Critical appraisal of quantitative PCR results in colorectal cancer research: can we rely on published qPCR results?

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.

Exogenous spike-in mouse RNAs for accurate differential gene expression analysis in barley using RT-qPCR

Reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) followed by the 2-ΔΔCt method is the most common way to measure transcript levels for relative gene expression assays. The quality of an RT-qPCR assay is dependent upon the identification and validation of reference genes to normalize gene expression data. The so-called housekeeping genes are commonly used as internal reference genes because they are assumed to be ubiquitously expressed at stable levels. Commonly, researchers do not validate their reference genes but rely on historical reference genes or previously validated genes from an unrelated experiment. Using previously validated reference genes to assess gene expression changes occurring during malting resulted in extensive variability. Therefore, a new method was tested and validated to circumvent the use of internal reference genes. Total mouse RNA was chosen as the external reference RNA and a suite of primer sets to putatively stable mouse genes was created to identify stably expressed genes for use as an external reference gene. cDNA was created by co-amplifying total mouse RNA, as an RNA spike-in, and barley RNA. When using the external reference genes to normalize malting gene expression data, standard deviations were significantly reduced and significant differences in transcript abundance were observed, whereas when using the internal reference genes, standard deviations were larger with no significant differences seen. Furthermore, external reference genes were more accurate at assessing expression levels in malting and developing grains, whereas the internal reference genes overestimated abundance in developing grains and underestimated abundance in malting grains.

A Strategy for the Selection of RT-qPCR Reference Genes Based on Publicly Available Transcriptomic Datasets

In the next-generation sequencing era, RT-qPCR is still widely employed to quantify levels of nucleic acids of interest due to its popularity, versatility, and limited costs. The measurement of transcriptional levels through RT-qPCR critically depends on reference genes used for normalization. Here, we devised a strategy to select appropriate reference genes for a specific clinical/experimental setting based on publicly available transcriptomic datasets and a pipeline for RT-qPCR assay design and validation. As a proof-of-principle, we applied this strategy to identify and validate reference genes for transcriptional studies of bone-marrow plasma cells from patients with AL amyloidosis. We performed a systematic review of published literature to compile a list of 163 candidate reference genes for RT-qPCR experiments employing human samples. Next, we interrogated the Gene Expression Omnibus to assess expression levels of these genes in published transcriptomic studies on bone-marrow plasma cells from patients with different plasma cell dyscrasias and identified the most stably expressed genes as candidate normalizing genes. Experimental validation on bone-marrow plasma cells showed the superiority of candidate reference genes identified through this strategy over commonly employed “housekeeping” genes. The strategy presented here may apply to other clinical and experimental settings for which publicly available transcriptomic datasets are available.

Current commercial dPCR platforms: technology and market review

Digital polymerase chain reaction (dPCR) technology has provided a new technique for molecular diagnostics, with superior advantages, such as higher sensitivity, precision, and specificity over quantitative real-time PCRs (qPCR). Eight companies have offered commercial dPCR instruments: Fluidigm Corporation, Bio-Rad, RainDance Technologies, Life Technologies, Qiagen, JN MedSys Clarity, Optolane, and Stilla Technologies Naica. This paper discusses the working principle of each offered dPCR device and compares the associated: technical aspects, usability, costs, and current applications of each dPCR device. Lastly, up-and-coming dPCR technologies are also presented, as anticipation of how the dPCR device landscape may likely morph in the next few years.

Innovative GenExpA software for selecting suitable reference genes for reliable normalization of gene expression in melanoma

The algorithms commonly used to select the best stable reference gene in RT-qPCR data analysis have their limitations. We showed that simple selection of the reference gene or pair of genes with the lowest stability value from the pool of potential reference genes—a commonly used approach—is not sufficient to accurately and reliably normalize the target gene transcript and can lead to biologically incorrect conclusions. For reliable assessment of changes in a target gene expression level, we propose our innovative GenExpA software, which works in a manner independent of the experimental model and the normalizer used. GenExpA software selects the best reference by combining the NormFinder algorithm with progressive removal of the least stable gene from the candidate genes in a given experimental model and in the set of daughter models assigned to it. The reliability of references is validated based on the consistency of the statistical analyses of normalized target gene expression levels through all models, described by the coherence score (CS). The use of the CS value imparts a new quality to qPCR analysis because it clarifies how low the stability value of reference must be in order for biologically correct conclusions to be drawn. We tested our method on qPCR data for the B4GALT genes family in melanoma, which is characterized by a high mutation rate, and in melanocytes. GenExpA is available at https://github.com/DorotaHojaLukowicz/GenExpA or https://www.sciencemarket.pl/baza-programow-open-source#oferty.

Stroma-derived extracellular vesicle mRNA signatures inform histological nature of prostate cancer

Histological assessment of prostate cancer is the key diagnostic test and can predict disease outcome. This is however an invasive procedure that carries associated risks, hence non-invasive assays to support the diagnostic pathway are much needed. A key feature of disease progression, and subsequent poor prognosis, is the presence of an altered stroma. Here we explored the utility of prostate stromal cell-derived vesicles as indicators of an altered tumour environment. We compared vesicles from six donor-matched pairs of adjacent-normal versus disease-associated primary stromal cultures. We identified 19 differentially expressed transcripts that discriminate disease from normal stromal extracellular vesicles (EVs). EVs isolated from patient serum were investigated for these putative disease-discriminating mRNA. A set of transcripts including Caveolin-1 (CAV1), TMP2, THBS1, and CTGF were found to be successful in discriminating clinically insignificant (Gleason = 6) disease from clinically significant (Gleason > 8) prostate cancer. Furthermore, correlation between transcript expression and progression-free survival suggests that levels of these mRNA may predict disease outcome. Informed by a machine learning approach, combining measures of the five most informative EV-associated mRNAs with PSA was shown to significantly improve assay sensitivity and specificity. An in-silico model was produced, showcasing the superiority of this multi-modal liquid biopsy compared to needle biopsy for predicting disease progression. This proof of concept highlights the utility of serum EV analytics as a companion diagnostic test with prognostic utility, which may obviate the need for biopsy.

The carbon source-dependent pattern of antimicrobial activity and gene expression in Pseudomonas donghuensis P482

Pseudomonas donghuensis P482 is a tomato rhizosphere isolate with the ability to inhibit growth of bacterial and fungal plant pathogens. Herein, we analysed the impact of the carbon source on the antibacterial activity of P482 and expression of the selected genes of three genomic regions in the P482 genome. These regions are involved in the synthesis of pyoverdine, 7-hydroxytropolone (7-HT) and an unknown compound ("cluster 17") and are responsible for the antimicrobial activity of P482. We showed that the P482 mutants, defective in these regions, show variations and contrasting patterns of growth inhibition of the target pathogen under given nutritional conditions (with glucose or glycerol as a carbon source). We also selected and validated the reference genes for gene expression studies in P. donghuensis P482. Amongst ten candidate genes, we found gyrB, rpoD and mrdA the most stably expressed. Using selected reference genes in RT-qPCR, we assessed the expression of the genes of interest under minimal medium conditions with glucose or glycerol as carbon sources. Glycerol was shown to negatively affect the expression of genes necessary for 7-HT synthesis. The significance of this finding in the light of the role of nutrient (carbon) availability in biological plant protection is discussed.

COVID-19 and Diagnostic Testing for SARS-CoV-2 by RT-qPCR-Facts and Fallacies

Although molecular testing, and RT-qPCR in particular, has been an indispensable component in the scientific armoury targeting SARS-CoV-2, there are numerous falsehoods, misconceptions, assumptions and exaggerated expectations with regards to capability, performance and usefulness of the technology. It is essential that the true strengths and limitations, although publicised for at least twenty years, are restated in the context of the current COVID-19 epidemic. The main objective of this commentary is to address and help stop the unfounded and debilitating speculation surrounding its use.

Selection of reference genes for quantitative PCR: identifying reference genes for airway epithelial cells exposed to Pseudomonas aeruginosa

Most quantitative PCR (qPCR) experiments report differential expression relative to the expression of one or more reference genes. Therefore, when experimental conditions alter reference gene expression, qPCR results may be compromised. Little is known about the magnitude of this problem in practice. We found that reference gene responses are common and hard to predict and that their stability should be demonstrated in each experiment. Our reanalysis of 15 airway epithelia microarray data sets retrieved from the National Center for Biotechnology Information (NCBI) identified no common reference gene that was reliable in all 15 studies. Reanalysis of published RNA sequencing (RNA-seq) data in which human bronchial epithelial cells (HBEC) were exposed to Pseudomonas aeruginosa revealed that minor experimental details, including bacterial strain, may alter reference gene responses. Direct measurement of 32 TaqMan reference genes in primary cultures of HBEC exposed to P. aeruginosa (strain PA14) demonstrated that choosing an unstable reference gene could make it impossible to observe statistically significant changes in IL8 gene expression. We found that reference gene instability is a general phenomenon and not limited to studies of airway epithelial cells. In a diverse compendium of 986 human microarray experiments retrieved from the NCBI, reference genes were differentially expressed in 42% of studies. Experimentally induced changes in reference gene expression ranged from 21% to 212%. These results highlight the importance of identifying adequate reference genes for each experimental system and documenting their response to treatment in each experiment. This will enhance experimental rigor and reproducibility in qPCR studies.

Validation and identification of reference genes in Chinese hamster ovary cells for Fc-fusion protein production

IMPACT STATEMENT

In order to reveal potential genotype-phenotype relationship, RT-qPCR reactions are frequently applied which require validated and reliable reference genes. With the investigation on long-term passage and fed-batch cultivation of CHO cells producing an Fc-fusion protein, four new reference genes-Akr1a1, Gpx1, Aprt, and Rps16, were identified from 20 candidates with the aid of geNorm, NormFinder, BestKeeper, and ΔCt programs and methods. This article provided more verified options in reference gene selection in related research on CHO cells.

Comparison between protocols and publications for prognostic and predictive cancer biomarker studies

BACKGROUND

Method prespecification in study protocols is important for controlling bias in reports. The primary goal of this study was to assess potential for discordance between study protocols and publications reporting predictive or prognostic cancer biomarker research. Secondary objectives included comparing characteristics of publications with accessible protocols compared to those without.

METHODS

Publications reporting predictive or prognostic cancer biomarker research were identified from 15 major journals, 2012-2015. Protocols were sought online or through repeated queries of corresponding authors. The following four items were extracted: (1) biomarkers, (2) biospecimen/assays, (3) sample size, (4) endpoints. We defined "explicit discordance" as the presence of major inconsistencies on these items.

RESULTS

Of 149 eligible publications, we obtained 19 eligible protocols online (13%). Out of a random sample of 103 publications where protocols were not available online, 12 protocols (12%) were furnished by corresponding authors; 8 (8% of authors) explicitly stated the absence of a protocol. Among 24 retrospective cohort studies, no protocol could be accessed. We found explicit discordance between publications and protocols for 18 studies (58%), in particular choice of biomarkers (36%), biospecimen/assays (6%), or endpoints (29%).

CONCLUSION

Protocols are generally not accessible or not used for cancer biomarker studies. Publications were often explicitly discordant with protocols, particularly regarding biomarkers and endpoints. Our findings point to common unaddressed risk of bias in publications of major journals reporting the relationship between cancer biomarkers and clinical endpoints.

Validation of a real-time PCR assay for detection of swinepox virus

Swine are the only known hosts of swinepox virus (SWPV), the sole member of the genus Suipoxvirus, family Poxviridae. Rapid diagnosis is recommended for appropriate interventions because of the high morbidity associated with this virus. This study describes a real-time quantitative PCR (qPCR) assay for rapid detection and quantification of SWPV. The detection limit, repeatability, reproducibility, and specificity of this assay were determined. The efficiency was 96%, and the R² value was 0.996. The detection limit was 1 fg or 10^-0.5 TCID₅₀/50 μL. Tests showed that the greatest source of error in the SWPV qPCR assay was variation between analysts rather than different qPCR kits or equipment. All nucleic acids from other viruses or samples collected from swine were negative in the specificity test. qPCR for SWPV is a new method with tested variables that allows main sources of error in laboratory diagnosis and viral quantification to be identified.

Pathogenic missense mutation pattern of forkhead box genes in neurodevelopmental disorders

Background

Forkhead box (FOX) proteins are a family of transcription factors. Mutations of three FOX genes, including FOXP1, FOXP2, and FOXG1, have been reported in neurodevelopmental disorders (NDDs). However, due to the lack of site‐specific statistical significance, the pathogenicity of missense mutations of these genes is difficult to determine.

Methods

DNA and RNA were extracted from peripheral blood lymphocytes. The mutation was detected by single‐molecule molecular inversion probe‐based targeted sequencing, and the variant was validated by Sanger sequencing. Real‐time quantitative PCR and western blot were performed to assay the expression of the mRNA and protein. To assess the pattern of disorder‐related missense mutations of NDD‐related FOX genes, we manually curated de novo and inherited missense or inframeshift variants within FOXP1, FOXP2, and FOXG1 that co‐segregated with phenotypes in NDDs. All variants were annotated by ANNOVAR.

Results

We detected a novel de novo missense mutation (NM_001244815: c.G1444A, p.E482K) of FOXP1 in a patient with intellectual disability and severe speech delay. Real‐time PCR and western blot revealed a dramatic reduction of mRNA and protein expression in patient‐derived lymphocytes, indicating a loss‐of‐function mechanism. We observed that the majority of the de novo or transmitted missense variants were located in the FOX domains, and 95% were classified as pathogenic mutations. However, 10 variants were located outside of the FOX domain and were classified as likely pathogenic or variants of uncertain significance.

Conclusion

Our study shows the pathogenicity of missense and inframeshift variants of NDD‐related FOX genes, which is important for clinical diagnosis and genetic counseling. Functional analysis is needed to determine the pathogenicity of the variants with uncertain clinical significance.

On resolving ambiguities in microbial community analysis of partial nitritation anammox reactors

PCR-based methods have caused a surge for integration of eco-physiological approaches into research on partial nitritation anammox (PNA). However, a lack of rigorous standards for molecular analyses resulted in widespread data misinterpretation and consequently lack of consensus. Data consistency and accuracy strongly depend on the primer selection and data interpretation. An in-silico evaluation of 16S rRNA gene eubacterial primers used in PNA studies from the last ten years unraveled the difficulty of comparing ecological data from different studies due to a variation in the coverage of these primers. Our 16S amplicon sequencing approach, which includes parallel sequencing of six 16S rRNA hypervariable regions, showed that there is no perfect hypervariable region for PNA microbial communities. Using qPCR analysis, we emphasize the significance of primer choice for quantification and caution with data interpretation. We also provide a framework for PCR based analyses that will improve and assist to objectively interpret and compare such results.

The Ultimate qPCR Experiment: Producing Publication Quality, Reproducible Data the First Time

Quantitative PCR (qPCR) is one of the most common techniques for quantification of nucleic acid molecules in biological and environmental samples. Although the methodology is perceived to be relatively simple, there are a number of steps and reagents that require optimization and validation to ensure reproducible data that accurately reflect the biological question(s) being posed. This review article describes and illustrates the critical pitfalls and sources of error in qPCR experiments, along with a rigorous, stepwise process to minimize variability, time, and cost in generating reproducible, publication quality data every time. Finally, an approach to make an informed choice between qPCR and digital PCR technologies is described.

Estrogen receptor profiles across tissues from male and female Rattus norvegicus

Background

Estrogen is formed by the enzyme aromatase (CYP19A1) and signals via three identified receptors ERα (ESR1), ERß (ESR2), and the G protein-coupled estrogen receptor (GPER). Understanding the relative contribution of each receptor to estrogenic signaling may elucidate the disparate effects of this sex hormone across tissues, and recent developments in PCR technology allow absolute quantification and direct comparison of multiple targets. We hypothesized that this approach would reveal tissue- and sex-specific differences in estrogen receptor mRNA.

Methods

ESR1, ESR2, GPER, and CYP19A1 were measured in four cardiovascular tissues (heart, aorta, kidney, and adrenal gland), three brain areas (somatosensory cortex, hippocampus, and prefrontal cortex), and reproductive tissues (ovaries, mammary gland, uterus, testes) from six male and six female adult Sprague-Dawley rats.

Results

GPER mRNA expression was relatively stable across all tissues in both sexes, ranging from 5.49 to 113 copies/ng RNA, a 21-fold difference. In contrast, ESR1/ESR2 were variable across tissues although similar within an organ system. ESR1 ranged from 4.46 to 614 copies/ng RNA (138-fold difference) while ESR2 ranged from 0.154 to 83.1 copies/ng RNA (540-fold). Significant sex differences were broadly absent except for renal ESR1 (female 206 vs. male 614 copies/ng RNA, P < 0.0001) and GPER (62.0 vs. 30.2 copies/ng RNA, P < 0.05) as well as gonadal GPER (5.49 vs. 47.5 copies/ng RNA, P < 0.01), ESR2 (83.1 vs. 0.299 copies/ng RNA, P < 0.01), and CYP19A1 (322 vs. 7.18 copies/ng RNA, P < 0.01). Cardiovascular tissues showed a predominance of ESR1, followed by GPER. In contrast, GPER was the predominant transcript in the brain with similarly low levels of ESR1 and ESR2. CYP19A1 was detected at very low levels except for reproductive tissues and the hippocampus.

Conclusion

While the data indicates a lack of sex differences in most tissues, significant differences were found in the range of receptor gene expression across tissues as well as in the receptor profile between organ systems. The data provide a guide for future studies by establishing estrogen receptor expression across multiple tissues using absolute PCR quantification. This knowledge on tissue-specific estrogen receptor profiles will aid the development of hormonal therapies that elicit beneficial effects in specific tissues.

dPCR: A Technology Review

Digital Polymerase Chain Reaction (dPCR) is a novel method for the absolute quantification of target nucleic acids. Quantification by dPCR hinges on the fact that the random distribution of molecules in many partitions follows a Poisson distribution. Each partition acts as an individual PCR microreactor and partitions containing amplified target sequences are detected by fluorescence. The proportion of PCR-positive partitions suffices to determine the concentration of the target sequence without a need for calibration. Advances in microfluidics enabled the current revolution of digital quantification by providing efficient partitioning methods. In this review, we compare the fundamental concepts behind the quantification of nucleic acids by dPCR and quantitative real-time PCR (qPCR). We detail the underlying statistics of dPCR and explain how it defines its precision and performance metrics. We review the different microfluidic digital PCR formats, present their underlying physical principles, and analyze the technological evolution of dPCR platforms. We present the novel multiplexing strategies enabled by dPCR and examine how isothermal amplification could be an alternative to PCR in digital assays. Finally, we determine whether the theoretical advantages of dPCR over qPCR hold true by perusing studies that directly compare assays implemented with both methods.

Improving the standardization of mRNA measurement by RT-qPCR

Human health and safety depend on reliable measurements in medical diagnosis and on tests that support the selection and evaluation of therapeutic intervention and newly discovered molecular biomarkers must pass a rigorous evaluation process if they are to be of benefit to patients. Measurement standardization helps to maximize data quality and confidence and ultimately improves the reproducibility of published research. Failure to consider how a given experiment may be standardized can be costly, both financially as well as in time and failure to perform and report pre-clinical research in an appropriately rigorous manner will hinder the development of diagnostic methods. Hence standardization is a crucial step in maintaining the integrity of scientific studies and is a key feature of robust investigation.

While it is not deliberate, much of today's biomedical research contains logical and technical flaws, showing a need for corrective action

Biomedical research has advanced swiftly in recent decades, largely due to progress in biotechnology. However, this rapid spread of new, and not always-fully understood, technology has also created a lot of false or irreproducible data and artifacts, which sometimes have led to erroneous conclusions. When describing various scientific issues, scientists have developed a habit of saying "on one hand… but on the other hand…", because discrepant data and conclusions have become omnipresent. One reason for this problematic situation is that we are not always thoughtful enough in study design, and sometimes lack enough philosophical contemplation. Another major reason is that we are too rushed in introducing new technology into our research without assimilating technical details. In this essay, we provide examples in different research realms to justify our points. To help readers test their own weaknesses, we raise questions on technical details of RNA reverse transcription, polymerase chain reactions, western blotting and immunohistochemical staining, as these methods are basic and are the base for other modern biotechnologies. Hopefully, after contemplation and reflection on these questions, readers will agree that we indeed know too little about these basic techniques, especially about the artifacts they may create, and thus many conclusions drawn from the studies using those ever-more-sophisticated techniques may be even more problematic.

qPCR primer design revisited

Primers are arguably the single most critical components of any PCR assay, as their properties control the exquisite specificity and sensitivity that make this method uniquely powerful. Consequently, poor design combined with failure to optimise reaction conditions is likely to result in reduced technical precision and false positive or negative detection of amplification targets. Despite the framework provided by the MIQE guidelines and the accessibility of wide-ranging support from peer-reviewed publications, books and online sources as well as commercial companies, the design of many published assays continues to be less than optimal: primers often lack intended specificity, can form dimers, compete with template secondary structures at the primer binding sites or hybridise only within a narrow temperature range. We present an overview of the main steps in the primer design workflow, with data that illustrate some of the unexpected variability that often occurs when theory is translated into practice. We also strongly urge researchers to report as much information about their assays as possible in their publications.

Talking the talk, but not walking the walk: RT-qPCR as a paradigm for the lack of reproducibility in molecular research

Poorly executed and inadequately reported molecular measurement methods are amongst the causes underlying the lack of reproducibility of much biomedical research. Although several high impact factor journals have acknowledged their past failure to scrutinise adequately the technical soundness of manuscripts, there is a perplexing reluctance to implement basic corrective measures. The reverse transcription real-time quantitative PCR (RT-qPCR) is probably the most straightforward measurement technique available for RNA quantification and is widely used in research, diagnostic, forensic and biotechnology applications. Despite the impact of the minimum information for the publication of quantitative PCR experiments (MIQE) guidelines, which aim to improve the robustness and the transparency of reporting of RT-qPCR data, we demonstrate that elementary protocol errors, inappropriate data analysis and inadequate reporting continue to be rife and conclude that the majority of published RT-qPCR data are likely to represent technical noise.

Transcriptome-Based Identification of the Optimal Reference CHO Genes for Normalisation of qPCR Data

Real-time quantitative PCR (qPCR) is the standard method for determination of relative changes in mRNA transcript abundance. Analytical accuracy, precision and reliability are critically dependent on the selection of internal control reference genes. In this study, the authors have identified optimal reference genes that can be utilised universally for qPCR analysis of CHO cell mRNAs. Initially, transcriptomic datasets were analysed to identify eight endogenous genes that exhibited high expression stability across four distinct CHO cell lines sampled in different culture phases. The relative transcript abundance of each gene in 20 diverse, commonly applied experimental conditions was then determined by qPCR analysis. Utilizing GeNorm, BestKeeper and NormFinder algorithms, the authors identified four mRNAs (Gnb1, Fkbp1a, Tmed2 and Mmadhc) that exhibited a highly stable level of expression across all conditions, validating their utility as universally applicable reference genes. Whilst any combination of only two genes can be generally used for normalisation of qPCR data, the authors show that specific combinations of reference genes are particularly suited to discrete experimental conditions. In summary, the authors report the identification of fully validated universal reference genes, optimised primer sequences robust to genomic mutations and simple reference gene pair selection guidelines that enable streamlined qPCR analyses of mRNA abundance in CHO cells with maximum accuracy and precision.

Droplet Digital PCR versus qPCR for gene expression analysis with low abundant targets: from variable nonsense to publication quality data

Quantitative PCR (qPCR) has become the gold standard technique to measure cDNA and gDNA levels but the resulting data can be highly variable, artifactual and non-reproducible without appropriate verification and validation of both samples and primers. The root cause of poor quality data is typically associated with inadequate dilution of residual protein and chemical contaminants that variably inhibit Taq polymerase and primer annealing. The most susceptible, frustrating and often most interesting samples are those containing low abundant targets with small expression differences of 2-fold or lower. Here, Droplet Digital PCR (ddPCR) and qPCR platforms were directly compared for gene expression analysis using low amounts of purified, synthetic DNA in well characterized samples under identical reaction conditions. We conclude that for sample/target combinations with low levels of nucleic acids (Cq ≥ 29) and/or variable amounts of chemical and protein contaminants, ddPCR technology will produce more precise, reproducible and statistically significant results required for publication quality data. A stepwise methodology is also described to choose between these complimentary technologies to obtain the best results for any experiment.

Reproducibility of biomedical research - The importance of editorial vigilance

Many journal editors are a failing to implement their own authors' instructions, resulting in the publication of many articles that do not meet basic standards of transparency, employ unsuitable data analysis methods and report overly optimistic conclusions. This problem is particularly acute where quantitative measurements are made and results in the publication of papers that lack scientific rigor and contributes to the concerns with regard to the reproducibility of biomedical research. This hampers research areas such as biomarker identification, as reproducing all but the most striking changes is challenging and translation to patient care rare.

Identification of reference genes for qPCR analysis during hASC long culture maintenance

Up to now quantitative PCR based assay is the most common method for characterizing or confirming gene expression patterns and comparing mRNA levels in different sample populations. Since this technique is relative easy and low cost compared to other methods of characterization, e.g. flow cytometry, we used it to typify human adipose-derived stem cells (hASCs). hASCs possess several characteristics that make them attractive for scientific research and clinical applications. Accurate normalization of gene expression relies on good selection of reference genes and the best way to choose them appropriately is to follow the common rule of the “Best 3”, at least three reference genes, three different validation software and three sample replicates. Analysis was performed on hASCs cultivated until the eleventh cell confluence using twelve candidate reference genes, initially selected from literature, whose stability was evaluated by the algorithms NormFinder, BestKeeper, RefFinder and IdealRef, a home-made version of GeNorm. The best gene panel (RPL13A, RPS18, GAPDH, B2M, PPIA and ACTB), determined in one patient by IdealRef calculation, was then investigated in other four donors. Although patients demonstrated a certain gene expression variability, we can assert that ACTB is the most unreliable gene whereas ribosomal proteins (RPL13A and RPS18) show minor inconstancy in their mRNA expression. This work underlines the importance of validating reference genes before conducting each experiment and proposes a free software as alternative to those existing.

Validation of suitable normalizers for miR expression patterns analysis covering tumour heterogeneity

Oncogenic microRNAs (miRs) have emerged as diagnostic biomarkers and novel molecular targets for anti-cancer drug therapies. Real-time quantitative PCR (qPCR) is one of the most powerful techniques for analyzing miRs; however, the use of unsuitable normalizers might bias the results. Tumour heterogeneity makes even more difficult the selection of an adequate endogenous normalizer control. Here, we have evaluated five potential referenced small RNAs (U6, rRNA5s, SNORD44, SNORD24 and hsa-miR-24c-3p) using RedFinder algorisms to perform a stability expression analysis in i) normal colon cells, ii) colon and breast cancer cell lines and iii) cancer stem-like cell subpopulations. We identified SNORD44 as a suitable housekeeping gene for qPCR analysis comparing normal and cancer cells. However, this small nucleolar RNA was not a useful normalizer for cancer stem-like cell subpopulations versus subpopulations without stemness properties. In addition, we show for the first time that hsa-miR-24c-3p is the most stable normalizer for comparing these two subpopulations. Also, we have identified by bioinformatic and qPCR analysis, different miR expression patterns in colon cancer versus non tumour cells using the previously selected suitable normalizers. Our results emphasize the importance of select suitable normalizers to ensure the robustness and reliability of qPCR data for analyzing miR expression.

Effects of RNAi-mediated MUC4 gene silencing on the proliferation and migration of human pancreatic carcinoma BxPC-3 cells

It was previously demonstrated that mucin 4 (MUC4) is not expressed in normal pancreatic tissues or in chronic pancreatitis tissue but is highly expressed in pancreatic cancer (PC) tissue. Effective MUC4 gene knockdown in PC may contribute to the elucidation of pancreatic tumor development and metastasis, and may be valuable in new therapeutic approaches. Thus to confirm this, in the present study, the BxPC-3 cell line was transfected with eight pairs of shRNA lentiviral vectors for MUC4. The qPCR results showed that expression of MUC4 mRNA in the BxPC-3 cells was significantly decreased at 96 h after transfection. One of these shRNA lentiviral vectors (shRNA‑A141) had showed the strongest suppressive effect on MUC4 mRNA expression and was used for MUC4 knockdown in BxPC-3 cells. After stable transfection, BxPC-3 cells showed a significantly lower expression of MUC4 mRNA and MUC4 protein, and were suppressed on cell growth and migration. In vivo, lower tumor growth rates and tumor volume were observed in the tumors derived from the MUC4-knockdown cells, whereas the transplanted tumors derived from the control group cells, grew rapidly. Thus, inhibition of MUC4 expression may be an effective means for mitigating metastasis and invasion of PC.

Selection and validation of miRNAs as normalizers for profiling expression of microRNAs isolated from thyroid fine needle aspiration smears

Fine needle aspiration cytology (FNAC) is currently the method of choice for malignancy prediction in thyroid nodules. Nevertheless, in some cases the interpretation of FNAC results may be problematic due to limitations of the method. The expression level of some microRNAs changes with the development of thyroid tumors, and its quantitation can be used to refine the FNAC results. For this quantitation to be reliable, the obtained data must be adequately normalized. Currently, no reference genes are universally recognized for quantitative assessments of microRNAs in thyroid nodules. The aim of the present study was the selection and validation of such reference genes. Expression of 800 microRNAs in 5 paired samples of thyroid surgical material corresponding to different histotypes of tumors was analyzed using NanoString technology and four of these (hsa-miR-151a-3p, -197-3p, -99a-5p and -214-3p) with the relatively low variation coefficient were selected. The possibility of use of the selected microRNAs and their combination as references was estimated by RT-qPCR on a sampling of cytological smears: benign (n=226), atypia of undetermined significance (n=9), suspicious for follicular neoplasm (n=61), suspicious for malignancy (n=19), medullary thyroid carcinoma (MTC) (n=32), papillary thyroid carcinoma (PTC) (n=54) and non-diagnostic material (ND) (n=34). In order to assess the expression stability of the references, geNorm algorithm was used. The maximum stability was observed for the normalization factor obtained by the combination of all 4 microRNAs. Further validation of the complex normalizer and individual selected microRNAs was performed using 5 different classification methods on 3 groups of FNAC smears from the analyzed batch: benign neoplasms, MTC and PTC. In all cases, the use of the complex classifier resulted in the reduced number of errors. On using the complex microRNA normalizer, the decision-tree method C4.5 makes it possible to distinguish between malignant and benign thyroid neoplasms in cytological smears with high overall accuracy (>91%).

The importance of selecting the appropriate reference genes for quantitative real time PCR as illustrated using colon cancer cells and tissue

Quantitative real-time reverse-transcription polymerase chain reaction (RT-qPCR) remains the most sensitive technique for nucleic acid quantification. Its popularity is reflected in the remarkable number of publications reporting RT-qPCR data. Careful normalisation within RT-qPCR studies is imperative to ensure accurate quantification of mRNA levels. This is commonly achieved through the use of reference genes as an internal control to normalise the mRNA levels between different samples. The selection of appropriate reference genes can be a challenge as transcript levels vary with physiology, pathology and development, making the information within the transcriptome flexible and variable. In this study, we examined the variation in expression of a panel of nine candidate reference genes in HCT116 and HT29 2-dimensional and 3-dimensional cultures, as well as in normal and cancerous colon tissue. Using normfinder we identified the top three most stable genes for all conditions. Further to this we compared the change in expression of a selection of PKC coding genes when the data was normalised to one reference gene and three reference genes. Here we demonstrated that there is a variation in the fold changes obtained dependent on the number of reference genes used. As well as this, we highlight important considerations namely; assay efficiency tests, inhibition tests and RNA assessment which should also be implemented into all RT-qPCR studies. All this data combined demonstrates the need for careful experimental design in RT-qPCR studies to help eliminate false interpretation and reporting of results.

Improving the reliability of peer-reviewed publications: We are all in it together

The current, and welcome, focus on standardization of techniques and transparency of reporting in the biomedical, peer-reviewed literature is commendable. However, that focus has been intermittent as well as lacklustre and so failed to tackle the alarming lack of reliability and reproducibly of biomedical research. Authors have access to numerous recommendations, ranging from simple standards dealing with technical issues to those regulating clinical trials, suggesting that improved reporting guidelines are not the solution. The elemental solution is for editors to require meticulous implementation of their journals' instructions for authors and reviewers and stipulate that no paper is published without a transparent, complete and accurate materials and methods section.

The importance of selecting the appropriate reference genes for quantitative real time PCR as illustrated using colon cancer cells and tissue

Quantitative real-time reverse-transcription polymerase chain reaction (RT-qPCR) remains the most sensitive technique for nucleic acid quantification. Its popularity is reflected in the remarkable number of publications reporting RT-qPCR data. Careful normalisation within RT-qPCR studies is imperative to ensure accurate quantification of mRNA levels. This is commonly achieved through the use of reference genes as an internal control to normalise the mRNA levels between different samples. The selection of appropriate reference genes can be a challenge as transcript levels vary with physiology, pathology and development, making the information within the transcriptome flexible and variable. In this study, we examined the variation in expression of a panel of nine candidate reference genes in HCT116 and HT29 2-dimensional and 3-dimensional cultures, as well as in normal and cancerous colon tissue. Using normfinder we identified the top three most stable genes for all conditions. Further to this we compared the change in expression of a selection of PKC coding genes when the data was normalised to one reference gene and three reference genes. Here we demonstrated that there is a variation in the fold changes obtained dependent on the number of reference genes used. As well as this, we highlight important considerations namely; assay efficiency tests, inhibition tests and RNA assessment which should also be implemented into all RT-qPCR studies. All this data combined demonstrates the need for careful experimental design in RT-qPCR studies to help eliminate false interpretation and reporting of results.

Generating a long DNA fragment of the target ncRNA for quantitative polymerase chain reaction by combining ncRNA-oligos hybridization and oligos ligation

The poor reproducibility of the reverse transcription combined with quantitative polymerase chain reaction (RT-qPCR) results in an unacceptable reliability of publications based on these data. We established a novel method, in which two short complementary DNA oligos were hybridized with target ncRNA molecules and linked by DNA ligase to obtain a long DNA strand (HL-DNA) replacing cDNA for qPCR detection (HL-qPCR). A series of diluted samples prepared from the same total RNA resource were measured by HL-qPCR and RT-qPCR respectively to acquire their relative concentration of RNU4-1, AK026510 and SNORA73B. For every tested sample, the relative concentration of RNU4-1, AK026510 and SNORA73B obtained by HL-qPCR instead of RT-qPCR is closer to its corresponding true value without significant difference, demonstrating that HL-qPCR exhibits higher accuracy compared with RT-qPCR. With three independent repeats, no significant difference was observed among AK026510/RNU4-1 values of four samples diluted from the same RNA resource, by employing HL-qPCR but not RT-qPCR. It strongly suggests that the good reproducibility of HL-qPCR results from the stable efficiency of HL-DNA production regardless of the concentration and individual features of ncRNA. The novel HL-qPCR could be applied for the regular relative ncRNA concentration detection in the future.

The Orthology Clause in the Next Generation Sequencing Era: Novel Reference Genes Identified by RNA-seq in Humans Improve Normalization of Neonatal Equine Ovary RT-qPCR Data

BACKGROUND

Vertebrate evolution is accompanied by a substantial conservation of transcriptional programs with more than a third of unique orthologous genes showing constrained levels of expression. Moreover, there are genes and exons exhibiting excellent expression stability according to RNA-seq data across a panel of eighteen tissues including the ovary (Human Body Map 2.0).

RESULTS

We hypothesized that orthologs of these exons would also be highly uniformly expressed across neonatal ovaries of the horse, which would render them appropriate reference genes (RGs) for normalization of reverse transcription quantitative PCR (RT-qPCR) data in this context. The expression stability of eleven novel RGs (C1orf43, CHMP2A, EMC7, GPI, PSMB2, PSMB4, RAB7A, REEP5, SNRPD3, VCP and VPS29) was assessed by RT-qPCR in ovaries of seven neonatal fillies and compared to that of the expressed repetitive element ERE-B, two universal (OAZ1 and RPS29) and four traditional RGs (ACTB, GAPDH, UBB and B2M). Expression stability analyzed with the software tool RefFinder top ranked the normalization factor constituted of the genes SNRPD3 and VCP, a gene pair that is not co-expressed according to COEXPRESdb and GeneMANIA. The traditional RGs GAPDH, B2M, ACTB and UBB were only ranked 3rd and 12th to 14th, respectively.

CONCLUSIONS

The functional diversity of the novel RGs likely facilitates expression studies over a wide range of physiological and pathological contexts related to the neonatal equine ovary. In addition, this study augments the potential for RT-qPCR-based profiling of human samples by introducing seven new human RG assays (C1orf43, CHMP2A, EMC7, GPI, RAB7A, VPS29 and UBB).

Optimization of Droplet Digital PCR from RNA and DNA extracts with direct comparison to RT-qPCR: Clinical implications for quantification of Oseltamivir-resistant subpopulations

The recent introduction of Droplet Digital PCR (ddPCR) has provided researchers with a tool that permits direct quantification of nucleic acids from a wide range of samples with increased precision and sensitivity versus RT-qPCR. The sample interdependence of RT-qPCR stemming from the measurement of Cq and ΔCq values is eliminated with ddPCR which provides an independent measure of the absolute nucleic acid concentration for each sample without standard curves thereby reducing inter-well and inter-plate variability. Well-characterized RNA purified from H275-wild type (WT) and H275Y-point mutated (MUT) neuraminidase of influenza A (H1N1) pandemic 2009 virus was used to demonstrate a ddPCR optimization workflow to assure robust data for downstream analysis. The ddPCR reaction mix was also tested with RT-qPCR and gave excellent reaction efficiency (between 90% and 100%) with the optimized MUT/WT duplexed assay thus enabling the direct comparison of the two platforms from the same reaction mix and thermal cycling protocol. ddPCR gave a marked improvement in sensitivity (>30-fold) for mutation abundance using a mixture of purified MUT and WT RNA and increased precision (>10 fold, p<0.05 for both inter- and intra-assay variability) versus RT-qPCR from patient samples to accurately identify residual mutant viral population during recovery.

Guiding our PCR experiments

The MIQE guidelines for qPCR and dPCR have been around for a while now, but few are taking advantage of this resource. Jeffrey Perkel looks at challenge of standardizing PCR.

Identification of optimal reference genes for gene expression normalization in a wide cohort of endometrioid endometrial carcinoma tissues

Accurate normalization is a primary component of a reliable gene expression analysis based on qRT-PCR technique. While the use of one or more reference genes as internal controls is commonly accepted as the most appropriate normalization strategy, many qPCR-based published studies still contain data poorly normalized and reference genes arbitrarily chosen irrespective of the particular tissue and the specific experimental design. To date, no validated reference genes have been identified for endometrial cancer tissues. In this study, 10 normalization genes (GAPDH, B2M, ACTB, POLR2A, UBC, PPIA, HPRT1, GUSB, TBP, H3F3A) belonging to different functional and abundance classes in various tissues and used in different studies, were analyzed to determine their applicability. In total, 100 endometrioid endometrial cancer samples, which were carefully balanced according to their tumor grade, and 29 normal endometrial tissues were examined using SYBR Green Real-Time RT-PCR. The expression stability of candidate reference genes was determined and compared by means of geNorm and NormFinder softwares. Both algorithms were in agreement in identifying GAPDH, H3F3A, PPIA, and HPRT1 as the most stably expressed genes, only differing in their ranking order. Analysis performed on the expression levels of all candidate genes confirm HPRT1 and PPIA as the most stably expressed in the study groups regardless of sample type, to be used alone or better in combination. As the stable expression of HPRT1 and PPIA between normal and tumor endometrial samples fulfill the basic requirement of a reference gene to be used for normalization purposes, HPRT1 expression showed significant differences between samples from low-grade and high-grade tumors. In conclusion, our results recommend the use of PPIA as a single reference gene to be considered for improved reliability of normalization in gene expression studies involving endometrial tumor samples at different tumor degrees.

Identification of a suitable qPCR reference gene in metastatic clear cell renal cell carcinoma

There is no data on reference gene (RG) selection in metastatic clear-cell renal cell carcinoma (mccRCC) for quantitative PCR (qPCR) data normalization. We aimed at selecting the most stable RG for further determination of new prognostic markers. Thirty-five nonmetastatic and 35 mccRCC patients undergoing radical nephrectomy were included. Paired primary tumor (T, n = 70) and normal (C, n = 70) kidney fragments were collected; from 12 out of 35 mccRCC cases, we also collected metastasized regional lymph nodes and adrenal gland tissues (M, n = 12). After RNA extraction, reverse transcription and qPCR were performed. Samples were divided into four analyzed groups. Fifteen candidate RGs were tested by RefFinder tool and manual statistics. To present the importance of RG selection, TP53 gene expression levels in samples were normalized with the use of RG data. RPL13 gene was the most stable RG in analysis of 35 primary tumor nonmetastatic versus 35 mccRCC samples and matched metastasized T/C/M samples (n = 12, each group). GUSB was the most suitable RG in total 152 samples and in paired T and C (n = 140) kidney samples. Expression of GUSB, RPL13, and the RPL13 + RPLP0 pair were independent of clinical/sample variables. Normalization of TP53 expression levels showed variability of GAPDH and ACTB assays. GUSB or RPL13 assays should be used in mccRCC for qPCR data normalization whereas GAPDH and ACTB assays should be avoided. Prior RG studies should precede each qPCR gene expression study since RG selection is associated with the origin and proportion of specimens.

The reproducibility of biomedical research: Sleepers awake!

There is increasing concern about the reliability of biomedical research, with recent articles suggesting that up to 85% of research funding is wasted. This article argues that an important reason for this is the inappropriate use of molecular techniques, particularly in the field of RNA biomarkers, coupled with a tendency to exaggerate the importance of research findings.

Quantifying mRNA and microRNA with qPCR in cervical carcinogenesis: a validation of reference genes to ensure accurate data

A number of recent studies have catalogued global gene expression patterns in a panel of normal, tumoral cervical tissues so that potential biomarkers can be identified. The qPCR has been one of the most widely used technologies for detecting these potential biomarkers. However, few studies have investigated a correct strategy for the normalization of data in qPCR assays for cervical tissues. The aim of this study was to validate reference genes in cervical tissues to ensure accurate quantification of mRNA and miRNA levels in cervical carcinogenesis. For this purpose, some issues for obtaining reliable qPCR data were evaluated such as the following: geNorm analysis with a set of samples which meet all of the cervical tissue conditions (Normal + CIN1 + CIN2 + CIN3 + Cancer); the use of individual Ct values versus pooled Ct values; and the use of a single (or multiple) reference genes to quantify mRNA and miRNA expression levels. Two different data sets were put on the geNorm to assess the expression stability of the candidate reference genes: the first dataset comprised the quantities of the individual Ct values; and the second dataset comprised the quantities of the pooled Ct values. Moreover, in this study, all the candidate reference genes were analyzed as a single “normalizer”. The normalization strategies were assessed by measuring p16^INK4a and miR-203 transcripts in qPCR assays. We found that the use of pooled Ct values, can lead to a misinterpretation of the results, which suggests that the maintenance of inter-individual variability is a key factor in ensuring the reliability of the qPCR data. In addition, it should be stressed that a proper validation of the suitability of the reference genes is required for each experimental setting, since the indiscriminate use of a reference gene can also lead to discrepant results.

Variability of the reverse transcription step: practical implications

BACKGROUND

The reverse transcription (RT) of RNA to cDNA is a necessary first step for numerous research and molecular diagnostic applications. Although RT efficiency is known to be variable, little attention has been paid to the practical implications of that variability.

METHODS

We investigated the reproducibility of the RT step with commercial reverse transcriptases and RNA samples of variable quality and concentration. We quantified several mRNA targets with either singleplex SYBR Green I or dualplex probe-based reverse transcription real-time quantitative PCR (RT-qPCR), with the latter used to calculate the correlation between quantification cycles (Cqs) of mRNA targets amplified in the same real-time quantitative PCR (qPCR) assay.

RESULTS

RT efficiency is enzyme, sample, RNA concentration, and assay dependent and can lead to variable correlation between mRNAs from the same sample. This translates into relative mRNA expression levels that generally vary between 2- and 3-fold, although higher levels are also observed.

CONCLUSIONS

Our study demonstrates that the variability of the RT step is sufficiently large to call into question the validity of many published data that rely on quantification of cDNA. Variability can be minimized by choosing an appropriate RTase and high concentrations of RNA and characterizing the variability of individual assays by use of multiple RT replicates.

Influence of trypsinization and alternative procedures for cell preparation before RNA extraction on RNA integrity

The accuracy of techniques such as microarrays, reverse transcription polymerase chain reaction, and whole transcriptome shotgun sequencing is critically dependent on RNA quality. We have repeatedly observed extensive RNA degradation following trypsinization, a routine procedure used to dissociate adherent tissue culture cells prior to RNA extraction. This study investigated the cause of this degradation and identifies an alternative procedure that enables extraction of intact high-quality RNA. Trypsinization and several alternative procedures were used to dissociate a range of different cell lines prior to RNA extraction. The contribution of exogenous ribonucleases or induction of endogenous ribonucleases by trypsin reagent proteases to RNA degradation was examined. Trypsinization resulted in a complete degradation of RNA regardless of cell line type, differentiation stage, or passage number. This occurred when intact RNA was incubated directly with trypsin and was not suppressed by inhibiting trypsin's protease activity. Prevention of degradation by sodium hypochlorite treatment of trypsin reagent identified the presence of ribonucleases in trypsin derived from animal pancreas. Consistent extraction of high-quality RNA requires the use of direct cell lysis with a phenol guanidine-based reagent or an animal origin-free protease-based dissociation agent if enzymatic detachment prior to RNA extraction cannot be avoided.

Critical appraisal of quantitative PCR results in colorectal cancer research: can we rely on published qPCR results?

The use of real-time quantitative polymerase chain reaction (qPCR) in cancer research has become ubiquitous. The relative simplicity of qPCR experiments, which deliver fast and cost-effective results, means that each year an increasing number of papers utilizing this technique are being published. But how reliable are the published results? Since the validity of gene expression data is greatly dependent on appropriate normalisation to compensate for sample-to-sample and run-to-run variation, we have evaluated the adequacy of normalisation procedures in qPCR-based experiments. Consequently, we assessed all colorectal cancer publications that made use of qPCR from 2006 until August 2013 for the number of reference genes used and whether they had been validated. Using even these minimal evaluation criteria, the validity of only three percent (6/179) of the publications can be adequately assessed. We describe common errors, and conclude that the current state of reporting on qPCR in colorectal cancer research is disquieting. Extrapolated to the study of cancer in general, it is clear that the majority of studies using qPCR cannot be reliably assessed and that at best, the results of these studies may or may not be valid and at worst, pervasive incorrect normalisation is resulting in the wholesale publication of incorrect conclusions. This survey demonstrates that the existence of guidelines, such as MIQE, is necessary but not sufficient to address this problem and suggests that the scientific community should examine its responsibility and be aware of the implications of these findings for current and future research.