EPA Method 1615 measures enteroviruses and noroviruses present in environmental and drinking waters. The viral ribonucleic acid (RNA) from water sample concentrates is extracted and tested for enterovirus and norovirus RNA using reverse transcription-quantitative PCR (RT-qPCR). Virus concentrations for the molecular assay are calculated in terms of genomic copies of viral RNA per liter based upon a standard curve. The method uses a number of quality controls to increase data quality and to reduce interlaboratory and intralaboratory variation. The method has been evaluated by examining virus recovery from ground and reagent grade waters seeded with poliovirus type 3 and murine norovirus as a surrogate for human noroviruses. Mean poliovirus recoveries were 20% in groundwaters and 44% in reagent grade water. Mean murine norovirus recoveries with the RT-qPCR assay were 31% in groundwaters and 4% in reagent grade water.

This dataset is associated with the following publication: Fout , S., J. Cashdollar , S. Griffin , N. Brinkman , E. Varughese , and S. Parshionikar. EPA Method 1615. Measurement of Enterovirus and Norovirus Occurrence in Water by Culture and RT-qPCR. Part III. Virus Detection by RT-qPCR. Journal of Visualized Experiments. JoVE, Somerville, MA, USA, 107: e52646, (2016).

In biological research, qPCR is a technique that is frequently used to measure gene expression levels. The calculation of gene amplification efficiency is a critical step in the processing of qPCR data since it helps to decide which method to employ to compute gene expression levels. Here, we introduce the R package qPCRtools, which enables users to analyze the efficiency of gene amplification. Additionally, this software can determine gene expression levels using one of three approaches: the conventional curve-based method, the 2−ΔΔCt method, and the SATQPCR method. The qPCRtools package produces a table with the statistical data of each method as well as a figure with a box or bar plot illustrating the results. The R package qPCRtools is freely available at CRAN (https://CRAN.R-project.org/package=qPCRtools) or GitHub (https://github.com/lixiang117423/qPCRtools/tree/main/CRAN/qPCRtools).

aFor gene names, refer to Table 3bNegative fold changes correspond to down-regulation of gene expression in cocaine tissue relative to control tissue.

Concentration estimates for HF183/BFDrev and HumM2 qPCR genetic markers in raw sewage collected from 54 geographic locations across the United States. This dataset is associated with the following publication: Boehm, A., J. Soller, and O. Shanks. Human-Associated Fecal qPCR Measurements and Predicted Risk of Gastrointestinal Illness in Recreational Waters Contaminated with Raw Sewage. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 2: 270-275, (2015).

The raw data of the sensitivity and reproducibility of TaqMan qPCR. The assay was evaluated using DNA of adult female P. pseudoannulata individuals at various time periods after the consumption of three adult D. melanogaster and a tenfold gradient dilution of standards ranging from 1.62 × 109 to 1.62 × 100 copies/μL.

Please see the inserted text box within this excel file for a description of the included data.

Plants respond to environmental stresses through controlled stem cell maintenance and meristem activity. One level of transcriptional control is RNA alternative splicing. However the mechanistic link between stress, meristem function and RNA splicing is poorly understood. The MERISTEM-DEFECTIVE (MDF)/DEFECTIVELY ORGANIZED TRIBUTARIES (DOT2) gene of Arabidopsis encodes a SR-related family protein, required for meristem function and leaf vascularization, and is the likely orthologue of the human SART1 and yeast snu66 splicing factors. MDF is required for the correct splicing and expression of key transcripts associated with root meristem function. We identified RSZ33 and ACC1, both known to regulate cell patterning, as splicing targets required for MDF function in the meristem. MDF expression is modulated by osmotic and cold stress, associated with differential splicing and specific isoform accumulation and shuttling between nucleus and cytosol, and acts in part via a splicing target SR34. We propose a model in which MDF controls splicing in the root meristem to promote stemness and repress stress response and cell differentiation pathways. Methods RNA extraction and sequencing RNA was extracted from three independent biological replicates using 7-day-old seedlings (ca. 100 mg tissue) grown on half-strength MS10 medium using the Sigma-Aldrich Plant Total RNA Kit (catalog number STRN50), with the On-Column DNase I Digestion Set (catalog Number: DNASE10-1SET) to eliminate any residual DNA molecules. Plant tissue was ground in liquid nitrogen before incubation in a lysis solution containing 2-mercaptoethanol at 65°C for 3 minutes. The solid debris was removed by centrifuging and 14 000 x g and column filtration before RNA was captured onto a binding column using the supplied binding solution, which helps preventing polysaccharide and genomic DNA from clogging the column. Most DNA was removed by wash solutions, and any trace of residual DNA was removed by DNase on the column. Then purified RNA was eluted using RNAase-free water. RNA sequencing from three biological replicate samples was carried out on an Illumina HiSeq 2500 System with the library prepared using the Illumina TruSeq Stranded Total RNA with Ribo-Zero Plant Sample Preparation kit (catalog Number: RS-122-2401). Ribosomal RNA (rRNA) was removed from isolated total RNA using biotinylated, target-specific oligos on rRNA removal beads. Purified RNA was quality checked using a TapeStation 2200 (Agilent Technology) with High Sensitivity RNA ScreenTape (catalog Number: 5067-5579), and the mRNA was fragmented into 120-200 bp sequences with a median size of 150 bp. Fragmented mRNA was used as a template to synthesise first-strand cDNA using reverse transcriptase and random primers, followed by second-strand cDNA synthesis with DNA Polymerase I and RNase H. Newly synthesised cDNA had a single adenine base added with ligation of adaptors, before being purified and amplified by PCR to make the final library. Library quality control was performed again using a TapeStation with D1000 ScreenTape (catalog Number: 5067-5582). Pre-processing of RNA-seq data, differential expression and differential usage analysis. RNAseq data were processed and aligned against the TAIR10 (EnsemblePlants) genome using TopHat and indexed with Samtools. DeSeq determined differential expression. Alternative splicing analysis was determined using RMats (p value of 0.05, a minimum of 10% inclusion difference). Alternative splicing events were visualised using Sashimi plots generated by the Integrative Genomics Viewer (IGV) (Robinson et al., 2011). Direct mRNA isolation and cDNA preparation for RT-qPCR or RT-PCR Seedlings were grown 7 days post-germination as described above. Roots and cotyledons were separated using a razor blade, and the material was frozen immediately in liquid nitrogen. Pools of seedlings were used to generate three separate biological samples. Each pool contained approximately 20 mg of root or cotyledon tissue. Total mRNA was extracted using Dynabeads®mRNA DIRECT™kit with Oligo(dT)25 labelled magnetic beads. Frozen tissue was ground with a sterile plastic micropestle and resuspended in 300 µl lysis buffer. The solution was then forced through a 21-gauge needle in a 1ml syringe 3-5 times to shear any DNA and mixed with 50 µl of Dynabeads Oligo(dT)25. The kit procedure was followed, with two final washes conducted. To ensure the complete removal of any genomic DNA in the subcellular fractionation experiments, this stage was followed by ezDnase™ treatment in a 10 µl volume (1µl ezDNASe™, 1 µl ezDNASe™ 10X buffer and 8 µl sterile H2O), 37˚C for 2 minutes followed by 1 µl DTT and 5 minutes at 55˚C in a heat block. cDNA was prepared using a SuperScript®IV First-Strand synthesis system directly on the bead solution. For RT-PCR and RT-qPCR beads were washed in 20 µl 1 x SSIV buffer before resuspension in 12 µl sterile H2O with 1 µl dNTP 10 mM each mix and incubated for 5 minutes at 50 ˚C in a Proflex PCR machine (Applied Biosystems). Then the following were added 4 µl 10 x SSIV buffer, 1 µl ribonuclease inhibitor and 1 µl Superscript®IV reverse transcriptase were added. The mixture was mixed by pipetting and incubated for 10 minutes at 50 ˚C, followed by 10 minutes at 80 ˚C, and then held at 4 ˚C. The 20 µl cDNA mix was stored at -20 and not eluted from the beads. Samples were checked for the presence of genomic DNA by PCR with Actin 2 primers ACT2 forward and reverse. A PCR reaction after 28 cycles with a Tm of 60 ˚C generated a 340 bp product if genomic DNA was a contaminant, 240 bp otherwise. All PCR and sequencing primers are listed in Table S3. RT-PCR 0.5 – 1 µl of cDNA/bead mix were used per PCR reaction. RT-PCR was performed with RSZ33 or ACC1 root-derived cDNA using Phusion™ (Thermofisher) high-fidelity polymerase. Relative levels of RSZ33 and ACC1 splice variants were determined using FIJI gel analysis software (Schindelin et al. 2012). Relative levels of cDNA per sample were determined using PCR-amplified PP2a transcript levels.

Comparison of relative gene expression fold in transcriptome data and qPCR results.

Due to the recognized proliferation and spread of antibiotic resistance genes by anthropogenic use of antibiotics for human, agriculture and aquaculture purposes, antibiotic resistance genes have been defined as an emerging contaminant (Laxminarayan and others, 2013; Rodriguez-Rojas and others, 2013; Niu and others, 2016). The presence and spread of these genes in non-clinical and non-agricultural environments has created the need for background investigations to enhance our understanding of the magnitude and risks associated with this emerging field (Allen and others, 2010). The current global economic costs of antibiotic resistant microorganisms is about 5.8 trillion USD, which is approximately equivalent to the combined GDP of Germany and the United Kingdom (Taylor and others, 2014). In this study researchers screened soil and sediment samples for the presence of 15 antibiotic resistance gene targets and 5 species of Vibrio (a marker of marine inundation) to determine natural background concentrations. These data provide a foundation to address background prevalence of these genetic targets in the northeastern United States (U.S.) to address regional influences (sources of pollutants) and to contrast future influences due to sea-level rise and large scale storms.

Quantitative gene expression analysis is an important tool in the scientist's belt. The identification of evenly expressed reference genes is necessary for accurate quantitative gene expression analysis, whether by traditional RT-PCR (reverse-transcription polymerase chain reaction) or by qRT-PCR (quantitative real-time PCR; qPCR). In the Stramenopiles (the major line of eukaryotes that includes brown algae) there is a noted lack of known reference genes for such studies, largely due to the absence of available molecular tools. Here we present a set of nine reference genes (Elongation Factor 1 alpha (EF1A), Elongation Factor 2 alpha (EF2A), Elongation Factor 1 beta (EF1B), 14-3-3 Protein, Ubiquitin Conjugating Enzyme (UBCE2), Glyceraldehyde-3-phosphate Dehydrogenase (GAPDH), Actin Related Protein Complex (ARP2/3), Ribosomal Protein (40s; S23), and Actin) for the brown alga Fucus distichus. These reference genes were tested on adult sporophytes across six abiotic stress conditions (desiccation, light and temperature modification, hormone addition, pollutant exposure, nutrient addition, and wounding). Suitability of these genes as reference genes was quantitatively evaluated across conditions using standard methods and the majority of the tested genes were evaluated favorably. However, we show that normalization genes should be chosen on a condition-by-condition basis. We provide a recommendation that at least two reference genes be used per experiment, a list of recommended pairs for the conditions tested here, and a procedure for identifying a suitable set for an experimenter's unique design. With the recent expansion of interest in brown algal biology and accompanied molecular tools development, the variety of experimental conditions tested here makes this study a valuable resource for future work in basic biology and understanding stress responses in the brown algal lineage.

Quantitative reverse transcription polymerase chain reaction (RTqPCR) data collected from RNA samples on 1 leg of each of the CAR212 and CAR216 cruises.

Data from qPCR machines

This environmental data-set consists of 56 sediment, 23 Cladophora and 23 water samples collected from beaches at Glen Haven, Good Harbor, Platte Bay and Esch road, located within The Sleeping Bear Dunes National Lakeshore, Leelanau and Benzie counties, Michigan. The data-set includes matrix type, location, date, and the qPCR reported value for each sample collected. Sample Collection and Processing: Samples were collected from Glen Haven, Good Harbor, Platte road and Esch road beaches in Sleeping Bear Dunes National Lakeshore. Sites were situated a short distance from stream or river inputs (except Glen Haven), and all sites had been associated with previous botulism outbreak events. Beach sediment, surface water, and Cladophora samples were collected from four sampling sites in SLBE from May to November 2012. At each site, surface water and beach sediment were collected from three locations, approximately 50 meters away from each other. Where available, sloughed Cladophora samples were collected from the beach or floating near the beach within the same range that sediment and water collected. Where applicable, samples were collected in triplicate as described in Wijesinghe and others, 2015. DNA Extraction: Sediment samples were collected in triplicate, composited into one sample and homogenized. Cladophora samples were collected as a single sample, in duplicate or in triplicate, composited into one sample and homogenized. Ten grams of sediment or Cladophora (wet weight) was used in each extraction per manufacture’s protocol (PowerMax® Soil DNA Isolation Kit. Mobio Laboratories, Carlsbad, CA). Water samples were composited, and one hundred milliliters of surface water was filtered through a polycarbonate filter. DNA was extracted per manufacture’s protocol, using a PowerSoil® DNA Isolation Kit used for water filters.

RNA interference (RNAi) is a powerful tool for studying functions of candidate genes in both model and non-model organisms and a promising technique for therapeutic applications. Successful application of this technique relies on the accuracy and reliability of methods used to quantify gene knockdown. With the limitation in the availability of antibodies for detecting proteins, quantitative PCR (qPCR) remains the preferred method for quantifying target gene knockdown after dsRNA treatment . We evaluated how qPCR primer binding site and target gene expression levels affect quantification of intact mRNA transcripts following dsRNA-mediated RNAi. The use of primer pairs targeting the mRNA sequence within the dsRNA target region failed to reveal a significant decrease in target mRNA transcripts for genes with low expression levels, but not for a highly expressed gene. By contrast, significant knockdown was detected in all cases with primer pairs targeting the mRNA sequence extending beyond the dsRNA target region, regardless of the expression levels of the target gene. Our results suggest that at least for genes with low expression levels, quantifying the efficiency of dsRNA-mediated RNAi with primers amplifying sequences completely contained in the dsRNA target region should be avoided due to the risk of false negative results. Instead, primer pairs extending beyond the dsRNA target region of the mRNA transcript sequences should be used for accurate and reliable quantification of silencing efficiency.

raw data for qPCR assays

Wastewater-based epidemiology (WBE) is a useful complement to clinical testing for managing COVID-19. While community-scale wastewater and clinical data frequently correlate, less is known about subcommunity relationships between the two data types. Moreover, nondetects in qPCR wastewater data are typically handled through methods known to bias results, overlooking perhaps better alternatives. We address these knowledge gaps using data collected from September 2020–June 2021 in Davis, California (USA). We hypothesize that coupling the expectation maximization (EM) algorithm with the Markov Chain Monte Carlo (MCMC) method could improve estimation of “missing” values in wastewater qPCR data. We test this hypothesis by applying EM-MCMC to city wastewater treatment plant data and comparing output to more conventional nondetect handling methods. Dissimilarities in results (i) underscore the importance of specifying nondetect handling method in reporting and (ii) suggest that using EM-MCMC may yield better agreement between community-scale clinical and wastewater data. We also present a novel framework for spatially aligning clinical data with wastewater data collected upstream of a treatment plant (i.e., distributed across a sewershed). Applying the framework to data from Davis reveals reasonable agreement between wastewater and clinical data at highly granular spatial scalesfurther underscoring the public-health value of WBE.

qPCR results and data analysis for RNA expression in C9-ALS patient cell lines (de-identified). qPCR data generated by the lab of Dr. Ekaterina Rogaeva. ∆∆Ct analysis by Monika Schmidt.

The provided data are technical repeats from the research experimental details. including qPCR data and image analysis for cellular viability.

Statistical Analysis. Data are presented as mean (±SE). All statistical analyses were performed using GraphPad Prism (version 9.0). Two-way ANOVAs assessed the effect of sleep treatment (ASF or NSF), time (1h, 2h, 6h, 12h, 24h), and their interaction on mRNA expression of cytokines, serum CORT levels, and serum IL-6 concentration. One-way ANOVAs were used to assess whether ASF and NSF groups differed significantly from baseline levels (time 0h). Tukey’s HSD and Bonferroni multiple comparisons were used for

The agronomical relevant tomato-Pseudomonas syringae pv. tomato pathosystem is widely used to explore and understand the underlying mechanisms of the plant immune response. Transcript abundance estimation, mainly through reverse transcription-quantitative PCR (RT-qPCR), is a common approach employed to investigate the possible role of a candidate gene in certain biological process under study. The accuracy of this technique relies heavily on the selection of adequate reference genes. Initially, genes derived from other techniques (such as Northern blots) were used as reference genes in RT-qPCR experiments, but recent studies in di erent systems suggest that many of these genes are not stably expressed. The development of high throughput transcriptomic techniques, such as RNA-seq, provides an opportunity for the identi cation of transcriptionally stable genes that can be adopted as novel and robust reference genes. Here we take advantage of a large set of RNA-seq data originating from tomato leaves in ltrated with di erent immunity inducers and bacterial strains. We assessed and validated 9 genes that are much more stable than two traditional reference genes. Speci cally, ARD2 and VIN3 were the most stably expressed genes and consequently we propose they be adopted for RT- qPCR experiments involving this pathosystem.