Integration of Cross Species RNA-seq Meta-Analysis and Machine-Learning Models Identifies the Most Important Salt Stress–Responsive Pathways in Microalga Dunaliella

Abstract

Photosynthetic microalgae are potentially yielding sources of different high-value secondary metabolites. Salinity is a complex stress that influences various metaboliterelated pathways in microalgae. To obtain a clear view of the underlying metabolic pathways and resolve contradictory information concerning the transcriptional regulation of Dunaliella species in salt stress conditions, RNA-seq meta-analysis along with systems levels analysis was conducted. A p-value combination technique with Fisher method was used for cross species meta-analysis on the transcriptomes of two Dunaliella salina and Dunaliella tertiolecta species. The potential functional impacts of core meta-genes were surveyed based on gene ontology and network analysis. In the current study, the integration of supervised machine-learning algorithms with RNA-seq meta-analysis was performed. The analysis shows that the lipid and nitrogen metabolism, structural proteins of photosynthesis apparatus, chaperone-mediated autophagy, and ROS-related genes are the keys and core elements of the Dunaliella salt stress response system. Cross-talk between Ca 2+ signal transduction, lipid accumulation, and ROS signaling network in salt stress conditions are also proposed. Our novel approach opens new avenues for better understanding of microalgae stress response mechanisms and for selection of candidate gene targets for metabolite production in microalgae.

Systems biology approach identifies functional modules and regulatory hubs related to secondary metabolites accumulation after transition from autotrophic to heterotrophic growth condition in microalgae

“…Contribution of tetrahydrofolate in cellular one-carbon (C1) pathways and ROS generation at stress condition has been reported previously [51]. Moreover, prior study have proved that SHMT1 switch nitrogen and carbon metabolism to secondary metabolite biosynthesis [11], validating the results of current study. An earlier study also showed that the overexpression of the SHMT1 increases biomass production [52].…”

“…In agree with our findings, it has been reported that inactivation of the LACS6 and LACS7 lipid breakdown [58] Another interesting gene that shows a large difference between connectivity in PR versus LG and TR brown module is LCE (Lycopene epsilon cyclase) which is involved in the carotenoids biosynthesis. Transcriptional variation of LCE during the lutein and beta-carotene accumulation circumstances has been reported [11] [4]; however, the changes in the connectivity pattern have not shown up yet, highlighting the efficiency of our integrative approach.…”

“…To reduce the batch effects between the two datasets, the empirical Bayes algorithm was applied [22]. Then, common genes between two datasets were selected based on the transcriptome meta-analysis according to the prescribed in previous studies [11]. Finally, identified meta-genes subjected to additional analysis (Fig 1).…”

“…With the development of high-throughput transcriptome sequencing technologies, the genes involved in the metabolite biosynthesis in microalgae have been identified [11].…”

Weighted gene co-expression network analysis of the salt-responsive transcriptomes reveals novel hub genes in green halophytic microalgae Dunaliella salina

“…Exploration of salt stress-responding mechanisms is an inevitable step in resolving these problems. The contribution of ROS and calcium signaling pathway in response to salinity condition has been reported previously 4 . Expressed sequence tag (EST) profiling of D. salina in hypersaline condition also identified 1401 unique responsive transcripts were contributed in protein synthesis, energy, primary metabolism, and protein fate 5 .…”