Use Of Detection Tools Research Articles

Development of environmental DNA (eDNA) methods for detecting high-risk freshwater fishes in live trade in Canada

Preventing the arrival, establishment, and spread of aquatic invasive species is an important step in protecting our aquatic environments. The use of detection tools, like DNA barcoding technologies, high-throughput sequencing and environmental DNA (eDNA) monitoring, is becoming increasingly important in preventing the introduction of potential invasive species. The combination of eDNA with realtime PCR (qPCR) provide the opportunity to have a rapid and specific detection. In this study, we developed a DNA sequence library that has sufficient depth and species coverage such that high-risk species can be confidently discriminated from legitimately imported and native species. A total of 12 species-specific qPCR assays were developed for the detection of 13 potential invasive species (pAIS) in bulk water samples. Detection of these species was also compared with a HTS approach. We have demonstrated the high sensitivity of qPCR assays using eDNA at very low densities, suggesting we could detect a low number of individuals mixed with non-target species in a simulated live shipment. For the detection of a targeted list of species, qPCR is advantageous. The mini-barcodes developed in this project offered a good sensitivity of detection, and HTS is a discovery tool that can be desirable when unlisted or numerous species need to be identified.

Quantifying Research Integrity

Institutions typically treat research integrity violations as black and white, right or wrong. The result is that the wide range of grayscale nuances that separate accident, carelessness and bad practice from deliberate fraud and malpractice often get lost. This lecture looks at how to quantify the grayscale range in three kinds of research integrity violations: plagiarism, data falsification, and image manipulation. Quantification works best with plagiarism, because the essential one-to one matching algorithms are well known and established tools for detecting when matches exist. Questions remain, however, how many matching words of what kind in what location in which discipline constitute reasonable suspicion of fraudulent intent. Different disciplines take different perspectives on quantity and location. Quantification is harder with data falsification, because the original data are often not available, and because experimental replication remains surprisingly difficult. The same is true with image manipulation, where tools exist for detecting certain kinds of manipulations, but where the tools are also easily defeated. This lecture looks at how to prevent violations of research integrity from a pragmatic viewpoint, and at what steps can institutions and publishers take to discourage problems beyond the usual ethical admonitions. There are no simple answers, but two measures can help: the systematic use of detection tools and requiring original data and images. These alone do not suffice, but they represent a start. The scholarly community needs a better awareness of the complexity of research integrity decisions. Only an open and wide-spread international discussion can bring about a consensus on where the boundary lines are and when grayscale problems shade into black. One goal of this work is to move that discussion forward.