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215 results for “water DNA”
Catalog of GenBank sequence read archive (SRA) entries of metagenomic DNA sequence analyses of bacterial and archaeal water column communities along the Eastern Beaufort Sea coast, North Slope, Alaska, 2012
In contrast to temperate systems, Arctic lagoons that span the Alaska Beaufort Sea coast face extreme seasonality. Nine months of ice cover up to ∼1.7 m thick is followed by a spring thaw that introduces an enormous pulse of freshwater, nutrients, and organic matter into these lagoons over a relatively brief 2–3 week period. Prokaryotic communities link these subsidies to lagoon food webs through nutrient uptake, heterotrophic production, and other biogeochemical processes, but little is known about how the genomic capabilities of these communities respond to seasonal variability. This study characterizes the metabolic capabilities of microbial communities across three seasons in two lagoons and one open coastal site along the eastern Alaska Beaufort Sea coast. We used metagenomic DNA sequence data of bacterial and archaeal water column communities to identify genes of relevant biogeochemical pathways. This data package catalogs sequence read archive (SRA) entries available through GenBank BioProject PRJNA642637 at https://www.ncbi.nlm.nih.gov/bioproject/PRJNA642637. This data package is associated with the following publication: Baker, Kristina D., Colleen T. E. Kellogg, James W. McClelland, Kenneth H. Dunton, and Byron C. Crump. “The Genomic Capabilities of Microbial Communities Track Seasonal Variation in Environmental Conditions of Arctic Lagoons.” Frontiers in Microbiology 12 (2021). https://doi.org/10.3389/fmicb.2021.601901. Environmental variables (physiochemical data from YSI and HOBO data loggers, as well as organic matter analysis and stable isotope data from discrete water samples) associated with this genomic dataset are available from the Arctic Data Center: Kenneth Dunton, Byron Crump, and James McClelland. Physical, chemical, and biological data from lagoons and open coastal waters in the nearshore environment of the eastern Alaska Beaufort Sea, 2011-2013. Arctic Data Center. doi:10.18739/A2DG13. To join the two datasets together, please use the provi
Isotopes and related data associated with water tracing with environmental DNA in a high-Alpine catchment
<p>Isotopes and related data associated with water tracing with environmental DNA in a high-Alpine catchment<br> Prepared by Natalie Ceperley, February 2020. </p> <p><br> All methods associated with this data are available in the manuscript: Elvira Mächler, Anham Salyani, Jean-Claude Walser, Annegret Larsen, Bettina Schaefli, Florian Altermatt, and Natalie Ceperley. 2019. Water tracing with environmental DNA in a high-Alpine catchment, Hydrology and Earth System Sciences. https://doi.org/10.5194/hess-2019-551. <br> Related data sets are and will be published in the Vallon de Nant Community on Zenodo. Associated sequencing data are publicly available on European Nucleotide Archive (Mächler et al., 2020). </p> <p>All isotope data analyzed in the laboratory of Torsten W. Vennemann at the University of Lausanne. </p> <p> </p> <p><br> All Files:<br> ▪ NaN - No measurement or sample<br> ▪ Details regarding measurement are available in paper or supplement. </p> <p>Files: <br> 1) climate_hydro_2017_daily.csv <br> ⁃ 16 columns: <br> ⁃ 1. day of year with January 1, 2017 = 1<br> ⁃ 2-5. Q: daily mean, min, max, and baseflow discharge as measured at outlet (location ER/MR), in liters / day <br> ⁃ 6. P: mean mm of rain across catchment per day<br> ⁃ 7. SR: total solar radiation per day in W/hr/m2 as median of 4 meteorological stations<br> ⁃ 8-10. SCA: mean, min, and max snow covered area on days with satellite imagery available for whole catchment area, in %<br> ⁃ 11-13. water temperature, mean, min, and max, at outlet (location ER/MR), in degrees C<br> ⁃ 14-16. air temperature, mean, min, and max at 4 meteorological stations, in degrees C</p> <p>2) delta-18-O_permil.csv <br> ⁃ stable isotopes of water (delta 18-O) in per mil<br> ⁃ columns correspond to sampling locations (locations.csv), rows correspond to sampling days (sampledates.csv)</p> <p>3) delta-2-H_permil.csv <br> ⁃ stable isotopes of water (delta 2-H) in per mil<br> ⁃ columns correspond to sampling locations (locations.csv), rows correspond to sampling days (sampledates.csv)</p> <p>4) dqdt_outlet_prev48hrs.csv<br> - dq/dt determined at the outlet for the previous 48 hours at sampling moment (TimeOfSamples_HR.csv) for each sampling site<br> ⁃ columns correspond to sampling locations (locations.csv), rows correspond to sampling days (sampledates.csv)</p> <p><br> 5) ednasamplecount.csv <br> - this is the tally of samples (1 sample includes 4 replicates)<br> ⁃ columns correspond to sampling locations (locations.csv), rows correspond to sampling days (sampledates.csv)</p> <p>6) electricalconductivity_instrument.csv <br> ⁃ Code: <br> 108 - post-analyzed using a glass bodied 6 mm probe in the laboratory (Jenway 4510, Staffordshire, UK). <br> 102 - hand measurement with WTW (multi-3510 with a IDS-tetracon-925, Xylem Analytics, Germany)<br> ⁃ columns correspond to sampling locations (locations.csv), rows correspond to sampling days (sampledates.csv)</p> <p><br> 7) electricalconductivity_uScm.csv <br> - this is the electrical conductivity in micro siemens per cm, according to the instruments coded in electricalconductivity_instrument.csv<br> ⁃ columns correspond to sampling locations (locations.csv), rows correspond to sampling days (sampledates.csv)</p> <p>8) LC-excess.csv <br> - this is the line control execss from the meteoric water line as determined by the samples in the file: precipitationistopemetadata.csv<br> ⁃ columns correspond to sampling locations (locations.csv), rows correspond to sampling days (sampledates.csv)</p> <p>9) locations.csv <br> ⁃ Location codes used in other files. <br> - Coordinates in CH1903 / LV03 and WGS 84 (lat/lon). Elevation in m. asl. </p> <p>10) precipitationisotopemetadata.csv <br> - This is the sampling information for the isotope data that was used to calculate the meteoric water line. <br> - The full data set will become available in a subsequent publication on Zenodo linked to the same community. <br> - 4 columns: <br> - 1. code: rain (1) or snow (2)<br> - 2. collection date and time<br> - 3. elevation in m. asl. <br> - 4. in the case of rain, this is the depth of collection in mm (area normalized volume), in the case of snow, this is the mean depth below the surface that the sample was taken from in cm. <br> ⁃ columns correspond to sampling locations (locations.csv), rows correspond to sampling days (sampledates.csv)</p> <p>11) sampledates.csv <br> - These are the sample dates in day, month, year and day of year corresponding to the rows in other files</p> <p>12) stationlocations.csv<br> - These are the locations of four meteorological stations and discharge measurement station. <br> - Coordinates in CH1903 / LV03 and WGS 84 (lat/lon). Elevation in m. asl. </p> <p>13) TimeOfSamples_HR.csv <br> - This is the time of the sample in hours and decimals correspond to minutes past hour<br> ⁃ columns correspond to sampling locations (locations.csv), rows correspond to sampling days (sampledates.csv)</p> <p>14) watertemperature_degC.csv <br> ⁃ columns correspond to sampling locations (locations.csv), rows correspond to sampling days (sampledates.csv)<br> - measure in degrees C<br> - instrument in watertemperature_instrument.csv</p> <p>15) watertemperature_instrument.csv <br> ⁃ Code: <br> 1 = hand measurement with WTW (multi-3510 with a IDS-tetracon-925, Xylem Analytics, Germany)<br> 2 = HOBO Pendant Temperature/Light Data Logger 64K - UA-002-64", Onset (Bourne, MA, USA)<br> 3 = Continually logging WTW (IDS-tetracon-325, Xylem Analytics, Germany)<br> 4 = Continually logging (10min) HOBO U24-001 Conductivity, Onset (Bourne, MA, USA) <br> ⁃ columns correspond to sampling locations (locations.csv), rows correspond to sampling days (sampledates.csv)</p>
Data from: Sorting states of environmental DNA: Effects of isolation method and water matrix on recovery of membrane-bound, dissolved, and adsorbed states of eDNA
<p>Environmental DNA (eDNA) once shed can exist in numerous states with varying behaviors including degradation rates and transport potential. In this study we consider three states of eDNA: 1) a membrane-bound state referring to DNA enveloped in a cellular or organellar membrane, 2) a dissolved state defined as the extracellular DNA molecule in the environment without any interaction with other particles, and 3) an adsorbed state defined as extracellular DNA adsorbed to a particle surface in the environment. Capturing, isolating, and analyzing a target state of eDNA provides utility for better interpretation of eDNA degradation rates and transport potential. While methods for separating different states of DNA have been developed, they remain poorly evaluated due to the lack of state-controlled experimentation. We evaluated the methods for separating states of eDNA from a single sample by spiking DNA from three different species to represent the three states of eDNA as state-specific controls. We used chicken DNA to represent the dissolved state, cultured mouse cells for the membrane-bound state, and salmon DNA adsorbed to clay particles as the adsorbed state. We performed the separation in three water matrices, two environmental and one synthetic, spiked with the three eDNA states. The membrane-bound state was the only state that was isolated with minimal contamination from non-target states. The membrane-bound state also had the highest recovery (54.11 ± 19.24 %), followed by the adsorbed state (5.08 ± 2.28 %), and the dissolved state had the lowest total recovery (2.21 ± 2.36 %). This study highlights the potential to sort the states of eDNA from a single sample and independently analyze them for more informed biodiversity assessments. However, further method development is needed to improve recovery and reduce cross-contamination.</p>
Data for fitness analyses used in: Environmentally-induced DNA methylation is inherited across generations in water fleas (Daphnia magna)
<p><span>Data of</span> fitness effects of environmental stressors on <em>Daphnia magna</em> over multiple generations. Ages of first and second reproduction, and sizes of first and second brood were measured and used to calculate replacement rate. This data is part of a study on whole-genome bisulphate sequencing on individual <em>Daphnia magna</em> to assess whether environmentally-induced DNA methylation can persist for up to four generations.</p>
Figure 4 in A new water mite species of the genus Teutonia Koenike, 1889 from Corsica, France, based on morphological data and DNA barcodes (Acari, Hydrachnidia, Teutoniidae)
Figure 4 Teutonia corsicanasp. nov., ♂ [CCDB 38559 F09], Ruisseau de Battesta, France: A – coxal and genital field, partial view; B – photograph of ejaculatory complex; C – palp, medial view; D – gnathosoma. Scale bars = 100 μm.
Figure 2 in A new water mite species of the genus Teutonia Koenike, 1889 from Corsica, France, based on morphological data and DNA barcodes (Acari, Hydrachnidia, Teutoniidae)
Figure 2 Results of ASAP analysis for COI sequences. (A) Distribution of pairwise differences, (B) Ranked pairwise differences.
Figure 1 in A new water mite species of the genus Teutonia Koenike, 1889 from Corsica, France, based on morphological data and DNA barcodes (Acari, Hydrachnidia, Teutoniidae)
Figure 1 Neighbour-Joining tree of the genusTeutonia, obtained from 17 nucleotide COI sequences.and the results of species delimitation analyses. Values near branches show bootstrap support (BS). The results of species delimitation by ASAP procedure are indicated by vertical bars. Country codes (alpha-2 code): DE – Germany, FR – France, MN – Montenegro, NO – Norway, TR – Turkey.
Figure 3 in A new water mite species of the genus Teutonia Koenike, 1889 from Corsica, France, based on morphological data and DNA barcodes (Acari, Hydrachnidia, Teutoniidae)
Figure 3 Teutonia corsicanasp. nov. (A-B, D-G – holotype ♀, Ruisseau de Tuara, France; C – ♀ [CCDB 38559 D12], preserved specimen, Riviere La Solenzara, France): A – coxal and genital field; B, C – genital field; D – palp, medial view (P-1 lacking); E – palp, lateral view; F – I-L-5 and -6; G – IV-L-5 and -6. Scale bars = 100 μm.
Figure 5 in A new water mite species of the genus Teutonia Koenike, 1889 from Corsica, France, based on morphological data and DNA barcodes (Acari, Hydrachnidia, Teutoniidae)
Figure 5 Teutonia cometes(Koch, 1837), ♀, Danilovgrad, spring under the bridge over the Zeta river, Montenegro: A – genital field; B – palp, medial view. Scale bar = 100 μm.
Figure 1 in Hydrodroma angelieri (Acari, Hydrachnidia: Hydrodromidae) a new water mite species from Corsica based on morphological and DNA barcode evidence
Figure 1 Hydrodroma angelieri sp. nov., holotype ♀, Tributary of Ruisseau de Canne, France: A – integument papillae; B – coxal field; C – genital field; D – palp, lateral view; E – palp, medial view; F – gnathosoma; G – chelicera. Scale bars = 100 μm.
Figure 3 in Checklist of Water mites in Mexico. Historical background and DNA barcoding perspectives
Figure 3 Neighbor joining tree based on all worldwideNeumaniaCOI sequences. The name is followed by the barcode index number (BIN). * Without data collection.
Fig. 3 in New record of blunthead pufferfish, Sphoeroides pachygaster (Muller & Troschel, 1848) (Tetraodontiformes: Tetraodontidae) from Indian water along with DNA barcode and some biological aspects
Fig. 3 — Phylogenetic tree topology for Sphoeroides pachygaster (Müller & Troschel, 1848) with sister species based on 16S gene sequences using maximum likelihood method
Fig. 2 in New record of blunthead pufferfish, Sphoeroides pachygaster (Muller & Troschel, 1848) (Tetraodontiformes: Tetraodontidae) from Indian water along with DNA barcode and some biological aspects
Fig. 2 — Histological section of gonad of S. pachygaster from the Indian water (10 µm thickness observed at 10X and 40X magnification). Fe: Follicular epithelium cells, Zr: Zona radiata, Yg: Yolk globules, Ysg: Egg yolk granules, and Af: Atretic follicle
Text-fig. 4. Electrophoresis after amplification: Electrophoretical analysis of mitochondrial DNA. mtDNA sequences were amplified by primers F15.412 and R16.169 (450 bp), R16.269 (550 bp), R16.519 (800 bp). Lane 1 are primers F15.412 + R16.169, lane 2 primers F15.412 + R16.269, lane 3 primers F15.412 + R16.519, NC – negative control – water, L – 100 bp DNA ladder (band size from 100 bp to 1500 bp). in Genetic Analysis Of Possibly The Oldest Greyhound Remains Within The Territory Of The Czech Republic As Proof Of A Local Elite Presence At Chotěbuz-Podobora Hillfort In The 8 -9 Century Ad
Text-fig. 4. Electrophoresis after amplification: Electrophoretical analysis of mitochondrial DNA. mtDNA sequences were amplified by primers F15.412 and R16.169 (450 bp), R16.269 (550 bp), R16.519 (800 bp). Lane 1 are primers F15.412 + R16.169, lane 2 primers F15.412 + R16.269, lane 3 primers F15.412 + R16.519, NC – negative control – water, L – 100 bp DNA ladder (band size from 100 bp to 1500 bp).
Figure 1 in An updated checklist of water mites (Acari, Hydrachnidia) of Serbia with new records revealed by DNA barcodes
Figure 1. Photographs of selected sampling sites: A – Visočica river, Pirot, Eastern Serbia (sampling site of Lebertia glabra, Torrentcola barsica, T. laskai and Atractides glandulosus). B – Vlasina, Milovanci, pond (sampling site of Arrenurus bruzelii and A. virens). C – Vlasina, Murinska reka, helocrenic springs and stream (sampling site of Hydryphantes parmulatus and Lebertia stigmatifera). Photos by V. Pešić.
Figure 2 in New records and first DNA barcodes of water mites (Acari, Hydrachnidia) from Georgia
Figure 2. Photographs of selected sampling sites: A – unnamed pond (Javakheti); B – Lake Saghamo; C – pond near Ozaani; D – Paravani Lake. Photos by L. Mumladze.
Figure 1 in New records and first DNA barcodes of water mites (Acari, Hydrachnidia) from Georgia
Figure 1. Thyasides dentatus (Thor, 1897), ♀, unnamed Pond (Javakheti), Georgia. Photographs of genital field (A) and palp (B).
Figure 7A-C in New DNA-assisted records of water mites from Sardinia, with the description of a new species (Acari, Hydrachnidia)
Figure 7A-C. Atractides disabatinoi sp. nov., paratype ♀ [CCDB_44310_HO6], ITALY, Sardinia, Comune di Fluminimaggiore, Sorgente Pubusinu, It 2022-1c. A – coxal and genital field; B – palp, medial view; C – I-L-5 and -6. Scale bar = 100 μm.
Figure 8 in New DNA-assisted records of water mites from Sardinia, with the description of a new species (Acari, Hydrachnidia)
Figure 8. Neighbour-Joining tree of the genus Atractides obtained from 64 nucleotide COI sequences. The results of species delimitation by ASAP procedure are indicated by vertical bars.
Figure 6A-E in New DNA-assisted records of water mites from Sardinia, with the description of a new species (Acari, Hydrachnidia)
Figure 6A-E Atractides disabatinoi sp. nov., holotype ♂ [CCDB_44301_HO9], ITALY, Sardinia, Comune di Fluminimaggiore, outflow of Sorgente Pubusinu, It 2022-2a. A – IV-L-4 and -5 (arrow indicate pointed lateral sheet covering the articulation of the next segment); B – genital field; C – I-L-5 and -6; D – palp, lateral view; E – palp, medial view. F A. robustus (Sokolow, 1940), ♂, MONTENEGRO, Morača river: genital field. Scale bars = 100 μm.
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Allen Brain Atlas
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