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• W2892709512 abstract "Differential RNA-Seq is a next-generation technology method to determine the significant transcriptomic differences between two and more samples. With this method it is possible to analyze the total RNA content of different samples making it the best global analysis method currently available to study the roles of exoribonucleases in the cell. These enzymes are responsible for the RNA processing and degradation in the cells and therefore affect the total RNA pool in ways not yet fully understood. In Escherichia coli there are three main degradative exoribonucleases RNase II, RNase R, and PNPase that degrade the RNA from the 3' to the 5'-end. These enzymes have several roles in the cell and even though they are degradative enzymes RNase II and PNPase can also protect some RNAs from degradation and PNPase can also act as an RNA polymerase under some conditions. The multiplicity of roles of these exoribonucleases leads to a very high number of transcripts that are affected by their absence in the cell. With the differential RNA-Seq it is possible to obtain a much deeper understanding of how these enzymes work and regulate the bacterial gene expression. In this chapter we have described a differential RNA-Seq data analysis protocol applied to the study of exoribonucleases. We also included the protocol for experimental validation of the RNA-Seq data using qPCR and motility assays. Although the methods described in this chapter were applied to the study of the exoribonucleases, they can also be used for other differential RNA-Seq studies." @default.
• W2892709512 created "2018-10-05" @default.
• W2892709512 creator A5056765512 @default.
• W2892709512 creator A5084693518 @default.
• W2892709512 date "2018-01-01" @default.
• W2892709512 modified "2023-10-17" @default.
• W2892709512 title "Characterizing the Role of Exoribonucleases in the Control of Microbial Gene Expression: Differential RNA-Seq" @default.
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• W2892709512 doi "https://doi.org/10.1016/bs.mie.2018.08.010" @default.
• W2892709512 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30502937" @default.
• W2892709512 hasPublicationYear "2018" @default.
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