iScienceMolecular BiologyPeer-reviewed journal article
Integrity assay for messenger RNA in mouse and human brain samples and synaptosomal preparations
Daina BujanauskienėiD, Kajus MerkevičiusiD, Ugnė KuliešiūtėiD, Jaroslav DenkovskijiD, Simonas Kutanovas, Gediminas LukšysiD, Saulius RočkaiD, Eiva BernotienėiD, Urtė NeniškytėiD
Abstract
Traditionally, RNA integrity evaluation is based on ribosomal RNAs (rRNAs). Nevertheless, gene expression studies are usually focused on protein coding messenger RNAs (mRNAs). As rRNA and mRNA have significant structural and functional differences, the assumption that rRNA integrity properly represents mRNA integrity may not be accurate. Moreover, contrary to whole tissue RNA samples, subcellular preparations such as synaptosomes contain almost no rRNA, thus prohibiting the use of traditional rRNA-based methods to assess sample RNA integrity. Here we present a RT-qPCR based assay, which estimates mRNA integrity by comparing the abundance of 3 and 5 mRNA fragments in a long constitutively expressed mouse or human PGK1 mRNA. The assay was tested and validated using plasmids with cloned 3- and 5-ends of the PGK1 cDNA reflecting different ratios of 3 and 5 cDNA amplicons in partially degraded RNA samples. The accuracy of integrity score calculation was ensured by integrating a mathematical correction of qPCR results to account for the variable amplification efficiency of different primer pairs. The 5:3 assay was used to quantify RNA degradation in heat-degraded mouse and human brain tissue RNA as well as in clinical human brain RNA samples. Importantly, the expression of housekeeping genes correlated better with 5:3 integrity value than with the RIN. Finally, we were even able to use 5':3' assay to assess mRNA integrity in mouse synaptosomal preparations that lack rRNAs. We concluded that the 5:3 assay can be used as a reliable and sensitive method to evaluate mRNA integrity in mouse and human brain tissue and subcellular preparations.
- organism: mouse
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
- Citations
- 3
- FWCI
- 0.41
- Field percentile
- top 47%
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