Find research datasets worth reusing

opencc-by-4.0Dec 2017View details →

Alterations in Patterns of Gene Expression and Perturbed Pathways Associated With Chemotherapy-Induced Nausea

This dataset contains the supplementary materials describing in detail the methods and the results of the analyses. The manuscript has been submitted for publication. Please cite both the paper as well as the DOI of this dataset if you make use of the data.

Fig. 3 in Effects of latitude, host body size, and host trophic guild on patterns of diversity of helminths associated with humans, wild and domestic mammals of Mexico

Fig. 3. Phylogenetic generalized least squares (PGLS) regression of host body mass (values were log-transformed) with richness of helminths associated to wildlife hosts (values were corrected for sampling effort).

Fig. 2 in Effects of latitude, host body size, and host trophic guild on patterns of diversity of helminths associated with humans, wild and domestic mammals of Mexico

Fig. 2. Relationships between latitude and the average taxonomic distinctness of overall helminths (A) and nematodes (B).

Fig. 4 in Effects of latitude, host body size, and host trophic guild on patterns of diversity of helminths associated with humans, wild and domestic mammals of Mexico

Fig. 4. Parasite richness and average taxonomic distinctness by host trophic guild (the size of circle represents the number of hosts belonging to each trophic guild).

Fig. 1 in Effects of latitude, host body size, and host trophic guild on patterns of diversity of helminths associated with humans, wild and domestic mammals of Mexico

Fig. 1. Maps showing the geographic locations of the records, classified by phylum of the subsetted database.

opencc-by-4.0Nov 2022View details →

Balancing selection at a wing pattern locus is associated with major shifts in genome-wide patterns of diversity and gene flow

Selection shapes genetic diversity around target mutations, yet little is known about how selection on specific loci affects the genetic trajectories of populations, including their genome-wide patterns of diversity and demographic responses. Here we study the patterns of genetic variation and geographic structure in a neotropical butterfly, Heliconius numata, and its closely related allies in the so-called melpomene-silvaniform clade. H. numata is known to have evolved an inversion supergene which controls variation in wing patterns involved in mimicry associations with distinct groups of co-mimics. Butterflies show disassortative mate preferences and heterozygote advantage at this locus. We contrasted patterns of genetic diversity and structure 1) among extant polymorphic and monomorphic populations of H. numata, 2) between H. numata and its close relatives, and 3) between ancestral lineages. We show that H. numata populations which carry the inversions as a balanced polymorphism show markedly distinct patterns of diversity compared to all other taxa. They show the highest genetic diversity and effective population size estimates in the entire clade, as well as a low level of geographic structure and isolation by distance across the entire Amazon basin. By contrast, monomorphic populations of H. numata as well as its sister species and their ancestral lineages all show lower effective population sizes and genetic diversity, and higher levels of geographical structure across the continent. One hypothesis is that the large effective population size of polymorphic populations could be caused by the shift to a regime of balancing selection due to the genetic load and disassortative preferences associated with inversions. Testing this hypothesis with forward simulations supported the observation of increased diversity in populations with the supergene. Our results are consistent with the hypothesis that the formation of a supergene triggered a change in gene flow, causing a general increase in genetic diversity and the homogenisation of genomes at the continental scale.

opencc-by-4.0Feb 2023View details →

Irrigation water source matters: Saline groundwater irrigation lowers date palm root-associated fungal richness and alters their community patterns

Saline groundwater irrigation is predominantly used for date palm (Phoenix dactylifera) cultivation in the arid regions of the Middle East and North Africa without knowing its impact on root-associated fungal (RAF) communities. We investigated the impact of irrigation water sources (freshwater vs. saline groundwater) on date palm RAF diversity, communities, and their assembly processes. Summarily, we show that water chemistry (pH and EC) mainly structures RAF communities, whereas water pH shapes saprotrophic and pathotrophic communities, and the higher abundance of saprotrophic RAF (i.e. Acrocalymma vagum) under saline groundwater irrigation, despite the higher importance of the drift process, indicates their potential role in nutrient cycling and plant growth promotion under saline conditions in arid agroecosystems.

opencc-by-4.0Feb 2023View details →

Deep Representation Learning of Physical Activity and Sleep Patterns During Pregnancy Identifies post-hoc Inferences Associated with Prematurity

Running title: series2signal gestational age "clock" for pregnancy monitoring Summary:  Preterm birth (PTB) is the leading cause of infant mortality globally. While research has focused on the development of predictive models for PTB, cost-effective interventions have remained understudied. Physical activity and sleep present unique opportunities for interventions in low- and middle-income populations. However, objective measurement of physical activity and sleep remains challenging and self-reported metrics suffer from low-resolution and accuracy that decays over time. In this study, we use physical activity data collected using a wearable device comprising over 181, 944 hours of data across N = 1, 083 patients. Using a new state-of-the art deep learning time-series classification architecture, we first develop a ”clock” of healthy dynamics in physical activity patterns during pregnancy by using gestational age (GA) as a surrogate for progression of pregnancy. We also developed a novel interpretability algorithm that integrates unsupervised clustering, model error analysis, feature attribution, and automated actigraphy analysis, allowing for model interpretation with respect to sleep, activity, and static clinical variables. Our model performs significantly better than 7 other machine learning and AI methods for modeling the progression of pregnancy based on measures of physical activity and sleep. Importantly, we found that deviations from this normal ”clock” of physical activity and sleep changes during pregnancy are strongly associated with pregnancy outcomes. When our model underestimates GA, there are 0.52 fewer preterm births than expected (P = 1.01e − 67) and when our model overestimates GA, there are 1.44 times (P = 2.82e − 39) more preterm births than expected. Model error is negatively correlated with interdaily stability (P = 0.043), indicating that our model assigns a more advanced GA when an individual’s daily rhythms are less precise. Supporting this, our model attributes higher importance to sleep periods in predicting higher-than-actual GA, relative to lower-than-actual GA (P = 1.01e − 21). Combining prediction with interpretability allows us to robustly signal when activity behaviors increase or decrease the likelihood of preterm birth and advocates for the future development of clinical decision support through passive monitoring and suggestions around exercise habits and sleep patterns, which are easily implemented in low- and middle-income countries (LMICs). Beyond this particular application, the presented pipeline can be used to analyze high-fidelity time-series data in other translational studies utilizing wearable devices.   Data description (brief): the raw wearables data is available as .mtn files with the GA encoded in the filename after the underscore. The processed data with sleep annotations can be loaded using the pickle module for serialized objects in python. See https://github.com/nealgravindra/wearables for examples.

opencc-by-4.0Jun 2023View details →

Associated Dataset for Genome-wide DNA methylation patterns in bumble bee (Bombus vosnesenskii) populations from spatial-environmental range extremes

The dataset contains the final methylation call set (n=14,627,533), variant calling file for population genomics analyses, analysis codes/scripts, and other associated files related to the research (Constitutive and variable patterns of genome-wide DNA methylation in populations from spatial-environmental range extremes of the bumble bee Bombus vosnesenskii). Raw WGBS reads generated in this study have been deposited and are currently available at the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) under NCBI BioProject PRJNA956115.

dryad40/100

Homophily in social and demographic traits predict association patterns in female western and mountain gorillas

Open the record for dataset details and reuse information.

publicOct 2024View details →

dryad40/100

Biogeographic patterns of community diversity associated with an introduced alga

Open the record for dataset details and reuse information.

publicOct 2024View details →

opencc-zeroNov 2020View details →

A codon model for associating phenotypic traits with altered selective patterns of sequence evolution

Detecting the signature of selection in coding sequences and associating it with shifts in phenotypic states can unveil genes underlying complex traits. Of the various signatures of selection exhibited at the molecular level, changes in the pattern of selection at protein coding genes have been of main interest. To this end, phylogenetic branch-site codon models are routinely applied to detect changes in selective patterns along specific branches of the phylogeny. Many of these methods rely on a pre-specified partition of the phylogeny to branch categories, thus treating the course of trait evolution as fully resolved and assuming that phenotypic transitions have occurred only at speciation events. Here we present TraitRELAX, a new phylogenetic model that alleviates these strong assumptions by explicitly accounting for the uncertainty in the evolution of both trait and coding sequences. This joint statistical framework enables the detection of changes in selection intensity upon repeated trait transitions. We evaluated the performance of TraitRELAX using simulations and then applied it to two case studies. Using TraitRELAX, we found an intensification of selection in the primate SEMG2 gene in polygynandrous species compared to species of other mating forms, as well as changes in the intensity of purifying selection operating on sixteen bacterial genes upon transitioning from a free-living to an endosymbiotic lifestyle.

opencc-zeroMar 2020View details →

Data from: Contrasting patterns of functional diversity in coffee root fungal communities associated with organic and conventionally-managed fields

The structure and function of fungal communities in the coffee rhizosphere is shaped by crop environment. Because coffee can be grown along a management continuum from conventional application of pesticides and fertilizers in full sun to organic management in a shaded understory, we used coffee fields to hold host constant while comparing rhizosphere fungal communities in markedly different environmental conditions with regard to shade and inputs. We characterized the shade and soil environment in 25 fields under conventional, organic or transitional management in two regions of Costa Rica. We amplified the ITS2 region of fungal DNA from coffee roots in these fields and characterized the rhizosphere fungal community via high-throughput sequencing. Sequences were assigned to guilds to determine differences in functional diversity and trophic structure among coffee field environments. Organic fields had more shade, a greater richness of shade tree species, more leaf litter, and were less acidic, with lower soil nitrate availability and higher soil copper, calcium, and magnesium than conventionally-managed fields, although differences between organic and conventionally-managed fields in shade, calcium and magnesium depended on region. Differences in richness and community composition of rhizosphere fungi between organic and conventionally-managed fields were also correlated with shade, soil acidity, nitrate, and copper. Trophic structure differed with coffee field management. Saprotrophs, plant pathogens, and mycoparasites were more diverse and plant pathogens were more abundant in organic than in conventionally-managed fields, while saprotroph-plant pathogens were more abundant in conventionally-managed fields. These differences reflected environmental differences and depended on region. IMPORTANCE Rhizosphere fungi play key roles in ecosystems, as nutrient cyclers, pathogens, and mutualists, yet little is currently known about which environmental factors and how agricultural management shape rhizosphere fungal communities and their functional diversity. This field study of the coffee agroecosystem suggests that organic management not only fosters a greater overall diversity of fungi, but also maintains a greater richness of saprotrophic, plant pathogenic and mycoparasitic fungi that has implications for efficiency of nutrient cycling and regulation of plant pathogen populations in agricultural systems. As well as influencing community composition and richness of rhizosphere fungi, shade management and use of fungicides and synthetic fertilizers altered the trophic structure of the coffee agroecosystem.

opencc-zeroDec 2017View details →

Data from: Variation in nest characteristics and brooding patterns of female Black-throated Blue Warblers is associated with thermal cues

Thermal variation poses a problem for nesting birds and can result in reduced offspring growth rates and survival. To increase the thermal stability of the nest, females can adjust nest characteristics and nest attendance in response to changes in environmental conditions. However, it is unclear how and to what extent females modify parental behaviors during various stages of offspring development. We tested the hypothesis that females adjust nest characteristics and brooding patterns in response to thermal variation during the nest-building and nestling stages, respectively. We examined elevational variation in nest location, nest construction, and brooding patterns in the migratory Black-throated Blue Warbler (Setophaga caerulescens) across a 28C gradient at the Hubbard Brook Experimental Forest, New Hampshire, USA. Density of woody stems at nest sites and nest wall thickness increased from low to high elevation, corresponding to decreasing temperatures, but we found no relationship between weather during nest building and nest characteristics. However, weather during the nestling stage was associated with female brooding patterns: at lower temperatures and with higher rainfall, females spent more time off the nest, which was associated with lower nestling mass near fledging. These results suggest that thermal cues during nest building may be unreliable as predictors of future conditions for developing nestlings and also that females might favor their own self-maintenance and compromise nestling growth under adverse thermal conditions.

opencc-zeroDec 2016View details →

Data from: Patterns of divergence across the geographic and genomic landscape of a butterfly hybrid zone associated with a climatic gradient

Hybrid zones are a valuable tool for studying the process of speciation and for identifying the genomic regions undergoing divergence and the ecological (extrinsic) and non-ecological (intrinsic) factors involved. Here, we explored the genomic and geographic landscape of divergence in a hybrid zone between Papilio glaucus and Papilio canadensis. Using a genome scan of 28,417 ddRAD SNPs, we identified genomic regions under possible selection and examined their distribution in the context of previously identified candidate genes for ecological adaptations. We showed that differentiation was genome-wide, including multiple candidate genes for ecological adaptations, particularly those involved in seasonal adaptation and host plant detoxification. The Z-chromosome and four autosomes showed a disproportionate amount of differentiation, suggesting genes on these chromosomes play a potential role in reproductive isolation. Cline analyses of significantly differentiated genomic SNPs, and of species diagnostic genetic markers, showed a high degree of geographic coincidence (81%) and concordance (80%) and were associated with the geographic distribution of a climate-mediated developmental threshold (length of the growing season). A relatively large proportion (1.3%) of the outliers for divergent selection were not associated with candidate genes for ecological adaptations and may reflect the presence of previously unrecognized intrinsic barriers between these species. These results suggest that exogenous (climate-mediated) and endogenous (unknown) clines may have become coupled and act together to reinforce reproductive isolation. This approach of assessing divergence across both the genomic and geographic landscape can provide insight about the interplay between the genetic architecture of reproductive isolation and endogenous and exogenous selection.