Next Article in Journal
Impact of Deficit Irrigation During Pre-Ripening Stages on Jujube (Ziziphus jujube Mill.‘Jing39’) Fruit-Soluble Solids Content and Cracking
Next Article in Special Issue
Special Issue: Gene Expressions in Response to Diseases, Abiotic Stresses, and Pest Damage of Horticultural Products
Previous Article in Journal
Isolation and Characterization of Pseudomonas sp. HX1, Streptomyces luteogriseus HR40, and Streptomyces flavofungini HR77 as Promising Biocontrol Agents Against Verticillium Wilt in Hops Affected by Verticillium nonalfalfae
Previous Article in Special Issue
Transcriptome and Physiological Analyses of Resistant and Susceptible Pepper (Capsicum annuum) to Verticillium dahliae Inoculum
 
 
Article
Peer-Review Record

Coordinated Regulation of Iron-Acquisition Genes and Citrate Biosynthesis Drives Seasonal Iron Deficiency Adaptation in ‘Yali’ Pears (Pyrus bretschneideri Rehd.)

Horticulturae 2025, 11(5), 460; https://doi.org/10.3390/horticulturae11050460
by Shuilin Liu 1,2,†, Ming Zhang 3,†, Huiying Wang 1, Yue Xu 1, Chaodie Wen 3, Jianguang Zhang 1, Yuxing Zhang 1,* and Haiyan Shi 1,*
Reviewer 1: Anonymous
Reviewer 2:
Reviewer 3: Anonymous
Horticulturae 2025, 11(5), 460; https://doi.org/10.3390/horticulturae11050460
Submission received: 24 March 2025 / Revised: 17 April 2025 / Accepted: 24 April 2025 / Published: 25 April 2025

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The manuscript “Coordinated Regulation of Iron-Acquisition Genes and Citrate Biosynthesis Drives Seasonal Iron Deficiency Adaptation in  ‘Yali’ Pear (Pyrus bretschneideri Rehd.)” by Liu et al. asseses the correlations between plant Fe deficiency responses and degree of chlorosis (none, medium or severe). This approach is unusual (at least to me), because rather than controlling the iron content, trees are seemingly treated the same but still develop different degrees of chlorosis. Despite some questions about the experimental approach and interpretation, I found the paper overall rather interesting to read. The data analysis was thorough and well presented, though I outline below that the occasional explanation of a concept and spelling out abbreviations would be helpful to the reader.

1) This experimental approach makes it is difficult to know cause and effect. Are plants severely chlorotic because of local soil conditions (such as pH)? This seems to be the main interpretation of the authors. Or are some plants severely chlorotic because they don’t show a proper iron deficiency response?

Doesn’t the fact that there is no difference in total iron content, but only in active iron content indicate that it is the tree that doesn’t show the proper iron deficiency response, and as a result becomes severely chlorotic, rather than a local soil Fe deficiency that “overwhelmes” the tree’s iron deficiency response? Authors suggest this interpretation themselves occasionally e.g. when they state in the results : ” which suggest that the ratio of active iron to total iron can reflect the overall iron utilization level of the plant [22].”

I suggest to keep the interpretation of cause and effects more open and acknowledge, that despite clear correlations, the causation is not that clear.

2) To help answer the question of cause and effect, it would be helpful to the reader to better understand the experiment.

Was there any difference in treatments or locations that could explain a difference in available Fe?

Were the chlorotic trees clustered in certain zones or rather intermittent?

Were there any trees that started with no or medium chlorosis and became more chlorotic over time to support the authors claim that chlorosis acted in two phases and eventually “overwhelmed” the Fe deficiency response?

 

3) Specific and minor points

ABSTRACT

 “focusing on the roles of PbFRO2, PbIRT1, and PbCS2” spell out the abbreviation for FRO2, IRT1 and CS2 at first mentioning

MATERIALS AND METHODS

 

“Approximately 0.5 g of root tissue from pear trees” How was this root tissue sampled? What part of the root system?

“FCR activity was measured according to Zheng et al. [18], with the root samples” Again, give some more information about the root samples, how much, what part of the root, in how many biological replications?

 

“2.9. Real-time PCR Analysis” because this is based on RNA, I suggest to name it  “qRT-PCR Analysis” (with RT standing for Reverse Transcriptase)

“Real-time Quantitative PCR” is redundant, “real time” makes PCR quantitative. Again, I suggest qRT-PCR.

Also, I suggest adding more information on how the qRT-PCR was performed: how was the cDNA generated? What supplier produced the supermix used for quantification? Was amplification efficiency taken into account? Was genomic DNA removed, was the absence of genomic DNA confirmed by no-RT controls?

 

RESULTS

Spell out abbreviations at first mentioning, and briefly explain concepts such as total versus active iron, SPAD values,…

“3.4. Effect of Different Chlorosis Levels on Root Iron Uptake Ability” This header again indicates that authors believe there is a causality from a cause (chlorosis) to an effect (root iron uptake), but it could as well be the other way round (less iron uptake could cause more severe chlorosis). I suggest to restate the header to keep cause and effect more open-ended (e.g “Correlation between Different Chlorosis Levels and Root Iron Uptake”. The same is true for headers 3.5 and 3.6.

“root vitality of ‘Yali’ pear under different chlorosis levels was measured” explain the concept of the “root vitality concept”

 

“To further investigate the impact of different chlorosis levels on the expression of genes involved in iron uptake and transport, we examined the expression levels of PbCS2, PbFRO2, and PbIRT” again mention the full gene name after first mentioning in the results section (even if mentioned in the introduction).

 

“These findings suggest that under moderate iron deficiency conditions, the capacity for iron transport in roots is activated, whereas under extreme deficiency, this capacity becomes limited.” Again, I find this cause-and-effect conclusion questionable; doesn’t it seem just as likely that plants that don’t show a strong iron deficiency response become more severely chlorotic as a result? There clearly is a correlation and that can be stated, but I would keep the direction of cause and effect more open.

 

“Using PCA and PLS-DA VIP analysis” spell out at first mentioning and briefly explain concept of PLS-DA VIP.

“However, as iron deficiency persists, these regulatory mechanisms gradually weaken or become suppressed.” Or the lack of response results in more severe chlorosis.

 

“This distinction underscores the complex metabolic regulatory strategies employed by pear trees under iron deficiency stress, where iron metabolism and photosynthetic deterioration occur gradually, while compensatory mechanisms peak early and subsequently wane.” To make such conclusions, one would need a different experimental design, ideally a time course of the same trees tested under increasing iron deficiency.

 

“The PLS-DA VIP analysis revealed that PbFRO2 consistently played a key role in regulating leaf chlorosis throughout the growing season” There is a correlation and that can be stated, but to say that FRO2v is “regulating leaf chlorosis” is over-stating.

 

DISCUSSION

In the discussion mention the possibility of a different interpretation of cause and effect, and explain why you believe that your current interpretation (severe Fe deficiency overwhelmes the Fe starvation response) is correct, as opposed to the possibility that “a reduced Fe deficiency responds can lead to severe chlorosis”.  

Author Response

The manuscript “Coordinated Regulation of Iron-Acquisition Genes and Citrate Biosynthesis Drives Seasonal Iron Deficiency Adaptation in ‘Yali’ Pear (Pyrus bretschneideri Rehd.)” by Liu et al. asseses the correlations between plant Fe deficiency responses and degree of chlorosis (none, medium or severe). This approach is unusual (at least to me), because rather than controlling the iron content, trees are seemingly treated the same but still develop different degrees of chlorosis. Despite some questions about the experimental approach and interpretation, I found the paper overall rather interesting to read. The data analysis was thorough and well presented, though I outline below that the occasional explanation of a concept and spelling out abbreviations would be helpful to the reader.

Response:

We deeply appreciate your invaluable comments on this manuscript. Your unselfish and impartial comments made us realize the shortcomings of our manuscript, so we decided to make a lot of revisions to the paper, sed on your comments, we have revised the manuscript as follows.

 

 

Major Comments:

 

Major Comment 1:

This experimental approach makes it is difficult to know cause and effect. Are plants severely chlorotic because of local soil conditions (such as pH)? This seems to be the main interpretation of the authors. Or are some plants severely chlorotic because they don’t show a proper iron deficiency response?

”Doesn’t the fact that there is no difference in total iron content, but only in active iron content indicate that it is the tree that doesn’t show the proper iron deficiency response, and as a result becomes severely chlorotic, rather than a local soil Fe deficiency that “overwhelmes” the tree’s iron deficiency response? Authors suggest this interpretation themselves occasionally e.g. when they state in the results: “which suggest that the ratio of active iron to total iron can reflect the overall iron utilization level of the plant [22]. ”

I suggest to keep the interpretation of cause and effects more open and acknowledge, that despite clear correlations, the causation is not that clear.

 

Response:

Thank you very much for your insightful comment. Your suggestion made us realize that we may have been too assertive in attributing the chlorosis symptoms in pear trees solely to soil iron deficiency. In reality, the situation is likely more complex, involving interactions among soil iron content, the expression levels of iron metabolism-related genes, and the degree of leaf chlorosis in 'Yali' pear. Based on your perceptive observation, we believe that future studies should include more refined control of variables to further investigate the relationships among these factors.

Since your comment here aligns with the issues raised in Minor Comment 10 and Minor Comment 15, we have provided a detailed response to those in the corresponding sections below.

 

Major Comment 2:

To help answer the question of cause and effect, it would be helpful to the reader to better understand the experiment.

  1. Was there any difference in treatments or locations that could explain a difference in available Fe?
  2. Were the chlorotic trees clustered in certain zones or rather intermittent?
  3. Were there any trees that started with no or medium chlorosis and became more chlorotic over time to support the authors claim that chlorosis acted in two phases and eventually “overwhelmed” the Fe deficiency response?

Response:

Thank you for your meticulous questions. We hereby provide additional clarifications regarding the experimental design:

All sampled pear trees were located in the same orchard with identical soil types and received no artificial treatments. The chlorosis grading was based on naturally occurring symptoms. Notably, trees with different chlorosis severity levels were not clustered spatially but rather distributed intermittently, suggesting that spatial heterogeneity of soil available iron may not be the sole determining factor.

Furthermore, we indeed observed field cases where mildly chlorotic trees progressively developed severe chlorosis over time, which supports our proposed "two-stage chlorosis model" in the manuscript. In a separate study (currently under analysis), we employed a hydroponic system to subject Pyrus betulifolia and Pyrus bretschneideri seedlings to graded Fe-deficient treatments. The preliminary results similarly demonstrated gradual chlorosis development, consistent with our field observations.

However, as you rightly pointed out, since this study did not conduct multi-year temporal sampling on individual trees, we have adopted more cautious language in presenting our inferences. We deeply appreciate the foresight embedded in your perspective. Following extensive discussions with my supervisor, we concur that implementing longitudinal time-series sampling on individual trees—as you suggested—represents a highly valuable direction for future research. This constructive suggestion will be formally incorporated into our ongoing investigations led by junior team members.

 

Minor concerns:

Minor Comment 1: Abstract

“focusing on the roles of PbFRO2, PbIRT1, and PbCS2” spell out the abbreviation for FRO2, IRT1 and CS2 at first mentioning

Response:

Thank you for your valuable comments. We have revised the abstract as follows: "focusing on the roles of PbFRO2 (Pyrus bretschneideri Ferric Reductase Oxidase 2), PbIRT1 (Pyrus bretschneideri Iron-Regulated Transporter 1), and PbCS2 (Pyrus bretschneideri Citrate Synthase 2) in iron uptake and homeostasis"(Line 21-23)

Similarly, in the Introduction section, we have provided full names for these genes at their first occurrence:" In plant iron metabolism, the genes FRO2 (Ferric Reductase Oxidase 2), IRT1 (Iron-Regulated Transporter 1), and CS2 (Citrate Synthase 2) play crucial roles in the absorption, transport, and storage of iron." (Line 60-62)

Minor Comment 2: Materials and Methods

“Approximately 0.5 g of root tissue from pear trees” How was this root tissue sampled? What part of the root system?

Response:

Thank you for your valuable suggestion. We have revised Section 2.5 to include detailed descriptions of root sampling protocols. The updated content is as follows (Line 159-172):

2.5. Root Vitality Measurement

Root vitality was determined as an indicator of metabolic activity in root tissues, reflecting the capacity for nutrient uptake and stress adaptation [16]. The assay was performed using triphenyltetrazolium chloride (TTC) reduction method [17]. Root sampling was performed at four cardinal directions (8 times trunk diameter distance from the tree base) using steel shovels. After removing surface soil, roots from 20-40 cm depth were carefully excavated through soil sieving. Secondary lateral roots (diameter <5 mm) with adhering rhizosphere soil were collected for physiological analysis. Approximately 0.5 g of root tissue from pear trees was incubated with 0.4% TTC solution and 5 mL sulfuric acid buffer (pH=7), and the root tips were fully immersed. The samples were incubated at 37°C in the dark for 2 hours, and the reaction was then terminated by adding 2 mL of 1 mol/L H2SO4. The roots were ground with ethyl acetate, washed 3 times, and triphenylformazan (TTF) was extracted. The absorbance at 485 nm was measured using a spectrophotometer (UV-2550, Shimadzu, Kyoto, Japan). Each sample was repeated 3 times.

 

Minor Comment 3: Materials and Methods

“FCR activity was measured according to Zheng et al. [18], with the root samples” Again, give some more information about the root samples, how much, what part of the root, in how many biological replications?

Response:

Thank you for your insightful comments. In response to your suggestions, we have comprehensively revised the methodology for ferric chelate reductase (FCR) enzyme assays in Section 2.6. The updated protocol is presented below(Line 173-182):

2.6. Ferric-chelate Reductase (FCR) Enzyme Activity Measurement

FCR activity was measured according to Zheng et al. [18], utilizing the same root specimens collected for root vitality assessment. Root segments were incubated in a CaSO4 (0.5 mM) solution for 10 minutes. After washing and wiping, they were placed in 5 mL enzyme activity detection solution and incubated in the dark for 1 hour. The absorbance at 535 nm was measured using a spectrophotometer (UV-2550, Shimadzu, Kyoto, Japan) and compared to a standard curve. Each sample was repeated 3 times.

Minor Comment 4: Materials and Methods

“2.9. Real-time PCR Analysis” because this is based on RNA, I suggest to name it “qRT-PCR Analysis” (with RT standing for Reverse Transcriptase)

“Real-time Quantitative PCR” is redundant, “real time” makes PCR quantitative. Again, I suggest qRT-PCR.

Response:

Thank you for your suggestion. We have revised the title of 2.9. as follows: “2.9. qRT-PCR Analysis”. (Line 210)

 

Minor Comment 5: Materials and Methods

Also, I suggest adding more information on how the qRT-PCR was performed: how was the cDNA generated? What supplier produced the supermix used for quantification? Was amplification efficiency taken into account? Was genomic DNA removed, was the absence of genomic DNA confirmed by no-RT controls?

Response:

We sincerely appreciate the reviewer's constructive feedback. The following revisions have been incorporated into the revised manuscript (Section 2.9.  Line 210-239):

2.9. qRT-PCR Analysis

Total RNA Extraction: Total RNA was extracted from pear roots using the Tiangen RNA extraction kit (TIANGEN, Beijing, China) following the manufacturer's instructions. RNA purity (A260/A280 ratio 1.8-2.0) was confirmed by UV spectrophotometry, and integrity was verified by electrophoresis on 1.2% agarose gels.

Genomic DNA removal and cDNA synthesis: Genomic DNA removal and first-strand cDNA synthesis were performed strictly following the manufacturer's instructions of the Fast QuantRT Kit (with gDNase) (TIANGEN, Beijing, China). The detailed procedures were as follows: a 10 μL reaction mixture was prepared containing 2.0 μL of 5×gDNA Buffer, 1.0 μg of total RNA, and RNase-free ddH₂O to adjust the volume. After brief centrifugation, the mixture was incubated at 42°C for 3 min and immediately placed on ice. For reverse transcription, 10 μL of RT master mix containing 2.0 μL of 10×Fast RT Buffer, 1.0 μL of RT Enzyme Mix, 2.0 μL of FQ-RT Primer Mix, and RNase-free ddH₂O to a final volume of 20 μL was added to the gDNA removed reaction solution. After thorough mixing, the reaction was performed at 42°C for 15 min, followed by heat inactivation at 95°C for 3 min.

qRT-PCR analysis: qRT-PCR was performed using the Mastercycler ep realplex4 sys-tem (Eppendorf, Hamburg, Germany) with TransStart Top Green qPCR SuperMix (AQ131, TransGen Biotech, Beijing, China). The 20 μL PCR reaction mixture contained 10 μL of TransStart SuperMix, 2.0 μL of cDNA template, 0.4 μL each of upstream and downstream primers (10 μM), and 7.2μL of ddH₂O. The thermal cycling conditions were: initial denaturation at 94°C for 30 s; 42 cycles of denaturation at 94°C for 5 s, annealing at 55°C for 15 s, and extension at 72°C for 10 s; followed by melting curve analysis (95°C for 15 s, 55°C for 60 s, and 95°C for 15 s). All samples were analyzed with three technical replicates. The pear actin gene was used as an internal reference, and relative gene expression levels were calculated using the 2-ΔΔCT method.

Primer Design: Specific primers for pear genes related to iron absorption and transport were designed by querying the NCBI database. The primers were synthesized by GeneScript Biotech (Shanghai) Co., Ltd. The gene names and sequences are listed in Table 1.

 

Minor Comment 6: Results

Spell out abbreviations at first mentioning, and briefly explain concepts such as total versus active iron, SPAD values,

Response:

Thank you for your suggestion. As recommended, we have provided the full term of "SPAD" upon its first appearance in Section 2.2. Additionally, detailed explanations for SPAD values, soil pH, soil organic matter content, and soil available iron content have been incorporated in both Sections 2.2 (Line 109-119) and 2.4(Line 133-158)to ensure methodological clarity.

 

2.2. SPAD (Soil and Plant Analyzer Development) Measurement

The SPAD meter provides a rapid and non-destructive estimation of relative chlorophyll content, which is used to visually classify the degree of leaf chlorosis. Therefore, in this study, SPAD values were measured using the SPAD-502 PLUS portable chlorophyll meter (Konica Minolta, Osaka, Japan). Measurements were conducted around 10:00 a.m. on clear days. For each tree, six healthy, pest‑free leaves from current‑year shoots were selected—specifically, the 3rd to 5th fully expanded leaves from the shoot tip—and SPAD measurements were taken at five predetermined positions along each leaf blade. The mean of these five SPAD readings was calculated for each leaf and used as its representative chlorophyll content. The very same leaves used for SPAD determination were employed in all subsequent analyses.

 

2.4. Soil Property Analysis

Soil pH reflects the acidity or alkalinity of the soil solution, which is a key factor in nutrient uptake and root activity. In this study, rhizosphere soil attached to roots during sampling was used for pH analysis [13]. Air-dried soil (passed through a 2-mm nylon-sieved) was weighed (10 g) into a 100 mL Erlenmeyer flask, mixed with 25 mL distilled water, stirred vigorously with a glass rod for 2 min, and allowed to settle for 30 min. pH values were measured using a pH meter (PB-10, Sartorius Scientific Instruments Co., Ltd., Beijing, China), with three replicates per treatment.

Soil organic matter is essential for enhancing soil fertility, structure, and water retention, thereby supporting nutrient cycling and overall ecosystem sustainability. In this study, the potassium dichromate-concentrated sulfuric acid method was used for soil organic matter analysis [14]. Briefly, 0.5 g of rhizosphere soil (passed through a 100-mesh nylon-sieved) was placed in a 250 mL Erlenmeyer flask. Then 10 mL of 1 mol/L K₂Cr₂O₇ (1/6 equivalent concentration) and 20 mL concentrated H₂SO₄ were added. The mixture was slowly rotated for 1 min, incubated for 30 min, diluted with 220 mL ultrapure water, and titrated with 0.5 mol/L FeSO₄ after adding 3-4 drops of phenanthroline indicator until the solution turned brick-red. Calculations were performed according to standard formulae.

Available iron refers to the proportion of iron that can be absorbed by plants. In this study, the DTPA extraction method was used for available iron analysis [15]. Specifically, 10.0 g of air-dried rhizosphere soil (2-mm nylon-sieved) was mixed with 20.0 mL DTPA extractant (pH 7.30; containing 0.005 mol/L DTPA, 0.01 mol/L CaCl₂, and 0.1 mol/L triethanolamine, adjusted to pH 7.30 with 6 mol/L HCl) in a 100 mL Erlenmeyer flask. The suspension was shaken at 180 rpm for 2 h at 25°C, immediately filtered, and the filtrate was analyzed by ICP-AES (PerkinElmer Optima 8000, Waltham, MA, USA). A standard calibration curve was established using iron reference materials prior to quantification.

 

Minor Comment 7: Results

“3.4. Effect of Different Chlorosis Levels on Root Iron Uptake Ability” This header again indicates that authors believe there is a causality from a cause (chlorosis) to an effect (root iron uptake), but it could as well be the other way round (less iron uptake could cause more severe chlorosis). I suggest to restate the header to keep cause and effect more open-ended (e.g “Correlation between Different Chlorosis Levels and Root Iron Uptake”. The same is true for headers 3.5 and 3.6.

Response:

Thank you for the valuable suggestion. We have revised the section titles to reflect correlation rather than causation.

3.2. Correlation between Different Chlorosis Levels and Iron Content

3.3. Correlation between Different Chlorosis Levels and Relative Chlorophyll Content and Chlorophyll Fluorescence Parameters

3.4. Correlation between Different Chlorosis Levels and Root Iron Uptake Ability

3.5. Correlation between Different Chlorosis Levels and Citrate Content

3.6. Correlation between Different Chlorosis Levels and the Expression of Iron Uptake-Related Genes

Minor Comment 8: Results

“root vitality of ‘Yali’ pear under different chlorosis levels was measured” explain the concept of the “root vitality concept”

Response:

Thank you very much for your suggestion. We have explained the concept of “root vitality” in section 2.5. Materials and methods.

(Line 159-172)

2.5. Root Vitality Measurement

Root vitality was determined as an indicator of metabolic activity in root tissues, reflecting the capacity for nutrient uptake and stress adaptation [16]. The assay was performed using triphenyltetrazolium chloride (TTC) reduction method [17]. Root sampling was performed at four cardinal directions (8 times trunk diameter distance from the tree base) using steel shovels. After removing surface soil, roots from 20-40 cm depth were carefully excavated through soil sieving. Secondary lateral roots (diameter <5 mm) with adhering rhizosphere soil were collected for physiological analysis. Approximately 0.5 g of root tissue from pear trees was incubated with 0.4% TTC solution and 5 mL sulfuric acid buffer (pH=7), and the root tips were fully immersed. The samples were incubated at 37°C in the dark for 2 hours, and the reaction was then terminated by adding 2 mL of 1 mol/L H2SO4. The roots were ground with ethyl acetate, washed 3 times, and triphenylformazan (TTF) was extracted. The absorbance at 485 nm was measured using a spectrophotometer (UV-2550, Shimadzu, Kyoto, Japan). Each sample was repeated 3 times.

 

Minor Comment 9: Results

“To further investigate the impact of different chlorosis levels on the expression of genes involved in iron uptake and transport, we examined the expression levels of PbCS2, PbFRO2, and PbIRT” again mention the full gene name after first mentioning in the results section (even if mentioned in the introduction).

Response:

Thank you very much for your comments, we have revised section 3.6. as follows (Line 379-382):

 

To further investigate the impact of different chlorosis levels on the expression of genes involved in iron uptake and transport, we examined the expression levels of PbCS2 (Pyrus bretschneideri Citrate Synthase 2), PbFRO2 (Pyrus bretschneideri Ferric Reductase Oxidase 2), and PbIRT1 (Pyrus bretschneideri Iron-Regulated Transporter 1) in the roots of ‘Yali’ pear (see Fig. 6).

 

Minor Comment 10: Results

“These findings suggest that under moderate iron deficiency conditions, the capacity for iron transport in roots is activated, whereas under extreme deficiency, this capacity becomes limited.” Again, I find this cause-and-effect conclusion questionable; doesn’t it seem just as likely that plants that don’t show a strong iron deficiency response become more severely chlorotic as a result? There clearly is a correlation and that can be stated, but I would keep the direction of cause and effect more open.

Response:

Thank you very much for your comment. We have revised the original causal implication to a correlation-based description. The revised content is as follows (Line 397-399):

“Our findings revealed a significant negative correlation between iron deficiency status and root iron translocation capacity in pear trees, with enhanced root iron transport activity under moderate deficiency but markedly reduced capacity observed during severe leaf chlorosis.”

 

Minor Comment 11: Results

“Using PCA and PLS-DA VIP analysis” spell out at first mentioning and briefly explain concept of PLS-DA VIP.

 

Response:

Thank you for your comments, we have revised section 3.7 as follows(Line 405-420):

 

3.7. Multivariate Analysis of Physiological Traits and Gene Expression

Principal Component Analysis (PCA) is an unsupervised statistical method that transforms high-dimensional data into a smaller number of principal components, thereby revealing overall differences and distribution patterns among samples. Partial Least Squares Discriminant Analysis (PLS-DA) is a supervised multivariate analysis technique used to identify variables that effectively distinguish between different treatment groups, while the Variable Importance in Projection (VIP) score is used to evaluate the importance of each variable in the classification model.

Therefore, to further elucidate the physiological changes and molecular regulatory mechanisms of pear trees under iron deficiency stress, we performed multivariate analysis on the measured physiological parameters and the expression levels of iron metabolism-related genes. We applied PCA and PLS-DA analyses, combined with VIP scoring, to assess the contribution of each variable to group discrimination. Through these methods, we aimed to uncover the effects of chlorosis severity on iron uptake, transport, and utilization in pear trees, with particular emphasis on the roles of the PbCS2, PbIRT1, and PbFRO2 genes.

Minor Comment 12: Results

“However, as iron deficiency persists, these regulatory mechanisms gradually weaken or become suppressed.” Or the lack of response results in more severe chlorosis.

Response:

Thank you for your comment. We have revised the sentence “These genes are upregulated in the early stages of chlorosis to enhance iron acquisition and redistribution. However, as iron deficiency persists, these regulatory mechanisms gradually weaken or become suppressed.” to: “During the early stages of chlorosis, these genes are upregulated to enhance iron acquisition and redistribution. However, as iron deficiency continues, these regulatory mechanisms gradually weaken or become suppressed, potentially exacerbating the severity of chlorosis. ” (Line 448-451)

Minor Comment 13: Results

“This distinction underscores the complex metabolic regulatory strategies employed by pear trees under iron deficiency stress, where iron metabolism and photosynthetic deterioration occur gradually, while compensatory mechanisms peak early and subsequently wane.” To make such conclusions, one would need a different experimental design, ideally a time course of the same trees tested under increasing iron deficiency.

Response:

Thank you very much for your comment. We agree that our previous conclusion was too hasty, and the data from this study are not sufficient to support such a statement. We have revised this part of the content as follows(Line 455-459):

Overall, these findings demonstrate a dual-phase physiological adaptation strategy in pear trees under iron-deficient conditions: PC1 represents the primary and progressive physiological alterations, whereas PC2 reflects a transient adaptive mechanism that is initially activated and later declines. This distinction underscores the complex metabolic regulatory strategies employed by pear trees under iron deficiency stress.

Minor Comment 14: Results

“The PLS-DA VIP analysis revealed that PbFRO2 consistently played a key role in regulating leaf chlorosis throughout the growing season” There is a correlation and that can be stated, but to say that FRO2v is “regulating leaf chlorosis” is over-stating.

Response:

Thank you for highlighting this point. We agree that the PLS-DA analysis identifies variables associated with group discrimination, but does not prove regulatory function. We have revised the sentence to (Line 470-471):

“The PLS-DA VIP analysis identified PbFRO2 as a consistently significant variable (VIP >1.5) associated with leaf chlorosis severity across all sampled growth stages (Fig. 8). ”

Minor Comment 15: Discussion and Conclusion

In the discussion mention the possibility of a different interpretation of cause and effect, and explain why you believe that your current interpretation (severe Fe deficiency overwhelmes the Fe starvation response) is correct, as opposed to the possibility that “a reduced Fe deficiency responds can lead to severe chlorosis”.

 

Response:

Thank you very much for your suggestion. In the "Discussion and Conclusion" section, we have revised the original statement that "iron deficiency-induced chlorosis in pear trees is caused solely by insufficient iron supply from the soil" to a more open expression: "iron deficiency-induced chlorosis in pear trees is associated with both limited soil iron availability and the plant's insufficient response to iron deficiency." The specific revision is as follows:

  1. Discussion and Conclusion

In this study, the active iron content in leaves of moderately and severely chlorotic groups was significantly reduced compared to the normal group, paralleling the decline in chlorophyll levels, which could be attributed to the critical role of iron in chlorophyll biosynthesis [29, 30]. Consistent with the "chlorosis paradox" observed in previous studies [31], total iron content in normal, mildly, and severely chlorotic leaves exhibited irregular fluctuations, indicating that total iron cannot serve as a reliable diagnostic indicator for the iron nutritional status of 'Yali' pear.

The molecular regulatory mechanism of iron uptake in 'Yali' pear exhibits a stage-specific response to chlorosis severity. Under moderate iron deficiency, root FCR activity and PbFRO2 expression are upregulated, consistent with the classical Strategy I mechanism of enhancing Fe3+ reduction and solubilization to counteract iron deficiency [13]. However, severe iron deficiency suppresses FCR activity, likely due to irreversible enzyme denaturation or cellular redox imbalance, further exacerbating iron limitation. Concurrently, the upregulation of PbIRT1 in moderate chlorotic roots mirrors the activation of Fe2+ transporters observed in Arabidopsis [32], indicating evolutionary conservation of iron uptake mechanisms in dicots. The CS2 gene plays a pivotal role in citrate biosynthesis, exerting dual functions in iron activation and transport through citrate metabolism [33]. In this study, leaf citrate content progressively accumulated with increasing chlorosis severity, while root citrate content (excluding July samples) exhibited a similar trend.

Multivariate analyses revealed a biphasic adaptation strategy. PCA demonstrated progressive physiological divergence, with severely chlorotic leaves forming a distinct cluster separate from normal and moderately chlorotic leaves (Figure 7A), indicating threshold-dependent collapse of metabolic and molecular adjustment mechanisms. PLSDA-VIP identified PbFRO2 as a core regulatory factor (VIP > 1.5, Table 4), whose expression strongly correlated with FCR activity (r = 0.73, P < 0.01) and active iron redistribution. Notably, transcript levels of PbFRO2, PbIRT1, and PbCS2 peaked in moderately chlorotic plants but markedly declined under severe stress (Figure 3D). This pattern suggests two potential mechanisms: (1) Plants may maintain a minimal transcriptional threshold of these genes to achieve adaptive iron homeostasis regulation; beyond this threshold, compensatory mechanisms fail, leading to irreversible physiological damage. (2) Transcriptional suppression of PbFRO2, PbIRT1, and PbCS2 could exacerbate iron deficiency chlorosis in pear trees, creating a self-reinforcing vicious cycle.

This study deciphered the molecular regulatory mechanisms underlying iron deficiency chlorosis in 'Yali' pear through integrative analyses. Under moderate iron deficiency, the synergistic upregulation of PbFRO2, PbIRT1, and PbCS2 likely triggered a compensatory cascade, alleviating chlorosis via enhanced Fe3+ reduction, Fe2+ transport, and citrate-mediated long-distance iron translocation. Conversely, severe iron deficiency potentially overwhelmed the regulatory network capacity, inducing gene expression threshold effects, inactivation of FCR, and photosynthetic dysfunction, ultimately disrupting iron homeostasis (these mechanisms require further validation). Organ-specific citrate dynamics revealed divergent adaptive strategies: leaf citrate prioritized iron reactivation to sustain photosynthetic function, while root citrate modulated seasonal iron allocation through concentration fluctuations. These findings establish a "gene-metabolite-phenotype" tripartite framework elucidating the molecular basis of iron stress in alkaline soils, with PbFRO2 serving as a central hub gene driving adaptive responses and offering potential targets for iron biofortification.

This work systematically characterizes the dynamic physiological and molecular adaptations during iron-deficient chlorosis in 'Yali' pear, providing novel insights into iron homeostasis regulation in perennial fruit trees and guiding iron-efficient cultivar breeding and precision fertilization in calcareous soils. However, the etiology of pear chlorosis remains dual-natured: whether it primarily stems from insufficient soil iron availability or compromised plant iron response capacity warrants resolution. To address this, follow-up studies will employ controlled iron supplementation combined with PbFRO2 overexpression and knockout approaches to dissect the causation of chlorosis and delineate the functional network of this pivotal gene.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The manuscript “Coordinated Regulation of Iron-Acquisition Genes and Citrate Biosynthesis Drives Seasonal Iron Deficiency Adaptation in ‘Yali’ Pear (Pyrus bretschneideri Rehd.)” by Liu et al. presents the physiological and molecular responses of yali pear trees to varying degrees of iron deficiency chlorosis in alkaline soils, focusing on the roles of PbFRO2, PbIRT1, and PbCS2 genes in iron uptake and homeostasis. This study found that moderate iron deficiency in yali plants resulted in increased PbFRO2 expression, enhanced root ferric reductase activity, and improved iron uptake. However, severe iron deficiency had the opposite effect, suppressing these processes and decreasing photosynthetic efficiency. Multivariate analyses showed a shift from compensatory activation to metabolic collapse under severe chlorosis, with PbFRO2 identified as a crucial regulator of iron storage and redistribution. Overall, the study reveals a two-phase adaptation strategy in yali in response to iron deficiency and suggests PbFRO2 as a potential target for breeding iron-efficient cultivars.

 

The article demonstrates strong presentation quality. Minor refinements to the introduction and methodology sections are suggested.:

 

Introduction:

 

Lines 41-42: “Iron deficiency chlorosis is a global limiting factor for plant growth, manifesting as chlorosis, slow growth, and significant reductions in fruit yield and quality”. The authors could specify that other important plants or crops are also affected by this type of deficiency.

 

Lines 52-63. The authors could specify in which other plants these mechanisms were identified.

 

Materials and Methods:

 

Lines 78-79: “The field experiment was conducted at the pear orchard of Hebei Agricultural University”. Please describe the weather conditions at the time the experiment was conducted, and indicate the predominant soil type in that area.

 

Lines 81-86. Explain how individuals were classified into groups with different degrees of chlorosis. Was it only a qualitative classification or were quantitative criteria used?

 

Lines 81-86. What was the experimental design used?

 

Lines 90-91: “Leaf SPAD values were measured using a SPAD-502 PLUS portable chlorophyll meter (Konica Minolta, Osaka, Japan)”. Please, indicate the time of day at which the measurement was taken, as this may cause variations in the data.

 

Lines 95-97: “The chlorophyll fluorescence parameter Fv/Fm was measured using a Handy-PEA fluorimeter Multifunctional Plant Efficiency Analyzer (Hansatech Instruments Ltd., Pentney, Norfolk, UK), according to the device's instructions”. Was a dark adaptation period performed before measurements? If applicable, please indicate how.

Line 99: “Soil pH was measured using the soil extraction method”. Please, provide more details about this method.

 

Lines 101-103: “Soil organic matter was determined by the potassium dichromate-concentrated sulfuric acid method [15]. Available Fe in the soil was measured using the DTPA extraction method [16]”. It would be advisable to briefly describe both methods.

 

Lines 110-111: “The absorbance at 485 nm was measured using a spectrophotometer”. Please, specify the model of spectrophotometer used.

 

Line 116: “The absorbance at 535 nm was measured and compared to a standard curve”. Indicate where the measurement was made.

 

Lines 118-119: “Total iron and active iron content was measured using inductively coupled plasma atomic emission spectrometer”. Was a calibration process performed previously?

 

Line 118: “....using inductively coupled…”. Replace by “....using an inductively coupled…”

 

Lines 131-135. Rephrase the paragraph with connectors describing the chromatography conditions.

 

Lines 137-155. As in the previous case, Rephrase the paragraph with connectors describing the respective methodology.

 

Lines 140-142: “The extracted total RNA was used as a template for cDNA synthesis, which was performed using the Tiangen Fast Quant RT Kit (containing gDNA)”. Describe which conditions were used for cDNA synthesis. Additionally, the authors should provide details on the cDNA quantification.

 

Lines 154-155: “The pear actin gene was used as the internal reference, and relative gene expression was analyzed using the 2-ΔΔCT method”. Why was actin used as a reference gene?

Comments on the Quality of English Language

The manuscript requires revision by a native language specialist to address grammatical errors and improve paragraph structure.

Author Response

The manuscript “Coordinated Regulation of Iron-Acquisition Genes and Citrate Biosynthesis Drives Seasonal Iron Deficiency Adaptation in ‘Yali’ Pear (Pyrus bretschneideri Rehd.)” by Liu et al. presents the physiological and molecular responses of yali pear trees to varying degrees of iron deficiency chlorosis in alkaline soils, focusing on the roles of PbFRO2, PbIRT1, and PbCS2 genes in iron uptake and homeostasis. This study found that moderate iron deficiency in yali plants resulted in increased PbFRO2 expression, enhanced root ferric reductase activity, and improved iron uptake. However, severe iron deficiency had the opposite effect, suppressing these processes and decreasing photosynthetic efficiency. Multivariate analyses showed a shift from compensatory activation to metabolic collapse under severe chlorosis, with PbFRO2 identified as a crucial regulator of iron storage and redistribution. Overall, the study reveals a two-phase adaptation strategy in yali in response to iron deficiency and suggests PbFRO2 as a potential target for breeding iron-efficient cultivars.

 

The article demonstrates strong presentation quality. Minor refinements to the introduction and methodology sections are suggested.

 

Thank you very much for your positive comments on this research, and we deeply appreciate your invaluable comments on this manuscript. Based on your comments, we have revised the manuscript as follows:

 

 

 

Minor Comments:

 

Minor Comment 1: Introduction

 

Lines 41-42: “Iron deficiency chlorosis is a global limiting factor for plant growth, manifesting as chlorosis, slow growth, and significant reductions in fruit yield and quality”. The authors could specify that other important plants or crops are also affected by this type of deficiency.

 

Response:

Thank you for your suggestion. As per your reminder, we have added a statement noting that soybeans, grapes, and citrus are also affected by iron deficiency. The revised version is as follows (Line 44-47):

Iron deficiency chlorosis is a global limiting factor for plant growth, manifesting as chlorosis, slow growth, and significant reductions in fruit yield and quality, including soybean (Glycine max (L.) Merr.) [1], grapevine (Vitis vinifera L.) [2], and citrus (Citrus spp.) [3].

 

Minor Comment 2: Introduction

Lines 52-63. The authors could specify in which other plants these mechanisms were identified.

Response:

Thank you for your meticulous review. We have carefully revised this section based on your comments and respectfully invite you to review the updated content. The revised version is as follows (Line 60-75):

In plant iron metabolism, the genes FRO2 (Ferric Reductase Oxidase 2), IRT1 (Iron-Regulated Transporter 1), and CS2 (Citrate Synthase 2) play crucial roles in the absorption, transport, and storage of iron. First, studies on Cydonia oblonga seedlings have revealed that the FRO2 gene encodes a ferric reductase enzyme that reduces ferric iron (Fe³⁺) to ferrous iron (Fe²⁺) in the soil, a process essential for iron absorption by plant roots [9]. Following this, research in Arabidopsis has demonstrated that the IRT1 gene encodes an iron transporter protein responsible for transferring the reduced Fe²⁺ from the soil into root cells, representing a critical step in iron uptake [10, 11]. Lastly, investigations on Malus xiaojinensis have shown that the CS2 gene regulates citrate synthesis, which facilitates iron transport and storage. Citrate binds with Fe²⁺ to form soluble complexes, enabling iron translocation across tissues and ensuring its efficient utilization and storage [12]. These genes collectively function through the classical Strategy I mechanism of enhancing Fe³⁺ reduction and solubilization to counteract iron deficiency [13].The coordinated action of these three genes is essential for the plant’s response to iron deficiency, collectively regulating iron metabolism and ensuring that the plant can maintain normal growth and development.

 

 

 

Minor Comment 3: Materials and Methods

 

Lines 78-79: “The field experiment was conducted at the pear orchard of Hebei Agricultural University”. Please describe the weather conditions at the time the experiment was conducted, and indicate the predominant soil type in that area.

 

Response:

We greatly appreciate your comment. Indeed, weather and soil conditions have a significant impact on fruit tree cultivation. The revised version is as follows (Line 89-106):

2.1. Plant Materials and Growth Conditions

The field experiment was conducted at the pear orchard of Hebei Agricultural University (38.814 N, 115.422 E). The region has a temperate monsoon climate, with an average temperature of 26°C and relative humidity of 55% during the experimental period. The soil is classified as calcareous cinnamon soil. The experimental material consisted of seven-year-old ‘Yali’ pear trees with varying degrees of chlorosis. The trees were planted at a row spacing of 3 m and tree spacing of 1 m, following conventional fertilizer and water management practices. The experimental trees were categorized into three groups based on the degree of chlorosis: Group 1 (Normal) with no chlorosis, Group 2 (Moderate chlorosis) with leaf interveinal chlorosis and green midribs (25%-50% chlorosis of the leaves), and Group 3 (Severe chlorosis) with complete loss of green color, resulting in a yellowish-white appearance (over 75% chlorosis of the leaves). Five replicates were set for each group. To assist in the classification, SPAD (Soil Plant Analysis Development) values were measured at the beginning of the experiment in May. Leaves exhibiting dark green coloration were assigned a SPAD value of 1. Moderately chlorotic leaves had SPAD values approximately 50% of normal, and severely chlorotic leaves had SPAD values below 25% of normal. Given that the normal SPAD value for leaves was 35, moderate chlorotic leaves had SPAD values around 20, and those with severe chlorosis had SPAD values below 10.

 

 

Minor Comment 4: Materials and Methods

Lines 81-86. Explain how individuals were classified into groups with different degrees of chlorosis. Was it only a qualitative classification or were quantitative criteria used?

Response:

Thank you for your comment. We have explained this in detail in “2.1. Plant Materials and Growth Conditions” as follows:

2.1. Plant Materials and Growth Conditions

The field experiment was conducted at the pear orchard of Hebei Agricultural University (38.814 N, 115.422 E). The region has a temperate monsoon climate, with an average temperature of 26°C and relative humidity of 55% during the experimental period. The soil is classified as calcareous cinnamon soil. The experimental material consisted of seven-year-old ‘Yali’ pear trees with varying degrees of chlorosis. The trees were planted at a row spacing of 3 m and tree spacing of 1 m, following conventional fertilizer and water management practices. The experimental trees were categorized into three groups based on the degree of chlorosis: Group 1 (Normal) with no chlorosis, Group 2 (Moderate chlorosis) with leaf interveinal chlorosis and green midribs (25%-50% chlorosis of the leaves), and Group 3 (Severe chlorosis) with complete loss of green color, resulting in a yellowish-white appearance (over 75% chlorosis of the leaves). Five replicates were set for each group. To assist in the classification, SPAD (Soil Plant Analysis Development) values were measured at the beginning of the experiment in May. Leaves exhibiting dark green coloration were assigned a SPAD value of 1. Moderately chlorotic leaves had SPAD values approximately 50% of normal, and severely chlorotic leaves had SPAD values below 25% of normal. Given that the normal SPAD value for leaves was 35, moderate chlorotic leaves had SPAD values around 20, and those with severe chlorosis had SPAD values below 10.

 

 

Minor Comment 5: Materials and Methods

Lines 81-86. What was the experimental design used?

Response:

In our orchard, we observed that under the same field planting conditions, pear trees exhibited different growth states, primarily in terms of varying degrees of chlorosis. Therefore, this study is not a controlled variable experiment. Instead, we analyzed leaf and root tissue samples from pear trees with different phenotypes, all growing under the same conditions. This analysis aimed to explore the physiological and molecular causes of these differences, with the goal of providing new insights into addressing iron deficiency-induced chlorosis in pear trees.

 

 

Minor Comment 6: Materials and Methods

Lines 90-91: “Leaf SPAD values were measured using a SPAD-502 PLUS portable chlorophyll meter (Konica Minolta, Osaka, Japan)”. Please, indicate the time of day at which the measurement was taken, as this may cause variations in the data. 

Response:

Thank you for your comments. We have revised section 2.2 as follows:

 

2.2. SPAD (Soil and Plant Analyzer Development) Measurement

The SPAD meter provides a rapid and non-destructive estimation of relative chlorophyll content, which is used to visually classify the degree of leaf chlorosis. Therefore, in this study, SPAD values were measured using the SPAD-502 PLUS portable chlorophyll meter (Konica Minolta, Osaka, Japan). Measurements were conducted around 10:00 a.m. on clear days. For each tree, six healthy, pest‑free leaves from current‑year shoots were selected—specifically, the 3rd to 5th fully expanded leaves from the shoot tip​—and SPAD measurements were taken at five predetermined positions along each leaf blade​. The mean of these five SPAD readings was calculated for each leaf and used as its representative chlorophyll content. The very same leaves used for SPAD determination were employed in all subsequent analyses.

 

 

Minor Comment 7: Materials and Methods

Lines 95-97: “The chlorophyll fluorescence parameter Fv/Fm was measured using a Handy-PEA fluorimeter Multifunctional Plant Efficiency Analyzer (Hansatech Instruments Ltd., Pentney, Norfolk, UK), according to the device's instructions”. Was a dark adaptation period performed before measurements? If applicable, please indicate how.

Response:

Thank you for your comment. Our method section was overly brief, which may have caused confusion for the readers. In response, we have revised section 2.3 as follows:

 

2.3. Chlorophyll Fluorescence Measurement

The leaf chlorophyll fluorescence parameter Fv/Fm was measured using a Handy-PEA fluorimeter Multifunctional Plant Efficiency Analyzer (Hansatech Instruments Ltd., Pentney, Norfolk, UK). Following manufacturer recommendations, leaf samples underwent 20-minute dark adaptation at 25°C prior to measurement to ensure complete relaxation of all PSII reaction centers. Measurements were performed on the mid-lamina region, an area less susceptible to edge effects and representative of overall photosynthetic performance. Two technical replicates per leaf and three biological replicates per experimental treatment were recorded to ensure data robustness and statistical reliability.

 

Minor Comment 8: Materials and Methods

Line 99: “Soil pH was measured using the soil extraction method”. Please, provide more details about this method.

 

Minor Comment 9: Materials and Methods

Lines 101-103: “Soil organic matter was determined by the potassium dichromate-concentrated sulfuric acid method [15]. Available Fe in the soil was measured using the DTPA extraction method [16]”. It would be advisable to briefly describe both methods.

Response:

Dear Reviewer, thank you for your insightful comments. Since your comments 8 and 9 are similar, we are addressing them together. We acknowledge that the descriptions of soil pH, organic matter, and the methods for measuring available iron were overly simplified. We have now made the following revisions to these sections (Line 133-158):

 

2.4. Soil Property Analysis

Soil pH reflects the acidity or alkalinity of the soil solution, which is a key factor in nutrient uptake and root activity. In this study, rhizosphere soil attached to roots during sampling was used for pH analysis [13]. Air-dried soil (passed through a 2-mm nylon-sieved) was weighed (10 g) into a 100 mL Erlenmeyer flask, mixed with 25 mL distilled water, stirred vigorously with a glass rod for 2 min, and allowed to settle for 30 min. pH values were measured using a pH meter (PB-10, Sartorius Scientific Instruments Co., Ltd., Beijing, China), with three replicates per treatment.

Soil organic matter is essential for enhancing soil fertility, structure, and water retention, thereby supporting nutrient cycling and overall ecosystem sustainability. In this study, the potassium dichromate-concentrated sulfuric acid method was used for soil organic matter analysis [14]. Briefly, 0.5 g of rhizosphere soil (passed through a 100-mesh nylon-sieved) was placed in a 250 mL Erlenmeyer flask. Then 10 mL of 1 mol/L K₂Cr₂O₇ (1/6 equivalent concentration) and 20 mL concentrated H₂SO₄ were added. The mixture was slowly rotated for 1 min, incubated for 30 min, diluted with 220 mL ultrapure water, and titrated with 0.5 mol/L FeSO₄ after adding 3-4 drops of phenanthroline indicator until the solution turned brick-red. Calculations were performed according to standard formulae.

Available iron refers to the proportion of iron that can be absorbed by plants. In this study, the DTPA extraction method was used for available iron analysis [15]. Specifically, 10.0 g of air-dried rhizosphere soil (2-mm nylon-sieved) was mixed with 20.0 mL DTPA extractant (pH 7.30; containing 0.005 mol/L DTPA, 0.01 mol/L CaCl₂, and 0.1 mol/L triethanolamine, adjusted to pH 7.30 with 6 mol/L HCl) in a 100 mL Erlenmeyer flask. The suspension was shaken at 180 rpm for 2 h at 25°C, immediately filtered, and the filtrate was analyzed by ICP-AES (PerkinElmer Optima 8000, Waltham, MA, USA). A standard calibration curve was established using iron reference materials prior to quantification.

 

 

Minor Comment 10: Materials and Methods

Lines 110-111: “The absorbance at 485 nm was measured using a spectrophotometer”. Please, specify the model of spectrophotometer used.

 

Response:

Thanks for your comments, we have added the UV-Vis spectrophotometer model. (Line 171-172)

The absorbance at 485 nm was measured using a spectrophotometer (UV-2550, Shimadzu, Kyoto, Japan). Each sample was repeated 3 times.

 

 

 

Minor Comment 11: Materials and Methods

Line 116: “The absorbance at 535 nm was measured and compared to a standard curve”. Indicate where the measurement was made.

Response:

Thank you for your comment, we have supplemented this part as follows (Line 179-182):

After the reaction, 2 mL of the colored supernatant was transferred to a 1 cm quartz cuvette and measured at 535 nm using a UV-2550 UV-Vis spectrophotometer (Shimadzu, Kyoto, Japan). A standard curve was established before measuring the samples. Each sample was repeated 3 times.

 

 

Minor Comment 12: Materials and Methods

Lines 118-119: “Total iron and active iron content was measured using inductively coupled plasma atomic emission spectrometer”. Was a calibration process performed previously?

Response:

We greatly appreciate your review comments. Prior to conducting ICP-AES analysis in this study, calibration was performed as follows: wavelength calibration was carried out using the instrument's built-in software system, and analytical calibration was achieved by establishing a standard curve, with measurements taken within the range of this curve. Additionally, we have revised section 2.7 as follows:

 

2.7. Total and Active Iron Measurement in Leaves

Total iron and active iron content was measured using an inductively coupled plasma atomic emission spectrometer (ICP-AES, PerkinElmer Optima 8000, Waltham, MA, USA), with slight modifications to the method of Zhang et al. [19]. Prior to sample analysis, calibration procedures were carried out; wavelength calibration was performed using the instrument’s built‐in software system, and analytical calibration was achieved by constructing a standard calibration curve, ensuring that measurements were conducted within the curve’s linear range. Leaf samples were dried at 105°C for 40 minutes and further dried at 75°C to constant weight. After grinding, 1 g of dried leaf powder was digested with 20 mL HNO3 and 5 mL HClO4, and the solution was diluted to 50 mL. The total iron content was then quantified using an ICP-AES.

Active iron content in fresh leaf or root samples (0.25 g) was extracted with 10 mL 1 mol/L HCl on a shaker for 12 hours, filtered, diluted to 25 mL, and measured by ICP-AES.

 

 

Minor Comment 13: Materials and Methods

Line 118: “....using inductively coupled…”. Replace by “....using an inductively coupled…”

Response:

Thank you for your comment. I acknowledge that my English proficiency needs improvement. We have made the revisions as per your request, as follows (Line 184-186):

Total iron and active iron content was measured using an inductively coupled plasma atomic emission spectrometer (ICP-AES, PerkinElmer Optima 8000, Waltham, MA, USA), with slight modifications to the method of Zhang et al. [17].

 

 

 

Minor Comment 14: Materials and Methods

Lines 131-135. Rephrase the paragraph with connectors describing the chromatography conditions.

Response:

Thank you very much for your comment. Our previous wording may have caused some misunderstanding among readers. We have revised this section accordingly, and the updated version is as follows (Line 196-209):

 

2.8. Measurement of Citrate in New Roots and Leaves

Citrate content was quantified by high-performance liquid chromatography (HPLC) following the protocol of Lucarini et al. [20]. Briefly, approximately 0.2 g of fresh roots or leaves were homogenized in liquid nitrogen, followed by extraction with ddH₂O to a final volume of 1.5 mL. The mixture was incubated at 75°C for 30 minutes and subsequently centrifuged at 12,000 × g for 30 minutes. After centrifugation, the supernatant was filtered through a 0.22 μm membrane prior to HPLC analysis.

Chromatographic conditions were as follows: An Agilent 1260 HPLC system (Agilent Technologies, Santa Clara, CA, USA) equipped with a UV detector was employed. Separations were achieved using an isocratic method with an Eclipse Plus C18 column (4.6 mm × 250 mm, 5 μm particle size) maintained at 25°C. The mobile phase consisted of 0.02 mol/L potassium dihydrogen phosphate buffer (pH 2.8), which was delivered isocratically at a flow rate of 0.5 mL/min. Finally, a 10 μL aliquot of the processed sample was injected for each analysis.

 

Minor Comment 15: Materials and Methods

Lines 137-155. As in the previous case, Rephrase the paragraph with connectors describing the respective methodology.

Minor Comment 16: Materials and Methods

Lines 140-142: “The extracted total RNA was used as a template for cDNA synthesis, which was performed using the Tiangen Fast Quant RT Kit (containing gDNA)”. Describe which conditions were used for cDNA synthesis. Additionally, the authors should provide details on the cDNA quantification.

Response:

Thank you very much for your comments 15 and 16. Since these two comments are closely related, please allow us to address them together. In light of your feedback and the comments from the other two reviewers, we have made extensive revisions to section "2.9." and kindly ask you to review it again. The updated version is as follows (Section 2.9. Line 210-239):

 

2.9. qRT-PCR Analysis

Total RNA Extraction: Total RNA was extracted from pear roots using the Tiangen RNA extraction kit (TIANGEN, Beijing, China) following the manufacturer's instructions. RNA purity (A260/A280 ratio 1.8-2.0) was confirmed by UV spectrophotometry, and integrity was verified by electrophoresis on 1.2% agarose gels.

Genomic DNA removal and cDNA synthesis: Genomic DNA removal and first-strand cDNA synthesis were performed strictly following the manufacturer's instructions of the Fast QuantRT Kit (with gDNase) (TIANGEN, Beijing, China). The detailed procedures were as follows: a 10 μL reaction mixture was prepared containing 2.0 μL of 5×gDNA Buffer, 1.0 μg of total RNA, and RNase-free ddH₂O to adjust the volume. After brief centrifugation, the mixture was incubated at 42°C for 3 min and immediately placed on ice. For reverse transcription, 10 μL of RT master mix containing 2.0 μL of 10×Fast RT Buffer, 1.0 μL of RT Enzyme Mix, 2.0 μL of FQ-RT Primer Mix, and RNase-free ddH₂O to a final volume of 20 μL was added to the gDNA removed reaction solution. After thorough mixing, the reaction was performed at 42°C for 15 min, followed by heat inactivation at 95°C for 3 min.

qRT-PCR analysis: qRT-PCR was performed using the Mastercycler ep realplex4 system (Eppendorf, Hamburg, Germany) with TransStart Top Green qPCR SuperMix (AQ131, TransGen Biotech, Beijing, China). The 20 μL PCR reaction mixture contained 10 μL of TransStart SuperMix, 2.0 μL of cDNA template, 0.4 μL each of upstream and downstream primers (10 μM), and 7.2μL of ddH₂O. The thermal cycling conditions were: initial dena-turation at 94°C for 30 s; 42 cycles of denaturation at 94°C for 5 s, annealing at 55°C for 15 s, and extension at 72°C for 10 s; followed by melting curve analysis (95°C for 15 s, 55°C for 60 s, and 95°C for 15 s). All samples were analyzed with three technical replicates. The pear actin gene was used as an internal reference, and relative gene expression levels were calculated using the 2-ΔΔCT method.

Primer Design: Specific primers for pear genes related to iron absorption and transport were designed by querying the NCBI database. The primers were synthesized by GeneScript Biotech (Shanghai) Co., Ltd. The gene names and sequences are listed in Table 1.

 

 

Minor Comment 17: Materials and Methods

Comment 1:Lines 154-155: “The pear actin gene was used as the internal reference, and relative gene expression was analyzed using the 2-ΔΔCT method”. Why was actin used as a reference gene?

Response:

We appreciate the reviewer's insightful question regarding our choice of the pear actin gene as the internal reference for qRT-PCR normalization. Actin is a classic housekeeping gene known for its relatively stable expression across various cell types and under different treatment conditions. This stability makes it a commonly used reference gene in gene expression studies.

In the initial phase of our study, we evaluated the expression stability of several candidate reference genes, including actin and tubulin. Our preliminary experiments demonstrated that the pear actin gene exhibited minimal variation in Ct values across different samples and treatment conditions. This consistency aligns with the criteria for an ideal internal control gene in qRT-PCR analyses.

Therefore, we selected the pear actin gene as the reference gene to ensure accurate and reliable normalization in our gene expression studies.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

The paper entitled "Coordinated Regulation of Iron-Acquisition Genes and Citrate Biosynthesis Drives Seasonal Iron Deficiency Adaptation in
‘Yali’ Pear (Pyrus bretschneideri Rehd.)" presents interesting data, however many points need to be verified. In addition, the discussion needs to be further developed.

All my notes are described in the PDF.

Comments for author File: Comments.pdf

Author Response

The paper entitled "Coordinated Regulation of Iron-Acquisition Genes and Citrate Biosynthesis Drives Seasonal Iron Deficiency Adaptation in
‘Yali’ Pear (Pyrus bretschneideri Rehd.)" presents interesting data, however many points need to be verified. In addition, the discussion needs to be further developed.

All my notes are described in the PDF.

We deeply appreciate your invaluable comments on this manuscript. Your unselfish and impartial comments made us realize the shortcomings of our manuscript, so we decided to make a lot of revisions to the paper, sed on your comments, we have revised the manuscript as follows.

First, we have revised the Conclusions and Discussion sections, and the updated version is as follows:

  1. Discussion and Conclusion

In this study, the active iron content in leaves of moderately and severely chlorotic groups was significantly reduced compared to the normal group, paralleling the decline in chlorophyll levels, which could be attributed to the critical role of iron in chlorophyll biosynthesis [29, 30]. Consistent with the "chlorosis paradox" observed in previous studies [31], total iron content in normal, mildly, and severely chlorotic leaves exhibited irregular fluctuations, indicating that total iron cannot serve as a reliable diagnostic indicator for the iron nutritional status of 'Yali' pear.

The molecular regulatory mechanism of iron uptake in 'Yali' pear exhibits a stage-specific response to chlorosis severity. Under moderate iron deficiency, root FCR activity and PbFRO2 expression are upregulated, consistent with the classical Strategy I mechanism of enhancing Fe3+ reduction and solubilization to counteract iron deficiency [13]. However, severe iron deficiency suppresses FCR activity, likely due to irreversible enzyme denaturation or cellular redox imbalance, further exacerbating iron limitation. Concurrently, the upregulation of PbIRT1 in moderate chlorotic roots mirrors the activation of Fe2+ transporters observed in Arabidopsis [32], indicating evolutionary conservation of iron uptake mechanisms in dicots. The CS2 gene plays a pivotal role in citrate biosynthesis, exerting dual functions in iron activation and transport through citrate metabolism [33]. In this study, leaf citrate content progressively accumulated with increasing chlorosis severity, while root citrate content (excluding July samples) exhibited a similar trend.

Multivariate analyses revealed a biphasic adaptation strategy. PCA demonstrated progressive physiological divergence, with severely chlorotic leaves forming a distinct cluster separate from normal and moderately chlorotic leaves (Figure 7A), indicating threshold-dependent collapse of metabolic and molecular adjustment mechanisms. PLSDA-VIP identified PbFRO2 as a core regulatory factor (VIP > 1.5, Table 4), whose expression strongly correlated with FCR activity (r = 0.73, P < 0.01) and active iron redistribution. Notably, transcript levels of PbFRO2, PbIRT1, and PbCS2 peaked in moderately chlorotic plants but markedly declined under severe stress (Figure 3D). This pattern suggests two potential mechanisms: (1) Plants may maintain a minimal transcriptional threshold of these genes to achieve adaptive iron homeostasis regulation; beyond this threshold, compensatory mechanisms fail, leading to irreversible physiological damage. (2) Transcriptional suppression of PbFRO2, PbIRT1, and PbCS2 could exacerbate iron deficiency chlorosis in pear trees, creating a self-reinforcing vicious cycle.

This study deciphered the molecular regulatory mechanisms underlying iron deficiency chlorosis in 'Yali' pear through integrative analyses. Under moderate iron deficiency, the synergistic upregulation of PbFRO2, PbIRT1, and PbCS2 likely triggered a compensatory cascade, alleviating chlorosis via enhanced Fe3+ reduction, Fe2+ transport, and citrate-mediated long-distance iron translocation. Conversely, severe iron deficiency potentially overwhelmed the regulatory network capacity, inducing gene expression threshold effects, inactivation of FCR, and photosynthetic dysfunction, ultimately disrupting iron homeostasis (these mechanisms require further validation). Organ-specific citrate dynamics revealed divergent adaptive strategies: leaf citrate prioritized iron reactivation to sustain photosynthetic function, while root citrate modulated seasonal iron allocation through concentration fluctuations. These findings establish a "gene-metabolite-phenotype" tripartite framework elucidating the molecular basis of iron stress in alkaline soils, with PbFRO2 serving as a central hub gene driving adaptive responses and offering potential targets for iron biofortification.

This work systematically characterizes the dynamic physiological and molecular adaptations during iron-deficient chlorosis in 'Yali' pear, providing novel insights into iron homeostasis regulation in perennial fruit trees and guiding iron-efficient cultivar breeding and precision fertilization in calcareous soils. However, the etiology of pear chlorosis remains dual-natured: whether it primarily stems from insufficient soil iron availability or compromised plant iron response capacity warrants resolution. To address this, follow-up studies will employ controlled iron supplementation combined with PbFRO2 overexpression and knockout approaches to dissect the causation of chlorosis and delineate the functional network of this pivotal gene.

 

Comment 1 (Line 38): Introduction

Iron is a    

set the pH range at which iron is available in the soil.

Response:

Thank you for your suggestion. We have revised the sentence in the Introduction to include the appropriate pH range (Line 47-52):

In previous reports, the optimal soil pH range for plant iron absorption is typically between 4.0-6.0, which falls within the slightly acidic to weakly acidic range. Within this pH range, iron exists primarily in the soluble ferrous form (Fe2+) that can be directly absorbed and utilized by plant roots. When soil pH exceeds 7.0 (neutral or alkaline), iron tends to form insoluble ferric hydroxide (Fe3+) or iron oxide precipitates, significantly reducing its availability and potentially inducing iron-deficiency chlorosis in plants [4, 5].

 

Comment 2 (Line 47): Introduction

alkaline and calcareous

Keeping in mind this alkaline soil condition, it is important to know the ATPase (HA) activity, to evaluate the plant's response to basic soil.

Comment 11 (Line 178): Results

7.41   7.92 for the moderate group, and 8.0

Interesting! This needs to be explored further, and is in line with the idea of evaluating ATP (HA), since it must be involved in decreasing pH in the rhizosphere.

Response:

Thank you very much for your comment. We believe that your Comment 2 is similar to Comment 11, and we address them together as follows:

We sincerely appreciate your insightful comments regarding the potential role of plasma membrane H⁺-ATPase (PM H⁺-ATPase) in mediating rhizosphere acidification. We fully acknowledge that PM H⁺-ATPase activity serves as a crucial mechanism for plants to regulate rhizospheric pH, thereby enhancing iron acquisition under deficiency conditions. However, as our current study primarily focused on leaf physiological and photochemical responses to iron deficiency, we did not include measurements of PM H⁺-ATPase activity. We concur that integrating rhizosphere pH monitoring with photosynthetic parameter analyses could provide valuable insights into holistic plant stress responses.

In our upcoming hydroponic experiments with pear seedlings—designed to systematically analyze root iron absorption dynamics under varying iron/pH combinations—we recognize the necessity of incorporating PM H⁺-ATPase measurements. This addition will significantly enhance our understanding of root-mediated iron acquisition strategies in calcareous soil environments.

 

Comment 3 (Line 47): Introduction

FRO2, IRT1

It would also be important to highlight the Fer/Fit gene, since its activity is controlled for iron deficiency.

Response:

Thank you for highlighting the crucial role of the FIT gene in regulating iron deficiency responses. We fully acknowledge FIT's pivotal role as a transcription factor in activating downstream iron uptake genes such as FRO2 and IRT1. Since this study primarily focuses on the direct functional modules of iron absorption and transport, we prioritized the detection of FRO2 and IRT1. Specifically, FRO2 is responsible for reducing Fe³⁺ to Fe²⁺, while IRT1 mediates Fe²⁺ uptake. Additionally, we analyzed CS2 to investigate its auxiliary role in internal iron allocation.

The rationale for not conducting an in-depth exploration of FIT is twofold:

  1. Research Focus and Scope:

This study aims to validate the functional roles of genes directly involved in iron absorption and transportation, with a specific emphasis on the iron reduction and transport processes. While FIT serves as an upstream regulator, its primary function lies in modulating the expression of downstream genes like FRO2 and IRT1—the key iron uptake factors central to our investigation.

  1. Experimental Design Feasibility:

Given the limitations of current experimental data and methodologies, we prioritized the analysis of effector genes directly associated with iron absorption. In future studies, we plan to expand our investigation to explore regulatory networks encompassing FIT and other upstream transcription factors, thereby providing a more comprehensive understanding of iron deficiency response mechanisms.

 

Comment 4 (Line 82): Materials and Methods

Group 1 (Normal) with no chlorosis, Group 2 (Moderate chlorosis) with leaf interveinal chlorosis and green midribs (25%-50% chlorosis of the leaves), and Group 3 (Severe chlorosis) with complete loss of green color, resulting in a yellowish-white appearance (over 75% chlorosis of the leaves). Five replicates were set for each group.

What was used to determine the percentage of chlorosis levels? What technique was used?

Response:

We appreciate your comment regarding the determination of chlorosis levels. As our study is not a controlled variable experiment but rather a classification based on different phenotypes of pear trees within the same orchard, we did not perform a precise quantitative analysis of chlorosis levels. Instead, we categorized the trees into three groups based on field observations.

Our classification was primarily based on two aspects:

  1. Visual Observation: As depicted in Figure 1 of the manuscript, the trees in the field exhibited distinct phenotypic differences, allowing for clear visual differentiation into three groups.
  2. SPAD Measurements: At the beginning of the experiment in May, we measured the SPAD values of the leaves to assist in classification. Leaves with dark green coloration were assigned a SPAD value of 1. Moderately chlorotic leaves had SPAD values approximately 50% of normal, and severely chlorotic leaves had SPAD values below 25% of normal. Given that the normal SPAD value for our leaves was 35, severely chlorotic leaves had SPAD values around 20, and those with severe chlorosis had SPAD values below 10.

We have also provided a more detailed explanation of this classification in section 2.1 "Plant Materials and Growth Conditions" of the revised manuscript. If you have any further questions or require additional information, please do not hesitate to contact us.

 

2.1. Plant Materials and Growth Conditions

The field experiment was conducted at the pear orchard of Hebei Agricultural University (38.814 N, 115.422 E). The region has a temperate monsoon climate, with an average temperature of 26°C and relative humidity of 55% during the experimental period. The soil is classified as calcareous cinnamon soil. The experimental material consisted of seven-year-old ‘Yali’ pear trees with varying degrees of chlorosis. The trees were planted at a row spacing of 3 m and tree spacing of 1 m, following conventional fertilizer and water management practices. The experimental trees were categorized into three groups based on the degree of chlorosis: Group 1 (Normal) with no chlorosis, Group 2 (Moderate chlorosis) with leaf interveinal chlorosis and green midribs (25%-50% chlorosis of the leaves), and Group 3 (Severe chlorosis) with complete loss of green color, resulting in a yellowish-white appearance (over 75% chlorosis of the leaves). Five replicates were set for each group. To assist in the classification, SPAD (Soil Plant Analysis Development) values were measured at the beginning of the experiment in May. Leaves exhibiting dark green coloration were assigned a SPAD value of 1. Moderately chlorotic leaves had SPAD values approximately 50% of normal, and severely chlorotic leaves had SPAD values below 25% of normal. Given that the normal SPAD value for leaves was around 35, moderate chlorotic leaves had SPAD values around 20, and those with severe chlorosis had SPAD values below 10.

 

Comment 5 (Line 89): Materials and Methods

2.2. SPAD Measurement Leaf SPAD values were measured using a SPAD-502 PLUS portable chlorophyll meter (Konica Minolta, Osaka, Japan). Six healthy and pest-free leaves from current-year shoots were selected per tree, and SPAD measurements were taken at five points on each leaf. The average SPAD value was used as the representative chlorophyll content.

The quantification of photosynthetic pigments biochemically is more precise than this index, since it considers the green, not the real concentration of pigments, thus being an indirect measurement.

Response:

Thank you very much for your valuable comment. Regarding the limitations of the SPAD meter measurement you mentioned, we would like to clarify that the SPAD meter in this study was primarily used for rapid and non-destructive estimation of relative chlorophyll content. This approach supports the quantitative classification of leaf chlorosis (i.e., normal, moderately chlorotic, and severely chlorotic) rather than for obtaining precise biochemical chlorophyll concentration data. We have further clarified this point in the revised methodology to avoid any misunderstanding by the readers as follows (Line 109-119):

 

2.2. SPAD (Soil and Plant Analyzer Development) Measurement

The SPAD meter provides a rapid and non-destructive estimation of relative chlorophyll content, which is used to visually classify the degree of leaf chlorosis. Therefore, in this study, SPAD values were measured using the SPAD-502 PLUS portable chlorophyll meter (Konica Minolta, Osaka, Japan). Measurements were conducted around 10:00 a.m. on clear days. For each tree, six healthy, pest‑free leaves from current‑year shoots were selected—specifically, the 3rd to 5th fully expanded leaves from the shoot tip—and SPAD measurements were taken at five predetermined positions along each leaf blade. The mean of these five SPAD readings was calculated for each leaf and used as its representative chlorophyll content. The very same leaves used for SPAD determination were employed in all subsequent analyses.

Comment 6 (Line 95): Materials and Methods

The chlorophyll fluorescence parameter Fv/Fm was measured using a Handy-PEA 95 fluorimeter Multifunctional Plant Efficiency Analyzer (Hansatech Instruments Ltd., Pent- 96 ney, Norfolk, UK), according to the device's instructions.   

Please explain in more detail how this analysis was performed.

What light actin was used, and the time of acclimatization in the dark?

Why didn't you present the other variables?

Response:

Thank you for your comment. According to the user manual provided by the instrument manufacturer, the measurement of Fv/Fm does not require the use of actinic light; therefore, we did not employ it in our measurements. However, based on your suggestion, we have revised Section 2.3 to provide a more detailed explanation. The revised content is as follows:

 

2.3. Chlorophyll Fluorescence Measurement

The leaf chlorophyll fluorescence parameter Fv/Fm was measured using a Handy-PEA fluorimeter Multifunctional Plant Efficiency Analyzer (Hansatech Instruments Ltd., Pentney, Norfolk, UK). Following manufacturer recommendations, leaf samples underwent 20-minute dark adaptation at 25°C prior to measurement to ensure complete relaxation of all PSII reaction centers. Measurements were performed on the mid-lamina region, an area less susceptible to edge effects and representative of overall photosynthetic performance. Two technical replicates per leaf and three biological replicates per experimental treatment were recorded to ensure data robustness and statistical reliability.

During the Fv/Fm measurement, a 650 nm red LED was used as a saturating pulse light source, with an intensity of 3000 μmol·m⁻²·s⁻¹ to determine Fm; F0 was measured under weak measuring light (<1 μmol·m⁻²·s⁻¹). No actinic light was used during the Fv/Fm measurements.

 

Comment 7 (Line 113): Materials and Methods

FCR activity was measured according to Zheng et al. [18], with the root samples incubated in a CaSO4 (0.5 mM) solution for 10 minutes. After washing and wiping, they 114 were placed in 5 mL enzyme activity detection solution and incubated in the dark for 1 hour. The absorbance at 535 nm was measured and compared to a standard curve.

Explain better how it was done.

 

Response:

 

Thank you very much for your comments. We have revised this part as follows (Line 173-182):

FCR activity was measured according to Zheng et al. [18], utilizing the same root specimens collected for root vitality assessment. Root segments were incubated in a CaSO4 (0.5 mM) solution for 10 minutes. After washing and wiping, they were placed in 5 mL of enzyme activity detection solution containing 50 mM Tris (pH 7.5), 0.5 mM CaSO4, 0.3 mM BPDS, and 50 mM FeEDTA. The reaction was carried out in the dark at 25°C for 1 hour, with gentle inversion every 10 minutes to mix. After the reaction, 2 mL of the colored supernatant was transferred to a 1 cm quartz cuvette and measured at 535 nm using a UV-2550 UV-Vis spectrophotometer (Shimadzu, Kyoto, Japan). A standard curve was established before measuring the samples. Each sample was repeated 3 times.

Comment 8 (Line 131): Materials and Methods

Chromatographic conditions: Agilent 1260 HPLC system (Agilent Technologies, Santa Clara, CA, USA) with a UV detector, using an Eclipse Plus C18 column (4.6mm × 132 250mm, 5μm), column temperature at 25°C, and a mobile phase of potassium dihydrogen phosphate (0.02 mol/L, pH 2.8). The flow rate was set at 0.5 mL/min, and the injection volume was 10 μL.

Was it an isocratic method? Explain better what other solvents were used in the mobile phase?

 

Response:

Thank you for raising this important clarification. We confirm that the HPLC analysis employed an isocratic elution method with a single mobile phase composed of 0.02 mol/L potassium dihydrogen phosphate (pH 2.8 adjusted with phosphoric acid). No additional organic solvents (e.g., acetonitrile or methanol) were used in the mobile phase. To improve clarity, we have revised the chromatographic conditions section to explicitly state the isocratic nature of the method and the pH adjustment process. Please see the updated text below (Line 196-209):

2.8. Measurement of Citrate in New Roots and Leaves

Citrate content was quantified by high-performance liquid chromatography (HPLC) following the protocol of Lucarini et al. [20]. Briefly, approximately 0.2 g of fresh roots or leaves were homogenized in liquid nitrogen, followed by extraction with ddH₂O to a final volume of 1.5 mL. The mixture was incubated at 75°C for 30 minutes and subsequently centrifuged at 12,000 × g for 30 minutes. After centrifugation, the supernatant was filtered through a 0.22 μm membrane prior to HPLC analysis.

Chromatographic conditions were as follows: An Agilent 1260 HPLC system (Agilent Technologies, Santa Clara, CA, USA) equipped with a UV detector was employed. Separations were achieved using an isocratic method with an Eclipse Plus C18 column (4.6 mm × 250 mm, 5 μm particle size) maintained at 25°C. The mobile phase consisted of 0.02 mol/L potassium dihydrogen phosphate buffer (pH 2.8), which was delivered isocratically at a flow rate of 0.5 mL/min. Finally, a 10 μL aliquot of the processed sample was injected for each analysis.

 

Comment 9 (Line 174): Results

pH

The pH for best availability and solubility of Fe is in the range of 4-6.

Response:

We thank the reviewer for this important note. We have added this information to the Results section (Line 273-275):

In summary, even though the overall soil pH in this study fell outside the optimal range (pH 4-6) for iron availability and solubility, our findings still demonstrated that increased iron-deficiency chlorosis severity correlated with elevated rhizosphere soil pH and reduced available iron content. This suggests these parameters may constitute key drivers of iron deficiency-induced chlorosis in pear trees.

 

Comment 10 (Line 176): Results

How was the pH measurement performed in the rhizosphere? Or is it the pH of the soil?

 

Response:

Thank you for your comment. The pH in this section refers to the pH of the rhizosphere soil. The detection method is as follows (Line 134-140):

2.4. Soil Property Analysis

Soil pH reflects the acidity or alkalinity of the soil solution, which is a key factor in nutrient uptake and root activity. In this study, rhizosphere soil attached to roots during sampling was used for pH analysis [13]. Air-dried soil (passed through a 2-mm nylon-sieved) was weighed (10 g) into a 100 mL Erlenmeyer flask, mixed with 25 mL distilled water, stirred vigorously with a glass rod for 2 min, and allowed to settle for 30 min. pH values were measured using a pH meter (PB-10, Sartorius Scientific Instruments Co., Ltd., Beijing, China), with three replicates per treatment.

 

Comment 12 (Line 219): Results

A: Total iron content in leaves,  

In which leaves was this iron concentration measured, since it is very high, I imagine that old leaves were used, since iron has low mobility in the plant.

Comment 13 (Line 467): Discussion and Conclusion

of young leaves

How young? Since this analysis is done on fully expanded leaves, as a way of ensuring that the photochemical apparatus is fully developed.

The values presented for Fv/Fm in the severe plants for the month of May are very low even for plants in deficiency, and even stranger, they improve over time, which may indicate that the apparatus was not fully developed. Fv/Fm close to 0.2 is already a value of a dead plant.

 

Response:

Thank you for your comment. In our study, the “young leaves” were defined as the youngest fully‑expanded leaves on each shoot—specifically, the 3rd to 5th leaf from the shoot tip—and the total iron content values were determined using our established assay protocol. We have clarified this point in the Methods section to avoid confusion.

(Line 109-119)

2.2. SPAD (Soil and Plant Analyzer Development) Measurement

The SPAD meter provides a rapid and non-destructive estimation of relative chlorophyll content, which is used to visually classify the degree of leaf chlorosis. Therefore, in this study, SPAD values were measured using the SPAD-502 PLUS portable chlorophyll meter (Konica Minolta, Osaka, Japan). Measurements were conducted around 10:00 a.m. on clear days. For each tree, six healthy, pest‑free leaves from current‑year shoots were selected—specifically, the 3rd to 5th fully expanded leaves from the shoot tip—and SPAD measurements were taken at five predetermined positions along each leaf blade. The mean of these five SPAD readings was calculated for each leaf and used as its representative chlorophyll content. The very same leaves used for SPAD determination were employed in all subsequent analyses.

 

In our field observations, the most severely chlorotic leaves in May were nearly white, reflecting extreme chlorosis, whereas by June and July they showed noticeable recovery, consistent with the SPAD readings. As for the very low Fv/Fm values we recorded, we attribute these to limited iron mobility within the plant: although these leaves exhibited severely impaired PSII efficiency, they were not dead and their Fv/Fm partially rebounded in June and July. We have added a statement in the Results and Discussion to highlight the poor translocation of iron within the plant. The specific revisions are as follows:

(Line 120-132)

 3.3. Correlation between Different Chlorosis Levels and Relative Chlorophyll Content and Chlorophyll Fluorescence Parameters

SPAD values, which serve as a relative indicator of chlorophyll content, were used to assess leaf chlorosis [24]. The results (see Fig. 3) indicated that SPAD values decreased significantly with the aggravation of chlorosis. The SPAD values of the normal group were 1.87 and 10.26 times, 1.70 and 8.88 times, and 1.57 and 3.59 times those of the moderate and severe chlorosis groups in each respective month. The maximum photochemical efficiency (Fv/Fm), reflecting the light energy conversion efficiency of PSII reaction centers, showed minor variations under normal conditions but decreased significantly under iron stress [25]. Results demonstrated that Fv/Fm values remained relatively stable in the normal group, with no significant differences observed between moderately chlorotic and normal leaves across months. However, Fv/Fm values in severely chlorotic leaves were significantly lower than those in both normal and moderately chlorotic groups. The Fv/Fm values of severely chlorotic leaves dropped to 0.16 in May and remained around 0.6 from June to July. These findings indicate that both moderate and severe iron deficiency chlorosis can reduce relative chlorophyll content, but only severe chlorosis significantly inhibits photosynthesis. The concurrent decline in SPAD values and Fv/Fm ratio under severe iron deficiency may be attributed to impaired iron mobility within plants, particularly given that our sampling focused on the 3rd to 5th newly emerged leaves at shoot apices—positions subject to lower iron allocation priority [26]. In contrast, the observed recovery of Fv/Fm values in June and July likely correlates with dynamic accumulation of active iron content in leaves during developmental progression (Fig. 2B).

 

 

 

Comment 15 (Line 241): Discussion and Conclusion

with the classical Strategy I mechanism of enhancing Fe3+ reduction and solubilization to counteract iron deficiency [31].

include this in the introduction.

 

Response:

Thank you for the recommendation. We have added a description into the Introduction for better conceptual context.

Revised third paragraph of the Introduction (Line 71-72):

  1. Introduction

These genes collectively function through the classical Strategy I mechanism of enhancing Fe³⁺ reduction and solubilization to counteract iron deficiency [13].

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

The authors addressed my concerns and suggestions; I believe the manuscript is now ready for publications.

Reviewer 3 Report

Comments and Suggestions for Authors

The work entitled "Coordinated Regulation of Iron-Acquisition Genes and Citrate Biosynthesis Drives Seasonal Iron Deficiency Adaptation in ‘Yali’ Pear (Pyrus bretschneideri Rehd.)" has undergone significant improvements, so that it is ready to be published in its current form.

Back to TopTop