Transcriptome analysis of gibberellins and abscisic acid during the flooding response in Fokienia hodginsii.

Flooding is one of the main abiotic stresses suffered by plants. Plants respond to flooding stress through regulating their morphological structure, endogenous hormone biosynthesis, and genetic signaling transduction. We previously found that Fokienia hodginsii varieties originating from Gutian exhibited typical flooding tolerance traits compared to three other provenances (Yongzhou, Sanming, Nanping), expressed as increased height, longer diameter at breast height (DBH), and smaller branch angle. Herein, the changes in endogenous gibberellins (GA) and abscisic acid (ABA) contents were measured under flooding stress in F. hodginsii, and ABA was found to decrease, whereas GA increased with time. Furthermore, the GA and ABA contents of the varieties originating from Gutian and the three other provenances were measured, and the results indicated that F. hodginsii from Gutian could respond more rapidly to flooding stress. The transcriptomes of the varieties originating from Gutian and the other three provenances were compared using RNA sequencing to explore the underlying genetic mechanisms of the flood-resistant phenotypes in F. hodginsii. The results indicated that two flood-stress response genes (TRINITY_DN142_c0_g2 and TRINITY_DN7657_c0_g1) were highly related to both the ABA and GA response in F. hodginsii.

Introduction

Water is essential for plant growth, but excess water, such as that caused by flooding, may severely limit plant growth. Under flooding conditions, plants are typically submerged or waterlogged [1, 2], and the resulting O2 deficiency can cause damage [3]. Plants have a variety of adaptive mechanisms to avoid O2 deficiency, such as aerenchyma formation, adventitious root formation, and the control of shoot, petiole, or internode elongation [1]. The adaptation of plants to long-term flooding also leads to variations in metabolism, hormone content, and enzyme systems [4]. These are considered as powerful drivers of adaptive evolution, leading to a wide range of physiological, molecular, and morphological adaptations [5, 6].

Plants balance the synthesis and transport of plant hormones and regulate the response to waterlogging via complex signaling processes [7-9]. Over the past few decades, numerous studies have shown that ABA and GA have antagonistic effects on many developmental processes in plants, including seed maturation, seed dormancy and germination, root initiation, hypocotyl and stem elongation, and flower transition. In addition, ABA, a well-established stress hormone, plays a key role in plant responses to abiotic stresses such as drought, flooding, salt and low temperature. Interestingly, recent evidence suggests that GA is also involved in plant responses to adverse environmental conditions. Thus, the complex crosstalk network between ABA and GA, mediated by different key regulatory factors, has been extensively investigated and recorded [10]. Under flooding stress, gibberellins (GAs), and abscisic acid (ABA) play the most crucial roles.

The expression of GA is induced directly or indirectly by ethylene. GAs are directly involved in escaping flooding stress in both DELLA (N-terminal D-E-L-L-A amino acid sequence) pathways [11, 12]. Ethylene and ABA are directly responsible for stomatal closure under waterlogging stress, whereas GAs are responsible for stomatal opening. In summary, GA and ABA play influential roles in resisting submergence stress, whereby ABA biosynthesis is reduced and GA signaling is induced for shoot elongation [13-15].

Fokienia hodginsii is mainly distributed in the humid climate zone of the central subtropics and is an important constituent species of subtropical evergreen broad-leaved forests and mixed natural forests of coniferous and broad-leaved species [16]. It is cultivated widely within its range as an excellent timber tree species [17]. It takes about 5–7 years from germination to flowering, with flowering in March-April and fruiting in October-November.

We established multi-generation seed orchards by means of genetic techniques, including seed source tests and determination of offspring of superior trees. During this process, we discovered that F. hodginsii from Gutian had a distinctive phenotype that differed from the other provenances.

According to historical information, the large-scale construction of reservoirs since 1956 submersed most of the region of Gutian, and the provenance of F. hodginsii from Gutian was collected in the late 1970s [18]. Therefore, we hypothesized that the phenotypes of F. hodginsii in the Gutian area may have been shaped by flooding stress. This study will reveal, for the first time, the molecular mechanism of flooding resistance-related phenotypes in F. hodginsii and enrich the understanding of the molecular basis of flooding resistance in woody plants.

Materials and methods

Different provenances of F. hodginsii

In this research, the wild type was collected from Forest Park in Fuzhou, Fujian, China (26°4′27.12″N 119°17′49.20″E); the provenance 1–Yongzhou was collected in Hunan, China (26°25′26.25″N 111°36′25.17″E); the provenance 2–Sanming was collected in Fujian, China (117°38′20.40″N 26°15′50.04″E); the provenance 3–Nanping was collected in Fujian, China (118°4′51.29″ N 27°22′57.88″E); and the provenance 4–Gutian was collected in Fujian, China (118°48′35.72″N 26°33′20.19″E).

Plant growth conditions

The seedling of F. hodginsii were grown under hydroponics in nutrient solution (10 g/L Huaduoduo 2# Peters®10-30-20+TE ICL Specialty Fertilizers) for two weeks. The growth conditions included 22°C,16-h light/8-h dark cycle, 60 μmol·m2·s-1 photon flux density, and 85% relative humidity.

Flooding assay

In the flooding stress experiment, the 2-week-old seedlings were completely immersed in purified water for 6 h/12 h/24 h/72 h, and there were three replicates per treatment and 15 samples per replicate, all treatments were performed under complete dark conditions that included 22°C and 85% relative humidity.

Simple Sequence Repeat (SSR) assay

Genomic DNA was extracted from the fresh leaves (100mg) of the four provenances of F. hodginsii using the cetyltrimethylammonium bromide (CTAB) method [19]. We used the assembled contig data (at least 200 bp) to search for hexanucleotide repeats of SSR loci. Identified SSR loci were then grouped into different classes. The SSR locus density was determined based on the frequency of SSR loci and the total length of contigs containing SSRs. Eleven pairs of SSR primers were used to analyse [20] (S1 Table). We also evaluated the motif length, loci numbers, and mean repeat numbers for the selected repetitive motifs [21].

The polymerase chain reaction (PCR) was conducted in a final volume of 20 μL containing 1 μL genomic DNA, 1 μL each of forward and reserve primer (10 μM), 10 μL of Dream TaqTM Green PCR Master Mix (Thermo Fisher Scientific, USA), and 7 μL ddH2O. The following PCR conditions were used: an initial denaturation of 95°C for 2 min; 35 cycles of 95°C for 30 s, annealing temperature of 53°C for 60 s, and 72°C for 35 s; followed by a 10-min extension at 72°C. The amplified products were evaluated on 5% agarose gel using the BIO-RAD Gel DocTM XR+. Fragment sizes were determined using Image Lab software version 6.0.

Quantification of endogenous ABA and GA3

The contents of endogenous ABA and GA3 were determined via high-performance liquid chromatography-mass spectrometry (HPLC-MS) [22].

Metabolites extraction

The samples were precisely weighed to Eppendorf tubes. After adding two small steel balls and 1000 μL of extraction solution (precooled at -20°C, acetonitrile-methanol-water, 2:2:1), the samples were vortexed for 30 s, and then were homogenized for 4 min at 40 Hz and sonicated for 5 min in ice-water bath. The homogenate and sonicate circle were repeated three times, followed by incubation at -40°C for 1 h and centrifugation at 12000 rpm (RCF = 13800(×g), R = 8.6cm) and 4°C for 15 min. An 80 μL aliquot of the clear supernatant was transferred to an auto-sampler vial for UHPLC-MS/MS analysis.

Standard solution preparation

Stock solutions were individually prepared by dissolving or diluting each standard substance to give a final concentration of 10 mmol/L. An aliquot of each of the stock solutions was transferred to a 10 mL flask to form a working standard solution. A series of calibration standard solutions were then prepared by stepwise dilution of this standard solution.

UHPLC-MRM-MS analysis

The UHPLC separation was carried out using an ACQUITY UPLC-I/CLASS(Waters), equipped with a Waters ACQUITY UPLC®BEH C18(100 × 2.1 mm, 1.7 μm, Waters). The mobile phase A was 0.1% formic acid in water, and the mobile phase B was methanol. The column temperature was set at 35°C. The auto-sampler temperature was set at 10°C and the injection volume was 2 μL. Waters Xevo TQ-S triple quadrupole mass spectrometer (Waters) was applied for assay development. Typical ion source parameters were: Capillary voltages = 3.5kV, Cone voltages = 42V, Desolvation Temperature = 650°C, Desolvation gas flow = 1000(L/Hr), Cone gas flow = 150(L/Hr), Nebuliser gas flow = 7.0(Bar) [23]. The MRM parameters for each of the targeted analytes were optimized using flow injection analysis, by injecting the standard solutions of the individual analytes, into the ESI source of the mass spectrometer. Several most sensitive transitions were used in the MRM scan mode to optimize the collision energy for each Q1/Q3 pair. Among the optimized MRM transitions per analyte, the Q1/Q3 pairs that showed the highest sensitivity and selectivity were selected as ‘quantifier’ for quantitative monitoring. The additional transitions acted as ‘qualifier’ for the purpose of verifying the identity of the target analytes. Skyline Software were employed for MRM data acquisition and processing.

Calibration curves

Calibration solutions were subjected to UPLC-MRM-MS/MS analysis using the methods described above. The y is the peak areas for analyte, and x is the concentration (nmol/L) for analyte. Least squares method was used for the regression fitting. 1/x weighting was applied in the curve fitting since it provided highest accuracy and correlation coefficient (R2). The level was excluded from the calibration if the accuracy of calibration was not within 80% -120%.

Limit of Detection (LOD) and Limit of Quantitation (LOQ)

The calibration standard solution was diluted stepwise, with a dilution factor of 2. These standard solutions were subjected to UHPLC-MRM-MS analysis. The signal-to-noise ratios (S/N) were used to determine the lower limits of detection (LLODs) and lower limits of quantitation (LLOQs). The LLODs and LLOQs were defined as the analyte concentrations that led to peaks with signal-to-noise ratios (S/N) of 3 and 10, respectively, according to the US FDA guideline for bioanalytical method validation.

Total RNA extraction, cDNA reverse transcription, and quantitative real-time (qRT) PCR

A polysaccharide polyphenol plant total RNA extraction kit (TIANGEN) and 500 mg leaves were used to extract the total RNA of the samples, extraction procedure according to instructions and a 1.2% agarose gel was used to detect the quality of the RNA and measured the RNA concentration, absorbance value, 260/230, 260/280 before reverse transcription. The strip was clear and non-dispersive, and the brightness of the 28S band was about twice as bright as the 18S band, confirming that the extract could be used for subsequent analysis.

For the RT-qPCR(QuantStudio™ 7 Flex), 1 μg of total RNA was treated with DNase Ⅰ and used for cDNA synthesis with a YEASEM Hifair®Ⅱ 1st Strand cDNA Synthesis SuperMix for qPCR Kit (CAT:1123ES60). ACT7 was selected as internal marker gene for real-time fluorescence quantification, and the primers were designed using the Primer 3.0 website. The primers used in this study are listed in S1 Table. The PCR was performed with SYBR-Green PCR Mastermix (CAT:11202ES08). The expression levels of the tested genes were estimated using the relative 2−△△ method [24].

RNA-Seq analysis and bioinformatics

The samples for RNA-Seq included the 2-week-old seedlings treated with 1 μM GA3 and 20 μM ABA [25, 26]. The seedling were grown under hydroponics, the 1 μM GA3 and 20 μM ABA treatments through adding the appropriate amount of powder to the culture solution to achieve the required concentration. Three varieties of seedlings from the same provenance were mixed together and frozen in liquid nitrogen. There were three biological replicates per treatment and three samples per replicate. The RNA extractions and RNA-Seq analysis of the leaves from F. hodginsii followed previous methods [27].

RNA-Seq was performed using the Illumina NovaSeq 6000 with 6G of data and Poly (A) RNA from 1 mg total RNA or purified mRNA and purified m6A-containing fragments were used to generate the cDNA libraries, respectively, according to TruSeq RNA Sample Prep Kit protocol. The sample library type was a eukaryotic unstranded specific transcriptome library. The trimming of raw data resulted in only the uniquely aligned reads, and a fold-change in expression of >1.3 and a false-discovery rate (FDR) <0.01 were set as the thresholds for designating the differentially expressed genes [28].

For the raw reads obtained from transcriptome sequencing, cut adapt and Perl scripts were used to remove splice sequences as well as low-quality sequences with a length <100 bp, <5% unknown bases, and bases with a quality value Q≤30 accounting for more than 20% of the whole sequence in the raw data, followed by verification of data quality using FASTQ. Analysis without a reference transcriptome was used, as no reference genome was available or the genome annotation information was incomplete.

The unigenes were annotated and classified according to GO (Gene Ontology) [2]. Based on this, differentially expressed genes were identified and subjected to GO term enrichment analysis. All samples were filtered using the transcriptome assembly software Trinity (Broad Institute, USA), and the resulting clean reads were assembled from scratch to obtain long fragments (contigs), which were assembled into sequences that could not be further extended at both ends, which were then finally normalized to unigenes. The unigenes were then evaluated for assembly quality, including length, GC content (GC%), and N50 [29].

The obtained unigenes were annotated against GO for functional annotation and classification, and differential expression analysis was performed on unigenes from different groups to find differentially expressed genes among the samples from the different localities of F. hodginsii.

Statistical analyses

All data are from biological replicates. Data were analysed using one-way analysis of variance (ANOVA) tests (Tukey’s post-hoc test), * and ** indicate significant differences (P<0.05 and P<0.01, respectively). Pairwise comparison was performed by Welch’s t-test and different upper and lowercase letters indicated the variability analysis of the amount of change in the same object at different times. GraphPad v.8 was used to perform statistical analysis of the data.

Results

Phenotype of F. hodginsii from four provenances

The phenotypic data of F. hodginsii from four provenances collected at roughly the same latitude were analyzed (Fig 1A), and thus the annual rainfall and average temperature were also approximately the same. Based on phenotypic observation and data analysis, we found that F. hodginsii from Gutian was significantly different from the other provenances. The average clear height of F. hodginsii from P1, P2, P3, and P4 was 4.31 m, 4.36 m, 2.58 m, and 9.45 m, respectively, with P4 being the tallest and also significantly different from the other three. In terms of diameter at breast height (DBH), P1 was 26.65 cm, P2 was 29.16 cm, P3 was 30.18 cm, and P4 was 52.56 cm. P4 also had the greatest DBH and was highly significantly different from the others. In terms of branching angle, P4 was 72.53° and was smaller than the other three, which were 85.65°, 82.14°, and 73.75°. There was a highly significant difference between P1 and P4 and a significant difference between P2 and P4, but no significant difference was detected between P3 and P4. In general, these features are consistent with flood tolerance (Fig 1B).

Fig 1

Geographical distribution and phenotypic differences among F. hodginsii from four provenances.

(A) The geographical distribution of the four provenances, almost at the same latitude. Provenance 1 is from Yongzhou, Hunan (average temperature 18.6°C, annual rainfall 1507 mm); provenance 2 is from Sanming, Fujian (average temperature 18.3°C, annual rainfall 1688 mm); provenance 3 is from Nanping, Fujian (average temperature 18.3°C, annual rainfall 1627 mm); provenance 4 is from Gutian, Fujian (average temperature 18.3°C, annual rainfall 1579 mm). This picture is from USGS National Map Viewer (https://apps.nationalmap.gov/viewer/). (B) The phenotypic characteristics of the four provenances were statistically analyzed based on height (m), diameter at breast height (cm), crown diameter (m), clear height (m), and branch angle (°). Height is measured as the distance from the root on the ground to the top of the tree. DBH measures the diameter of a tree 1.3-m above the ground. Crown diameter is the arithmetic mean of the maximum and minimum numbers. Clear height calculates the height of the trunk. Branch angle represents the angle of the outermost branch of the crown. Data for each index were collected from 15 samples. * and ** indicate significant differences (P<0.05 and P<0.01, respectively) relative to P4 in height, diameter at breast height, crown diameter, clear height, and branch angle, based on one-way ANOVA with multiple comparisons using Tukey-test.

Changes in endogenous ABA and GA3 of F. hodginsii under flooding stress

To verify whether the endogenous ABA and GA3 in F. hodginsii changed in response to flooding stress, the changes in ABA and GA3 in wild-type F. hodginsii (Fuzhou local provenance) were detected by water flooding at four time points of 6 h, 12 h, 24 h, and 72 h. We found that the ABA content gradually decreased and the GA3 content gradually increased with time in the wild type after 6 h of flooding treatment (Fig 2).

Fig 2

The flooding stress treatments increased endogenous GA3 and decreased endogenous ABA in the F. hodginsii seedings.

The tested seedings were local varieties of Fuzhou and were cultivated hydroponically for 2 weeks. The hydroponic solution was 10 g nutrient solution mixed with 1 L water. For the flooding stress treatments, the seedings were submerged in water for 6 h/12 h/24 h/72 h, the leaves were collected, and the endogenous ABA and GA3 were determined. Three independent experiments were performed, each with three biological replicates. Data are the means of three biological repetitions ± SD, n = 9. Different capital letters (A, B, C) indicate the significance of GA3 content at different treatment times compare to 6 h (p < 0.05), while different lowercase letters (a, b, c) indicate the significance of ABA content at different treatment times relative to 6 h (p < 0.05), Tukey-test was used for comparison between data.

On the basis of these observations, we quantified the endogenous ABA and GA3 contents of the three varieties of F. hodginsii from Gutian (G007, G008, G011) and the three varieties from Yongzhou (E010, E015, E025), as these two provenances exhibited significant phenotypic differences. The quantitative analysis revealed that the endogenous ABA content of all three varieties of F. hodginsii from Gutian was lower than that of the three varieties from Yongzhou, while in terms of GA3 content, all three varieties from Gutian had higher contents than the three varieties of Yongzhou (P<0.05) (Fig 3A and 3B).

Fig 3

Quantification of endogenous GA3 and ABA in F. hodginsii and changes in response to flooding stress treatments in provenance 1 (P1) and provenance 4 (P4).

(A&C) Three varieties of P1 (E010, E025, E015) and P4 (G007, G008, G011) showing the amount of endogenous ABA indicating the change trend after 12 h/24 h/72 h flooding stress treatments compared with 6 h. (B&D) The amount of endogenous GA3 in E010, E025, E015, and G007, G008, G011, and the change in GA3 in the seedings subjected to 12 h/24 h/72 h flooding stress treatments compared with 6 h. The data are shown as means ± SD (n = 3). * and ** indicate significant differences (P<0.05 and P<0.01, respectively) between P1 and P2 in different times, based on one-way ANOVA with multiple comparisons using Tukey-test.

Next, the six varieties were subjected to flooding treatments for 6 h, 12 h, 24 h, and 72 h to detect the changes in endogenous ABA and GA3. The results showed that the endogenous ABA content of both provenances showed a decreasing trend with the duration of the flooding treatment, but the three varieties from Gutian changed more rapidly, and the content of endogenous ABA was obviously less than in the three varieties from Yongzhou after 6 h. In terms of the changes in endogenous GA3, the three varieties from Yongzhou exhibited no significant change and only increased slightly after 24 h of flooding treatment. However, the three varieties from Gutian changed rapidly, reaching a plateau stage after 12 h of flooding treatment, with a relative GA amount that was 3.25 times higher than that in Yongzhou (Fig 3C and 3D).

Transcriptomic analyses reveal different ABA- and GA-related response genes

The transcriptomes of three varieties of F. hodginsii from P4-Gutian (G007, G008, G011) were compared with three varieties from P1-Yongzhou (E010, E015, E025), and a total of 6281 differentially expressed genes were screened. There were 366 upregulated genes and 227 downregulated genes, accounting for 5.8% and 3.6%, respectively. GO functional analysis was performed by identifying the 15 functional categories with the most significant enrichment according to the upregulated and downregulated genes.

In the GO enrichment analysis of differentially upregulated genes in P4 compared to P1, 10 signaling pathways were identified as ABA-related genes (P<0.001) and were mainly related to biosynthesis, mitosis, and hormonal response. Among the upregulated genes, genes in the regulation of mitotic spindle organization and activation of protein kinase activity had a gene ratio of 0.75, which was the highest (Fig 4A). Eleven signaling pathways which were GA-related genes were detected in the GO enrichment analysis of the upregulated genes and were mainly involved in the metabolic and catabolic activities of life and the redox of cells and hormonal response, and the glycine catabolic process had the highest gene ratio of 0.6 (Fig 4B).

Fig 4

GO term enrichment analysis and screening of GA3 and ABA related major regulatory genes.

(A) and (B) 6281 differentially expressed genes were screened (P<0.05, fold-change ≥ 1) via the Illumina RNA-Seq results of P1 (E010, E025, E015 from provenance 1) and P4 (G007, G008, G011 from provenance 4). The RNA-Seq samples (n = 9) originated from hydroponically cultivated 2-week-old seedings, which were treated with 1 μM GA3 and 20 μM ABA for 24 h. The GO analysis was based on the 15 regulatory pathways that had greater significant enrichment of upregulated and downregulated genes (arranged by P-value). The abscissa represents the P-value of the different genes in this functional classification. The ordinate represents different GO function classifications. The size of the dots represents this pathway gene number in relation to the total, and the color represents the enrichment. (C) and (D) Two crosstalk genes (TRINITY_DN142_c0_g2, TRINITY_DN7657_c0_g1) between ABA and GA3 were selected from the regulation of salicylic acid-mediated, cellular response to salicylic acid stimulus, and regulation of defense response signaling pathway. P1 (E010, E025, E015) and P4 (G007, G008, G011) were treated with flooding stress for 24 h, and the samples from each provenance were combined. The relative expression of the crosstalk genes was indicated via qPCR (2−△△CT). The data are shown as means ± SD (n = 3). ** indicates significant differences (P<0.01) based on one-way ANOVA with multiple comparisons using Tukey-test.

Eight related genes were identified by screening overlapping upregulated and downregulated genes in the regulation of salicylic acid mediated, cellular response to salicylic acid stimulus, and regulation of defense response signaling pathways, as indicated in S2 Table. Through designing primers for these eight genes and RT-qPCR, two genes with significant changes in the regulation of ABA and GA3 responses were selected from the quantification results. After 20 μM ABA treatment for 24 h, the expression of TRINITY_DN142_c0_g2 and TRINITY_DN7657_c0_g1 in P4 was lower than in P1 and there was a highly significant difference (Fig 4C). Following treatment with 1 μM GA3 for 24 h, theTRINITY_DN142_c0_g2 and TRINITY_DN7657_c0_g1 genes of P1 were more highly expressed than P4 and were highly significantly different (Fig 4D).

Discussion

Land plants are sensitive to waterlogging, which hinders the growth and survival [30, 31]. Numerous studies have reported that physiological and molecular alterations occur in plants under flooding conditions [32-34]. RNA-Seq is an effective method for assessing transcriptomic changes under waterlogging and can assist in elucidating waterlogging tolerance mechanisms in plants.

Previous studies found that F. hodginsii from Gutian possessed some phenotypes related to resistance to flooding, and the phenotypic characteristics of resistance to flooding were also more pronounced than in the other three provenances (Yongzhou, Sanming, Nanping). Genetic diversity analysis of P1, P2, P3, and P4 by SSRs revealed that P4 also had higher genetic diversity than the other three provenances. This suggested that P4 was more adaptable than P1, P2, and P3.

Phytohormones play a central role in flooding stress conditions for plant survival including morphological, anatomical, biochemical, molecular, and signaling mechanisms. GAs and ABA have crosstalk roles during submergence stress in plants [35], whereby ABA biosynthesis is reduced and GA signaling is induced [13]. The endogenous hormone contents and the associated change trends were explored by conducting flooding treatments in three varieties of P1 (E010, E015, E025) and P4 (G007, G008, G011). We found that the ABA content in G007, G008, and G011 was lower than in E010, E015, and E025. In terms of the content of GA3, G007, G008, and G011 were all higher than E010, E015, and E025. Additionally, G007, G008, and G011 exhibited more visible trends than E010, E015, and E025 in terms of both ABA and GA3. This is consistent with previous findings [14]. Based on these results, we infer that the degree of flooding tolerance is more prominent and the response to flooding stress is more dramatic in F. hodginsii from Gutian.

Here, 15 regulatory pathways that had greater significant enrichment of upregulated and downregulated genes which were arranged by P-value were identified using RNA-Seq and mainly related to biosynthesis, mitosis, the metabolic and catabolic activities of life, the redox of cells and hormonal response. Three of these signaling pathways are present in both up- and down-regulated gene expression, they were regulation of salicylic acid-mediated, cellular response to salicylic acid stimulus and regulation of defense response, which were closely related to ABA and GA3.

Many adaptation mechanisms are related to changes in ABA and GA metabolism and signaling [36-38]. ABA has a main role in regulating the stomata by adjusting the size of the guard cells and regulating the water potential in plants. Thus, ABA is considered to be a key hormone in water stress responses [39, 40]. ABA can be perceived in the guard cells, and ABA signaling can lead to a reduction in the turgor and volume of the guard cells via the efflux of anions and potassium ions and the gluconeogenic conversion of malate into starch, which finally results in stomatal closure; a process that has been previously well illustrated [41, 42]. GAs is one of the essential plant hormones regulating growth and development. GAs regulates multiple processes in plant growth and development, mainly by controlling the size and number of cells [43]. These functional modulations allow them to play an important role in plant defense response.

Ethylene (ET) is a gaseous hormone and its accumulation is an important way to response to flooding stress. It has long been acknowledged as the main regulator of plants’ responses to reduced O2 conditions [44-46]. Numerous studies show that ET signaling uncouples the catabolism of ABA, and constitutes a putative independent hypoxia signaling pathway [47]. Moreover, any effect on ABA signaling affects GA signaling, as ABA promotes the stabilization of the negatively regulated proteins of DELLA [48]. However, none of the above signaling pathways are associated with ethylene. Possible reasons are that ethylene is a gaseous hormone, which is volatile in air, and that it accumulates more in plant roots and fruits and less in leaves [49].

In addition to the plant defense response, two other signaling pathways were associated with salicylic acid (SA). In plants, SA is a common phenolic compound, which regulates cells’ antioxidant mechanism through inducing the expression of stress-related genes to resist to stress [50-52]. Some experiments have shown that Salicylic acid, as a signal substance, can induce changes in physiological characteristics by increasing the activities of ethanol dehydrogenase, proline, POD and CAT. Thus, protecting leaves and root membranes from damage and maintaining photosynthesis in leaves as well as the activities of root [53]. Previous studies have investigated the function of hormones or salicylic acid as a single component in response to flooding stress, these signaling pathways provide a reference and reference for multi-omics studies of flooding stress.

Based on the above signaling pathway, we obtained eight related genes by screening for overlapping upregulated and downregulated genes from the three signaling pathways. Two genes, including TRINITY_DN142_c0_g2 and TRINITY_DN7657_c0_g1, which exhibited significant changes in the regulation of ABA and GA responses, were selected based on the results of the RT-qPCR. Following treatment with 1 μM GA3 and 20 μM ABA for 24 h, the relative expression of these two genes in F. hodginsii of P1 was significantly higher than in P4. Treatment with 20 μM ABA resulted in the opposite. This indicated that F. hodginsii from Gutian had a better ability to adapt to the flooding stress. The TRINITY_DN142_c0_g2 and TRINITY_DN7657_c0_g1 genes may be central to its flooding resistance and might also constitute the basis of its adaptive evolution.

Conclusion

When plants are exposed to flooding stress, they initiate various defensive measures, such as stomatal closure, shoot growth, and petiole or internode elongation control under both escape and quiescence strategies. In previous experiments, we found that the varieties of F. hodginsii that originated from Gutian were taller and had a greater DBH but smaller branching angle compared with three other provenances originating from Yongzhou, Sanming, and Nanping. These features were consistent with flood tolerance, suggesting that the F. hodginsii varieties originating from Gutian possessed typical flooding tolerance traits compared to the other three provenances. We then used HPLC technology to measure the dynamics in endogenous GA3 and ABA content, which indicated that ABA decreased but GA3 increased with time under flooding stress. Furthermore, the GA3 and ABA contents of the varieties originating from Gutian and the other three provenances were measured, which indicated that the F. hodginsii from Gutian could respond more rapidly to flooding stress. We then immediately compared the transcriptomes of the varieties originating from Gutian with the other three provenances via RNA-Seq. We identified eight related genes by screening for overlapping upregulated and downregulated genes in the regulation of salicylic acid-mediated, cellular response to salicylic acid stimulus, and regulation of defense response signaling pathways. To explore the underlying genetic mechanisms of the flood-resistant phenotypes, based on the primers designed for these eight genes and RT-qPCR, two genes (TRINITY_DN142_c0_g2 and TRINITY_DN7657_c0_g1) with significant changes in the regulation of ABA and GA responses were selected from the quantification results. Both genes were highly related to ABA and GA response and thus may be the reasons for phenotypic variation of F. hodginsii. The analysis of phenotypic differences in F. hodginsii revealed the intrinsic molecular regulatory mechanisms and provided some reference value for resistance breeding and adaptive evolution.

Genetic diversity and phylogenetic evolution analysis of four provenance.

SSR (Simple Sequence Repeat) molecular markers were used to predict the genetic diversity among provenances 1–4. Using the DNA of provenances 1–4 as templates, SSR 1–11 primers were used to amplify sequences via PCR. Based on the amplified sequences, alleles frequency of provenance 1–4 were explored. The different colors represent the length of fragment separation, and the dendrogram indicates the genetic evolutionary distance.

(TIF)

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List of primers for SSR and RT-qPCR used in this research.

(DOCX)

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Overlapping genes of ABA and GA.

(DOCX)

Click here for additional data file.

4 Oct 2021

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Comments to the Author

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Reviewer #1: Yes

Reviewer #2: No

Reviewer #3: Partly

**********

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Reviewer #1: Yes

Reviewer #2: No

Reviewer #3: Yes

**********

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Reviewer #1: Yes

Reviewer #2: No

Reviewer #3: No

**********

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Very nice paper on flooding tolerance! The data support is very clear. My main comments are about the grammar and wording structure, and to especially state the research gap this study fills.

Line 33: For “other three provenances” it may be helpful to specify the country of origin within introduction of the species.

Line 66: Missing a statement on the aim of this study at the end of the introduction section. What is novel about this research? Has physiological and molecular characterizations of F. hodginsii not been done before?

Line 78: Is the flooding assay done with some light or complete darkness?

Line 173: I feel the title “Different ABA- and GA-related response genes” is too simple and can be more elaborated, like “Transcriptomic analyses reveal different…”

Line 181: Missing hyphen “ABA related genes”

Line 228: Needs space between “1(“

Line 228: The jump between paragraphs from GA to SUB1 does not connect with the first sentence. It is more clear when the next sentence mentions GA. This may not be necessary, but perhaps there can be a better transition between the paragraphs.

Line 236: By the end of the SUB1 paragraph, it does not clarify how the SUB1 work relates to the data obtained. Perhaps a sentence can be added linking the connections between the studies, or how the SUB1 data can help support the current data.

Line 255: Before you mention the measurements of ABA and GA, you can highlight why you performed this work, the purpose, or how the research is novel. This is interpreted but not clearly stated.

Fig 1A: The black text in the map is hard to read and the font is small in the box.

Fig 1B: Since the squares are most strongly stacked and slightly bigger than the other symbols, perhaps showing a bar or box & whisker graph might make the data points more clear and easier to interpret.

Fig 2: Missing axis title for hours of submergence.

Fig 3A & C: It would help to draw a line under the provenance 1 & 4 samples in the graph.

Fig 3B & D: Missing axis title for hours of submergence.

Table S1: FJB91-R format needs to be centered.

More experimental support of course would be great, such as functional validation of the RNA-seq dataset, but for this level of publication I would not request any additional experiments.

Reviewer #2: The manuscript entitled 'Transcriptome analysis of gibberellins and abscisic acid during the flooding response in Fokienia hodginsii' describes the transcriptional and hormonal response of a Cupresaceaous tree to a 72h submergence period.

There are several critical aspects that need clarification:

1) In the M&M section says F. hodginsii seedlings were grown in hydroponics and subsequently (2 weeks after germination) completely immersed in water. The same hydroponic medium was used? Tap or clean water (potentially leading to the dilution of nutrients and a nutritional imbalance)? Seedlings were transplanted to soil prior to submergence? This needs to be further elaborated. O2 levels need to be measured in these conditions.

2) RNAseq data has to be deposited in a publicly available repository (e.g. NCBI SRA or similar) before manuscript is accepted for publication or upon acceptance, not later.

3) Authors recorded phenotypic data from F. hodginsii accessions collected from four different locations, but do not provide data that link these phenotypic traits with improved or decreased tolerance to anoxia. Moreover, phenotype responses to hypoxia were not measured or considered.

4) Typical responses to hypoxia are missing (ADH, PDC, SUSY upregulation) as well as induction of ERFVII homologs. This needs to be clearly present in the manuscript.

5) Statistical analysis is missing in Figures 1, 2 and 3

6) RNAseq results need to be provided as supplementary data, including annotation and statistical analyses.

7) Effects of flooding on GA and ABA signaling pathways needs to be supported also by transcriptional data. What GA was/were measured? What internal standards were used as surrogates?

Major aspects:

Ethylene has long been acknowledged as the main regulator of plants' responses to reduced O2 conditions, therefore, it cannot be excluded from the discussion. Interactions of ET with GA and ABA pathways in hypoxic conditions have been recently discussed (González-Guzmán et al. 2021).

A proper phenotypic evaluation of accessions in response to hypoxic conditions is required.

The proposal that SA signaling is involved is interesting but needs certain experimental backup. What happens with SA levels? What happens with typical SA-linked responses such as PR1 homolog overexpression? Could authors provide a tentative close relative of TRINITY_DN142_c0_g2 and TRINITY_DN7657_c0_g1?

L214-217 'suspect' is not scientific. Authors must provide plausible explanations well-grounded on empirical results.

L228-236 SUB1A is a non-canonical ERFVII which is not regulated by the N-end rule pathway and is present in rice. Does F. hodginsii has any potential ortholog? If not, these is out of context here. Other canonical ERFVII are better candidates to link ET and ABA or GA signaling (e.g. Arabidopsis RAP2.3, for instance).

For the sake of transparency and to allow replicability of results, transcriptional results must be presented in full, including annotation RPKM and statistics (FDR corrected) as supplementary.

To confirm that low O2 responses were activated under the experimental conditions described, expression of ET/O2 signaling ortholog elements must be presented along with typical anoxia survival responses (expression and/or enzyme activity of ADH, PDC and SUSY). Likewise, signaling pathways for GAs and ABA also need to be presented (expression of ABA receptors, PP2Cs, SnRKs and ABA-responsive genes such as ABI5, DREB2A, RD29, etc...).

Minor aspects:

L190 Where is Table 2, maybe authors refer to supporting Table S2. Please, amend.

Please, use the same coloring in Figures 3 and 4, as it stands is misleading.

Reviewer #3: Dear Dr. Tengfei Zhu,

I have read through the manuscript entitled "Transcriptome analysis of gibberellins and abscisic acid during the flooding response in Fokienia hodginsii”. The manuscript can provide new information in understanding the flooding tolerance mechanisms in non-model crops. With that in mind I would like to give the following comments and questions regarding the manusript.

1. Components of the PCR reaction volume doesn’t add up to 20. list them all. (Line 89)

Used GA standard/s (if used) not specified. There are various forms of GA available in the plants system, which one did you measure? (Line 95-102)

2. The gel electrophoresis will not tell you much/precisely the quality of the RNA. Have you run a the samples on the bioanalyzer? or Nano drop absorbance for these purposes? (Line 105)

3. what reference genome did you use to design the primers? (Line 109)

which qRT-PCR instrument did you use? (Line 108-113)

4. consistency in writing terminologies. For example qRT-PCR (Line 108) vs RT-qPCR (supporting information line 9. Look into the rest of the manuscript for consistency

5. How did you calculate the relative GA and ABA amounts in Fig. 2 and 3 (Line 14-19; 22-28)? it should be elaborated in the figure legends and method section.

6. I recommend to include the hormone analysis data, at least in the supporting information section of the manuscript.

7. Can the authors reanalyse the transcriptomic data considering the quality check used at the begining of the analysis were Q10. It should be at least Q30 with inferred base call accuracy of 99.99% rather than 90% in Q10 (Line 124).

8. How do you explain that you have supplemented the plants to be analyzed for RNAseq with GA3 but quantification from the other set of experiment stated only endogeneous GA. Can you reanalyze the hormone data by including other GA forms rather than stating indogenoeus GA, considering their que-specific responses?

Regards,

**********

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Reviewer #1: Yes: Elaine Yeung

Reviewer #2: No

Reviewer #3: No

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29 Nov 2021

Journal Requirement:

1. Please address the comments of all reviewers. In particular, please provide the accession number for your sequences from RNA-seq (which should be deposited to a database prior to resubmission of a revision of this manuscript, but can be made publicly available after acceptance).

Response: The sequence data reported in this study have been deposited in the Genome Sequence Archive in BIG Data Center, Beijing Institute of Genomics (BIG), Chinese Academy of Sciences, under accession numbers CRA005262, CRA005262 that are publicly accessible at https://bigd.big.ac.cn/gsa/browse/CRA005262.

2. Please include full details of statistical analyses in the Materials and Methods.

Response: Line 175. We have added the statistical analyses in the Materials and Methods.

3. The text that needs to be addressed involves the Discussion section.

Response: We have reworked the sentences in the discussion section.

4. Thank you for stating the following financial disclosure:

" The "Eagle Plan" Young Talent Project of Fujian Province."

At this time, please address the following queries:

a) Please clarify the sources of funding (financial or material support) for your study. List the grants or organizations that supported your study, including funding received from your institution.

b) State what role the funders took in the study. If the funders had no role in your study, please state: “The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.”

c) If any authors received a salary from any of your funders, please state which authors and which funders.

d) If you did not receive any funding for this study, please state: “The authors received no specific funding for this work.”

Response: We have amended statements in cover letter.

5. Please include your full ethics statement in the ‘Methods’ section of your manuscript file. In your statement, please include the full name of the IRB or ethics committee who approved or waived your study, as well as whether or not you obtained informed written or verbal consent. If consent was waived for your study, please include this information in your statement as well.

Response: No ethics statement need to claim in this manuscript.

6. We note that Figure 1 in your submission contain [map/satellite] images which may be copyrighted. All PLOS content is published under the Creative Commons Attribution License (CC BY 4.0), which means that the manuscript, images, and Supporting Information files will be freely available online, and any third party is permitted to access, download, copy, distribute, and use these materials in any way, even commercially, with proper attribution. For these reasons, we cannot publish previously copyrighted maps or satellite images created using proprietary data, such as Google software (Google Maps, Street View, and Earth).

Response: we have supplied a replacement figure that complies with the CC BY 4.0 license from USGS National Map Viewer (public domain): http://viewer.nationalmap.gov/viewer/.

Response to reviewer:

Reviewer #1.

1. Line 33: For “other three provenances” it may be helpful to specify the country of origin within introduction of the species.

Response: Line 27. This is a very good suggestion. We have already added the regions of origin to specify “other three provenances”.

2. Line 66: Missing a statement on the aim of this study at the end of the introduction section. What is novel about this research? Has physiological and molecular characterizations of F. hodginsii not been done before?

Response: Line 74. Thank you for reminding. We have added the statement at the end of introduction.

As far as I know, the research on F. hodginsii is mainly focused on genetic evolution and metabolites, and there is very little gene function research.

3. Line 78: Is the flooding assay done with some light or complete darkness?

Response: Line91. It was conducted in complete darkness to minimize the o2- contamination and we have added the condition of this treatment.

4. Line 173: I feel the title “Different ABA- and GA-related response genes” is too simple and can be more elaborated, like “Transcriptomic analyses reveal different…”

Response: Line 222. Thanks for this kind advice, we have changed the title “Different ABA- and GA-related response genes” to “Transcriptomic analyses reveal different ABA- and GA-related response genes”.

5. Line 181: Missing hyphen “ABA related genes”

Response: Line 230. We deeply sorry about this mistake, we have added the hyphen.

6. Line 228: Needs space between “1(“

Response: This less relevant paragraph has been removed based on the comments of other reviewers.

7. Line 228: The jump between paragraphs from GA to SUB1 does not connect with the first sentence. It is more clear when the next sentence mentions GA. This may not be necessary, but perhaps there can be a better transition between the paragraphs.

Response: This less relevant paragraph has been removed based on the comments of other reviewers.

8. Line 236: By the end of the SUB1 paragraph, it does not clarify how the SUB1 work relates to the data obtained. Perhaps a sentence can be added linking the connections between the studies, or how the SUB1 data can help support the current data.

Response: This less relevant paragraph has been removed based on the comments of other reviewers.

9. Line 255: Before you mention the measurements of ABA and GA, you can highlight why you performed this work, the purpose, or how the research is novel. This is interpreted but not clearly stated.

Response: Line 49. In the background section, we have added an elaboration on the selection of ABA and GA.

Fig 1A: The black text in the map is hard to read and the font is small in the box.

Response: Corrections have been made.

Fig 1B: Since the squares are most strongly stacked and slightly bigger than the other symbols, perhaps showing a bar or box & whisker graph might make the data points more clear and easier to interpret.

Response: Corrections have been made.

Fig 2: Missing axis title for hours of submergence.

Response: Corrections have been made.

Fig 3A & C: It would help to draw a line under the provenance 1 & 4 samples in the graph.

Response: Corrections have been made.

Fig 3B & D: Missing axis title for hours of submergence.

Response: Corrections have been made.

Table S1: FJB91-R format needs to be centered.

Response: Corrections have been made.

Reviewer #2.

1. In the M&M section says F. hodginsii seedlings were grown in hydroponics and subsequently (2 weeks after germination) completely immersed in water. The same hydroponic medium was used? Tap or clean water (potentially leading to the dilution of nutrients and a nutritional imbalance)? Seedlings were transplanted to soil prior to submergence? This needs to be further elaborated. O2 levels need to be measured in these conditions.

Response: Line 89. F. hodginsii seedlings were cultured used the same hydroponic medium and the water used treated was purified water, these have been added in the M&M section. About O2, Flooding is a complex abiotic stress, anoxia is one of the important stress caused by flooding, it is reasonable to clarify the O2 levels in different conditions. But in our case, we want provide a basic understanding of the flooding, the integrated stress, other than part of it. Moreover, O2 level was not always mentioned in similar works, partly because quantify the O2 levels may miss lead the audience that anoxia can be isolated from the flooding stress.

2. RNAseq data has to be deposited in a publicly available repository (e.g. NCBI SRA or similar) before manuscript is accepted for publication or upon acceptance, not later.

Response: The sequence data reported in this study have been deposited in the Genome Sequence Archive in BIG Data Center, Beijing Institute of Genomics (BIG), Chinese Academy of Sciences, under accession numbers CRA005262, CRA005262 that are publicly accessible at https://bigd.big.ac.cn/gsa/browse/CRA005262.

3. Authors recorded phenotypic data from F. hodginsii accessions collected from four different locations, but do not provide data that link these phenotypic traits with improved or decreased tolerance to anoxia. Moreover, phenotype responses to hypoxia were not measured or considered.

Response: Thanks for your advices. As we mentioned earlier, anoxia is one of the stress caused by flooding, not all of it. And, it was well studied that controlling of shoot, petiole, or internode elongation were the phenotypes greatly associated with flooding stress. Moreover, it is impossible to collect phenomics data other than height, diameter at breast height, crown diameter, clear height, and branch angle in the field, considering the complex working condition and poor operability. In this work, phenotypic data from the field is only the hint to leading this research. The GA and ABA content in different conditions were the real “phenotypic data” to explain the transcriptome results.

4. Typical responses to hypoxia are missing (ADH, PDC, SUSY upregulation) as well as induction of ERFVII homologs. This needs to be clearly present in the manuscript.

Response: The RNA-seq of F. hodginsii was no reference transcriptome, the information of the proteins available is limited, so we do not have the conditions to explore these target proteins, and we can analyze them according to our current results when the reference genome information is released.

5. Statistical analysis is missing in Figures 1, 2 and 3

Response: Thanks, corrections have been made.

6. RNAseq results need to be provided as supplementary data, including annotation and statistical analyses.

Response: Sequencing analysis and annotations have been uploaded to the appendix.

7. Major aspects:

Ethylene has long been acknowledged as the main regulator of plants' responses to reduced O2 conditions, therefore, it cannot be excluded from the discussion. Interactions of ET with GA and ABA pathways in hypoxic conditions have been recently discussed (González-Guzmán et al. 2021).

Response: Line 283. We have added the interactions of ET with GA and ABA pathways in hypoxic conditions in the discussion section.

A proper phenotypic evaluation of accessions in response to hypoxic conditions is required.

Response: Flooding is a complex abiotic stress, anoxia is one of the important stress caused by flooding, it is reasonable to clarify the O2 levels in different conditions. But in our case, we want provide a basic understanding of the flooding, the integrated stress, other than part of it. Moreover, O2 level was not always mentioned in similar works, partly because quantify the O2 levels may miss lead the audience that anoxia can be isolated from the flooding stress.

The proposal that SA signaling is involved is interesting but needs certain experimental backup. What happens with SA levels? What happens with typical SA-linked responses such as PR1 homolog overexpression? Could authors provide a tentative close relative of TRINITY_DN142_c0_g2 and TRINITY_DN7657_c0_g1?

Response: Line 291. Thank you for the affirmation. We have added in the Discussion section about the functions played by SA in abiotic stresses and future research will also be conducted to explain this issue.

L214-217 'suspect' is not scientific. Authors must provide plausible explanations well-grounded on empirical results.

Response: Line 265. Thank you for the advice, we have changed the 'suspect' to 'infer'.

L228-236 SUB1A is a non-canonical ERFVII which is not regulated by the N-end rule pathway and is present in rice. Does F. hodginsii has any potential ortholog? If not, these is out of context here. Other canonical ERFVII are better candidates to link ET and ABA or GA signaling (e.g. Arabidopsis RAP2.3, for instance).

Response: Indeed, as you said, this paragraph was not convincing, so we have removed it.

For the sake of transparency and to allow replicability of results, transcriptional results must be presented in full, including annotation RPKM and statistics (FDR corrected) as supplementary.

Response: Thanks for reminding. Sequencing analysis and annotations have been uploaded to the appendix.

To confirm that low O2 responses were activated under the experimental conditions described, expression of ET/O2 signaling ortholog elements must be presented along with typical anoxia survival responses (expression and/or enzyme activity of ADH, PDC and SUSY). Likewise, signaling pathways for GAs and ABA also need to be presented (expression of ABA receptors, PP2Cs, SnRKs and ABA-responsive genes such as ABI5, DREB2A, RD29, etc...).

Response: Thanks for the suggestion. The transcriptome of this article is a non-reference transcriptome, compared to the reference transcriptome, functional gene analysis is not as detailed. Therefore, our idea is to screen as well as validate the F. hodginsii genes with the highest correlation with water flooding, and it is difficult to provide any other valuable information.

8. Minor aspects:

L190 Where is Table 2, maybe authors refer to supporting Table S2. Please, amend.

Please, use the same coloring in Figures 3 and 4, as it stands is misleading.

Response: We deeply sorry about the mistake. We have changed “Table 2” to “Table S2”.

Reviewer #3.

1. Components of the PCR reaction volume doesn’t add up to 20. list them all. (Line 89)

Used GA standard/s (if used) not specified. There are various forms of GA available in the plants system, which one did you measure? (Line 95-102)

Response: Line 101.Thanks for pointing this out. We have listed “7 µL ddH2O”.

Line 107. We detected the contents of endogenous ABA and GA3, corrections have been made.

2. The gel electrophoresis will not tell you much/precisely the quality of the RNA. Have you run a the samples on the bioanalyzer? or Nano drop absorbance for these purposes? (Line 105)

Response: The gel electrophoresis is only to detect whether RNA is degraded, and we have measured the RNA concentration, absorbance value, 260/230, 260/280 before reverse transcription.

3. what reference genome did you use to design the primers? (Line 109)

which qRT-PCR instrument did you use? (Line 108-113)

Response: Line 145.primers were designed by using De novoassembly RNA-seq data (Table S1) and qRT-PCR instrument is Applied Biosystems QuantStudio™ 7 Flex.

4. consistency in writing terminologies. For example qRT-PCR (Line 108) vs RT-qPCR (supporting information line 9. Look into the rest of the manuscript for consistency

Response: Thanks for pointing out, Line145,240,303,325 - we have standardized to “RT-qPCR".

5. How did you calculate the relative GA and ABA amounts in Fig. 2 and 3 (Line 14-19; 22-28)? it should be elaborated in the figure legends and method section.

I recommend to include the hormone analysis data, at least in the supporting information section of the manuscript.

Response: Line 109. In the Materials and Methods section, we have added detailed steps and methods for the determination.

6. Can the authors reanalyse the transcriptomic data considering the quality check used at the begining of the analysis were Q10. It should be at least Q30 with inferred base call accuracy of 99.99% rather than 90% in Q10 (Line 124).

Response: Line 162. Thanks for pointing out, we checked the sequencing results again, sequence splicing assembly is based on Q30 standard to ensure the accuracy of the results.

7. How do you explain that you have supplemented the plants to be analyzed for RNAseq with GA3 but quantification from the other set of experiment stated only endogeneous GA. Can you reanalyze the hormone data by including other GA forms rather than stating indogenoeus GA, considering their que-specific responses?

Response: Thanks for pointing this out. Actually, we only quantified GA3 by HPLC-MS since GA3 was proved to be the most sensitive form of GA to flooding. Relative changes have been made to clarify that only GA3 was quantified in this study

Submitted filename: Response to comments.docx

Click here for additional data file.

19 Dec 2021

Submitted filename: renamed_c3051.docx

Click here for additional data file.

19 Jan 2022

To editor:

1. L121 space before comma should be deleted

Respone: Line 123. Thank you for reminding. Corrections have been made.

2. L145 should be “DNase I”

Respone: Line 148. Thank you for reminding. Corrections have been made.

3. L184 CRA005262 is currently duplicated

Respone: Line 188. Thank you for reminding. Corrections have been made.

To reviewer:

1. At no point in the text is cited the country where the provinces are located. It is implied but not explicit. Furthermore, the denominations of the provinces are ambiguous and change during the text, making the understanding of the reader from another country confusing.

Response: Line79. Thank you for reminding. The original country “China” has been added for F. hodginsii.

2. In the introduction, in the paragraph beginning on line 71, the flooding conditions that may have triggered the plants' adaptation to excess water are mentioned. It would be interesting to inform the time needed for the studied species to complete a reproductive cycle, since the epigenetic changes triggered by stress might not have established themselves as marks transmitted between generations in a short period of time.

Response: Line 67. “It takes about 5-7 years from germination to flowering, with flowering in March-April and fruiting in October-November” has been added. The time of the 1956 flooding was well documented, perhaps it happened before that too, but there is no record of it, so we have no way of knowing. And later seed gardens may have accelerated this genetic effect.

3. In lines 85-87 it is not clear whether the plants were grown under hydroponic conditions or in soil.

Response: Line87. “under hydroponics” has been added.

4. In line 91, it would be pertinent to add the justification for the growth to have occurred in the dark. Do the authors believe that the gene expression observed in the dark condition reflects the transcript pattern that would be expected for these plants under natural conditions? Furthermore, there is no information on acclimation to the dark condition or the growing temperature.

Response: Line 92. “all treatments were performed under complete dark conditions that included 22℃ and 85% relative humidity.” has been added. It was conducted in complete darkness to minimize the O2- contamination. Dark conditions were operated in a darkened room which included 22℃ and 85% relative humidity.

5. In line 100 there is no information on where the sequences of primers used in the experiment are found.

Response: Line99. Thank you for reminding. “Eleven pairs of SSR primers were used to analyse [20] (Table S1)” has been added.

6. In line 122 there is not enough information about the analysis conditions in UHPLC.

Response: Line 129. We have refined the analysis conditions of UHPLC-MRM-MS and “The MRM parameters for each of the targeted analytes were optimized using flow injection analysis, by injecting the standard solutions of the individual analytes, into the ESI source of the mass spectrometer. Several most sensitive transitions were used in the MRM scan mode to optimize the collision energy for each Q1/Q3 pair. Among the optimized MRM transitions per analyte, the Q1/Q3 pairs that showed the highest sensitivity and selectivity were selected as ‘quantifier’ for quantitative monitoring. The additional transitions acted as ‘qualifier’ for the purpose of verifying the identity of the target analytes. Skyline Software were employed for MRM data acquisition and processing.” has been added.

7. In the “Simple Sequence Repeat (SSR) assay” section, there is no information on the methodology for extracting genetic material. How many grams of material were used? Did each sample come from different plants or from a pool of individuals? Couldn't the genetic variability of the species mask the results if different individuals make up the same sample?

Response: Line 96. Approximately 100mg leaf samples were used to extract DNA. They were pool of individuals from same.

8. In the section “Total RNA extraction, cDNA reverse transcription, and quantitative real-time (qRT) PCR” there is no information on the methodology used to extract the genetic material from the sample. How many grams were used in the extraction and which plant organs were collected for this trial? Did each individual compose a sample or was a pool of individuals performed during the extraction? Given the genetic variability of the species, would the pool represent a uniform condition of transcripts during the analyses?

Response: Line151. We have added the detail “500 mg leaves”. The samples were pool of individuals from same.

9. In the section “RNA-Seq analysis and bioinformatics” an experiment is mentioned where the seedlings were treated with 1 µM GA3 and 20 µM ABA, but this methodology was not described in the text.

Response: Line 166. “The seedling were grown under hydroponics, the 1 µM GA3 and 20 µM ABA treatments through adding the appropriate amount of powder to the culture solution to achieve the required concentration.” has been added.

10. In line 159 the conditions for RNA sequencing were not described.

Response: Line 172. We have added the conditions for RNA-seq and “RNA-Seq was performed using the Illumina NovaSeq 6000 with 6G of data and Poly (A) RNA from 1 mg total RNA or purified mRNA and purified m6A-containing fragments were used to generate the cDNA libraries, respectively, according to TruSeq RNA Sample Prep Kit protocol. The sample library type was a eukaryotic unstranded specific transcriptome library.” has been added.

11. The “INITY_DN7657_c0_g1” gene is constantly written without “TR” (lines 36, 248, 250, 308 and 313 for example), and it was not clear if it was a typo or if the name really is “inity, since in the response to Reviewer #2 and in the caption of Figure 4 it was written as “TRINITY_DN7657_c0_g1”.

Response: Lines 36, 265, 267, 335, 330 and 349.Thank you for reminding. Corrections have been made.

12. On line 291, correct O2 to O2

Response: Line 308. Thank you for reminding. The “O2” has corrected to “O2”.

13. Between lines 289-296 the role of ethylene in flooding conditions was discussed. Did the authors analyze ethylene-responsive genes in transcriptomic analysis? The same can be pointed out in the discussion of salicylic acid (lines 297-305).

Response: These two relevant changes were not found in the available data. Due to genomic information is not available, there is no way to answer the above question further.

14. In the conclusion, it would be interesting to include the relevance of the results obtained in this work, as well as the future perspective for new experiments.

Response: Line 351. We describe the relevance of the results and the outlook and “thus may be the reasons for phenotypic variation of F. hodginsii. The analysis of phenotypic differences in F. hodginsii revealed the intrinsic molecular regulatory mechanisms and provided some reference value for resistance breeding and adaptive evolution.” has been added.

15. With regard to the images, in Figure 1B the data caption in the graph is in inverse order to the bars in the graphs (in the bars Province 4 appears first, although it is the last in the image caption).

Response: Thank you for reminding. We have corrected the figure.

16. It would be interesting to include the title of each graphic in the images (and not just in the caption).

Response: Thank you for your advice. We tried to take your suggestion, but some of the images have more characters and look a bit crowded with the captions.

17. Figures 4A and 4B are very small and difficult to read.

Response: Sorry about this. We have changed the size and sharpness of the images.

Submitted filename: Response to comments.docx

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21 Jan 2022

Transcriptome analysis of gibberellins and abscisic acid during the flooding response in Fokienia hodginsii

PONE-D-21-26095R2

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2 Feb 2022

PONE-D-21-26095R2

Transcriptome analysis of gibberellins and abscisic acid during the flooding response in Fokienia hodginsii

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