Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
29
datasets available to search
ShareScore release 0.9.0
Dataset results
29 results for “pesticide resistance”
Data from: Independently evolved and gene flow‐accelerated pesticide resistance in two‐spotted spider mites
<p>Pest species are often able to develop resistance to pesticides used to control them, depending on how rapidly resistance can emerge within a population or spread from another resistant population. We examined the evolution of bifenazate resistance in China in the two‐spotted spider mite (TSSM) <em>Tetranychus</em> <em>uticae</em> Koch (Acari: Tetranychidae), one of the most resistant arthropods, by using bioassays, detection of mutations in the target <em>cytb</em> gene, and population genetic structure analysis using microsatellite markers. Bioassays showed variable levels of resistance to bifenazate. The <em>cytb</em> mutation G126S, which confers medium resistance in TSSM to bifenazate, had previously been detected prior to the application of bifenazate and was now widespread, suggesting likely resistance evolution from standing genetic variation. G126S was detected in geographically distant populations across different genetic clusters, pointing to the independent origin of this mutation in different TSSM populations. A novel A269V mutation linked to a low‐level resistance was detected in two southern populations. Widespread resistance associated with a high frequency of the G126S allele was found in four populations from the Beijing area which were not genetically differentiated. In this case, a high level of gene flows likely accelerated the development of resistance within this local region, as well as into an outlying region distant from Beijing. These findings, therefore, suggest patterns consistent with both local evolution of pesticide resistance as well as an impact of migration, helping to inform resistance management strategies in TSSM.</p>
Figure 12 in Biological control of spider mites in North-Italian vineyards using pesticide resistant predatory mites
Figure 12 Seasonal abundance of predatory mites observed during 2010 (months are indicated in x-axis) on different treatments in Farm B.
Figure 11 Seasonal abundance ofEotetranychus. carpiniobserved during 2010 in Biological control of spider mites in North-Italian vineyards using pesticide resistant predatory mites
Figure 11 Seasonal abundance ofEotetranychus. carpiniobserved during 2010 (months are indicated in x-axis) on different treatments in Farm B.
Figure 7 Seasonal abundance ofKampimodromus aberransobserved during 2010 in Biological control of spider mites in North-Italian vineyards using pesticide resistant predatory mites
Figure 7 Seasonal abundance ofKampimodromus aberransobserved during 2010 (months are indicated in x-axis) on different treatments in vineyards of Farm A.
Figure 2 Seasonal abundance ofEotetranychus carpiniobserved during 2009 in Biological control of spider mites in North-Italian vineyards using pesticide resistant predatory mites
Figure 2 Seasonal abundance ofEotetranychus carpiniobserved during 2009 (months are indicated in x-axis) on different treatments in vineyards of Farm A.
Figure 8 Seasonal abundance ofTyphlodromus pyriobserved during 2009 in Biological control of spider mites in North-Italian vineyards using pesticide resistant predatory mites
Figure 8 Seasonal abundance ofTyphlodromus pyriobserved during 2009 (months are indicated in x-axis) on different treatments in vineyards of Farm A.
Figure 9 Seasonal abundance ofTyphlodromus pyriobserved during 2010 in Biological control of spider mites in North-Italian vineyards using pesticide resistant predatory mites
Figure 9 Seasonal abundance ofTyphlodromus pyriobserved during 2010 (months are indicated in x-axis) on different treatments in vineyards of Farm A.
Figure 4 Seasonal abundance ofAmblyseius andersoniobserved during 2009 in Biological control of spider mites in North-Italian vineyards using pesticide resistant predatory mites
Figure 4 Seasonal abundance ofAmblyseius andersoniobserved during 2009 (months are indicated in x-axis) on different treatments in vineyards of Farm A.
Figure 10 in Biological control of spider mites in North-Italian vineyards using pesticide resistant predatory mites
Figure 10 Canopy's feature parameters observed in different vineyards of Farm A. Different letters indicate significant differences at Tukey test (α = 0.05).
Figure 3 Seasonal abundance ofEotetranychus carpiniobserved during 2010 in Biological control of spider mites in North-Italian vineyards using pesticide resistant predatory mites
Figure 3 Seasonal abundance ofEotetranychus carpiniobserved during 2010 (months are indicated in x-axis) on different treatments in vineyards of Farm A.
Figure 6 Seasonal abundance ofKampimodromus aberransobserved during 2009 in Biological control of spider mites in North-Italian vineyards using pesticide resistant predatory mites
Figure 6 Seasonal abundance ofKampimodromus aberransobserved during 2009 (months are indicated in x-axis) on different treatments in vineyards of Farm A.
Figure 1 Seasonal abundance ofPanonychus ulmiobserved during 2009 in Biological control of spider mites in North-Italian vineyards using pesticide resistant predatory mites
Figure 1 Seasonal abundance ofPanonychus ulmiobserved during 2009 (months are indicated in x-axis) on different treatments in vineyards
Figure 5 Seasonal abundance ofAmblyseius andersoniobserved during 2010 in Biological control of spider mites in North-Italian vineyards using pesticide resistant predatory mites
Figure 5 Seasonal abundance ofAmblyseius andersoniobserved during 2010 (months are indicated in x-axis) on different treatments in vineyards of Farm A.
Dataset for: The redlegged earth mite draft genome provides new insights into pesticide resistance evolution and demography in its invasive Australian range
<p>Data and analyses for Thia et al. "The redlegged earth mite draft genome provides new insights into pesticide resistance evolution and demography in its invasive Australian range" submitted to <em>Journal of Evolutionary Biology</em>.</p> <p>This repository comprises data and scripts used to replicate the analyses in this paper.</p> <p>The goals of this study were to: (1) assemble a draft reference genome for <em>Halotydeus destructor</em>; (2) perform a comparative analysis of acetylcholinesterase genes among different agricultural arthropod pests; (3) characterise the population genetic patterns among Australian <em>H. destructor</em> populations; and (4) perform demographic modelling to understand the evolutionary relationships between eastern and western populations of <em>H. destructor</em> in Australia.</p>
Dataset for: Expanding risk predictions of pesticide resistance evolution in arthropod pests with a proxy for selection pressure
Open the record for dataset details and reuse information.
Data from: Independently evolved and gene flow‐accelerated pesticide resistance in two‐spotted spider mites
Open the record for dataset details and reuse information.
Dataset for: The redlegged earth mite draft genome provides new insights into pesticide resistance evolution and demography in its invasive Australian range
Open the record for dataset details and reuse information.
Data from: Chromosome-level genome of the melon thrips yields insights into evolution of a sap-sucking lifestyle and pesticide resistance
<p>Thrips are tiny insects from the order Thysanoptera (Hexapoda: Condylognatha), including many sap-sucking pests that are causing increasing damage to crops worldwide. In contrast to their closest relatives of Hemiptera (Hexapoda: Condylognatha) including numerous sap-sucking species, there are few genomic resources available for thrips. In this study, we assembled the first thrips genome at the chromosome level from the melon thrips, <i>Thrips palmi</i>, a notorious pest in agriculture, using PacBio long-read and Illumina short-read sequences. The assembled genome was 270.43 Mb in size with 4,120 contigs and a contig N50 of 426 kb. All contigs were assembled into 16 linkage groups assisted by the Hi-C technique. In total, 16,333 protein-coding genes were predicted, of which 88.13% were functionally annotated. Among sap-sucking insects, polyphagous species usually possess more detoxification genes than oligophagous species. The polyphagous thrips genomes characterized so far have relatively more detoxification genes in the GST and CCE families than polyphagous aphids, but they have fewer UGTs. HSP genes, especially from the Hsp70s group, have expanded in thrips compared to other hemipteran insects. These differences point to different genetic mechanisms associated with detoxification and stress responses in these two groups of sap-sucking insects. The expansion of these gene families may contribute to the rapid development of pesticide resistance in thrips, as supported by a transcriptome comparison of resistant and sensitive populations of <i>T. palmi</i>. The high-quality genome developed here provides an invaluable resource for understanding the ecology, genetics and evolution of thrips as well as their relatives more generally.</p>
Data from: The phyllosphere microbiome in Tsuga canadensis: Possible relationships with resistance to Adelges tsugae and effects of the pesticide dinotefuran
<p>Eastern hemlock (<em>Tsuga canadensis</em>) is an important forest tree species in North America. It currently faces threats from invasive insects; primarily hemlock woolly adelgid (HWA -<em> Adelges tsugae</em>)<em> </em>and elongate hemlock scale (EHS - <em>Fiorinia externa</em><em>). </em>Both insect species are native to Asia with Tsuga species in the native range typically resistant to the damage they cause. We conducted a study of the phyllosphere microbiome of two hemlock species native to North America and susceptible to HWA (<em>T. canadensis</em> and <em>T. caroliniana</em>), and two species native to Asia and resistant to HWA (<em>T. chinensis</em> and <em>T. diversifolia</em>). The files for this experiment are labelled "Hemlock Microbiome." Since pesticide application is often used to treat North American hemlock species impacted by HWA and EHS, we also examined how the pesticide dinotefuran affected the microbiome and overall plant physiology of <em>T. canadensis</em>. The files for this experiment are labelled "Hemlock Dinotefuran."</p> <p>Included here are zOTU tables for fungi and bacteria and the taxonomic matches for each zOTU from both experiments, as well as the codes used in the programs USEARCH and Cutadapt to generate these data tables. (Note that raw sequence reads are publicly available in the Sequence Read Archive under BioProject number PRJNA1052676.) In addition, R scripts that show 1) how these data were analyzed with PERMANOVA and PERMDISP and visualized with PCoA in the R package vegan, including sequence read normalization in the R package DESeq2, 2) how the relative abundance of the top taxa were graphed in the R package phyloseq, and 3) indicator species analysis in the R package indicspecies are included. Finally, the raw data for plant physiology measurements are also included, along with the R script on how these data were analyzed with ANOVAs.</p>
Simulation scripts and data for the stochastic modelling of evolutionary rescue in resistance to pesticides
<p>Evolutionary rescue occurs when the genetic evolution of adaptation saves a population from extinction after environmental change. The evolution of resistance to pesticides is a special scenario of abrupt environmental change, where rescue occurs under strong selection for one or a few <em>de novo</em> resistance mutations of large effect. Here, we develop continuous-time approximations that accurately predict classic discrete-time dynamics in population genetics and population ecology in an integrated eco-evolutionary model of adaptive rescue through pesticide resistance. We derive analytical approximations for the key distributions and statistics that characterise the results, including the probability density function for the time to resistance and the probability of population extinction. The time to resistance shows a lag period, a narrow peak and a long tail, which implies that it can be difficult to predict when resistance will arise. The probability of population extinction shows a sharp transition, in that when extinction is possible, it is also highly likely, which can make eradication a theoretically achievable goal. Alongside these results contributing to the theory of evolutionary rescue, the methods have produced powerful approximations that lay the foundations of a flexible modelling framework for the applied study of eco-evolutionary dynamics to improve scientific resistance management.</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.