Find research datasets worth reusing

single-cell RNAseq data (data set 14) in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data

The present dataset (dataset14) was used as input to build scFASTCORMICS models. The files correspond to the clusters identified by Seurat in the single-cell data from pancreas donor12 downloaded from the GEO website  (GSE114297).    see the protocol: scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data and github: <a href="https://github.com/sysbiolux/scFASTCORMICS">https://github.com/sysbiolux/scFASTCORMICS</a> For more information, version updates of the scFASTCORMICS.

single-cell RNAseq data (data set 9) in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data

The present dataset (dataset9) was used as input to build scFASTCORMICS models. The files correspond to the clusters identified by Seurat in the single-cell data from pancreas donor7 downloaded from the GEO website  (GSE114297).    see the protocol: scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data and github: <a href="https://github.com/sysbiolux/scFASTCORMICS">https://github.com/sysbiolux/scFASTCORMICS</a> For more information, version updates of the scFASTCORMICS.

single-cell RNAseq data (data set 8) in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data

The present dataset (dataset8) was used as input to build scFASTCORMICS models. The files correspond to the clusters identified by Seurat in the single-cell data from pancreas donor6 downloaded from the GEO website  (GSE114297).    see the protocol: scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data and github: <a href="https://github.com/sysbiolux/scFASTCORMICS">https://github.com/sysbiolux/scFASTCORMICS</a> For more information, version updates of the scFASTCORMICS.

single-cell RNAseq data (data set 7) in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data

The present dataset (dataset7) was used as input to build scFASTCORMICS models. The files correspond to the clusters identified by Seurat in the single-cell data from pancreas donor5 downloaded from the GEO website  (GSE114297).    see the protocol: scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data and github: <a href="https://github.com/sysbiolux/scFASTCORMICS">https://github.com/sysbiolux/scFASTCORMICS</a> For more information, version updates of the scFASTCORMICS.

single-cell RNAseq data (data set 19) in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data

The present dataset (dataset19) was used as input to build scFASTCORMICS models. The files correspond to the clusters identified by Seurat in the single-cell data from Liver cancer set 2 samples downloaded from the GEO website (GSE125449).    see the protocol: scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data and github: <a href="https://github.com/sysbiolux/scFASTCORMICS">https://github.com/sysbiolux/scFASTCORMICS</a> For more information, version updates of the scFASTCORMICS.

Discretized bulk data by the discretization step of rFASTCORMICS used in in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data

Bulk data RNAseq data were downloaded from GEO, GTEX, and other sources (see below) and discretized by the discretization step of rFASTCORMICS (Pacheco et al, 2019) used in the optimization step in scFASTCORMICS: CRC bulk RNAseq data were obtained from Lee et al(2020)  CRC control (NM) was downloaded from GSE81861  (GTEX, Healthy colon from) Pancreatic  Human islet bulk RNAseq data was downloaded from EBI Expression Atlas (Pancreatic islet cells) Immune cells in pancreatic carcinoma bulk data were obtained from GEO (GSE156278) liver and breast cancer bulk RNAseq data were obtained from the TCGA (GSE62944)   rFASTCORMICS and tutorial on rFASTCORMICS can be found: https://github.com/sysbiolux

single-cell RNAseq data (data set 5) in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data

The present dataset (dataset5) was used as input to build scFASTCORMICS models. The files correspond to the clusters identified by Seurat in the single-cell data from pancreas donor3 downloaded from the GEO website (GSE114297).  see the protocol: scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data and github: https://github.com/sysbiolux/scFASTCORMICS For more information, version updates of the scFASTCORMICS.

single-cell RNAseq data (data set 15) in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data

The present dataset (dataset15) was used as input to build scFASTCORMICS models. The files correspond to the clusters identified by Seurat in the single-cell data from CD8 T-cells in PACA samples downloaded from the GEO website (GSE156728).  see the protocol: scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data and github: https://github.com/sysbiolux/scFASTCORMICS For more information, version updates of the scFASTCORMICS.

single-cell RNAseq data (data set 4) in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data

The present dataset (dataset4) was used as input to build scFASTCORMICS models. The files correspond to the clusters identified by Seurat in the single-cell data from pancreas donor2 downloaded from the GEO website  (GSE114297).    see the protocol: scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data and github: https://github.com/sysbiolux/scFASTCORMICS For more information, version updates of the scFASTCORMICS.

single-cell RNAseq data (data set 3) in the publication scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data

The present dataset (dataset3) was used as input to build scFASTCORMICS models. The files correspond to the clusters identified by Seurat in the single-cell data from normal Pancreas donor1 downloaded from the GEO website (GSE114297).  see the protocol: scFASTCORMICS: A contextualization algorithm to reconstruct metabolic multi-cell population models from single-cell RNAseq data and github: https://github.com/sysbiolux/scFASTCORMICS For more information, version updates of the scFASTCORMICS.  <pre>  </pre>

opencc-zeroNov 2022View details →

Eastern-flowering Dogwood population genetics and ecological/environmental data

Forest fragmentation and introduced pathogens are negatively impacting trees and forests globally, including the Carolinian forest of southern Ontario, Canada. Multiple species-at-risk live in this threatened but biodiverse forest, including the endangered Cornus florida (Eastern flowering dogwood), which is now limited to fragmented woodlots, and has been decimated by the introduced fungal pathogen Discula destructiva (dogwood anthracnose). Ongoing management of C. florida in Canada is challenged by multiple knowledge gaps, two of which we aimed to address in this study. We first evaluated the association between anthracnose disease prevalence and a suite of ecological and environmental variables across 21 sites. Across our sites, larger trees tended to have the highest disease incidence, and trees on shallow slopes had the most crown dieback. We then quantified genetic diversity and gene flow and found that genetic structure has not been substantially impacted by habitat fragmentation, although dispersal typically covers short distances. However, genetic diversity is relatively low in smaller populations, and in younger trees. Localized dispersal and eroding genetic diversity may limit future adaptation and hence exacerbate population declines. We recommend that managers prioritize plantings in small populations, avoid shallow slopes, and track younger trees to evaluate age-related mortality.

Data for: Temperature effects on growth rates of Daphnia from different populations

When comparing somatic growth thermal performance curves (TPCs), higher somatic growth across experimental temperatures is often observed for populations originating from colder environments. Such countergradient variation has been suggested to represent adaptation to seasonality, or shorter favorable seasons in colder climates. Alternatively, populations from cold climates may outgrow those from warmer climates at low temperature, and vice versa at high temperature, representing adaptation to temperature. Using modelling, we show that distinguishing between these two types of adaptation based on TPCs requires knowledge about (i) the relationship between somatic growth rate and population growth rate, which in turn depends on the scale of somatic growth (absolute or proportional), and (ii) the relationship between somatic growth rate and mortality rate in the wild. We illustrate this by quantifying somatic growth rate TPCs for three populations of Daphnia magna where population growth scales linearly with proportional somatic growth. For absolute somatic growth, the northern population outperformed the two more southern populations across temperatures, and more so at higher temperatures, consistent with adaptation to seasonality. In contrast, for the proportional somatic growth TPCs, and hence population growth rate, TPCs tended to converge towards the highest temperatures. Thus, if the northern population pays an ecological mortality cost of rapid growth in the wild, this may create crossing population growth TPCs consistent with adaptation to temperature. Future studies within this field should be more explicit in how they extrapolate from somatic growth in the lab to fitness in the wild.

Data from: Top-down control of a marine mesopredator: Increase in native white-tailed eagles accelerates the extinction of an endangered seabird population

1. Bottom-up control is an important regulator of marine mesopredators such as seabirds. The prevalence of top-down control on these species is however less well understood. In particular, how native predators affect seabird populations has rarely been quantified. 2. Here, we investigate how an increase in white-tailed eagles in northern Norway, a stronghold for the species, affected a local population of 25,000 pairs of black-legged kittiwakes, a red-listed seabird, during a 42-year period ending with colony extinction. We use a natural experiment of two neighbouring colonies with/without eagle predation to disentangle the effects of eagles from local kittiwake foraging conditions (using size of young herring as a proxy). 3. At the colony where eagle predation occurred, and in contrast to the eagle-free colony, kittiwake breeding success and population size declined with increased eagle abundance, the latter more strongly under poor foraging conditions. Breeding success increased with foraging conditions at both colonies. 4. Simple population modelling shows that although conditions were insufficient to sustain the eagle-exposed colony, the increased abundance of eagles sped up its extirpation by many years. 5. Policy implications. Our study shows that top-down effects from avian predators can be significant regulators of seabird populations, challenging their conservation where native, often protected, predators are rising. Such effects, and their possible interaction with other factors, must also be accounted for when using seabird demographic traits as environmental indicators and when developing more flexible and effective management and action plans.

Data for: The central Alps comprise a major dispersal barrier between western and eastern populations of two butterfly species

Aim: Environmental and species-specific factors shape spatial patterns in genetic diversity and population structure. Comparing different species within the same area helps to disentangle more general from species-specific factors affecting such geographic patterns. Here, we examined genetic diversity and population structuring through geographic features in two alpine butterfly species. Location: European Alps. Taxon: Copper butterflies (Lycaena spp.). Methods: We sampled 21 Lycaena hippothoe and 14 L. virgaureae populations with 18 individuals per population. We analysed the genetic diversity and structure<a> </a>of these populations by using 14 and nine microsatellite markers for L. hippothoe and L. virgaureae , respectively. Results: We found higher number of alleles, allelic richness, observed heterozygosity, FST values and more genetic clusters in L. hippothoe than in L. virgaureae. Both species displayed a major genetic barrier in the central Alps. Western and eastern L. hippothoe populations but central L. virgaureae populations showed the highest genetic diversity. Main Conclusions: The population genetic structures of both Copper butterflies seemed to be strongly affected by population history and demography. Patterns indicate for both species a western and an eastern glacial refuge. The high genetic diversity and pronounced population structure found in L. hippothoe seems to be related to a low dispersal ability and closed populations with high local abundances as opposed to L. virgaureae. The higher dispersal of the latter likely caused hybridisation in the central alpine contact zone boosting genetic diversity, which was not the case in L. hippothoe. These findings suggest that different conservation strategies are needed for these closely related species.

opencc-by-4.0Dec 2022View details →

Animal population data complementing the European Union One Health 2021 Zoonoses Report

This dataset includes animal population aggregated data under the framework of Directive 2003/99/EC.

Data and MATLAB files for: Timescale analyses of fluctuations in coexisting populations of a native and invasive tree squirrel

1. Competition from invasive species is an increasing threat to biodiversity. In Southern California, the western gray squirrel (Sciurus griseus, WGS) is facing increasing competition from the fox squirrel (Sciurus niger, FS), an invasive congener. 2. We used spectral methods to analyze 140 consecutive monthly censuses of WGS and FS within a 11.3 ha section of the California Botanic Garden. Variation in the numbers for both species and their synchrony was distributed across long timescales (> 15 months). 3. After filtering out annual changes, concurrent mean monthly temperatures from nearby Ontario Airport (ONT) yielded a spectrum with a large semiannual peak and significant spectral power at long timescales (> 30 months). Squirrel-temperature cospectra showed significant negative covariation at long timescales (> 35 months) for WGS and smaller significant negative peaks at 6 months for both species. 4. Simulations from a Lotka-Volterra model of two competing species indicates that the risk of extinction for the weaker competitor increases quickly as environmental noise shifts from short to long timescales. 5. We analyzed the timescales of fluctuations in detrended mean annual temperatures for the time period 1915-2014 from 1218 locations across the continental USA. In the last two decades, significant shifts from short timescales to long timescales have occurred, changing from less than 3 years to 4-6 years. 6. Our results indicate that (i) population fluctuations in co-occurring native and invasive tree squirrels are synchronous, occur over long timescales, and may be driven by fluctuations in environmental conditions; (ii) long timescale population fluctuations increase the risk of extinction in competing species, especially for the inferior competitor; and (iii) the timescales of interannual environmental fluctuations may be increasing from recent historical values. These results have broad implications for the impact of climate change on the maintenance of biodiversity.

Flow cytometry YFP and CFP data and deep sequencing data of populations evolving in galactose

Copy-number and point mutations form the basis for most evolutionary novelty through the process of gene duplication and divergence. While a plethora of genomic sequence data reveals the long-term fate of diverging coding sequences and their cis-regulatory elements, little is known about the early dynamics around the duplication event itself. In microorganisms, selection for increased gene expression often drives the expansion of gene copy-number mutations, which serves as a crude adaptation, prior to divergence through refining point mutations. Using a simple synthetic genetic system that allows us to distinguish copy-number and point mutations, we study their early and transient adaptive dynamics in real-time in Escherichia coli. We find two qualitatively different routes of adaptation depending on the level of functional improvement selected for: In conditions of high gene expression demand, the two types of mutations occur as a combination. Under low gene expression demand, negative epistasis between the two types of mutations renders them mutually exclusive. Thus, owing to their higher frequency, adaptation is dominated by copy-number mutations. Ultimately, due to high rates of reversal and pleiotropic cost, copy-number mutations may not only serve as a crude and transient adaptation but also <a>constrain</a> sequence divergence over evolutionary time scales.

opencc-zeroJan 2023View details →

Data for: Species identification and population genetics of the Antarctic fish genera Lepidonotothen and Nototheniops (Perciformes, Notothenioidei)

Accurate species identification is essential to assess biodiversity and species richness in ecosystems threatened by rapid and recent environmental changes, such as warming in most Antarctic waters. The Lepidonotothen species complex comprises demersal notothenioid fishes which inhabit the shelf areas of the Antarctic Peninsula, the Scotia Arc and sub-Antarctic islands with a circum-Antarctic distribution. Species determination in this group has often been problematic. In particular, whether Lepidonotothen squamifrons and Lepidonotothen kempi are valid as separate species has been questioned. In this study, we analysed the genetic variation among four nominal southern polar species within this complex (L. kempi, L. squamifrons, Nototheniops larseni, Nototheniops nudifrons) by means of three different markers (ND2 and tRNA mitochondrial genes and a panel of 16 nuclear microsatellites). We tested whether individuals morphologically assigned to L. kempi showed genetic separation from L. squamifrons. Our analyses indicated a lack of differentiation between L. kempi and L. squamifrons. However, a genetically distinct population was found for L. squamifrons at the Shag Rocks islands near South Georgia. Antarctic and sub-Antarctic islands are known to be home to many cryptic species and further studies will elucidate if the genetically differentiated population we found potentially originated from this context and can be considered as an incipient species. Our analysis contributes to further characterize the species composition of the most abundant fish suborder in the Southern Ocean, which is amongst the regions most threatened by climate change.

opencc-zeroJan 2023View details →

Data from: Population connectivity patterns of genetic diversity, immune responses and exposure to infectious pneumonia in a metapopulation of desert bighorn sheep

Habitat fragmentation is an important driver of biodiversity loss and can be remediated through management actions aimed at maintenance of natural connectivity in metapopulations. Connectivity may protect populations from infectious diseases by preserving immunogenetic diversity and disease resistance. However, connectivity could exacerbate the risk of infectious disease spread across vulnerable populations. We tracked the spread of a novel strain of Mycoplasma ovipneumoniae in a metapopulation of desert bighorn sheep (Ovis canadensis nelsoni) in the Mojave desert to investigate how variation in connectivity among populations influenced disease outcomes. M. ovipneumoniae was detected throughout the metapopulation, indicating that the relative isolation of many of these populations did not protect them from pathogen invasion. However, we show that connectivity among bighorn sheep populations was correlated with higher immunogenetic diversity, a protective immune response and lower disease prevalence. Variation in protective immunity predicted infection risk in individual bighorn sheep and was associated with heterozygosity at genetic loci linked to adaptive and innate immune signalling. Together, these findings may indicate that population connectivity maintains immunogenetic diversity in bighorn sheep populations in this system and has direct effects on immune responses in individual bighorn sheep and their susceptibility to infection by a deadly pathogen. Our study suggests that the genetic benefits of population connectivity could outweigh the risk of infectious disease spread and supports conservation management that maintains natural connectivity in metapopulations.