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RNA Degradation

RNA degradation is the process by which cellular RNA molecules are broken down and removed.
This essential process regulates gene expression and ensures the proper turnover of RNA species.
Researchers studying RNA degradation can leverage AI-powered tools like PubCompare.ai to easily locate and evaluate the most effective protocols from literature, preprints, and patents.
These intelligent comparison tools provide valuable insights to identify the best approaches and products for your RNA degradation research needs, enabling seamless and optimized experimentation.
PubCompare.ai's AI-driven platform helps scientists streamline their RNA degradation studies and accelerate their discoveries.

Most cited protocols related to «RNA Degradation»

1
Comprehensive Molecular Profiling of Prostate Cancer

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Open the protocol to access the free full text link

Publication 2015
Blindness Cells DNA Chips Ethics Committees, Research Exome Freezing Malignant Neoplasms Methylation MicroRNAs Microtubule-Associated Proteins Neoplasm Metastasis Neoplasms Pathologists Patients Prostate Prostate Cancer Prostatic Intraepithelial Neoplasias Protein Arrays Proteins RNA Degradation Seminal Vesicles System, Genitourinary Tissues
2
Microarray Data Analysis Pipeline
Scanned images were first inspected for quality control (QC) using a variety of built-in QC tools from the Bioconductor package [10 ] of R, the open source environment for statistical analysis. QC consisted of visual examination of probe array images, scatter plots from replicates, hierarchical clustering of array hybridizations, RNA degradation plots and MvA plots. Feature intensity values from scanned arrays were normalised and reduced to expression summaries using the GC Robust Multiarray Algorithm (GCRMA) [11 ,12 (link)] implemented as a function in the Bioconductor GCRMA library [13 (link)]. Detection calls indicating the presence or absence of signal from each probe set were obtained by processing the raw data with the Microarray Analysis Suite 5.0 (MAS5). To obtain a consensus detection call across replicate hybridizations, a probe set was considered to be present if it received a P (present) detection call from all replicates or n-1 replicates with an M (marginal) call from the remaining replicate. A (absent) detection calls were determined in the same way.
For further analysis, probesets 3' locations were obtained by downloading the MOE430a probe tab files made available by the Affymetrix online support [39]. A probeset location was considered equal to the 3' distance of the probe that is most distal from the 3' end of the corresponding target within the set.
To test for differential expression, two statistical methods were used. The bayesian adjusted t-statistics from the linear models for Micoarray data (limma) package [14 ,15 ] and the Z-scores method as described by Quackenbush [16 ]. With both methods, a multiple testing correction based on the false discovery rate (FDR) was performed.
Diboun I., Wernisch L., Orengo C.A, & Koltzenburg M. (2006). Microarray analysis after RNA amplification can detect pronounced differences in gene expression using limma. BMC Genomics, 7, 252.
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Publication 2006
cDNA Library Crossbreeding DNA Replication Microarray Analysis RNA Degradation
3
RNA Integrity Assessment Methodology
For classification of RNA integrity, ten categories were defined from 1 (totally degraded RNA) to 10 (fully intact RNA). Figure 2 illustrates qualitatively the differences between the categories. Each of the 1208 samples was assigned manually to one of the categories by experienced expert users.
The categorical values provide the target values for the adaptive learning steps. The assignment to categories was very carefully done as it is critical for the performance of the resulting algorithm. Especially for RNA samples at the borderline of two adjacent integrity categories, the assignment to each of the two categories could be justified but one had to be selected. This reflects a natural randomness which is inherent in a gradual process like RNA degradation. However, such random noise in the target values can easily be handled by the learning model, which assumes noise in the target data.
Detecting abnormalities in the electropherogram is another important preprocessing step to get a clean set of training samples. Various anomalies can disturb the usual shape of an electropherogram, e.g., ghost peaks, spikes, wavy baseline, and unexpected sample type. They were observed in approx. 5% of the samples. To separate anomalies from normal samples, several simple detectors were constructed. Each detector performs a linear classification based on a threshold value. Spikes, for example, can have a large peak height but have very narrow peak width; they appear as very sharp peaks. Normally, the largest peaks in the electrophoretic traces are located at the 18S and 28S bands but compared to a spike are significantly broader. If a high peak does not cover the minimal requested area, it is rejected as a spike and marked as abnormal. Applying these detection criteria to the data set returned 117 electropherograms as abnormal. Eleven abnormal samples could not be detected for example, because a spike arose near the 28S peak and could not be identified as such. All of them were assigned a sensible label and put in the test set. This reflects the natural occurrence of such effects in the test phase.
In the application phase we distinguish between critical and non-critical anomalies based on their influence on the computation of the RIN. The former are anomalies of baseline and anomalies in the 5S-region, the latter anomalies in the pre-region, precursor-region and post-region (cf. fig. 8).
If a critical anomaly is detected, the RIN is not computed. Instead, an error message appears to the user. If a non-critical anomaly is detected, the RIN is computed and a warning to the user is displayed [10 ,11 ]. Baseline correction and normalization are applied to the electropherogram prior to the actual feature extraction process. These functions are standard features of Agilent's Expert Software [12 ]. The baseline is a constant background signal of the electropherogram and its level may significantly differ between different electropherograms. The baseline-corrected signal is then normalized. For height related features it is normalized to the global maximum of the 5S-region to precursor-region. For area related features it is normalized to the global signal area in the 5S-region to precursor-region. The pre-region, marker-region and post-region are intentionally not considered critical elements of the electrophoretic trace since they don't contain critical information about the RNA degradation process.
Schroeder A., Mueller O., Stocker S., Salowsky R., Leiber M., Gassmann M., Lightfoot S., Menzel W., Granzow M, & Ragg T. (2006). The RIN: an RNA integrity number for assigning integrity values to RNA measurements. BMC Molecular Biology, 7, 3.
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Publication 2006
Acclimatization Congenital Abnormality Electrophoresis Red Cell Ghost RNA Degradation Trace Elements
4
In Silico Single-Cell RNA-Seq Simulation
To generate an in silico library for a single cell, we built a simulator that first selects G genes at random from a relative expression profile (Pbulk) derived from a bulk RNA-Seq experiment to represent the hypothetical relative abundance of a single-cell in cell lysate. These values are rescaled to proportions (i.e. summing to 1), or ρscaled.
ρscaled∼scale(uniform(Pbulk(1,2,…),G))
These proportions are then used to parameterize a multinomial distribution from which T transcripts are drawn to obtain the transcripts in the library space where we also consider there is αi percentage of the RNA is degraded. Therefore, we have:
library:Yijl∼multinomial(ρscaled,(1−αi)Ti) To this pool of transcripts, a fixed number of spike-in transcripts are added, forming a mixture of simulated “endogenous” and “spike-in” mRNAs where the degradation of spike-in transcripts is represented by βi. Of these, θi percent are selected uniformly at random to simulate incomplete mRNA capture by the reverse transcription process. Finally, the abundances of these cDNAs relative to one another were used to parameterize another multinomial, from which Ri reads are sampled. The read counts are then used to calculate the relative abundance for the spike-in and the endogenous RNA.
In this study, we systematically simulated the sc RNA-seq process obtained from bulk RNA-Seq measurements made in Trapnell and Cacchiarelli et al18 by varying the gene number G, capture rate θ, endogenous RNA degradation α, spike-in degradation β, total endogenous transcript count T and total number of reads R. Results based on simulation are shown in Supplemental Figure 4.
Qiu X., Hill A., Packer J., Lin D., Ma Y.A, & Trapnell C. (2017). Single-cell mRNA quantification and differential analysis with Census. Nature methods, 14(3), 309-315.
Publication 2017
cDNA Library Dietary Fiber DNA, Complementary Genes Reverse Transcription RNA, Messenger RNA-Seq RNA Degradation Single-Cell RNA-Seq
5
RNAtag-Seq Library Preparation Protocol
K562 dUTP libraries were generated as described with rRNA depleted using the RNaseH approach22 (link). Bacterial dUTP libraries were generated as described21 (link) with rRNA depleted using with RiboZero (Epicentre). In all RiboZero reactions, the maximal amount recommended by the manufacturer per reaction was used to avoid an additional quantification step during library construction and ensure the RNA did not exceed the capacity of the solution. RNAtag-Seq cDNA libraries were generated according to the detailed protocol in the Supplementary Protocol. Briefly, 200-400 ng of total RNA was fragmented, depleted of genomic DNA and dephosphorylated before its ligation to barcoded adaptors with a 5′ phosphate and a 3′ blocking group. DNA adaptors carried 5′-AN8-3′ barcodes and RNA adaptors 5′-rArN6-3′ barcodes. Sequences of these barcodes are provided in the Supplementary Protocol and Supplementary Table 2. Barcoded RNAs were pooled and depleted of rRNA using the appropriate RiboZero rRNA depletion kit (Epicentre) for bacterial and K562 pools (8 samples per pool, Supplementary Table 2) and as previously described23 (link) for mouse pools. These pools of barcoded RNAs were converted to Illumina cDNA libraries in three key steps: (i) reverse transcription of the RNA using a primer designed to the constant region of the barcoded adaptor; (ii) degradation of the RNA and ligation of a second adaptor to the single-stranded cDNA; (iii) PCR amplification using primers that target the constant regions of the 3′ and 5′ ligated adaptors and contain the full sequence of the Illumina sequencing adaptors (Fig. 1). Two SPRI cleanup steps are included following adaptor ligations to ensure efficient removal of adaptor dimers (<1% of our sequencing reads represented adaptor dimers). Modifications of the RNAtag-Seq protocol used in generation of mouse libraries are detailed in Appendix A in the Supplementary Protocol. cDNA libraries were sequenced on Illumina MiSeq or HiSeq2500
Shishkin A.A., Giannoukos G., Kucukural A., Ciulla D., Busby M., Surka C., Chen J., Bhattacharyya R.P., Rudy R.F., Patel M.M., Novod N., Hung D.T., Gnirke A., Garber M., Guttman M, & Livny J. (2015). Simultaneous generation of many RNA-seq libraries in a single reaction. Nature methods, 12(4), 323-325.
Publication 2015
Bacteria cDNA Library deoxyuridine triphosphate DNA, Complementary Genome Ligation Mice, House Oligonucleotide Primers Phosphates Reverse Transcription Ribosomal RNA RNA RNA, immune RNA Degradation RNA I

Most recents protocols related to «RNA Degradation»

1
In Vitro Transcription for Customized mRNA Synthesis
Not available on PMC !

Example 3

The in vitro transcription reactions can generate polynucleotides containing uniformly modified polynucleotides. Such uniformly modified polynucleotides can comprise a region or part of the polynucleotides of the invention. The input nucleotide triphosphate (NTP) mix can be made using natural and un-natural NTPs.

A typical in vitro transcription reaction can include the following:

    • 1 Template cDNA—1.0
    • 2 10× transcription buffer (400 mM Tris-HCl pH 8.0, 190 mM MgCl2, 50 mM DTT, mM Spermidine)—2.0
    • 3 Custom NTPs (25 mM each)—7.2 μl
    • 4 RNase Inhibitor—20 U
    • 5 T7 RNA polymerase—3000 U
    • 6 dH2O—Up to 20.0 μl. and
    • 7 Incubation at 37° C. for 3 hr-5 hrs.

The crude IVT mix can be stored at 4° C. overnight for cleanup the next day. 1 U of RNase-free DNase can then be used to digest the original template. After 15 minutes of incubation at 37° C., the mRNA can be purified using Ambion's MEGACLEAR™ Kit (Austin, TX) following the manufacturer's instructions. This kit can purify up to 500 μg of RNA. Following the cleanup, the RNA can be quantified using the NanoDrop and analyzed by agarose gel electrophoresis to confirm the RNA is the proper size and that no degradation of the RNA has occurred.

US11859215B2. Polynucleotides encoding ornithine transcarbamylase for the treatment of urea cycle disorders (2024-01-02). ModernaTX, Inc. [US]. Inventors: Zhijian Zhuo [US], Andrea Lea Frassetto [US], Paolo G. V. Martini [US], Vladimir Presnyak [US], Patrick Finn [US].
Full text: Click here
Patent 2024
austin Buffers Deoxyribonuclease I DNA, Complementary DNA-Directed RNA Polymerase Electrophoresis, Agar Gel Endoribonucleases Magnesium Chloride Nucleotides Polynucleotides ribonuclease U RNA, Messenger RNA Degradation Spermidine Transcription, Genetic triphosphate Tromethamine
2
Capping of Polynucleotides via IVT RNA
Not available on PMC !

Example 4

Capping of a polynucleotide can be performed with a mixture includes: IVT RNA μg-180 μg and dH2O up to 72 μl. The mixture can be incubated at 65° C. for 5 minutes to denature RNA, and then can be transferred immediately to ice.

The protocol can then involve the mixing of 10× Capping Buffer (0.5 M Tris-HCl (pH 8.0), 60 mM KCl, 12.5 mM MgCl2) (10.0 IA); 20 mM GTP (5.0 IA); 20 mM S-Adenosyl Methionine (2.5 μl); RNase Inhibitor (100 U); 2′-O-Methyltransferase (400U); Vaccinia capping enzyme (Guanylyl transferase) (40 U); dH2O (Up to 28 μl); and incubation at 37° C. for 30 minutes for 60 μg RNA or up to 2 hours for 180 μg of RNA.

The polynucleotide can then be purified using Ambion's MEGACLEAR™ Kit (Austin, TX) following the manufacturer's instructions. Following the cleanup, the RNA can be quantified using the NANODROP™ (ThermoFisher, Waltham, MA) and analyzed by agarose gel electrophoresis to confirm the RNA is the proper size and that no degradation of the RNA has occurred. The RNA product can also be sequenced by running a reverse-transcription-PCR to generate the cDNA for sequencing.

US11859215B2. Polynucleotides encoding ornithine transcarbamylase for the treatment of urea cycle disorders (2024-01-02). ModernaTX, Inc. [US]. Inventors: Zhijian Zhuo [US], Andrea Lea Frassetto [US], Paolo G. V. Martini [US], Vladimir Presnyak [US], Patrick Finn [US].
Full text: Click here
Patent 2024
austin Buffers DNA, Complementary Electrophoresis, Agar Gel Endoribonucleases Enzymes Magnesium Chloride Methyltransferase Polynucleotides Reverse Transcription RNA Degradation S-Adenosylmethionine Transferase Tromethamine Vaccinia virus
3
Capping and Purification of IVT RNA
Not available on PMC !

Example 5

Capping of a RNA polynucleotide is performed as follows where the mixture includes: IVT RNA 60 μg-180 μg and dH2O up to 72 μl. The mixture is incubated at 65° C. for 5 minutes to denature RNA, and then is transferred immediately to ice.

The protocol then involves the mixing of 10× Capping Buffer (0.5 M Tris-HCl (pH 8.0), 60 mM KCl, 12.5 mM MgCl2) (10.0 μl); 20 mM GTP (5.0 μl); 20 mM S-Adenosyl Methionine (2.5 μl); RNase Inhibitor (100 U); 2′-O-Methyltransferase (400U); Vaccinia capping enzyme (Guanylyl transferase) (40 U); dH2O (Up to 28 μl); and incubation at 37° C. for 30 minutes for 60 μg RNA or up to 2 hours for 180 μg of RNA.

The RNA polynucleotide may then be purified using Ambion's MEGACLEAR™ Kit (Austin, TX) following the manufacturer's instructions. Following the cleanup, the RNA may be quantified using the NANODROP™ (ThermoFisher, Waltham, MA) and analyzed by agarose gel electrophoresis to confirm the RNA polynucleotide is the proper size and that no degradation of the RNA has occurred. The RNA polynucleotide product may also be sequenced by running a reverse-transcription-PCR to generate the cDNA for sequencing.

US11872278B2. Combination HMPV/RSV RNA vaccines (2024-01-16). ModernaTX, Inc. [US]. Inventors: Giuseppe Ciaramella [US], Sunny Himansu [US].
Full text: Click here
Patent 2024
austin Buffers DNA, Complementary Electrophoresis, Agar Gel Endoribonucleases Enzymes Magnesium Chloride Methyltransferase Polynucleotides Reverse Transcription RNA Caps RNA Degradation S-Adenosylmethionine Transferase Tromethamine Vaccinia virus
4
Transcriptome Analysis of Sea Bass Intestines
Intestines were obtained from the sea bass in the two Groups 24 h after infection. Total RNA of the two groups was extracted using the TRIzol method. RNA degradation and contamination were monitored on 1% agarose gels. RNA concentration was measured using a Qubit® RNA Assay Kit in a Qubit® 2.0 Fluorometer (Life Technologies, CA, United States). A total amount of 1 μg RNA per sample was used as input material for the RNA sample preparations. Sequencing libraries were generated using the NEBNext® UltraTM RNA Library Prep Kit for Illumina® (NEB, United States) following the manufacturer’s recommendations, and index codes were added to attribute sequences to each sample. The clustering of the index-coded samples was performed on a cBot Cluster Generation System using TruSeq PE Cluster Kit v3-cBot-HS (Illumina) according to the manufacturer’s instructions. After cluster generation, the library preparations were sequenced on an Illumina HiSeq platform, and 125 bp/150 bp paired-end reads were generated. High-throughput transcriptome sequencing was completed by Wuhan Metware Biotechnology Co., Ltd.
Pan C., Zhu Y., Cao K., Li J., Wang S., Zhu J., Zeng X., Zhang H, & Qin Z. (2023). Transcriptome, intestinal microbiome and histomorphology profiling of differences in the response of Chinese sea bass (Lateolabrax maculatus) to Aeromonas hydrophila infection. Frontiers in Microbiology, 14, 1103412.
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Publication 2023
Biological Assay DNA Library Gels Infection Intestines RNA Degradation Sepharose Serranidae Transcriptome trizol
5
Transcriptomic Analysis of Chicken Uterine Tissue
Based on the results of production performance and egg quality, a total of 6 birds were randomly selected from groups C and N1 for further transcriptomics analysis of uterine tissue by RNA-seq. Birds were euthanized with 1 cc Euthasol® intravenously after 12 h fasting on the last day of the experiment and then remove uterus tissue.
Total RNA was extracted from tissue samples using Trizol reagent. The degree of RNA degradation was analyzed by agarose gel electrophoresis and RNA purity was detected using a Nanodrop 2000 spectrophotometer. The RNA concentration was accurately quantified by Qubit 2.0; and RNA integrity was detected using the Agilent 2100 Bioanalyzer. Following sample testing, a total amount of 3 μg RNA per sample was used as input material for the RNA sample preparations. Sequencing libraries were generated using NEBNext® UltraTM RNA Library Prep Kit for Illumina® (NEB, USA) following manufacturer's recommendations and index codes were added to attribute sequences to each sample (15 (link)). The quality of library was assessed on the Agilent Bioanalyzer 2100 system.
The library preparations were sequenced on an Illumina HiSeq. 2500 platform.Quality control of the reads was performed by using in-house written scripts. Raw data of Fastq format were initially processed by in-house perl scripts. In this step, clean reads were obtained by removing reads containing adapter, poly-N, and low-quality reads from raw data. Q20, Q30 and GC content were calculated for the clean data. All downstream analyses were based on clean data with high quality. The PE 150 paired-end sequencing strategy was used in this study. The chicken's genome sequence (90 version) was downloaded from genome website (ftp://ftp.ensembl.org/pub/current_fasta/gallus_gallus/dna/Gallus_gallus.Gallus_gallus-5.0.dna.toplevel.fa.gz). Index of the reference genome was built using Hisat2 v2.0.5 and paired-end clean reads were aligned to the reference genome using Hisat2 v2.0.5. The gene expression level was estimated by the number of normalized fragments per kilogram of transcript per million fragments (FPKM) method. The differential expression analysis of the groups was performed using the DESeq. 2R package (1.16.1) based on the readcount data. The resulting P values were adjusted using the Benjamini and Hochberg's approach for controlling the false discovery rate. Genes with an adjusted P < 0.05 found by DESeq. Two were assigned as differentially expressed. The group C was used as the control group to analyze the differentially expressed genes in the uterine tissue as affected by NCG supplementation.
Gene ontology (GO) (http://www.geneontology.org/) enrichment analysis of differentially expressed genes was performed using GOseq based on Wallenius non-central hyper-geometric distribution43. This includes three parts: molecular function, biological process, and cellular component. A specific P-value was used to determine if a DEG is enriched in the GO. Usually, a P < 0.05 is indicative of enrichment. Pathway enrichment analysis was assessed using the KEGG (Kyoto Encyclopedia of Genes and Genomes) database44 (http://www.genome.jp/kegg/). The ClusterProfiler R package was used to test the statistical enrichment of differential expression genes in KEGG pathways. A P < 0.05 was considered indicative of the function being enriched.
Ma W., Lu Y, & Wang C. (2023). Production performance, egg quality, and uterine gene expression for layers as affected by N-Carbamylglutamate supplementation. Frontiers in Veterinary Science, 10, 1110801.
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Publication 2023
Aves Biological Processes Cellular Structures Chickens DNA Library Electrophoresis, Agar Gel Gene Expression Gene Expression Profiling Genes Genome Poly A RNA-Seq RNA Degradation Tissues trizol Uterus

Top products related to «RNA Degradation»

1
Rna nano 6000 assay kit by Agilent Technologies
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The RNA Nano 6000 Assay Kit is a laboratory equipment product designed for the analysis and quantification of RNA samples. It provides a standardized method for the assessment of RNA integrity and concentration.
2
Trizol reagent by Thermo Fisher Scientific
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TRIzol reagent is a monophasic solution of phenol, guanidine isothiocyanate, and other proprietary components designed for the isolation of total RNA, DNA, and proteins from a variety of biological samples. The reagent maintains the integrity of the RNA while disrupting cells and dissolving cell components.
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Nanophotometer spectrophotometer by Implen
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The NanoPhotometer® is a UV-Vis spectrophotometer designed for precise and accurate measurements of nucleic acid and protein concentrations. It features a compact, robust, and easy-to-use design for laboratory applications.
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Qubit rna assay kit by Thermo Fisher Scientific
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The Qubit® RNA Assay Kit is a quantitative and sensitive fluorescence-based assay designed for measuring the concentration of RNA in solution. The kit provides a simple and accurate method to determine the RNA concentration in a sample.
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Agilent bioanalyzer 2100 system by Agilent Technologies
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The Agilent Bioanalyzer 2100 system is a microfluidics-based platform designed for the analysis of DNA, RNA, proteins, and cells. It provides automated electrophoretic separation and detection of these biomolecules in a miniaturized format.
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Bioanalyzer 2100 system by Agilent Technologies
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The Bioanalyzer 2100 system is a lab equipment product from Agilent Technologies. It is designed to perform automated electrophoretic analysis of DNA, RNA, and proteins. The system provides quantitative and qualitative data on the size, concentration, and integrity of these biomolecules.
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Qubit 2.0 fluorometer by Thermo Fisher Scientific
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The Qubit 2.0 Fluorometer is a compact and sensitive instrument designed for quantifying nucleic acids and proteins. It utilizes fluorescent dye-based detection technology to provide accurate and reproducible measurements of sample concentrations. The Qubit 2.0 Fluorometer is a self-contained unit that can be used for a variety of applications in research and clinical settings.
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Trizol by Thermo Fisher Scientific
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TRIzol is a monophasic solution of phenol and guanidine isothiocyanate that is used for the isolation of total RNA from various biological samples. It is a reagent designed to facilitate the disruption of cells and the subsequent isolation of RNA.
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Rneasy mini kit by Qiagen
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The RNeasy Mini Kit is a laboratory equipment designed for the purification of total RNA from a variety of sample types, including animal cells, tissues, and other biological materials. The kit utilizes a silica-based membrane technology to selectively bind and isolate RNA molecules, allowing for efficient extraction and recovery of high-quality RNA.

More about "RNA Degradation"

RNA degradation is a fundamental biological process where cellular RNA molecules are broken down and removed.
This essential process helps regulate gene expression and ensures the proper turnover of various RNA species.
Researchers studying RNA degradation can leverage powerful AI-driven tools like PubCompare.ai to easily locate and evaluate the most effective protocols from scientific literature, preprints, and patents.
These intelligent comparison tools provide valuable insights that can help identify the best approaches and products for your RNA degradation research needs, enabling seamless and optimized experimentation.
PubCompare.ai's AI-powered platform assists scientists in streamlining their RNA degradation studies and accelerating their discoveries.
In addition to PubCompare.ai, researchers can also utilize other cutting-edge technologies and techniques for their RNA degradation research.
The RNA Nano 6000 Assay Kit, for instance, can be used to assess the quality and integrity of RNA samples.
The TRIzol reagent is a popular method for RNA extraction, while the NanoPhotometer® spectrophotometer and Agilent 2100 Bioanalyzer are commonly used for RNA quantification and analysis.
The Qubit® RNA Assay Kit and Agilent Bioanalyzer 2100 system are also valuable tools for accurate RNA quantification and quality assessment.
The Qubit 2.0 Fluorometer, in particular, provides a sensitive and specific way to measure RNA concentrations.
Additionally, the TRIzol and RNeasy Mini Kit are widely used for efficient RNA isolation and purification.
By leveraging these cutting-edge technologies and techniques, researchers can optimize their RNA degradation studies, enhance their understanding of this essential biological process, and accelerate their groundbreaking discoveries.