Saccharina japonica is one of the most important economic seaweeds. Several aspects such as photosynthesis in Saccharina lives are affected by blue light, the predominant light spectrum in the habitat. In this study, transcriptome profiling of S. japonica by next generation sequencing technology generated 55,102 qualified transcripts and 40.5 % transcripts were assigned to functional annotation. Expression of a large proportion of genes has been previously reported to be regulated by blue light, taking dark as control. However, by comparison among white, blue and red light, the significantly differentially expressed gene tags (DEGs) accounted for only 6.75 % of the identified sequences. It indicated that light-regulated gene expression in kelps is not a specific blue-light response. Unexpectedly, red light had more extensive effects on the transcriptomic activity than blue light did, since the most (68.4 %) DEGs were red light-regulated and only 17.5 % were specifically regulated by blue light. Some of the DEGs with the highest mRNA levels under blue light are not blue light-upregulated but red light-downregulated. The extensive regulation on gene expression under red light together with the abundant presence of phytochrome-like protein gene tags in S. japonica indicated their significant roles in the lives of brown algae. By highlighting the photosynthetic metabolism, blue light is more efficient than red light in triggering the pigment biosynthesis, light reaction and carbon fixation, revealing a molecular basis for rapid growth of kelps, since most of the time blue light is predominant in their habitat.

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As a temperate-cold species, Saccharina japonica often suffers heat stress when it is transplanted to temperate and subtropical zones. Study the heat stress response and resistance mechanism of Saccharina is of great significance for understanding the acclimation to heat stress under domestication as well as for breeding new cultivars with heat stress resistance. In this study, we identified a set of heat stress-responsive miRNAs and analysed their regulation during the heat stress response. CO (control) and heat stress (HS) sRNA libraries were constructed and sequenced. Forty-nine known miRNAs and 75 novel miRNAs were identified, of which seven known and 25 novel miRNAs were expressed differentially under heat stress. Quantitative PCR of six selected miRNAs confirmed that these loci were responsive to heat stress. Thirty-nine and 712 genes were predicted to be targeted by the seven known miRNAs and 25 novel miRNAs, respectively. Gene function and pathway analyses showed that these genes probably play important roles in S. japonica heat stress tolerance. The miRNAs identified represent the first set of heat-responsive miRNAs identified from S. japonica, and their identification can help elucidate the heat stress response and resistance mechanisms in S. japonica.

Background Caulerpa lentillifera is one of the most important economic green macroalgae in the world. Increasing demand for consumption has led to the commercial cultivation of C. lentillifera in Japan and Vietnam in recent decades. Concomitant with the increase of C. lentillifera cultivation is a rise in disease. We hypothesise that epiphytes or other microorganisms outbreak at the C. lentillifera farm may be an important factor contributing to disease in C. lentillifera. The main aims are obtaining differences in the microbial community structure and diversity between healthy and diseased C. lentillifera and key epiphytes and other microorganisms affecting the differences through the results of high-throughput sequencing and bioinformatics analysis in the present study. Results A total of 14,050, 2479, and 941 operational taxonomic units (OTUs) were obtained from all samples using 16S rDNA, 18S rDNA, and internal transcribed spacer (ITS) high-throughput sequencing, respectively. 16S rDNA sequencing and 18S rDNA sequencing showed that microbial community diversity was higher in diseased C. lentillifera than in healthy C. lentillifera. Both PCoA results and UPGMA results indicated that the healthy and diseased algae samples have characteristically different microbial communities. The predominant prokaryotic phyla were Proteobacteria, Planctomycetes, Bacteroidetes, Cyanobacteria, Acidobacteria, Acidobacteria and Parcubacteria in all sequences. Chlorophyta was the most abundant eukaryotic phylum followed by Bacillariophyta based on 18S rDNA sequencing. Ascomycota was the dominant fungal phylum detected in healthy C. lentillifera based on ITS sequencing, whereas fungi was rare in diseased C. lentillifera, suggesting that Ascomycota was probably fungal endosymbiont in healthy C. lentillifera. There was a significantly higher abundance of Bacteroidetes, Cyanobacteria, Bacillariophyta, Ulvales and Tetraselmis in diseased C. lentillifera than in healthy C. lentillifera. Disease outbreaks significantly change carbohydrate metabolism, environmental information processing and genetic information processing of prokaryotic communities in C. lentillifera through predicted functional analyses using the Tax4Fun tool. Conclusions Bacteroidetes, Cyanobacteria, Bacillariophyta, Ulvales and Tetraselmis outbreak at the C. lentillifera farm sites was an important factor contributing to disease in C. lentillifera.