Trascriptome meta-analysis of microalga Dunaliella tertiolecta under stress condition

Microalgae are photosynthetic organisms, which are considered as a potential source for sustainable metabolite production. Furthermore, stress conditions can affect metabolite production. In this study, a meta-analysis of RNA-seq experiments was performed to evaluate the response of metabolite biosynthesis pathways in Dunaliella tertiolecta to abiotic stress conditions, including high light, nitrogen deficiency, and high salinity. The results indicated down-regulation of light reaction, photorespiration, tetrapyrrole, and lipid-related pathways in salt stress. In comparison to salt stress, nitrogen deficiency mostly induced light reaction and photorespiration metabolisms. The up-regulation of phosphoenolpyruvate carboxylase, phosphoglucose isomerase, bisphosphoglycerate mutase, and glucose-6-phosphate-1-dehydrogenase (involved in central carbon metabolism) was observed under salt, high light, and nitrogen stress conditions. Interestingly, the results indicated that the meta-genes (i.e., modules of genes strongly correlated) tended to be located in a hub of stress-specific PPI (Protein-Protein Interaction) networks. Module enrichment of meta-genes PPI networks highlighted the cross talk between photosynthesis, fatty acids, starch, and sucrose metabolism under multiple stress conditions. Moreover, it was observed that the coordinated expression of the tetrapyrrole intermediated with meta-genes involved in starch biosynthesis. The results of the present study also showed that some pathways such as vitamin B6 metabolism, methane metabolism, ribosome biogenesis, and folate biosynthesis responded to different stress factors specifically. In conclusion, the results of this study revealed the main pathways underlying the abiotic stress responses for optimized metabolite production by the microalga Dunaliella in future studies. PRISMA check list was also included in the study.


Introduction
Photosynthetic microalgae have been considered as a potential source of secondary metabolites 45 and proposed as a promising cell factory since they have efficient photosynthesis apparatus and 46 biomass production (Spolaore et al. 2006, Del Campo et al. 2007). Environmental stress 47 conditions can redirect microalga energy flux towards the production and accumulation of fatty 48 acids, starch, and carotenoids (Dellomonaco et al. 2010). This feature is exploited to produce 49 biofuels, pigments, and starch; however, it can reduce metabolite production as well. The growth   Transcriptome meta-analysis is the most promising strategies to overcome the abovementioned 88 challenges (Zhang et al. 2020). It is an efficient tool for the identification of fundamental and 89 principal genes/pathways and often forms the basis for novel hypotheses (Zhang et al. 2018). For 90 RNA-seq meta-analysis, the p-value combination technique is proposed based on the inverse 91 normalization and Fisher's methods (Rau A. et al. 2014a). This approach has been successfully 92 applied to gain insight into crop responses to environmental stresses (Rest et al. 2016). More  The microalga Dunaliella is frequently considered for industrial applications because of 96 its potential to produce high value compounds such as beta-carotene, its high growth rate,   Table 1. Processing RNA-Seq data 112 Raw FASTQ files of the above-mentioned datasets were quality controlled using FastQC 113 software version 0.11.5. In this step, reads with quality score below 30 were excluded.  where, denotes the one-side P -value obtained from gene in the experiment under the null 146 hypothesis indicating no effect in each study. The Benjamini-Hochberg method (Benjamini and 147 Hochberg 1995) was used to correct for multiple testing. Genes with the adjusted meta P-value 148 ≤0.05 were considered to be statistically significant.  Table S1). Despite down-regulation of the genes directly involved in the Triacylglycerol (TAG) 177 and Fatty acid (FA) synthesis, up-regulation of glycolytic-related transcripts such as pyruvate 178 kinase and pyruvate dehydrogenase are observed ( Fig. 1 and Supplementary table S1).

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The findings also demonstrated that nitrogen deficiency down-regulated the ACP, whilst     Table S2).

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Interestingly, the results indicate that the key meta-analysis genes tend to be located in a 245 hub situation of the stress-specific PPI networks (indicated by a circle, Fig. 4). Surprisingly, 246 some of these hubs such as serine hydroxyl methyltransferase (SHMT1) and PSBO are the key 247 regulators of CCM pathways (Fang et al. 2017). Not unexpectedly, it the overproduction of 248 storage metabolites seems to be interconnected with defense-related pathways. It is also reported 249 that the functions of SHMT1 influence resistance to different stress, and the mutation of SHMT1  Table S2). It has been proposed that the STA1 mutants significantly reduce 253 granular starch deposition (Wattebled et al. 2003).

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The module enrichment of the PPI networks also highlighted the cross talk between 255 photosynthesis, fatty acids, starch, and sucrose metabolism under multiple stress conditions (Fig.   256   4). The KEGG enrichment of the identified meta-genes under the above-mentioned stress 257 conditions suggested that tetrapyrrole biosynthesis was a key stress responsive pathway in D.

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The meta-genes of the three abiotic stresses were also enriched in photosynthesis processes.  The findings also indicated that ribosome biogenesis specifically enriched under salt 305 stress (Fig. 4). Among protein synthesis apparatus involved genes in D. tertiolecta, nine large  Table S2).    Table 1 . Raw data set ID, run accession and read count (before and after trimming).