The real-time reverse transcription-polymerase chain reaction (real-time RT-qPCR) has become a leading technique for the detection and quantification of arboviruses, including chikungunya, dengue, and zika viruses. In this study, an updated real-time RT-qPCR assay was designed and evaluated together with a synthetic positive-control chimeric RNA for the simultaneous detection and quantification of chikungunya, dengue, and Zika viruses.
Amplification assays were performed to verify the construct integrity and optimal reaction/thermal cycling conditions. The analytical sensitivity of the assay was determined for each virus in single and multiplex reactions, as well as the performance in the detection and viral load quantification of experimental samples. The real-time RT-qPCR assay presented here allowed for the simultaneous detection and quantification of chikungunya, dengue, and zika viruses and could be applied in several studies where the accurate quantification of viral genomes is required.

Human Chr18 transcriptome dataset combined from the Illumina HiSeq, ONT MinION, and qPCR data

The chromosome-centric dataset was created by applying several technologies of transcriptome profiling. The described dataset is available at NCBI repository (BioProject ID PRJNA635536). The dataset referred to the same type of tissue, cell lines, transcriptome sequencing technologies, and was accomplished in a period of 8 years (the first data were obtained in 2013 while the last ones – in 2020).
The high-throughput sequencing technologies were employed along with the quantitative PCR (qPCR) approach, for data generation using the gene expression level assessment. qPCR was performed for a limited group of genes, encoded on human chromosome 18, for the Russian part of the Chromosome-Centric Human Proteome Project. The data of high-throughput sequencing are provided as Excel spreadsheets, where the data on FPKM and TMP values were evaluated for the whole transcriptome with both Illumina HiSeq and Oxford Nanopore Technologies MinION sequencing.

DNA-methylation-based telomere length estimator: comparisons with measurements from flow FISH and qPCR

Telomere length (TL) is a marker of biological aging associated with several health outcomes. High throughput reproducible TL measurements are needed for large epidemiological studies. We compared the novel DNA methylation-based estimator (DNAmTL) with the high-throughput quantitative PCR (qPCR) and the highly accurate flow cytometry with fluorescent in situ hybridization (flow FISH) methods using blood samples from healthy adults.
 An updated RT-qPCR assay for the simultaneous detection and quantification of chikungunya, dengue and zika viruses
We used Pearson’s correlation coefficient, Bland Altman plots and linear regression models for statistical analysis. Shorter DNAmTL was associated with older age, male sex, white race, and cytomegalovirus seropositivity (p<0.01 for all). DNAmTL was moderately correlated with qPCR TL (N=635, r=0.41, p < 0.0001) and flow FISH total lymphocyte TL (N=144, r=0.56, p < 0.0001). The agreements between flow FISH TL and DNAmTL or qPCR were acceptable but with wide limits of agreement.
DNAmTL correctly classified >70% of TL categorized above or below the median, but the accuracy dropped with increasing TL categories. The ability of DNAmTL to detect associations with age and other TL-related factors in the absence of strong correlation with measured TL may indicate its capture of aspects of telomere maintenance mechanisms and not necessarily TL. The inaccuracy of DNAmTL prediction should be considered during data interpretation and across-study comparisons.

Relative Quantification of Residue-Specific m 6 A RNA Methylation Using m 6 A-RT-QPCR

Technological advances in high-throughput sequencing in combination with antibody enrichment and/or induced nucleotide-specific chemical modifications have accelerated the mapping of epitranscriptomic modifications. However, site-specific detection and quantification of m6A are still technically challenging. Here, we describe a simple RT-QPCR-based approach for the relative quantification of candidate m6A regions that takes advantage of the diminished capacity of BstI enzyme to retrotranscribe m6A residues.

Detection of GPCR mRNA Expression in Primary Cells Via qPCR, Microarrays, and RNA-Sequencing

A workflow is described for assaying the expression of G protein-coupled receptors (GPCRs) in cultured cells, using a combination of methods that assess GPCR mRNAs. Beginning from the isolation of cDNA and preparation of mRNA, we provide protocols for designing and testing qPCR primers, assaying mRNA expression using qPCR and high-throughput analysis of GPCR mRNA expression via TaqMan qPCR-based, GPCR-selective arrays.
We also provide a workflow for analysis of expression from RNA-sequencing (RNA-seq) assays, which can be queried to yield expression of GPCRs and related genes in samples of interest, as well as to test changes in expression between groups, such as in cells treated with drugs or from healthy and diseased subjects.
We place priority on optimized protocols that distinguish signal from noise, as GPCR mRNAs are typically present in low abundance, necessitating techniques that maximize sensitivity while minimizing noise. These methods may also be applicable for assessing the expression of members of families of other low abundance genes via high-throughput analyses of mRNAs, followed by independent confirmation and validation of results via qPCR.

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