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1,737 results for “host data”
Data from: A heritable symbiont and host-associated factors shape fungal endophyte communities across spatial scales
1. Although microbial ecologists are intensely interested in the processes governing microbial community assembly, progress has been limited by a lack of studies that span multiple geographical scales and levels of biological organization. 2. We used high throughput sequencing to characterize foliar fungal endophyte communities and host plant genetic structure both within, and among, 24 populations of spotted locoweed (Astragalus lentiginosus) across the Great Basin Desert. 3. Across the Great Basin, both within, and among populations of the host plant, fungal endophyte richness was predicted by plant size and variation in the seed-borne, heritable fungus, Alternaria fulva, which produces the bioactive alkaloid swainsonine. 4. The degree of between-plant turnover in the endophyte community was inversely related to host plant inbreeding and average plant size, and positively related to the relative abundance of A. fulva. Plant size was inversely related to endophyte community richness, both among, and within populations. The genetic and physical distance between host populations was not predictive of differences in fungal community structure. 5. Synthesis: Through pairing intensive local- and regional sampling, we uncovered a primacy of deterministic forces imposed by a heritable symbiont on the community structure of locoweed endophytes.
Data from: Is there a disease-free halo at species range limits? The co-distribution of anther-smut disease and its host species
1. While disease is widely recognized as affecting host population size, it has rarely been considered to play a role in determining host range limits. Many diseases may not be able to persist near the range limit if host population density falls below the critical threshold level for pathogen invasion. However, in vector- and sexually-transmitted diseases, pathogen transmission may be largely independent of host density and theory demonstrates that diseases with frequency-dependent transmission may persist in small populations near the range limit. 2. Empirical studies of disease at species range limits have lagged behind the theory, and to date, no previous study has tested the hypothesis that vector or sexually transmitted diseases can be maintained at host range limits. 3. We studied the distribution of anther-smut disease, a sterilizing pollinator-transmitted disease, on four alpine plant species to determine whether disease was present at the host range limits. 4. We found that host abundance declined towards the elevational range limits, and disease extended to the most extreme elevational range limits in three of the four host species. Maximum likelihood estimation of the magnitude of the disease-free halo showed that it was small or non-existent for all host species. Moreover, disease prevalence within populations was often higher nearer the host's range limit than in the range center and was independent of host density. 5. Synthesis: Our results show that diseases where transmission is frequency-dependent have the potential to affect host distributions not just in theory, but also in real world populations.
Data from: Context-dependent costs and benefits of tuberculosis resistance traits in a wild mammalian host
Disease acts as a powerful driver of evolution in natural host populations, yet individuals in a population often vary in their susceptibility to infection. Energetic trade-offs between immune and reproductive investment lead to the evolution of distinct life-history strategies, driven by the relative fitness costs and benefits of resisting infection. However, examples quantifying the cost of resistance outside of the laboratory are rare. Here, we observe two distinct forms of resistance to bovine tuberculosis (bTB), an important zoonotic pathogen, in a free-ranging African buffalo (Syncerus caffer) population. We characterize these phenotypes as 'infection resistance', in which hosts delay or prevent infection, and 'proliferation resistance', in which the host limits the spread of lesions caused by the pathogen after infection has occurred. We found weak evidence that infection resistance to bTB may be heritable in this buffalo population (h2=0.10) and comes at the cost of reduced body condition and marginally reduced survival once infected, but also associates with an overall higher reproductive rate. Infection resistant animals thus appear to follow a 'fast' pace of life syndrome, in that they reproduce more quickly but die upon infection. In contrast, proliferation resistance had no apparent costs and was associated with measures of positive host health- such as having a higher body condition and reproductive rate. This study quantifies striking phenotypic variation in pathogen resistance and provides evidence for a link between life history variation and a disease resistance trait in a wild mammalian host population.
Data from: Running in circles in phylomorphospace: host environment constrains morphological diversification in parasitic wasps
Understanding phenotypic diversification and the conditions that spur morphological novelty or constraint is a major theme in evolutionary biology. Unequal morphological diversity between sister clades can result from either differences in the rate of morphological change or in the ability of clades to explore novel phenotype ranges. We combine an existing phylogenetic framework with new phylogenomic data and geometric morphometrics to explore the relative roles of rate versus mode of morphological evolution for a hyperdiverse group: cryptine ichneumonid wasps. Data from genomic ultraconserved elements (UCEs) confirm that cryptines are divided into two large clades: one specialized in the use of hosts that are deeply concealed under hard substrates, and another with a much more diversified host range. Using a phylomorphospace approach, we show that both clades have experienced similar rates of morphological evolution. Nonetheless, the more specialized group is much more restricted in morphospace occupation, indicating that it repeatedly evolved morphological change through the same morphospace regions. This is in agreement with our prediction that host use imposes constraints in the morphospace available to lineages, and reinforces an important distinction between evolutionary stasis as opposed to a scenario of continual morphological change restricted to a certain range of morphotypes.
Data from: Incomplete host immunity favors the evolution of virulence in an emergent pathogen
Immune memory evolved to protect hosts from reinfection, but incomplete responses that allow future reinfection might inadvertently select for more harmful pathogens. We present empirical and modeling evidence that incomplete immunity promotes the evolution of higher virulence in a natural host-pathogen system. We performed sequential infections of house finches with Mycoplasma gallisepticum strains of varying virulence. Virulent bacterial strains generated stronger host protection against reinfection than less virulent strains, and thus excluded less virulent strains from infecting previously-exposed hosts. In a two-strain model, the resulting fitness advantage selected for an almost two-fold increase in pathogen virulence. Thus, the same immune systems that protect hosts from infection can concomitantly drive the evolution of more harmful pathogens in nature.
Data from: Parasitoids as drivers of symbiont diversity in an insect host
<p>Immune systems have repeatedly diversified in response to parasite diversity. Many animals have outsourced part of their immune defence to defensive symbionts, which should be affected by similar evolutionary pressures as the host's own immune system. Protective symbionts provide efficient and specific protection and respond to changing selection pressure by parasites. Here, we use the aphid Aphis fabae, its protective symbiont Hamiltonella defensa and its parasitoid Lysiphlebus fabarum to test whether parasite diversity can maintain diversity in protective symbionts. We exposed aphid populations with the same initial symbiont composition to parasitoid populations that differed in their diversity. As expected, single parasitoid genotypes mostly favoured a single symbiont that was most protective against that particular parasitoid, while multiple symbionts persisted in aphids exposed to more diverse parasitoid populations, which in turn affected aphid population density and rates of parasitism. Parasite diversity may be crucial to maintaining symbiont diversity in nature.</p>
Data from: Environment and host as large-scale controls of ectomycorrhizal fungi
Explaining the large-scale diversity of soil organisms that drive biogeochemical processes—and their responses to environmental change—is critical. However, identifying consistent drivers of belowground diversity and abundance for some soil organisms at large spatial scales remains problematic. Here we investigate a major guild, the ectomycorrhizal fungi, across European forests at a spatial scale and resolution that is—to our knowledge—unprecedented, to explore key biotic and abiotic predictors of ectomycorrhizal diversity and to identify dominant responses and thresholds for change across complex environmental gradients. We show the effect of 38 host, environment, climate and geographical variables on ectomycorrhizal diversity, and define thresholds of community change for key variables. We quantify host specificity and reveal plasticity in functional traits involved in soil foraging across gradients. We conclude that environmental and host factors explain most of the variation in ectomycorrhizal diversity, that the environmental thresholds used as major ecosystem assessment tools need adjustment and that the importance of belowground specificity and plasticity has previously been underappreciated.
Data from: Combining experimental evolution and genomics to understand how seed beetles adapt to a marginal host plant
<p>Genes that affect adaptive traits have been identified, but our knowledge of the genetic basis of adaptation in a more general sense (across multiple traits) remains limited. We combined population-genomic analyses of evolve and resequence experiments, genome-wide association mapping of performance traits, and analyses of gene expression to fill this knowledge gap, and shed light on the genomics of adaptation to a marginal host (lentil) by the seed beetle <em>Callosobruchus maculatus</em>. Using population-genomic approaches, we detected modest parallelism in allele frequency change across replicate lines during adaptation to lentil. Mapping populations derived from each lentil-adapted line revealed a polygenic basis for two host-specific performance traits (weight and development time), which had low to modest heritabilities. We found less evidence of parallelism in genotype-phenotype associations across these lines than in allele frequency changes during the experiments. Differential gene expression caused by differences in recent evolutionary history exceeded that caused by immediate rearing host. Together, the three genomic data sets suggest that genes affecting traits other than weight and development time are likely to be the main causes of parallel evolution, and that detoxification genes (especially cytochrome P450s and beta-glucosidase) could be especially important for colonization of lentil by <em>C. maculatus</em>.</p>
Data from: No evidence that gut microbiota impose a net cost on their butterfly host
Gut microbes are believed to play a critical role in most animal life, yet fitness effects and cost benefit-tradeoffs incurred by the host are poorly understood. Unlike most hosts studied to date, butterflies largely acquire their nutrients from larval feeding, leaving relatively little opportunity for nutritive contributions by the adult's microbiota. This provides an opportunity to measure whether hosting gut microbiota comes at a net nutritional price. Since host and bacteria may compete for sugars, we hypothesized that gut flora would be nutritionally neutral to adult butterflies with plentiful food, but detrimental to semi-starved hosts, especially when at high density. We held field-caught adult Speyeria mormonia under abundant or restricted food conditions. Since antibiotic treatments did not generate consistent variation in their gut microbiota, we leveraged inter-individual variability in bacterial loads and OTU abundances to examine correlations between host fitness and the abdominal microbiota present upon natural death. We detected strikingly few relationships between microbial flora and host fitness. Neither total bacterial load nor the abundances of dominant bacterial taxa were related to butterflies' fecundity, egg mass, or egg chemical content. Increased abundance of a Commensalibacter species did correlate with longer host lifespan, while increased abundance of a Rhodococcus species correlated with shorter lifespan. Contrary to our expectations, these relationships were unchanged by food availability to the host and were unrelated to reproductive output. Our results suggest the butterfly microbiota comprise parasitic, commensal, and beneficial taxa that together do not impose a net reproductive cost, even under caloric stress.
Data from: Risk alleles for tuberculosis infection associate with reduced immune reactivity in a wild mammalian host
Integrating biological processes across scales remains a central challenge in disease ecology. Genetic variation drives differences in host immune responses, which, along with environmental factors, generates temporal and spatial infection patterns in natural populations that epidemiologists seek to predict and control. However, genetics and immunology are typically studied in model systems, whereas population-level patterns of infection status and susceptibility are uniquely observable in nature. Despite obvious causal connections, organizational scales from genes to host outcomes to population patterns are rarely linked explicitly. Here we identify two loci near genes involved in macrophage (phagocyte) activation and pathogen degradation that additively increase risk of bovine tuberculosis infection by up to 9-fold in wild African buffalo. Furthermore, we observe genotype-specific variation in IL-12 production indicative of variation in macrophage activation. Here we provide measurable differences in infection resistance at multiple scales by characterizing the genetic and inflammatory variation driving patterns of infection in a wild mammal.
Data from: Genome-wide support for incipient Tula orthohantavirus species within a single rodent host lineage
<p>Evolutionary divergence of viruses is most commonly driven by co-divergence with their hosts or through isolation of transmission after host-shifts. It remains mostly unknown, however, whether divergent phylogenetic clades within named virus species represent functionally equivalent byproducts of high evolutionary rates or rather incipient virus species. Here, we test these alternatives with genomic data from two widespread phylogenetic clades in Tula orthohantavirus (TULV) within a single evolutionary lineage of their natural rodent host, the common vole Microtus arvalis. We examined voles from 42 locations in the contact region between clades for TULV infection by RT-PCR. Sequencing yielded 23 TULV Central North and 21 TULV Central South genomes which differed by 14.9-18.5% at the nucleotide and 2.2-3.7% at the amino acid level without evidence of recombination or reassortment. Geographic cline analyses demonstrated an abrupt (<1 km wide) transition between the parapatric TULV clades in continuous landscape. This transition was located within the Central mitochondrial lineage of M. arvalis and genomic SNPs showed gradual mixing of host populations across it. Genomic differentiation of hosts was much weaker across the TULV Central North to South transition than across the nearby hybrid zone between two evolutionary lineages in the host. We suggest that these parapatric TULV clades represent functionally distinct, incipient species which are likely differently affected by genetic polymorphisms in the host. This highlights the potential of natural viral contact zones as systems for investigating of the genetic and evolutionary factors enabling or restricting the transmission of RNA viruses.</p>
Data sets for Polyplax serrata article "Highly-resolved genomes of two closely related lineages of the rodent louse Polyplax serrata with different host specificities"
<p><strong>Supplementary data for Polyplax serrata article 2023</strong></p> <p>Data included in this repository were generated and used in various genomic and phylogenetic analysis presented by the publication "<strong>Highly-resolved genomes of two closely related lineages of the louse </strong><em><strong>Polyplax serrata</strong></em><strong> with different host specificities</strong>"</p> <p><strong>Description of the data and file structure</strong></p> <p>Data provided for each analyzed taxa include:</p> <p>- Annotation table.</p> <p>- fasta format files for transcripts (CDS and mRNA).</p> <p>- fasta format file for genome.</p> <p>- protein fasta file.</p> <p>- gbk format file that includes the genome with its corresponding annotations.</p> <p>Additionally,</p> <p>- repeat families in fasta format were included for <em>Polyplax serrata</em> S and N lineages.</p> <p>- rRNA in fasta format were included for <em>Polyplax serrata</em> S and N lineages, <em>Pediculus humanus, Columbicola columbae </em>and <em>Brueelia nebulsa</em>. </p> <p><strong>Sharing/Access information</strong></p> <p>GenBank accession number of analyzed taxa:</p> <p>· <em>Aedes Aegypti</em> (GenBank accession no. GCF_002204515.2).</p> <p>· <em>Brueelia nebulsa</em> ( GenBank accession no. GCA_028293925.1).</p> <p>· <em>Columbicola columbae</em> (GenBank accession no. GCA_016920875.1).</p> <p>· <em>Cimex lectularis</em> (GenBank accession no. GCF_000648675.2).</p> <p>· <em>Glossina morsitans</em> (GenBank accession no. GCA_001077435.1).</p> <p>· <em>Pediculus humanus</em> (GenBank accession no. GCA_000006295.1).</p> <p>· <em>Rhodnius prolixus</em> (GenBank accession no. GCA_000181055.3).</p> <p>· <em>Polyplax serrata S lineage</em> (GenBank accession no. JAWJWF000000000).</p> <p>· <em>Polyplax serrata N lineage</em> (GenBank accession no. JAWJWE000000000).</p> <p> </p> <p>Note: All the latter genomes except for the two genomes of <em>Polyplax serrata</em> S and N lineages, were acquired from GenBank database and were subjected to the same gene prediction and annotation workflow as <em>P. serrata</em> genomes to maintain methodological consistence in downstream analysis of the annotation results.</p> <p><strong>Software</strong></p> <p>- Gene prediction and annotation was performed using Funannotate v1.18.14 (<a href="https://github.com/nextgenusfs/funannotate">https://github.com/nextgenusfs/funannotate)</a>).</p> <p>- Repeat were identified in the genomes of P. serrata S and N lineages using RepeatModeler v2.0.3.</p>
Data from: Parasitic fish embryos do a 'front-flip' on the yolk to resist expulsion from the host
<p><span>Bitterlings are brood parasitic fish which complete their early development in the internal gill spaces of freshwater mussels. Bitterling embryos have wing-like yolk sac extensions that help prevent them from being expelled from the gills by the water flow</span><span>. The ability to resist expulsion may be helped by the consistent 'head-down' position that all embryos adopt in the gills</span><span>. The mechanism behind this positioning is unknown. We hypothesise here that it might lie in a process of unknown function, specific to bitterlings. That process is <em>blastokinesis</em> — the rotation of the embryo on the yolk ball before hatching</span><span>. </span>We used time-lapse imaging, histology, X-ray tomography, and expression profiling of the genes <em>fgf8a</em>,<em> krt8</em>,<em> msx3 </em>and <em>ctslb</em> by <em><span>in situ</span></em><span> hybridization in the </span>pre-hatching and hatching stages of the rosy bitterling (<em>Rhodeus ocellatus</em>). We find <span>that blastokinesis is a gastrulation process that has been ventralized by the shape of the yolk mass. Furthermore, we show that bitterlings, unlike other teleosts, hatch mechanically without hatching enzymes, and we provide evidence that this is mediated instead by the apical tubercles on the yolk sac extension. Finally, our data suggest that blastokinesis is functional, because it represents the mechanism behind the optimal, 'head-down' positioning of the embryo. Our study provides an example of how selection pressures can lead to a suite of dramatic and coordinated modifications of early development.</span></p>
Data from: A zebrafish model to elucidate the impact of host genes on the microbiota
<p>Every host species and organism provide a unique environmental niche contributing to the overall diversity of microbial ecosystems from the intestine of an animal to the oceans and forests of our planet. The study of host-microbiota interactions has long focused on the well-established effects the microbiota has on its host. In contrast, little focus has been allocated to the role of the host in these intricate interactions. However, understanding the role of the host may well be an essential key to understanding the complexity of the relationship between the host and its microbiota. In this study, we present a model in which the effects of host genes on the microbiota can be elucidated and how such genetic effects may shape host-associated microbiota. We demonstrate a hologenomic approach implementing the CRISPR/Cas system in the zebrafish model to combine the effects of a host gene with 16S metabarcoding and metabolomics data. We show that knocking out the gene coding for the rate-limiting enzyme in melanogenesis, tyrosinase <em>(tyr</em>), correlates with changes in the intestinal microbiota of zebrafish and differences in the abundance of specific metabolites illustrating the value of our model for studying the impact of host genes on the composition and function of the intestinal microbiota.</p>
Infection success data from experimental pairings of cane toad hosts and lungworm parasites
<p>By imposing novel selection pressures on both participants, biological invasions can disrupt evolutionary "arms races" between hosts and parasites. A spatially replicated cross-infection experiment reveals strong divergence in the ability of lungworms (<em>Rhabdias pseudosphaerocephala</em>) to infect invasive cane toads (<em>Rhinella marina</em>) in Australia. In areas colonised for > 20 years, toads are more resistant to infection by local strains of parasites than by allopatric strains. The situation reverses at the invasion front, where super-infective parasites have evolved. Invasion-induced shifts in genetic diversity and selective pressures may explain why hosts win the arms race in long-colonised areas whereas parasites win the arms race at the invasion front.</p>
Data and Analyses for Host plant-mediation of viral transmission and its consequences for a native butterfly
<p>This contains R code for all analyses and creation of figures included in the publication entitled "Host plant-mediation of viral transmission and its Q1 consequences for a native butterfly". This article has now been accepted for publication under DOI: 10.1002/ecy.4282. The files containing the data analysis script have been updated to reflect the final analyses included in this paper. </p>
(Extended Data) Amplicon deep sequencing of ama1 and mdr1 to track within-host P. falciparum diversity throughout treatment in a clinical drug trial
<p>These extended data accompany the manuscript: Targeted Amplicon deep sequencing of ama1 and mdr1 to track within-host <em>P. falciparum</em> diversity throughout treatment in a clinical drug trial</p> <p><strong>Table S1: Concentration ratios and resulting parasitemia in artificial dna mixtures of P. falciparum Lab Isolates 3D7 and Dd2.</strong> This table presents the parasitemia for the artificial mixtures of P. falciparum lab isolates 3D7 and Dd2. Each mixture was prepared at varying ratios of 3D7 to Dd2, starting from equal proportions to a complete presence of only 3D7. The original concentration of each isolate was approximately 50,000 parasites per microliter (pf/μl), and the table displays the proportion of each strain in the mixture and the resulting total parasitemia concentration.</p> <p><strong>Table S2. List of PCR and deep sequencing primers.</strong> This table shows the list of forward and reverse primers used for deep sequencing. In boldface are the MID tags, while in the regular face are the forward primers</p> <p><strong>Table S3. The relative frequencies of each ama1 variant and the number of samples with each variant.</strong> The relative frequencies (%) of the 33 AMA1 variants in pre-and post-treatment samples (n = 330) are shown as a 33 amino acid sequence. The frequencies were calculated by dividing the number of reads of each microhaplotype by the total number of reads obtained per sample (116,187,131).</p> <p><strong>Table S4. Distribution of microhaplotypes among samples.</strong> This table shows the occurrence of microhaplotypes across all participants, both with monoclonal and multiclonal ama1 infections. It presents the ama1 clonality – monoclonal or multiclonal (column 1) - participant IDs (column 2), microhaplotype IDs (column 3), and the relative frequencies of these microhaplotypes across timepoints from 0 to 1008 hours (day 42) (column 3). Dashes represent time points where microhaplotypes were missing or were not detected.</p> <p><strong>Table S5. Distribution of rare microhaplotypes among samples.</strong> This table shows the occurrence of rare microhaplotypes in various samples. It presents participant IDs (column 1), microhaplotype IDs (column 2), and the relative frequencies of these microhaplotypes across time points from 0 to 1008 hours (day 42) (column 3). Samples containing rare microhaplotypes - specifically from PID10, PID32, PID38, PID40, PID49, PID60, PID63, and PID65 - are shown in orange, along with the corresponding rare microhaplotypes and their time points of occurrence. Furthermore, participants are categorised by shared microhaplotypes to indicate instances of rarity and commonality. Except for one microhaplotype unique to PID30, rare microhaplotypes were detected in several samples, frequently exceeding a 5% relative frequency. Dashes represent time points where microhaplotypes were missing or were not detected.</p> <p><strong>Table S6. The parasitemia levels associated with each ama1 microhaplotype per timepoint.</strong> This table shows the parasitemia for each ama1 microhaplotype per timepoint and each participant. “Patient ID” represents the patient ID, “AMA1 COI at 0h” represents the complexity of infection (COI) for each participant at baseline, based on ama1 while subsequent columns represent the parasitemia for each ama1 microhaplotype from timepoint 0h to 1008h. Parasitemia was back-calculated using the COI and total parasitemia for each time point. For time points with a COI > 1, parasitemia for the respective ama1 microhaplotypes are separated by commas, cells in red indicate timepoints without sequencing data (ND = not determined). In contrast, cells in grey indicate time points where microhaplotypes were detected below 10 parasites/μl, hence at risk of falling below the sampling limit.</p> <p><strong>Figure S1. Performance of AmpSeq in the sequencing controls.</strong> Six aliquots were prepared for each control set to ensure sufficient control data in case of PCR or sequencing failure. The median read depth in the lab controls was 5,658 (range 4,310 – 12,603) and 704 (291 – 1,676). The x-axis represents the aliquot identifier across the five mixtures, starting from 1 to 6, while the y-axis represents the proportions of each variant across all aliquots. For ama1 (A), two variants (3D7 and Dd2) were detected, whereas in mdr1 (B), two variants were detected YY, FY and NY following amplification of Dd2 Copy I, Dd2 Copy II and 3D7, respectively. For ama1, sequencing failed for aliquot 6 of control set 1, while for mdr1, sequencing failed for aliquot 2 and 6 of control set 3, aliquots 1 and 6 of control set 4 and aliquots 1 and 5 of control set 5. Under the mdr1 control set 4, the Dd2 copy II (86F, 184Y) was not identified, possibly due to having very low concentrations that were not picked up in this aliquot. Based on our control mixtures, the minimum variant frequency we could detect was 5%.</p> <p><strong>Figure S2. Heatmaps of the successfully PCR amplified and sequenced samples for ama1 (A) and mdr1 (B).</strong> The rows represent the study participants, while the columns represent time in hours. Successfully sequenced samples are shown in blue, those that failed PCR are shown in red and those that failed sequencing are in black. The timepoint “ Rec” represents unscheduled visits where a recurrent sample was collected. The unshaded areas with "-" are time points where samples were not collected. For each time point, the number of samples successfully sequenced (n Successful) is indicated in the last row of each panel. The table in panel C shows the groupings of samples based on parasitemia, high (> 5,000), moderate (100-5,000) and low (< 100 parasites per microlitre). Many samples collected between 0h-12h had high parasitemia, samples collected between 18h–30h had moderate parasitemia, while samples collected after 30h were primarily of low parasitemia.</p> <p><strong>Figure S3. The mean complexity of infection (COI) by AMA1 throughout treatment.</strong> The mean COI (red diamonds) appeared to be stable (between 1.5 - 2) from baseline (0h) up to 72h and thereafter fluctuated due to the small sample sizes (<5) in the post-treatment samples. The black dots represent the COI per sample.</p> <p> </p>
Data From: Lighting pathways to success in STEM: A virtual Lab Meeting Program (LaMP) mutually benefits mentees and host labs
<p>Developing robust professional networks can help shape the trajectories of early career scientists. Yet, historical inequities in STEM fields make access to these networks highly variable across academic programs, and senior academics often have little time for mentoring. Here, we illustrate the success of a Virtual Lab Meeting Program (LaMP). In this program, we matched students ("Mentees") with a more experienced researcher ("Mentors") from a research group. The Mentees then attended the Mentors' lab meetings during the academic year with two lab meetings specifically dedicated to the Mentee's professional development. Survey results indicate that Mentees expanded their knowledge of the hidden curriculum as well as their professional network, while only requiring a few extra hours of their Mentor's time over eight months. In addition, host labs benefitted from Mentees sharing new perspectives and knowledge in lab meetings. The diversity of the Mentees was significantly higher than the Mentors, suggesting that the program increased the participation of traditionally underrepresented groups. Finally, we found that providing a stipend was very important to many mentees. We conclude that Virtual Lab Meeting Programs can be an inclusive and cost-effective way to foster trainee development and increase diversity within STEM fields with little additional time commitment.</p>
Data for: Local adaptation of a generalist hemiparasitic plant to one of its potential host plants
<p>Coevolution is often found in parasite-host interactions but has not yet been described for hemiparasitic plants and their hosts. Root hemiparasites like <em>Rhinanthus alectorolophus</em> perform photosynthesis but also parasitize other plant species, some of which (e.g. <em>Plantago lanceolata</em>) may defend themselves against parasite attack by blocking the haustoria of the parasites. We grew seedlings of the hemiparasite <em>Rhinanthus alectorolophus</em> and the potential host <em>Plantago lanceolata</em> from seven grassland sites in a factorial design. To detect differences in host defence, we also included hosts from two 'naïve' populations from regions where the parasite does not occur.<em> R. alectorolophus</em> grew consistently larger and had higher fitness with sympatric than with allopatric hosts, suggesting parasite adaptation to local host populations. Moreover, <em>R. alectorolophus</em> remained smallest with allopatric hosts from the same region and reached intermediate sizes with allopatric hosts from other regions or naïve hosts, suggesting host adaptation to parasites at the regional scale. Parasite presence reduced the size of the host plants already after four weeks, but only that of hosts with 'experience' of the parasite, suggesting an early host response. Follow-up experiments confirmed that parasites attach to hosts already after four weeks and hosts respond by changing belowground allocation patterns. However, parasite roots did not preferentially grow towards sympatric hosts. Our results suggest that local adaptation to hosts can occur even in generalist parasites and does not require specialization on individual hosts. We discuss the role of potential mechanisms, including variation in chemical signalling (early) and in host defence (late effects).</p>
Data and code for: Host-use Drives Convergent Evolution in Clownfish
<p>This folder contains the following files:</p> <p>data/Alignments_WithOutgroups.tar.gz:<br> Contains the alignments of 10,720 genes with the sequences of the outgroup Pomacentrus moluccensis. The gene IDs correspond to the ID of the Amphiprion frenatus reference genome (Marcionetti et al., 2018; https://datadryad.org/stash/dataset/doi:10.5061/dryad.nv1sv). The position of the gene on the Amphiprion percula chromosomes is also reported. For information on the methods and sample names, please refer to the publication. These alignments were used to infer the species tree with ASTRAL-III. Alignments for the genes selected with SortaDate and used for dating with BEAST are also available and are: chr04_g2455.t1.WithOutgroup.phy, chr05_g51486.t1.WithOutgroup.phychr05_g56452.t1.WithOutgroup.phy, chr08_g50086.t1.WithOutgroup.phy, chr09_g35092.t1.WithOutgroup.phy, chr09_g49030.t1.WithOutgroup.phy, chr10_g47484.t1.WithOutgroup.phy, chr11_g5494.t1.WithOutgroup.phy, chr11_g32313.t1.WithOutgroup.phy, chr12_g7961.t1.WithOutgroup.phy, chr12_g27572.t1.WithOutgroup.phy, chr12_g32580.t1.WithOutgroup.phy, chr13_g33152.t1.WithOutgroup.phy, chr15_g60485.t1.WithOutgroup.phy, chr16_g18013.t1.WithOutgroup.phy, chr17_g60288.t1.WithOutgroup.phy, chr22_g6154.t1.WithOutgroup.phy, chr22_g22141.t1.WithOutgroup.phy, chr22_g29206.t1.WithOutgroup.phy, chr23_g36756.t1.WithOutgroup.phy. </p> <p>data/DatedTree.WithOutgroup.tree:<br> BEAST2 output. The clownfish dated phylogenetic tree with the outgroup Pomacentrus moluccensis used for rooting. The tree was obtained with BEAST2, using 20 most informative genes. For each partition, we applied a GTR+ G site model and an uncorrelated relaxed clock with a lognormal distribution. A secondary calibration points was used, setting uniform prior from 10 to 18 MYA for the crown age of clownfishes. For more information on the methods, please refer to the publication. </p> <p><br>data/Example.DatFile.evolver.tar.gz: <br> Templates of the .dat files (MCcodonNSbranchsites.Shifts_to_Entacmaea.dat, MCcodonNSbranchsites.Shifts_to_Radianthus.dat) containing information to simulate sequences with evolver. The two .dat files were used to simulate sequences under different selection scenarios (no positive selection, convergent positive selection, positive selection on "long" or "clade" branches only) during the shifts to Entacmaeae or Radianthus hosts. The files were used with the scripts Create_DATFile_Evolved.Shift_to_Entacmaea.py and Create_DATFile_Evolved.Shift_to_Radianthus.py to generate .dat files for all the conditions, used then in evolver. For more information on the methods, please refer to the publication. </p> <p>data/DatFiles.Evolver.tar.gz<br> The .dat files that were obtained for the different omega and evolutionary scenarios, for shifts to Entacmaea and Radianthus hosts. The files are obtained with the template files (Example.DatFile.evolver.tar.gz) and the scripts Create_DATFile_Evolved.Shift_to_Entacmaea.py and Create_DATFile_Evolved.Shift_to_Radianthus.py. The resulting .dat files are run in evolver:</p> <p> evolverNSbranchsites 6 DAT_FILES.dat </p> <p> to obtain the codon alignment files to perform power and false positive rate analyses. For more information, please refer to the publication. </p> <p>data/Alignments_ProteinCodingGenes.tar.gz: <br> Contains the alignments of the 18,390 protein-coding genes analysed in the study. The gene IDs correspond to the ID of the Amphiprion frenatus reference genome (Marcionetti et al., 2018; https://datadryad.org/stash/dataset/doi:10.5061/dryad.nv1sv). The position of the gene on the Amphiprion percula chromosomes is also reported. For information on the methods and sample names, please refer to the publication. These alignments were used to test for convergent positive selection occurring during host shifts. </p> <p>data/Example.ControlFiles.CodeML.tar.gz<br> It contains examples of the control files for the null model (no positive selection, H0), alternative model (positive selection, H1), and the site model M1a (used to verify the correct optimization of the null model). The final control files for each gene and condition (shift to Entacmaea or Readianthus host) were generated with the script Create_CTLFile_CodeML.py. </p> <p>data/LabelledTree.CodeML.tar.gz<br> Tree files used in codeml analyses, with shifts to Entacmaea labelled as foreground branches (ClownTree.Rooted.Label_Entacmaea.nwk, ClownTree.Rooted.Label_Entacmaea.NoLongBranches.nwk) and shifts to Radianthus labelled as foreground branches (ClownTree.Rooted.Label_Radianthus.nwk, ClownTree.Rooted.Label_Radianthus.NoLongBranches.nwk). The trees do or do not have the 3 "long branches" species (A. ocellaris, A. percula, P. biaculeatus). For more information, refer to the publication. An additional folder (Additional_labelled_trees_for_test_on_simulated_data.tar.gz) containg the trees with only specific species kept and labelled. These trees were used for codeml analyses on simulated alignments, to investigate false positives and power of the analyses. For more information, refer to the publication. </p> <p>data/SimulatedData_BranchSite_Results.tar.gz<br> It contains the results for the branch site model on the simulated data. Each file name reports the simulated scenario (Simulated without positive selection: Simulated_NO_PS_Entacmaea / Simulated_NO_PS_Radianthus; simulated convergent positive selection: Simulated_PS_Entacmaea / Simulated_PS_Radianthus; Simulated positive selection on long branches : Simulated_PS_LongBranches / Simulated_PS_Premnas; Simulated positive selection on "clade" branches: Simulated_PS_AKA / Simulated_PS_Ephi), as well as the tested scenario (Tested for positive selection: Tested_PS_Entacmaea / Tested_PS_Radianthus; or tested for positive selection on specific branches). Each file contains the information on the name of the original file, the simulated scenario, the tested scenario, the simulated omega, the replicate number, the log-likelihood of the tested model (site model: M1a, null model without positive selection: H0, alternative model with positive selection: H1), and the p-values associated to the likelihood-ratio test (LRT_pvalue). For more information, refer to the publication. </p> <p>data/EmpiricalData_BranchSite_Results.tar.gz<br> It contains the results for the branch site model for the 18,390 protein-coding genes tested in the study, for shifts to Entacmaea (Results.BranchSiteModel.Shifts_To_Entacmaea.txt, Results.BranchSiteModel.Shifts_To_Entacmaea.NoLongBranches.txt) and shifts to Radianthus hosts (Results.BranchSiteModel.Shifts_To_Radianthus.txt, Results.BranchSiteModel.Shifts_To_Radianthus.NoLongBranches.txt). Each file contains information on the chromosome information of the analyzed gene, the name of the gene, the log-likelihood of the M1a model (site model, used to verify the correct optimization of the null model), the log-likelihood of the null model (H0) and the alternative model (H1), and the p-values associated to the likelihood-ratio test (LRT_pvalue). These p-values were subsequentially corrected for multiple testing. For more information, refer to the publication. </p> <p>data/ASR_adult_host_4st.rds<br> It contains the results of reproductive host associations ancestral states reconstruction to the form of a list() R object. In the list $joint returns a tree with joint ancestral states (returns the most likely ancestral reproductive host association at nodes), $marginal returns a tree with the likelihood of each state at nodes, $simmap returns 100 stochastic maps of ancestral states along branches of the tree calculated over the marginal reconstruction, $map returns a map of ancestral states along branches estimated from the joint reconstruction.</p> <p>data/Absolute_host_assoc.tar.gz<br> It contains description of the sources used for characterizing host associations for each species of clownfish. For each species, we provide a list of pictures used from public citizen science databases with associated urls and additional published references if used. reprod_host.csv contains our final classification of reproductive host associations.</p> <p>data/DEC.tar.gz<br> It contains files used for the biogeographic reconstruction (areas_adjacency_clowns.txt, areas_clowns.txt, calibrated_tree.tre, distances.txt, geo_col.txt) and results of the biogeographic reconstruction. geo_obj.rds is a R object containing the joint reconstruction of ancestral biogeographic states formatted for being used in phylogenetic comparative methods analyses. list_geo_obj.rds is a list of a 100 similar objects generated from stochastic maps of ancestral biogeographic states.</p> <p>data/phenotype.tar.gz<br> It contains results of clownfish individuals phenotyping. Within each file, the first column is the name of the species identified from the picture. morph_pca.csv contains results of the pca analysis performed on the procrustes of clownfish individuals. morph_traits.csv contains traits values calculated from the prcrustes of clownfish individuals. colorRGB.csv contains results of the pca analysis performed on the concatenated red green and blue channels of each clownfish image. colorWOB.csv contains results of the pca analyses performed independantly on white, orange and black channels. columns with names ending with W represent pca axis generated from white channel (O: orange channel, B: black channel)</p> <p>scripts/Create_CTLFile_CodeML.py: <br> Script used to generate the codeml control files for codeml analyses (simulated data or empirical data). The scripts needs the path to the folder were the codon alignments (see Alignments_ProteinCodingGenes.tar.gz or Alignments created for simulations) are found, the path were the output file are gonna be written; the path to the alignment, tree file and output as they will be written in the control file; the output suffix. </p> <p> python Create_CTLFile_CodeML.py PATH/to/Alignments/ PATH/to/out/CTL_files/ alignment_in_ctlFile tree_in_ctlFile path_to_output_in_ctlFile Output_Suffix</p> <p> This produces the control files of the null model (H0, no positive selection) and alternative model (H1, positive selection), that can be run with codeml</p> <p> codeml CONTROL_FILE.ctl </p> <p> to obtain the results. This was done using the tree with shifts to Ratianthus or Entacmaea as foreground branches (see LabelledTree.CodeML.tar.gz). This was also performed on real data or simulated data. For more information, refer to the publication. </p> <p><br>scripts/Create_DATFile_Evolved.Shift_to_Entacmaea.py<br>scripts/Create_DATFile_Evolved.Shift_to_Radianthus.py<br> Scripts used to generate the .dat files for evolver simulations. The scripts need the template .dat files (provided in Example.DatFile.evolver.tar.gz) and the information of the path where to save the resulting .dat files:</p> <p> python Create_DATFile_Evolved.Shift_to_Entacmaea.py MCcodonNSbranchsites.Shifts_to_Entacmaea.dat Out_dat_files_Entacmaeae/</p> <p> python Create_DATFile_Evolved.Shift_to_Radianthus.py MCcodonNSbranchsites.Shifts_to_Radianthus.dat Out_dat_files_Radianthus/</p> <p> The .dat files obtained are then run in evolver to generate the simulated alignments:</p> <p> evolverNSbranchsites 6 DAT_FILES.dat </p> <p> The simulated alignments and tree were then used in codeml to evaluate power and false positive rate of positive selection analyes. The file Create_CTLFile_CodeML.py was used to create control files and control files were run with codeml. For more information, refer to the publication. </p> <p>scripts/ASR_adult_host.R<br> Script used to perform the ancestral state reconstruction of reproductive host assocication. It uses data/Absolute_host_assoc/reprod_host.csv and data/BEAST2.DatedTree.WithOutgroup.tree and outputs the data/ASR_adult_host_4st.rds file. It requires the instalation of a few R packages ("ape", "igraph", "mvMORPH", "scales", "sda", "TeachingDemos","png", "corHMM","phytools") that can be installed with the function (install.packages("package-name"))</p> <p> Rscript scripts/ASR_adult_host.R</p> <p>scipts/BGB_fit.R<br> Script used to perform the ancestral state reconstruction of biogeographic region. It uses data embeded into data/DEC.tar.gz and outputs data/geo_obj.rds and data/list_geo_obs.rds. It requires the instalation of a few R packages ("ape","BioGeoBEARS", "GenSA", "FD", "snow", "parallel","cladoRcpp","rexpokit") that can be installed with the function (install.packages("package-name")).</p> <p> Rscript scripts/BGB_fit.R</p> <p>scripts/PCM_fit.R<br> Script used to perform the phylogenetic comparative analyses. It uses data embeded into the data folder. First part performs multivariate phylogenetic anova. Second part performs model testing and parameter estimations using multivariate and univariate datasets and ancestral state reconstruction joint maps. Third part performs model testing and parameter estimations using multivariate and univariate datasets and 100 stochastic maps from marginal ancestral state reconstructions. Results are saved into .rds files. It requires the instalation of a few R packages ("ape", "phytools", "mvMORPH", "RPANDA", "geiger","OUwie") that can be installed with the function (install.packages("package-name")).</p> <p> Rscript scripts/PCM_fit.R</p> <p>scripts/manova_var.R<br> Script used to estimate uncertainties on the mANOVA that are due to intraspecific variation. It uses data embeded into the data folder. Results are saved into .rds files. It requires the instalation of a few R packages ("ape", "phytools", "mvMORPH", "RPANDA", "geiger","OUwie") that can be installed with the function (install.packages("package-name")).</p> <p> Rscript scripts/manova_var.R</p> <p> </p> <p> </p> <p> </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.