Comparison of reverse transcriptases in gene expression analysis

Validation of one-step reverse transcription digital PCR assays for Norovirus GI

Regular monitoring of Norovirus presence in environmental and food samples is crucial due to its high transmission rates and outbreak potential. For detecting Norovirus GI, reverse transcription qPCR method is commonly used, but its sensitivity can be affected by assay performance. This study shows significantly reduced assay performance in digital PCR or qPCR when using primers targeting Norovirus GI genome 5291-5319 (NC_001959), located on the hairpin of the predicted RNA structure. It is highly recommended to avoid this region in commercial kit development or diagnosis to minimizing potential risk of false negatives.

Exploring the impact of primer length on efficient gene detection via high-throughput sequencing

Reverse transcription (RT) is a crucial step in most RNA analysis methods. Optimizing protocols for this initial stage is critical for effective target detection, particularly when working with limited input RNA. Several factors, such as the input material quality and reaction conditions, influence RT efficiency. However, the effect of RT primer length on gene detection efficiency remains largely unknown. Thus, we investigate its impact by generating RNA-seq libraries with random RT primers of 6, 12, 18, or 24 nucleotides. To our surprise, the 18mer primer shows superior efficiency in overall transcript detection compared to the commonly used 6mer primer, especially in detecting longer RNA transcripts in complex human tissue samples. This study highlights the critical role of primer length in RT efficiency, which has significant potential to benefit various transcriptomic assays, from basic research to clinical diagnostics, given the central role of RT in RNA-related analyses.

Interfering factors in the diagnosis of Senecavirus A

BACKGROUND

Senecavirus A (SV-A) is an RNA virus that belongs to the genus Senecavirus within the family Picornaviridae. This study aimed to analyze factors that can influence the molecular diagnosis of Senecavirus A, such as oligonucleotides, RNA extraction methods, and RT-qPCR kits.

METHODS

Samples from suspected cases of vesicular disease in Brazilian pigs were analyzed for foot-and-mouth disease, swine vesicular disease, and vesicular stomatitis. All tested negative for these diseases but positive for SV-A. RT-qPCR tests were used, comparing different reagent kits and RNA extraction methods. Sensitivity and repeatability were evaluated, demonstrating efficacy in detecting SV-A in clinical samples.

RESULTS

In RNA extraction, significant reduction in Cq values was observed with initial dilutions, particularly with larger supernatant volumes. Trizol and Maxwell showed greater sensitivity in automated equipment protocols, though results varied in tissue tests. RT-qPCR kit comparison revealed differences in amplification using viral RNA but minimal differences with plasmid DNA. Sensitivity among methods was comparable, with slight variations in non-amplified samples. Repeatability tests showed consistent results among RT-qPCRs, demonstrating similarity between methods despite minor discrepancies in Cq values.

CONCLUSIONS

Trizol, silica columns, and semi-automated extraction were compared, as well as different RT-qPCR kits. The study found significant variations that could impact the final diagnosis.

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.

Digital RNA sequencing using unique molecular identifiers enables ultrasensitive RNA mutation analysis

Mutation analysis is typically performed at the DNA level since most technical approaches are developed for DNA analysis. However, some applications, like transcriptional mutagenesis, RNA editing and gene expression analysis, require RNA analysis. Here, we combine reverse transcription and digital DNA sequencing to enable low error digital RNA sequencing. We evaluate yield, reproducibility, dynamic range and error correction rate for seven different reverse transcription conditions using multiplexed assays. The yield, reproducibility and error rate vary substantially between the specific conditions, where the yield differs 9.9-fold between the best and worst performing condition. Next, we show that error rates similar to DNA sequencing can be achieved for RNA using appropriate reverse transcription conditions, enabling detection of mutant allele frequencies <0.1% at RNA level. We also detect mutations at both DNA and RNA levels in tumor tissue using a breast cancer panel. Finally, we demonstrate that digital RNA sequencing can be applied to liquid biopsies, analyzing cell-free gene transcripts. In conclusion, we demonstrate that digital RNA sequencing is suitable for ultrasensitive RNA mutation analysis, enabling several basic research and clinical applications.

Recommendations for Method Development and Validation of qPCR and dPCR Assays in Support of Cell and Gene Therapy Drug Development

The emerging use of qPCR and dPCR in regulated bioanalysis and absence of regulatory guidance on assay validations for these platforms has resulted in discussions on lack of harmonization on assay design and appropriate acceptance criteria for these assays. Both qPCR and dPCR are extensively used to answer bioanalytical questions for novel modalities such as cell and gene therapies. Following cross-industry conversations on the lack of information and guidelines for these assays, an American Association of Pharmaceutical Scientists working group was formed to address these gaps by bringing together 37 industry experts from 24 organizations to discuss best practices to gain a better understanding in the industry and facilitate filings to health authorities. Herein, this team provides considerations on assay design, development, and validation testing for PCR assays that are used in cell and gene therapies including (1) biodistribution; (2) transgene expression; (3) viral shedding; (4) and persistence or cellular kinetics of cell therapies.

A duplex droplet digital PCR assay for absolute quantification and characterization of long self-amplifying RNA

Self-amplifying messenger ribonucleic acid (saRNA) provides extended expression of genes of interest by encoding an alphavirus-derived RNA replicase and thus is 2-3 times larger than conventional messenger RNA. However, quality assessment of long RNA transcripts is challenging using standard techniques. Here, we utilized a multiplex droplet digital polymerase chain reaction (ddPCR) assay to assess the quality of saRNA produced from an in vitro transcription reaction and the replication kinetics in human cell lines. Using the one-step reverse transcription ddPCR, we show that an in vitro transcription generates 50-60% full-length saRNA transcripts. However, we note that the two-step reverse transcription ddPCR assay results in a 20% decrease from results obtained using the one-step and confirmed using capillary gel electrophoresis. Additionally, we provided three formulas that differ in the level of stringency and assumptions made to calculate the fraction of intact saRNA. Using ddPCR, we also showed that subgenomic transcripts of saRNA were 19-to-108-fold higher than genomic transcripts at different hours post-transfection of mammalian cells in copies. Therefore, we demonstrate that multiplex ddPCR is well suited for quality assessment of long RNA and replication kinetics of saRNA based on absolute quantification.

Improved protocol for Bst polymerase and reverse transcriptase production and application to a point-of-care diagnostics system

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has raised awareness in the scientific community about the importance of being prepared for sanitary emergencies. Many measures implemented during the COVID pandemic are now being expanded to other applications. In the field of molecular and immunological diagnostics, the need to massively test the population worldwide resulted in the application of a variety of methods to detect viral infection. Besides gold standard reverse transcription quantitative polymerase chain reaction (RT-qPCR), the use of reverse transcription loop-mediated isothermal amplification (RT-LAMP) arose as an alternative and sensitive method to amplify and detect viral genetic material. We have used openly available protocols and have improved the protein production of RT-LAMP enzymes Bst polymerase and HIV-reverse transcriptase. To optimize enzyme production, we tested different protein tags, and we shortened the protein purification protocol, resulting in reduced processing time and handling of the enzymes and, thus, preserved the protein activity with high purity. The enzymes showed significant stability at 4 °C and 25 °C, over 60 days, and were highly reliable when used as a one-step RT-LAMP reaction in a portable point-of-care device with clinical samples. The enzymes and the reaction setup can be further expanded to detect other infectious diseases agents.

Artifacts and biases of the reverse transcription reaction in RNA sequencing

RNA sequencing has spurred a significant number of research areas in recent years. Most protocols rely on synthesizing a more stable complementary DNA (cDNA) copy of the RNA molecule during the reverse transcription reaction. The resulting cDNA pool is often wrongfully assumed to be quantitatively and molecularly similar to the original RNA input. Sadly, biases and artifacts confound the resulting cDNA mixture. These issues are often overlooked or ignored in the literature by those that rely on the reverse transcription process. In this review, we confront the reader with intra- and intersample biases and artifacts caused by the reverse transcription reaction during RNA sequencing experiments. To fight the reader's despair, we also provide solutions to most issues and inform on good RNA sequencing practices. We hope the reader can use this review to their advantage, thereby contributing to scientifically sound RNA studies.

One-step endpoint RT-PCR assays for confirmatory body fluid identification

Messenger RNA (mRNA) expression analysis is increasingly used in casework, in the form of multiplex two-step reverse transcriptase PCR (RT-PCR) assays such as CellTyper 2 (CT2), developed by the Institute of Environmental Science and Research (ESR). This paper presents the development of a one-step endpoint RT-PCR workflow to improve the efficiency and precision of confirmatory body fluid identification. A comparative study of commercial one-step RT-PCR kits was undertaken, with the highest performing kit (RNA to C_T) retained for further development. Sensitivity, specificity across body fluids, and precision was assessed simultaneously using receiver operating characteristic (ROC) curves. An optimal RFU cut-off value which maximised sensitivity and specificity was determined for each marker. All assays performed significantly better when compared to the equivalent of a completely uninformative test (area under the curve of 0.5) for their target body fluid. Sensitivity varied between different donors, but the limit of detectionss were estimated as follows; saliva markers HTN3: 1 in 100 dilution of a whole buccal swab and FDCSP: 1 in 10 dilution of a whole buccal swab, circulatory blood marker SLC4A1: 0.1 µL blood, menstrual fluid markers STC1, MMP10: 1 in 10 dilution of a whole menstrual swab, spermatozoa markers PRM1, TNP1: 0.1 µL semen, seminal fluid markers KLK2: 0.1 µL semen and MSMB: 0.01 µL semen, and vaginal material marker CYP2B7P: 1 in 1000 dilution of a whole vaginal swab. The method successfully detected most body fluids in a range of simple mixtures with 77 out of 80 markers observed when expected. The developed one-step endpoint RT-PCR assays lack the sensitivity and precision required for forensic casework and provide little benefit when compared with standard two-step endpoint RT-PCR, other than minimal time and cost savings, similar sensitivity, and improved precision for some markers. As both methods utilise endpoint RT-PCR, they have the same narrow linear dynamic range. The novel method is therefore similarly susceptible to varied RNA input, a major disadvantage of this approach. The limited sensitivity and precision consistently encountered with endpoint RT-PCR - regardless of cDNA synthesis strategy - could be addressed by a real-time PCR approach.

The chromosome-scale genome assembly of the yellowtail clownfish Amphiprion clarkii provides insights into the melanic pigmentation of anemonefish

Anemonefish are an emerging group of model organisms for studying genetic, ecological, evolutionary, and developmental traits of coral reef fish. The yellowtail clownfish Amphiprion clarkii possesses species-specific characteristics such as inter-species co-habitation, high intra-species color variation, no anemone specificity, and a broad geographic distribution, that can increase our understanding of anemonefish evolutionary history, behavioral strategies, fish-anemone symbiosis, and color pattern evolution. Despite its position as an emerging model species, the genome of A. clarkii is yet to be published. Using PacBio long-read sequencing and Hi-C chromatin capture technology, we generated a high-quality chromosome-scale genome assembly initially comprised of 1,840 contigs with an N50 of 1,203,211 bp. These contigs were successfully anchored into 24 chromosomes of 843,582,782 bp and annotated with 25,050 protein-coding genes encompassing 97.0% of conserved actinopterygian genes, making the quality and completeness of this genome the highest among all published anemonefish genomes to date. Transcriptomic analysis identified tissue-specific gene expression patterns, with the brain and optic lobe having the largest number of expressed genes. Further analyses revealed higher copy numbers of erbb3b (a gene involved in melanocyte development) in A. clarkii compared with other anemonefish, thus suggesting a possible link between erbb3b and the natural melanism polymorphism observed in A. clarkii. The publication of this high-quality genome, along with A. clarkii's many unique traits, position this species as an ideal model organism for addressing scientific questions across a range of disciplines.

Gene Expression Quantification from Pathogenic Bacterial Biofilms by Quantitative PCR

Quantitative PCR (qPCR) is one of the most used techniques to quantify gene expression in bacterial biofilms due to its easiness, sensitivity, and robustness. However, several practical aspects need to be considered to obtain accurate and reliable results. Here, we describe a detailed and optimized protocol to quantify mRNA transcripts from bacterial biofilms using qPCR, including pieces of advice to improve RNA quality, which ultimately increases the accuracy, consistency, and relevance of gene expression data.

Quantitative analysis of miRNAs using SplintR ligase-mediated ligation of complementary-pairing probes enhanced by RNase H (SPLICER)-qPCR

Here, a method using SplintR ligase-mediated ligation of complementary-pairing probes enhanced by RNase H (SPLICER) for miRNAs quantification was established. The strategy has two steps: (1) ligation of two DNA probes specifically hybridize to target miRNA and (2) qPCR amplifying the ligated probe. The miRNA-binding regions of the probes are stem-looped, a motif significantly reduces nonspecific ligation at high ligation temperature (65°C). The ends of the probes are designed complementary to form a paired probe, facilitating the recognition of target miRNAs with low concentrations. RNase H proved to be able to stabilize the heteroduplex formed by the probe and target miRNA, contributing to enhanced sensitivity (limit of detection = 60 copies). High specificity (discriminating homology miRNAs differing only one nucleotide), wide dynamic range (seven orders of magnitude) and ability to accurately detect plant miRNAs (immune to hindrance of 2'-O-methyl moiety) enable SPLICER comparable with the commercially available TaqMan and miRCURY assays. SYBR green I, rather than expensive hydrolysis or locked nucleic acid probes indispensable to TaqMan and miRCURY assays, is adequate for SPLICER. The method was efficient (<1 h), economical ($7 per sample), and robust (able to detect xeno-miRNAs in mammalian bodies), making it a powerful tool for molecular diagnosis and corresponding therapy.

Comparison of Reverse Transcriptase (RT) Activities of Various M-MuLV RTs for RT-LAMP Assays

Reverse transcriptases (RTs) are a family of enzymes synthesizing DNA using RNA as a template and serving as indispensable tools in studies related to RNA. M-MuLV RT and its analogs are the most commonly used RTs. RTs are widely applied in various diagnostics methods, including reverse-transcription loop-mediated isothermal amplification (RT-LAMP). However, the performance of different RTs in LAMP remains relatively unknown. Here, we report on the first direct comparison of various M-MuLV RTs in RT-LAMP, including enzymes with a different number of mutations and fusions with Sto7d. Several parameters were assessed, namely: optimal reaction temperature, enzyme concentration, reverse transcription time, a minimal amount of RNA template, and tolerance to inhibitors. Mutations increased the optimal reaction temperature from 55 °C to 60-65 °C. All of the RTs were suitable for RT-LAMP with RNA templates in the range of 10¹-10⁶ copies per reaction. Highly mutated enzymes were 1.5-3-fold more tolerant to whole blood, blood plasma, and guanidinium, but they were two-fold more sensitive to high concentrations of NaCl. The comparison of different RTs presented here could be helpful for selecting the optimal enzyme when developing novel LAMP-based diagnostic tests.

Accurate quantification of SARS-CoV-2 RNA by isotope dilution mass spectrometry and providing a correction of reverse transcription efficiency in droplet digital PCR

The novel coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected more than 505 million confirmed cases, including over 6 million deaths. Reference materials (RMs) of SARS-CoV-2 RNA played a crucial role in performance evaluation and quality control of testing laboratories. As the potential primary characterization method of RMs, reverse transcription digital PCR (RT-dPCR) measures the copy number of RNA, but the accuracy of reverse transcription (RT) efficiency has yet to be confirmed. This study established a method of enzymatic digestion followed by isotope dilution mass spectrometry (IDMS), which does not require an RT reaction, to quantify in vitro-transcribed SARS-CoV-2 RNA. RNA was digested to nucleotide monophosphate (NMP) within 15 min and analyzed by IDMS within 5 min. The consistency among the results of four different NMPs demonstrated the reliability of the proposed method. Compared to IDMS, the quantitative result of RT-dPCR turned out to be about 10% lower, possibly attributed to the incompleteness of the reverse transcription process. Therefore, the proposed approach could be valuable and reliable for quantifying RNA molecules and evaluating the RT efficiency of RT-based methods.

Selective ablation of 3' RNA ends and processive RTs facilitate direct cDNA sequencing of full-length host cell and viral transcripts

Alternative splicing (AS) is necessary for viral proliferation in host cells and a critical regulatory component of viral gene expression. Conventional RNA-seq approaches provide incomplete coverage of AS due to their short read lengths and are susceptible to biases and artifacts introduced in prevailing library preparation methodologies. Moreover, viral splicing studies are often conducted separately from host cell transcriptome analysis, precluding an assessment of the viral manipulation of host splicing machinery. To address current limitations, we developed a quantitative full-length direct cDNA sequencing strategy to simultaneously profile viral and host cell transcripts. This nanopore-based approach couples processive reverse transcriptases with a novel one-step chemical ablation of 3' RNA ends (termed CASPR), which decreases ribosomal RNA reads and enriches polyadenylated coding sequences. We extensively validate our approach using synthetic reference transcripts and show that CASPR doubles the breadth of coverage per transcript and increases detection of long transcripts (>4 kb), while being functionally equivalent to PolyA+ selection for transcript quantification. We used our approach to interrogate host cell and HIV-1 transcript dynamics during viral reactivation and identified novel putative HIV-1 host factors containing exon skipping or novel intron retentions and delineated the HIV-1 transcriptional state associated with these differentially regulated host factors.

Design, optimization, and application of multiplex rRT-PCR in the detection of respiratory viruses

Viral respiratory infections are common and serious diseases. Because there is no effective treatment method or vaccine for respiratory tract infection, early diagnosis is vital to identify the pathogen so as to determine the infectivity of the patient and to quickly take measures to curb the spread of the virus, if warranted, to avoid serious public health problems. Real-time reverse transcriptase PCR (rRT-PCR), which has high sensitivity and specificity, is the best approach for early diagnosis. Among rRT-PCR methods, multiplex rRT-PCR can resolve issues arising from various types of viruses, high mutation frequency, coinfection, and low concentrations of virus. However, the design, optimization, and validation of multiplex rRT-PCR are more complicated than singleplex rRT-PCR, and comprehensive research on multiplex rRT-PCR methodology is lacking. This review summarizes recent progress in multiplex rRT-PCR methodology, outlines the principles of design, optimization and validation, and describes a scheme to help diagnostic companies to design and optimize their multiplex rRT-PCR detection panel and to assist laboratory staff to solve problems in their daily work. In addition, the analytical validity, clinical validity and clinical utility of multiplex rRT-PCR in viral respiratory tract infection diagnosis are assessed to provide theoretical guidance and useful information for physicians to understand the test results.

Identification and validation of suitable housekeeping genes for gene expression studies in BCR-ABL1 positive B-lineage acute lymphoblastic leukemia

BACKGROUND

The stability of the housekeeping gene (HKG) expression is an absolute prerequisite for accurate normalization of target gene expression in a quantitative real-time polymerase chain reaction (RQ-PCR). In RQ-PCR, the widely used normalization approach involves the standardization of target genes to the most stable HKG control genes. According to the recent literature, in different experimental conditions the HKGs exhibit either up or down-regulation and thus affecting the gene expression profiles of target genes which leads to erroneous results. This implies that it is very important to select the appropriate HKG and verify the expression stability of the HKG before quantification of the target gene.

METHODS AND RESULTS

The present study aims to analyze six different HKGs for their expression profiles and stability in BCR-ABL1 negative cases and validate them in BCR-ABL1 positive cases, detected by multiplex reverse transcribed polymerase chain reaction (RT-PCR). Six commonly used reference genes (GAPDH, ABL1, RNA18S, ACTB, GUSB, and EEF2) were selected in this study. RQ-PCR was performed on 24 BCR-ABL1 negative cases and the outcomes were validated on 24 BCR-ABL1 positive cases. RefFinder™, a web-based composite software was used to check the stability of HKG genes by different algorithms and comprehensive ranking of each HKG gene in BCR-ABL1 negative cases and finally validated in BCR-ABL1 positive cases.

CONCLUSIONS

It was found that RNA18S, ABL1 and GUSB are good stable HKG genes, which showed minimum variability in gene expression compared to GAPDH, EEF2, and ACTB, the most commonly used HKG.

Obtaining Reliable RT-qPCR Results in Molecular Diagnostics—MIQE Goals and Pitfalls for Transcriptional Biomarker Discovery

In this review, we discuss the development pipeline for transcriptional biomarkers in molecular diagnostics and stress the importance of a reliable gene transcript quantification strategy. Hence, a further focus is put on the MIQE guidelines and how to adapt them for biomarker discovery, from signature validation up to routine diagnostic applications. First, the advantages and pitfalls of the holistic RNA sequencing for biomarker development will be described to establish a candidate biomarker signature. Sequentially, the RT-qPCR confirmation process will be discussed to validate the discovered biomarker signature. Examples for the successful application of RT-qPCR as a fast and reproducible quantification method in routinemolecular diagnostics are provided. Based on the MIQE guidelines, the importance of “key steps” in RT-qPCR is accurately described, e.g., reverse transcription, proper reference gene selection and, finally, the application of automated RT-qPCR data analysis software. In conclusion, RT-qPCR proves to be a valuable tool in the establishment of a disease-specific transcriptional biomarker signature and will have a great future in molecular diagnostics or personalized medicine.

PHi-RACE: PGIMER in-house rapid & cost effective classifier for the detection of BCR-ABL1-like acute lymphoblastic leukaemia in Indian patients

For the detection of BCR-ABL1-like ALL cases, two methodologies, specifically Gene expression profiling (GEP) or Next-generation targeted sequencing (NGS) and TaqMan based low-density (TLDA) card, are being used. NGS is very costly and TLDA is not widely commercially available. In this study, we quantified the expression of 8 selected overexpressed genes in 536 B-ALL cases. We identified 26.67% (143/536) BCR-ABL1-like ALLs using hierarchical clustering and principal component analysis. BCR-ABL1-like ALL cases were significantly older at presentation (p = 0.036) and had male preponderance (p = 0.047) compared to BCR-ABL1-negative ALL cases. MRD-positivity and induction failure were more commonest in BCR-ABL1-like ALL cases (30.55 vs.19.35% in BCR-ABL1-negative ALL cases). Lastly, we built a PHi-RACE classifier (sensitivity = 95.2%, specificity= 83.7%, AUC= 0.927) using logistic regression to detect BCR-ABL1-like ALL cases promptly at diagnosis. This classifier is beneficial for hematologists in quick decision making at baseline to start tailored treatment regimes.

Tutorial: Guidelines for Single-Cell RT-qPCR

Reverse transcription quantitative PCR (RT-qPCR) has delivered significant insights in understanding the gene expression landscape. Thanks to its precision, sensitivity, flexibility, and cost effectiveness, RT-qPCR has also found utility in advanced single-cell analysis. Single-cell RT-qPCR now represents a well-established method, suitable for an efficient screening prior to single-cell RNA sequencing (scRNA-Seq) experiments, or, oppositely, for validation of hypotheses formulated from high-throughput approaches. Here, we aim to provide a comprehensive summary of the scRT-qPCR method by discussing the limitations of single-cell collection methods, describing the importance of reverse transcription, providing recommendations for the preamplification and primer design, and summarizing essential data processing steps. With the detailed protocol attached in the appendix, this tutorial provides a set of guidelines that allow any researcher to perform scRT-qPCR measurements of the highest standard.

Non-coding Natural Antisense Transcripts: Analysis and Application

Non-coding natural antisense transcripts (ncNATs) are regulatory RNA sequences that are transcribed in the opposite direction to protein-coding or non-coding transcripts. These transcripts are implicated in a broad variety of biological and pathological processes, including tumorigenesis and oncogenic progression. With this complex field still in its infancy, annotations, expression profiling and functional characterisations of ncNATs are far less comprehensive than those for protein-coding genes, pointing out substantial gaps in the analysis and characterisation of these regulatory transcripts. In this review, we discuss ncNATs from an analysis perspective, in particular regarding the use of high-throughput sequencing strategies, such as RNA-sequencing, and summarize the unique challenges of investigating the antisense transcriptome. Finally, we elaborate on their potential as biomarkers and future targets for treatment, focusing on cancer.

Use and Misuse of Cq in qPCR Data Analysis and Reporting

In the analysis of quantitative PCR (qPCR) data, the quantification cycle (C_q) indicates the position of the amplification curve with respect to the cycle axis. Because C_q is directly related to the starting concentration of the target, and the difference in C_q values is related to the starting concentration ratio, the only results of qPCR analysis reported are often C_q, ΔC_q or ΔΔC_q values. However, reporting of C_q values ignores the fact that C_q values may differ between runs and machines, and, therefore, cannot be compared between laboratories. Moreover, C_q values are highly dependent on the PCR efficiency, which differs between assays and may differ between samples. Interpreting reported C_q values, assuming a 100% efficient PCR, may lead to assumed gene expression ratios that are 100-fold off. This review describes how differences in quantification threshold setting, PCR efficiency, starting material, PCR artefacts, pipetting errors and sampling variation are at the origin of differences and variability in C_q values and discusses the limits to the interpretation of observed C_q values. These issues can be avoided by calculating efficiency-corrected starting concentrations per reaction. The reporting of gene expression ratios and fold difference between treatments can then easily be based on these starting concentrations.

Quantitative analysis of RNA by HPLC and evaluation of RT-dPCR for coronavirus RNA quantification

Nucleic acid detection and quantification have been known to be important at various fields, from genetically modified organisms and gene expression to virus detection. For DNA molecules, digital PCR has been developed as an absolute quantification method which is not dependent on external calibrators. While when it comes to RNA molecules, reverse transcription (RT) step must be taken before PCR amplification to obtain cDNA. With different kinds of reverse transcriptase (RTase) and RT reaction conditions being used in laboratory assays, the efficiency of RT process differs a lot which led variety in quantification results of RNA molecules. In this study, we developed HPLC method combined with enzymatic digestion of RNA to nucleotides for quantification of RNA without RT process. This method was metrologically traceable to four nuceloside monophosphate (NMP) Certification Reference Materials of National Institute of Metrology, China (NIMC) for insurance of accuracy. The established method was used to evaluate the reverse transcription digital polymerase chain reaction (RT-dPCR) of three target genes of Middle East Respiratory Syndrome Coronavirus (MERS-CoV) RNA, including open reading frame 1ab (ORF1ab), nucleocapsid protein (N) and envelope protein (E) gene. Three available RT kits had been evaluated and disparities were observed for the RT efficiency varied from 9% to 182%. It is thus demonstrated that HPLC combined with enzymatic digestion could be a useful method to quantify RNA molecules and evaluate RT efficiency. It is suggested that RT process should be optimized and identified in RNA quantification assays.

Performance Comparison of Reverse Transcriptases for Single-Cell Studies

BACKGROUND

Recent advances allowing quantification of RNA from single cells are revolutionizing biology and medicine. Currently, almost all single-cell transcriptomic protocols rely on reverse transcription (RT). However, RT is recognized as a known source of variability, particularly with low amounts of RNA. Recently, several new reverse transcriptases (RTases) with the potential to decrease the loss of information have been developed, but knowledge of their performance is limited.

METHODS

We compared the performance of 11 RTases in quantitative reverse transcription PCR (RT-qPCR) on single-cell and 100-cell bulk templates, using 2 priming strategies: a conventional mixture of random hexamers with oligo(dT)s and a reduced concentration of oligo(dT)s mimicking common single-cell RNA-sequencing protocols. Depending on their performance, 2 RTases were further tested in a high-throughput single-cell experiment.

RESULTS

All tested RTases demonstrated high precision (R2 > 0.9445). The most pronounced differences were found in their ability to capture rare transcripts (0%-90% reaction positivity rate) and in their absolute reaction yield (7.3%-137.9%). RTase performance and reproducibility were compared with Z scores. The 2 best-performing enzymes were Maxima H- and SuperScript IV. The validity of the obtained results was confirmed in a follow-up single-cell model experiment. The better-performing enzyme (Maxima H-) increased the sensitivity of the single-cell experiment and improved resolution in the clustering analysis over the commonly used RTase (SuperScript II).

CONCLUSIONS

Our comprehensive comparison of 11 RTases in low RNA input conditions identified 2 best-performing enzymes. Our results provide a point of reference for the improvement of current single-cell quantification protocols.

Enzyme- and gene-specific biases in reverse transcription of RNA raise concerns for evaluating gene expression

Reverse transcription is the first step of most analyses of gene expression, yet the quantitative biases it introduces are largely overlooked. Following a series of purpose-designed systematic experiments we cherry-pick examples of various biases introduced by reverse transcription, and alert the “gene expression community” to the pitfalls and improved practice of this fundamental technique.

Reverse transcriptase enzyme and priming strategy affect quantification and diversity of environmental transcripts

Reverse-transcriptase-quantitative PCR (RT-Q-PCR) and RT-PCR amplicon sequencing, provide a convenient, target-specific, high-sensitivity approach for gene expression studies and are widely used in environmental microbiology. Yet, the effectiveness and reproducibility of the reverse transcription step has not been evaluated. Therefore, we tested a combination of four commercial reverse transcriptases with two priming techniques to faithfully transcribe 16S rRNA and amoA transcripts from marine sediments. Both enzyme and priming strategy greatly affected quantification of the exact same target with differences of up to 600-fold. Furthermore, the choice of RT system significantly changed the communities recovered. For 16S rRNA, both enzyme and priming had a significant effect with enzyme having a stronger impact than priming. Inversely, for amoA only the change in priming strategy resulted in significant differences between the same samples. Specifically, more OTUs and better coverage of amoA transcripts diversity were obtained with GS priming indicating this approach was better at recovering the diversity of amoA transcripts. Moreover, sequencing of RNA mock communities revealed that, even though transcript α diversities (i.e., OTU counts within a sample) can be biased by the RT, the comparison of β diversities (i.e., differences in OTU counts between samples) is reliable as those biases are reproducible between environments.

Visceral Adipose Tissue Inflammatory Factors (TNF-Alpha, SOCS3) in Gestational Diabetes (GDM): Epigenetics as a Clue in GDM Pathophysiology

Gestational diabetes (GDM) is among the most challenging diseases in westernized countries, affecting mother and child, immediately and in later life. Obesity is a major risk factor for GDM. However, the impact visceral obesity and related epigenetics play for GDM etiopathogenesis have hardly been considered so far. Our recent findings within the prospective ‘EaCH’ cohort study of women with GDM or normal glucose tolerance (NGT), showed the role, critical factors of insulin resistance (i.e., adiponectin, insulin receptor) may have for GDM pathophysiology with epigenetically modified expression in subcutaneous (SAT) and visceral (VAT) adipose tissues. Here we investigated the expression and promoter methylation of key inflammatory candidates, tumor necrosis factor-alpha (TNF-α) and suppressor of cytokine signaling 3 (SOCS3) in maternal adipose tissues collected during caesarian section (GDM, n = 19; NGT, n = 22). The mRNA expression of TNF-α and SOCS3 was significantly increased in VAT, but not in SAT, of GDM patients vs. NGT, accompanied by specific alterations of respective promoter methylation patterns. In conclusion, we propose a critical role of VAT and visceral obesity for the pathogenesis of GDM, with epigenetic alterations of the expression of inflammatory factors as a potential factor.

Visceral adipose tissue alteration of PI3KR1 expression is associated with gestational diabetes but not promoter DNA methylation

Obesity and diabetes are at an epidemic rate, as well as growing incidences of gestational diabetes mellitus (GDM) which causes pregnancy risks, and harm in both maternal and child health. It remains unclear which molecular mechanisms are driving the functional differences between visceral and subcutaneous fat and how these types directly affect an individual’s health outcome. Paired abdominal subcutaneous and omental visceral adipose tissue were collected from women with GDM (n = 20) and with normal glucose tolerance (NGT, n = 22) during planned caesarian section. Both groups had similar maternal age (average 32.5 years) and BMI at delivery (average 33.3 kg/m²). Adipose tissue mRNA expression analyses of insulin signalling genes: PI3KCA, PI3KR1, IRS1 and IRS2 showed significantly decreased PI3KR1 expression (−23%) in visceral fat in GDM with no association to promoter DNA methylation. Reduced visceral fat PI3KR1 expression appears to be a pathogenic factor in GDM but not through altered promoter methylation.

The effect of reverse transcription enzymes and conditions on high throughput amplicon sequencing of the 16S rRNA

It is assumed that the sequencing of ribosomes better reflects the active microbial community than the sequencing of the ribosomal RNA encoding genes. Yet, many studies exploring microbial communities in various environments, ranging from the human gut to deep oceans, questioned the validity of this paradigm due to the discrepancies between the DNA and RNA based communities. Here, we focus on an often neglected key step in the analysis, the reverse transcription (RT) reaction. Previous studies showed that RT may introduce biases when expressed genes and ribosmal rRNA are quantified, yet its effect on microbial diversity and community composition was never tested. High throughput sequencing of ribosomal RNA is a valuable tool to understand microbial communities as it better describes the active population than DNA analysis. However, the necessary step of RT may introduce biases that have so far been poorly described. In this manuscript, we compare three RT enzymes, commonly used in soil microbiology, in two temperature modes to determine a potential source of bias due to non-standardized RT conditions. In our comparisons, we have observed up to six fold differences in bacterial class abundance. A temperature induced bias can be partially explained by G-C content of the affected bacterial groups, thus pointing toward a need for higher reaction temperatures. However, another source of bias was due to enzyme processivity differences. This bias is potentially hard to overcome and thus mitigating it might require the use of one enzyme for the sake of cross-study comparison.

Improved measurement of absolute mRNA quantity without reverse transcription

Gene expression studies using microarrays have provided important insights into understanding the mechanisms of transcriptional regulation in a variety of biological and disease phenomena. In a previous study, we developed Photo-DEAN, a universal-microarray-based RNA quantification method that enabled reverse transcription-free multiplex measurement of the absolute amount of RNA. Photo-DEAN promotes high-throughput and bias-less transcriptome analysis without the need for common controls or additional complicated normalization steps. In this study, we empirically identified two conditions (individual specificity and uniform duplex stability) necessary for in silico design of probe sequences, allowing the Photo-DEAN method to accurately measure the absolute amount of target RNA in total RNA. We then demonstrated that using the modified probe design conditions, the Photo-DEAN method successfully measured the absolute amount of pgi mRNA spiked into E. coli total RNA. The measurement was performed at five different sites in the coding region of pgi mRNA, exhibiting no significant site dependence. Theoretical considerations suggested that probe sequences longer than the previously used 30-bases better satisfy the necessary design conditions.

Identification and Validation of Novel Reference Genes in Acute Lymphoblastic Leukemia for Droplet Digital PCR

Droplet digital PCR is the most robust method for absolute nucleic acid quantification. However, RNA is a very versatile molecule and its abundance is tissue-dependent. RNA quantification is dependent on a reference control to estimate the abundance. Additionally, in cancer, many cellular processes are deregulated which consequently affects the gene expression profiles. In this work, we performed microarray data mining of different childhood cancers and healthy controls. We selected four genes that showed no gene expression variations (PSMB6, PGGT1B, UBQLN2 and UQCR2) and four classical reference genes (ACTB, GAPDH, RPL4 and RPS18). Gene expression was validated in 40 acute lymphoblastic leukemia samples by means of droplet digital PCR. We observed that PSMB6, PGGT1B, UBQLN2 and UQCR2 were expressed ~100 times less than ACTB, GAPDH, RPL4 and RPS18. However, we observed excellent correlations among the new reference genes (p < 0.0001). We propose that PSMB6, PGGT1B, UBQLN2 and UQCR2 are housekeeping genes with low expression in childhood cancer.

Rapid Amplification of Sequences from the 5' Ends of mRNAs: 5'-RACE

Isolating a full-length clone of cDNA provides certainty that the entire protein-coding sequence of the mRNA has been identified and allows the 5' end of the mRNA to be precisely mapped onto the genomic DNA sequence. Unfortunately, partial clones that lack sequences corresponding to the 5' end of the target mRNA occur commonly in cDNA libraries. Rapid amplification of cDNA ends (RACE) provides a means to overcome this obstacle by amplifying the 5'-terminal sequences of cDNA. This technique differs from conventional polymerase chain reaction in that it only requires knowledge of a small region of sequence within either the target RNA or in a partial clone of cDNA. In the first step of 5'-RACE, extension of the primer by reverse transcriptase yields single-stranded cDNAs complementary to the 5' regions of the mRNA. In the second step, a homopolymeric tail or a primer-adaptor is added to the 3' ends of the cDNAs. This generates a primer-binding site upstream of the unknown 5'-sequence of the target mRNA. Finally, synthesis of the second cDNA strand and amplification of the resulting double-stranded cDNAs is performed using the gene-specific primer and the upstream primer. The double-stranded products of the final stage are purified and cloned into a vector for sequencing analysis and subsequent manipulation.

Rapid Amplification of Sequences from the 3' Ends of mRNAs: 3'-RACE

cDNAs whose first-strand synthesis has been primed by oligo(dT) generally contain the 3' sequences of the RNA. However, cDNAs generated by internal gene-specific primers will usually lack one or both terminal regions of the parental mRNA. And alternate splicing or the presence of an internal A-rich tract can generate cDNA clones that lack 3' sequences. These sequences can be recovered using 3'-RACE (rapid amplification of cDNA ends), which can also be used to map the 3' termini of families of mRNAs with alternative polyadenylation sites. Briefly, a population of mRNAs is transcribed into cDNA using an adaptor-primer with a poly(T) at its 3' end and 30-40 nt containing the recognition sites for two or three restriction enzymes at its 5' end. Reverse transcription is usually followed by two successive rounds of polymerase chain reaction (PCR). The first is primed by a gene-specific sense oligonucleotide and the antisense (dT) adaptor-primer. The products of the first PCR can be used as templates for a second, nested PCR, which is primed by a gene-specific sense oligonucleotide internal to the first, and a second antisense oligonucleotide whose sequence is identical to the central region of the (dT) adaptor-primer. The products amplified in the second PCR are isolated, cleaved with a suitable restriction enzyme, cloned, and characterized.

Amplification of cDNA Generated by Reverse Transcription of mRNA: Two-Step Reverse Transcription-Polymerase Chain Reaction (RT-PCR)

Reverse transcription-polymerase chain reaction (RT-PCR) is a powerful method to detect and synthesize cDNA copies of low-copy-number mRNAs. Two enzymes are used: reverse transcriptase to produce single-stranded cDNA copies, which are then used as templates in an amplification reaction catalyzed by a thermostable DNA polymerase. For this reason, the method is known as "two-step RT-PCR." This protocol describes the traditional method of RT-PCR in which the two synthetic reactions are performed separately and sequentially.

Shedding light: The importance of reverse transcription efficiency standards in data interpretation

The RNA-to-cDNA conversion step in transcriptomics experiments is widely recognised as inefficient and variable, casting doubt on the ability to do quantitative transcriptomics analyses. Multiple studies have focused on ways to optimise this process, resulting in contradictory recommendations. Here we explore the problem of reverse transcription efficiency using digital PCR and the RT method’s impact on subsequent data analysis. Using synthetic RNA standards, an example experiment is presented, outlining a method to (1) determine relevant efficiency and variability values and then to (2) incorporate this information into downstream analyses as a way to improve the accuracy of quantitative transcriptomics experiments.

What do we measure when we measure cell-associated HIV RNA

Cell-associated (CA) HIV RNA has received much attention in recent years as a surrogate measure of the efficiency of HIV latency reversion and because it may provide an estimate of the viral reservoir size. This review provides an update on some recent insights in the biology and clinical utility of this biomarker. We discuss a number of important considerations to be taken into account when interpreting CA HIV RNA measurements, as well as different methods to measure this biomarker.

Absolute Regulatory Small Noncoding RNA Concentration and Decay Rates Measurements in Escherichia coli

Regulation of RNA turnover is of utmost importance for controlling the concentration of transcripts and consequently cellular protein levels. Among the processes controlling RNA decay, small noncoding regulatory RNAs (sRNAs) have recently emerged as major new players. In this chapter, we describe and discuss protocols that can be used to measure sRNA concentration in vivo and to assess sRNA decay rates in Gram-negative bacteria. Precisely, we focus our analyses on the Escherichia coli Gram-negative bacterium as a model. The information described in this chapter provides a guideline to help develop a protocol in order to assess these important parameters and to identify RNA-processing enzymes involved in sRNA degradation processes.

Laser microdissection: A powerful tool for genomics at cell level

Laser microdissection (LM) has become widely democratized over the last fifteen years. Instruments have evolved to offer more powerful and efficient lasers as well as new options for sample collection and preparation. Technological evolutions have also focused on the post-microdissection analysis capabilities, opening up investigations in all disciplines of experimental and clinical biology, thanks to the advent of new high-throughput methods of genome analysis, including RNAseq and proteomics, now globally known as microgenomics, i.e. analysis of biomolecules at the cell level. In spite of the advances these rapidly developing methods have allowed, the workflow for sampling and collection by LM remains a critical step in insuring sample integrity in terms of histology (accurate cell identification) and biochemistry (reliable analyzes of biomolecules). In this review, we describe the sample processing as well as the strengths and limiting factors of LM applied to the specific selection of one or more cells of interest from a heterogeneous tissue. We will see how the latest developments in protocols and methods have made LM a powerful and sometimes essential tool for genomic and proteomic analyzes of tiny amounts of biomolecules extracted from few cells isolated from a complex tissue, in their physiological context, thus offering new opportunities for understanding fundamental physiological and/or patho-physiological processes.

Two-tailed RT-qPCR: a novel method for highly accurate miRNA quantification

MicroRNAs are a class of small non-coding RNAs that serve as important regulators of gene expression at the posttranscriptional level. They are stable in body fluids and pose great potential to serve as biomarkers. Here, we present a highly specific, sensitive and cost-effective system to quantify miRNA expression based on two-step RT-qPCR with SYBR-green detection chemistry called Two-tailed RT-qPCR. It takes advantage of novel, target-specific primers for reverse transcription composed of two hemiprobes complementary to two different parts of the targeted miRNA, connected by a hairpin structure. The introduction of a second probe ensures high sensitivity and enables discrimination of highly homologous miRNAs irrespectively of the position of the mismatched nucleotide. Two-tailed RT-qPCR has a dynamic range of seven logs and a sensitivity sufficient to detect down to ten target miRNA molecules. It is capable to capture the full isomiR repertoire, leading to accurate representation of the complete miRNA content in a sample. The reverse transcription step can be multiplexed and the miRNA profiles measured with Two-tailed RT-qPCR show excellent correlation with the industry standard TaqMan miRNA assays (r² = 0.985). Moreover, Two-tailed RT-qPCR allows for rapid testing with a total analysis time of less than 2.5 hours.

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.

Reverse Transcription Past Products of Guanine Oxidation in RNA Leads to Insertion of A and C opposite 8-Oxo-7,8-dihydroguanine and A and G opposite 5-Guanidinohydantoin and Spiroiminodihydantoin Diastereomers

Reactive oxygen species, both endogenous and exogenous, can damage nucleobases of RNA and DNA. Among the nucleobases, guanine has the lowest redox potential, making it a major target of oxidation. Although RNA is more prone to oxidation than DNA is, oxidation of guanine in RNA has been studied to a significantly lesser extent. One of the reasons for this is that many tools that were previously developed to study oxidation of DNA cannot be used on RNA. In the study presented here, the lack of a method for seeking sites of modification in RNA where oxidation occurs is addressed. For this purpose, reverse transcription of RNA containing major products of guanine oxidation was used. Extension of a DNA primer annealed to an RNA template containing 8-oxo-7,8-dihydroguanine (OG), 5-guanidinohydantoin (Gh), or the R and S diastereomers of spiroiminodihydantoin (Sp) was studied under standing start conditions. SuperScript III reverse transcriptase is capable of bypassing these lesions in RNA inserting predominantly A opposite OG, predominantly G opposite Gh, and almost an equal mixture of A and G opposite the Sp diastereomers. These data should allow RNA sequencing of guanine oxidation products by following characteristic mutation signatures formed by the reverse transcriptase during primer elongation past G oxidation sites in the template RNA strand.

Technical aspects and recommendations for single-cell qPCR

Single cells are basic physiological and biological units that can function individually as well as in groups in tissues and organs. It is central to identify, characterize and profile single cells at molecular level to be able to distinguish different kinds, to understand their functions and determine how they interact with each other. During the last decade several technologies for single-cell profiling have been developed and used in various applications, revealing many novel findings. Quantitative PCR (qPCR) is one of the most developed methods for single-cell profiling that can be used to interrogate several analytes, including DNA, RNA and protein. Single-cell qPCR has the potential to become routine methodology but the technique is still challenging, as it involves several experimental steps and few molecules are handled. Here, we discuss technical aspects and provide recommendation for single-cell qPCR analysis. The workflow includes experimental design, sample preparation, single-cell collection, direct lysis, reverse transcription, preamplification, qPCR and data analysis. Detailed reporting and sharing of experimental details and data will promote further development and make validation studies possible. Efforts aiming to standardize single-cell qPCR open up means to move single-cell analysis from specialized research settings to standard research laboratories.

[PCR analysis of the absolute number of copies of human chromosome 18 transcripts in liver and HepG2 cells]

Using reverse transcription in conjunction with the quantitative real-time PCR or digital droplet PCR, the transcriptome profiling of human chromosome 18 has been carried out in liver hepatocytes and hepatoblastoma cells (HepG2 cell line) in terms of the absolute number of each transcript per cell. The transcript abundance varies within the range of 0.006 to 9635 and 0.011 to 4819 copies per cell for HepG2 cell line and hepatocytes, respectively. The expression profiles for genes of chromosome 18 in hepatocytes and HepG2 cells were found to significantly correlate: the Spearman's correlation coefficient was equal to 0.81. The distribution of frequency of transcripts over their abundance was bimodal for HepG2 cells and unimodal for liver hepatocytes. Bioinformatic analysis of the differential gene expression has revealed that genes of chromosome 18, overexpressed in HepG2 cells compared to hepatocytes, are associated with cell division and cell adhesion processes. It is assumed that the enhanced expression of those genes in HepG2 cells is related to the proliferation activity of cultured cells. The differences in transcriptome profiles have to be taken into account when modelling liver hepatocytes with cultured HepG2 cells.

Stable reference genes in granulosa cells of bovine dominant follicles during follicular growth, FSH stimulation and maternal aging

The aim of the present study was to determine a set of reference genes in granulosa cells of dominant follicles that are suitable for relative gene expression analyses during maternal and follicular aging. Granulosa cells of growing and preovulatory dominant follicles were collected from aged and young cows (maternal aging study) and from FSH-stimulated follicles developing under different durations of FSH treatment (follicular aging study). The mRNA levels of the two commonly used reference genes (GAPDH, ACTB) and four novel genes (UBE2D2, EIF2B2, SF3A1, RNF20) were analysed using cycle threshold values. Results revealed that mRNA levels of GAPDH, ACTB, EIF2B2, RNF20, SF3A1 and UBE2D2 were similar (P>0.05) between dominant follicle type, age and among follicles obtained after FSH-stimulation, but differed (P=0.005) due to mRNA processing (i.e. with versus without amplification). The stability of reference genes was analysed using GeNorm, DeltaCT and NormFinder programs and comprehensive ranking order was determined using RefFinder. The mRNA levels of GAPDH and ACTB were less stable than those of UBE2D2 and EIF2B2. The geometric mean of multiple genes (UBE2D2, EIF2B2, GAPDH and SF3A1) is a more appropriate reference control than the use of a single reference gene to compare relative gene expression among dominant and FSH-stimulated follicles during maternal and/or follicular aging studies.

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.

Single-Cell-Based Analysis Highlights a Surge in Cell-to-Cell Molecular Variability Preceding Irreversible Commitment in a Differentiation Process

In some recent studies, a view emerged that stochastic dynamics governing the switching of cells from one differentiation state to another could be characterized by a peak in gene expression variability at the point of fate commitment. We have tested this hypothesis at the single-cell level by analyzing primary chicken erythroid progenitors through their differentiation process and measuring the expression of selected genes at six sequential time-points after induction of differentiation. In contrast to population-based expression data, single-cell gene expression data revealed a high cell-to-cell variability, which was masked by averaging. We were able to show that the correlation network was a very dynamical entity and that a subgroup of genes tend to follow the predictions from the dynamical network biomarker (DNB) theory. In addition, we also identified a small group of functionally related genes encoding proteins involved in sterol synthesis that could act as the initial drivers of the differentiation. In order to assess quantitatively the cell-to-cell variability in gene expression and its evolution in time, we used Shannon entropy as a measure of the heterogeneity. Entropy values showed a significant increase in the first 8 h of the differentiation process, reaching a peak between 8 and 24 h, before decreasing to significantly lower values. Moreover, we observed that the previous point of maximum entropy precedes two paramount key points: an irreversible commitment to differentiation between 24 and 48 h followed by a significant increase in cell size variability at 48 h. In conclusion, when analyzed at the single cell level, the differentiation process looks very different from its classical population average view. New observables (like entropy) can be computed, the behavior of which is fully compatible with the idea that differentiation is not a “simple” program that all cells execute identically but results from the dynamical behavior of the underlying molecular network.

A single-cell transcriptomics analysis offers a new dynamical view of the differentiation process, involving an increase in between-cell variability prior to commitment.

The differentiation process has classically been seen as a stereotyped program leading from one progenitor toward a functional cell. This vision was based upon cell population-based analyses averaged over millions of cells. However, new methods have recently emerged that allow interrogation of the molecular content at the single-cell level, challenging this view with a new model suggesting that cell-to-cell gene expression stochasticity could play a key role in differentiation. We took advantage of a physiologically relevant avian cellular model to analyze the expression level of 92 genes in individual cells collected at several time-points during differentiation. We first observed that the process analyzed at the single-cell level is very different and much less well ordered than the population-based average view. Furthermore, we showed that cell-to-cell variability in gene expression peaks transiently before strongly decreasing. This rise in variability precedes two key events: an irreversible commitment to differentiation, followed by a significant increase in cell size variability. Altogether, our results support the idea that differentiation is not a “simple” series of well-ordered molecular events executed identically by all cells in a population but likely results from dynamical behavior of the underlying molecular network.