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Rhodotorula toruloides has been increasingly explored as a host for bioproduction of lipids, fatty acid derivatives and terpenoids. Various genetic tools have been developed, but neither a centromere nor an autonomously replicating sequence (ARS), both necessary elements for stable episomal plasmid maintenance, has yet been reported. In this study, cleavage under targets and release using nuclease (CUT&RUN), a method used for genome-wide mapping of DNA–protein interactions, was used to identify R. toruloides IFO0880 genomic regions associated with the centromeric histone H3 protein Cse4, a marker of centromeric DNA. Fifteen putative centromeres ranging from 8 to 19 kb in length were identified and analyzed, and four were tested for, but did not show, ARS activity. These centromeric sequences contained below average GC content, corresponded to transcriptional cold spots, were primarily nonrepetitive and shared some vestigial transposon-related sequences but otherwise did not show significant sequence conservation. Future efforts to identify an ARS in this yeast can utilize these centromeric DNA sequences to improve the stability of episomal plasmids derived from putative ARS elements.

This dataset contains data and R scripts used to analyze the trade of non-native pet amphibians in the United States by integrating online classified advertisements with U.S. Fish and Wildlife Service import records. The data include records of amphibian advertisements, U.S. imports, taxonomic reference lists, and conservation status information. The dataset supports analyses identifying domestically produced species, species entering U.S. markets through unrecorded or unofficial trade pathways, and price differences associated with documented and undocumented trade. The dataset supports the analyses presented in an associated peer-reviewed publication in Biological Conservation.

This dataset contains ecological and demographic data for William’s bright‑eyed frog (Boophis williamsi), a critically endangered amphibian restricted to the Ankaratra Massif in Madagascar’s central highlands. Field surveys were conducted between September 2018 – March 2019 and July 2021 across ten 100‑m stream transects to estimate abundance and identify habitat associations for both tadpoles and adult frogs. Data include repeated counts of individuals and associated habitat variables (e.g., canopy cover, substrate type, stream depth, discharge, and temperature). Abundance was estimated using N‑mixture models implemented in R (version 4.3.1) with the ubms package, with separate models for tadpoles and frogs to account for differences in detection probability. The dataset consists of multiple CSV files capturing microhabitat, environmental variables, and raw survey count data (y_frogs.csv and y_tadpoles.csv) and an R script (boophis_abundance.R) used for model fitting. The dataset was compiled for an article accepted in the Herpetological Journal by the British Herpetological Society and is intended to support long‑term monitoring and conservation planning for B. williamsi and other threatened amphibians in Madagascar.

CoNSEPT is a tool to predict gene expression in various cis and trans contexts. Inputs to CoNSEPT are enhancer sequence, transcription factor levels in one or many trans conditions, TF motifs (PWMs), and any prior knowledge of TF-TF interactions.

Raw data of Auchenorrhyncha (Hemiptera) species presence and abundance from samples collected as part of Morgan Brown's M.S. thesis entitled "Investigating changes in Auchenorrhyncha (Hemiptera) communities in Illinois prairies over 25 years." Collection_Events_MBrown.pdf contains information that corresponds to each collection event code listed in the raw data files, including coordinates, date of collection, collection method, and name of collector. Each CSV file contains Auchenorrhyncha species presence and abundance data from each sampling area in Illinois: Route 45 Railroad Prairie, Richardson Wildlife Foundation, Mason County nature preserves, and Twelve Mile Prairie. Variables included in the CSV files include: Family: Taxonomic family to which each species belongs Subfamily: Taxonomic subfamily to which each species belongs Tribe: Taxonomic tribe to which each species belongs Species: Lowest taxonomic level to which individuals were identified The first row of column 5 to the end are collection event codes which correspond to each code listed in the PDF * New in V2: The CSV files originally uploaded in V1 contained outdated species names. V2 provides updated CSV files with the corrected names. * New in V3: There were some inconsistencies in the collection event codes listed in the PDF and CSV files uploaded in V1 and V2. V3 provides updated PDF and CSV files with the corrected codes. File update status: Collection_Events_MBrown_V2.pdf -> updated in this V3 (in V2 it remained the same as in V1 but now is updated in V3) MasonCounty_RawData_V3.csv -> updated in this V3 RichardsonWildlifeFoundation_RawData_V2.csv -> remains the same as in V2 Route45_RawData_V3.csv -> updated in this V3 TwelveMilePrairie_RawData_V3.csv -> updated in this V3

The diel activity of study animals while feeding at their kills in the Santa Cruz Mountains of California

This dataset includes data from a study conducted in southern Illinois, USA, which was published in the Journal of Applied Ecology. The study investigated the interactive effects of fire history and invasion by the non-native grass Microstegium vimineum on fire intensity and oak regeneration in central hardwood forests. The dataset includes data on environmental conditions, historical fire occurrence, experimental fire intensity and fuel load, seedling and juvenile oak characteristics, Microstegium cover, and plot descriptions.

This dataset contains the raw skin temperature data recorded from female Indiana bats (Myotis sodalis) recorded in Indiana and Kentucky from April through August of 2021. This dataset also contains the raw daily heterothermic response variable data that were used in this analysis. This dataset also includes the raw ambient temperature weather data recorded at our Indiana and Kentucky field sites. Lastly, this dataset contains the R script needed to analyze the above dataset.

This dataset contains the data related to Chapter 2 of Iacaruso, N. (2026) "EVALUATING ENVIRONMENTAL DNA AS AN EARLY DETECTION METHOD FOR AQUATIC INVASIVE SPECIES". Doctoral Dissertation. University of Illinois Urbana-Champaign. This chapter will also be represented in Iacaruso et al. (2025) "Environmental DNA metabarcoding for monitoring fish biodiversity in remote lakes". North American Journal of Fisheries Management. (Forthcoming). The files contain the eDNA metabarcoding sequences from sampling Isle Royale lakes in 2021 and 2022, species read counts for each eDNA sample, and other information collected at each site.

This dataset contains seed germination data from two inoculation experiments involving two fig species, Ficus beddomei and Ficus callosa, found in the tropical forests of the Western Ghats, India, and fungal taxa that were isolated from them. The file "first_inoculation_expt_Nov_2025" contains germination data for screening of select fungal taxa for their effects on the two fig species. The file "serial_inoculation_expt_Nov_2025" contains germination data from a serial inoculation experiment involving successive inoculation of seeds with an endophytic followed by a pathogenic fungal taxon.

Arecibo ISR CLP ion-line spectra obtained from RI receiver with 500 kHz bandwidth and 120-640 km altitude range, experiment dates September 23-26, 2016. Used for Mitigation of ion-temperature/composition ambiguity in the inversion of F-region ion-line spectra measured at Arecibo using coded long pulses.

Data collected at 71 study sites from 2023 to 2024 for Reves, Olivia P. (2025): Using Environmental DNA Metabarcoding to Inform Biodiversity Conservation in Agricultural Landscapes. Master's thesis, University of Illinois Urbana-Champaign. Files include study site information, taxa by site matrices for vertebrates from environmental DNA metabarcoding using multiple mitochondrial DNA primers (COI, 12S), and bird species audibly detected by a phone app at study sites.

This dataset supports the analysis presented in the study on curbside electric vehicle (EV) charging infrastructure planning in San Francisco and the published paper titled "Urban electric vehicle infrastructure: Strategic planning for curbside charging." It includes spatial data layers and tabular data used to evaluate location suitability under multiple criteria, such as demand, accessibility, and environmental benefits. This dataset can be used to replicate the multi-criteria decision-making framework, perform additional spatial analyses, or inform policy decisions related to EV infrastructure siting in urban environments. The paper's DOI is https://doi.org/10.1016/j.jtrangeo.2025.104328.

The uploaded data is part of the paper titled: Self-Modifying Percolation Governs Detachment in Soft Suction Wet Adhesion, which shows the detachment mechanism of liquid suction-based adhesion.

This dataset contains all the code, notebooks, datasets used in the study conducted to measure the spatial accessibility of COVID-19 healthcare resources with a particular focus on Illinois, USA. Specifically, the dataset measures spatial access for people to hospitals and ICU beds in Illinois. The spatial accessibility is measured by the use of an enhanced two-step floating catchment area (E2FCA) method (Luo & Qi, 2009), which is an outcome of interactions between demands (i.e, # of potential patients; people) and supply (i.e., # of beds or physicians). The result is a map of spatial accessibility to hospital beds. It identifies which regions need more healthcare resources, such as the number of ICU beds and ventilators. This notebook serves as a guideline of which areas need more beds in the fight against COVID-19. ## What's Inside A quick explanation of the components of the zip file * `COVID-19Acc.ipynb` is a notebook for calculating spatial accessibility and `COVID-19Acc.html` is an export of the notebook as HTML. * `Data` contains all of the data necessary for calculations:       * `Chicago_Network.graphml`/`Illinois_Network.graphml` are GraphML files of the OSMNX street networks for Chicago and Illinois respectively.       * `GridFile/` has hexagonal gridfiles for Chicago and Illinois       * `HospitalData/` has shapefiles for the hospitals in Chicago and Illinois       * `IL_zip_covid19/COVIDZip.json` has JSON file which contains COVID cases by zip code from IDPH       * `PopData/` contains population data for Chicago and Illinois by census tract and zip code.       * `Result/` is where we write out the results of the spatial accessibility measures       * `SVI/`contains data about the Social Vulnerability Index (SVI) * `img/` contains some images and HTML maps of the hospitals (the notebook generates the maps) * `README.md` is the document you're currently reading! * `requirements.txt` is a list of Python packages necessary to use the notebook (besides Jupyter/IPython). You can install the packages with `python3 -m pip install -r requirements.txt`

This dataset contains all raw data corresponding to the figures in the main text and appendices of the paper "Dispersion Engineering of Planar Sub-millimeter Wave Waveguides and Resonators with Low Radiation Loss."

This is the dataset that accompanies the paper titled "A Dual-Frequency Radar Retrieval of Snowfall Properties Using a Neural Network", submitted for peer review in August 2020. Please see the github for the most up-to-date data after the revision process: https://github.com/dopplerchase/Chase_et_al_2021_NN Authors: Randy J. Chase, Stephen W. Nesbitt and Greg M. McFarquhar Corresponding author: Randy J. Chase (randyjc2@illinois.edu) Here we have the data used in the manuscript. Please email me if you have specific questions about units etc. 1) DDA/GMM database of scattering properties: base_df_DDA.csv This is the combined dataset from the following papers: Leinonen & Moisseev, 2015; Leinonen & Szyrmer, 2015; Lu et al., 2016; Kuo et al., 2016; Eriksson et al., 2018. The column names are D: Maximum dimension in meters, M: particle mass in grams kg, sigma_ku: backscatter cross-section at ku in m^2, sigma_ka: backscatter cross-section at ka in m^2, sigma_w: backscatter cross-section at w in m^2. The first column is just an index column. 2) Synthetic Data used to train and test the neural network: Unrimed_simulation_wholespecturm_train_V2.nc, Unrimed_simulation_wholespecturm_test_V2.nc This was the result of combining the PSDs and DDA/GMM particles randomly to build the training and test dataset. 3) Notebook for training the network using the synthetic database and Google Colab (tensorflow): Train_Neural_Network_Chase2020.ipynb This is the notebook used to train the neural network. 4)Trained tensorflow neural network: NN_6by8.h5 This is the hdf5 tensorflow model that resulted from the training. You will need this to run the retrieval. 5) Scalers needed to apply the neural network: scaler_X_V2.pkl, scaler_y_V2.pkl These are the sklearn scalers used in training the neural network. You will need these to scale your data if you wish to run the retrieval. 6) <b>New in this version</b> - Example notebook of how to run the trained neural network on Ku- Ka- band observations. We showed this with the 3rd case in the paper: Run_Chase2021_NN.ipynb 7) <b>New in this version</b> - APR data used to show how to run the neural network retrieval: Chase_2021_NN_APR03Dec2015.nc The data for the analysis on the observations are not provided here because of the size of the radar data. Please see the GHRC website (<a href="https://ghrc.nsstc.nasa.gov/home/">https://ghrc.nsstc.nasa.gov/home/</a>) if you wish to download the radar and in-situ data or contact me. We can coordinate transferring the exact datafiles used. The GPM-DPR data are avail. here: <a href="http://dx.doi.org/10.5067/GPM/DPR/GPM/2A/05">http://dx.doi.org/10.5067/GPM/DPR/GPM/2A/05</a>

Transport and MFM data of brickwork artificial spin ice composed of permalloy are included, which are reproductions of the data in an article named "Magnetic response of brickwork artificial spin ice". Transport data represent magnetic response of connected brickwork artificial spin ice, and MFM data represent how both connected and disconnected brickwork artificial spin ice react to external magnetic fields. SEM images of typical samples are included, where individual nanowire leg (island) is approximately 660 nm long and 140 nm wide with a 40 nm thickness. For the transport, each sample was measured in a longitudinal and a transverse geometry. Red curves are the 2500 Oe to -2500 Oe sweeps and the blue curves are -2500 Oe to 2500 Oe sweeps. Transport measurements were taken by using a standard 4-wire technique. Each plot was saved in pdf format.

Vector competence and survival data for Aedes albopictus mosquitoes exposed to Ross River virus

Information to characterize the solar-induced chlorophyll fluorescence (SIF)-gross primary production (GPP) relationship in C4 cropping systems remains limited. The annual C4 crop corn and perennial C4 crop miscanthus differ in phenology, canopy structure and leaf physiology. Investigating the SIF-GPP relationships in these species could deepen our understanding of SIF-GPP relationships within C4 crops. Using in situ canopy SIF and GPP measurements for both species along with leaf-level measurements, we found considerable differences in the SIF-GPP relationships between corn and miscanthus, with a stronger SIF-GPP relationship and higher slope of SIF-GPP observed in corn compared to miscanthus. These differences were mainly caused by leaf physiology. For miscanthus, high non-photochemical quenching (NPQ) under high light, temperature and water vapor deficit (VPD) conditions caused a large decline of fluorescence yield (ΦF), which further led to a SIF midday depression and weakened the SIF-GPP relationship. The larger slope in corn than miscanthus was mainly due to its higher GPP in mid-summer, largely attributed to the higher leaf photosynthesis and less NPQ. Our results demonstrated variation of the SIF-GPP relationship within C4 crops and highlighted the importance of leaf physiology in determining canopy SIF behaviors and SIF-GPP relationships.

Sulfolobus islandicus, an emerging archaeal model organism, offers unique advantages for metabolic engineering and synthetic biology applications owing to its ability to thrive in extreme environments. Although several genetic tools have been established for this organism, the lack of well-characterized chromosomal integration sites has limited its potential as a cellular factory. Here, we systematically identified and characterized 13 artificial CRISPR RNAs targeting eight integration sites in S. islandicus using the CRISPR-COPIES pipeline and a multi-omics-informed computational workflow. We leveraged the endogenous CRISPR-Cas system to integrate the reporter gene lacS and validated heterologous expression through a β-galactosidase assay, revealing significant positional effects. As a proof of concept, we utilized these sites to genetically manipulate lipid ether composition by overexpressing glycerol dibiphytanyl glycerol tetraether (GDGT) ring synthase B (GrsB). This study expands the genetic toolbox for S. islandicus and advances its potential as a robust platform for archaeal synthetic biology and industrial biotechnology.

This dataset contains information about absorptive roots from 170 plots along a latitudinal and temperature gradient in northern Alaska, including tussock sedges and deciduous alder, birch, and willow shrubs. This dataset accompanies the paper "Impacts of Arctic Shrubs on Root Traits and Belowground Nutrient Cycles Across a Northern Alaskan Climate Gradient," which was published in Frontiers in Plant Sciences. <b>*Note:</b> in the "patch coordinates" tab, the same coordinates/elevation ("Long", "Lat", and "Elev (m)") apply to all patches that share a number. For ex: "Patch" W1, B1, and G1 share the same "Long", "Lat", and "Elev (m)" values as "Patch" A1.

Ethanol and lactate are typical waste products of glucose fermentation. In mammals, glucose is catabolized by glycolysis into circulating lactate, which is broadly used throughout the body as a carbohydrate fuel. Individual cells can both uptake and excrete lactate, uncoupling glycolysis from glucose oxidation. Here we show that similar uncoupling occurs in budding yeast batch cultures of Saccharomyces cerevisiae and Issatchenkia orientalis. Even in fermenting S. cerevisiae that is net releasing ethanol, media 13C-ethanol rapidly enters and is oxidized to acetaldehyde and acetyl-CoA. This is evident in exogenous ethanol being a major source of both cytosolic and mitochondrial acetyl units. 2H-tracing reveals that ethanol is also a major source of both NADH and NADPH high-energy electrons, and this role is augmented under oxidative stress conditions. Thus, uncoupling of glycolysis from the oxidation of glucose-derived carbon via rapidly reversible reactions is a conserved feature of eukaryotic metabolism.

Data for 'Atomic-scale imaging and charge state manipulation of NV centers by scanning tunneling microscopy' to be published in Nature Communications.

This page contains the data for the publication "Myc and Tor drive growth and cell competition in the regeneration blastema of Drosophila wing imaginal discs" published in Development, 2025.