Project description:Population scale sweeps of viral pathogens, such as SARS-CoV-2, require high intensity testing for effective management. However, reliable systems affording parallel testing of thousands of patients for pathogen infection have not yet been routinely employed. Here we describe “Systematic Parallel Analysis of RNA coupled to Sequencing for Covid-19 screening” (C19-SPAR-Seq), a multiplexed, readily automated platform for SARS-CoV-2 detection capable of analyzing tens of thousands of patient samples in a single instrument run. To address strict requirements for control of assay parameters and output demanded by clinical diagnostics, we employed a control-based Precision-Recall and Receiver Operator Characteristics (coPR) analysis to assign run-specific quality control metrics. C19-SPAR-Seq coupled to coPR on a trial cohort of several hundred patients performed with a specificity of 100% and sensitivity of 91% on samples with low viral loads. Our study thus establishes the feasibility of employing C19-SPAR-Seq for the large-scale monitoring of SARS-CoV-2 and other pathogens.
Project description:As part of the EcoToxChip project, 49 distinct exposure studies were conducted on three lab model species (Japanese quail, fathead minnow, African clawed frog) and three ecologically relevant species (double crested cormorant, rainbow trout, northern leopard frog), at multiple life stages (embryo, adult), exposed to eight chemicals of environmental concern (ethinyl estradiol-EE2, hexabromocyclododecane-HBCD, lead-Pb, selenomethionine-SeMe, 17β trenbolone-TB, chlorpyrifos-CPF, fluoxetine-FLX, and benzo [a] pyrene-BaP. Whole transcriptome analyses were conducted on these samples resulting in a rich RNA seq dataset covering various species, life stages and chemicals, which is one of the largest purposeful complications of RNA seq data within ecotoxicology. Recently, a unified bioinformatics platform of relevance to ecotoxicology, EcoOmicsAnalyst and ExpressAnalyst, was developed to facilitate RNA Seq analysis of non-model species lacking a reference transcriptome. The platform uses the Seq2Fun algorithm to map RNA-seq reads from eukaryotic species to an ortholog database comprised of protein sequences from >600 eukaryotic species (EcoOmicsDB) with a translated search. The availability of these tools presents a unique opportunity to examine the EcoToxChip RNA Seq dataset for cross species comparisons. This work shows the potential of the EcoOmicsAnalyst and Seq2Fun platform to facilitate fast and simple analysis of RNA Seq datasets from non-model organisms with unannotated genomes and conduct comparative transcriptomic analysis across various species and life stages for cross-species extrapolation.