RDML-Ninja and RDMLdb for standardized exchange of qPCR data

Improving the quality of quantitative polymerase chain reaction experiments: 15 years of MIQE

The quantitative polymerase chain reaction (qPCR) is fundamental to molecular biology. It is not just a laboratory technique, qPCR is a bridge between research and clinical practice. Its theoretical foundations guide the design of experiments, while its practical implications extend to diagnostics, treatment, and research advancements in the life sciences, human and veterinary medicine, agriculture, and forensics. However, the accuracy, reliability and reproducibility of qPCR data face challenges arising from various factors associated with experimental design, execution, data analysis and inadequate reporting details. Addressing these concerns, the Minimum Information for the Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines have emerged as a cohesive framework offering a standardised set of recommendations that describe the essential information required for assessing qPCR experiments. By emphasising the importance of methodological rigour, the MIQE guidelines have made a major contribution to improving the trustworthiness, consistency, and transparency of many published qPCR results. However, major challenges related to awareness, resources, and publication pressures continue to affect their consistent application.

Oral Cancer Cells Release Vesicles that Cause Pain

Oral cancer pain is attributed to the release from cancers of mediators that sensitize and activate sensory neurons. Intraplantar injection of conditioned media (CM) from human tongue cancer cell line HSC-3 or OSC-20 evokes nociceptive behavior. By contrast, CM from noncancer cell lines, DOK, and HaCaT are non-nociceptive. Pain mediators are carried by extracellular vesicles (EVs) released from cancer cells. Depletion of EVs from cancer cell line CM reverses mechanical allodynia and thermal hyperalgesia. CM from non-nociceptive cell lines become nociceptive when reconstituted with HSC-3 EVs. Two miRNAs (hsa-miR-21-5p and hsa-miR-221-3p) are identified that are present in increased abundance in EVs from HSC-3 and OSC-20 CM compared to HaCaT CM. The miRNA target genes suggest potential involvement in oral cancer pain of the toll like receptor 7 (TLR7) and 8 (TLR8) pathways, as well as signaling through interleukin 6 cytokine family signal transducer receptor (gp130, encoded by IL6ST) and colony stimulating factor receptor (G-CSFR, encoded by CSF3R), Janus kinase and signal transducer and activator of transcription 3 (JAK/STAT3). These studies confirm the recent discovery of the role of cancer EVs in pain and add to the repertoire of algesic and analgesic cancer pain mediators and pathways that contribute to oral cancer pain.

Web-based LinRegPCR: application for the visualization and analysis of (RT)-qPCR amplification and melting data

BACKGROUND

The analyses of amplification and melting curves have been shown to provide valuable information on the quality of the individual reactions in quantitative PCR (qPCR) experiments and to result in more reliable and reproducible quantitative results.

IMPLEMENTATION

The main steps in the amplification curve analysis are (1) a unique baseline subtraction, not using the ground phase cycles, (2) PCR efficiency determination from the exponential phase of the individual reactions, (3) setting a common quantification threshold and (4) calculation of the efficiency-corrected target quantity with the common threshold, efficiency per assay and C_q per reaction. The melting curve analysis encompasses smoothing of the observed fluorescence data, normalization to remove product-independent fluorescence loss, peak calling and assessment of the correct peak by comparing its melting temperature with the known melting temperature of the intended amplification product.

RESULTS

The LinRegPCR web application provides visualization and analysis of a single qPCR run. The user interface displays the analysis results on the amplification curve analysis and melting curve analysis in tables and graphs in which deviant reactions are highlighted. The annotated results in the tables can be exported for calculation of gene-expression ratios, fold-change between experimental conditions and further statistical analysis. Web-based LinRegPCR addresses two types of users, wet-lab scientists analyzing the amplification and melting curves of their own qPCR experiments and bioinformaticians creating pipelines for analysis of series of qPCR experiments by splitting its functionality into a stand-alone back-end RDML (Real-time PCR Data Markup Language) Python library and several companion applications for data visualization, analysis and interactive access. The use of the RDML data standard enables machine independent storage and exchange of qPCR data and the RDML-Tools assist with the import of qPCR data from the files exported by the qPCR instrument.

CONCLUSIONS

The combined implementation of these analyses in the newly developed web-based LinRegPCR ( https://www.gear-genomics.com/rdml-tools/ ) is platform independent and much faster than the original Windows-based versions of the LinRegPCR program. Moreover, web-based LinRegPCR includes a novel statistical outlier detection and the combination of amplification and melting curve analyses allows direct validation of the amplification product and reporting of reactions that amplify artefacts.

Hypomethylation of AHRR (cg05575921) Is Related to Smoking Status in the Mexican Mestizo Population

Tobacco smoking results in a multifactorial disease involving environmental and genetic factors; epigenome-wide association studies (EWAS) show changes in DNA methylation levels due to cigarette consumption, partially reversible upon tobacco smoking cessation. Therefore, methylation levels could predict smoking status. This study aimed to evaluate the DNA methylation level of cg05575921 (AHRR) and cg23771366 (PRSS23) and their correlation with lung function variables, cigarette consumption, and nicotine addiction in the Mexican smoking population. We included 114 non-smokers (NS) and 102 current tobacco smokers (TS); we then further subclassified them as heavy smokers (HS) (n = 53) and light smokers (LS) (n = 49). We used restriction enzymes (MspI/HpaII) and qPCR to determine the DNA methylation level. We observed significant hypomethylation of cg05575921 in smokers compared to NS (p = 0.003); further analysis found a difference between HS and NS (p = 0.02). We did not observe differences between other groups or a positive correlation between methylation levels and age, BMI, cigarette consumption, nicotine addiction, or lung function. In conclusion, the cg05575921 site of AHRR is significantly hypomethylated in Mexican smokers, especially in HS (≥20 cigarettes per day).

The Digital MIQE Guidelines Update: Minimum Information for Publication of Quantitative Digital PCR Experiments for 2020

Digital PCR (dPCR) has developed considerably since the publication of the Minimum Information for Publication of Digital PCR Experiments (dMIQE) guidelines in 2013, with advances in instrumentation, software, applications, and our understanding of its technological potential. Yet these developments also have associated challenges; data analysis steps, including threshold setting, can be difficult and preanalytical steps required to purify, concentrate, and modify nucleic acids can lead to measurement error. To assist independent corroboration of conclusions, comprehensive disclosure of all relevant experimental details is required. To support the community and reflect the growing use of dPCR, we present an update to dMIQE, dMIQE2020, including a simplified dMIQE table format to assist researchers in providing key experimental information and understanding of the associated experimental process. Adoption of dMIQE2020 by the scientific community will assist in standardizing experimental protocols, maximize efficient utilization of resources, and further enhance the impact of this powerful technology.

Enabling reproducible real-time quantitative PCR research: the RDML package

Motivation

Reproducibility, a cornerstone of research, requires defined data formats, which include the setup and output of experiments. The real-time PCR data markup language (RDML) is a recommended standard of the minimum information for publication of quantitative real-time PCR experiments guidelines. Despite the popularity of the RDML format for analysis of quantitative PCR data, handling of RDML files is not yet widely supported in all PCR curve analysis softwares.

Results

This study describes the open-source RDML package for the statistical computing language R. RDML is compatible with RDML versions ≤ 1.2 and provides functionality to (i) import RDML data; (ii) extract sample information (e.g. targets and concentration); (iii) transform data to various formats of the R environment; (iv) generate human-readable run summaries; and (v) to create RDML files from user data. In addition, RDML offers a graphical user interface to read, edit and create RDML files.

Availability and implementation

https://cran.r-project.org/package=RDML. rdmlEdit server http://shtest.evrogen.net/rdmlEdit/. Documentation: http://kablag.github.io/RDML/.

Contact

k.blag@yandex.ru.

Supplementary information

Supplementary data are available at Bioinformatics online.

Application of Individual qPCR Performance Parameters for Quality Control of Circulating MicroRNA Data

Although circulating miRNAs are promising candidates for biomarkers, several challenges must be overcome before miRNAs can be used for diagnosis and monitoring. One is quality control for the RNA extraction and quantification process. RNA quality control techniques are unsuitable as circulating miRNAs are in the fM range. Additionally, biofluids may contain inhibitors of the reverse transcriptase and polymerase enzymes, which may survive RNA purification. Herein, we describe the protocol we have used to check the robustness of miRNA purification and measurement by the addition of spike-ins and by evaluating the quality of the qPCR data, respectively.

rdml: A Mathematica package for parsing and importing Real-Time qPCR data

OBJECTIVE

The purpose and objective of the research presented is to provide a package for easy importing of Real-Time PCR data markup language (RDML) data to Mathematica.

RESULTS

Real-Time qPCR is the most widely used experimental method for the accurate quantification of gene expression. To enable the straightforward archiving and sharing of qPCR data and its associated experimental information, an XML-based data standard was developed-the Real-Time PCR data markup language (RDML)-devised by the RDML consortium. Here, we present rdml, a package to parse and import RDML data into Mathematica, allowing the quick loading and extraction of relevant data, thus promoting the re-analysis, meta-analysis or experimental re-validation of gene expression data deposited in RDML format.

Salidroside inhibits high-glucose induced proliferation of vascular smooth muscle cells via inhibiting mitochondrial fission and oxidative stress

The mitochondria are highly dynamic organelles, carefully maintaining network homeostasis by regulating mitochondrial fusion and fission. Mitochondrial dynamics are involved in the regulation of a variety of pathophysiological processes, including cell proliferation. Oxidative stress serves an important role in the remodeling of arterial vascular tissue in diabetic patients by affecting the proliferation of vascular smooth muscle cells (VSMCs). Salidroside is the primary active component of Rhodiola rosea and has been demonstrated to be an antioxidant with cardio- and vascular-protective effects, in addition to improving glucose metabolism. Therefore, the present study aimed to examine the impact of Salidroside on VSMC proliferation, reactive oxygen species (ROS) generation and mitochondrial dynamics under high glucose conditions and the potential mechanisms involved. The current study used Salidroside and a mitochondrial division inhibitor, specifically of Drp1 (Mdivi-1) to treat VSMCs under high glucose conditions for 24 h and assessed VSMCs proliferation, the state of mitochondrial fission and fusion and the expression level of proteins related to mitochondrial dynamics including dynamin-related protein (Drp1) and mitofusin 2 (Mfn2), ROS level and nicotinamide adenine dinucleotide phosphate oxidase activity. The results of the present study indicate that Salidroside and Mdivi-1 inhibit VSMC proliferation, Drp1 expression and oxidative stress and upregulate Mfn2 expression (all P<0.05). The inhibitive effect on VSMC proliferation may be partly reversed by exogenous ROS. In addition, the inhibitive effect on VSMCs proliferation and oxidative stress may also be in part reversed by Mfn2-siRNA. Collectively, these data suggest that Salidroside inhibits VSMCs proliferation induced by high-glucose and may perform its therapeutic effect via maintaining mitochondrial dynamic homeostasis and regulating oxidative stress level, with Mfn2 as a therapeutic target.

Data on individual PCR efficiency values as quality control for circulating miRNAs

This data article contains data related to the research article entitled “Variability in microRNA recovery from plasma: Comparison of five commercial kits, doi:10.1016/j.ab.2015.07.018” Brunet-Vega (2015) [1]. PCR efficiency, along with RNA and cDNA quality, are the most important factors affecting the quality of qPCR results. Constant amplification efficiency in all compared samples is indispensable when relative quantification is used to measure changes in gene expression. An easy way to measure PCR efficiency, without the need of a standard curve, is LinRegPCR software. Individual PCR efficiency can be determined as a part of qPCR quality control. This is especially important when the initial RNA quantity is so low that cannot be accurately quantified, such as in circulating RNA extractions. This data article reports the Cqs and PCR efficiencies of 5 miRNAs quantified in RNA isolated from 4 patients with colorectal cancer (CRC) and 4 healthy donors using five commercially available kits.

Removal of between-run variation in a multi-plate qPCR experiment

Quantitative PCR (qPCR) is the method of choice in gene expression analysis. However, the number of groups or treatments, target genes and technical replicates quickly exceeds the capacity of a single run on a qPCR machine and the measurements have to be spread over more than 1 plate. Such multi-plate measurements often show similar proportional differences between experimental conditions, but different absolute values, even though the measurements were technically carried out with identical procedures. Removal of this between-plate variation will enhance the power of the statistical analysis on the resulting data. Inclusion and application of calibrator samples, with replicate measurements distributed over the plates, assumes a multiplicative difference between plates. However, random and technical errors in these calibrators will propagate to all samples on the plate. To avoid this effect, the systematic bias between plates can be removed with a correction factor based on all overlapping technical and biological replicates between plates. This approach removes the requirement for all calibrator samples to be measured successfully on every plate. This paper extends an already published factor correction method to the use in multi-plate qPCR experiments. The between-run correction factor is derived from the target quantities which are calculated from the quantification threshold, PCR efficiency and observed C_q value. To enable further statistical analysis in existing qPCR software packages, an efficiency-corrected C_q value is reported, based on the corrected target quantity and a PCR efficiency per target. The latter is calculated as the mean of the PCR efficiencies taking the number of reactions per amplicon per plate into account. Export to the RDML format completes an RDML-supported analysis pipeline of qPCR data ranging from raw fluorescence data, amplification curve analysis and application of reference genes to statistical analysis.