cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25442/hku.30931712
title: Supporting data for "Transcriptional regulation of flavone biosynthesis in rice"

description: Flavones, a major flavonoid subclass, are abundantly accumulated in monocots and they are commonly present in the forms of flavone <i>C</i>-glycosides and <i>O</i>-conjugated flavones. In rice, the biosynthetic pathways of flavone and flavone <i>C</i>-glycosides are well characterized, but the transcriptional regulation of key enzymes remained largely unknown. This study characterizes the MYB transcription factors involved in the regulation of flavone and flavone <i>C</i>-glycoside biosynthesis genes in rice.In rice, chalcone synthase (OsCHS1) initiates flavonoid biosynthesis by producing naringenin chalcone. Whether OsCHS1 is continuously expressed spanning the rice life cycle was unclear. In this study, a systematic analysis of the expression of <i>OsCHS1</i> was carried out using the non-invasive <i>RUBY</i> reporter system. The formation of red betalain indicates the expressionof <i>OsCHS1</i>, and the results presented in "Figures_chapter2.pptx" suggest the tissue-specific and stage-specific expression patterns of <i>OsCHS1</i>. Meanwhile, transient overexpression in rice protoplasts identified various culm-expressed R2R3-MYB proteins, functioning as higher hierarchical regulators for the expression of <i>OsCHS1</i> and flavone biosynthesis genes, and their transcriptional activities are described in "Figures_chapter2.pptx" and "Dataset_chapter2".This study also characterizes the role of OsMYB58/63 in the regulation of flavone biosynthesis. The files "Figures_chapter3.pptx" and "Dataset_chapter3.xlsx" include the results of gene expression analysis, metabolitc analysis, dual-luciferase reporter assays and in vitro protein-DNA binding assays which explain how OsMYB58/63 functions as transcriptional activator in regulating flavone biosynthesis. Moreover, the data in the file "Dataset_Supplementary.xlsx" suggest the multifunctional roles of OsMYB58/63 in regulating specialized metabolism in rice.Lastly, this study characterizes a R2R3-MYB protein, OsP1L, as a transcriptional activator of the flavone <i>C</i>-glycoside biosynthesis in rice. The files "Figures_chapter4.pptx" and "Dataset_chapter4.xlsx" include the results of gene expression analysis, DAP-seq analysis, dual-luciferase reporter assays and EMSA which elucidate how OsP1L regulates the expression of <i>OsCHI</i>, <i>OsCYP93G2</i> and <i>OsCYP75B3</i>. Moreover, these files include the expression patterns of flavone <i>C</i>-glycoside biosynthesis genes and the metabolic analysis of flavone <i>C</i>-glycosides in various tissues.
DOI: 10.25442/hku.30931712.v1
title: Supporting data for "Transcriptional regulation of flavone biosynthesis in rice"

description: Flavones, a major flavonoid subclass, are abundantly accumulated in monocots and they are commonly present in the forms of flavone <i>C</i>-glycosides and <i>O</i>-conjugated flavones. In rice, the biosynthetic pathways of flavone and flavone <i>C</i>-glycosides are well characterized, but the transcriptional regulation of key enzymes remained largely unknown. This study characterizes the MYB transcription factors involved in the regulation of flavone and flavone <i>C</i>-glycoside biosynthesis genes in rice.In rice, chalcone synthase (OsCHS1) initiates flavonoid biosynthesis by producing naringenin chalcone. Whether OsCHS1 is continuously expressed spanning the rice life cycle was unclear. In this study, a systematic analysis of the expression of <i>OsCHS1</i> was carried out using the non-invasive <i>RUBY</i> reporter system. The formation of red betalain indicates the expressionof <i>OsCHS1</i>, and the results presented in "Figures_chapter2.pptx" suggest the tissue-specific and stage-specific expression patterns of <i>OsCHS1</i>. Meanwhile, transient overexpression in rice protoplasts identified various culm-expressed R2R3-MYB proteins, functioning as higher hierarchical regulators for the expression of <i>OsCHS1</i> and flavone biosynthesis genes, and their transcriptional activities are described in "Figures_chapter2.pptx" and "Dataset_chapter2".This study also characterizes the role of OsMYB58/63 in the regulation of flavone biosynthesis. The files "Figures_chapter3.pptx" and "Dataset_chapter3.xlsx" include the results of gene expression analysis, metabolitc analysis, dual-luciferase reporter assays and in vitro protein-DNA binding assays which explain how OsMYB58/63 functions as transcriptional activator in regulating flavone biosynthesis. Moreover, the data in the file "Dataset_Supplementary.xlsx" suggest the multifunctional roles of OsMYB58/63 in regulating specialized metabolism in rice.Lastly, this study characterizes a R2R3-MYB protein, OsP1L, as a transcriptional activator of the flavone <i>C</i>-glycoside biosynthesis in rice. The files "Figures_chapter4.pptx" and "Dataset_chapter4.xlsx" include the results of gene expression analysis, DAP-seq analysis, dual-luciferase reporter assays and EMSA which elucidate how OsP1L regulates the expression of <i>OsCHI</i>, <i>OsCYP93G2</i> and <i>OsCYP75B3</i>. Moreover, these files include the expression patterns of flavone <i>C</i>-glycoside biosynthesis genes and the metabolic analysis of flavone <i>C</i>-glycosides in various tissues.
DOI: 10.1594/pangaea.987223
title: Accumulation measurements from stake farm Neumayer Pegelfeld Spuso, Ekström Ice Shelf, Antarctica, 2020

description: This publication series contains the accumulation measurements from stake farm Pegelfeld Spuso on the Ekström Ice Shelf, Antarctica. The stake farm at the Air Chemistry Observatory (Spuso), located approximately 1.5 km to the south of the present Neumayer Station, has been in operation since September 2009. It consists of 16 aluminum poles (balise), placed in a grid of 4 x 4 with a spacing of 10 m. Readings have been carried out in approx. weekly intervals by the overwintering staff of the air chemistry observatory. Each data set in the series contains all measurements of each stake from one calendar year in a tsv file, the average accumulation of the stake farm for each measurement and the standard deviation of the stake farm for each measurement. The data sets are accompanied by figures illustrating the development of the cumulative accumulation since the beginning of the measurements to date, a bar chart of the monthly accumulation for the year and a collection of panels (one panel per measurement) illustrating the variation of accumulation within the stake farm.
DOI: 10.1594/pangaea.882254
title: Radiocarbon ages of sediment core POPEI_VC2B
DOI: 10.1594/pangaea.988075
title: ADCP current measurements (600 kHz) on RV HEINCKE during RV HEINCKE cruise HE667

description: Ocean velocities were collected by a Teledyne RDI 600 kHz Workhorse Mariner ADCP that was mounted on RV HEINCKE during RV HEINCKE cruise HE667. The transducer was located at 4 m below the water line. The instrument was operated in single-ping, broadband mode with bin size of 1 m and a blanking distance of 1 m. The velocity of the ship was calculated from position fixes obtained by the Global Positioning System (GPS) received directly from RV HEINCKE. Heading, Pitch and Roll were obtained both from the MRU of RV HEINCKE and the internal ADCP gyro. Heading as well as pitch and roll data from ADCP's internal gyrocompass and the navigation and motion data were used by the data acquisition software ViSea DAS (AquaVision®) internally to convert ADCP velocities into earth coordinates. Accuracy of the ADCP velocities mainly depends on the quality of the position fixes and internal ADCP heading data. Further errors stem from a misalignment of the transducer with RV HEINCKE's centerline. ADCP data is provided at minutely sample rate. Raw data or secondly binned data are available on request.
DOI: 10.1594/pangaea.944432
title: Ice nucleating particle number concentration (NINP) as a function of temperature, based on samples taken close to Punta Arena in 2019 and 2020

description: Dataset contains the ice nucleating particle number concentration (NINP) as a function of temperature.
DOI: 10.1594/pangaea.944436
title: Ice nucleating particle number concentration (NINP) after heating as a function of temperature, based on samples taken close to Punta Arena in 2019 and 2020

description: Dataset contains the ice nucleating particle number concentration (NINP) as a function of temperature. Aforehand, the samples have been heated at 95 °C for 1 hour.
DOI: 10.1594/pangaea.944427
title: Overview information of PM10 filter samples collected close to Punta Arena in 2019 and 2020

description: Information of PM10 filter samples, including sample number, start time, end time, duration, total sampling volume, sampling volume per well, and sample groups.
description: Blind filters have been taken during following periods (UTC date, yyyy-mm-dd): Filter, Put-in date, Take-out date Blind01, 2019-04-02, 2019-04-25 Blind02, 2019-05-28, 2019-06-04 Blind03, 2019-07-02, 2019-07-09 Blind04, 2019-07-02, 2019-07-09 Blind05, 2019-07-09, 2019-07-17 Blind06, 2019-07-09, 2019-07-17
DOI: 10.1594/pangaea.944438
title: Surface site density of INP (ns) as a function of temperature, based on samples taken close to Punta Arena in 2019 and 2020

description: Dataset contains the surface site density of INP (ns) as a function of temperature.
DOI: 10.15468/dl.9rkegd
title: Occurrence Download

description: A dataset containing 28 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Michelia champaca",
 "Year 1960-2010"
 ]
}

 The dataset includes 28 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013152-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1594/pangaea.944439
title: Surface site density of INP (ns) after heating as a function of temperature, based on samples taken close to Punta Arena in 2019 and 2020

description: Dataset contains the surface site density of INP (ns) as a function of temperature. Aforehand, the samples have been heated at 95 °C for 1 hour.
DOI: 10.1594/pangaea.946417
title: Relative abundances of PARAFAC components, 2D FDOM indices and other bulk, quantitative parameters determined on water sample from sediment core GeoB 19339-1
DOI: 10.1594/pangaea.906943
title: (Supplement 2) Ice nucleating particles at the Cape Verde Atmospheric Observatory using PM10 filters
DOI: 10.1594/pangaea.882263
title: TOC, Norg and CaCO3 content of sediment core POPEI_VC2B
DOI: 10.1594/pangaea.925350
title: Manual in situ measurements of snow water equivalent and snow depth at the high Arctic Bayelva site during the winter period 2019/2020

description: The high Arctic Bayleva site is located on western Spitsbergen about 3 km from the settlement of Ny Ålesund. Snow water equivalent (SWE) measurements were performed at the Bayelva site during the winter season 2019/2020. The manual measurements consist of measuring the snow depth and weighing a known volume of snow to within ±0.01 kg using a steel tube with a radius of 0.04 m and a length of 0.6 m. If the snow depth exceeds 0.6 m the measurement has to be performed in more than one layer, which can add some uncertainty to the recorded values. In each measurement session several snow pits were dug in a radial pattern around the automatic SWE system, covering approximately the same snow conditions as covered by the footprint of the CS725 in order to validate the automatic measurements.
DOI: 10.1594/pangaea.882268
title: Pollen abundances of sediment core POPEI_VC2B
DOI: 10.1594/pangaea.882266
title: Biomarker content of sediment core POPEI_VC2B
DOI: 10.1594/pangaea.984690
title: Continuous optical chlorophyll-a and turbidity data along RV SONNE cruise SO307

description: Underway optical chlorophyll-a and turbidity data were collected along the cruise track with Sea-Bird Scientific ECO FLNTU sensors installed within two autonomous measurement systems, called self-cleaning monitoring boxes (SMBs). The SMBs measure alternatingly. While one box is measuring, the other one is being cleaned. The boxes switched generally every 12 hours. The water inlet for the SMBs is at about 4 m below sea surface. Observed chlorophyll-a and turbidity data were both quality controlled. Analysis of the chlorophyll-a and turbidity data during parallel operation of the sensors in the two boxes showed significant differences between the sensors. The sensors were aligned resulting in consistent chlorophyll-a and turbidity time series. The corrected chlorophyll-a data was calibrated based on chlorophyll-a values from discrete water samples taken from the CTD rosette Niskin bottles at depths between 9 and 14 m and measured fluorometrically in the lab. A homogenous upper layer was assumed. Only eight data pairs were used for the calibration which is therefore not expected to be very accurate. The calibrated chlorophyll-a time series and corrected turbidity time series were compared against Globcolour CHL1 and SPM-OC5 products, respectively. Details on all quality control steps and the comparison with satellite data can be found in the data processing report. The data set user should keep in mind that some parts of the time series might be affected by non-photochemical quenching, see data processing report. It was out of the scope of the quality control to flag or correct non-photochemical quenching. The resulting data set contains the original data and corresponding quality flags achieved by the quality control algorithm as well as the calibrated chlorophyll-a and corrected turbidity data with corresponding quality flags. The data source is given through the name of the active SMB. The data set contains data during transit time and station work. We recommend to use ship's speed to filter for only transit data.
DOI: 10.1594/pangaea.987819
title: Relative proportions of fatty acids in Melosira assemblages, and subsequently isolated unialgal cultures collected in June 2023 during the RV Kronprins Haakon cruise 2023-1 in Fram Strait

description: During the AO2023-1 expedition (1-21 June 2023), Melosira assemblages were collected using a handpump at a sampling site in Fram Strait. In addition to performing physiological measurements and filtering the material for trophic markers, living material was brought back to Oslo and two strains were established as unialgal cultures. The cultures are maintained in artificial seawater-based L1 medium at 4°C and 25 µmol m-2 s-1 light with a 16:8 L:D cycle. Lipids were extracted from freeze-dried samples following the method of Folch et al. (1957), using a dichloromethane/methanol mixture (2:1, v/v) in a sonication bath. The extracted lipids were converted to fatty acid methyl esters and analyzed by gas chromatography (Agilent 6890N Network GC, Agilent Technologies) equipped with a DB-FFAP capillary column (30 m length, 0.25 mm internal diameter, 0.25 μm film thickness), split injection, and a flame ionization detector. The temperature program ranged from 160°C to 240°C. Fatty acid analysis was conducted to complement datasets on fatty acid stable isotope compositions and sterol proportions. Collectively, the datasets enable a detailed characterization of the biochemical composition of different Melosira arctica-dominated algal assemblages from the Arctic Ocean, and a comparison with a unialgal culture of this important species.
DOI: 10.1594/pangaea.987939
title: Shipboard ADCP current measurements (75 kHz) during RV METEOR cruise M211

description: Current velocities of the upper water column along the cruise track of R/V Meteor cruise M211 were collected by a vessel-mounted 75 kHz RDI Ocean Surveyor ADCP. The ADCP transducer was located at 5.0 m below the water line. The instrument was operated in narrowband mode (WM10) with a bin size of 8.00 m, a blanking distance of 4.00 m, and a total of 100 bins, covering the depth range between 17.0 m and 809.0 m. Attitude data from the ship's motion reference unit were used by the data acquisition software VmDAS internally to convert ADCP beam velocities to geographic coordinates. The Python toolbox OSADCP (version 2.2.0) was used for data post-processing. Acoustic Interferences were identified based on outliers in the ADCP echo intensity data. Echo intensity data were cleaned accordingly and affected velocity cells were flagged to be removed prior ensemble-averaging. The ship's velocity was calculated from position fixes obtained by the Global Navigation Satellite System (GNSS), taking into account lever arms of ADCP transducer and GNSS antenna. Accuracy of the derived water velocities mainly depends on the quality of the position fixes and the ship's heading data. Further errors stem from a misalignment of the transducer with the ship's centerline. Data processing included water track calibration of the misalignment angle (-46.2848° +/- 0.4822°) and scale factor (1.0025 +/- 0.0108) of the measured velocities. The velocity data were averaged in time using an average interval of 60 s. Depth cells with ensemble-averaged percent-good values below 25% are marked as 'bad data'.
DOI: 10.1594/pangaea.987943
title: Continuous optical chlorophyll-a and turbidity data along RV SONNE cruise SO308/2

description: Underway optical chlorophyll-a and turbidity data were collected along the cruise track with Sea-Bird Scientific ECO FLNTU sensors installed within two autonomous measurement systems, called self-cleaning monitoring boxes (SMBs). The SMBs measure alternatingly. While one box is measuring, the other one is being cleaned. The boxes switched generally every 12 hours. The water inlet for the SMBs is at about 4 m below sea surface. Observed chlorophyll-a and turbidity data were both quality controlled. Analysis of the chlorophyll-a and turbidity data during parallel operation of the sensors in the two boxes showed significant differences between the sensors. The sensors were aligned resulting in consistent chlorophyll-a and turbidity time series. The corrected chlorophyll-a data was compared with reference chlorophyll-a from water samples collected with Niskin bottles of the CTD water sampler at 10 m depth and satellite data, the Globcolour CHL1 product. Since the first half of the time series shows 24 h period cycles which are likely connected to non-photochemical quenching which could not be separated from actual changes in biomass, the reference chlorophyll-a samples were not used for calibration. Roughly, high chlorophyll-a values were estimated to be at least a factor three too high. Details on all quality control steps and the comparison with satellite data can be found in the data processing report. It was out of the scope of the quality control to flag or correct non-photochemical quenching. The resulting data set contains the original data and corresponding quality flags achieved by the quality control algorithm as well as the corrected chlorophyll-a and turbidity data with corresponding quality flags. The data source is given through the name of the active SMB. The data set contains data during transit time and station work. We recommend to use ship's speed to filter for only transit data.
DOI: 10.1594/pangaea.987975
title: Dual Nitrate Stable Isotopes of SONNE 303 BIOGIN-IIOE2 cruise in the Equatorial Indian Ocean

description: This dataset includes dual nitrate stable isotope collected at 13 stations of the R/V Sonne cruise SO303 BIOGIN-IIOE2 (23 January – 19 February 2024). Samples were collected at 13 stations at selected water depths from Niskin Bottles attached to the CTD. Dual nitrate stable isotopes were measured during the denitrifier method. This data was used to study nitrogen cycling in the Equatorial Indian Ocean.
DOI: 10.1594/pangaea.988134
title: Harmonized Landsat/Sentinel-2 & SAR Sentinel-1 dataset labeled with UAV-LiDAR-derived forest structural attributes in Alaska and Northwest Canada

description: This dataset presents Harmonized Landsat Sentinel-2 and SAR Sentinel-1 tiles labeled with forest structural information at 86 sites (minimum 50 m by 500 m) in the boreal forests of Alaska and Northwest Canada. UAV-LiDAR data was collected at each site between 2022 and 2024. Canopy height and crown coverage were derived from the point clouds. The HLS pixels were collected as time series for two seasons: peak summer (June 20th to August 10th 2022, 2023, 2024) with 648 tiles, and late summer (August 20th to September 30th, 2022, 2023, 2024) with 258 tiles. We applied a 30 % cloud cover filter and masked remaining clouds, water bodies, and snow with the HLS Fmask bit filters. We computed and added one NDVI band per season. The Sentinel-1 data (VV, VH, angle) were collected for the same seasons (peak and late summer) and pre-processed following Mullissa et al. 2021 (https://doi.org/10.3390/rs13101954 ; https://github.com/adugnag/gee_s1_ard) in python and Google Earth Engine). The median pixel value of HLS and S-1 was taken from the median composites at each site. We resampled the crown coverage and median canopy height with the HLS grid resolution (30 m) and stacked the rasters together.
description: There is one raster per site, containing 25 bands (see read_me file):Band 1 = HLS PS BlueBand 2 = HLS PS GreenBand 3 = HLS PS RedBand 4 = HLS PS NIRBand 5 = HLS PS SWIR 1Band 6 = HLS PS SWIR 2Band 7 = HLS PS NDVIBand 8 = HLS LS BlueBand 9 = HLS LS GreenBand 10 = HLS LS RedBand 11 = HLS LS NIRBand 12 = HLS LS SWIR 1Band 13 = HLS LS SWIR 2Band 14 = HLS LS NDVIBand 15 = Median Canopy Height (meters) (from our raster data)Band 16 = SD canopy heightBand 17 = Minimum Canopy Height value (meters)Band 18 = Maximum Canopy Height value (meters)Band 19 = Crown cover percentage (%)Band 20 = Sentinel-1 PS VH Band 21 = Sentinel-1 PS VVBand 22 = Sentinel-1 PS angleBand 23 = Sentinel-1 LS VH Band 24 = Sentinel-1 LS VVBand 25 = Sentinel-1 LS angle