DNA barcoding gene sequences and files associated with their analysis

This file includes the following data for 25 stream sites in the Little Miami River watershed: diatom operational taxonomic units with their numbers and relative abundances of rbcL gene sequence reads, watershed land cover, and nutrient concentration and conductivity data. This dataset is associated with the following publication: Yuan, L., N. Smucker, C. Nietch, and E. Pilgrim. Quantifying spatial and temporal relationships between diatoms and nutrients in streams strengthens evidence of nutrient effects from monitoring data. Freshwater Science. The Society for Freshwater Science, Springfield, IL, 41(1): 100-112, (2022).

LMR watershed temporal DNA metabarcoding 2016 study. This dataset is associated with the following publication: Smucker, N., E. Pilgrim, H. Wu, C. Nietch, J. Darling, M. Molina, B. Johnson, and L. Yuan. Characterizing temporal variability in streams supports nutrient indicator development using diatom and bacterial DNA metabarcoding. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 831: 154960, (2022).

LMR watershed temporal DNA metabarcoding 2016 study. This dataset is associated with the following publication: Smucker, N., E. Pilgrim, H. Wu, C. Nietch, J. Darling, M. Molina, B. Johnson, and L. Yuan. Characterizing temporal variability in streams supports nutrient indicator development using diatom and bacterial DNA metabarcoding. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 831: 154960, (2022).

These raw data associated with this research were collected as part of the United States Environmental Protection Agency's 2018-2019 National Rivers and Streams Assessment (NRSA). The worksheet "Water chemistry data" includes environmental variables examined in this study including total phosphorus (TP), total nitrogen (TN), conductivity, pH, and ecoregion. The worksheet "Diatom ASVs" includes relative abundances of gene sequence reads for each amplicon sequence variant (ASV), which are referred to as taxa. This dataset is associated with the following publication: Smucker, N., E. Pilgrim, C. Nietch, L. Gains-Germain, C. Carpenter, J. Darling, L. Yuan, R. Mitchell, and A. Pollard. Using DNA metabarcoding to characterize national scale diatom-environment relationships and to develop indicators in streams and rivers of the United States. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 939: 173502, (2024).

Raw data associated with this research. This dataset is associated with the following publication: Yuan, L., R. Mitchell, E. Pilgrim, and N. Smucker. Inferences based on diatom compositions improve estimates of nutrient concentrations in streams. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 952: 176032, (2024).

DNA sequences--already publicly available

Data associated with the Hydrobiologia article titled "Spatial and temporal dynamics of a freshwater eukaryotic plankton community revealed via 18S rRNA gene metabarcoding." They include the number of reads and assigned taxonomies for each observational taxonomic unit (OTU) within each sampling date and location. This dataset is associated with the following publication: Banerji, A., M. Bagley, M. Elk, E. Pilgrim, J. Martinson, and J. Santodomingo. Spatial and temporal dynamics of a freshwater eukaryotic plankton community revealed via 18S rRNA gene metabarcoding. HYDROBIOLOGIA. Springer, New York, NY, USA, 818(1): 71-86, (2018).

Data associated with the Hydrobiologia article titled "Spatial and temporal dynamics of a freshwater eukaryotic plankton community revealed via 18S rRNA gene metabarcoding." They include the number of reads and assigned taxonomies for each observational taxonomic unit (OTU) within each sampling date and location. This dataset is associated with the following publication: Banerji, A., M. Bagley, M. Elk, E. Pilgrim, J. Martinson, and J. Santodomingo. Spatial and temporal dynamics of a freshwater eukaryotic plankton community revealed via 18S rRNA gene metabarcoding. HYDROBIOLOGIA. Springer, New York, NY, USA, 818(1): 71-86, (2018).

To evaluate the ability of precipitation-based environmental DNA (eDNA) sample collection and mitochondrial 12S metabarcoding sequencing to reconstruct well-studied fish communities in lakes and rivers. Specific objectives were to 1) determine correlations between eDNA species detections and known community composition based on traditional field sampling, 2) compare efficiency of eDNA to detect fish biodiversity among systems with variable morphologies and trophic states, and 3) determine if species habitat preferences predicts eDNA detection. Fish community composition was estimated for seven lakes and two MIssissippi River navigation pools using sequence data from the mitochonrial 12S gene amplified from 10 to 50 water samples per waterbody collected in 50-mL centrifuge tubes at a single time point. Environmental DNA (eDNA) was concentrated without filtration by centrifuging samples to reduce per-sample handling time. Taxonomic detections from eDNA were compared to established community monitoring databases containing up to 40 years of sampling and a detailed habitat/substrate preference matrix to identify patterns of bias. Mitochondrial 12S gene metabarcoding detectec 15-47% of the known species at each waterbody and 30-76% of known genera. Non-metric multidimensional scaling (NMDS) assessment of the community structure indicated that eDNA detected communities grouped in a similar pattern as known communities. Discriminant analysis of principal components indicated that there was a high degree of overlap in habitat/substrate preference of eDNA detected and eDNA undetected species suggesting limited habitat bias for eDNA sampling. Large numbers of small volume samples sequenced at the mitochondrial 12S gene can describe the course community structure of freshwater systems. However, additional traditional sampling and environmental DNA sampling may be necessary for a complete diversity census.