smarter stranded total rna seq kit v2 pico input mammalian  (TaKaRa)

Journal: iScience

Article Title: HDAC inhibitor treatment restores transcriptome, chromatin accessibility, and memory deficits in a mouse model for Down syndrome

doi: 10.1016/j.isci.2026.117670

Figure Lengend Snippet: SAHA rescues chromatin and transcriptomic changes (A) Outline of the experimental strategy. (B) PCA plot of ATAC-seq data obtained from four WT, five TS mice, and three TS-SAHA (TST). (C) PCA plot of RNA-seq data obtained from four WT and four TS mice and three TS-SAHA (TST). (D) Number of differentially accessible regions (DARs) for each comparison (left), and number of DARs in non-triplicated and triplicated genomic regions (right). (E) Number of differentially expressed genes (DEGs) for each comparison (left) and number of DEGs in non-triplicated and triplicated genomic regions (right). (F) Analysis of differentially accessible regions (DARs) in TS neurons and their rescue upon SAHA treatment, shown as line-plots (left) and Venn diagram (left). Kruskal-Wallis test followed by pairwise Wilcoxon tests with multiple-comparison correction, ∗∗∗ p < 0.001. (G) Analysis of differentially expressed genes (DEGs) in TS neurons and their rescue upon SAHA treatment, shown as line-plots (left) and Venn diagram (right). Kruskal-Wallis test followed by pairwise Wilcoxon tests with multiple-comparison correction, ∗∗∗ p < 0.001. (H) Heatmap of transcription factor motif enrichment among gained peaks in TS and TS-SAHA neurons, with significance and fold enrichment. (I) Gene set enrichment analysis of differentially expressed genes in TS (red) and TS-SAHA neurons (orange). See also .

Article Snippet: SMARTer Stranded Total RNA-Seq Kit v2 - Pico Input Mammalian , Takara , Cat#634411.

Techniques: RNA Sequencing, Comparison, Analysis

Journal: iScience

Article Title: HDAC inhibitor treatment restores transcriptome, chromatin accessibility, and memory deficits in a mouse model for Down syndrome

doi: 10.1016/j.isci.2026.117670

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Article Snippet: SMARTer Stranded Total RNA-Seq Kit v2 - Pico Input Mammalian , Takara , Cat#634411.

Techniques: Cell-Signaling, Recombinant, Bicinchoninic Acid Protein Assay, Isolation, DNA Library Preparation, Software, Analysis

Journal: iScience

Article Title: OM-sqPCR enables one-step multiplex quantification of circulating small-RNA subclasses for colorectal cancer classification

doi: 10.1016/j.isci.2026.117540

Figure Lengend 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.

Article Snippet: RNA Simple Total RNA Kit , Tiangen Biotech , DP419.

Techniques: Multiplex Assay, Reverse Transcription, Real-time Polymerase Chain Reaction, Control, Sequencing, Stability, Amplification, Biomarker Discovery, Fluorescence, Quantitative RT-PCR

Journal: iScience

Article Title: OM-sqPCR enables one-step multiplex quantification of circulating small-RNA subclasses for colorectal cancer classification

doi: 10.1016/j.isci.2026.117540

Figure Lengend 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.

Article Snippet: RNA Simple Total RNA Kit , Tiangen Biotech , DP419.

Techniques: Quantitative RT-PCR, Multiplex Assay, Amplification, Analysis, Blood/Plasma/Serum Samples, DNA Sequencing, Comparison, Two Tailed Test

Journal: iScience

Article Title: OM-sqPCR enables one-step multiplex quantification of circulating small-RNA subclasses for colorectal cancer classification

doi: 10.1016/j.isci.2026.117540

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Article Snippet: RNA Simple Total RNA Kit , Tiangen Biotech , DP419.

Techniques: Sequencing, Gene Expression, Software