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Transcriptome-wide identification and evaluation of optimal reference genes for RT-qPCR expression analysis of Saccharina latissima responses to biotic and abiotic stress

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Saccharina latissima , known as sugar kelp, is a brown macroalga with huge ecological and economic values. In marine intertidal environment, S. latissima has to cope with both biotic and… Click to show full abstract

Saccharina latissima , known as sugar kelp, is a brown macroalga with huge ecological and economic values. In marine intertidal environment, S. latissima has to cope with both biotic and abiotic stress, which can cause the reduction of the yield during cultivation. To better understand the physiological responses of S. latissima under different stress conditions, large-scale transcriptomic analyses are useful to explore global metabolic pathway regulations. In addition, real-time quantitative polymerase chain reaction (RT-qPCR) is a powerful and rapid method for further quantifying changes in gene expression, and for targeting specific defense-related gene pathways. However, its level of accuracy is highly related to the expression stability of reference genes used for normalization and those still need to be evaluated in S. latissima . In this study, we therefore experimentally tested eight candidate reference genes identified from in silico screening of public transcriptomic datasets of S. latissima from different abiotic and biotic stress treatments. The stability analysis using complementary statistical approaches showed that EIF5B and ATPase are the most stable reference genes under biotic stress, whereas, under temperature and light stress, their combination with NDH gene is the best choice for RT-qPCR normalization. The validated reference genes were used to monitor the expression of target genes, related to oxidative responses, such as those involved in oxylipin pathways, in S. latissima plantlets submitted to different stress in laboratory-controlled conditions.

Keywords: expression; saccharina latissima; stress; reference genes

Journal Title: Journal of Applied Phycology
Year Published: 2020

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