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.
Highlights
The brown alga Saccharina latissima, known as the sugar kelp, is a seaweed of great ecological and economic values (Bartsch et al 2008; Lüning and Mortensen 2015)
A total of 23,049 unigenes from S. latissima was analyzed based on RNA-seq and microarray datasets: the dispersion measure (DPM) was calculated to evaluate their expression variability according to different experimental conditions, using PaGeFinder
Eight candidate genes with low expression variance were screened using large transcriptomic datasets generated in the kelp S. latissima under biotic and abiotic stress conditions
Summary
The brown alga Saccharina latissima, known as the sugar kelp, is a seaweed of great ecological and economic values (Bartsch et al 2008; Lüning and Mortensen 2015). In the Northern hemisphere, the underwater forests formed by S. latissima and other kelp species provide habitats and food and play a significant role in the primary production of the coastal area. The cultivation of S. latissima is becoming an important research field in applied phycology, this species being the closest European relative to S. japonica, a
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