cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5061/dryad.42d3b
title: Data from: Phylogenomic data yield new and robust insights into the phylogeny and evolution of weevils

description: The phylogeny and evolution of weevils (the beetle superfamily
 Curculionoidea) has been extensively studied, but many relationships,
 especially in the large family Curculionidae (true weevils; &gt; 50000
 species), remain uncertain. We used phylogenomic methods to obtain DNA
 sequences from 522 protein coding genes for representatives of all
 families of weevils and all subfamilies of Curculionidae. Most of our
 phylogenomic results had strong statistical support, and the inferred
 relationships were generally congruent with those reported in previous
 studies, but with some interesting exceptions. Notably, the backbone
 relationships of the weevil phylogeny were consistently strongly
 supported, and the former Nemonychidae (pine flower snout beetles) were
 polyphyletic, with the subfamily Cimberidinae (here elevated to
 Cimberididae) placed as sister group of all other weevils. The clade
 comprising the sister families Brentidae (straight-snouted weevils) and
 Curculionidae was maximally supported and the composition of both families
 was firmly established. The contributions of substitution modeling, codon
 usage and/or mutational bias to differences between trees reconstructed
 from amino acid and nucleotide sequences were explored. A reconstructed
 timetree for weevils is consistent with a Mesozoic radiation of
 gymnosperm-associated taxa to form most extant families and
 diversification of Curculionidae alongside flowering plants—first
 monocots, then other groups—beginning in the Cretaceous.
description: Amino-acid concatenated
 phylip fileAmino-acid concatenated
 datasetAA_concatenated.phyNucleotide concatenated phylip fileNucleotide concatenated datasetNT_concatenated.phyAA_partitionsPartition text file for amino-acid dataset.NT_partitionsPartition text file for nucleotide datasetOrthograph_output_processing_pipelineOrthograph_output_processing_pipeline
DOI: 10.34740/kaggle/dsv/14631130
title: List Benchmarks Kaggle
DOI: 10.5061/dryad.rr064j8q
title: Data from: The Chlamydiales pangenome revisited: structural stability and functional coherence

description: The entire publicly available set of 37 genome sequences from the
 bacterial order Chlamydiales has been subjected to comparative analysis in
 order to reveal the salient features of this pangenome and its
 evolutionary history. Over 2,000 protein families are detected across
 multiple species, with a distribution consistent to other studied
 pangenomes. Of these, there are 180 protein families with multiple
 members, 312 families with exactly 37 members corresponding to core genes,
 428 families with peripheral genes with varying taxonomic distribution and
 finally 1,125 smaller families. The fact that, even for smaller genomes of
 Chlamydiales, core genes represent over a quarter of the average protein
 complement, signifies a certain degree of structural stability, given the
 wide range of phylogenetic relationships within the group. In addition,
 the propagation of a corpus of manually curated annotations within the
 discovered core families reveals key functional properties, reflecting a
 coherent repertoire of cellular capabilities for Chlamydiales. We further
 investigate over 2,000 genes without homologs in the pangenome and
 discover two new protein sequence domains. Our results, supported by the
 genome-based phylogeny for this group, are fully consistent with previous
 analyses and current knowledge, and point to future research directions
 towards a better understanding of the structural and functional properties
 of Chlamydiales.
description: Supplement
 (01-10)Supplements described in
 manuscript: S1 is sequence input (fasta format); S2 is time-ordered list
 of species; S3 is CAST output; S4 is parsed BLAST output; S5 is MCL
 output; S6 is BLAST output for unique genes; S7 is genome distance matrix;
 S8 is full sequence dataset from Figure 4 (fasta format); S9 is sequence
 dataset from Figure 5 (fasta format); S10 is count of new family
 contributions.Supplement.zip
DOI: 10.5061/dryad.1qq7050
title: Data from: Perceptually relevant speech tracking in auditory and motor cortex reflects distinct linguistic features

description: During online speech processing, our brain tracks the acoustic
 fluctuations in speech at different timescales. Previous research has
 focused on generic timescales (for example, delta or theta bands) that are
 assumed to map onto linguistic features such as prosody or syllables.
 However, given the high intersubject variability in speaking patterns,
 such a generic association between the timescales of brain activity and
 speech properties can be ambiguous. Here, we analyse speech tracking in
 source-localised magnetoencephalographic data by directly focusing on
 timescales extracted from statistical regularities in our speech material.
 This revealed widespread significant tracking at the timescales of phrases
 (0.6–1.3 Hz), words (1.8–3 Hz), syllables (2.8–4.8 Hz), and phonemes
 (8–12.4 Hz). Importantly, when examining its perceptual relevance, we
 found stronger tracking for correctly comprehended trials in the left
 premotor (PM) cortex at the phrasal scale as well as in left middle
 temporal cortex at the word scale. Control analyses using generic bands
 confirmed that these effects were specific to the speech regularities in
 our stimuli. Furthermore, we found that the phase at the phrasal timescale
 coupled to power at beta frequency (13–30 Hz) in motor areas. This
 cross-frequency coupling presumably reflects top-down temporal prediction
 in ongoing speech perception. Together, our results reveal specific
 functional and perceptually relevant roles of distinct tracking and
 cross-frequency processes along the auditory–motor pathway.
description: AK_CK_speech_tracking_2018
DOI: 10.5061/dryad.hq40q06
title: Data from: Predicting genotypes environmental range from genome-environment associations

description: Genome-environment association methods aim to detect genetic markers
 associated with environmental variables. The detected associations are
 usually analysed separately to identify the genomic regions involved in
 local adaptation. However, a recent study suggests that single-locus
 associations can be combined and used in a predictive way to estimate
 environmental variables for new individuals on the basis of their
 genotypes. Here, we introduce an original approach to predict the
 environmental range (values and upper and lower limits) of species
 genotypes from the genetic markers significantly associated with those
 environmental variables in an independent set of individuals. We
 illustrate this approach to predict aridity in a database constituted of
 950 individuals of wild beets and 299 individuals of cultivated beets
 genotyped at 14,409 random Single Nucleotide Polymorphisms (SNPs). We
 detected 66 alleles associated with aridity and used them to calculate the
 fraction (I) of aridity-associated alleles in each individual. The
 fraction I correctly predicted the values of aridity in an independent
 validation set of wild individuals and was then used to predict aridity in
 the 299 cultivated individuals. Wild individuals had higher median values
 and a wider range of values of aridity than the cultivated individuals,
 suggesting that wild individuals have higher ability to resist to
 stress-aridity conditions and could be used to improve the resistance of
 cultivated varieties to aridity.
description: SNP genotypes and
 aridity index(i) SNP data for the
 1249 accessions belonging to six taxa of beets, of which 950 individuals
 of Beta vulgaris subsp. maritima (wild taxon) and 299 individuals of the
 relative cultivated varieties B. vulgaris subsp. vulgaris including all
 the cultivated forms (collected in Europe) and used in genomic environment
 association (ii) Aridity index for the 950 individuals of Beta vulgaris
 subsp. maritima (third row )Data.xlsx
DOI: 10.5061/dryad.10g45
title: Data from: Two areas for familiar face recognition in the primate brain

description: Familiarity alters face recognition: Familiar faces are recognized more
 accurately than unfamiliar ones and under difficult viewing conditions
 when unfamiliar face recognition fails. The neural basis for this
 fundamental difference remains unknown. Using whole-brain functional
 magnetic resonance imaging, we found that personally familiar faces engage
 the macaque face-processing network more than unfamiliar faces. Familiar
 faces also recruited two hitherto unknown face areas at anatomically
 conserved locations within the perirhinal cortex and the temporal pole.
 These two areas, but not the core face-processing network, responded to
 familiar faces emerging from a blur with a characteristic nonlinear surge,
 akin to the abruptness of familiar face recognition. In contrast,
 responses to unfamiliar faces and objects remained linear. Thus, two
 temporal lobe areas extend the core face-processing network into a
 familiar face-recognition system.
description: Brain areas for familiar
 faces (single subjects)Structural images and
 significance maps for the contrast Faces vs. Objects of the Face Localizer
 Experiment and the Face and Object Familiarity Experiment for the subjects
 M1-M4. These compressed NIfTI files were generated using the freely
 available FreeSurfer package, a software application developed at the
 Martinos Center for Biomedical Imaging by the Laboratory for Computational
 Neuroimaging, available at , and files
 may be viewed using this software. Enhanced activation is show as negative
 values, due to the use of contrast agent for functional magnetic resonance
 imaging scanning.familiar_faces_maps.zip
DOI: 10.5061/dryad.3629v
title: Data from: Resolving conflict in eutherian mammal phylogeny using phylogenomics and the multispecies coalescent model

description: The reconstruction of the Tree of Life has relied almost entirely on
 concatenation methods, which do not accommodate gene tree heterogeneity, a
 property that simulations and theory have identified as a likely cause of
 incongruent phylogenies. However, this incongruence has not yet been
 demonstrated in empirical studies. Several key relationships among
 eutherian mammals remain controversial and conflicting among previous
 studies, including the root of eutherian tree and the relationships within
 Euarchontoglires and Laurasiatheria. Both Bayesian and maximum-likelihood
 analysis of genome-wide data of 447 nuclear genes from 37 species show
 that concatenation methods indeed yield strong incongruence in the
 phylogeny of eutherian mammals, as revealed by subsampling analyses of
 loci and taxa, which produced strongly conflicting topologies. In
 contrast, the coalescent methods, which accommodate gene tree
 heterogeneity, yield a phylogeny that is robust to variable gene and taxon
 sampling and is congruentwith geographic data. The data also demonstrate
 that incomplete lineage sorting, a major source of gene tree
 heterogeneity, is relevant to deep-level phylogenies, such as those among
 eutherian mammals. Our results firmly place the eutherian root between
 Atlantogenata and Boreoeutheria and support ungulate polyphyly and a
 sister-group relationship between Scandentia and Primates. This study
 demonstrates that the incongruence introduced by concatenation methods is
 a major cause of longstanding uncertainty in the phylogeny of eutherian
 mammals, and the same may apply to other clades. Our analyses suggest that
 such incongruence can be resolved using phylogenomic data and coalescent
 methods that deal explicitly with gene tree heterogeneity.
description: sequences of 447 CDS in
 nexus formatsequences of the 447
 genes use in the studygene447_final.nexus
DOI: 10.5061/dryad.23rj4pm
title: Data from: Bumblebee visual allometry results in locally improved resolution and globally improved sensitivity

description: The quality of visual information that is available to an animal is
 limited by the size of its eyes. Differences in eye size can be observed
 even between closely related individuals, yet we understand little about
 how this affects vision. Insects are good models for exploring the effects
 of size on visual systems because many insect species exhibit size
 polymorphism. Previous work has been limited by difficulties in
 determining the 3D structure of eyes. We have developed a novel method
 based on x-ray microtomography to measure the 3D structure of insect eyes
 and to calculate predictions of their visual capabilities. We used our
 method to investigate visual allometry in the bumblebee Bombus terrestris
 and found that size affects specific aspects of vision, including
 binocular overlap, optical sensitivity, and dorsofrontal visual
 resolution. This reveals that differential scaling between eye areas
 provides flexibility that improves the visual capabilities of larger
 bumblebees.
description: Bee Eye
 DataThe data resulting from
 computational analysis of the segmented bee eye volumes in the study by
 Taylor et al. The Zip archive contains an individual Matlab data file
 (.mat format) for each of the eight analysed bee, as well as an single
 data file with the coordinates of a reference sphere onto which the data
 for each bee is projected. Please see the ReadMe file for further
 information.Bee_Eye_Data.zipOriginal calculated data to use for plottingUse this data as input to plotting files available at: https://github.com/gavinscode/compound-eye-plotting-elife.git Parts of the 'Bee_Eye_Data.zip' file were taken from this file. However, this file contains additional data used for plotting and is formatted in a different way.DataForPlots.matMeasured facet sizesFacet sizes measured from volume renderings of bee eyes are original resolution in csv format. The file numbering corresponds to scan numbers These data are required as input for the computational code at: https://github.com/gavinscode/compound-eye-plotting-elife.gitFacet_Sizes.zipBee Compound Eyes and LabelsRaw volumes and label volumes for eyes and heads. These data are archived at MorphoSource project ID 646. They are required as input for the computational code at: https://github.com/gavinscode/compound-eye-plotting-elife.gitGithub gavinscode/compound-eye-plotting-elifeMatlab scripts required for plotting.
DOI: 10.5061/dryad.s14m0
title: Data from: Genome dynamics of hybrid Saccharomyces cerevisiae during vegetative and meiotic divisions

description: Mutation and recombination are the major sources of genetic diversity in
 all organisms. In the baker's yeast, all mutation rate estimates are
 in homozygous background. We determined the extent of genetic change
 through mutation and loss of heterozygosity (LOH) in a heterozygous
 Saccharomyces cerevisiae genome during successive vegetative and meiotic
 divisions. We measured genome wide LOH and base mutation rates during
 vegetative and meiotic divisions in a hybrid (S288c/YJM789) S. cerevisiae
 strain. The S288c/YJM789 hybrid showed nearly complete reduction in
 heterozygosity within 31 generations of meioses and improved spore
 viability. LOH in the meiotic lines was driven primarily by the mating of
 spores within the tetrad. The S288c/YJM789 hybrid lines propagated
 vegetatively for the same duration as the meiotic lines, showed variable
 LOH (from 2-3% and up to 35%). Two of the vegetative lines with extensive
 LOH, showed frequent and large internal LOH tracts that suggest a high
 frequency of recombination repair. These results suggest significant LOH
 can occur in the S288c/YJM789 hybrid during vegetative propagation
 presumably due to return to growth events. The average base substitution
 rates for the vegetative lines (1.82 x 10-10 per base per division) and
 the meiotic lines (1.22 x 10-10 per base per division), are the first
 genome wide mutation rate estimates for a hybrid yeast. This study
 therefore provides a novel context for the analysis of mutation rates
 (especially in the context of detecting LOH during vegetative divisions),
 compared to previous mutation accumulation studies in yeast that used
 homozygous backgrounds.
description: SNP segregation files
 and the custom R scriptsHybrid_MA_line_NKT_dryad19_july.zipData_S1
DOI: 10.5061/dryad.987j0
title: Data from: Large scale determination of previously unsolved protein structures using evolutionary information

description: The prediction of the structures of proteins without detectablesequence
 similarity to any protein of known structure remains anoutstanding
 scientific challenge. Here we describe de novo blindstructure predictions
 of unprecedented accuracy for two proteins in large families made in the
 recent CASP11 blind test of protein structure prediction methods by
 incorporating residue-residue co-evolution information in the Rosetta
 structure prediction program. We then use the method to generate structure
 models for 58 of the 121 large protein families in prokaryotes for which
 three dimensionalstructures are not available. These models, which are
 posted online for public access, provide structural information for the
 over 400,000 proteins belonging to the 58 families and suggest hypotheses
 about mechanism for the subset for which the function is known, and
 hypotheses about function for the remainder.
description: Models for 58 protein
 families predicted with Rosetta-GREMLINPDB files, contact maps
 and images of the predicted protein families. For an interactive version
 of the data and latest models please see:
 http://gremlin.bakerlab.org/structures.phpfiles_from_web.zip
DOI: 10.5061/dryad.8g0v3
title: Data from: No silver bullets in correlative ecological niche modeling: insights from testing among many potential algorithms for niche estimation

description: The field of ecological niche modeling or species distribution modeling
 has seen enormous activity and attention in recent years, in light of
 exciting biological inferences that can be drawn from correlational models
 of species’ environmental requirements (i.e., ecological niches) and
 inferences of potential geographic distributions. Among the many methods
 used in the field, one or two are in practice assumed to be ‘best’ and are
 used commonly, often without explicit testing. We explore herein
 implications of the “No Free Lunch” theorem, which suggests that no single
 optimization approach will prove to be best under all circumstances: we
 developed diverse virtual species with known niche and dispersal
 properties to test a suite of niche modeling algorithms designed to
 estimate potential areas of distribution. The result was that (1) indeed,
 no single ‘best’ algorithm was found, and (2) different algorithms perform
 in very different manners depending on the particularities of the virtual
 species. The conclusion is that niche or distribution modeling studies
 should begin by testing a suite of algorithms for predictive ability under
 the particular circumstances of the study, and choose an algorithm for a
 particular challenge based on the results of those tests. Studies that do
 not take this step may use algorithms that are not optimal for that
 particular challenge.
description: Details of
 characteristics of the 29 virtual species* Method to generate the
 virtual species - A virtual species is a group of occurrences, which are
 selected by an ellipsoid in a 3D environmental space. In this case, we did
 a principal component analysis (PCA) on the 19 bioclimatic variables, and
 used the first 3 principal components to create a 3D environmental space.
 The x, y, z axes are the first three principal components. All of these
 processes were implemented via Niche Analyst
 (http://biodiversity-informatics-training.org/software-data-sources/nichea/). Using Niche Analyst, we created two groups of virtual species with different volumes. The volume of ‘big’ group was 143.69, and the ‘small’ one was 2.14. Each group had 7 virtual species with the same centroid and same directions of semi-axes. * The distribution maps of virtual species - Once niches were created, we explored their projections into geographic space, and created different scenarios of abiotic factors in relation to dispersal. Specifically, we created a scenario in which all suitable conditions were accessible (“Hutchinson’s Dream,” or HD), one in which distributional limitation was driven by dispersal/access exclusively and not by abiotic conditions (“Wallace’s Dream,” or WD), and one in which both abiotic and dispersal considerations act to limit distributions in different areas (“Classic BAM,” or CB).data.zip
DOI: 10.5061/dryad.j6q71
title: Data from: Cellular basis of morphological variation and temperature-related plasticity in Drosophila melanogaster strains with divergent wing shapes

description: Organ shape evolves through cross-generational changes in developmental
 patterns at cellular and/or tissue levels that ultimately alter tissue
 dimensions and final adult proportions. Here, we investigated the cellular
 basis of an artificially selected divergence in the outline shape of
 Drosophila melanogaster wings, by comparing flies with elongated or
 rounded wing shapes but with remarkably similar wing sizes. We also tested
 whether cellular plasticity in response to developmental temperature was
 altered by such selection. Results show that variation in cellular traits
 is associated with wing shape differences, and that cell number may play
 an important role in wing shape response to selection. Regarding the
 effects of developmental temperature, a size-related plastic response was
 observed, in that flies reared at 16 °C developed larger wings with larger
 and more numerous cells across all intervein regions relative to flies
 reared at 25 °C. Nevertheless, no conclusive indication of altered
 phenotypic plasticity was found between selection strains for any wing or
 cellular trait. We also described how cell area is distributed across
 different intervein regions. It follows that cell area tends to decrease
 along the anterior wing compartment and increase along the posterior one.
 Remarkably, such pattern was observed not only in the selected strains but
 also in the natural baseline population, suggesting that it might be
 canalized during development and was not altered by the intense program of
 artificial selection for divergent wing shapes.
description: Torquato_et-al_2014_MeasurementsExcel file containing all wing measurements, trichome counting and cellular estimates. All variables have the same name from the original paper. For further details on each variable, please refer to the original paper.Torquato_et-al_2014_G64-WING-IMAGESImages of all G64 female wings. Note that wing images are named after each specimen listed in the excel file (Torquato_et-al_2014_Measurements.xlsx).Torquato_et-al_2014_G64-TRICHOME-IMAGESTrichome images for each G64 female wing. Trichome images are also named after each specimen listed in the excel file (Torquato_et-al_2014_Measurements.xlsx). But note that trichome images have an extra last digit associated with the intervein region (IVR) within which the given image was taken: 1 = IVRA; 2 = IVRB; 3 = IVRC; 4 = IVRD; 5 = IVRE.