Use of RNA-seq data to identify and validate RT-qPCR reference genes for studying the tomato-Pseudomonas pathosystem.
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.
Instituto de Fisiología Vegetal, INFIVE, Universidad Nacional de La Plata, CONICET, La Plata, Buenos Aires, Argentina.
Marina A
MA
Pombo
Boyce Thompson Institute for Plant Research, 533 Tower Road, Ithaca, NY 14853, USA.
Yi
Y
Zheng
Boyce Thompson Institute for Plant Research, 533 Tower Road, Ithaca, NY 14853, USA.|USDA-ARS Robert W. Holley Center for Agriculture and Health, Ithaca, NY 14853, USA.
Zhangjun
Z
Fei
Boyce Thompson Institute for Plant Research, 533 Tower Road, Ithaca, NY 14853, USA.|Section of Plant Pathology and Plant-Microbe Biology, School of Integrative Plant Science, Cornell University, Ithaca, NY 14853, USA.
Gregory B
GB
Martin
Instituto de Fisiología Vegetal, INFIVE, Universidad Nacional de La Plata, CONICET, La Plata, Buenos Aires, Argentina.
Hernan G
HG
Rosli
D000465:Algorithms; D019295:Computational Biology / Q000379:methods; D020869:Gene Expression Profiling; D018506:Gene Expression Regulation, Plant; D059014:High-Throughput Nucleotide Sequencing; D054884:Host-Pathogen Interactions / Q000235:genetics* / Q000276:immunology; D018551:Solanum lycopersicum / Q000235:genetics* / Q000382:microbiology*; D010935:Plant Diseases / Q000235:genetics / Q000382:microbiology; D044224:Pseudomonas syringae / Q000502:physiology; D015203:Reproducibility of Results; D017423:Sequence Analysis, RNA; D059467:Transcriptome