxML phylogenetic analyses of Onciderini (Coleoptera: Cerambycidae: Lamiinae: Onciderini).</div> <div>- Partitions_AICc_RAxML.txt: partitioning scheme used in the RAxML analysis as predefined by PartitionFinder v2.1.1 using the corrected Akaike Information Criterion (AICc).</div> <div>- RAxML_bestTree.Onciderini_concat_matrix_ML: best-scoring maximum likelihood tree inferred by RAxML for the concatenated matrix of Onciderini.</div> <div>- RAxML_bipartitions.Onciderini_concat_matrix_final: bipartitions (clades) of the maximum likelihood tree inferred by RAxML with support values estimated from 1,000 pseudoreplicates.</div> <div>- RAxML_bipartitionsBranchLabels.Onciderini_concat_matrix_final: final maximum likelihood tree inferred by RAxML for the concatenated matrix of Onciderini, with labeled branches showing bootstrap support values.</div> <div>- RAxML_bootstrap.Onciderini_concat_matrix_bootstrap: bootstrap trees generated from a non-parametric bootstrap analysis in RAxML based on 1,000 pseudoreplicates.</div> <div>- RAxML_info.Onciderini_concat_matrix_bootstrap: log file containing details of the bootstrap analysis, including the settings and parameters used in the non-parametric bootstrap runs in RAxML.</div> <div>- RAxML_info.Onciderini_concat_matrix_final: log file summarizing the RAxML analysis, including settings and convergence statistics for the final maximum likelihood tree.</div> <div>- RAxML_info.Onciderini_concat_matrix_ML: log file containing details of the maximum likelihood tree search, including the parameters and models applied during the maximum likelihood analysis conducted by RAxML.</div> <div>- RAxML_log.Onciderini_concat_matrix_ML: log file of the maximum likelihood tree search for the concatenated matrix of Onciderini.</div> <div>- RAxML_parsimonyTree.Onciderini_concat_matrix_ML: parsimony starting tree used by RAxML during the maximum likelihood analysis for the concatenated matrix of Onciderini.</div> <div>- RAxML_result.Onciderini_concat_matrix_ML: maximum likelihood tree inferred by RAxML from the concatenated matrix of Onciderini, summarizing the tree topology and likelihood score for the best tree obtained.</div> <div> </div> <div><strong>BI_AICc_Onciderini_concat_matrix (zip file)</strong></div> <div>- BI_AICc_Onciderini_concat_matrix.nex: nexus file containing the concatenated matrix of Onciderini used for Bayesian Inference (BI), including the best-fit model scheme identified by PartitionFinder and MCMC parameters for running the analysis in MrBayes.</div> <div>- BI_AICc_Onciderini_concat_matrix.nex_r1_r2_combined_consensus.tree: consensus tree from two combined independent Bayesian Inference (BI) runs based on the concatenated matrix of Onciderini, after discarding the first 25% of initial generations as burn-in.</div> <div>- BI_AICc_Onciderini_concat_matrix.nex.run1.p: log file containing parameter values and likelihood scores from the first run of the Bayesian Inference (BI) based on the concatenated matrix of Onciderini.</div> <div>- BI_AICc_Onciderini_concat_matrix.nex.run2.p: log file containing parameter values and likelihood scores from the second run of the Bayesian Inference (BI) based on the concatenated matrix of Onciderini.</div> <div> </div> <div><strong>BEAST2_Onciderini_BD_lognormal (zip file)</strong></div> <div>- BEAUTi_Onciderini_BD_lognormal.xml: XML file generated by BEAUTi for running BEAST2, based on the concatenated matrix of Onciderini, using a birth-death (BD) process model and a lognormal distribution.</div> <div>- BEAST2_Onciderini_BD_lognormal_run[1-8].log: log files from eight independent runs of BEAST2, based on the concatenated matrix of Onciderini, using a birth-death (BD) process model and a lognormal distribution.</div> <div>- TreeAnnotator_Onciderini_BD_lognormal_run1-run8_consensus.out: TreeAnnotator output file combining the results of eight BEAST2 runs based on the concatenated matrix of Onciderini, using a birth-death (BD) process model and a lognormal distribution.</div> <div>- TreeAnnotator_Onciderini_BD_lognormal_run1-run8_consensus.tre: consensus tree from eight combined BEAST2 runs, based on the concatenated matrix of Onciderini, using a birth-death (BD) process model and a lognormal distribution, after discarding the first 10% of initial generations as burn-in.</div> <div> </div> <div><strong>BEAST2_Onciderini_BD_exponential (zip file)</strong></div> <div>- BEAUTi_Onciderini_BD_exponential.xml: XML file generated by BEAUTi for running BEAST2, based on the concatenated matrix of Onciderini, using a birth-death (BD) process model and an exponential distribution.</div> <div>- BEAST2_Onciderini_BD_exponential_[1-8].log: log files from eight independent runs of BEAST2, based on the concatenated matrix of Onciderini, using a birth-death (BD) process model and an exponential distribution.</div> <div>- TreeAnnotator_Onciderini_BD_exponential_run1-run8_consensus.out: TreeAnnotator output file combining the results of eight BEAST2 runs based on the concatenated matrix of Onciderini, using a birth-death (BD) process model and an exponential distribution.</div> <div>- TreeAnnotator_Onciderini_BD_exponential_run1-run8_consensus.tre: consensus tree from eight combined BEAST2 runs, based on the concatenated matrix of Onciderini, using a birth-death (BD) process model and an exponential distribution, after discarding the first 10% of initial generations as burn-in.</div> <div> </div> <div><strong>BEAST2_Onciderini_BD_uniform (zip file)</strong></div> <div>- BEAUTi_Onciderini_BD_uniform.xml: XML file generated by BEAUTi for running BEAST2, based on the concatenated matrix of Onciderini, using a birth-death (BD) process model and a uniform distribution.</div> <div>- BEAST2_Onciderini_BD_uniform_[1-8].log: log files from eight independent runs of BEAST2, based on the concatenated matrix of Onciderini, using a birth-death (BD) process model and a uniform distribution.</div> <div>- TreeAnnotator_Onciderini_BD_uniform_run1-run8_consensus.out: TreeAnnotator output file combining the results of eight BEAST2 runs based on the concatenated matrix of Onciderini, using a birth-death (BD) process model and a uniform distribution.</div> <div>- TreeAnnotator_Onciderini_BD_uniform_run1-run8_consensus.tre: consensus tree from eight combined BEAST2 runs, based on the concatenated matrix of Onciderini, using a birth-death (BD) process model and a uniform distribution, after discarding the first 10% of initial generations as burn-in.</div> <div> </div> <div><strong>Comparative_analyses (zip file)</strong></div> <div><strong>RawData (folder):</strong> raw morphometric and girdling data, plus tree that was later pruned for downstream comparative analyses; these data were used as input for the OncidHeadDimorphism-DatasetPREP-FINAL.R data cleaning script. </div> <div>- Onciderini_BD_lognormal_run1-run8_consensus.nwk: newick version of TreeAnnotator_Onciderini_BD_lognormal_run1-run8_consensus.tre (outputted as a newick file by importing the .tre file into FigTree and exporting in newick format).</div> <div>- Measurements_Onciderini_Raw_Final.csv: individual-level raw morphometric data for Onciderini.</div> <div>- Behav_Matrix_2_states_trimmed_2022-12-15.csv: species-level data on girdling status for Onciderini species, with all Lochmaeocles species classified as girdlers (2 behavioral states across Onciderini species). </div> <div>- Matrix_3_states_trimmed_final.csv: species-level data on girdling status for Onciderini species, with all Lochmaeocles species classified as facultative girdlers (3 behavioral states across Onciderini species). </div> <div>- Matrix_2_states_trimmed_1LochGirdler_Final.csv: species-level data on girdling status for Onciderini species, with only one Lochmaeocles species (L. tessellatus) classified as a girdler (2 behavioral states across Onciderini species). </div> <div> </div> <div><strong>ProcessedData (folder): </strong>filtered data and pruned trees outputted by the OncidHeadDimorphism-DatasetPREP-FINAL.R script</div> <div>- oncid_f_36spp_clean.csv: dataset of species means and log-ratios for morphometric traits in females, plus girdling data; only includes species that have girdling data and are in the phylogenetic tree</div> <div>- oncid_m_42spp_clean.csv: dataset of species means and log-ratios for morphometric traits in males, plus girdling data; only includes species that have girdling data and are in the phylogenetic tree</div> <div>- oncid_sd_35spp_clean.csv: dataset of species means for sexual dimorphism in morphometric traits, plus girdling data; only includes species that have girdling data and are in the phylogenetic tree</div> <div>- oncid_girdlingbehav_allingroupspp_clean.csv: full dataset of girdling behavior for 56 Onciderini species that are in the phylogenetic tree; includes separate columns for the three alternative girdling classification schemes</div> <div>- oncid_tree_behavfull_56spp.nwk: pruned phylogenetic tree for the full girdling dataset (56 species)</div> <div>- oncid_tree_f_36spp.nwk: pruned phylogenetic tree for the female morphometric dataset (36 species)</div> <div>- oncid_tree_m_42spp.nwk: pruned phylogenetic tree for the male morphometric dataset (42 species)</div> <div>- oncid_tree_mf_43spp.nwk: pruned phylogenetic tree for all species with morphometric data for males or females; used for the stochastic character map next to the heatmap plot (Fig 4)</div> <div>- oncid_tree_sd_35spp.nwk: pruned phylogenetic tree for the sexual dimorphism dataset (35 species)</div> <div> </div> <div><strong>FittedModels (folder): </strong>fitted models (mvgls, model comparison analyses, OUM models, simmaps) outputted by the OncidHeadDimorphism-Analysis-FINAL.R script </div> <div>- MacroModelFits_logRtraits_f_36spp-2024-10-12.Rdata: summary of model comparison results for Brownian Motion (BM), single-peak Ornstein-Uhlenbeck (OU), multipeak OU (OUM), and multi-rate Brownian motion (BMM) models (univariate and multivariate) fitted to female morphometric data across 100 stochastic character maps of girdling behavior</div> <div>- MacroModelFits_logRtraits_m_42spp-2024-10-12.Rdata: summary of model comparison results for Brownian Motion (BM), single-peak Ornstein-Uhlenbeck (OU), multipeak OU (OUM), and multi-rate Brownian motion (BMM) models (univariate and multivariate) fitted to male morphometric data across 100 stochastic character maps of girdling behavior</div> <div>- MacroModelFits-SDDI-35spp_2024-10-11.Rdata: summary of model comparison results for Brownian Motion (BM), single-peak Ornstein-Uhlenbeck (OU), multipeak OU (OUM), and multi-rate Brownian motion (BMM) models (univariate and multivariate) fitted to sexual dimorphism data across 100 stochastic character maps of girdling behavior</div> <div>- mvgls-results-headsize-mf-2024-10-12.Rdata: fitted mvgls regression models for male and female traits (analyzed separately)</div> <div>- mvgls-results-sddi-2024-10-12.Rdata: fitted mvgls regression models for sexual dimorphism</div> <div>- OUM_headtraits_f_36spp-2024-10-12.Rdata: fitted OUM models and summary statistics for female head traits</div> <div>- OUM_headtraits_m_42spp-2024-10-12.Rdata: fitted OUM models and summary statistics for male head traits</div> <div>- OUM-SDDI-35spp-2024-10-12.Rdata: fitted OUM models and summary statistics for sexual dimorphism in head traits</div> <div>- simmaps_ard_full_2state.RDS: stochastic character maps of girdling behaviour for all 56 species with girdling data, with two behavioral states (girdling or non-girdling) - all Lochmaeocles species are classified as girdlers</div> <div>- simmaps_ard_full_3state.RDS: stochastic character maps of girdling behaviour for all 56 species with girdling data, with three behavioral states (girdling, non-girdling, or facultative girdling)</div> <div>- simmaps_ard_full_1Loch.RDS: stochastic character maps of girdling behaviour for all 56 species with girdling data, with two behavioral states (girdling or non-girdling) - only one Lochmaeocles species (L. tessellatus) is classified as a girdler</div> <div>- simmaps_ard_m.RDS: stochastic character map for the 42 species used in the analyses of male morphometric traits</div> <div>- simmaps_ard_f.RDS: stochastic character map for the 36 species used in the analyses of female morphometric traits</div> <div>- simmaps_ard.RDS: stochastic character map for the 35 species used in the sexual dimorphism analyses; 2 behavioral states.</div> <div> </div> <div><strong>Rscripts (folder): </strong>R scripts used to process data and run phylogenetic comparative analyses of head size and girdling behavior.</div> <div>- OncidHeadDimorphism-DatasetPREP-FINAL.R: R script used to filter data and prune trees from the RawData folder for downstream phylogenetic comparative analyses; outputs of this script are in the ProcessedData folder.</div> <div>- OncidHeadDimorphism-Analysis-FINAL.R: R script used to analyze data in the ProcessedData folder to answer questions about the origin and evolution of girdling behavior and the relationship between girdling and head size or head size sexual dimorphism; fitted models outputted by this script are in the FittedModels folder</div> <div>- OncidHeadDimorphism-Plots-FINAL.R: R script used to generate plots for the manuscript<br><br></div>
Fig. 8 in On ''Molecular Phylogeny of Vespidae (Hymenoptera) and the Evolution of Sociality in Wasps''
Fig. 8. Screen display of first step in realignment. See text for explanation of gap insertion.
Fig. 9 in On ''Molecular Phylogeny of Vespidae (Hymenoptera) and the Evolution of Sociality in Wasps''
Fig. 9. Screen display of second step in realignment. See text for explanation of gap insertion.
Fig. 1. Cladogram for the 16S in On ''Molecular Phylogeny of Vespidae (Hymenoptera) and the Evolution of Sociality in Wasps''
Fig. 1. Cladogram for the 16S mtrDNA alignment of Schmitz and Moritz (1998). The length is
Data for "Covalent functionalization of CdSe quantum dot films with molecular [FeFe] hydrogenase mimics for light-driven hydrogen evolution"
<p>This dataset contains UV/Vis absorption and photoluminescence spectra, AFM and SEM data, FT-IR, XPS, and XRF characterization, and data on photocatalytic hydrogen evolution.</p>
Data from: Dissecting molecular evolution of class 1 integron gene cassettes and their bacterial hosts in suburban creeks via epicPCR
<p>Horizontal gene transfer (HGT) of class 1 integrons plays a key role in the dissemination of antimicrobial resistance (AMR) with clinical consequences worldwide. Class 1 integrons in clinical pathogens are commonly associated with AMR genes and embedded in mobile genetic elements. Over time, these mobile class 1 integrons have spread to diverse environmental bacterial hosts via HGT. We applied a single-cell fusion PCR-based technique to link class 1 integron gene cassette arrays to the phylogenetic markers in their bacterial hosts. Class 1 integrons and associated gene cassettes were detected in <em>Alpha</em>- and <em>Gammaproteobacteria </em>hosts from freshwater samples from two creeks in suburban Sydney. Molecular and bioinformatic characterisations of altered gene cassettes generated new insights into mechanisms that contribute to the evolution of class 1 integron gene cassettes. Here, we present experimental and bioinformatic evidence for key signatures of molecular evolution of gene cassettes, including the gain of a regulatory 5'-untranslated region (5'-UTR), the loss of <em>attC </em>recombination sites between adjacent gene cassettes, and the invasion of a 5'-UTR by an insertion sequence (IS) element. Notably, our experimental testing of a new variant of the aminoglycoside adenylyltransferase encoding <em>aadA11 </em>gene cassette demonstrated that the gain of 5'-UTR contributed to a 3-fold increase in the minimum inhibitory concentration of streptomycin relative to the ancestral reference gene cassette. Understanding these signatures of molecular evolution allows us to explain their effects on AMR phenotypes and offers the potential to better predict evolutionary trajectories of class 1 integrons.</p>
Data from: Evaluating the accuracy of methods for detecting correlated rates of molecular and morphological evolution
<p class="MsoNormal"><span>Determining the link between genomic and phenotypic change is a </span><span>fundamental goal in evolutionary biology. Insights into this link can be gained by using a phylogenetic approach to test for correlations between rates of molecular and morphological evolution. However, there has been persistent uncertainty about the relationship between these rates, partly because conflicting results have been obtained using various methods that have not been examined in detail. We carried out a simulation study to evaluate the performance of five statistical methods for detecting correlated rates of evolution. Our simulations explored the evolution of molecular sequences and morphological characters under a range of conditions. Of the methods tested, Bayesian relaxed-clock estimation of branch rates was able to detect correlated rates of evolution correctly in the largest number of cases. This was followed by correlations of root-to-tip distances, Bayesian model selection, independent sister-pairs contrasts, and likelihood-based model selection. As expected, the power to detect correlated rates increased with the amount of data, both in terms of tree size and number of morphological characters. Likewise, greater among-lineage rate variation in the data led to improved performance of all five methods, particularly for Bayesian relaxed-clock analysis when the rate model was mismatched. We then applied these methods to a data set from flowering plants and did not find evidence of a correlation in evolutionary rates between genomic data and morphological characters. The results of our study have practical implications for phylogenetic analyses of combined molecular and morphological data sets, and highlight the conditions under which the links between genomic and phenotypic rates of evolution can be evaluated quantitatively.</span></p>
Heterogeneity in the rate of molecular sequence evolution substantially impacts the accuracy of detecting shifts in diversification rates
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Supplementary data: The molecular evolution of cancer associated genes in mammals
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Molecular evolution and depth-related adaptations of rhodopsin in the adaptive radiation of cichlid fishes in Lake Tanganyika
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