Reference genes for normalization of qPCR assays in sugarcane plants under water deficit View Full Text


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Article Info

DATE

2017-12

AUTHORS

Larissa Mara de Andrade, Michael dos Santos Brito, Rafael Fávero Peixoto Junior, Paulo Eduardo Ribeiro Marchiori, Paula Macedo Nóbile, Alexandre Palma Boer Martins, Rafael Vasconcelos Ribeiro, Silvana Creste

ABSTRACT

BACKGROUND: Sugarcane (Saccharum spp.) is the main raw material for sugar and ethanol production. Among the abiotic stress, drought is the main one that negatively impact sugarcane yield. Although gene expression analysis through quantitative PCR (qPCR) has increased our knowledge about biological processes related to drought, gene network that mediates sugarcane responses to water deficit remains elusive. In such scenario, validation of reference gene is a major requirement for successful analyzes involving qPCR. RESULTS: In this study, candidate genes were tested for their suitable as reference genes for qPCR analyses in two sugarcane cultivars with varying drought tolerance. Eight candidate reference genes were evaluated in leaves sampled in plants subjected to water deficit in both field and greenhouse conditions. In addition, five genes were evaluated in shoot roots of plants subjected to water deficit by adding PEG8000 to the nutrient solution. NormFinder and RefFinder algorithms were used to identify the most stable gene(s) among genotypes and under different experimental conditions. Both algorithms revealed that in leaf samples, UBQ1 and GAPDH genes were more suitable as reference genes, whereas GAPDH was the best reference one in shoot roots. CONCLUSION: Reference genes suitable for sugarcane under water deficit were identified, which would lead to a more accurate and reliable analysis of qPCR. Thus, results obtained in this study may guide future research on gene expression in sugarcane under varying water conditions. More... »

PAGES

28

References to SciGraph publications

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/s13007-017-0178-2

    DOI

    http://dx.doi.org/10.1186/s13007-017-0178-2

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1084860854

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/28428808


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    N-Triples is a line-based linked data format ideal for batch operations.

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    RDF/XML is a standard XML format for linked data.

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