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Leaf spectroscopy and active fluorescence datasets for early drought and nitrogen stress diagnosis in tomato
<p>The dataset contains different plant physiological parameters collected during a 14-day stress and recovery experiment on tomato (<em>Solanum lycopersicum</em> L. cv Moneymaker) plants, undergoing a nitrogen deficiency, drought or control treatment. </p> <p>A full description of the experiment, together with the scientific results, is published by Pescador-Dionisio et al. (2024), and can be found through: <a href="https://doi.org/10.1111/nph.20253">https://doi.org/10.1111/nph.20253.</a></p> <p>The goal of the dataset collection was to obtain a non-invasive proximal sensing dataset at leaf level (reflectance, transmittance, upward and downward fluorescence), in parallel to gas exchange and active fluorescence measurements. The leaf spectroscopy dataset was further processed by a pigment spectral unmixing algorithm according to Van Wittenberghe et al. (2024), to calculate fluorescence quantum efficiency (<em><strong>FQE</strong></em>) and effective absorbance (<strong><em>A_eff</em></strong>) changes associated to the activation of regulated heat dissipation (<strong><em>A_eff_535_Xan</em></strong>). The latter absorption feature is linked to the xanthophyll ('<strong>Xan</strong>') absorption in the 500-600 nm range, which is modelled by the sum of three Gaussians. For a full description of this feature, see Van Wittenberghe et al. (2021).</p> <p>Gas exchange and active fluorescence measurements were carried out with a LI-6400 portable photosysthesis system (LI-COR Biosciences, Lincoln, USA) equipped with a 6400-40 leaf chamber fluorometer. Steady-state measurements were done at 300 and 1000 μmol m−2 s−1 ('<strong><em>PAR300</em></strong>' and '<em><strong>PAR1000</strong></em>'), i.e. growing light conditions and light saturating conditions. Light response curves were taken on different days. Common fluorescence parameters (e.g., <em><strong>Fv/Fm, Fo, Fm, NPQ, YNO, YNPQ</strong></em>) are provided together with 'sustained' and reversible' NPQ parameters calculated according Porcar-Castell (2011).</p> <p>Leaf spectroscopy and active steady-state fluorescence measurements were performed on the same measuring days ('<em><strong>d0</strong></em>', '<em><strong>d2</strong></em>', '<em><strong>d4</strong></em>', '<em><strong>d7</strong></em>', '<em><strong>d14</strong></em>') and on the same leaf, both at 300 and 1000 μmol m−2 s−1 ('<em><strong>PAR300</strong></em>' and '<em><strong>PAR1000</strong></em>'), taking into account an adaptation time. We used a LED light source and several filters, placed in front of a FluoWat leaf clip, which was connected to two high-performance VIS-NIR spectroradiometers (QEPRO, Ocean Insight Inc., Orlando, Florida, USA). The spectroscopy measurements are presented in the Matlab structures for each measuring day, e.g. "<strong><em>2023_d0_Leaf_Spec_Tomato_Stress.mat</em></strong>".</p> <p>The outputs of the pigment spectral fitting code are presented by Matlab structures, e.g. "<strong><em>2023_d0_Leaf_Fitting_Tomato_Stress.mat</em></strong>", which contains the effective absorbance fitting (<strong><em>A_eff</em></strong>) of each pigment (<strong>Chl a, Chl b, Carotene-b, Anthocyanins, and Xanthophylls</strong>) for the wavelength range [500-780] nm, the absorbed photosynthetically active radiation by Chlorophyll a ('<em><strong>APAR_Chla</strong></em>') for the wavelength range [400-800] nm, and the fluorescence quantum efficiency, calculated as the ratio of the emitted fluorescence photons and the flux of photons absorbed by Chlorophyll a. </p> <p>Additional metadata from HPLC photosynthetic pigment analyses, xanthophyll-related enzyme expression, biomass and total content of elemental nitrogen are provided.</p> <p>Please follow the README files for more detailed information.</p> <p> </p>
FASTA file containing to the MYB encoding gene Ant1 genomic sequences corresponding to wild and cultivated tomato accessions
<p>Fasta sequence correspond to the MYB encoding gene <em>An2-like</em>. The genomic sequences correspond to <em>Solanum galagpagnese</em> accession LA1141 (this study), <em>S. lycopersicum</em> variety OH8245 (this study), <em>S. lycopersicum</em> variety Heinz 1706 reference genome, and 84 tomato accessions published as part of The 100 Tomato Genome Sequencing Consortium (The 100 Tomato Genome Sequencing Consortium et al., 2014). Local sequences databases were made and retrieved using BLAST version/2018-08 for 84 accessions from The 100 Tomato Genome Sequencing Consortium (The 100 Tomato Genome Sequencing Consortium et al., 2014). Sequences corresponding to Heinz 1706 (Hosmani et al., 2018), were accessed using the Basic Local Alignment Search Tool (BLAST) tool available from the Sol Genomics Network (SGN) (available at <a href="https://solgenomics.net/tools/blast/">https://solgenomics.net/tools/blast/</a>).</p>
FASTA file containing the MYB encoding gene An2-like genomic sequences corresponding to wild and cultivated tomato accessions
<p>FASTA sequence corresponds to the MYB encoding gene <em>An2-like</em>. The genomic sequences correspond to <em>Solanum galagpagnese</em> accession LA1141 (this study), <em>S. lycopersicum</em> variety OH8245 (this study), <em>S. lycopersicum</em> variety Heinz 1706 reference genome (Hosmani et al., 2019), <em>S. lycopersicum </em>variety Indigo Rose (Yan et al., 2020), <em>S. lycopersicum</em> accession LA1996 [MN242011.1 (Colanero et al., 2020)], <em>S. chilense </em>accession LA1930 [MN242012.1 (Colanero et al., 2020)], and 84 tomato accessions published as part of The 100 Tomato Genome Sequencing Consortium (The 100 Tomato Genome Sequencing Consortium et al., 2014). Local sequences databases were made and retrieved using BLAST version/2018-08 for 84 accessions from The 100 Tomato Genome Sequencing Consortium (The 100 Tomato Genome Sequencing Consortium et al., 2014). Sequences corresponding to Heinz 1706 (Hosmani et al., 2018), Indigo Rose [MN433087 (Yan et al., 2020)], <em>S. lycopersicum </em>accession LA1996 [MN242011.1, EF433417.1 (Sapir et al., 2008; Colanero et al., 2020)], <em>S. chilense</em> accession LA1930 [MN242012.1 (Colanero et al., 2020)] were accessed using the Basic Local Alignment Search Tool (BLAST) tool available from the Sol Genomics Network (SGN) (available at <a href="https://solgenomics.net/tools/blast/">https://solgenomics.net/tools/blast/</a>) and the National Center for Biotechnology Information (NCBI)(available at NCBI: <a href="https://www.ncbi.nlm.nih.gov">https://www.ncbi.nlm.nih.gov</a>).</p>
FASTA file containing the MYB encoding genes at the Aft locus with genomic sequences corresponding to wild and cultivated tomato accessions
<p>FASTA sequences correspond to the MYB encoding genes <em>An2-like </em>and <em>Ant1</em>. The genomic sequences were combined correspond to <em>Solanum galagpagnese</em> accession LA1141 (this study), <em>S. lycopersicum</em> variety OH8245 (this study), <em>S. lycopersicum</em> variety Heinz 1706 reference genome (Hosmani et al., 2019), LA1996 [MN242011.1, EF433417.1(Sapir et al., 2008; Colanero et al., 2020)], and 84 tomato accessions published as part of The 100 Tomato Genome Sequencing Consortium (The 100 Tomato Genome Sequencing Consortium et al., 2014). Local sequences databases were made and retrieved using BLAST version/2018-08 for 84 accessions from The 100 Tomato Genome Sequencing Consortium (The 100 Tomato Genome Sequencing Consortium et al., 2014). Sequences corresponding to Heinz 1706 (Hosmani et al., 2018), <em>S. lycopersicum </em>accession LA1996 [MN242011.1, EF433417.1 (Sapir et al., 2008; Colanero et al., 2020)], <em>S. chilense</em> accession LA1930 [MN242012.1 (Colanero et al., 2020)] were accessed using the Basic Local Alignment Search Tool (BLAST) tool available from the Sol Genomics Network (SGN) (available at <a href="https://solgenomics.net/tools/blast/">https://solgenomics.net/tools/blast/</a>) and the National Center for Biotechnology Information (NCBI) (available at NCBI: <a href="https://www.ncbi.nlm.nih.gov/">https://www.ncbi.nlm.nih.gov</a>).</p>
A Deep Learning Dataset for Tomato Pest Leafminer TUTA ABSOLUTA
<p>The images of tomato leafminer (<em>Tuta absoluta</em>) were taken in in-house plots between August 2018 and May 2019 in Arusha, Tanzania. Under net-house that were controlled from other others. <em>T.absoluta</em> larvae were inoculated on the commonly grown tomato varieties at the early growth stage (herein, on the second day after transplanting). The images were taken for the first 2 weeks after inoculation. Images captured the canopy of the plants. </p> <p><strong>File Description</strong><br> All Images are in the <strong>.zip</strong> files; "dataset_1_H.zip" has 1926 Images, dataset_1_NH.zip has 325 Images, dataset_2 .zip has 3482 Images and the files labels are in "file_labels.csv" the image file name in column "FileName" and respective label in column "Label", labels meaning "1" refer to healthy (plants not inoculated with <em>T.absoluta</em> larvae and "2" refer to <em>T.absoluta</em> affected plants. A total of 4341 image files are labelled. </p> <p> </p>
FASTA file containing the MYB encoding gene An2-like and Ant1 coding sequences corresponding to wild and cultivated tomato accessions
<p>The coding sequence (CDS) of the MYB encoding genes <em>Ant1</em> and <em>An2-like</em>. Sequences were retrieved from regions corresponding to the<em> Aft</em> locus from <em>Solanum galapagense </em>accession LA1141, <em>S. lycopersicum</em> variety OH8245, and 84 tomato accessions published as part of The 100 Tomato Genome Sequencing Consortium (The 100 Tomato Genome Sequencing Consortium et al., 2014). Sequences were compared to available CDS available from the Sol genomics network (SGN) and the National Center for Biotechnology Information. The CDS was retrieved from <em>S. lycopersicum</em> variety Indigo Rose [MN433087 (Yan et al., 2020)], <em>S. lycopersicum</em> accession LA1996 [MN242011.1, EF433417.1( Sapir et al., 2008; Colanero et al., 2020)], and <em>S. chilense </em>accession LA1930 [MN242012.1 (Colanero et al., 2020)], The orthologous CDS corresponding to the <em>Aft </em>MYB encoding genes from <em>Solanum tuberosum</em> L. Group Phureja clone DM1-3 genome (PGSC DM v4.03 Pseudomolecules) was retrieved from the Potato Genome Sequence Consortium (PGSC: Potato Genome Sequencing Consortium et al., 2011), and the Capsicum annum cv. CM334 genome was retrieved from <em>Capsicum annuum </em>cv CM334 genome chromosome release 1.55 (Hulse-Kemp et al. 2018). These CDS were obtained using the Basic Local Alignment Search Tool (BLAST) tool available from the Sol Genomics Network (SGN) (available at https://solgenomics.net/tools/blast/). Comparison of syntenic chromosomal regions using known positions of tomato, potato, and pepper markers with comparative map viewer from SGN: (available at https://solgenomics.net/cview) on chromosome 10, was used as a quality check for S.<em> tuberosom</em> and <em>C. annuum.</em> Orthologous CDS corresponding to <em>Salvia miltiorrhiza, Arabidopsis thaliana</em>, [NM_105308.2, NM_105310.4 (Teng et al., 2005, Cominelli et al., 2008; Beradini et al., 2015)] were chosen based on tomato <em>Aft</em> sequence homology and gene annotations of positive R2R3 MYB regulation of anthocyanin. The CDS corresponding to the <em>Aft</em> genes were retrieved from the CDS reference genomes available from the Sol Genomics Network SGN: Tomato Genome CDS (ITAG release 4.0), Potato PGSC DM v3.4 CDS sequences, <em>Capsicum annuum </em>cv CM334 Genome CDS (release 1.55), or from the National Center for Biotechnology Information (NCBI: https://www.ncbi.nlm.nih.gov) reference sequences (RefSeq) section of the Genbank records. When accessed from Genank records, the CDS sequence was extracted from the “features” section and exported as a FASTA file.</p>
Root symbionts alter the volatile profile of herbivore-infested tomato plants and aid the attraction of a predator
<p>Beneficial root microbes are among the most frequently used biocontrol agents in cropping systems, since they have been shown to promote plant growth and crop yield. Moreover, they are able to enhance protection against pathogens and insect herbivores by activating plant resistance mechanisms. Plant defense responses against herbivorous insects include the induction of metabolic pathways involved in the synthesis of defense-related metabolites. These metabolites include volatile organic compounds (VOCs), which attract natural enemies of the herbivores as a form of indirect resistance. Considering that beneficial root microbes may affect direct herbivore resistance, we hypothesized that also indirect resistance may be affected. We tested this hypothesis in a study system composed of tomato, the arbuscular mycorrhizal fungus <em>Rhizophagus irregularis</em>, the growth-promoting fungus <em>Trichoderma harzianum</em>, the generalist chewing herbivore <em>Spodoptera exigua </em>and the omnivorous predator<em> Macrolophus pygmaeus</em>. Using a Y-tube olfactometer we found that <em>M. pygmaeus</em> preferred plants with <em>S. exigua </em>herbivory, but microbe-inoculated plants more than non-inoculated ones. We used a targeted GC-MS approach to assess the impact of beneficial microbes on the emission of volatiles twenty-four hours after herbivory to explain the choice of <em>M. pygmaeus</em>. We observed that the volatile composition of the herbivore-infested plants differed from that of the non-infested plants, which was driven by the higher emission of green leaf volatile compounds, methyl salicylate, and several monoterpenes and sesquiterpenes. Inoculation with microbes had only a marginal effect on the emission of some terpenoids in our experiment. Gene expression analysis showed that the marker genes involved in the jasmonic and salicylic acid pathways were differentially expressed in the microbe-inoculated plants after herbivory. Our results pinpoint the role of root symbionts in determining plant-microbe-insect interactions up to the third trophic level, and elucidates their potential to be used in plant protection.</p>
Tomato Classification using Mass Spectrometry-Machine Learning Technique: a Food Safety-enhancing Platform
<p>Food safety and quality assessment mechanisms are unmet needs that industries and countries have been continuously facing in recent years. Our study aimed at developing a platform using Machine Learning algorithms to analyze Mass Spectrometry data for classification of tomatoes on organic and non-organic. Tomato samples were analyzed using silica gel plates and direct-infusion electrospray-ionization mass spectrometry technique. Decision Tree algorithm was tailored for data analysis. This model achieved 92% accuracy, 94% sensitivity and 90% precision in determining to which group each fruit belonged. Potential biomarkers evidenced differences in treatment and production for each group.</p>
Mass spectrometry Imaging dataset for the study on fungicide application to tomato leaves - I
<p>The dataset uploaded here is in association to a manuscript in press by Ajith et al. titled, "Visualizing active fungicide formulation mobility in tomato leaves with Desorption Electrospray Ionisation Mass Spectrometry Imaging". This dataset contains .imzML format files of Mass Spectrometry Imaging data along with the zipped .ibd files for a fungicide application study with a commerical Azoxystrobin formulation. The files were generated with a DESI Imprint imaging method for a commercial pesticide formulation applied young tomato leaves after 2 hours, 24 hours, 56 hours and a week after application.</p> <table> <tbody> <tr> <td>File Name</td> <td>Time point</td> </tr> <tr> <td>DTIM_2h</td> <td>2h Adaxial Imprint</td> </tr> <tr> <td>DTIM_24h_1</td> <td>24h Adaxial Imprint</td> </tr> <tr> <td>DTIM_24h_2</td> <td>24h Adaxial Imprint</td> </tr> <tr> <td>DTIM_24h_3</td> <td>24h Adaxial Imprint</td> </tr> <tr> <td>DTIM_56h_1</td> <td>56h Adaxial Imprint</td> </tr> <tr> <td>DTIM_56h_2</td> <td>56h Adaxial Imprint</td> </tr> <tr> <td>DTIM_56h_3</td> <td>56h Adaxial Imprint</td> </tr> <tr> <td>DTIM_1week_1</td> <td>1 week Adaxial Imprint</td> </tr> <tr> <td>DTIM_1week_2</td> <td>1 week Adaxial Imprint</td> </tr> <tr> <td>DTIM_1week_3</td> <td>1 week Adaxial Imprint</td> </tr> <tr> <td>DTIM_48h_Abaxial</td> <td>48h Abaxial imprint</td> </tr> <tr> <td>DTIM_48h_Adaxial</td> <td>48h Adaxial Imprint</td> </tr> </tbody> </table> <p> </p>
Population genomics reveals molecular determinants of specialization to tomato in the polyphagous fungal pathogen Botrytis cinerea
<p>Single nucleotide polymorphisms detected in Illumina-sequenced isolates of B. cinerea collected from tomato, grape, hydrangea and bramble in France.</p>
MinION Reads From a Tomato Source: David Eccles' TEDxWellington 2016 Dataset
<p>This is a dump of the data (i.e. MinION reads) that were produced during an on-stage sequencing run for the TEDxWellington 2016 conference. The data dump also includes presentation slides, associated videos, and a script of the talk that I gave during the conference.</p>
Figure 4 in Efficiency of some commercial stimulants in inducing tomato resistance to Tetranychus urticae (Acari: Tetranychidae)
Figure 4. Scanning Electron Microscopy (SEM) images of the upper-surface of leaves sprayed with water (control), Silical®, Postar®, and Ultrafit® to visualize the diversity of trichome types (glandular: GT and non-glandular: NGT) and densities for tomato cultivars K-186 F1 and 023 F1.
Figure 2 in Efficiency of some commercial stimulants in inducing tomato resistance to Tetranychus urticae (Acari: Tetranychidae)
Figure 2. Population of movable stages of Tetranychus urticae on tomato leaves over old 3–13 weeks after transplanting for two cultivars treated with commercial stimulants during the 2017 and 2018 summer seasons. Ultrafat * applied by adding to soil below the plants. Columns with the same letter represent means that are not significantly different according to Tukey's multiple range test (p <0.05). Vertical bars represent ± standard error of the mean (n = 36).
Figure 1 in Efficiency of some commercial stimulants in inducing tomato resistance to Tetranychus urticae (Acari: Tetranychidae)
Figure 1. Population of movable stages of Tetranychus urticae on tomato leaves of several plant ages for cultivars K186 F1 and 023 F1 treated with some commercial stimulants during the 2017 (A) and 2018 (B) summer seasons. Population at three weeks after transplanting was immediately before treatment. Columns with the same letter represent means that are not significantly different according to Tukey's multiple range test (p <0.05). Vertical bars represent ± standard error of the mean (n = 21).
Figure 3 in Efficiency of some commercial stimulants in inducing tomato resistance to Tetranychus urticae (Acari: Tetranychidae)
Figure 3. Scanning Electron Microscopy (SEM) images of the lower-surface of leaves sprayed with water (control), Silical®, Postar®, and Ultrafit® to visualize the diversity of trichome types (glandular: GT and non-glandular: NGT) and densities for tomato cultivars K-186 F1 and 023 F1.
Dataset underlying the study "Enhanced Susceptibility to Tomato Chlorosis Virus (ToCV) in Hsp90- and Sgt1-Silenced Plants: Insights from Gene Expression Dynamics"
<p>This dataset is underlying the scientific publication titled "Enhanced Susceptibility to Tomato Chlorosis Virus (ToCV) in Hsp90- and Sgt1-Silenced Plants: Insights from Gene Expression Dynamics", published in the <a href="https://www.mdpi.com/1999-4915/15/12/2370">Viruses</a> journal. </p><p>The dataset includes a time-course transcriptome analysis using RNA-seq of naïve (no whitefly and no virus), mock (non-viruliferous whiteflies) and ToCV (ToCV_viruliferous whiteflies)-treated tomato samples at 2, 7, and 14 days post-infection (dpi) and viral small RNAs derived from Tomato plants infected with ToCV at 14 dpi. The dataset provided here has been deposited in full by the authors in the European Nucleotide Archive (ENA) at EMBL-EBI under accession number PRJEB67704 (<a href="https://www.ebi.ac.uk/ena/browser/view/PRJEB67704"><strong>https://www.ebi.ac.uk/ena/browser/view/PRJEB67704</strong></a><br><br>The provided information in the dataset are further discussed and interpreted in detail, as well as their subsequent results, in the scientific publication.</p><p>This research was conducted within the VIRTIGATION project, which is part of the EU Open Research Data pilot. This project has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No. 101000570.</p>
Data from: Solanum pennellii (LA5240) backcross inbred lines (BILs) for high resolution mapping in tomato
<p>Wild species are an invaluable source of new traits for crop improvement. Over the years the tomato community bred cultivated lines that carry introgressions from different species of the tomato tribe to facilitate trait discovery and mapping. The next phase in such projects is to find the genes that drive the identified phenotypes. This can be achieved by genotyping a few thousand individuals resulting in fine-mapping that can potentially identify the causative gene. To couple trait discovery and fine mapping we are presenting large, recombination-rich, Backcross Inbred Line (BIL) populations involving an unexplored accession of the wild, green-fruited species Solanum pennellii (LA5240; the Lost Accession) with two modern tomato inbreds: LEA, determinate, and TOP indeterminate. The LEA and TOP BILs are in BC2F6-8 generation and include 1,400 and 500 lines respectively. The BILs were genotyped with ~5,000 SPET markers, showing that in the euchromatic regions there was one recombinant every 17-18 Kb while in the heterochromatin a recombinant every 600-700 Kb (TOP and LEA respectively). To gain perspective on the topography of recombination we compared five independent members of the self-pruning gene family with their respective neighboring genes; based on PCR markers, in all cases we found recombinants. Further mapping analysis of two known morphological mutations that segregated in the BILs (Self-pruning and Hair), showed that the maximal delimited intervals were 73 Kb and 210 Kb respectively and included the known causative genes. The LOST_BILs provide a solid framework to study traits derived from a tolerant wild tomato.</p>
Differential impact of impaired steryl ester biosynthesis on the metabolome of tomato seeds and fruits
<p>Steryl esters (SE) are a storage pool of sterols that accumulates in cytoplasmic lipid droplets and helps to maintaining plasma membrane sterol homeostasis throughout plant growth and development. Ester formation of plant SE is catalyzed by phospholipid:sterol acyltransferase (PSAT) and acyl-CoA:sterol acyltransferase (ASAT), which transfer long-chain fatty acid groups to free sterols from phospholipids and acyl-CoA, respectively. Comparative mass spectrometry-based metabolomic analysis between ripe fruits and seeds of a tomato (Solanum lycopersicum cv Micro-Tom) mutant lacking functional PSAT and ASAT enzymes (slasat1xslpsat1) shows that disruption of SE biosynthesis has a differential impact on the metabolome of these organs, including changes in the relative proportions of free and glycosylated sterols. Significant perturbations were observed in the fruit lipidome in contrast to the mild effect detected in the lipidome of seeds. A contrasting response was also observed in phenylpropanoid metabolism, which is down-regulated in fruits and appears to be stimulated in seeds. Comparison of global metabolic changes using volcano plot analysis suggests that disruption of SE biosynthesis favors a general state of metabolic activation that is more evident in seeds than fruits. Interestingly, there is an induction of autophagy in both tissues, which may contribute along with other metabolic changes to the phenotypes of early seed germination and enhanced fruit resistance to Botrytis cinerea displayed by the slasat1xslpsat1 mutant. The results of this study reveal unreported connections between SE metabolism and the metabolic status of plant cells, and lay the basis for further studies aimed at elucidating the mechanisms underlying the observed effects.</p> <p> </p> <p>Data: </p> <p>W1-54; AxP LC polar.zip: raw files LC-polar</p> <p>W1-1 (1)-(54); AxP LC lipid.zip: raw files lipid LC</p> <p>GCtomato.zip: raw files GC polar</p> <p>spreadsheet (.csv) with sample IDs</p>
Tomato Prosystemin Is Much More than a Simple Systemin Precursor
<p>Dataset related to the paper "Tomato Prosystemin Is Much More than a Simple Systemin Precursor", Biology (MDPI) 2022. DOI: <a href="https://doi.org/10.3390/biology11010124">10.3390/biology11010124</a></p> <p> </p>
Manhattan and QQ plots of GWAS on salt stress responses in root system architecture parameters of wild tomato (S. pimpinellifolium)
<p>The population of +/2 200 accessions of wild tomato was screened with the protocol described <a href="https://www.protocols.io/view/studying-root-system-architecture-changes-in-tomat-2mqgc5w">here</a> with the only exception that the plants were transferred 4 days after germination (rather than 3 - described in the protocol). The images were analyzed using the <a href="https://smartroot.github.io/">SmartRoot</a> for days 0, 1, 2, 3, and 4 after transfer to treatment plates (0 or 100 mM NaCl, 1/4 MS, 0.5% sucrose, 0.1% MES, 1% Dashin agar). The data analysis was performed as described <a href="https://rpubs.com/mjulkowska/BIGpimp_RSA_salt">here</a>, while the pareto front calculations were done according to Chandrasekhar & Julkowska paper (<a href="https://www.biorxiv.org/content/10.1101/2021.08.12.456185v1">preprint here</a>). The GWAS was performed using the ASReml script similar to <a href="https://onlinelibrary.wiley.com/doi/10.1111/tpj.15310">Awlia et al. (2021)</a>. The raw GWAS outputs can be found <a href="https://zenodo.org/badge/DOI/10.5281/zenodo.5856310.svg">here</a>. This dataset represents Manhattan plots and QQ plots made out of the data. </p>
ScienceDex guides
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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.