Publicações

@article{Rogerio2019,

title = {Reference genes for gene expression studies by RT-qPCR in Brevipalpus yothersi (Acari: Tenuipalpidae), the mite vector of citrus leprosis virus},

author = {Luana Aparecida Rogerio and Diogo Manzano Galdeano and Gabriella Dias Arena and Maria Andreia Nunes and Marcos Antonio Machado and Valdenice Moreira Novelli},

url = {https://www.nature.com/articles/s41598-019-42993-2},

doi = {10.1038/s41598-019-42993-2},

issn = {2045-2322},

year  = {2019},

date = {2019-01-01},

journal = {Scientific Reports 2019 9:1},

volume = {9},

issue = {1},

pages = {1-9},

publisher = {Nature Publishing Group},

abstract = {Quantitative reverse transcription PCR (RT-qPCR) is a high-throughput method to analyze the transcriptional expression of genes. Currently, no reference genes have been described for evaluating gene expression in Brevipalpus yothersi, the false spider mite, a polyphagous that act as vector of the citrus leprosis virus C (CiLV-C), an important citrus disease. This study aimed to identify the most stable reference genes in B. yothersi. The RT-qPCR expression data for selected genes were evaluated from three conditions: different developmental stages, plant hosts and acquisition of CiLV-C. To analyze the stability of the candidate reference genes we used ΔCq method, GeNorm, NormFinder, BestKeeper and RefFinder. Ubiq and GAPDH are best suited for normalizing gene expression data in viruliferous and non-viruliferous mites. Ubiq, EF1α and GAPDH are the most stable for different developmental stages. RPL13 and RPL32 are the best reference genes for approaches to B. yothersi in different host plants. Considering all the experimental conditions, Ubiq, EF1α, and GAPDH were the most stable genes. Here we developed an accurate and comprehensive RT-qPCR strategy for use in B. yothersi gene expression analysis. These results will improve the understanding of the biology of the false spider mites and their role as virus vectors.},

keywords = {Gene expression, Gene expression profiling, RNAi},

pubstate = {published},

tppubtype = {article}

}