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Article

Waterlogging Hardening Effect on Transplant Stress Tolerance in Pinus densiflora

by
Siyeon Byeon
1,2,
Seohyun Kim
2,
Jeonghyun Hong
2,
Tae Kyung Kim
2,
Woojin Huh
2,
Kunhyo Kim
2,
Minsu Lee
2,
Hojin Lee
3,
Sukyung Kim
2,
Chanoh Park
2,
Narayan Bhusal
2,4,
Ah Reum Han
5,
Umashankar Chandrasekaran
2,6,* and
Hyun Seok Kim
2,3,6,7,*
1
Department of Forest Bioresources, National Institute of Forest Science, Suwon 16631, Republic of Korea
2
Department of Agriculture, Forestry and Bioresources, College of Agriculture and Life Sciences, Seoul National University, Seoul 08826, Republic of Korea
3
Interdisciplinary Program in Agricultural and Forest Meteorology, College of Agriculture and Life Sciences, Seoul National University, Seoul 08826, Republic of Korea
4
Department of Botany and Plant Sciences, University of California, Riverside, CA 92521-0124, USA
5
Division of Basic Research, National Institute of Ecology, Maseo-Myeon 33657, Republic of Korea
6
Research Institute of Agriculture and Life Sciences, College of Agriculture and Life Sciences, Seoul National University, Seoul 08826, Republic of Korea
7
National Center for Agro Meteorology, Seoul 08826, Republic of Korea
*
Authors to whom correspondence should be addressed.
Forests 2024, 15(3), 445; https://doi.org/10.3390/f15030445
Submission received: 10 January 2024 / Revised: 16 February 2024 / Accepted: 21 February 2024 / Published: 26 February 2024
(This article belongs to the Special Issue Physiological, Biochemical and Morphological Adaptation Characteristics of Woody Plants to the External Environment)
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Versions Notes

Abstract

:
Waterlogging induces oxidative damage by accumulation of reactive oxygen species due to stomatal closure. Plants alter their physiological and molecular mechanisms to reduce and adapt to oxidative stress. This mechanism of adaptation to stress, known as hardening, can support future stress tolerance. Pinus densiflora seedlings were grown under waterlogging treatment for three years and then transplanted to another site to identify the waterlogging hardening effect on transplanting. Transcriptome analysis was conducted before and after transplanting, and physiological factors were measured after transplanting. After transplanting, wounding stress is the main cause of transplant stress, and 13 genes related to phenylpropanoid were upregulated for the recovery of wounded roots in waterlogged hardened seedlings. The leaf starch and soluble sugar content of the waterlogged hardened seedlings were 50.3% and 40.5% lower due to the formation of cell walls. However, auxin-related genes were downregulated in waterlogging hardened seedlings, resulting in a lower tendency for height growth in hardened waterlogged seedlings. Waterlogging hardening mitigated transplant stress by wounding more than non-hardening, whereas waterlogging hardening may negatively affect seedling height. Our study provides evidence for the hardening effect of long-term waterlogging on transplanted P. densiflora seedlings.

1. Introduction

Flooding and waterlogging are environmental stressors that trigger reductions in crop production and biomass accumulation in trees worldwide [1,2,3,4]. Globally, a total of 93,319 ha and 1.6 million tons of crops were damaged by flooding between 2003 and 2013 [5]. In the case of cotton (Gossypium hirsutum L.), waterlogging stress reduced the yield from 10% to 40% [6,7]. In Texas, sudden vegetation dieback, including five succulent and graminoid species, occurs because of extreme precipitation events, during which many areas receive more than 1000 mm of precipitation over a four-day period [8].
The cause of reduced plant productivity and plant death is triggered by the reduction in stomatal conductance [9]. Low O2 (oxygen) levels in submerged roots decrease ATP synthesis and leaf stomatal conductance [10,11]. Decreased stomatal conductance results in reduced transpiration, photosynthesis, and respiration [2,12], leading to internal water and nutrient deficits [13]. Decreased stomatal conductance also leads to the accumulation of reactive oxygen species (ROS), resulting in membrane damage and lipid peroxidation under anoxic conditions [14,15].
Phytohormones play a crucial role in physiological mechanisms [16,17]. Phytohormones play important roles in waterlogging stress [18] such as jasmonic acid (JA) which regulates waterlogging stress by inducing antioxidants to scavenge ROS [19,20]. In the case of abscisic acid (ABA), the effect of ABA on waterlogging tolerance has been contradictory. Under waterlogging stress, increased ABA in overexpressing plants led to an increase in the antioxidant system and reduced oxidative damage under waterlogging stress in cotton [21,22] and wheat [23]. In contrast, a waterlogging-resistant line showed reduced ABA content in soybeans [24]. Ethylene and auxins induced adventitious root formation, aerenchyma formation, and shoot growth to adapt to flooding stress [25,26]. In addition to adventitious root formation, high stomatal conductance is a key indicator of tolerance to flooding stress by reducing the accumulation of ROS [27,28]. The flood-tolerant species Zea mays and Vicia faba (bean) maintain photosynthesis rate and high stomatal conductance under flooding stress, whereas Phaseolus vulgaris and Pisum sativum have reduced stomatal conductance and photosynthesis rate [27]. These adaptation processes may constitute stress memories and affect subsequent stress tolerance by modulating metabolism, morphological characteristics, and gene expression [29].
Stress tolerance is improved by an adaptation process to prior stress exposure called “hardening” [30,31]. Hardening enhances tolerance to various abiotic stresses, such as drought [32,33,34], chilling [35,36], and salinity [37]. Previous studies have reported that waterlogging hardening can alleviate the loss of production in wheat [38]. Waterlogged wheat has higher chlorophyll content and photosynthetic rate than non-hardened wheat [38]. Waterlogging reduces oxidative damage and yield loss in soybeans (Glycine max) under continuous waterlogging stress [39]. Abiotic stress hardening can induce cross-stress tolerance to subsequent stresses [40,41,42].
Cross-stress tolerance is induced by prior moderate stress, which stimulates common defenses against different stresses [41]. In trees, it is important to pretreat hardening under nursery conditions to improve cross-stress tolerance [43,44]. Transplant stress negatively affects plant growth and survival when seedlings are transferred to other environments [45]. Transplant stress is manifested by various symptoms, such as a reduced growth rate in newly planted seedlings compared to naturally regenerating seedlings of the same age. Under severe conditions, it can also result in leaf abscission and mortality [46]. Transplant stress is linked to the acclimatization process of seedlings to the new environmental conditions. For low-temperature conditions, tree seedlings are susceptible to cold stress because the seedlings are not be acclimated to the low temperatures [45]. Transplant stress mainly arises from root system loss during the transplantation process, which limits water and nutrient uptake due to root pruning, and shares common responses with drought and waterlogging stress [45,47]. Nursery management is necessary to improve stress tolerance. However, few studies have been conducted on the hardening effect of transplanting stress in trees [48].
Here, to understand the transcriptional response to waterlogging and transplant stress and to identify stress tolerance after waterlogging hardening, we analyzed transcriptional responses of the conifer species P. densiflora. P. densiflora Siebold and Zucc., a gymnosperm species commonly known as Korean red pine, is widely distributed in East Asia [49]. This species occupies more than 22% of Korean forests [50]. Mass dieback of P. densiflora due to drought stress has been documented in South Korea from 2008 to 2017 [51,52].
Trees were grown for three years under two different water availabilities: control (100% natural precipitation; C) and waterlogging (30% additional irrigation; W). After three years of waterlogging, trees were transplanted to another site to study the waterlogging hardening effect. To investigate the effects of waterlogging hardening on transplant stress tolerance, transcriptome analysis was performed after transplanting. This study aimed to (i) determine whether waterlogging stress improves stress tolerance after transplanting, (ii) identify transplant stress-tolerance genes and pathways after waterlogging hardening, and (iii) identify physiological changes after waterlogging stress and transplanting.

2. Materials and Methods

2.1. Experiment Sites and Plant Materials

Waterlogging hardening was conducted for 3 years at Mt. Jiri (127°27′09.8″ N 35°17′09.3″, elevation 282 m a.s.l) in Gurye, South Jeolla Province, Republic of Korea (April 2018 to October 2020). The waterlogged experimental site consisted of two treatments: control (C) and waterlogged treatment (W). In the C treatment, plants were grown under natural precipitation, whereas in the W treatment, irrigation was supplemented with sprinklers. A total of 48 sprinklers were installed at 3 m height and a 70 cm interval. Additional irrigation was performed as follows: If the weekly precipitation was lower than the 20-year average precipitation from 1997 to 2017, additional irrigation was applied [53]. Irrigation was not added in the case of precipitation higher than the 20-year average precipitation of the weekly precipitation.
Soil temperature was measured using soil temperature sensors (HOBO S-TMB-M002; Onset Computer Corporation, Bourne, MA USA), and 30 sensors (15 per treatment) were placed at a depth of 20 cm. The soil water content of the top 30 cm was recorded using a soil moisture sensor (%, CS-616, Campbell Scientific Inc., Logan, UT, USA; 12 in each treatment) at a 15 s interval and averaged for 30 min. Soil moisture data were collected from the HOBO stations (HOBO RX3000; Onset Computer Corporation) in each plot.
A total of 24 three-year-old P. densiflora seedlings were transplanted to each treatment in April 2018. Each treatment consisted of three cells (each cell 1.5 m × 1.5 m) and four seedlings were transplanted in each cell at an 80 cm distance between seedlings. The soil texture was sandy clay loam with a pH of 6.5. Additional details and environmental variables of the site were provided by Bhusal et al. [53].
The seedlings grown at C and W were transplanted after root pruning at Mt. Taehwa in central Korea (E 127°18′38.1″ N 37°18′46.6″, 137 m a.s.l) in October 2020. The transplant experimental site consisted of four cells (1.0 m × 3.0 m, 2 cells per treatment). Each cell consisted of three seedlings at a 1.0 m distance between seedlings. Seedlings were categorized based on their growth conditions until 2020 (C: TC and W: TW). The trees grown under the same treatment conditions were then transplanted into the same cells. During transplanting, shoot pruning was conducted to prevent transpiration and water loss on the same day. The soil moisture data were recorded by HOBO stations (HOBO RX3000; Onset Computer Corporation) at 15 s interval and averaged over 30 min. Two soil moisture sensors were installed in the top 10 cm of horizon A after the organic layer was removed in December 2020. Soil biochemical analyses were performed using an Elemental Analyzer (Flash EA 1112; Thermo Electron, Waltham, MA, USA) at the National Instrumentation Center for Environmental Management (NICEM), Seoul National University.
Leaf samples were harvested between 8:00 and 10:00 a.m. from three replicate trees for transcriptomic analyses in August 2020 and 2021. All the collected samples were immediately placed in liquid nitrogen.

2.2. Growth

After transplanting, the root collar diameter and height were measured in March and October 2021. The height and root collar diameter were measured using a height rod and digital calipers (Mitutoyo Vernier calipers, 100 mm, Mitutoyo, Japan), respectively.

2.3. Leaf Gas Exchange Measurement Growth

Leaf gas exchange measurements were conducted on six seedlings from each treatment between 08:00 a.m. and 13:00 p.m. in August 2021. The net photosynthetic rate (Pmax), stomatal conductance (gs), and transpiration rate were measured from 10 needles of each seedling using a portable infrared (IR) gas analyzer (LI-6400; LI-COR, Lincoln, NE, USA). The fixed factors of photosynthetic measurement were as follows: CO2 concentration (ambient CO2 concentration: 400 µmol mol−1), temperature (25 °C), photosynthetic photon flux density (PPFD) (1400 µmol m−2 s−1), relative humidity (RH; 50%–60%), and airflow rate (500 µmol s−1). Instantaneous water use efficiency (WUE) was calculated as Pmax divided by the transpiration rate [54]. The projected leaf area of the measurement chamber was measured to recalculate the gas exchange variables considering leaf area. Afterwards, the needles were fully collected in a 15 mL tube and immediately placed in a liquid nitrogen tank for analysis of nonstructural carbohydrates (NSCs), proline, and chlorophyll content.

2.4. Leaf Nonstructural Carbohydrates Content

Leaf NSCs were analyzed by measuring soluble sugars and starch, following the method of Newell et al. [55]. Fifteen milligrams of P. densiflora needles was dried for 72 h at 70 °C. The dried samples were ground with two 5 mm beads using a homogenizer (FastPrep-24; MP Biomedicals, Solon, OH, USA). The ground samples were added to 1.5 mL of 80% (v/v) ethanol, and the mixture was incubated in a water bath at 80 °C for 30 min. The mixture was centrifuged at 14,000× g at 15 °C for 10 min. Soluble sugar content was measured at 490 nm using a spectrometer (Optizen 2120UV; KLAB, Daejeon, Republic of Korea) following the phenol–sulfuric acid colorimetric method [56]. After soluble sugar extraction, the remaining pellets were dried to measure the starch content. Each pellet was added to 2.5 mL sodium acetate buffer (0.2 M), and the mixture was incubated at 100 °C for 1 h in a water bath. Afterwards, 2 mL sodium acetate buffer and 1 mL amyloglucosidase (0.5% (w/w); Sigma A9229-1G; Sigma-Aldrich Corp., St. Louis, MO, USA) were added to the mixture and incubated at 55 °C overnight. After centrifugation for 10 min at 15 °C at 14,000× g, the supernatant was moved into another tube to quantify starch content. Starch content was determined colorimetrically at 490 nm using the phenol–sulfuric acid colorimetric method.

2.5. Proline Content

Fresh 0.1 g needles at −80 °C were used for proline extraction according to the method of Ábrahám et al. [57]. The samples were ground with a single 5 mm bead using a homogenizer (FastPrep-24; MP Biomedicals). The ground samples were added in 3 mL of 3% (w/v) sulfosalicylic acid at 4 °C. The mixture was centrifuged at 14,000× g at 4 °C for 5 min and incubated at 90 °C for 5 min. Next, 2 mL supernatant was mixed with 2 mL of acidic ninhydrin (ninhydrin 1% (w/v) in acetic acid 60% (v/v), ethanol 20% (v/v)), 1 mL of glacial acetic acid, and 2 mL of 6 M orthophosphoric acid. The mixture was maintained at 100 °C for 1 h. The mixture was transferred to an ice bath to stop the reaction. Toluene was added to the mixture and incubated at 15 °C for 5 min. The proline content was determined colorimetrically at 520 nm using a spectrometer (Optizen 2120UV; KLAB, Republic of Korea).

2.6. Total Chlorophyll Content

Total chlorophyll content was measured using the dimethyl sulfoxide (DMSO) method [58]. Fresh 0.2 g needles in 5 mL DMSO were incubated at 65 °C for 6 h. The chlorophyll content was measured at 649 nm and 665 nm using a spectrophotometer (Optizen 2120UV; KLAB, Republic of Korea). Total chlorophyll content was calculated using the following equation (Wellburn [59]):
Total chlorophyll content (μg·mL−1) = 21.44 A649 + 5.97 A665

2.7. Statistical Analysis

Two-way repeated-measures ANOVA was performed for height and root collar diameter with the fixed factor “treatment” and the random factor “year.” An independent t-test was used to identify the effects of waterlogging hardening on plant height, root collar diameter growth, Pmax, gs, WUE, NSC, proline, and chlorophyll. All statistical analyses were conducted using R v. 4.0.3 (R Core Team, Vienna, Austria).

2.8. RNA Extraction and Sequencing

Total RNA was extracted from about 40 mg needles from 6 replicate trees using the Ribospin™ Plant kit (GeneAll, Seoul, Republic of Korea). The extracted RNA was analyzed using Macrogen (Seoul, Republic of Korea) for library construction and sequencing. The RNA integrity number (RIN) was evaluated using a Bioanalyzer RNA Pico 6000 chip, and the samples with an RIN higher than seven were used for the cDNA library construction. The cDNA library (paired-end nondirectional, 2 × 101 bp) was constructed using a TruSeq Standard mRNA Library Prep Kit and sequenced using an Illumina NovaSeq 6000 system (Macrogen, Seoul, Republic of Korea).

2.9. Transcriptome Analysis: De Novo Assembly and Differential Expression Analysis

Raw read data were filtered using Prinseq-lite version 0.20.4 [60]. Clean reads were assembled de novo (Trinity v.2.13.2) [61]. To find the candidate coding regions of the assembled transcripts, Transdecoder v.5.5.0 was used with default parameters [62]. CD-HIT-EST v.4.8.1 was used to cluster transcripts (similarity 95%) [63]. To assess the quality of the assembled transcriptome, Benchmarking Universal Single Copy-Orthologs (BUSCO, v.3) was used with the Embryophyta_odb10 database [64].
Salmon v.1.8.0 was used to map clean reads to the assembled transcriptome in an alignment-based mode [65]. After mapping, DESeq2 v.1.34.0 was applied to normalize the read counts and compare differentially expressed genes (DEGs) between treatments [66] with lower than 0.05 of a false-discovery rate (FDR)-adjusted p-value and |log2 fold change (log2 FC)| > 1 parameters.

2.10. Functional Analysis and MapMan Analysis

The Basic Local Alignment Search Tool for proteins (BLASTX) was used to compare the sequences against those of Arabidopsis thaliana (A. thaliana) using an e-value threshold of 1 × 10−7 to reveal gene functional annotations [67]. The PANTHER gene ontology (GO) classification system was used to identify cellular components, molecular functions, and biological processes using Fisher’s exact test with FDR < 0.05; http://www.geneontology.org [68]. Transcription factors (TFs) of A. thaliana in the Plant Transcription Factor Database v4.0 (http://planttfdb.cbi.pku.edu.cn/) were used as references to identify TFs families of P. densiflora [69,70]. Pathway analysis of DEGs was conducted using MapMan v. 3.5.1R2.

2.11. Quantitative Real-Time (qRT)-PCR Validation

RNA extraction was performed using the Ribospin™ Plant kit (GeneAll, Seoul, Republic of Korea). The extracted RNA was used to synthesize cDNA using an iScriptTM cDNA synthesis kit (Bio-Rad, Hercules, CA, USA). Primers for the 10 genes were designed using Primer3 (https://www.bioinformatics.nl/cgi-bin/primer3plus/primer3plus.cgi, accessed on 10 October 2022) (Table S1). The reference gene F-box was used for gene expression normalization [71]. Each mixture for qRT-PCR contained 10 μL of mastermix (IQ Sybr Green SuperMix; Biorad, Hercules, CA, USA), 10 μM forward and reverse primer, 1 μL cDNA (50 ng μL−1), and 7 μL DNase/RNase free water. Then, qRT-PCR was performed using CFX96 Touch Real-Time PCR Detection System (Bio-Rad, Hercules, CA, USA) using the following conditions: 95 °C for 2 min, followed by 40 cycles at 95 °C for 10 s, 61 °C for 30 s, and 72 °C for 30 s. qRT-PCR reactions were carried out with three biological replicates. Gene expression was calculated using the 2−ΔΔCt method [72]. Correlation analysis of RNA-seq and qRT-PCR results was performed using R v.4.0.3.

2.12. Data Deposition

All the read data were deposited in the SRA databases as part of project PRJNA944986.

3. Results

3.1. Data Deposition

Waterlogging treatment conditions before transplanting were reported by Bhusal et al. [53]. The annual precipitation in C was 1392, 1495, and 1565 mm, and that in W was 1811, 1891, and 2128 mm in 2018, 2019, and 2020, respectively. The average soil water content in C was 21.54 ± 0.92%, 24.24 ± 0.69%, and 26.69 ± 0.98%, and that in W was 27.48 ± 0.93%, 30.12 ± 0.78%, and 32.95 ± 0.99% in 2018, 2019, and 2020, respectively. After transplanting, the mean temperature and total precipitation were 10.11 ± 0.9 °C and 841 mm from October 2020 to December 2021, respectively (Figure 1A,B). The average of soil moisture was 22.9 ± 0.07% between December 2020 and 2021 (Figure 1C). The soil texture was sandy loam with a pH of 5.2 ± 0.1. Soil organic matter and soil N were 2.74 ± 0.19% and 0.16 ± 0.0%, respectively.

3.2. Assembled Transcriptome Data

A total of 406,823,434 and 368,384,228 raw paired reads were generated in the waterlogging experiment and after transplanting, respectively. We obtained a total of 269,984 transcripts and 134,369 genes after filtering and de novo assembly using the Trinity software v. 2.13.2 (Table 1). GC content was 41.3%, and the contig N50 length was 1501. The total number of assembled bases was 236,105,474. To assess assembly quality, we conducted BUSCO analysis, and 1483 (91.9%) complete BUSCO genes were predicted, with 49 (3.0%) fragmented and 82 (5.1%) missing genes.

3.3. Comparison of Differentially Expressed Genes between Waterlogging and Control Seedlings

With a threshold of FDR < 0.05, and |log2 FC| > 1, 3, 12 DEGs were up- and downregulated in W compared to C, respectively (Figure 2). After transplanting, 232 and 155 DEGs were upregulated and downregulated in TW, respectively, compared to TC. When comparing TC vs. C and TW vs. W, 988 and 1871 DEGs were upregulated, and 611 and 808 DEGs were downregulated, respectively. Among them, two DEGs were commonly regulated between TW vs. TC and W vs. C (Figure 3A). When comparing TW vs. W and TC vs. C to identify transplant stress, 1119 DEGs were commonly expressed (Figure 3B).

3.4. Gene Ontology (GO) Term Classification of Genes Induced by Transplant Stress

Transplant stress, which was expressed as common DEGs between TW and W and TC and C, caused the upregulation of 794 genes that were categorized into 198 biological processes, 49 molecular functions, and 71 cellular components (Table S2). The upregulated biological processes included responses to wounding, mechanical stimuli, bacteria, fungi, osmotic stress, and reactive oxygen species. In particular, cell wall organization, loosening, and modification were the biological processes most significantly upregulated by transplant stress and subsequently resulted in the upregulation of the biosynthesis genes of lignin, glucuronoxylan, cellulose, hemicellulose, galacturonan, and xyloglucan. Similarly, molecular function and cellular components were upregulated in the cell wall-related genes and activities. In addition, defense mechanisms, JA-mediated signaling pathway, phenylpropanoid biosynthesis, and flavonoid metabolism were upregulated after transplanting. In contrast, 303 downregulated genes were identified during transplant stress and were categorized into 72 biological processes, 53 molecular functions, and 46 cellular components (Table S2). Photosynthesis was the most significantly downregulated in biological processes and cellular components; furthermore, photosystem I, light harvesting, carbon fixation, and dark reactions were also downregulated (Table S2). Excluding commonly expressed genes, upregulated genes were associated with 23 GO categories, including various responses to stress, and 17 biological processes were found in downregulated genes when comparing TC and C (Table S3). In the case of TW and W, excluding genes commonly expressed with TC and C, various cell wall organization processes and phenylpropanoid biosynthetic processes were classified under upregulated genes (Table S3). In the same comparisons, 29 biological processes were identified in downregulated genes.

3.5. Gene Ontology (GO) Term Classification of Differentially Expressed Genes between Waterlogging and Control after Transplanting

The effects of waterlogging hardening before and after transplanting were represented as the DEGs of W vs. C and TW vs. TC, respectively. Before transplanting, waterlogging hardening resulted in 3 upregulated and 12 downregulated genes, which were not categorized into GO terms. After transplanting, 233 upregulated genes in TW were categorized into 66 biological processes, 21 molecular functions, and 10 cellular components (Figure 4A). In contrast, 156 genes were downregulated in the TW treatment, and these were categorized into five molecular functions, such as oxidoreductase activity, anion binding, and catalytic activity (Figure 4B).
Upregulated biological processes included stress-tolerance-related processes, such as the biosynthesis of oxylipin, lignin, flavonoids, and phenylpropanoids. In addition, carbohydrate metabolic processes; immune systems; defense responses to fungi and bacteria; and responses to wounding, water deprivation, jasmonic acid, and salicylic acid (SA) were upregulated (Figure 4A). In the phenylpropanoid biosynthesis process, phenylalanine ammonia-lyase 4 (PAL4), UDP-glycosyltransferase 72B1 (UGT72B1), and putative cinnamyl alcohol dehydrogenase 9 (CAD9) were upregulated in TW compared with TC. The upregulated flavonoid biosynthesis processes included dihydroflavonol 4-reductase (DFRA), leucoanthocyanidin dioxygenase (LODX), chalcone-flavanone isomerase 1 (CHI1), and anthocyanidin reductase (BAN) (Table S4). The upregulated molecular functions included ABC-type transporter activity, oxidoreductase activity, quercetin 7-O-glucosyltransferase, quercetin 3-O-glucosyltransferase, UDP-glucosyltransferase, hydrolase activity, and O-glycosyl compound hydrolysis (Figure 4A). The ABC transporter ABCG29 was upregulated in TW compared with TC (Table S4). Among cellular components, the cell wall, chloroplast, and membrane-related genes were upregulated (Figure 4A).

3.6. Transcription Factors and Pathway Analysis after Transplanting

Similar to the GO terms, there were no differentially expressed genes before transplanting (C vs. W). However, eight downregulated and seven upregulated TFs were identified after transplanting (TW vs. TC) (Figure 5). Downregulated TFs in TW included two members of the ethylene-responsive factor (ERF) family (ERF9 and RAP2-13), RAV, basic leucine zipper domain (bZIP), auxin response factor (ARF), C3H, GRAS, and Trihelix. Highly expressed TFs in TW included three members of the lateral organ boundaries domain (LBD) family (LBD1), 2 MYB family (MYB3 and MYB5), bZIP29, and ERF017.
In the MapMan analysis, genes related to the cell wall, JA, mitogen-activated protein kinase (MAPK) signaling, and secondary metabolites were upregulated in TW compared to TC. Jasmonate synthesis–degradation, lipoxygenase, salicylic acid (SA) synthesis–degradation, cell wall proteins, phenylpropanoids, lignin biosynthesis, flavonoids, redox thioredoxin, peroxidase, and glutathione-S-transferase presented a log2 FC value higher than 7. Whereas the Log2 FC value of genes related to auxin, ethylene signal transduction, PR protein, and MAPK was lower than −7 in TW than in TC (Figure 6).

3.7. Validation of RNA-Seq Expression of Waterlogging Hardened Trees in Transplant Stress

To confirm the accuracy of the RNA-seq expression, we compared the qRT-PCR expression of nine genes between TW and TC. Log2 FC values of RNA-seq expression showed a significant correlation with the log2 FC values and qRT-PCR (R2 = 0.914, Figure 7).

3.8. Physiological Response of Waterlogging Hardening after Transplanting

Before transplanting, the photosynthetic rate, leaf water potential, height, and root collar diameter were lower in W than in C for two years [53]; however, the trees transplanted to Taehwa showed no differences in height and root collar diameter in 2020 (Table 2). After transplanting, the height and root collar diameter showed no differences between TW and TC throughout the year. Height growth tended to be lower in TW than in TC; however, the difference was not statistically significant (Table 3). Similar to the morphological characteristics, physiological characteristics showed no differences between TW and TC, except for starch concentration (Table 3). Starch concentration in TW was 50.3% lower than in TC (p = 0.007, Table 3). Similarly, soluble sugars were 40.5% lower in TW compared with TC; however, the difference was not statistically significant. In contrast, Pmax, stomatal conductance, and chlorophyll tended to be higher in TW than in TC, but neither of them was statistically significant.

4. Discussion

4.1. Genes Regulated by Transplant Stress

Transplant stress is defined as a negative effect on growth and mortality after transplanting into different environmental conditions and during the process of recovery [46,73]. Root loss by pruning during transplanting causes a reduction in water and nutrient uptake, which leads to water stress, stomatal closure, and photosynthesis inhibition [45,74]. Our study revealed the upregulation of genes related to the response to wounding and biotic stimuli as a recovery process after root loss by pruning. In addition, photosynthetic genes, including those involved in carbon fixation and light harvesting, were downregulated under transplant stress. Similar to our results, net photosynthesis, stomatal conductance, and transpiration were significantly lower in root-pruned seedlings than in non-pruned seedlings grown on green ash (Fraxinus pennsylvanica Marsh.) and linden trees [75]. Owing to water stress caused by root pruning, trees reduce stomatal conductance and photosynthesis, which leads to the inhibition of shoot elongation. However, transplanted maple trees can recover photosynthesis quickly because of their accelerated root regeneration, which reduces water-deficit stress [76,77]. Therefore, the root regeneration capacity is important for the alleviation of transplant stress.
Our study showed that cell wall-related genes were upregulated. Similar to our results, wounding stress induces callus formation and expression of cell wall biosynthesis and cell cycle genes within 24 h in Arabidopsis thaliana [78]. Additionally, wounding triggers lignin biosynthesis in maize [79]. In contrast, cell wall modification and loosening are important for the defense against pathogens and abiotic stresses to prevent cell wall cleavage by ROS [80,81,82,83,84]. The phenylpropanoid biosynthetic pathway is activated under stressful conditions to scavenge ROS and recover wounded tissues [85,86]. In the present study, the main cause of transplant stress was wound stress caused by root pruning. Transplanted trees showed general wounding and defense responses, such as cell wall modification and biosynthesis of secondary metabolites, to defend themselves against ROS.

4.2. Waterlogging Hardening Effect after Transplanting

In the third waterlogging experimental year, there were no categorized biological processes of either upregulated or downregulated genes in W compared to those in C. Similar to the transcriptome data, at the same site, there were no differences between W and C groups in the third year. In contrast, stomatal conductance and photosynthetic rate decreased, and midday leaf water potential increased in the first and second years [53]. In the same study, P. densiflora exhibited a notable increase of 23.3% in above-ground biomass under waterlogging stress compared to control, indicating its strong resilience to this particular stress condition [53]. Gymnosperms, in general, exhibit greater tolerance to water stress compared to angiosperms. This can be attributed to their lower stomatal sensitivity and the presence of cavitation-resistant xylem [87]. Conifers have xylem composed entirely of tracheids, while angiosperms have both tracheids and wide vessels. Although the presence of wide vessels allows for higher water transport capacity in angiosperms, it also results in a smaller safety margin when it comes to xylem pressures [88]. The probable reason for the lack of response to waterlogging stress is that the total precipitation in the third year in C was 1565 mm, which was higher than that in the first and second years; therefore, C was under mild waterlogging conditions [53].
After transplanting, stress-tolerance-related genes, such as JA, signaling, and secondary metabolites, were more upregulated in TW than in TC. Phenylpropanoid compounds, including lignins, flavonoids, and phenolics, are secondary metabolites induced by JA and play important roles in biotic and abiotic stress tolerance and cell wall organization [85,86]. LBD (lateral organ boundaries domain) proteins are involved in various plant developmental processes [89]. In Arabidopsis roots, overexpression of LBD genes (LBD1, LBD3, LBD4, and LBD11) leads to rapid radial root growth [90]. In Populus, overexpression of PtaLBD1 significantly enhances wood growth by regulating phloem development [91]. In Populus tremula × Populus alba, there was a significant increase in phloem production in transgenic lines as LBD1-overexpressing, when auxin levels were lower in the tissues [91]. Furthermore, MYB TFs induce phenylpropanoid biosynthesis pathway genes, such as PAL, and activate the biosynthesis of lignin and cellulose in Arabidopsis and Populus [92,93,94,95]. Lignins are transported to the cell wall and plasma membrane only by ABCG29 in the ABC transporter [96]. Similar to a previous study, MYB and LBD TFs, UGT72B1, PAL4, and ABCG29, were upregulated in TW compared to TC, whereas auxin-related genes were downregulated in TW. In previous studies, UGT72B1 was found to be crucial for normal cell wall lignification and was expressed in young xylem tissues, and the overexpression of PAL enhanced lignin and stress tolerance [97,98,99,100]. In addition, the degradation of leaf starch in TW showed that the leaf starch was converted to the cell wall and exported to the roots [101]. Decreased NSCs do not always reflect tree death, and NSC mobilization reflects various physiological functions of trees [102,103]. For example, NSC alleviates water stress by increasing below-ground allocation [104,105] and repairing damaged vessels [106,107].
In TW, the biosynthesis of flavonoids, including quercetin 7-O-glucosyltransferase, quercetin 3-O-glucosyltransferase, and UDP-glucosyltransferase, which are other phenylpropanoid compounds involved in increasing antioxidants in wound healing, is upregulated [85,86]. In the stress pathway, antioxidant genes, such as redox thioredoxin, peroxidase, and glutathione-S-transferase, were highly expressed; however, some genes related to antioxidants were downregulated. These results indicate that the phenylpropanoid pathway is reprogrammed to recover damaged tissue by upregulating lignin more than flavonoids [108].
After transplanting, waterlogging hardening enhanced wound recovery and increased cell wall formation and some antioxidants. Previous studies have shown that overexpression of genes-induced phenylpropanoid compounds leads to increased resistance to stresses [109,110,111]. By overexpressing genes involved in the phenylpropanoid pathway or using these genes as markers, it is suggested that the selection of crops or trees with high resistance to both biotic and abiotic stresses can be facilitated. Increased recovery ability by waterlogging hardening effect showed a higher tendency in photosynthesis and stomatal conductance similar to previous studies [27,28,77]. However, waterlogging hardening could have a negative effect on plant height growth due to the degradation of auxins involved in plant height growth [112,113]. Under waterlogged conditions, auxin and ethylene produce adventitious roots that adapt to the waterlogging conditions [25,114]. However, auxins are inactivated due to a decline in adventitious root formation [115].

5. Conclusions

Long-term waterlogging hardening has both positive and negative effects on transplant stress tolerance. After transplanting, the upregulated phenylpropanoid pathway in TW increased lignin biosynthesis for cell wall formation for the recovery of wounded roots. Decreased leaf NSC also showed root recovery ability by converting it into structural carbon and exporting it to the roots. The higher recovery ability due to waterlogging hardening led to a higher tendency for photosynthesis and stomatal conductance in TW. However, the degradation of auxins in TW reduced seedling height during the growing season compared with TC. Our research builds on the first long-term waterlogging hardening effect on transplanting stress. These findings will provide a comprehensive insight into waterlogging hardening effect after transplanting and inform nursery management to mitigate transplant stress. Further long-term molecular and physiological investigation is required to validate the identified candidate gene and waterlogging hardening effect.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/f15030445/s1, Table S1: Primer sequences used to validate RNA-sequencing results of trees grown under waterlogging treatment versus control after transplanting; Table S2: Gene ontology (GO) analysis of transplant stress; Table S3: Description of upregulated secondary metabolites genes under waterlogging hardening after transplanting; Table S4: Description of upregulated secondary metabolites genes under waterlogging hardening after transplanting.

Author Contributions

Writing—original draft preparation, formal analysis, validation, and visualization, S.B.; investigation and data curation, S.K. (Seohyun Kim), J.H., T.K.K., W.H., K.K., H.L., S.K. (Sukyung Kim), C.P., M.L. and N.B.; conceptualization and project administration, A.R.H.; supervision and writing—review and editing, U.C.; writing—review and editing, supervision, and funding acquisition, H.S.K. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the National Research Foundation of Korea (grant number: 2021R1I1A2044159) and the National Institute of Ecology (NIE), funded by the Ministry of Environment (MOE) of the Republic of Korea (NIE-B-2022-02).

Data Availability Statement

The data presented in this study are available upon request from the corresponding author. This manuscript is part of a PhD thesis by the first author, available online at https://www.riss.kr/link?id=T16749632, accessed on 28 February 2023.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Environmental variables at Mt. Taehwa from October 2020 to December 2021: (A) temperature, (B) precipitation, and (C) soil moisture.
Figure 1. Environmental variables at Mt. Taehwa from October 2020 to December 2021: (A) temperature, (B) precipitation, and (C) soil moisture.
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Figure 2. Number of differentially expressed genes (DEG) in each comparison. Letters indicate waterlogging treatment in 2020: control (100% natural precipitation; C) and waterlogging (additional irrigation 20-year average, W) and trees were transplanted in October 2020. Samples collected in 2021. TC and TW indicate trees grown at C and W in 2018–2020, respectively. Differential expression was defined as >1-fold change in expression at FDR < 0.05.
Figure 2. Number of differentially expressed genes (DEG) in each comparison. Letters indicate waterlogging treatment in 2020: control (100% natural precipitation; C) and waterlogging (additional irrigation 20-year average, W) and trees were transplanted in October 2020. Samples collected in 2021. TC and TW indicate trees grown at C and W in 2018–2020, respectively. Differential expression was defined as >1-fold change in expression at FDR < 0.05.
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Figure 3. Venn diagram showing the DEGs for each comparison. (A) Commonly regulated genes compared to control before and after transplanting. (B) Transplant stress: control (100% natural precipitation; C) and waterlogging (additional irrigation 20-year average, W) and trees were transplanted in October 2020. Samples collected in 2021. TC and TW indicate trees grown at C and W in 2018–2020, respectively. Differential expression was defined as >1-fold change in expression at FDR < 0.05.
Figure 3. Venn diagram showing the DEGs for each comparison. (A) Commonly regulated genes compared to control before and after transplanting. (B) Transplant stress: control (100% natural precipitation; C) and waterlogging (additional irrigation 20-year average, W) and trees were transplanted in October 2020. Samples collected in 2021. TC and TW indicate trees grown at C and W in 2018–2020, respectively. Differential expression was defined as >1-fold change in expression at FDR < 0.05.
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Figure 4. Gene ontology (GO) analysis of differentially expressed genes in comparisons between P. densiflora grown waterlogging stress after transplanting (TW and TC). (A) Upregulated GO term at TW. (B) Downregulated GO term at TW. The x axis indicates p-value −log10 (FDR). TC and TW indicate trees grown at control (100% natural precipitation; C) and waterlogging (additional irrigation 20-year average, W) in 2018–2020, respectively. The GO terms associated with Fisher’s exact test with FDR-corrected p-value < 0.05. The CC, MF, and BP indicate cellular component, molecular function, and biological process, respectively.
Figure 4. Gene ontology (GO) analysis of differentially expressed genes in comparisons between P. densiflora grown waterlogging stress after transplanting (TW and TC). (A) Upregulated GO term at TW. (B) Downregulated GO term at TW. The x axis indicates p-value −log10 (FDR). TC and TW indicate trees grown at control (100% natural precipitation; C) and waterlogging (additional irrigation 20-year average, W) in 2018–2020, respectively. The GO terms associated with Fisher’s exact test with FDR-corrected p-value < 0.05. The CC, MF, and BP indicate cellular component, molecular function, and biological process, respectively.
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Figure 5. Heatmap of expression of transcription factor (TF) genes in comparisons in the waterlogging experiment: control (100% natural precipitation; C) and waterlogging (additional irrigation 20-year average, W), and trees were transplanted in October 2020. Samples collected in 2021. TC and TW indicate trees grown at C and W in 2018–2020, respectively. Heatmap colors indicate the Z-scores of TMM-normalized TPM values. The darker purple color indicates a higher expression of the gene.
Figure 5. Heatmap of expression of transcription factor (TF) genes in comparisons in the waterlogging experiment: control (100% natural precipitation; C) and waterlogging (additional irrigation 20-year average, W), and trees were transplanted in October 2020. Samples collected in 2021. TC and TW indicate trees grown at C and W in 2018–2020, respectively. Heatmap colors indicate the Z-scores of TMM-normalized TPM values. The darker purple color indicates a higher expression of the gene.
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Figure 6. MapMan analysis of stress-related DEGs of P. densiflora genes compared to TW and TC. Letters indicate control (100% natural precipitation; C) and waterlogging (additional irrigation 20-year average, W) and trees were transplanted in October 2020. Samples collected in 2021. TC and TW indicate trees grown at C and W in 2018–2020, respectively. The different colors represent the log2 TPM values of the gene expression. Red indicates downregulated and blue indicates upregulated genes. ABA, abscisic acid; brassinost., brassinosteroid; HSP, heat-shock protein; JA, jasmonic acid; PR, pathogenesis-related; SA, salicylic acid.
Figure 6. MapMan analysis of stress-related DEGs of P. densiflora genes compared to TW and TC. Letters indicate control (100% natural precipitation; C) and waterlogging (additional irrigation 20-year average, W) and trees were transplanted in October 2020. Samples collected in 2021. TC and TW indicate trees grown at C and W in 2018–2020, respectively. The different colors represent the log2 TPM values of the gene expression. Red indicates downregulated and blue indicates upregulated genes. ABA, abscisic acid; brassinost., brassinosteroid; HSP, heat-shock protein; JA, jasmonic acid; PR, pathogenesis-related; SA, salicylic acid.
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Figure 7. Validation of RNA-Sequencing results using quantitative real-time PCR (qRT-PCR). Correlation of log2 FC value analyzed by RNA-Seq (x axis) with data obtained using quantitative real-time PCR (y axis) in trees grown under waterlogging hardening versus control conditions in transplant stress.
Figure 7. Validation of RNA-Sequencing results using quantitative real-time PCR (qRT-PCR). Correlation of log2 FC value analyzed by RNA-Seq (x axis) with data obtained using quantitative real-time PCR (y axis) in trees grown under waterlogging hardening versus control conditions in transplant stress.
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Table 1. Summary statistics for de novo transcriptome assembly.
Table 1. Summary statistics for de novo transcriptome assembly.
Assembled ContigsNumber
Total Trinity genes (n)134,369
Total Trinity transcripts (n)269,984
GC content (%)41.32
Contig N50 length (bp)1501
Average contig length (bp)874.52
Total assembled bases236,105,474
Table 2. Results of a two-way ANOVA with repeated measures across years and averages of the height and root collar diameter of P. densiflora grown at control (100% natural precipitation) and waterlogging treatment after transplanting.
Table 2. Results of a two-way ANOVA with repeated measures across years and averages of the height and root collar diameter of P. densiflora grown at control (100% natural precipitation) and waterlogging treatment after transplanting.
Yearp-Value
FactorTreatment20202021TreatmentYearTreatment × Year
Height (cm)Control63.67 ± 5.8979.00 ± 6.350.8810.4060.762
Waterlogging 63.02 ± 5.7375.15 ± 5.85
Root collar
diameter (mm)		Control11.25 ± 1.0714.28 ± 1.380.9020.4240.723
Waterlogging 12.62 ± 0.9115.68 ± 0.09
Table 3. Results of ANOVA for the height and diameter growth, the maximum photosynthetic rate (Pmax), stomatal conductance (gs), water use efficiency (WUE), leaf soluble sugars and starch, and chlorophyll content measured in P. densiflora after transplanting. Letters indicate control (100% natural precipitation; C) and waterlogging (additional irrigation 20-year average, W), and trees were transplanted in October 2020. Samples collected in 2021. TC and TW indicate trees grown at C and W in 2018–2020, respectively.
Table 3. Results of ANOVA for the height and diameter growth, the maximum photosynthetic rate (Pmax), stomatal conductance (gs), water use efficiency (WUE), leaf soluble sugars and starch, and chlorophyll content measured in P. densiflora after transplanting. Letters indicate control (100% natural precipitation; C) and waterlogging (additional irrigation 20-year average, W), and trees were transplanted in October 2020. Samples collected in 2021. TC and TW indicate trees grown at C and W in 2018–2020, respectively.
Treatmentp-Value
TCTW
Height growth
(cm)		15.33 ± 1.76
(n = 6)		12.15 ± 1.19
(n = 6)		0.166
Root collar diameter growth
(mm)		3.02 ± 0.49
(n = 6)		3.05 ± 0.17
(n = 6)		0.952
Pmax
(µmol s−1 m−2)		15.63 ± 2.67
(n = 6)		21.05 ± 2.98
(n = 4)		0.217
Stomatal conductance
(mol s−1 m−2)		0.19 ± 0.04
(n = 6)		0.32 ± 0.07
(n = 4)		0.126
WUE
(mmol mol−1)		88.11 ± 10.88
(n = 6)		70.71 ± 13.16
(n = 4)		0.334
Soluble sugars
(mg g−1)		77.60 ± 10.97
(n = 6)		46.15 ± 7.22
(n = 4)		0.059
Starch
(mg g−1)		87.89 ± 8.86
(n = 6)		43.48 ± 7.22
(n = 4)		0.007
Chlorophyll
(mg g−1)		0.41 ± 0.03
(n = 6)		0.49 ± 0.05
(n = 4)		0.201
p-values for ANOVA are in bold when significant (p < 0.05).
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MDPI and ACS Style

Byeon, S.; Kim, S.; Hong, J.; Kim, T.K.; Huh, W.; Kim, K.; Lee, M.; Lee, H.; Kim, S.; Park, C.; et al. Waterlogging Hardening Effect on Transplant Stress Tolerance in Pinus densiflora. Forests 2024, 15, 445. https://doi.org/10.3390/f15030445

AMA Style

Byeon S, Kim S, Hong J, Kim TK, Huh W, Kim K, Lee M, Lee H, Kim S, Park C, et al. Waterlogging Hardening Effect on Transplant Stress Tolerance in Pinus densiflora. Forests. 2024; 15(3):445. https://doi.org/10.3390/f15030445

Chicago/Turabian Style

Byeon, Siyeon, Seohyun Kim, Jeonghyun Hong, Tae Kyung Kim, Woojin Huh, Kunhyo Kim, Minsu Lee, Hojin Lee, Sukyung Kim, Chanoh Park, and et al. 2024. "Waterlogging Hardening Effect on Transplant Stress Tolerance in Pinus densiflora" Forests 15, no. 3: 445. https://doi.org/10.3390/f15030445

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