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167 results for “Metagenomic DNA”
Supplementary material 1 from: Lee T, Alemseged Y, Mitchell A (2018) Dropping Hints: Estimating the diets of livestock in rangelands using DNA metabarcoding of faeces. Metabarcoding and Metagenomics 2: e22467. https://doi.org/10.3897/mbmg.2.22467
Location of sample sites in south-western New South Wales, Australia. Location of study area shown as a rectangle on the map of Australia (insert). Names of states and territories are marked. Solid lines indicate state boundaries. Dashed line indicates the course of the Darling River. Dotted line indicates the course of the Great Darling Anabranch. Circles indicate sampling locations, squares indicate towns. Created using Inkscape 0.92.0 (https://inkscape.org/en/). Based on information from Geoscience Australia, Commonwealth of Australia 'National base map with external territories', (http://www.ga.gov.au/interactive-maps/#/theme/national-location-information/map/nationalmap) published under the Creative Commons license CC-By-Au.
Supplementary material 8 from: Ushio M, Murakami H, Masuda R, Sado T, Miya M, Sakurai S, Yamanaka H, Minamoto T, Kondoh M (2018) Quantitative monitoring of multispecies fish environmental DNA using high-throughput sequencing. Metabarcoding and Metagenomics 2: e23297. https://doi.org/10.3897/mbmg.2.23297
The relationship between MiSeq sequence reads and DNA copy numbers quantified by qPCR. Correlations for the total fish eDNA (all data, a; enlarged figure, b), Japanese anchovy (Engraulis japonicus; all data, c; enlarged figure, d) and Japanese jack mackerel (Trachurus japonicus; all data, e; enlarged figure, f). Dashed and soild lines indicate 1:1 line and linear regression line, respectively. Regression lines in the enlarged figures were drawn by excluding outliers. All regression lines, except for the lines for total fish eDNA, were significant (P < 0.05). Dotted boxed regions in a, c and e correspond to the range of the graphs in b, d and f, respectively. The intensity of red colour indicates the slope of the regression line used to convert sequence reads to the copy numbers.
Supplementary material 13 from: Lee T, Alemseged Y, Mitchell A (2018) Dropping Hints: Estimating the diets of livestock in rangelands using DNA metabarcoding of faeces. Metabarcoding and Metagenomics 2: e22467. https://doi.org/10.3897/mbmg.2.22467
Species level taxa (GenBank Data), at 3 minimum read depth. Underlined taxa were changed based on the distribution of taxa in the study zone.
Supplementary material 2 from: Lee T, Alemseged Y, Mitchell A (2018) Dropping Hints: Estimating the diets of livestock in rangelands using DNA metabarcoding of faeces. Metabarcoding and Metagenomics 2: e22467. https://doi.org/10.3897/mbmg.2.22467
Table displaying the closest matches on the BOLD database for the 24 reference samples for matK, rbcL and ITS2.
Supplementary material 15 from: Lee T, Alemseged Y, Mitchell A (2018) Dropping Hints: Estimating the diets of livestock in rangelands using DNA metabarcoding of faeces. Metabarcoding and Metagenomics 2: e22467. https://doi.org/10.3897/mbmg.2.22467
Species level taxa (BOLD Data), at 3 minimum read depth. Underlined taxa were changed based on the distribution of taxa in the study zone
Supplementary material 10 from: Lee T, Alemseged Y, Mitchell A (2018) Dropping Hints: Estimating the diets of livestock in rangelands using DNA metabarcoding of faeces. Metabarcoding and Metagenomics 2: e22467. https://doi.org/10.3897/mbmg.2.22467
Tests for normailty and equality of variance to establish whether conducting t-tests on the Dorper and Merino speccies and family level diversity data is appropriate.
Supplementary material 6 from: Lee T, Alemseged Y, Mitchell A (2018) Dropping Hints: Estimating the diets of livestock in rangelands using DNA metabarcoding of faeces. Metabarcoding and Metagenomics 2: e22467. https://doi.org/10.3897/mbmg.2.22467
Species level taxa (BOLD Data). Underlined taxa were changed based on the distribution of taxa in the study zone ('*' indicates that the column contains no taxa).
Supplementary material 4 from: Ushio M, Murakami H, Masuda R, Sado T, Miya M, Sakurai S, Yamanaka H, Minamoto T, Kondoh M (2018) Quantitative monitoring of multispecies fish environmental DNA using high-throughput sequencing. Metabarcoding and Metagenomics 2: e23297. https://doi.org/10.3897/mbmg.2.23297
The relationship between MiSeq sequence reads and copy numbers of standard DNAs for 52 samples. Blue line indicates the linear regression between sequence reads and copy numbers. The regression lines are used to convert the MiSeq reads into the calculated copy numbers. Numbers in a grey region indicate sampling date. Note that regression slopes are different amongst samples, i.e. the number of sequence reads generated per eDNA copy is different amongst samples.
Supplementary material 11 from: Lee T, Alemseged Y, Mitchell A (2018) Dropping Hints: Estimating the diets of livestock in rangelands using DNA metabarcoding of faeces. Metabarcoding and Metagenomics 2: e22467. https://doi.org/10.3897/mbmg.2.22467
Shapiro-Wilk and Levene's tests exploring the appropriateness of the data for use in ANOVA or Kruskal-Wallis tests.
Supplementary material 5 from: Ushio M, Murakami H, Masuda R, Sado T, Miya M, Sakurai S, Yamanaka H, Minamoto T, Kondoh M (2018) Quantitative monitoring of multispecies fish environmental DNA using high-throughput sequencing. Metabarcoding and Metagenomics 2: e23297. https://doi.org/10.3897/mbmg.2.23297
The relationship between regression residuals and copy numbers of standard DNAs for 52 samples. Dashed line indicates zero residuals.
Supplementary material 3 from: Li Y, Evans NT, Renshaw MA, Jerde CL, Olds BP, Shogren AJ, Deiner K, Lodge DM, Lamberti GA, Pfrender ME (2018) Estimating fish alpha- and beta-diversity along a small stream with environmental DNA metabarcoding. Metabarcoding and Metagenomics 2: e24262. https://doi.org/10.3897/mbmg.2.24262
The longitudinal distance (upper triangular) and β- diversity (lower triangular) between sampling locations along Eagle Creek. :
Supplementary material 4 from: Li Y, Evans NT, Renshaw MA, Jerde CL, Olds BP, Shogren AJ, Deiner K, Lodge DM, Lamberti GA, Pfrender ME (2018) Estimating fish alpha- and beta-diversity along a small stream with environmental DNA metabarcoding. Metabarcoding and Metagenomics 2: e24262. https://doi.org/10.3897/mbmg.2.24262
Mantel r and p-values for all the pairwise comparisons between single marker, three markers and longitudinal distance. :
Supplementary material 5 from: Li Y, Evans NT, Renshaw MA, Jerde CL, Olds BP, Shogren AJ, Deiner K, Lodge DM, Lamberti GA, Pfrender ME (2018) Estimating fish alpha- and beta-diversity along a small stream with environmental DNA metabarcoding. Metabarcoding and Metagenomics 2: e24262. https://doi.org/10.3897/mbmg.2.24262
The correlation between environmental variables and β-diversity and longitudinal distance using Mantel test :
Supplementary material 2 from: Hubancheva A, Bozicevic V, Morinière J, Goerlitz HR (2023) DNA metabarcoding data from faecal samples of the lesser (Myotis blythii) and the greater (Myotis myotis) mouse-eared bats from Bulgaria. Metabarcoding and Metagenomics 7: e106844. https://doi.org/10.3897/mbmg.7.106844
Taxonomic relationships and relative abundance of prey and parasite species in faecal samples from M. myotis and M. blythii from Bulgaria
Supplementary material 9 from: Macher T-H, Schütz R, Yildiz A, Beermann AJ, Leese F (2023) Evaluating five primer pairs for environmental DNA metabarcoding of Central European fish species based on mock communities. Metabarcoding and Metagenomics 7: e103856. https://doi.org/10.3897/mbmg.7.103856
Processed TaXon tables of each primer pair (subtracted negative controls and filtered for fish and lamprey taxa OTUs)
Supplementary material 1 from: Macher T-H, Schütz R, Yildiz A, Beermann AJ, Leese F (2023) Evaluating five primer pairs for environmental DNA metabarcoding of Central European fish species based on mock communities. Metabarcoding and Metagenomics 7: e103856. https://doi.org/10.3897/mbmg.7.103856
Pairwise comparison of the log-transformed reads of the non-normalized mock community (MC1) compared to the DNA concentration (ng/ul) of each species
Supplementary material 3 from: Macher T-H, Schütz R, Yildiz A, Beermann AJ, Leese F (2023) Evaluating five primer pairs for environmental DNA metabarcoding of Central European fish species based on mock communities. Metabarcoding and Metagenomics 7: e103856. https://doi.org/10.3897/mbmg.7.103856
Sampled specimens and their respective species assignment collected for the fish mock community, extraction date, collection site, and concentration after DNA extraction
Supplementary material 4 from: Macher T-H, Schütz R, Yildiz A, Beermann AJ, Leese F (2023) Evaluating five primer pairs for environmental DNA metabarcoding of Central European fish species based on mock communities. Metabarcoding and Metagenomics 7: e103856. https://doi.org/10.3897/mbmg.7.103856
List of all species reported from Germany, their occurrence status, and their presence in the mock community (data from fishbase.org)
Supplementary material 2 from: Macher T-H, Schütz R, Yildiz A, Beermann AJ, Leese F (2023) Evaluating five primer pairs for environmental DNA metabarcoding of Central European fish species based on mock communities. Metabarcoding and Metagenomics 7: e103856. https://doi.org/10.3897/mbmg.7.103856
Pairwise comparison of the log-transformed reads of the non-normalized mock community (MC1) compared to log-transformed reads of the normalized mock community (MC2) of each species
Supplementary material 1 from: Duarte S, Vieira PE, Costa FO (2020) Assessment of species gaps in DNA barcode libraries of non-indigenous species (NIS) occurring in European coastal regions. Metabarcoding and Metagenomics 4: e55162. https://doi.org/10.3897/mbmg.4.55162
Supplementary figures and tables used to analyse the data
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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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.