Rna Quality Assessment
Rna Quality Assessment - Related Videos
05:07
Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes
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2025
This protocol allows initial quality control for RNA-seq experiments for wet-lab biologists with limited bioinformatics experience.
18:17
Obtaining High Quality RNA from Single Cell Populations in Human Postmortem Brain Tissue
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Cited by 39 •
2009
We describe a process using laser-capture microdissection to isolate and extract RNA from a homogeneous cell population, pyramidal neurons, in layer III of the superior temporal gyrus in postmortem human brains. We subsequently linearly amplify (T7-based) mRNA, and hybridize the sample to the Affymetrix human X3P microarray.
05:00
Using a Chemical Biopsy for Graft Quality Assessment
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Cited by 11 •
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The protocol presents utilization of the chemical biopsy approach followed by comprehensive metabolomic and lipidomic analysis for quality assessment of kidney grafts allocated for transplantation.
09:54
RNA-Seq
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2023
Among different methods to evaluate gene expression, the high-throughput sequencing of RNA, or RNA-seq. is particularly attractive, as it can be performed and analyzed without relying on prior available genomic information. During RNA-seq, RNA isolated from samples of interest is used to generate a DNA library, which is then amplified and sequenced. Ultimately, RNA-seq can determine which genes are expressed, the levels of their expression, and the presence of any previously unknown transcripts.
13:16
Assessment of DNA Contamination in RNA Samples Based on Ribosomal DNA
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Cited by 26 •
2018
Here, we present a protocol for tracing genomic DNA (gDNA) contamination in RNA samples. The presented method utilizes primers specific for the internal transcribed spacer region (ITS) of ribosomal DNA (rDNA) genes. The method is suited for reliable and sensitive detection of DNA contamination in most eukaryotes and prokaryotes.
FAQs
Purity and integrity answer different quality questions. Absorbance-based measurements indicate how much RNA is present and whether contaminants may be affecting the sample, whereas gel or capillary electrophoresis shows whether RNA molecules remain intact or have been degraded. Considering both measurements prevents a concentrated sample with damaged or contaminated RNA from being treated as suitable.
Electrophoresis separates RNA according to size, so the resulting pattern provides a direct view of molecular integrity and degradation. An RNA Integrity Number, or RIN, condenses instrument-derived integrity information into a summary value. Together, these outputs help compare samples consistently and identify material that may compromise downstream measurements.
RNA integrity matters because degraded material may no longer preserve the original transcript representation. That distortion can influence reverse transcription, quantitative PCR, RNA sequencing, and broader transcriptome analysis, making differences between samples harder to interpret. Assessing integrity before these experiments helps distinguish changes associated with sample damage from biological changes in gene expression.
A damaged or inconsistent RNA sample can introduce variation that does not reflect the biology under study. Comparing concentration, contaminant indicators, and integrity information across samples helps investigators identify such technical differences before interpreting expression results. This is particularly important when deciding whether apparent gene-expression changes represent biological effects or unequal sample quality.
A practical workflow begins by measuring RNA concentration and indicators of contamination with an absorbance-based method. The sample is then examined by gel or capillary electrophoresis to evaluate molecular integrity, while an instrument may provide an RNA Integrity Number. Researchers can use the combined results to identify damaged samples and judge suitability for downstream experiments.
Measurements can identify damaged samples and make sample handling more consistent before downstream analysis. Concentration information supports comparable RNA input, while purity and integrity findings indicate whether a sample is suitable for the planned experiment. This standardization reduces avoidable technical variation and improves the basis for comparing reverse-transcription or gene-expression results.
The checks are especially relevant before reverse transcription, quantitative PCR, RNA sequencing, and transcriptome analysis. These methods depend on RNA that preserves representative transcript information and is not compromised by contaminants or degradation. Quality results therefore help researchers decide whether a sample can support the intended assay and interpret downstream measurements with greater confidence.