rna simple total rna kit (tiangen biotech co)
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rna simple total rna kit
Rna Simple Total Rna Kit, supplied by tiangen biotech co, used in various techniques. Bioz Stars score: 98/100, based on 1212 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/rna+kit/RNAsimple+Total+RNA+Kit/pmc13635554-6-0-6
Average 98 stars, based on 1212 article reviews
Rna Simple Total Rna Kit, supplied by tiangen biotech co, used in various techniques. Bioz Stars score: 98/100, based on 1212 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/rna+kit/RNAsimple+Total+RNA+Kit/pmc13635554-6-0-6
Average 98 stars, based on 1212 article reviews
rna simple total rna kit - by Bioz Stars,
2026-10
98/100 stars
Images
1) Product Images from "OM-sqPCR enables one-step multiplex quantification of circulating small-RNA subclasses for colorectal cancer classification"
Article Title: OM-sqPCR enables one-step multiplex quantification of circulating small-RNA subclasses for colorectal cancer classification
Journal: iScience
doi: 10.1016/j.isci.2026.117540
Figure Legend Snippet: Overview of the OM-sqPCR platform The OM-sqPCR platform is an integrated system for multiplex small RNA quantification, enabling simultaneous reverse transcription and real-time quantitative PCR of multiple small RNA markers within a single closed reaction tube. Algorithm-guided optimization of primer-probe combinations markedly improves quantification efficiency, assay reproducibility, and multiplex compatibility. (A) The OM-sqPCR system employs optimized enzyme cocktails—including reverse transcriptase, hot-start DNA polymerase, and uracil-DNA glycosylase (UDG)—together with precisely tuned buffer compositions and temperature control tailored for short RNA templates. (B) Algorithms calculate primer-probe parameters, including sequence length, GC content, secondary structure stability, dimerization potential, and annealing temperature, to ensure target-specific amplification while minimizing cross-interference among multiple sRNAs. (C) The OM-sqPCR workflow comprises two coordinated steps: (i) algorithm-guided design and validation of primer-probe sets, (ii) one-tube integration of reverse transcription and qPCR reactions. The primer-probe sets include four sequences: ① stemloop primer; ② forward primer; ③ probe; ④ reverse primer. Sequence ① enables reverse transcription, while sequences ②–④ facilitate real-time fluorescence quantitative PCR. Compared with conventional two-step RT-qPCR, OM-sqPCR rapidly identifies optimal primer-probe configurations, eliminates iterative optimization, and performs all amplification steps in a single tube—thereby reducing assay time and cost (< US$1 per test) while streamlining workflows and improving data stability. This figure was created using BioRender under agreement no. WQ2A4QH3S7.
Techniques Used: Multiplex Assay, Reverse Transcription, Real-time Polymerase Chain Reaction, Control, Sequencing, Stability, Amplification, Biomarker Discovery, Fluorescence, Quantitative RT-PCR
Figure Legend Snippet: Analytical performance of the OM-sqPCR platform (A) Development of the algorithm-guided assay-design framework. A parameter library for sRNA RT-qPCR was established, encompassing stem-loop motifs, primer-probe length ranges, melting-temperature windows, Gibbs free-energy (ΔG) thresholds, forward-primer 5′-extension lengths, and reverse-primer gap distances. Experimental feedback was used to refine the parameter network and identify high-performing primer–probe combinations. A scoring algorithm then ranked multiplex configurations by predicted amplification efficiency, specificity, and spectral compatibility. (B) Real-time amplification curves for four representative sRNAs measured by OM-sqPCR across concentrations from 100 aM to 100 pM. (C) Reproducibility analysis of serum samples with high, medium, and low RNA abundance. (D) Sanger sequencing confirmed the identities of the four amplicons. (E) Interoperator and interinstrument reproducibility of rsRNA-28S-12 measurements across 27 replicate measurements (nine measurements for each operator-instrument configuration). (F) Comparison of OM-sqPCR and conventional two-step RT-qPCR measurements in the same 40 samples. No significant between-method differences were detected for hsa-miR-223-3p ( p = 0.9992), tsRNA-Asp-GTC-1 ( p > 0.9999), rsRNA-28S-12 ( p = 0.9525), or hsa-let-7f-5p ( p > 0.9999). (G) OM-sqPCR measurements in patients with CRC ( n = 15) and non-CRC controls ( n = 25). Concentrations were higher in CRC for hsa-miR-223-3p ( p < 0.0001), tsRNA-Asp-GTC-1 ( p = 0.0002), rsRNA-28S-12 ( p = 0.0007), and hsa-let-7f-5p ( p = 0.0004). The coefficient of variation was calculated as CV (%) = 100 × SD/mean (E). Data in (F) and (G) are presented as the mean ± SEM. Comparisons used two-tailed paired student’s t tests in (F) and two-tailed unpaired student’s t tests in (G). Asterisks denote the following significance thresholds: p ≥ 0.05, ns, ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, ∗∗∗∗ p < 0.0001.
Techniques Used: Quantitative RT-PCR, Multiplex Assay, Amplification, Analysis, Blood/Plasma/Serum Samples, DNA Sequencing, Comparison, Two Tailed Test
Figure Legend Snippet:
Techniques Used: Sequencing, Gene Expression, Software
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