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10 protocols using rneasy plus kit

1

RNA-seq Analysis of Gene Expression

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Total RNA was extracted from cell pellets using the RNeasy Plus kit (QIAGEN). RNA was checked for quality using TapeStation and Qubit before library preparation using Kappa stranded mRNA Hyper Prep and sequencing using Illumina NS500. Reads were mapped to Hg19 using STAR alignment (Dobin et al., 2013 (link)) and counts were generated using HTseq (Anders et al., 2015 (link)). Differential gene expression analysis was perform using DESeq2 (Love et al., 2014 (link)) and heatmaps were generated using R package pheatmap. Mean counts were generated using DESeq2 mean-ratio normalization method. Gene set enrichment analysis was conducted using GSEA software (https://www.broad.mit.edu/gsea/downloads.jsp) (Mootha et al., 2003 (link); Subramanian et al., 2005 (link)). RNA-seq datasets have been deposited in the GEO database (accession number GSE154545). Gene annotations in Figure 5D for G1/S and G2/M genes are from Schade et al. (2019) (link). RT-qPCR to validate RNA expression data was done using cDNA generated from total RNA isolated by the RNeasy Plus kit and the High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems). qPCR was performed on the cDNA using the primers listed in Table S3 and Brilliant III Ultra-Fast qPCR Master Mix (Agilent) using a MxAria (Agilent)
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2

RNA-seq Analysis of Gene Expression

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Total RNA was extracted from cell pellets using the RNeasy Plus kit (QIAGEN). RNA was checked for quality using TapeStation and Qubit before library preparation using Kappa stranded mRNA Hyper Prep and sequencing using Illumina NS500. Reads were mapped to Hg19 using STAR alignment (Dobin et al., 2013 (link)) and counts were generated using HTseq (Anders et al., 2015 (link)). Differential gene expression analysis was perform using DESeq2 (Love et al., 2014 (link)) and heatmaps were generated using R package pheatmap. Mean counts were generated using DESeq2 mean-ratio normalization method. Gene set enrichment analysis was conducted using GSEA software (https://www.broad.mit.edu/gsea/downloads.jsp) (Mootha et al., 2003 (link); Subramanian et al., 2005 (link)). RNA-seq datasets have been deposited in the GEO database (accession number GSE154545). Gene annotations in Figure 5D for G1/S and G2/M genes are from Schade et al. (2019) (link). RT-qPCR to validate RNA expression data was done using cDNA generated from total RNA isolated by the RNeasy Plus kit and the High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems). qPCR was performed on the cDNA using the primers listed in Table S3 and Brilliant III Ultra-Fast qPCR Master Mix (Agilent) using a MxAria (Agilent)
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3

Quantitative Analysis of Osteogenic Gene Expression

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RNA was isolated with an RNeasy Plus Kit and reverse transcribed into cDNA using the SuperScript III First-Strand Synthesis System (Invitrogen). Gene expression was measured using qRT-PCR. Reactions included 25 ng cDNA per 10μl with QuantiTect SYBR Green PCR Kit (Qiagen, Valencia, CA) and the CFX384 Real-Time System (BioRad, Hercules, CA). Transcript levels were normalized to the housekeeping gene Gapdh. Gene expression levels were quantified using the 2ΔΔCt method. Gene specific primer sequences: Gapdh (Forward: 5′-GGGAAG CCCATCACCATCTT, Reverse: 5′-GCCTCACC CCATTTG ATGTT), Osteocalcin (Bglap) (Forward: 5′-CCTGAGTCTGACAAAGCCTTCA, Reverse: 5′-GCCGGAGTCTGTTCACTACCTT), and Alkaline phosphatase (Alpl) (Forward: 5′-CACAGATTCCCAAAGCACCT, Reverse: 5′-GGGATGGAGGAGAGAAGGTC).
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4

Gene Expression Analysis via qPCR

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mRNA was isolated (Qiagen RNeasy Plus Kit) and transcribed to cDNA (Invitrogen SuperScript III). Gene expression was analyzed using Taqman probes and the OneStep Plus system (Applied Biosystems). Each biological sample was analyzed in experimental replicate (n=2 repeated wells of the qPCR reaction) and the Ct value of each replicate was averaged and handed as n=1 unique biologic sample. Expression for each sample was normalized to β-Actin (ACTA1) gene expression (ΔCt) and relative to peripheral lung tissue control samples (ΔΔCt), and fold change calculated by 2-ΔΔCt (24 (link)). A total of n=3 unique biological samples were analyzed for each experiment.
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5

Quantitative PCR for RNAi Knockdown Efficiency

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Quantitative PCR was used to assay efficiency of RNAi knockdowns according to standard techniques. Briefly, total RNA was isolated from cells using a Qiagen RNeasy Plus kit and then converted to cDNA using the Invitrogen SuperScript III First-Strand Synthesis System for RT-PCR. Primers for qPCR were designed using the Primer-BLAST website (http://www.ncbi.nlm.nih.gov/tools/primer-blast/). Reactions were set up using KAPA SYBR FAST qPCR kits and run on an Applied Biosystems 7300 Real-Time PCR System.
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6

Quantitative Gene Expression Analysis

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We conducted RT-PCR to verify gene-level changes in the CON, DSS, and H-BBr groups. Extracted total RNA from colon tissues using RNeasy Plus Kit (Invitrogen, New York, United States). Following the manufacturer’s instructions, reverse transcription performing by using the BioRT Master HisSensi cDNA First-Strand Synthesis kit (Shanghai Roche, China). PCR2720 thermal cycler (Applied Biosystems, United States) and ABI7500 PCR system perform RT-qPCR. The fluorescence reagent used in this experiment was SYBR Green I, and the cycling conditions refer to Supplementary Figure 2. The primers used for PCR amplification which listed in Supplementary Table 2.
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7

Quantitative Real-Time PCR Protocol

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Total RNA was isolated using the RNeasy plus kit (Invitrogen) according to the manufacturer’s instruction. cDNA was synthesized from total RNA using the ProtoScript First Strand cDNA Synthesis Kit (NEBioLabs). Quantitative real-time PCR was performed using SYBR Green (BioRad). The fold induction of each target gene was calculated using the comparative CT method (2-ΔΔCt). The Ct of each gene of interest was first normalized to the housekeeping gene GAPDH (ΔCt), and then to the control of the experiment (vehicle or DMSO treatment) to calculate the ΔΔCt., The oligonucleotide sequences used were the following:
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8

Quantifying Gene Expression in Lung Tissue

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mRNA was isolated (Qiagen RNeasy Plus Kit) and transcribed to cDNA (Invitrogen SuperScript III). Gene expression was analyzed using Taqman probes and the OneStep Plus system (Applied Biosystems). Each biological sample was analyzed in experimental replicate (n=2 repeated wells of the qPCR reaction) with the Ct value of each replicate averaged and handed as n=1 unique biologic sample. Expression for each sample was normalized to β-Actin (ACTA1) gene expression (ΔCt) and relative to cadaveric peripheral lung tissue control samples (ΔΔCt), with fold change calculated by 2−ΔΔCt (33 (link)).
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9

Quantitative Gene Expression Analysis

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For cultured haSMCs or haECs, RNA was isolated with the RNeasy Plus Kit (Life Technologies). For newborn mice, PBS was perfused through the left ventricle, the entire aorta from the root to the iliac arteries was dissected, and aortic RNA was extracted with mechanical homogenization in TRIzol (Invitrogen) and PureLink RNA columns (Invitrogen). The isolated RNA was reverse transcribed with the iScript cDNA Synthesis Kit (Bio-Rad), and qRT-PCR was performed on a CFX96 Real-Time System (Bio-Rad) using SsoFast EvaGreen supermix (Bio-Rad) and primer pairs as per Supplemental Table 3. Normalized mRNA levels are relative to 18S rRNA for cultured cells and to 18S rRNA or Gapdh for murine aortas.
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10

Vascular Gene Expression Profiling

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Descending aortas were dissected from mouse embryos and snap frozen in liquid nitrogen. The RNA of individual aortas of specific Eln genotypes was isolated with the RNeasy Plus kit (Life Technologies), and this RNA (0.5 µg) was reverse transcribed with the iScript cDNA Synthesis kit (Bio-Rad Laboratories). Expression levels of selected genes were determined by quantitative PCR and normalized to Gapdh. The following forward and reverse primer pairs were used for these genes (encoded protein): Acta2 (SMA), 5′-GTCCCAGACATCAGGGAGTAA-3′ and 5′-TCGGATACTTCAGCGTCAGGA-3′; Tagln (SM22-α), 5′-CAACAAGGGTCCATCCTACGG-3′ and 5′-ATCTGGGCGGCCTACATCA-3′; Myh11 (SMMHC), 5′-AAGCTGCGGCTAGAGGTCA-3′ and 5′-CCCTCCCTTTGATGGCTGAG-3′; Itgb1 (Integrin β1), 5′-CTCCAGAAGGTGGCTTTGATGC-3′ and 5′-GTGAAACCCAGCATCCGTGGAA-3′; Itgb3 (Integrin β3), 5′-GTGAGTGCGATGACTTCTCCTG-3′ and 5′-CAGGTGTCAGTGCGTGTAGTAC-3′; and Gapdh (GAPDH), 5′-CATCACTGCCACCCAGAAGACTG-3′ and 5′-ATGCCAGTGAGCTTCCCGTTCAG-3′.
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