Physiological and transcriptomic analyses reveal the effects of phytohormones on growth and astaxanthin accumulation in Haematococcus pluvialis

Physiological and transcriptomic analyses reveal the effects of phytohormones on growth and astaxanthin accumulation in Haematococcus pluvialis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Physiological and transcriptomic analyses reveal the effects of phytohormones on growth and astaxanthin accumulation in Haematococcus pluvialis Yang Sun, Yun Li, Jing Zhang, Rui Zhao, Jiaji Zhang, Mingxin Guo, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8198834/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 14 Mar, 2026 Read the published version in BMC Plant Biology → Version 1 posted 10 You are reading this latest preprint version Abstract Background Haematococcus pluvialis is recognized as the richest natural source of astaxanthin, a high-value ketocarotenoid with potent antioxidant properties. Commercial production typically relies on a two-stage cultivation strategy, comprising a green vegetative phase for biomass accumulation and a red inductive phase for astaxanthin synthesis. However, a major bottleneck in this process is the balance between cell growth and pigment accumulation, as the stress conditions required for astaxanthin synthesis often inhibit biomass productivity. Phytohormones are critical signaling molecules that regulate growth and metabolism in photosynthetic organisms. Exploring their potential to decouple these conflicting physiological processes is crucial for optimizing industrial astaxanthin production. Results In this study, physiological and transcriptomic analyses were performed to evaluate the effects of five phytohormones (IAA, ABA, MeJA, ZT, and IPR) on H. pluvialis during its two-stage cultivation. Physiological data indicated distinct hormonal requirements for each stage: 0.01 mg L⁻¹ IAA significantly enhanced biomass in the green stage (0.37 g L⁻¹ vs. 0.29 g L⁻¹ in control), whereas 0.1 mg L⁻¹ MeJA maximized astaxanthin content in the red stage (29.22 mg g⁻¹ vs. 23.09 mg g⁻¹ in control). Transcriptomic profiling revealed that IAA promoted vegetative growth by upregulating genes involved in primary carbon metabolism ( PPDK ), cell cycle progression ( CDKB1-1 ), and nutrient uptake ( ZIP9 ). Conversely, MeJA treatment reprogrammed metabolism towards secondary biosynthesis by upregulating key ketolase genes ( CRTW and BKT3 ) while downregulating competing carotenoid pathway genes ( CRTZ and LCYE ) and photosynthesis-related transcripts. Conclusions This study elucidates the distinct molecular mechanisms by which phytohormones regulate the dichotomy between growth and secondary metabolism in H. pluvialis . The findings suggest that the targeted application of IAA to boost biomass and MeJA to induce pigmentation offers a practical hormone guided strategy to improve two-stage astaxanthin production and provides molecular targets for further optimization. Astaxanthin Biomass accumulation Haematococcus pluvialis Phytohormone Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1. Background Astaxanthin is a high-value red ketocarotenoid characterized by a unique chemical structure of thirteen conjugated double bonds [1]. This configuration provides potent antioxidant activity, effectively scavenging reactive oxygen species and free radicals with an antioxidant capacity up to 65-fold greater than vitamin C [2, 3]. Due to its powerful bioactivity, astaxanthin has been widely applied in many industries such as nutraceuticals, aquaculture, cosmetics, food, and animal feed [4]. The global astaxanthin market was valued at USD 1.63 billion in 2021 and is projected to reach USD 3.2 billion in 2026 [5]. Commercial astaxanthin products are classified into two main categories: synthetic and natural. Due to its lower production cost (approximately USD 1,000 per kg), synthetic astaxanthin holds the largest market share [6]. Chemically, synthetic astaxanthin exists primarily in a non-esterified form and is a racemic mixture of stereoisomers. In contrast, natural astaxanthin is highly esterified with fatty acids (95%) and consists almost exclusively of the (3S,3′S) stereoisomer [7, 8]. This specific stereochemical configuration is associated with superior antioxidant efficacy [9]. Despite its functional advantages, the global yield of natural astaxanthin remains low, and overcoming this production bottleneck is a major challenge [10]. Several microalgae are capable of synthesizing astaxanthin, with Haematococcus pluvialis being the richest known natural source [11]. Under environmental stress or adverse cultivation conditions, it can accumulate astaxanthin to 5% of its dry weight, a crucial self-protection mechanism against oxidative stress [11-13]. And this process is often coupled with transitions of life stages. The life stages of H. pluvialis can be divided into the green stage and the red stage [14]. Under favorable conditions, H. pluvialis predominantly exists as green vegetative cells characterized by vigorous cell growth and division [14, 15]. Upon exposure to adverse environmental conditions, green vegetative cells reduce division, thicken cell walls and accumulate large amounts of carotenoids which are primarily astaxanthin in cytoplasmic lipid droplets, resulting in transformation into the red stage [16, 17]. Consequently, the industrial production of astaxanthin from H. pluvialis typically employs a two-phase cultivation strategy. The green stage involves cultivation under suitable temperature, light and nutrient conditions to accumulate biomass. Once a sufficient biomass is reached, the red stage is initiated by applying stress such as high temperature, high light intensity, or nitrogen deprivation to induce astaxanthin accumulation [7, 18]. The production of astaxanthin inherently requires the application of stress conditions to induce its synthesis, which presents a delicate balance between astaxanthin accumulation and biomass growth [17, 19]. Therefore, identifying optimal stress levels or selecting appropriate inducers that maximize astaxanthin yield without compromising productivity is critical. Phytohormones are critical endogenous signaling molecules that regulate virtually all aspects of plant growth, development, and responses to environmental stimuli [20, 21]. The roles of phytohormones have been extensively studied in higher plants, and increasing evidence indicates that these hormones also play significant roles in the physiology and metabolism of microalgae [22]. Indeed, numerous studies have demonstrated their positive effects on enhancing microalgal productivity. Abscisic acid (ABA) stimulates the activity of carbon metabolism-related enzymes, promoting lipid accumulation in Chlorella sp. [23]. Indole-3-acetic acid (IAA) was found to upregulate genes in the porphyrin metabolism pathway of Phaeodactylum tricornutum , leading to enhanced chlorophyll biosynthesis and thereby stimulated growth [24]. Zeatin (ZT) plays significant roles in the cell cycle, cell division and photosynthetic pigment synthesis of Nannochloropsis oculata [25]. Given the pronounced effects of phytohormones on microalgae, the application in cultivation of H. pluvialis offers substantial potential. Hu et al. [26] demonstrated that the combined application of salicylic acid (SA) and high-light stress increased astaxanthin content in H. pluvialis by 0.33 mg L⁻¹ at 48 h. Gao et al. [27] found that carotenoid-biosynthesis genes (e.g. , psy, pds , and zds ) involved in astaxanthin production were upregulated following treatment with either SA or jasmonic acid (JA). However, previous studies have typically investigated only a limited range of hormones and have lacked comprehensive studies on the green stage. The present study aimed to investigate the effects of five plant hormones including IAA, ABA, ZT, methyl jasmonate (MeJA) and N 6 -(Δ 2 -Isopentenyl) adenosine (IPR) on the biomass and physiological composition (chlorophyll, astaxanthin, carbohydrates and proteins) of H. pluvialis . Transcriptomic analysis was performed on H. pluvialis from treatment groups that showed significant increases in biomass and astaxanthin accumulation, which will provide a molecular level understanding of phytohormone mediated regulatory networks governing growth and astaxanthin biosynthesis. The findings of this research are expected to facilitate the optimized application of phytohormones in H. pluvialis cultivation for the enhanced production of high-value bioproducts. 2. Materials and methods 2.1 Microalgae strain and phytohormones The H. pluvialis strain was purchased from Shanghai Guangyu Biological Technology Co., Ltd. (Shanghai, China). The strain is maintained in the Microalgae Culture Collection at the Laboratory of Applied Microalgal Biology, Ocean University of China, under the internal accession number LAMB284. Five phytohormones were obtained from MACKLIN, China: IAA (≥ 98%), ABA (≥ 98%), MeJA (≥ 98%), ZT (≥ 99%), IPR (≥ 98.5%). 2.2 Algal culture and phytohormonal additions H. pluvialis of green stage was cultivated in 300 mL Erlenmeyer flasks containing 200 mL of BG11 medium [ 28 ] under a light intensity of 30 µmol m − ² s − 1 with a 14h/10h light-dark cycle at 22 ± 1 ℃ and 7.1 ± 0.1 pH. The initial inoculation density was 1×10 4 cells mL − 1 . The phytohormones used were IAA, ABA, IPR, and ZT. Phytohormones were first prepared as concentrated stocks (1 g L⁻¹) using sterile water (with a minimal amount of ethanol when needed for solubility), stored at 4°C and used within 7 days. Before application, stocks were diluted with culture medium to the working concentrations of 0.001, 0.01, 0.1, and 1 mg L⁻¹. Controls received the same volume of sterile water (or solvent at the matching final v/v when ethanol was used). Cultivation lasted 15 days, with samples collected every 3 days for dry weight determination and samples from day 9 were taken for physiological measurement. H. pluvialis of red stage was obtained as follows: after 15 days cultivation under the same conditions above without phytohormone supplementation, the light intensity was increased to 100 µmol m − ² s − 1 and four phytohormones (IAA, ABA, MeJA, and ZT) were added to medium. Cultivation was continued for another 15 days, with samples collected every 3 days to measure astaxanthin and samples from day 24 were analyzed for physiological data. All days are counted from the initial inoculation. The choice of IPR for the green stage and MeJA for the red stage was based on our prior measurement of endogenous phytohormones in H. pluvialis . Endogenous IPR was abundant in the green stage and decreased in the red stage, whereas endogenous MeJA increased during the red stage [ 29 ]. For each phytohormone concentration, 3 independent biological replicates were used. 2.3 Physiological analysis 2.3.1 Measurement of dry weight First, 20 mL of algal culture at the green stage was concentrated at 2000 g for 10 minutes to discard the supernatant. The pellets were washed twice with distilled water, then dried at 60 ℃ for 24 h. Finally, the dried samples were weighed to determine the dry weight. 2.3.2 Determination of total chlorophyll content Total chlorophyll was extracted using ethanol and measured using a spectrophotometer, following the method described by Rowan [ 30 ]. Briefly, 10 mL of algal culture was centrifuged at 2000 × g for 10 min to collect the cell pellet. The pellet was resuspended in 10 mL of 95% ethanol and incubated in darkness for 24 h. Absorbance of the extract was measured at 665 and 649 nm, with chlorophyll content calculated using the following formula: C Chl a (mg L − 1 ) = 13.70A 665 – 5.76A 649 C Chl b (mg L − 1 ) = 25.8 A 649 –7.60A 665 C Total Chl (mg L − 1 ) = C Chl a + C Chl b 2.3.3 Measurement of astaxanthin The method of astaxanthin measurement referred to Zhang et al [ 31 ]. Briefly, 5 mL of culture were centrifuged at 2000 g for 10 min and the supernatant discarded. Pellets were resuspended in 3 mL dimethyl sulfoxide and heated at 80°C for 10 min. Samples were centrifuged at 2000 g for 10 min and the supernatant transferred to a clean tube. Extraction was repeated until pellets turned white. The pooled supernatant absorbance was measured at 530 nm on a UH5300 spectrophotometer (Hitachi, Japan). Astaxanthin standard (purity ≥ 98%, Solarbio, China) was used for quantification. 2.3.4 Measurement of carbohydrate The total carbohydrate content of H. pluvialis was determined using the anthrone method [ 32 ]. A 2 mL of algal suspension was centrifuged at 2000 g for 10 min. The pellet was reacted with 8 mL of anthrone solution, which was prepared by mixing 0.2 g anthrone, 8 mL absolute ethanol, and 100 mL concentrated sulfuric acid (98%). The mixture was heated at 90 ℃ for 10 min. After cooling, the absorbance was measured at 620 nm. A standard curve was constructed by glucose standards. 2.3.5 Measurement of protein The protein content of H. pluvialis was quantified using the Coomassie Brilliant Blue G‑250 colorimetric assay [ 33 ]. 5 mL of algal suspension was centrifuged (2000 g, 10 min), and cell pellet was resuspended in 200 µL of 1 M NaOH before incubation at 80 ℃ for 10 min. After the addition of 800 µL of distilled water, samples were centrifuged at 3000 g for 30 min. The supernatants were collected and the process was repeated twice. All supernatants were pooled and diluted to a volume of 5 mL. 2 mL of the extract were mixed with 5 mL of Coomassie Brilliant Blue G-250 solution (1 mg mL⁻¹) and incubated at room temperature for 15 minutes. 200 µL aliquot was added to a 96-well microplate, and absorbance was measured at 595 nm using a microplate reader (Synergy™ Mx, BioTek, USA). Bovine serum albumin was used to generate the standard curve. 2.3.6 Statistical analysis All physiological composition data were presented as mean ± SD (n = 3). Group differences were assessed by one-way ANOVA followed by Tukey’s HSD for multiple comparisons ( p < 0.05). All statistical analyses were performed using SPSS 26.0 and Graphpad Prism (v9.5). 2.4 Transcriptome analysis 2.4.1 RNA extraction, library preparation and sequencing Total RNA was extracted from H. pluvialis in the control group, the biomass optimized group and the astaxanthin optimized group using RNAprep Pure Plant Kit (TIANGEN, China). RNA integrity and quality were assessed with an Agilent 2100 Bioanalyzer. mRNA was isolated from the total RNA using oligo (dT) magnetic beads and subsequently fragmented into smaller strands. cDNA synthesis was conducted in two steps: first-strand cDNA synthesis using random hexamer primers, followed by second-strand synthesis. Library preparation involved sequential steps of end repair, A-tailing, adapter ligation, size selection, PCR amplification, and purification. The resulting libraries were pooled based on effective concentration and target sequencing depth. DNA nanoballs were generated through rolling-circle replication after 5′-phosphorylation and circularization. Sequencing was carried out on the DNBSEQ-T7 platform (MGI Tech Co., Ltd., China). All sequence data were 2 × 75 bp in length. Raw sequencing data have been deposited in the NCBI Sequence Read Archive (SRA) database under accession number PRJNA1279618. 2.4.2 Bioinformatics Analysis Raw sequencing reads were pre-processed to remove low-quality reads, adapter sequences, and poly-N sequences using fastp. Clean reads were then mapped to the H. pluvialis reference genome (NCBI RefSeq: GCA_030144725.1) using HISAT2 v2.2.1. Gene expression levels were quantified as FPKM (Fragments Per Kilobase of transcript per Million mapped reads) using StringTie v2.2.1. Differential expression analysis was performed using DESeq2 v1.42.0 to identify genes significantly altered in the hormone treated groups compared to the control. Genes with a |log 2 FoldChange| ≥ 1 and an adjusted pvalue < 0.05 were considered differentially expressed. Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of differentially expressed genes were conducted using clusterProfiler R package (v4.8.1) to identify over-represented biological processes, molecular functions, cellular components, and metabolic pathways. 2.4.3 Functional annotation Putative gene functions were assigned by BLAST based searches. Protein sequences were queried against the Swiss-Prot database, and Gene Ontology terms were transferred from the best Swiss-Prot match where available. KEGG Orthology identifiers were assigned using the KEGG database and were used for pathway mapping. 2.5 Validation of RNA-seq data by qRT-PCR To validate the RNA-seq results, quantitative real-time PCR (qPCR) was performed on H. pluvialis samples collected from the green and red stages. For the green stage, cells from the control group and the 0.01 mg L⁻¹ IAA-treated group were analyzed; for the red stage, cells from the control group and the 0.1 mg L⁻¹ MeJA-treated group were analyzed. Total RNA was extracted using the Servicebio MF168 RNA extraction kit following the manufacturer’s instructions. RNA concentration and purity were assessed with a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific), and samples with acceptable A260/280 ratios (1.8–2.2) were used for reverse transcription. First-strand cDNA was synthesized from 1 µg of total RNA in a 20 µL reaction using the Vazyme HiScript III 1st Strand cDNA Synthesis Kit with gDNA wiper. The reverse transcription program was 37°C for 15 min followed by 85°C for 5 s. QPCR was carried out using Vazyme Taq Pro Universal SYBR qPCR Master Mix on a BIO-RAD CFX95 Real-Time PCR System (C1000 Touch Thermal Cycler), and fluorescence data were collected with CFX Manager 3.1. Each 20 µL qPCR reaction contained 10 µL SYBR master mix, 0.4 µL of each primer (10 µM), and 2 µL of diluted cDNA (equivalent to 20 ng total RNA), with nuclease-free water added to volume. The thermal cycling conditions were 95°C for 30 s, followed by 40 cycles of 95°C for 10 s and 60°C for 30 s. Following the cycling protocol, a melting curve analysis was performed from 65°C to 95°C to verify the specificity of the PCR products. Primer pairs were designed using NCBI Primer-BLAST, and primer sequences and amplicon sizes are listed in Supplementary File 1 (Table S1 ). Expression levels were normalized to the reference gene gene_QJQ45_016574 and gene_QJQ45_003696 , and relative transcript abundance was calculated using the 2^−ΔΔCt method. Three biological replicates were analyzed for each condition, with three technical replicates per sample. No-template controls (NTC) and no-RT controls were included in each run to ensure specificity and exclude contamination. 3. Results 3.1 Biomass and astaxanthin content under phytohormone treatments The effects of different phytohormone treatments on biomass accumulation during the green stage of H. pluvialis are shown in Fig. 1 A–D. All groups exhibited slow growth during the initial 3 days, then entering an exponential phase. By day 15, the biomass of the green stage control (GCon) reached 0.29 g L⁻¹. Among all treatments, 0.01 mg L⁻¹ IAA resulted in the highest biomass yield, with biomass attaining 0.37 g L⁻¹ at day 15. In addition to IAA, 0.001 and 0.01 mg L-1 concentrations of ABA, ZT, and IPR also promoted growth to varying extents, whereas higher concentrations of these hormones inhibited H. pluvialis growth. Astaxanthin accumulation during the red stage is presented in Fig. 1 E–H. The accumulation rate peaked between days 3 and 6 and declined thereafter. On day 15, the astaxanthin content of the red stage control (RCon) was 23.09 mg g⁻¹. Treatment with 0.1 mg L⁻¹ MeJA yielded the highest astaxanthin accumulation of 29.22 mg g⁻¹. Other phytohormones also promoted astaxanthin synthesis to lesser degrees. However, phytohormone treatments at 1 mg L⁻¹ markedly inhibited astaxanthin accumulation. 3.2 Effects of phytohormones on physiological parameters Physiological parameters under phytohormone treatments during the green stage are summarized in Table 1 . Exogenous ABA, ZT, and IPR at low concentrations (0.001 and 0.01 mg L⁻¹) significantly enhanced carbohydrate content, with 0.01 mg L⁻¹ ABA producing the greatest increase. In contrast, higher phytohormone concentrations generally inhibited carbohydrate accumulation. Protein content likewise increased under low to moderate phytohormone levels but declined markedly at 1 mg L⁻¹, reaching a minimum of 27.03 ± 2.22 mg g⁻¹. Table 1 Effects of phytohormone treatments on physiological and biochemical measurements of green stage of H. pluvialis Measurements Algal samples Carbohydrate Protein Chlorophyll GCon 40.42 ± 1.18 38.07 ± 3.23 10.53 ± 1.05 ABA_0.001 57.46 ± 1.56 ** 49.2 ± 1.39 ** 11.51 ± 0.88 ABA_0.01 82.27 ± 1.77 ** 43.88 ± 0.98 11.50 ± 1.56 ABA_0.1 25.39 ± 0.62 ** 31.71 ± 1.25 5.36 ± 0.52 ** ABA_1 15.65 ± 0.80 ** 27.03 ± 2.22 ** 2.49 ± 0.23 ** IAA_0.001 36.22 ± 1.59 * 48.32 ± 0.9 ** 11.80 ± 0.81 IAA_0.01 35.97 ± 1.41 * 49.11 ± 4.07 ** 14.20 ± 1.31 ** IAA_0.1 32.08 ± 0.59 ** 45.58 ± 2.75 11.19 ± 1.01 IAA_1 14.57 ± 0.76 ** 33.81 ± 0.79 4.41 ± 0.40 ** ZT_0.001 53.03 ± 1.42 ** 36.5 ± 3.32 11.48 ± 1.03 ZT_0.01 47.58 ± 3.34 ** 51.13 ± 2.09 ** 12.76 ± 1.23 * ZT_0.1 35.73 ± 1.00 * 50.32 ± 1.73 ** 5.23 ± 0.70 ** ZT_1 18.48 ± 0.73 ** 46.51 ± 4.67 * 2.94 ± 0.33 ** IPR_0.001 47.47 ± 2.34 ** 43.44 ± 1.95 11.12 ± 1.49 IPR_0.01 81.51 ± 0.75 ** 35.66 ± 2.6 12.82 ± 1.00 * IPR_0.1 39.53 ± 0.62 45.66 ± 2.73 5.63 ± 0.62 ** IPR_1 21.73 ± 0.78 ** 48.67 ± 3.45 ** 2.84 ± 0.30 ** Data are given as means ± SD, n = 3. Unit is mg g − 1 . * P < 0.05, ** P < 0.01 compared to the control group. The numbers following phytohormone names represent treatment concentrations (mg L⁻¹). Physiological responses during the red stage are presented in Table 2 . Carbohydrate content was elevated in almost all groups during the red stage. The treatment group with ZT at 0.1 mg L⁻¹ achieved the highest level (159.92 ± 5.84 mg g⁻¹). Compared with the control, the treatments of 0.001 mg L⁻¹ MeJA, 0.1 mg L⁻¹ ZT, and 0.1 mg L⁻¹ IAA resulted in a significant decrease in protein content, with the lowest level observed under 0.1 mg L⁻¹ IAA (10.05 ± 0.67 mg g⁻¹). Conversely, significant increases were observed under the treatments of 0.01 mg L⁻¹ ZT, 1 mg L⁻¹ ABA, 1 mg L⁻¹ ZT, and 1 mg L⁻¹ IAA, with 0.01 mg L⁻¹ ZT showing the highest protein content (25.46 ± 1.73 mg g⁻¹). Table 2 Effects of phytohormone treatments on physiological and biochemical measurements of red stage of H. pluvialis . Measurements Algal samples Carbohydrate Protein Chlorophyll RCon 95.00 ± 4.62 15.96 ± 0.48 1.64 ± 0.10 MeJA_0.001 136.97 ± 5.65 ** 11.04 ± 0.51 ** 1.35 ± 0.08 MeJA_0.01 115.15 ± 6.48 * 13.32 ± 0.06 1.18 ± 0.10 ** MeJA_0.1 142.40 ± 8.46 ** 15.96 ± 0.43 0.95 ± 0.08 ** MeJA_1 89.21 ± 3.92 17.92 ± 1.18 0.37 ± 0.03 ** ABA_0.001 122.73 ± 4.80 ** 19.02 ± 0.23 1.79 ± 0.13 ABA_0.01 120.51 ± 7.70 ** 18.11 ± 0.43 2.21 ± 0.14 ** ABA_0.1 117.25 ± 6.23 ** 17.37 ± 1.17 1.20 ± 0.09 ** ABA_1 95.92 ± 6.26 22.4 ± 1.68 ** 0.55 ± 0.04 ** ZT_0.001 88.70 ± 6.01 16.13 ± 0.79 1.48 ± 0.11 ZT_0.01 121.53 ± 5.78 ** 25.46 ± 1.73 ** 2.08 ± 0.19 ** ZT_0.1 159.92 ± 5.84 ** 11.4 ± 0.37 ** 1.31 ± 0.09 * ZT_1 51.94 ± 3.04 ** 22 ± 0.53 ** 0.78 ± 0.03 ** IAA_0.001 108.04 ± 7.22 14.8 ± 1.2 1.78 ± 0.07 IAA_0.01 108.29 ± 6.96 17.96 ± 1.22 2.83 ± 0.16 ** IAA_0.1 146.68 ± 7.30 ** 10.05 ± 0.67 ** 1.99 ± 0.10 * IAA_1 65.59 ± 4.21 ** 22.09 ± 0.38 ** 1.01 ± 0.08 ** Data are given as means ± SD, n = 3. Unit is mg g − 1 . * P < 0.05, ** P < 0.01 compared to the control group. The numbers following phytohormone names represent treatment concentrations (mg L⁻¹). 3.3 Overview of transcriptome sequencing data To deeply explore the molecular regulatory mechanisms of phytohormones on H. pluvialis growth and astaxanthin accumulation, we conducted transcriptome sequencing analysis on the groups with the highest biomass accumulation (0.01 mg L⁻¹ IAA), the highest astaxanthin accumulation (0.1 mg L⁻¹ MeJA), and their respective controls (GCon and RCon). Strict quality control was performed on the raw sequencing data of all samples. As shown in Table 3 , all samples had sufficient sequencing data, with an average of 40-50M reads/sample. After quality filtering, 39-48M clean reads/sample were retained, meeting expectations. In terms of base quality, the Q30 percentage of all samples was above 96%, and the GC content was stable (58.73–60.54%). The mapping rate of reads aligned to the H. pluvialis reference genome ranged from 64.11% to 76.51%, consistent with mapping rates reported for this species using genome based alignment (≈ 63.3% on average), and the high read quality together with the known highly repetitive genome indicates that such rates are expected for H. pluvialis [ 34 ]. In the GCon, IAA treated groups, RCon, and MeJA treated groups, 34625, 34430, 34270, and 35267 expressed genes were identified, respectively. The FPKM for each sample group is shown in Supplementary File 1: Figure S1 . The results indicate that 25% of the expressed genes were in the 0-0.5 FPKM range, 35% were in the 0.5-5 FPKM range, 35% were in the 5-100 FPKM range, and 3% of genes had FPKM values exceeding 100. Functional annotation assigned 10,021 genes to GO categories, 499 to KEGG pathways, 498 to KEGG Orthology identifiers, and 6,650 to protein interaction entries. Table 3 RNA sequencing results Algal Samples Raw reads Clean reads Error rate (%) Q30 (%) GC content (%) Mapping rate (%) GCon_1 43009230 41841168 0.02 96.66 59.42 72.31 GCon_2 42935178 41838162 0.02 96.64 59.11 76.51 GCon_3 46886006 45483570 0.02 96.62 59.26 71.84 IAA_1 46519838 45163956 0.02 96.49 58.73 65.44 IAA_2 43069706 41577938 0.02 96.76 58.97 66.52 IAA_3 47104636 45607276 0.02 96.63 58.96 68.53 RCon_1 47533786 46393270 0.02 96.65 60.54 67.61 RCon_2 46725614 45734276 0.02 96.27 60.42 68.63 RCon_3 47131428 45941918 0.02 96.51 60.41 68.32 MeJA_1 49255422 47856734 0.02 96.55 60.08 64.11 MeJA_2 47068684 45484812 0.02 96.84 60.21 64.38 MeJA_3 40264948 38984278 0.02 96.4 59.99 68.67 GO classification of 10,021 genes emphasized categories that are most informative for growth and metabolism in H. pluvialis (Fig. 2 ). At the biological process level, annotations concentrated in protein and nucleic acid metabolism and biosynthetic and macromolecule modification processes. At the cellular component level, genes were mainly associated with the membrane and intracellular organelles including the cytoplasm, nucleus and ribosome. At the molecular function level, binding and catalytic activity dominated, with nucleotide or ATP binding and hydrolase and transferase activities also prominent. 3.4 qRT-PCR validation of RNA-seq data To experimentally validate the RNA-seq results, qRT-PCR was performed on a randomly selected subset of DEGs from both developmental stages. Six DEGs were chosen from the green stage and another six from the red stage, with the selection covering both up-regulated and down-regulated transcripts. As shown in Fig. 3 , the qRT-PCR results exhibited expression trends fully consistent with those obtained from the RNA-seq analysis in both stages. 3.5 Differential expression analysis Clustering analysis of differentially expressed genes (DEGs) showed that biological replicate samples from the same treatment group clustered together (Fig. 4 ), indicating good experimental reproducibility. More importantly, samples from different growth stages formed distinct clustering branches, with the GCon and IAA treated group clustering into one category, and the RCon and MeJA treated group clustering into another. To further identify differentially expressed genes induced by phytohormones, we used ∣log 2 FoldChange∣ ≥ 1 and padj < 0.05 as screening thresholds to construct volcano plots illustrating the overall distribution of DEGs between the GCon and IAA-treated groups, and the RCon and MeJA-treated groups (Fig. 5 ). As shown in Fig. 5 A, in the comparison between the IAA-treated group and the GCon, a total of 490 significantly differentially expressed genes were identified, of which 400 genes were upregulated and 90 genes were downregulated. In the comparison between the MeJA-treated group and the RCon (Fig. 5 B), a total of 3208 DEGs were identified, with 1927 genes significantly upregulated and 1281 genes downregulated. Since these genes required functional annotation, we annotated the differentially expressed genes in the Swiss-Prot database in section 3.5 to explore their potential biological functions. 3.6 Functional annotation and in-depth analysis of key DEGs 3.6.1 Key DEGs in response to IAA treatment Transcriptome analysis revealed significant changes in H. pluvialis gene expression after IAA treatment. A total of 163 annotated differentially expressed genes were obtained, of which 112 were upregulated and 51 were downregulated (Supplementary File 2, Sheet1). Key DEGs associated with growth are presented in Table 4 . Table 4 DEGs between IAA treated group and GCon group. Protein Gene_id Best-hit annotation (species) Ref symbol log 2 FoldChange pvalue Pyruvate phosphate dikinase novel.2670 pyruvate phosphate dikinase 1 (Oryza sativa) PPDK1 1.57 1.7E-26 Pyruvate phosphate dikinase novel.8652 pyruvate phosphate dikinase 1 (Arabidopsis thaliana) PPDK 1.49 6.3E-23 Pyruvate phosphate dikinase novel.2399 pyruvate phosphate dikinase 1 (Oryza sativa) PPDK1 1.49 3.6E-16 Pyruvate kinase gene_QJQ45_025570 pyruvate kinase, cytosolic 2 (Oryza sativa) PK 1.69 2.1E-4 Fructokinase gene_QJQ45_013744 fructokinase 2 (Oryza sativa) FRK2 1.12 1.3E-4 Zinc transporter 9 gene_QJQ45_017004 zinc transporter 9 (Oryza sativa) ZIP9 3.54 2E-65 Zinc transporter 9 gene_QJQ45_020772 zinc transporter 9 (Oryza sativa) ZIP9 1.43 1.5E-19 Cyclin-dependent kinase B1-1 gene_QJQ45_023291 cyclin-dependent kinase B1-1 (Oryza sativa) CDKB1-1 1.48 2.9E-4 Cyclin B2-1 gene_QJQ45_026341 cyclin B2-1 (Oryza sativa) CYCB2-1 1.56 4.5E-4 Three loci annotated as pyruvate phosphate dikinase ( PPDK ; novel.2670 , novel.8652 , novel.2399 ) were concordantly upregulated. In parallel, transcripts encoding pyruvate kinase ( PK ; gene_QJQ45_025570 ) and fructokinase ( FRK2 ; gene_QJQ45_013744 ) increased, indicating coordinated enhancement of flux at the PEP/pyruvate node. Two zinc transporter 9 loci ( ZIP9 ; gene_QJQ45_017004 and gene_QJQ45_020772 ) were strongly upregulated. Transcripts for CDKB1-1 ( gene_QJQ45_023291 ) and CYCB2-1 ( gene_QJQ45_026341 ) also increased. 3.6.2 Key DEGs in response to MeJA treatment DEGs in H. pluvialis after MeJA treatment were also annotated using Swiss-Prot, yielding a total of 1103 annotated differentially expressed genes. 596 were upregulated and 507 were downregulated (Supplementary File 2, Sheet2). Key DEGs associated with astaxanthin biosynthesis are presented in Table 5 . Table 5 DEGs between MeJA treated group and Rcon group. Proteins Gene_id Best-hit annotation (species) Ref symbol log 2 Foldchange pvalue β-carotene ketolase gene_QJQ45_019472 beta-carotene ketolase ( Haematococcus pluvialis ) CRTW 1.29 2.9E-130 β-carotene 4-ketolase 3 gene_QJQ45_024144 beta-carotene ketolase 3 ( Haematococcus pluvialis ) BKT3 1.62 4.1E-129 β-carotene 3-hydroxylase gene_QJQ45_001374 beta-carotene 3-hydroxylase ( Haematococcus pluvialis ) CRTZ -1.34 3.4E-12 β-carotene 3-hydroxylase gene_QJQ45_030451 beta-carotene 3-hydroxylase ( Haematococcus pluvialis ) CRTZ -1.18 5.3E-05 Lycopene epsilon cyclase gene_QJQ45_015099 lycopene epsilon cyclase ( Solanum lycopersicum ) LCYE -1.55 1.2E-72 Lycopene epsilon cyclase gene_QJQ45_027358 lycopene epsilon cyclase ( Solanum lycopersicum ) LCYE -1.42 6.8E-09 Two ketolase-encoding genes were significantly upregulated: CRTW ( gene_QJQ45_019472 ) and BKT3 ( gene_QJQ45_024144 ). Two loci annotated as β-carotene 3-hydroxylase ( CRTZ ; gene_QJQ45_001374 and gene_QJQ45_030451 ) were downregulated, and two lycopene ε-cyclase loci ( LCYE ; gene_QJQ45_015099 and gene_QJQ45_027358 ) likewise decreased. 3.7 Functional Enrichment Analysis To systematically elucidate the biological effects of IAA in the green phase and MeJA in the red phase on the H. pluvialis transcriptome, we performed KEGG pathway and GO enrichment analyses on the identified differentially expressed genes (DEGs). The enrichment analysis results are presented as bubble plots (Fig. 6 and Fig. 7 ). KEGG pathway enrichment results of IAA treated group are shown in Fig. 6 A, in which multiple pathways related to carbon and energy metabolism were significantly enriched, including pyruvate metabolism, carbon metabolism, and carbon fixation in photosynthetic organisms. Additionally, biosynthesis of secondary metabolites and fatty acid metabolism were also significantly enriched. GO functional enrichment results of IAA treated group are shown in Fig. 7 A. Within biological process, the most significantly enriched term was carbohydrate metabolic process. Additional enriched biological processes included monocarboxylic acid metabolism, lipid modification, organophosphate metabolism, and organic acid metabolism. For cellular component, significantly enriched terms comprised peroxisome and microbody. In terms of molecular function, various hydrolase activities and transporter activities were enriched. The KEGG pathway and GO enrichment analysis results for DEGs of MeJA treated H. pluvialis in the red phase (MeJA VS RCon) are shown in Fig. 6 B and 7 B, respectively. KEGG showed that metabolic pathways were the most significantly enriched pathways. Significantly enriched specific pathways included porphyrin metabolism, carbon fixation in photosynthetic organisms, carbon metabolism, and biosynthesis of secondary metabolites. Among these, biosynthesis of secondary metabolites, biosynthesis of cofactors and pentose phosphate pathway also showed enrichment. GO result showed in terms of biological process, carbohydrate metabolic process was still significantly enriched. Photosynthesis-related GO terms such as photosynthesis, chlorophyll biosynthetic process, and their related sub-processes were all significantly enriched, and most genes showed downregulation. Simultaneously, the enrichment of tetrapyrrole biosynthetic process corresponded to porphyrin metabolism in KEGG. In terms of cellular component, photosystem, photosynthetic membrane, and thylakoid, all related to photosynthesis, were significantly enriched, and genes in these components were generally downregulated. Additionally, ATP synthase complex, plastid, and chloroplast membrane components also showed enrichment. In terms of molecular function, iron binding was significantly enriched. Notably, monooxygenase activity was also significantly enriched. 4. Discussion 4.1 Interpreting biomass and astaxanthin outcomes As a key regulator of cell division, differentiation, and proliferation, IAA has been shown to enhance microalgal growth. For example, Salama et al. [ 35 ] reported a 1.9-fold increase in Scenedesmus obliquus cell density under 10⁻⁵ M IAA. Such biphasic dose responses to phytohormones in microalgae have been widely documented [ 36 – 38 ]. Similarly, Khalili et al. [ 39 ] demonstrated that 32 µM MeJA significantly enhanced astaxanthin accumulation in Chlorella sorokiniana . Chen et al. [ 40 ] also reported that high concentrations of hormones such as IAA, IBA, and NAA suppressed astaxanthin production due to cellular dysfunction and increased cell mortality. 4.2 Interpreting physiological parameters Low dose phytohormones act as metabolic signals to promote carbon fixation, whereas excessive doses impose osmotic or feedback inhibition on photosynthesis [ 37 ]. Protein content likewise increased under low to moderate hormone levels but declined markedly at 1 mg L⁻¹, reaching a minimum of 27.03 ± 2.22 mg g⁻¹, implying that optimal phytohormone dosing enhances nitrogen assimilation and protein biosynthesis, while overdose may trigger protein degradation [ 41 ]. Chlorophyll content remained stable at low phytohormone concentrations, but was significantly reduced at 1 mg L⁻¹, indicating that high hormone doses exert stress on the photosystems or inhibit chlorophyll synthesis [ 42 ]. Carbohydrate content was elevated in all groups during the red stage, which indicated that H. pluvialis would accumulate a large amount of carbohydrate under stress conditions [ 43 ]. Chlorophyll levels were largely suppressed in the red stage, consistent with stress-induced downregulation of chlorophyll synthesis and upregulation of astaxanthin production [ 44 ]. 4.3 DEG patterns across stages Compared to the IAA group, the expression changes in the MeJA-treated group were more drastic, with some genes having − log 10 (padj) approaching 300, indicating that MeJA induced a stronger transcriptional response in the red algal stage. These results suggest that IAA primarily induced a slight increase in gene expression during the green growth phase, while MeJA led to the activation and suppression of a large number of genes during the red phase. 4.4 Functional interpretation of IAA responsive DEGs Genes encoding pyruvate phosphate dikinase (PPDK), such as novel.2670, novel.8652, and novel.2399, showed significant upregulation, with log 2 FoldChange values ranging from 1.49 to 1.57. The enzyme PPDK catalyzes the conversion of pyruvate to phosphoenolpyruvate, a key enzyme for improving CO 2 fixation efficiency in C 4 plants [ 45 , 46 ]. However, in C 3 plants such as Oryza sativa , PPDK primarily acts as an auxiliary enzyme in glycolysis, balancing carbon flow towards the biosynthesis of starch, proteins, fatty acids, and amino acids, especially being highly expressed in the starchy endosperm cytoplasm [ 47 , 48 ]. It may also provide ATP in hypoxic regions [ 49 ]. The significant upregulation of PPDK may imply that IAA induces a reprogramming of carbon metabolism in H. pluvialis to more efficiently utilize carbon sources for the synthesis of biological macromolecules, thereby supporting rapid cell proliferation and biomass accumulation [ 46 ]. As a photoautotrophic organism, the efficiency of carbon metabolism directly affects the growth of H. pluvialis , thus this regulation is consistent with the known function of IAA in promoting growth and biomass increase [ 50 ]. Furthermore, genes encoding pyruvate kinase ( PK , gene_QJQ45_025570 ) and fructokinase ( FRK , gene_QJQ45_013744 ) were also significantly upregulated (Table 4 ). PK is the final enzyme in the glycolysis pathway, responsible for producing ATP and pyruvate [ 51 ]. Its gene upregulation suggested that IAA may stimulate the rate of glycolysis in H. pluvialis , thereby increasing ATP production efficiency to provide sufficient energy support for various cellular activities, particularly growth and biosynthesis [ 52 , 53 ]. FRK converts fructose to fructose-6-phosphate, allowing it to enter the glycolysis pathway [ 54 ]. Its gene upregulation may mean that IAA promoted the ability of H. pluvialis to utilize different sugar substrates, enhancing the flexibility of carbohydrate metabolism. This helped cells maintain efficient energy production and biosynthesis under different carbon source conditions, thereby supporting continuous growth [ 55 ]. In terms of ion and nutrient transport, IAA significantly affected the absorption and distribution of key elements in H. pluvialis . ZIP9 genes, including gene_QJQ45_017004 and gene_QJQ45_020772 , both showed extremely high upregulation, with log 2 FoldChange values of 3.54 and 1.43, respectively (Table 4 ). The ZIP9 protein belongs to the ZIP family of proteins, responsible for transporting zinc ions from the extracellular environment into the cell [ 56 , 57 ]. Zinc is an important component of cell growth, proliferation, division, and apoptosis signaling, and also a structural component of many metalloenzymes and zinc finger transcription factors, and rapidly dividing cells usually require more zinc [ 58 , 59 ]. The extremely high upregulation of ZIP9 genes indicated that IAA strongly stimulated zinc absorption in H. pluvialis to meet its demand for zinc during rapid cell proliferation and metabolic activities [ 56 ]. The direct impact of IAA on cell division and cycle regulation in H. pluvialis was reflected at the gene expression level. CDKB1-1 ( gene_QJQ45_023291 ) and CYCB2-1 ( gene_QJQ45_026341 ) were both significantly upregulated, with log 2 FoldChange values of 1.49 and 1.56, respectively (Table 4 ). CDKB is a plant-specific CDK1 ortholog that binds to cyclins to co-regulate cell division, particularly G2/M phase transition and mitosis [ 60 , 61 ]. CYCB2-1 binds to CDKB1-1 to form an active complex, and both are important components of cell-cycle regulatory mechanisms [ 62 , 63 ]. As an auxin, one of IAA's most significant functions is to promote cell division [ 64 ]. The significant upregulation of these genes directly provided molecular evidence that IAA promoted cell proliferation in H. pluvialis by accelerating cell cycle progression, which is the basis for rapid biomass accumulation [ 65 ]. 4.5 Functional interpretation of MeJA responsive DEGs Astaxanthin synthesis is a multi-step enzymatic process involving the synergistic action of several key enzymes. The gene CRTW ( gene_QJQ45_019472 ) encoding β-carotene ketolase catalyzes a key step in the astaxanthin biosynthesis pathway (Table 5 ), responsible for converting β -carotene into canthaxanthin, a direct precursor to astaxanthin [ 66 , 67 ]. CRTW transcripts were significantly upregulated. BKT3 ( gene_QJQ45_024144 ) encoding β-carotene 4-ketolase 3, was also significantly upregulated (Table 5 ). This is an enzyme from the BKT family which activates the core step of β-carotene conversion to astaxanthin, and its upregulation further confirms that MeJA treatment stimulates the synthesis of astaxanthin [ 68 ]. Genes annotated as CRTZ ( gene_QJQ45_001374 and gene_QJQ45_030451 , encoding β-carotene 3-hydroxylase) were significantly downregulated (Table 5 ). These genes encode β-carotene hydroxylase (CHYB), a key enzyme in the astaxanthin biosynthetic pathway. CHYB hydroxylates β-carotene to β-cryptoxanthin and then to zeaxanthin, which is subsequently ketolated by β-carotene ketolase (BKT) to form adonixanthin and ultimately astaxanthin [ 69 , 70 ]. LCYE ( gene_QJQ45_015099 and gene_QJQ45_027358 ) were significantly downregulated (Table 5 ). The LCYE protein (lycopene ε-cyclase) cyclizes lycopene to delta-carotene, an enzyme in the alpha-carotene branch that competes for substrates with the β -carotene branch [ 71 ]. The expression patterns of these core synthesis genes reveal the precise regulation of the astaxanthin synthesis pathway by MeJA. The significant upregulation of the genes CRTW and BKT3 promotes the conversion of β -carotene towards astaxanthin [ 68 , 72 ]. Simultaneously, the downregulation of CRTZ and LCYE indicates that MeJA treatment inhibits bypass or competitive branches of the astaxanthin synthesis pathway, thereby reducing carbon flow to other carotenoids [ 27 , 69 ]. This transcriptomic pattern strongly suggested that MeJA induced astaxanthin accumulation in H. pluvialis was not merely a general activation of carotenoid synthesis. Instead, it appears to be a fine metabolic regulatory strategy that effectively shifts carbon flow from other carotenoids to astaxanthin, maximizing target product yield by specifically upregulating key genes in the astaxanthin branch while simultaneously inhibiting competitive branches [ 26 , 72 , 73 ]. 4.6 Interpreting enrichment results and integration Combining the KEGG and GO enrichment results, the effect of IAA on H. pluvialis in the green phase primarily focuses on the remodeling of carbohydrate and energy metabolism [ 74 ]. The significant enrichment of pyruvate, carbon metabolism, and carbon fixation in photosynthetic organism pathways, along with the prominence of carbohydrate metabolic processes in GO, collectively point to IAA's strong regulation of primary metabolism [ 74 , 75 ]. IAA, as a plant hormone, is known to promote cell growth and division [ 64 ]. During the highly photosynthetic green phase, enhanced carbohydrate synthesis and utilization are fundamental to supporting rapid growth [ 74 ]. Our observed differential expression of key genes encoding enzymes such as pyruvate kinase and PPDK further corroborates this inference [ 46 , 51 ]. IAA-induced changes in these pathways and genes may optimize the allocation of photosynthetic products or promote the synthesis of specific carbon skeletons to support biomass accumulation [ 76 , 77 ]. The enrichment of peroxisomes and transporter activities suggests a fine regulation of substance transport and intracellular environment by cells under IAA signaling to adapt to growth demands [ 78 , 79 ]. MeJA, as a stress phytohormone, induced a transcriptomic response in red phase H. pluvialis that was significantly different from IAA. GO and KEGG results consistently indicated that MeJA inhibited photosynthesis and primary carbon metabolism while promoting the biosynthesis of secondary metabolites [ 80 ]. As H. pluvialis transitions from the green to the red phase, photosynthetic efficiency typically decreases to conserve energy for astaxanthin synthesis [ 81 ]. MeJA may act as a signaling molecule in this process, accelerating this metabolic reprogramming [ 72 , 82 ]. Collectively, these findings were summarized in a mechanistic scheme (Fig. 8 ), explaining the principles by which IAA promotes biomass growth and MeJA boosts astaxanthin production in H. pluvialis . 5. Conclusion This study systematically investigated the effects of various phytohormones on the growth and physiological parameters of H. pluvialis during its green and red stages. Phytohormone application significantly altered both growth and physiological indices, and 0.01 mg L⁻¹ IAA exhibited the greatest growth-promoting effect, whereas 0.1 mg L⁻¹ MeJA yielded the highest astaxanthin accumulation. Further transcriptomic profiling of these two treatments revealed that IAA promoted biomass of green stage by upregulating carbon metabolism and cell cycle genes, while MeJA induced red stage astaxanthin biosynthesis via upregulation of CRTW and BKT3 and suppression of competing genes (e.g., CRTZ , LCYE ). These transcriptomic insights aligned with the observed enhancements in growth and pigment accumulation. These findings provide an important theoretical basis and molecular targets for utilizing hormones to regulate H. pluvialis biomass and astaxanthin production. Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Authors' contributions Yang Sun: Writing-original draft, Investigation, Formal analysis, Data curation; Yun Li: Writing – original draft, Investigation, Conceptualization, Methodology. Jing Zhang: Investigation, Formal analysis, Data curation; Rui Zhao: Formal analysis, Data curation; Jiaji Zhang: Conceptualization, Methodology; Mingxin Guo: Investigation, Methodology, Data curation; Wenjie Yan: Investigation, Writing-review & editing, Funding acquisition; Xu Gao: Writing-review & editing, Project administration, Funding acquisition. Data availability Data will be made available on request. The transcriptomic data have been deposited in NCBI (accession number: PRJNA1279618). Competing interest All authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Funding This work was financially supported by the Taishan Scholar Foundation of Shandong Province (No. tsqn202211067), the Fundamental Research Funds for the Central Universities (No. 202262002), the National Natural Science Foundation of China (42306135, 42176018) and the Open Project Program of Key Laboratory of Ecological Warning, Protection & Restoration for Bohai Sea, Ministry of Natural Resources (2024102). References Ren Y, Deng J, Huang J, Wu Z, Yi L, Bi Y, et al. Using green alga Haematococcus pluvialis for astaxanthin and lipid co-production: Advances and outlook. Bioresource Technology. 2021;340. Villaró S, Ciardi M, Morillas-España A, Sánchez-Zurano A, Acién-Fernández G, Lafarga T. Microalgae Derived Astaxanthin: Research and Consumer Trends and Industrial Use as Food. Foods. 2021;10(10):2303. Ekpe L, Inaku K, Ekpe V, Contact L, Ekpe V. Antioxidant effects of astaxanthin in various diseases-a review. Oxidants and Antioxidants in Medical Science. 2018:1-6. 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Int J Mol Sci. 2016;18(1). Raman V, Ravi S. Effect of salicylic acid and methyl jasmonate on antioxidant systems of Haematococcus pluvialis . Acta Physiologiae Plantarum. 2011;33(3):1043-9. Additional Declarations No competing interests reported. Supplementary Files SupplementaryFile1.docx SupplementaryFile2.xlsx Cite Share Download PDF Status: Published Journal Publication published 14 Mar, 2026 Read the published version in BMC Plant Biology → Version 1 posted Editorial decision: Revision requested 16 Jan, 2026 Reviews received at journal 14 Jan, 2026 Reviews received at journal 01 Jan, 2026 Reviewers agreed at journal 13 Dec, 2025 Reviewers agreed at journal 09 Dec, 2025 Reviewers invited by journal 09 Dec, 2025 Editor assigned by journal 07 Dec, 2025 Editor invited by journal 03 Dec, 2025 Submission checks completed at journal 02 Dec, 2025 First submitted to journal 02 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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1","display":"","copyAsset":false,"role":"figure","size":147631,"visible":true,"origin":"","legend":"\u003cp\u003eChanges of dry weight of \u003cem\u003eH. pluvialis\u003c/em\u003e in the green stage (A-D) and astaxanthin content in the red stage (E-H).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8198834/v1/c60275ba74432d5c88d34276.png"},{"id":98252815,"identity":"8cc4cf3c-393d-47a8-b70d-74139f50d701","added_by":"auto","created_at":"2025-12-15 17:28:25","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":216577,"visible":true,"origin":"","legend":"\u003cp\u003eGene function classification of all unigenes annotated by GO. Histogram representation of Gene Ontology classification.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8198834/v1/b60f0ed658d8e69fd75aa7c5.png"},{"id":98434919,"identity":"d67ea586-4da7-404c-a20c-c561b74fa12a","added_by":"auto","created_at":"2025-12-17 16:52:45","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":70115,"visible":true,"origin":"","legend":"\u003cp\u003eqRT-PCR analysis of DEGs. The six DEGs on the left correspond to the green-stage validation set (control vs. 0.01 mg L⁻¹ IAA), whereas the six DEGs on the right correspond to the red-stage validation set (control vs. 0.1 mg L⁻¹ MeJA).\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8198834/v1/92ecdc9fb3ffbfa6ca206712.png"},{"id":98252817,"identity":"eb13f1d6-17bd-4e93-99f5-4f2b76a028f0","added_by":"auto","created_at":"2025-12-15 17:28:25","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":214901,"visible":true,"origin":"","legend":"\u003cp\u003eCluster analysis and gene expression profiling of DEGs. The X axis presents treatments, while the red and green represent up-regulation and down-regulation\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8198834/v1/6443c8b4596b86135a39c3a0.png"},{"id":98252821,"identity":"7a2f2027-dea5-4357-a881-3ae346aa296f","added_by":"auto","created_at":"2025-12-15 17:28:25","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":99965,"visible":true,"origin":"","legend":"\u003cp\u003eVolcano plots of differentially expressed DEGs in response to phytohormone treatments. A: DEGs for the IAA vs GCon comparison. B: DEGs for the MeJA vs. RCon comparison. Blue dots represent upregulated genes, and red dots represent downregulated genes. Significantly upregulated genes are marked with blue dots in the figure, downregulated genes with red dots, and non-significantly differentially expressed genes with green dots.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8198834/v1/0dd2045089213741c1edb2b2.png"},{"id":98252823,"identity":"ab893d17-bee9-4880-9adc-eef794942fb5","added_by":"auto","created_at":"2025-12-15 17:28:25","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":91331,"visible":true,"origin":"","legend":"\u003cp\u003eKEGG pathway enrichment analysis of differentially expressed genes DEGs. A: IAA vs GCon comparison. B: MeJA vs RCon comparison. The size of each dot represents the number of genes enriched in the pathway (count), and the color indicates the significance of the enrichment (−log\u003csub\u003e10\u003c/sub\u003e(pvalue)). The x-axis shows the GeneRatio, which is the percentage of enriched genes in the total number of genes in the pathway.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-8198834/v1/71ed4d0cedebee14a6193c05.png"},{"id":98433803,"identity":"98108462-d0fe-42b8-a5d9-808496829903","added_by":"auto","created_at":"2025-12-17 16:51:08","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":240804,"visible":true,"origin":"","legend":"\u003cp\u003eGO pathway enrichment analysis of differentially expressed genes DEGs. A: IAA vs GCon comparison. B: MeJA vs RCon comparison.\u0026nbsp; The size of each dot represents the number of genes enriched in the pathway (count), and the color indicates the significance of the enrichment (−log\u003csub\u003e10\u003c/sub\u003e(pvalue)). The x-axis shows the GeneRatio, which is the percentage of enriched genes in the total number of genes in the pathway.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-8198834/v1/65484d2e53414cb2f66be1b0.png"},{"id":98433617,"identity":"08bb5121-1ef0-4201-978c-6e764fed6ce2","added_by":"auto","created_at":"2025-12-17 16:50:56","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":469840,"visible":true,"origin":"","legend":"\u003cp\u003eHypothetical models of phytohormone-regulated biomass growth and astaxanthin production in\u003cem\u003e H. pluvialis\u003c/em\u003e.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-8198834/v1/9e4ce04acf7e78b09f115be3.png"},{"id":104739416,"identity":"bdb43335-2f44-4fab-9405-3fcfe2215303","added_by":"auto","created_at":"2026-03-16 16:06:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2997932,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8198834/v1/c276f5a2-1f5c-48a0-8402-a91117bf2d19.pdf"},{"id":98252822,"identity":"3c29d71e-8d1d-42f9-8817-ffca210cd8c5","added_by":"auto","created_at":"2025-12-15 17:28:25","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":204076,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8198834/v1/b3564c0a8d6590a8e296d4f3.docx"},{"id":98252825,"identity":"63a3dca4-9d72-49eb-99ff-082b2e08f23e","added_by":"auto","created_at":"2025-12-15 17:28:25","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":140885,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFile2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8198834/v1/b18672dd0c63b5338021d300.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Physiological and transcriptomic analyses reveal the effects of phytohormones on growth and astaxanthin accumulation in Haematococcus pluvialis","fulltext":[{"header":"1. Background","content":"\u003cp\u003eAstaxanthin is a high-value red ketocarotenoid characterized by a unique chemical structure of thirteen conjugated double bonds [1]. This configuration provides potent antioxidant activity, effectively scavenging reactive oxygen species and free radicals with an antioxidant capacity up to 65-fold greater than vitamin C [2, 3]. Due to its powerful bioactivity, astaxanthin has been widely applied in many industries such as nutraceuticals, aquaculture, cosmetics, food, and animal feed [4]. The global astaxanthin market was valued at USD 1.63 billion in 2021 and is projected to reach USD 3.2 billion in 2026 [5]. Commercial astaxanthin products are classified into two main categories: synthetic and natural. Due to its lower production cost (approximately USD 1,000 per kg), synthetic astaxanthin holds the largest market share [6]. Chemically, synthetic astaxanthin exists primarily in a non-esterified form and is a racemic mixture of stereoisomers. In contrast, natural astaxanthin is highly esterified with fatty acids (95%) and consists almost exclusively of the (3S,3\u0026prime;S) stereoisomer [7, 8]. This specific stereochemical configuration is associated with superior antioxidant efficacy [9]. Despite its functional advantages, the global yield of natural astaxanthin remains low, and overcoming this production bottleneck is a major challenge [10].\u003c/p\u003e\n\u003cp\u003eSeveral microalgae are capable of synthesizing astaxanthin, with \u003cem\u003eHaematococcus pluvialis\u003c/em\u003e being the richest known natural source [11]. Under environmental stress or adverse cultivation conditions, it can accumulate astaxanthin to 5% of its dry weight, a crucial self-protection mechanism against oxidative stress [11-13]. And this process is often coupled with transitions of life stages. The life stages of \u003cem\u003eH. pluvialis\u003c/em\u003e can be divided into the green stage and the red stage [14]. Under favorable conditions, \u003cem\u003eH. pluvialis\u003c/em\u003e predominantly exists as green vegetative cells characterized by vigorous cell growth and division [14, 15]. Upon exposure to adverse environmental conditions, green vegetative cells reduce division, thicken cell walls and accumulate large amounts of carotenoids which are primarily astaxanthin in cytoplasmic lipid droplets, resulting in transformation into the red stage [16, 17]. Consequently, the industrial production of astaxanthin from \u003cem\u003eH. pluvialis\u003c/em\u003e typically employs a two-phase cultivation strategy. The green stage involves cultivation under suitable temperature, light and nutrient conditions to accumulate biomass. Once a sufficient biomass is reached, the red stage is initiated by applying stress such as high temperature, high light intensity, or nitrogen deprivation to induce astaxanthin accumulation [7, 18]. The production of astaxanthin inherently requires the application of stress conditions to induce its synthesis, which presents a delicate balance between astaxanthin accumulation and biomass growth [17, 19]. Therefore, identifying optimal stress levels or selecting appropriate inducers that maximize astaxanthin yield without compromising productivity is critical.\u003c/p\u003e\n\u003cp\u003ePhytohormones are critical endogenous signaling molecules that regulate virtually all aspects of plant growth, development, and responses to environmental stimuli [20, 21]. The roles of phytohormones have been extensively studied in higher plants, and increasing evidence indicates that these hormones also play significant roles in the physiology and metabolism of microalgae [22]. Indeed, numerous studies have demonstrated their positive effects on enhancing microalgal productivity. Abscisic acid (ABA) stimulates the activity of carbon metabolism-related enzymes, promoting lipid accumulation in \u003cem\u003eChlorella\u003c/em\u003e sp. [23]. Indole-3-acetic acid (IAA) was found to upregulate genes in the porphyrin metabolism pathway of \u003cem\u003ePhaeodactylum tricornutum\u003c/em\u003e, leading to enhanced chlorophyll biosynthesis and thereby stimulated growth [24]. Zeatin (ZT) plays significant roles in the cell cycle, cell division and photosynthetic pigment synthesis of \u003cem\u003eNannochloropsis oculata\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e[25]. Given the pronounced effects of phytohormones on microalgae, the application in cultivation of \u003cem\u003eH. pluvialis\u003c/em\u003e offers substantial potential. Hu et al. [26] demonstrated that the combined application of salicylic acid (SA) and high-light stress increased astaxanthin content in \u003cem\u003eH. pluvialis\u003c/em\u003e by 0.33 mg L⁻\u0026sup1; at 48 h. Gao et al. [27] found that carotenoid-biosynthesis genes (e.g.\u003cem\u003e, psy, pds\u003c/em\u003e, and \u003cem\u003ezds\u003c/em\u003e) involved in astaxanthin production were upregulated following treatment with either SA or jasmonic acid (JA). However, previous studies have typically investigated only a limited range of hormones and have lacked comprehensive studies on the green stage.\u003c/p\u003e\n\u003cp\u003eThe present study aimed to investigate the effects of five plant hormones including IAA, ABA, ZT, methyl jasmonate (MeJA) and N\u003csup\u003e6\u003c/sup\u003e-(\u0026Delta;\u003csup\u003e2\u003c/sup\u003e-Isopentenyl) adenosine (IPR) on the biomass and physiological composition (chlorophyll, astaxanthin, carbohydrates and proteins) of \u003cem\u003eH. pluvialis\u003c/em\u003e. Transcriptomic analysis was performed on \u003cem\u003eH. pluvialis\u003c/em\u003e from treatment groups that showed significant increases in biomass and astaxanthin accumulation, which will provide a molecular level understanding of phytohormone mediated regulatory networks governing growth and astaxanthin biosynthesis. The findings of this research are expected to facilitate the optimized application of phytohormones in \u003cem\u003eH. pluvialis\u003c/em\u003e cultivation for the enhanced production of high-value bioproducts.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Microalgae strain and phytohormones\u003c/h2\u003e\u003cp\u003eThe \u003cem\u003eH. pluvialis\u003c/em\u003e strain was purchased from Shanghai Guangyu Biological Technology Co., Ltd. (Shanghai, China). The strain is maintained in the Microalgae Culture Collection at the Laboratory of Applied Microalgal Biology, Ocean University of China, under the internal accession number LAMB284. Five phytohormones were obtained from MACKLIN, China: IAA (\u0026ge;\u0026thinsp;98%), ABA (\u0026ge;\u0026thinsp;98%), MeJA (\u0026ge;\u0026thinsp;98%), ZT (\u0026ge;\u0026thinsp;99%), IPR (\u0026ge;\u0026thinsp;98.5%).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Algal culture and phytohormonal additions\u003c/h2\u003e\u003cp\u003e\u003cem\u003eH. pluvialis\u003c/em\u003e of green stage was cultivated in 300 mL Erlenmeyer flasks containing 200 mL of BG11 medium [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] under a light intensity of 30 \u0026micro;mol m\u003csup\u003e\u0026minus;\u003c/sup\u003e\u0026sup2; s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e with a 14h/10h light-dark cycle at 22\u0026thinsp;\u0026plusmn;\u0026thinsp;1 ℃ and 7.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1 pH. The initial inoculation density was 1\u0026times;10\u003csup\u003e4\u003c/sup\u003e cells mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The phytohormones used were IAA, ABA, IPR, and ZT. Phytohormones were first prepared as concentrated stocks (1 g L⁻\u0026sup1;) using sterile water (with a minimal amount of ethanol when needed for solubility), stored at 4\u0026deg;C and used within 7 days. Before application, stocks were diluted with culture medium to the working concentrations of 0.001, 0.01, 0.1, and 1 mg L⁻\u0026sup1;. Controls received the same volume of sterile water (or solvent at the matching final v/v when ethanol was used). Cultivation lasted 15 days, with samples collected every 3 days for dry weight determination and samples from day 9 were taken for physiological measurement.\u003c/p\u003e\u003cp\u003e\u003cem\u003eH. pluvialis\u003c/em\u003e of red stage was obtained as follows: after 15 days cultivation under the same conditions above without phytohormone supplementation, the light intensity was increased to 100 \u0026micro;mol m\u003csup\u003e\u0026minus;\u003c/sup\u003e\u0026sup2; s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and four phytohormones (IAA, ABA, MeJA, and ZT) were added to medium. Cultivation was continued for another 15 days, with samples collected every 3 days to measure astaxanthin and samples from day 24 were analyzed for physiological data. All days are counted from the initial inoculation.\u003c/p\u003e\u003cp\u003eThe choice of IPR for the green stage and MeJA for the red stage was based on our prior measurement of endogenous phytohormones in \u003cem\u003eH. pluvialis\u003c/em\u003e. Endogenous IPR was abundant in the green stage and decreased in the red stage, whereas endogenous MeJA increased during the red stage [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. For each phytohormone concentration, 3 independent biological replicates were used.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Physiological analysis\u003c/h2\u003e\u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\u003ch2\u003e2.3.1 Measurement of dry weight\u003c/h2\u003e\u003cp\u003eFirst, 20 mL of algal culture at the green stage was concentrated at 2000 g for 10 minutes to discard the supernatant. The pellets were washed twice with distilled water, then dried at 60 ℃ for 24 h. Finally, the dried samples were weighed to determine the dry weight.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\u003ch2\u003e2.3.2 Determination of total chlorophyll content\u003c/h2\u003e\u003cp\u003eTotal chlorophyll was extracted using ethanol and measured using a spectrophotometer, following the method described by Rowan [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Briefly, 10 mL of algal culture was centrifuged at 2000 \u0026times; g for 10 min to collect the cell pellet. The pellet was resuspended in 10 mL of 95% ethanol and incubated in darkness for 24 h. Absorbance of the extract was measured at 665 and 649 nm, with chlorophyll content calculated using the following formula:\u003c/p\u003e\u003cp\u003e\u003cem\u003eC\u003c/em\u003e\u003csub\u003eChl a\u003c/sub\u003e (mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u0026thinsp;=\u0026thinsp;13.70A\u003csub\u003e665\u003c/sub\u003e \u0026ndash; 5.76A\u003csub\u003e649\u003c/sub\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eC\u003c/em\u003e\u003csub\u003eChl b\u003c/sub\u003e (mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u0026thinsp;=\u0026thinsp;25.8 A\u003csub\u003e649\u003c/sub\u003e\u0026ndash;7.60A\u003csub\u003e665\u003c/sub\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eC\u003c/em\u003e\u003csub\u003eTotal Chl\u003c/sub\u003e (mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u0026thinsp;=\u0026thinsp;\u003cem\u003eC\u003c/em\u003e\u003csub\u003eChl a\u003c/sub\u003e + \u003cem\u003eC\u003c/em\u003e\u003csub\u003eChl b\u003c/sub\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section3\"\u003e\u003ch2\u003e2.3.3 Measurement of astaxanthin\u003c/h2\u003e\u003cp\u003eThe method of astaxanthin measurement referred to Zhang et al [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Briefly, 5 mL of culture were centrifuged at 2000 g for 10 min and the supernatant discarded. Pellets were resuspended in 3 mL dimethyl sulfoxide and heated at 80\u0026deg;C for 10 min. Samples were centrifuged at 2000 g for 10 min and the supernatant transferred to a clean tube. Extraction was repeated until pellets turned white. The pooled supernatant absorbance was measured at 530 nm on a UH5300 spectrophotometer (Hitachi, Japan). Astaxanthin standard (purity\u0026thinsp;\u0026ge;\u0026thinsp;98%, Solarbio, China) was used for quantification.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\u003ch2\u003e2.3.4 Measurement of carbohydrate\u003c/h2\u003e\u003cp\u003eThe total carbohydrate content of \u003cem\u003eH. pluvialis\u003c/em\u003e was determined using the anthrone method [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. A 2 mL of algal suspension was centrifuged at 2000 g for 10 min. The pellet was reacted with 8 mL of anthrone solution, which was prepared by mixing 0.2 g anthrone, 8 mL absolute ethanol, and 100 mL concentrated sulfuric acid (98%). The mixture was heated at 90 ℃ for 10 min. After cooling, the absorbance was measured at 620 nm. A standard curve was constructed by glucose standards.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section3\"\u003e\u003ch2\u003e2.3.5 Measurement of protein\u003c/h2\u003e\u003cp\u003eThe protein content of \u003cem\u003eH. pluvialis\u003c/em\u003e was quantified using the Coomassie Brilliant Blue G‑250 colorimetric assay [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. 5 mL of algal suspension was centrifuged (2000 g, 10 min), and cell pellet was resuspended in 200 \u0026micro;L of 1 M NaOH before incubation at 80 ℃ for 10 min. After the addition of 800 \u0026micro;L of distilled water, samples were centrifuged at 3000 g for 30 min. The supernatants were collected and the process was repeated twice. All supernatants were pooled and diluted to a volume of 5 mL. 2 mL of the extract were mixed with 5 mL of Coomassie Brilliant Blue G-250 solution (1 mg mL⁻\u0026sup1;) and incubated at room temperature for 15 minutes. 200 \u0026micro;L aliquot was added to a 96-well microplate, and absorbance was measured at 595 nm using a microplate reader (Synergy\u0026trade; Mx, BioTek, USA). Bovine serum albumin was used to generate the standard curve.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section3\"\u003e\u003ch2\u003e2.3.6 Statistical analysis\u003c/h2\u003e\u003cp\u003eAll physiological composition data were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD (n\u0026thinsp;=\u0026thinsp;3). Group differences were assessed by one-way ANOVA followed by Tukey\u0026rsquo;s HSD for multiple comparisons (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). All statistical analyses were performed using SPSS 26.0 and Graphpad Prism (v9.5).\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Transcriptome analysis\u003c/h2\u003e\u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\u003ch2\u003e2.4.1 RNA extraction, library preparation and sequencing\u003c/h2\u003e\u003cp\u003eTotal RNA was extracted from \u003cem\u003eH. pluvialis\u003c/em\u003e in the control group, the biomass optimized group and the astaxanthin optimized group using RNAprep Pure Plant Kit (TIANGEN, China). RNA integrity and quality were assessed with an Agilent 2100 Bioanalyzer. mRNA was isolated from the total RNA using oligo (dT) magnetic beads and subsequently fragmented into smaller strands. cDNA synthesis was conducted in two steps: first-strand cDNA synthesis using random hexamer primers, followed by second-strand synthesis. Library preparation involved sequential steps of end repair, A-tailing, adapter ligation, size selection, PCR amplification, and purification. The resulting libraries were pooled based on effective concentration and target sequencing depth. DNA nanoballs were generated through rolling-circle replication after 5\u0026prime;-phosphorylation and circularization. Sequencing was carried out on the DNBSEQ-T7 platform (MGI Tech Co., Ltd., China). All sequence data were 2 \u0026times; 75 bp in length. Raw sequencing data have been deposited in the NCBI Sequence Read Archive (SRA) database under accession number PRJNA1279618.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section3\"\u003e\u003ch2\u003e2.4.2 Bioinformatics Analysis\u003c/h2\u003e\u003cp\u003eRaw sequencing reads were pre-processed to remove low-quality reads, adapter sequences, and poly-N sequences using fastp. Clean reads were then mapped to the \u003cem\u003eH. pluvialis\u003c/em\u003e reference genome (NCBI RefSeq: GCA_030144725.1) using HISAT2 v2.2.1. Gene expression levels were quantified as FPKM (Fragments Per Kilobase of transcript per Million mapped reads) using StringTie v2.2.1.\u003c/p\u003e\u003cp\u003eDifferential expression analysis was performed using DESeq2 v1.42.0 to identify genes significantly altered in the hormone treated groups compared to the control. Genes with a |log\u003csub\u003e2\u003c/sub\u003eFoldChange| \u0026ge; 1 and an adjusted pvalue\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered differentially expressed.\u003c/p\u003e\u003cp\u003eGene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of differentially expressed genes were conducted using clusterProfiler R package (v4.8.1) to identify over-represented biological processes, molecular functions, cellular components, and metabolic pathways.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\u003ch2\u003e2.4.3 Functional annotation\u003c/h2\u003e\u003cp\u003ePutative gene functions were assigned by BLAST based searches. Protein sequences were queried against the Swiss-Prot database, and Gene Ontology terms were transferred from the best Swiss-Prot match where available. KEGG Orthology identifiers were assigned using the KEGG database and were used for pathway mapping.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Validation of RNA-seq data by qRT-PCR\u003c/h2\u003e\u003cp\u003eTo validate the RNA-seq results, quantitative real-time PCR (qPCR) was performed on \u003cem\u003eH. pluvialis\u003c/em\u003e samples collected from the green and red stages. For the green stage, cells from the control group and the 0.01 mg L⁻\u0026sup1; IAA-treated group were analyzed; for the red stage, cells from the control group and the 0.1 mg L⁻\u0026sup1; MeJA-treated group were analyzed. Total RNA was extracted using the Servicebio MF168 RNA extraction kit following the manufacturer\u0026rsquo;s instructions. RNA concentration and purity were assessed with a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific), and samples with acceptable A260/280 ratios (1.8\u0026ndash;2.2) were used for reverse transcription. First-strand cDNA was synthesized from 1 \u0026micro;g of total RNA in a 20 \u0026micro;L reaction using the Vazyme HiScript III 1st Strand cDNA Synthesis Kit with gDNA wiper. The reverse transcription program was 37\u0026deg;C for 15 min followed by 85\u0026deg;C for 5 s.\u003c/p\u003e\u003cp\u003eQPCR was carried out using Vazyme Taq Pro Universal SYBR qPCR Master Mix on a BIO-RAD CFX95 Real-Time PCR System (C1000 Touch Thermal Cycler), and fluorescence data were collected with CFX Manager 3.1. Each 20 \u0026micro;L qPCR reaction contained 10 \u0026micro;L SYBR master mix, 0.4 \u0026micro;L of each primer (10 \u0026micro;M), and 2 \u0026micro;L of diluted cDNA (equivalent to 20 ng total RNA), with nuclease-free water added to volume. The thermal cycling conditions were 95\u0026deg;C for 30 s, followed by 40 cycles of 95\u0026deg;C for 10 s and 60\u0026deg;C for 30 s. Following the cycling protocol, a melting curve analysis was performed from 65\u0026deg;C to 95\u0026deg;C to verify the specificity of the PCR products. Primer pairs were designed using NCBI Primer-BLAST, and primer sequences and amplicon sizes are listed in Supplementary File 1 (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Expression levels were normalized to the reference gene \u003cem\u003egene_QJQ45_016574\u003c/em\u003e and \u003cem\u003egene_QJQ45_003696\u003c/em\u003e, and relative transcript abundance was calculated using the 2^\u0026minus;ΔΔCt method. Three biological replicates were analyzed for each condition, with three technical replicates per sample. No-template controls (NTC) and no-RT controls were included in each run to ensure specificity and exclude contamination.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Biomass and astaxanthin content under phytohormone treatments\u003c/h2\u003e\u003cp\u003eThe effects of different phytohormone treatments on biomass accumulation during the green stage of \u003cem\u003eH. pluvialis\u003c/em\u003e are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA\u0026ndash;D. All groups exhibited slow growth during the initial 3 days, then entering an exponential phase. By day 15, the biomass of the green stage control (GCon) reached 0.29 g L⁻\u0026sup1;. Among all treatments, 0.01 mg L⁻\u0026sup1; IAA resulted in the highest biomass yield, with biomass attaining 0.37 g L⁻\u0026sup1; at day 15. In addition to IAA, 0.001 and 0.01 mg L-1 concentrations of ABA, ZT, and IPR also promoted growth to varying extents, whereas higher concentrations of these hormones inhibited \u003cem\u003eH. pluvialis\u003c/em\u003e growth.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAstaxanthin accumulation during the red stage is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE\u0026ndash;H. The accumulation rate peaked between days 3 and 6 and declined thereafter. On day 15, the astaxanthin content of the red stage control (RCon) was 23.09 mg g⁻\u0026sup1;. Treatment with 0.1 mg L⁻\u0026sup1; MeJA yielded the highest astaxanthin accumulation of 29.22 mg g⁻\u0026sup1;. Other phytohormones also promoted astaxanthin synthesis to lesser degrees. However, phytohormone treatments at 1 mg L⁻\u0026sup1; markedly inhibited astaxanthin accumulation.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Effects of phytohormones on physiological parameters\u003c/h2\u003e\u003cp\u003ePhysiological parameters under phytohormone treatments during the green stage are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Exogenous ABA, ZT, and IPR at low concentrations (0.001 and 0.01 mg L⁻\u0026sup1;) significantly enhanced carbohydrate content, with 0.01 mg L⁻\u0026sup1; ABA producing the greatest increase. In contrast, higher phytohormone concentrations generally inhibited carbohydrate accumulation. Protein content likewise increased under low to moderate phytohormone levels but declined markedly at 1 mg L⁻\u0026sup1;, reaching a minimum of 27.03\u0026thinsp;\u0026plusmn;\u0026thinsp;2.22 mg g⁻\u0026sup1;.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eEffects of phytohormone treatments on physiological and biochemical measurements of green stage of \u003cem\u003eH. pluvialis\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMeasurements\u003c/p\u003e\u003cp\u003eAlgal samples\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCarbohydrate\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eProtein\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eChlorophyll\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGCon\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e40.42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e38.07\u0026thinsp;\u0026plusmn;\u0026thinsp;3.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e10.53\u0026thinsp;\u0026plusmn;\u0026thinsp;1.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eABA_0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e57.46\u0026thinsp;\u0026plusmn;\u0026thinsp;1.56\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e49.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.39\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e11.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eABA_0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e82.27\u0026thinsp;\u0026plusmn;\u0026thinsp;1.77\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e43.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e11.50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.56\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eABA_0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e25.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.62\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e31.71\u0026thinsp;\u0026plusmn;\u0026thinsp;1.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e5.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eABA_1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e15.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.80\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e27.03\u0026thinsp;\u0026plusmn;\u0026thinsp;2.22\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e2.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIAA_0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e36.22\u0026thinsp;\u0026plusmn;\u0026thinsp;1.59\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e48.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e11.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIAA_0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e35.97\u0026thinsp;\u0026plusmn;\u0026thinsp;1.41\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e49.11\u0026thinsp;\u0026plusmn;\u0026thinsp;4.07\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e14.20\u0026thinsp;\u0026plusmn;\u0026thinsp;1.31\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIAA_0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e32.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.59\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e45.58\u0026thinsp;\u0026plusmn;\u0026thinsp;2.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e11.19\u0026thinsp;\u0026plusmn;\u0026thinsp;1.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIAA_1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e14.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.76\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e33.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e4.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.40\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZT_0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e53.03\u0026thinsp;\u0026plusmn;\u0026thinsp;1.42\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e36.5\u0026thinsp;\u0026plusmn;\u0026thinsp;3.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e11.48\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZT_0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e47.58\u0026thinsp;\u0026plusmn;\u0026thinsp;3.34\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e51.13\u0026thinsp;\u0026plusmn;\u0026thinsp;2.09\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e12.76\u0026thinsp;\u0026plusmn;\u0026thinsp;1.23\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZT_0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e35.73\u0026thinsp;\u0026plusmn;\u0026thinsp;1.00\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e50.32\u0026thinsp;\u0026plusmn;\u0026thinsp;1.73\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e5.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.70\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZT_1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e18.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e46.51\u0026thinsp;\u0026plusmn;\u0026thinsp;4.67\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e2.94\u0026thinsp;\u0026plusmn;\u0026thinsp;0.33\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIPR_0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e47.47\u0026thinsp;\u0026plusmn;\u0026thinsp;2.34\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e43.44\u0026thinsp;\u0026plusmn;\u0026thinsp;1.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e11.12\u0026thinsp;\u0026plusmn;\u0026thinsp;1.49\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIPR_0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e81.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e35.66\u0026thinsp;\u0026plusmn;\u0026thinsp;2.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e12.82\u0026thinsp;\u0026plusmn;\u0026thinsp;1.00\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIPR_0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e39.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e45.66\u0026thinsp;\u0026plusmn;\u0026thinsp;2.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e5.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.62\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIPR_1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e21.73\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e48.67\u0026thinsp;\u0026plusmn;\u0026thinsp;3.45\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e2.84\u0026thinsp;\u0026plusmn;\u0026thinsp;0.30\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eData are given as means\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, n\u0026thinsp;=\u0026thinsp;3. Unit is mg g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. *\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, **\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01 compared to the control group. The numbers following phytohormone names represent treatment concentrations (mg L⁻\u0026sup1;).\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ePhysiological responses during the red stage are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Carbohydrate content was elevated in almost all groups during the red stage. The treatment group with ZT at 0.1 mg L⁻\u0026sup1; achieved the highest level (159.92\u0026thinsp;\u0026plusmn;\u0026thinsp;5.84 mg g⁻\u0026sup1;). Compared with the control, the treatments of 0.001 mg L⁻\u0026sup1; MeJA, 0.1 mg L⁻\u0026sup1; ZT, and 0.1 mg L⁻\u0026sup1; IAA resulted in a significant decrease in protein content, with the lowest level observed under 0.1 mg L⁻\u0026sup1; IAA (10.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.67 mg g⁻\u0026sup1;). Conversely, significant increases were observed under the treatments of 0.01 mg L⁻\u0026sup1; ZT, 1 mg L⁻\u0026sup1; ABA, 1 mg L⁻\u0026sup1; ZT, and 1 mg L⁻\u0026sup1; IAA, with 0.01 mg L⁻\u0026sup1; ZT showing the highest protein content (25.46\u0026thinsp;\u0026plusmn;\u0026thinsp;1.73 mg g⁻\u0026sup1;).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eEffects of phytohormone treatments on physiological and biochemical measurements of red stage of \u003cem\u003eH. pluvialis\u003c/em\u003e.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMeasurements\u003c/p\u003e\u003cp\u003eAlgal samples\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCarbohydrate\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eProtein\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eChlorophyll\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRCon\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e95.00\u0026thinsp;\u0026plusmn;\u0026thinsp;4.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e15.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e1.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMeJA_0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e136.97\u0026thinsp;\u0026plusmn;\u0026thinsp;5.65\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e11.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e1.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMeJA_0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e115.15\u0026thinsp;\u0026plusmn;\u0026thinsp;6.48\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e13.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e1.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMeJA_0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e142.40\u0026thinsp;\u0026plusmn;\u0026thinsp;8.46\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e15.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e0.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMeJA_1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e89.21\u0026thinsp;\u0026plusmn;\u0026thinsp;3.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e17.92\u0026thinsp;\u0026plusmn;\u0026thinsp;1.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e0.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eABA_0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e122.73\u0026thinsp;\u0026plusmn;\u0026thinsp;4.80\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e19.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e1.79\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eABA_0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e120.51\u0026thinsp;\u0026plusmn;\u0026thinsp;7.70\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e18.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e2.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eABA_0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e117.25\u0026thinsp;\u0026plusmn;\u0026thinsp;6.23\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e17.37\u0026thinsp;\u0026plusmn;\u0026thinsp;1.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e1.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eABA_1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e95.92\u0026thinsp;\u0026plusmn;\u0026thinsp;6.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e22.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.68\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e0.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZT_0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e88.70\u0026thinsp;\u0026plusmn;\u0026thinsp;6.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e16.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e1.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZT_0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e121.53\u0026thinsp;\u0026plusmn;\u0026thinsp;5.78\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e25.46\u0026thinsp;\u0026plusmn;\u0026thinsp;1.73\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e2.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZT_0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e159.92\u0026thinsp;\u0026plusmn;\u0026thinsp;5.84\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e11.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e1.31\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZT_1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e51.94\u0026thinsp;\u0026plusmn;\u0026thinsp;3.04\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e0.78\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIAA_0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e108.04\u0026thinsp;\u0026plusmn;\u0026thinsp;7.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e14.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e1.78\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIAA_0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e108.29\u0026thinsp;\u0026plusmn;\u0026thinsp;6.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e17.96\u0026thinsp;\u0026plusmn;\u0026thinsp;1.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e2.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIAA_0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e146.68\u0026thinsp;\u0026plusmn;\u0026thinsp;7.30\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e10.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.67\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e1.99\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIAA_1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e65.59\u0026thinsp;\u0026plusmn;\u0026thinsp;4.21\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e22.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e\u003cp\u003e1.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eData are given as means\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, n\u0026thinsp;=\u0026thinsp;3. Unit is mg g\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. *\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, **\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01 compared to the control group. The numbers following phytohormone names represent treatment concentrations (mg L⁻\u0026sup1;).\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Overview of transcriptome sequencing data\u003c/h2\u003e\u003cp\u003eTo deeply explore the molecular regulatory mechanisms of phytohormones on \u003cem\u003eH. pluvialis\u003c/em\u003e growth and astaxanthin accumulation, we conducted transcriptome sequencing analysis on the groups with the highest biomass accumulation (0.01 mg L⁻\u0026sup1; IAA), the highest astaxanthin accumulation (0.1 mg L⁻\u0026sup1; MeJA), and their respective controls (GCon and RCon). Strict quality control was performed on the raw sequencing data of all samples. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, all samples had sufficient sequencing data, with an average of 40-50M reads/sample. After quality filtering, 39-48M clean reads/sample were retained, meeting expectations. In terms of base quality, the Q30 percentage of all samples was above 96%, and the GC content was stable (58.73\u0026ndash;60.54%). The mapping rate of reads aligned to the \u003cem\u003eH. pluvialis\u003c/em\u003e reference genome ranged from 64.11% to 76.51%, consistent with mapping rates reported for this species using genome based alignment (\u0026asymp;\u0026thinsp;63.3% on average), and the high read quality together with the known highly repetitive genome indicates that such rates are expected for \u003cem\u003eH. pluvialis\u003c/em\u003e [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. In the GCon, IAA treated groups, RCon, and MeJA treated groups, 34625, 34430, 34270, and 35267 expressed genes were identified, respectively. The FPKM for each sample group is shown in Supplementary File 1: Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. The results indicate that 25% of the expressed genes were in the 0-0.5 FPKM range, 35% were in the 0.5-5 FPKM range, 35% were in the 5-100 FPKM range, and 3% of genes had FPKM values exceeding 100. Functional annotation assigned 10,021 genes to GO categories, 499 to KEGG pathways, 498 to KEGG Orthology identifiers, and 6,650 to protein interaction entries.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eRNA sequencing results\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAlgal Samples\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRaw reads\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eClean reads\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eError rate (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eQ30 (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eGC content (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eMapping rate (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGCon_1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e43009230\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e41841168\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e96.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e59.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e72.31\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGCon_2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e42935178\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e41838162\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e96.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e59.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e76.51\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGCon_3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e46886006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e45483570\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e96.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e59.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e71.84\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIAA_1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e46519838\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e45163956\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e96.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e58.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e65.44\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIAA_2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e43069706\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e41577938\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e96.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e58.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e66.52\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIAA_3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e47104636\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e45607276\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e96.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e58.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e68.53\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRCon_1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e47533786\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e46393270\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e96.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e60.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e67.61\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRCon_2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e46725614\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e45734276\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e96.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e60.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e68.63\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRCon_3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e47131428\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e45941918\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e96.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e60.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e68.32\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMeJA_1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e49255422\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e47856734\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e96.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e60.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e64.11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMeJA_2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e47068684\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e45484812\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e96.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e60.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e64.38\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMeJA_3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e40264948\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e38984278\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e96.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e59.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e68.67\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eGO classification of 10,021 genes emphasized categories that are most informative for growth and metabolism in \u003cem\u003eH. pluvialis\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). At the biological process level, annotations concentrated in protein and nucleic acid metabolism and biosynthetic and macromolecule modification processes. At the cellular component level, genes were mainly associated with the membrane and intracellular organelles including the cytoplasm, nucleus and ribosome. At the molecular function level, binding and catalytic activity dominated, with nucleotide or ATP binding and hydrolase and transferase activities also prominent.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003e3.4 qRT-PCR validation of RNA-seq data\u003c/h2\u003e\u003cp\u003eTo experimentally validate the RNA-seq results, qRT-PCR was performed on a randomly selected subset of DEGs from both developmental stages. Six DEGs were chosen from the green stage and another six from the red stage, with the selection covering both up-regulated and down-regulated transcripts. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the qRT-PCR results exhibited expression trends fully consistent with those obtained from the RNA-seq analysis in both stages.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\u003ch2\u003e3.5 Differential expression analysis\u003c/h2\u003e\u003cp\u003eClustering analysis of differentially expressed genes (DEGs) showed that biological replicate samples from the same treatment group clustered together (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), indicating good experimental reproducibility. More importantly, samples from different growth stages formed distinct clustering branches, with the GCon and IAA treated group clustering into one category, and the RCon and MeJA treated group clustering into another.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo further identify differentially expressed genes induced by phytohormones, we used ∣log\u003csub\u003e2\u003c/sub\u003eFoldChange∣ \u0026ge; 1 and padj\u0026thinsp;\u0026lt;\u0026thinsp;0.05 as screening thresholds to construct volcano plots illustrating the overall distribution of DEGs between the GCon and IAA-treated groups, and the RCon and MeJA-treated groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA, in the comparison between the IAA-treated group and the GCon, a total of 490 significantly differentially expressed genes were identified, of which 400 genes were upregulated and 90 genes were downregulated. In the comparison between the MeJA-treated group and the RCon (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB), a total of 3208 DEGs were identified, with 1927 genes significantly upregulated and 1281 genes downregulated. Since these genes required functional annotation, we annotated the differentially expressed genes in the Swiss-Prot database in section \u003cspan refid=\"Sec22\" class=\"InternalRef\"\u003e3.5\u003c/span\u003e to explore their potential biological functions.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec23\" class=\"Section2\"\u003e\u003ch2\u003e3.6 Functional annotation and in-depth analysis of key DEGs\u003c/h2\u003e\u003cdiv id=\"Sec24\" class=\"Section3\"\u003e\u003ch2\u003e3.6.1 Key DEGs in response to IAA treatment\u003c/h2\u003e\u003cp\u003eTranscriptome analysis revealed significant changes in \u003cem\u003eH. pluvialis\u003c/em\u003e gene expression after IAA treatment. A total of 163 annotated differentially expressed genes were obtained, of which 112 were upregulated and 51 were downregulated (Supplementary File 2, Sheet1). Key DEGs associated with growth are presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDEGs between IAA treated group and GCon group.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProtein\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGene_id\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBest-hit annotation (species)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRef symbol\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003elog\u003csub\u003e2\u003c/sub\u003eFoldChange\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003epvalue\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePyruvate phosphate dikinase\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003enovel.2670\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003epyruvate phosphate dikinase 1 (Oryza sativa)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePPDK1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.7E-26\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePyruvate phosphate dikinase\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003enovel.8652\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003epyruvate phosphate dikinase 1 (Arabidopsis thaliana)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePPDK\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6.3E-23\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePyruvate phosphate dikinase\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003enovel.2399\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003epyruvate phosphate dikinase 1 (Oryza sativa)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePPDK1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.6E-16\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePyruvate kinase\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003egene_QJQ45_025570\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003epyruvate kinase, cytosolic 2 (Oryza sativa)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePK\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.1E-4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFructokinase\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003egene_QJQ45_013744\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003efructokinase 2 (Oryza sativa)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFRK2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.3E-4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZinc transporter 9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003egene_QJQ45_017004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ezinc transporter 9 (Oryza sativa)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eZIP9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e3.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2E-65\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZinc transporter 9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003egene_QJQ45_020772\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ezinc transporter 9 (Oryza sativa)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eZIP9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.5E-19\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCyclin-dependent kinase B1-1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003egene_QJQ45_023291\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ecyclin-dependent kinase B1-1 (Oryza sativa)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCDKB1-1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.9E-4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCyclin B2-1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003egene_QJQ45_026341\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ecyclin B2-1 (Oryza sativa)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCYCB2-1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.5E-4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThree loci annotated as pyruvate phosphate dikinase (\u003cem\u003ePPDK\u003c/em\u003e; \u003cem\u003enovel.2670\u003c/em\u003e, \u003cem\u003enovel.8652\u003c/em\u003e, \u003cem\u003enovel.2399\u003c/em\u003e) were concordantly upregulated. In parallel, transcripts encoding pyruvate kinase (\u003cem\u003ePK\u003c/em\u003e; \u003cem\u003egene_QJQ45_025570\u003c/em\u003e) and fructokinase (\u003cem\u003eFRK2\u003c/em\u003e; \u003cem\u003egene_QJQ45_013744\u003c/em\u003e) increased, indicating coordinated enhancement of flux at the PEP/pyruvate node. Two zinc transporter 9 loci (\u003cem\u003eZIP9\u003c/em\u003e; \u003cem\u003egene_QJQ45_017004\u003c/em\u003e and \u003cem\u003egene_QJQ45_020772\u003c/em\u003e) were strongly upregulated. Transcripts for \u003cem\u003eCDKB1-1\u003c/em\u003e (\u003cem\u003egene_QJQ45_023291\u003c/em\u003e) and \u003cem\u003eCYCB2-1\u003c/em\u003e (\u003cem\u003egene_QJQ45_026341\u003c/em\u003e) also increased.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec25\" class=\"Section3\"\u003e\u003ch2\u003e3.6.2 Key DEGs in response to MeJA treatment\u003c/h2\u003e\u003cp\u003eDEGs in \u003cem\u003eH. pluvialis\u003c/em\u003e after MeJA treatment were also annotated using Swiss-Prot, yielding a total of 1103 annotated differentially expressed genes. 596 were upregulated and 507 were downregulated (Supplementary File 2, Sheet2). Key DEGs associated with astaxanthin biosynthesis are presented in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDEGs between MeJA treated group and Rcon group.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProteins\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGene_id\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eBest-hit annotation (species)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRef symbol\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003elog\u003csub\u003e2\u003c/sub\u003eFoldchange\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003epvalue\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eβ-carotene ketolase\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003egene_QJQ45_019472\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ebeta-carotene ketolase (\u003cem\u003eHaematococcus pluvialis\u003c/em\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCRTW\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.9E-130\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eβ-carotene 4-ketolase 3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003egene_QJQ45_024144\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ebeta-carotene ketolase 3 (\u003cem\u003eHaematococcus pluvialis\u003c/em\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBKT3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.1E-129\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eβ-carotene 3-hydroxylase\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003egene_QJQ45_001374\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ebeta-carotene 3-hydroxylase (\u003cem\u003eHaematococcus pluvialis\u003c/em\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCRTZ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-1.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.4E-12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eβ-carotene 3-hydroxylase\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003egene_QJQ45_030451\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ebeta-carotene 3-hydroxylase (\u003cem\u003eHaematococcus pluvialis\u003c/em\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCRTZ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-1.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5.3E-05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLycopene epsilon cyclase\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003egene_QJQ45_015099\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003elycopene epsilon cyclase (\u003cem\u003eSolanum lycopersicum\u003c/em\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLCYE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-1.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.2E-72\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLycopene epsilon cyclase\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003egene_QJQ45_027358\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003elycopene epsilon cyclase (\u003cem\u003eSolanum lycopersicum\u003c/em\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLCYE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-1.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6.8E-09\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTwo ketolase-encoding genes were significantly upregulated: \u003cem\u003eCRTW\u003c/em\u003e (\u003cem\u003egene_QJQ45_019472\u003c/em\u003e) and \u003cem\u003eBKT3\u003c/em\u003e (\u003cem\u003egene_QJQ45_024144\u003c/em\u003e). Two loci annotated as β-carotene 3-hydroxylase (\u003cem\u003eCRTZ\u003c/em\u003e; \u003cem\u003egene_QJQ45_001374\u003c/em\u003e and \u003cem\u003egene_QJQ45_030451\u003c/em\u003e) were downregulated, and two lycopene ε-cyclase loci (\u003cem\u003eLCYE\u003c/em\u003e; \u003cem\u003egene_QJQ45_015099\u003c/em\u003e and \u003cem\u003egene_QJQ45_027358\u003c/em\u003e) likewise decreased.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec26\" class=\"Section2\"\u003e\u003ch2\u003e3.7 Functional Enrichment Analysis\u003c/h2\u003e\u003cp\u003eTo systematically elucidate the biological effects of IAA in the green phase and MeJA in the red phase on the \u003cem\u003eH. pluvialis\u003c/em\u003e transcriptome, we performed KEGG pathway and GO enrichment analyses on the identified differentially expressed genes (DEGs). The enrichment analysis results are presented as bubble plots (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eKEGG pathway enrichment results of IAA treated group are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA, in which multiple pathways related to carbon and energy metabolism were significantly enriched, including pyruvate metabolism, carbon metabolism, and carbon fixation in photosynthetic organisms. Additionally, biosynthesis of secondary metabolites and fatty acid metabolism were also significantly enriched.\u003c/p\u003e\u003cp\u003eGO functional enrichment results of IAA treated group are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA. Within biological process, the most significantly enriched term was carbohydrate metabolic process. Additional enriched biological processes included monocarboxylic acid metabolism, lipid modification, organophosphate metabolism, and organic acid metabolism. For cellular component, significantly enriched terms comprised peroxisome and microbody. In terms of molecular function, various hydrolase activities and transporter activities were enriched.\u003c/p\u003e\u003cp\u003eThe KEGG pathway and GO enrichment analysis results for DEGs of MeJA treated \u003cem\u003eH. pluvialis\u003c/em\u003e in the red phase (MeJA VS RCon) are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB, respectively. KEGG showed that metabolic pathways were the most significantly enriched pathways. Significantly enriched specific pathways included porphyrin metabolism, carbon fixation in photosynthetic organisms, carbon metabolism, and biosynthesis of secondary metabolites. Among these, biosynthesis of secondary metabolites, biosynthesis of cofactors and pentose phosphate pathway also showed enrichment.\u003c/p\u003e\u003cp\u003eGO result showed in terms of biological process, carbohydrate metabolic process was still significantly enriched. Photosynthesis-related GO terms such as photosynthesis, chlorophyll biosynthetic process, and their related sub-processes were all significantly enriched, and most genes showed downregulation. Simultaneously, the enrichment of tetrapyrrole biosynthetic process corresponded to porphyrin metabolism in KEGG. In terms of cellular component, photosystem, photosynthetic membrane, and thylakoid, all related to photosynthesis, were significantly enriched, and genes in these components were generally downregulated. Additionally, ATP synthase complex, plastid, and chloroplast membrane components also showed enrichment. In terms of molecular function, iron binding was significantly enriched. Notably, monooxygenase activity was also significantly enriched.\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec28\" class=\"Section2\"\u003e\u003ch2\u003e4.1 Interpreting biomass and astaxanthin outcomes\u003c/h2\u003e\u003cp\u003eAs a key regulator of cell division, differentiation, and proliferation, IAA has been shown to enhance microalgal growth. For example, Salama et al. [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] reported a 1.9-fold increase in \u003cem\u003eScenedesmus obliquus\u003c/em\u003e cell density under 10⁻⁵ M IAA. Such biphasic dose responses to phytohormones in microalgae have been widely documented [\u003cspan additionalcitationids=\"CR37\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Similarly, Khalili et al. [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e] demonstrated that 32 \u0026micro;M MeJA significantly enhanced astaxanthin accumulation in \u003cem\u003eChlorella sorokiniana\u003c/em\u003e. Chen et al. [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e] also reported that high concentrations of hormones such as IAA, IBA, and NAA suppressed astaxanthin production due to cellular dysfunction and increased cell mortality.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec29\" class=\"Section2\"\u003e\u003ch2\u003e4.2 Interpreting physiological parameters\u003c/h2\u003e\u003cp\u003eLow dose phytohormones act as metabolic signals to promote carbon fixation, whereas excessive doses impose osmotic or feedback inhibition on photosynthesis [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Protein content likewise increased under low to moderate hormone levels but declined markedly at 1 mg L⁻\u0026sup1;, reaching a minimum of 27.03\u0026thinsp;\u0026plusmn;\u0026thinsp;2.22 mg g⁻\u0026sup1;, implying that optimal phytohormone dosing enhances nitrogen assimilation and protein biosynthesis, while overdose may trigger protein degradation [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Chlorophyll content remained stable at low phytohormone concentrations, but was significantly reduced at 1 mg L⁻\u0026sup1;, indicating that high hormone doses exert stress on the photosystems or inhibit chlorophyll synthesis [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Carbohydrate content was elevated in all groups during the red stage, which indicated that \u003cem\u003eH. pluvialis\u003c/em\u003e would accumulate a large amount of carbohydrate under stress conditions [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Chlorophyll levels were largely suppressed in the red stage, consistent with stress-induced downregulation of chlorophyll synthesis and upregulation of astaxanthin production [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec30\" class=\"Section2\"\u003e\u003ch2\u003e4.3 DEG patterns across stages\u003c/h2\u003e\u003cp\u003eCompared to the IAA group, the expression changes in the MeJA-treated group were more drastic, with some genes having\u0026thinsp;\u0026minus;\u0026thinsp;log\u003csub\u003e10\u003c/sub\u003e(padj) approaching 300, indicating that MeJA induced a stronger transcriptional response in the red algal stage. These results suggest that IAA primarily induced a slight increase in gene expression during the green growth phase, while MeJA led to the activation and suppression of a large number of genes during the red phase.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec31\" class=\"Section2\"\u003e\u003ch2\u003e4.4 Functional interpretation of IAA responsive DEGs\u003c/h2\u003e\u003cp\u003eGenes encoding pyruvate phosphate dikinase (PPDK), such as novel.2670, novel.8652, and novel.2399, showed significant upregulation, with log\u003csub\u003e2\u003c/sub\u003eFoldChange values ranging from 1.49 to 1.57. The enzyme PPDK catalyzes the conversion of pyruvate to phosphoenolpyruvate, a key enzyme for improving CO\u003csub\u003e2\u003c/sub\u003e fixation efficiency in C\u003csub\u003e4\u003c/sub\u003e plants [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. However, in C\u003csub\u003e3\u003c/sub\u003e plants such as \u003cem\u003eOryza sativa\u003c/em\u003e, PPDK primarily acts as an auxiliary enzyme in glycolysis, balancing carbon flow towards the biosynthesis of starch, proteins, fatty acids, and amino acids, especially being highly expressed in the starchy endosperm cytoplasm [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. It may also provide ATP in hypoxic regions [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. The significant upregulation of \u003cem\u003ePPDK\u003c/em\u003e may imply that IAA induces a reprogramming of carbon metabolism in \u003cem\u003eH. pluvialis\u003c/em\u003e to more efficiently utilize carbon sources for the synthesis of biological macromolecules, thereby supporting rapid cell proliferation and biomass accumulation [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. As a photoautotrophic organism, the efficiency of carbon metabolism directly affects the growth of \u003cem\u003eH. pluvialis\u003c/em\u003e, thus this regulation is consistent with the known function of IAA in promoting growth and biomass increase [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFurthermore, genes encoding pyruvate kinase (\u003cem\u003ePK\u003c/em\u003e, \u003cem\u003egene_QJQ45_025570\u003c/em\u003e) and fructokinase (\u003cem\u003eFRK\u003c/em\u003e, \u003cem\u003egene_QJQ45_013744\u003c/em\u003e) were also significantly upregulated (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). PK is the final enzyme in the glycolysis pathway, responsible for producing ATP and pyruvate [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Its gene upregulation suggested that IAA may stimulate the rate of glycolysis in \u003cem\u003eH. pluvialis\u003c/em\u003e, thereby increasing ATP production efficiency to provide sufficient energy support for various cellular activities, particularly growth and biosynthesis [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. FRK converts fructose to fructose-6-phosphate, allowing it to enter the glycolysis pathway [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Its gene upregulation may mean that IAA promoted the ability of \u003cem\u003eH. pluvialis\u003c/em\u003e to utilize different sugar substrates, enhancing the flexibility of carbohydrate metabolism. This helped cells maintain efficient energy production and biosynthesis under different carbon source conditions, thereby supporting continuous growth [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn terms of ion and nutrient transport, IAA significantly affected the absorption and distribution of key elements in \u003cem\u003eH. pluvialis\u003c/em\u003e. \u003cem\u003eZIP9\u003c/em\u003e genes, including \u003cem\u003egene_QJQ45_017004\u003c/em\u003e and \u003cem\u003egene_QJQ45_020772\u003c/em\u003e, both showed extremely high upregulation, with log\u003csub\u003e2\u003c/sub\u003eFoldChange values of 3.54 and 1.43, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The ZIP9 protein belongs to the ZIP family of proteins, responsible for transporting zinc ions from the extracellular environment into the cell [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. Zinc is an important component of cell growth, proliferation, division, and apoptosis signaling, and also a structural component of many metalloenzymes and zinc finger transcription factors, and rapidly dividing cells usually require more zinc [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. The extremely high upregulation of \u003cem\u003eZIP9\u003c/em\u003e genes indicated that IAA strongly stimulated zinc absorption in \u003cem\u003eH. pluvialis\u003c/em\u003e to meet its demand for zinc during rapid cell proliferation and metabolic activities [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe direct impact of IAA on cell division and cycle regulation in \u003cem\u003eH. pluvialis\u003c/em\u003e was reflected at the gene expression level. \u003cem\u003eCDKB1-1\u003c/em\u003e (\u003cem\u003egene_QJQ45_023291\u003c/em\u003e) and \u003cem\u003eCYCB2-1\u003c/em\u003e (\u003cem\u003egene_QJQ45_026341\u003c/em\u003e) were both significantly upregulated, with log\u003csub\u003e2\u003c/sub\u003eFoldChange values of 1.49 and 1.56, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). CDKB is a plant-specific CDK1 ortholog that binds to cyclins to co-regulate cell division, particularly G2/M phase transition and mitosis [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. CYCB2-1 binds to CDKB1-1 to form an active complex, and both are important components of cell-cycle regulatory mechanisms [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. As an auxin, one of IAA's most significant functions is to promote cell division [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. The significant upregulation of these genes directly provided molecular evidence that IAA promoted cell proliferation in \u003cem\u003eH. pluvialis\u003c/em\u003e by accelerating cell cycle progression, which is the basis for rapid biomass accumulation [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec32\" class=\"Section2\"\u003e\u003ch2\u003e4.5 Functional interpretation of MeJA responsive DEGs\u003c/h2\u003e\u003cp\u003eAstaxanthin synthesis is a multi-step enzymatic process involving the synergistic action of several key enzymes. The gene \u003cem\u003eCRTW\u003c/em\u003e (\u003cem\u003egene_QJQ45_019472\u003c/em\u003e) encoding β-carotene ketolase catalyzes a key step in the astaxanthin biosynthesis pathway (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), responsible for converting \u003cem\u003eβ\u003c/em\u003e-carotene into canthaxanthin, a direct precursor to astaxanthin [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. \u003cem\u003eCRTW\u003c/em\u003e transcripts were significantly upregulated. \u003cem\u003eBKT3\u003c/em\u003e (\u003cem\u003egene_QJQ45_024144\u003c/em\u003e) encoding β-carotene 4-ketolase 3, was also significantly upregulated (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). This is an enzyme from the \u003cem\u003eBKT\u003c/em\u003e family which activates the core step of β-carotene conversion to astaxanthin, and its upregulation further confirms that MeJA treatment stimulates the synthesis of astaxanthin [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]. Genes annotated as \u003cem\u003eCRTZ\u003c/em\u003e (\u003cem\u003egene_QJQ45_001374\u003c/em\u003e and \u003cem\u003egene_QJQ45_030451\u003c/em\u003e, encoding β-carotene 3-hydroxylase) were significantly downregulated (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). These genes encode β-carotene hydroxylase (CHYB), a key enzyme in the astaxanthin biosynthetic pathway. CHYB hydroxylates β-carotene to β-cryptoxanthin and then to zeaxanthin, which is subsequently ketolated by β-carotene ketolase (BKT) to form adonixanthin and ultimately astaxanthin [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e]. \u003cem\u003eLCYE\u003c/em\u003e (\u003cem\u003egene_QJQ45_015099\u003c/em\u003e and \u003cem\u003egene_QJQ45_027358\u003c/em\u003e) were significantly downregulated (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). The LCYE protein (lycopene ε-cyclase) cyclizes lycopene to delta-carotene, an enzyme in the alpha-carotene branch that competes for substrates with the \u003cem\u003eβ\u003c/em\u003e-carotene branch [\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe expression patterns of these core synthesis genes reveal the precise regulation of the astaxanthin synthesis pathway by MeJA. The significant upregulation of the genes \u003cem\u003eCRTW\u003c/em\u003e and \u003cem\u003eBKT3\u003c/em\u003e promotes the conversion of \u003cem\u003eβ\u003c/em\u003e-carotene towards astaxanthin [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. Simultaneously, the downregulation of \u003cem\u003eCRTZ\u003c/em\u003e and \u003cem\u003eLCYE\u003c/em\u003e indicates that MeJA treatment inhibits bypass or competitive branches of the astaxanthin synthesis pathway, thereby reducing carbon flow to other carotenoids [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. This transcriptomic pattern strongly suggested that MeJA induced astaxanthin accumulation in \u003cem\u003eH. pluvialis\u003c/em\u003e was not merely a general activation of carotenoid synthesis. Instead, it appears to be a fine metabolic regulatory strategy that effectively shifts carbon flow from other carotenoids to astaxanthin, maximizing target product yield by specifically upregulating key genes in the astaxanthin branch while simultaneously inhibiting competitive branches [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec33\" class=\"Section2\"\u003e\u003ch2\u003e4.6 Interpreting enrichment results and integration\u003c/h2\u003e\u003cp\u003eCombining the KEGG and GO enrichment results, the effect of IAA on \u003cem\u003eH. pluvialis\u003c/em\u003e in the green phase primarily focuses on the remodeling of carbohydrate and energy metabolism [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e]. The significant enrichment of pyruvate, carbon metabolism, and carbon fixation in photosynthetic organism pathways, along with the prominence of carbohydrate metabolic processes in GO, collectively point to IAA's strong regulation of primary metabolism [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e]. IAA, as a plant hormone, is known to promote cell growth and division [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. During the highly photosynthetic green phase, enhanced carbohydrate synthesis and utilization are fundamental to supporting rapid growth [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e]. Our observed differential expression of key genes encoding enzymes such as pyruvate kinase and \u003cem\u003ePPDK\u003c/em\u003e further corroborates this inference [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. IAA-induced changes in these pathways and genes may optimize the allocation of photosynthetic products or promote the synthesis of specific carbon skeletons to support biomass accumulation [\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e]. The enrichment of peroxisomes and transporter activities suggests a fine regulation of substance transport and intracellular environment by cells under IAA signaling to adapt to growth demands [\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eMeJA, as a stress phytohormone, induced a transcriptomic response in red phase \u003cem\u003eH. pluvialis\u003c/em\u003e that was significantly different from IAA. GO and KEGG results consistently indicated that MeJA inhibited photosynthesis and primary carbon metabolism while promoting the biosynthesis of secondary metabolites [\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e]. As \u003cem\u003eH. pluvialis\u003c/em\u003e transitions from the green to the red phase, photosynthetic efficiency typically decreases to conserve energy for astaxanthin synthesis [\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e]. MeJA may act as a signaling molecule in this process, accelerating this metabolic reprogramming [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eCollectively, these findings were summarized in a mechanistic scheme (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e), explaining the principles by which IAA promotes biomass growth and MeJA boosts astaxanthin production in \u003cem\u003eH. pluvialis\u003c/em\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study systematically investigated the effects of various phytohormones on the growth and physiological parameters of \u003cem\u003eH. pluvialis\u003c/em\u003e during its green and red stages. Phytohormone application significantly altered both growth and physiological indices, and 0.01 mg L⁻\u0026sup1; IAA exhibited the greatest growth-promoting effect, whereas 0.1 mg L⁻\u0026sup1; MeJA yielded the highest astaxanthin accumulation. Further transcriptomic profiling of these two treatments revealed that IAA promoted biomass of green stage by upregulating carbon metabolism and cell cycle genes, while MeJA induced red stage astaxanthin biosynthesis via upregulation of \u003cem\u003eCRTW\u003c/em\u003e and \u003cem\u003eBKT3\u003c/em\u003e and suppression of competing genes (e.g., \u003cem\u003eCRTZ\u003c/em\u003e, \u003cem\u003eLCYE\u003c/em\u003e). These transcriptomic insights aligned with the observed enhancements in growth and pigment accumulation. These findings provide an important theoretical basis and molecular targets for utilizing hormones to regulate \u003cem\u003eH. pluvialis\u003c/em\u003e biomass and astaxanthin production.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eYang Sun:\u003c/strong\u003e Writing-original draft, Investigation, Formal analysis, Data curation; \u003cstrong\u003eYun Li:\u0026nbsp;\u003c/strong\u003eWriting – original draft, Investigation, Conceptualization, Methodology.\u003cstrong\u003e\u0026nbsp;Jing Zhang:\u003c/strong\u003e Investigation, Formal analysis, Data curation; \u003cstrong\u003eRui Zhao:\u0026nbsp;\u003c/strong\u003eFormal analysis, Data curation; \u003cstrong\u003eJiaji Zhang:\u0026nbsp;\u003c/strong\u003eConceptualization, Methodology; \u003cstrong\u003eMingxin Guo:\u003c/strong\u003eInvestigation, Methodology, Data curation;\u003cstrong\u003e\u0026nbsp;Wenjie Yan:\u003c/strong\u003e Investigation, Writing-review \u0026amp; editing, Funding acquisition; \u003cstrong\u003eXu Gao:\u003c/strong\u003e Writing-review \u0026amp; editing, Project administration, Funding acquisition.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData will be made available on request. The transcriptomic data have been deposited in NCBI (accession number: PRJNA1279618).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was financially supported by the Taishan Scholar Foundation of Shandong Province (No. tsqn202211067), the Fundamental Research Funds for the Central Universities (No. 202262002), the National Natural Science Foundation of China (42306135, 42176018) and the Open Project Program of Key Laboratory of Ecological Warning, Protection \u0026amp; Restoration for Bohai Sea, Ministry of Natural Resources (2024102).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eRen Y, Deng J, Huang J, Wu Z, Yi L, Bi Y, et al. 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Acta Physiologiae Plantarum. 2011;33(3):1043-9.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-plant-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pbio","sideBox":"Learn more about [BMC Plant Biology](http://bmcplantbiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pbio/default.aspx","title":"BMC Plant Biology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Astaxanthin, Biomass accumulation, Haematococcus pluvialis, Phytohormone","lastPublishedDoi":"10.21203/rs.3.rs-8198834/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8198834/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003e\u003cem\u003eHaematococcus pluvialis\u003c/em\u003e is recognized as the richest natural source of astaxanthin, a high-value ketocarotenoid with potent antioxidant properties. Commercial production typically relies on a two-stage cultivation strategy, comprising a green vegetative phase for biomass accumulation and a red inductive phase for astaxanthin synthesis. However, a major bottleneck in this process is the balance between cell growth and pigment accumulation, as the stress conditions required for astaxanthin synthesis often inhibit biomass productivity. Phytohormones are critical signaling molecules that regulate growth and metabolism in photosynthetic organisms. Exploring their potential to decouple these conflicting physiological processes is crucial for optimizing industrial astaxanthin production.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eIn this study, physiological and transcriptomic analyses were performed to evaluate the effects of five phytohormones (IAA, ABA, MeJA, ZT, and IPR) on \u003cem\u003eH. pluvialis\u003c/em\u003e during its two-stage cultivation. Physiological data indicated distinct hormonal requirements for each stage: 0.01 mg L⁻\u0026sup1; IAA significantly enhanced biomass in the green stage (0.37 g L⁻\u0026sup1; vs. 0.29 g L⁻\u0026sup1; in control), whereas 0.1 mg L⁻\u0026sup1; MeJA maximized astaxanthin content in the red stage (29.22 mg g⁻\u0026sup1; vs. 23.09 mg g⁻\u0026sup1; in control). Transcriptomic profiling revealed that IAA promoted vegetative growth by upregulating genes involved in primary carbon metabolism (\u003cem\u003ePPDK\u003c/em\u003e), cell cycle progression (\u003cem\u003eCDKB1-1\u003c/em\u003e), and nutrient uptake (\u003cem\u003eZIP9\u003c/em\u003e). Conversely, MeJA treatment reprogrammed metabolism towards secondary biosynthesis by upregulating key ketolase genes (\u003cem\u003eCRTW\u003c/em\u003e and \u003cem\u003eBKT3\u003c/em\u003e) while downregulating competing carotenoid pathway genes (\u003cem\u003eCRTZ\u003c/em\u003e and \u003cem\u003eLCYE\u003c/em\u003e) and photosynthesis-related transcripts.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eThis study elucidates the distinct molecular mechanisms by which phytohormones regulate the dichotomy between growth and secondary metabolism in \u003cem\u003eH. pluvialis\u003c/em\u003e. The findings suggest that the targeted application of IAA to boost biomass and MeJA to induce pigmentation offers a practical hormone guided strategy to improve two-stage astaxanthin production and provides molecular targets for further optimization.\u003c/p\u003e","manuscriptTitle":"Physiological and transcriptomic analyses reveal the effects of phytohormones on growth and astaxanthin accumulation in Haematococcus pluvialis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-15 17:28:20","doi":"10.21203/rs.3.rs-8198834/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-16T15:09:31+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-15T04:39:16+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-01T13:45:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"271357353042228766305111946756481785615","date":"2025-12-13T11:20:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"148441329132242797846431906930378006272","date":"2025-12-10T04:42:08+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-09T15:54:22+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-08T03:12:21+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-03T16:23:05+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-03T03:46:34+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Plant Biology","date":"2025-12-03T03:40:26+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-plant-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pbio","sideBox":"Learn more about [BMC Plant Biology](http://bmcplantbiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pbio/default.aspx","title":"BMC Plant Biology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8582acdf-e1ce-42bc-8352-204776aafb56","owner":[],"postedDate":"December 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-16T16:02:44+00:00","versionOfRecord":{"articleIdentity":"rs-8198834","link":"https://doi.org/10.1186/s12870-026-08577-9","journal":{"identity":"bmc-plant-biology","isVorOnly":false,"title":"BMC Plant Biology"},"publishedOn":"2026-03-14 15:59:05","publishedOnDateReadable":"March 14th, 2026"},"versionCreatedAt":"2025-12-15 17:28:20","video":"","vorDoi":"10.1186/s12870-026-08577-9","vorDoiUrl":"https://doi.org/10.1186/s12870-026-08577-9","workflowStages":[]},"version":"v1","identity":"rs-8198834","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8198834","identity":"rs-8198834","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}