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Sci Rep ; 9(1): 2501, 2019 02 21.
Article in English | MEDLINE | ID: mdl-30792499

ABSTRACT

Reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) is a very sensitive widespread technique considered as the gold standard to explore transcriptional variations. While a particular methodology has to be followed to provide accurate results many published studies are likely to misinterpret results due to lack of minimal quality requirements. Yersinia pestis is a highly pathogenic bacterium responsible for plague. It has been used to propose a ready-to-use and complete approach to mitigate the risk of technical biases in transcriptomic studies. The selection of suitable reference genes (RGs) among 29 candidates was performed using four different methods (GeNorm, NormFinder, BestKeeper and the Delta-Ct method). An overall comprehensive ranking revealed that 12 following candidate RGs are suitable for accurate normalization: gmk, proC, fabD, rpoD, nadB, rho, thrA, ribD, mutL, rpoB, adk and tmk. Some frequently used genes like 16S RNA had even been found as unsuitable to study Y. pestis. This methodology allowed us to demonstrate, under different temperatures and states of growth, significant transcriptional changes of six efflux pumps genes involved in physiological aspects as antimicrobial resistance or virulence. Previous transcriptomic studies done under comparable conditions had not been able to highlight these transcriptional modifications. These results highlight the importance of validating RGs prior to the normalization of transcriptional expression levels of targeted genes. This accurate methodology can be extended to any gene of interest in Y. pestis. More generally, the same workflow can be applied to identify and validate appropriate RGs in other bacteria to study transcriptional variations.


Subject(s)
Bacterial Proteins/genetics , Gene Expression Profiling/standards , Yersinia pestis/growth & development , Computational Biology , Gene Expression Regulation, Bacterial , Reference Standards , Temperature , Workflow , Yersinia pestis/genetics
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