Use of RNA-seq data to identify and validate RT-qPCR reference genes for studying the tomato-Pseudomonas pathosystem

Abstract

The agronomical relevant tomato-Pseudomonas syringae pv. tomato pathosystem is widely used to explore and understand the underlying mechanisms of the plant immune response. Transcript abundance estimation, mainly through reverse transcription-quantitative PCR (RT-qPCR), is a common approach employed to investigate the possible role of a candidate gene in certain biological process under study. The accuracy of this technique relies heavily on the selection of adequate reference genes. Initially, genes derived from other techniques (such as Northern blots) were used as reference genes in RT-qPCR experiments, but recent studies in different systems suggest that many of these genes are not stably expressed. The development of high throughput transcriptomic techniques, such as RNA-seq, provides an opportunity for the identification of transcriptionally stable genes that can be adopted as novel and robust reference genes. Here we take advantage of a large set of RNA-seq data originating from tomato leaves infiltrated with different immunity inducers and bacterial strains. We assessed and validated 9 genes that are much more stable than two traditional reference genes. Specifically, ARD2 and VIN3 were the most stably expressed genes and consequently we propose they be adopted for RT-qPCR experiments involving this pathosystem.

Tomato wall-associated kinase SlWak1 acts in an Fls2- and Fls3-dependent manner to promote apoplastic immune responses toPseudomonas syringae

“…tomato (Rosli et al ., 2013). In tomato leaves, transcript abundance of the Wak1 gene (Solyc09g014720) is significantly increased after treatment with flg22, flgII-28, or csp22, suggesting Wak1 might play a role in tomato- Pst interactions (Rosli et al ., 2013; Pombo et al ., 2017). To study the possible role of Wak1 in plant immunity, we generated mutations in Wak1 using CRISPR/Cas9 with a guide RNA, Wak1-gRNA1 (GTTAAGATTAGCATAAAACA; Fig.…”

“…Third, Fls3 gene expression induced by flgII-28 was the same in Δwak1 plants as it was in wild-type plants. Transcriptional changes also occur rapidly (within 1 hour) of MAMP treatment (Pombo et al ., 2017). As expected, the induction of Wak1 gene expression by flgII-28 was compromised in Δfls2.1/2.2/3 plants.…”

Selection and validation of reference genes for gene expression studies in Pseudomonas brassicacearum GS20 using real-time quantitative reverse transcription PCR

“…BestKeeper estimated the standard deviation (SD) of the Cq values [SD (± Cq)] and SD of the absolute regulation coefficients [SD (± x-fold)] and then considered whether a reference gene was acceptable. Generally, suitable reference genes should have values of SD [± Cq] < 1 and SD [± x-fold] <2 [27]. According to this standard, the candidate reference genes rho, 16S, gyr, and gmk passed this filter and gmk had the lowest SD [± Cq] (0.59) and SD [± x-fold] (1.50), while ftsz had both the highest SD [± Cq] (1.31) and SD [± x-fold] (2.49).…”

Multi-tissue transcriptome analysis using hybrid-sequencing reveals potential genes and biological pathways associated with azadirachtin A biosynthesis in neem (Azadirachta indica)&nbsp;

“…The inconsistency between FPKM and qRT-PCR may result from multiple reasons. Although qRT-PCR and RNA-seq are both used to measure gene expression, the unit of measurement [40] as well as the computing method are different for FPKM and qRT-PCR. Many factors affect the accuracy of FPKM and qRT-PCR.…”