This data set includes qPCR data for the microcystin producing planktothrix (mcyApla) gene and the microcystin producing cyanobacteria (Hep) gene for samples collected from Grand Lake St. Marys and downstream waterways in 2025.

This data set includes qPCR data for the microcystin producing planktothrix (mcyApla) gene and the microcystin producing cyanobacteria (Hep) gene for samples collected from Grand Lake St. Marys and downstream waterways in 2023.

This data set includes qPCR data for the microcystin producing planktothrix (mcyApla) gene and the microcystin producing cyanobacteria (Hep) gene for samples collected from Grand Lake St. Marys and downstream waterways in 2024.

This Dataset includes the spatial and temporal quantification of planktothrix cyanobacteria filaments within the canal and river system of St. Mary's, OH for the year 2023.

This Dataset includes the spatial and temporal quantification of planktothrix cyanobacteria filaments within the canal and river system of St. Mary's, OH for the year 2022.

Water sample data collected and curated by Ohio State University's Stone Laboratory and others between 2013 and 2024 in Lake Erie. The samples were collected in part of several projects funded by various state (Ohio EPA and Ohio Sea Grant) and federal agencies (US EPA, NSF, NIH, NOAA). The program column describes who or why the samples were collected. The captains program is a partnership between Stone Lab and the Lake Erie Charter Boat Association in which the captains collect water samples and Stone Lab analyzes them (https://ohioseagrant.osu.edu/products/4c0k6/charter-boat-captains-help-monitor-lake-erie-water-quality). The SL Buoy program is a high temporal resolution dataset of grab samples paired with a high temporal resolution sonde data attached to a buoy (https://doi.org/10.1007/s11356-018-2612-z). The HABs Grab were high spatial resolution samples collected on two days during peak blooms of 2018 and 2019 (https://doi.org/10.1016/j.hal.2021.102080). The flow-through program was an attempt to collect water quality data throughout the winter by pumping lake water into the research building at Stone Lab. Programs Stone Lab and UToledo were samples collected by Stone Lab and UT Lake Erie Center from research vessels at routinely monitored locations. Samples were analyzed for chlorophyll a (an indicator of algae biomass), microcystins (a group of toxins produced by cyanobacteria), total phosphorus and nitrogen (indicators of maximum biomass potential), dissolved nitrate, phosphate, and silicate (nutrients available for algae), and total suspended solids (mass of all particulates in the water).

qPCR and RT-qPCR. This dataset is associated with the following publication: Lu, J., I. Struewing, L. Wymer, D. Tettenhorst, J. Shoemaker, and J. Allen. Use of qPCR and RT-qPCR for monitoring variations of microcystin producers and as an early warning system to predict toxin production in an Ohio inland lake. WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, 170: 115262, (2020).

The data include sequences, qPCR, RT-qPCR, water nutrients and cyanotoxins.

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Monitoring the community structure and metabolic activities of cyanobacterial blooms in Upper Klamath Lake, Oregon, is critical to lake management because these blooms degrade water quality and produce toxic microcystins that are harmful to humans, domestic animals, and wildlife. Genetic tools, such as DNA fingerprinting by terminal restriction fragment length polymorphism (T-RFLP) analysis, high-throughput DNA sequencing (HTS), and real-time, quantitative polymerase chain reaction (qPCR) provide more sensitive and rapid assessments of bloom ecology than traditional techniques. The objectives of this study were (1) to characterize the microbial community at one site in Upper Klamath Lake and determine changes in the cyanobacterial community through time using T-RFLP and HTS in comparison with traditional light microscopy; (2) to determine relative abundances and changes in abundance over time of toxigenic Microcystis using qPCR; and (3) to determine relative abundances and changes in abundance over time of Aphanizomenon, Microcystis, and total cyanobacteria using qPCR. T-RFLP analysis of total cyanobacteria showed a dominance of only one or two distinct genotypes in samples from 2013, but results of HTS in 2013 and 2014 showed more variations in the bloom cycle that fit with the previous understanding of bloom dynamics in Upper Klamath Lake and indicated that potentially toxigenic Microcystis was more prevalent in 2014 than in years prior. The qPCR-estimated copy numbers of all target genes were higher in 2014 than in 2013, when microcystin concentrations also were higher. Total Microcystis density was shown with qPCR to be a better predictor of late-season increases in microcystin concentrations than the relative proportions of potentially toxigenic cells. In addition, qPCR targeting Aphanizomenon at one site in Upper Klamath Lake indicated a moderate bloom of this species (corresponding to chlorophyll a concentrations between approximately 75 and 200 micrograms per liter) from mid-June to mid-August, 2014. After August 18, the Aphanizomenon bloom was overtaken by Microcystis late in the season as microcystin concentrations peaked. Overall, results of this study showed how DNA-based, genetic methods may provide rapid and sensitive diagnoses for the presence of toxigenic cyanobacteria and that they are useful for general monitoring or ecological studies and identification of cyanobacterial community members in complex aquatic habitats. These same methods can also be used to simultaneously address spatial (horizontal and vertical) and temporal variation under different conditions. Additionally, with some modifications, the same techniques can be applied to different sample types, including water, sediment, and tissue.