Transcriptome-Wide Survey of LBD Transcription Factors in Actinidia valvata Under Waterlogging Stress and Functional Analysis of Two AvLBD41 Members

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The paper is complete and well written. The molecular and bioinformatic analysis were complete and well connected, but the title must be change and the focus must be moved from waterlogging to salinity response.

 

In M&M there are any waterlogging tests, any submersion, only hydroponic cultivation and salinity increasing in nutrient solutions.  A correct waterlogging test was reported in ref. 33 and 37. I suggest to change in the title the word waterlogging with salinity. Also in the text, in the description and in the other consideration, remove replace "waterlogging" with the salinity aspects.

Also the use of NaOH for pH increasing is not correct because there are inside the Na toxicity and salinity. To simulate the alkaline stress the authors must use the elements that cause the high pH in the cultivated soil, typically Calcium.

I strongly suggest to re-elaborate the text about salinity stress and Sodium toxicity, not waterlogging and not alkalinity.

Of course the author can make references to waterlogging stress and tolerance basing on the bibliography and other experiments of waterlogging, but it is a speculation or an indirect evidence.

Comments for author File: Comments.pdf

Author Response

Comments 1: In M&M there are any waterlogging tests, any submersion, only hydroponic cultivation and salinity increasing in nutrient solutions.  A correct waterlogging test was reported in ref. 33 and 37. I suggest to change in the title the word waterlogging with salinity. Also in the text, in the description and in the other consideration, remove replace "waterlogging" with the salinity aspects.

Response 1: Thank you for pointing this out. We agree with this comment. Therefore, to avoid any ambiguity, we have revised the experimental design and removed all salt- and alkali-stress treatments; the manuscript now focuses exclusively on waterlogging stress. The  transcriptome dataset used in this study was generated from Actinidia valvata under waterlogging stress.

Comments 2: Also the use of NaOH for pH increasing is not correct because there are inside the Na toxicity and salinity. To simulate the alkaline stress the authors must use the elements that cause the high pH in the cultivated soil, typically Calcium.

Response 2: We sincerely appreciate your insightful comments on the alkali-stress experimental design. In the new MS, we have removed all alkali-related treatments from the present study and will refine the methodology for future work.

Comments 3: I strongly suggest to re-elaborate the text about salinity stress and Sodium toxicity, not waterlogging and not alkalinity.

Response 3: We sincerely appreciate your insightful comments. To avoid any ambiguity, all salt-stress data have also been removed from the revised manuscript.

Comments 4: Of course the author can make references to waterlogging stress and tolerance basing on the bibliography and other experiments of waterlogging, but it is a speculation or an indirect evidence.

Response 4: Thank you for this helpful suggestion. We have now expanded the Methods section with a full description of the waterlogging protocol (water depth, duration, controls, replication, lines ) and have added references that document the superior flood tolerance of A. valvata compared with commercial cultivars (Lines 58-65).

Lines 173-177: In a previous experiment, asexually propagated KR5 plants at five- to six-leaf stage were subjected to waterlogging for 0, 12, 24 or 72 h. The 0-h treatment served as the non-waterlogged control. Two potted plants were immersed in each plastic tray (45 cm × 35 cm × 16 cm) and the water level was kept 2-3 cm above the soil surface. Every time point comprised four pots, and the experiment was replicated three times.

Lines 58-65: By contrast, A. valvata develops a robust, woody, highly aerated root system and survives prolonged waterlogging far better than A. deliciosa. Previous studies demonstrated that A. valvata maintains carbohydrate reserves, and restricts oxidative damage in roots during prolonged waterlogging stress. One adaptive morphology trait is the rapid development of adventitious roots, structures that enable internal oxygen diffusion under hypoxic conditions. The superior waterlogging tolerance is maintained when A. valvata is used as a rootstock for commercial scions.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

This is a well-structured and comprehensive study on the LBD transcription factor family in Actinidia valvata, a kiwifruit rootstock prized for its waterlogging tolerance. The research is methodologically sound, effectively integrating multiple techniques from bioinformatics and molecular biology, including transcriptome-wide analysis, gene expression profiling, and protein-protein interaction assays. The primary merit of the paper is its novel findings regarding the molecular regulation of stress response. The identification of a specific transcriptional module where LBD41_7 interacts with both the activator ERF75 and the repressor HRA1 is a significant contribution. Furthermore, the research has clear agricultural relevance (an edible fruit and stress response). By identifying some of the key regulators of waterlogging tolerance, it provides valuable molecular targets for breeding more resilient kiwifruit varieties.

However, the study's main demerit is the absence of in vivo functional validation. While the molecular interactions are convincingly demonstrated, the ultimate proof of function, such as using stable transgenic plants to show that altering LBD41 expression changes waterlogging tolerance, is missing. Having said that, I do understand that asking this would be beyond the scope of this research work.

A minor limitation is that identifying genes from a transcriptome dataset, not a full genome, may well have resulted in an incomplete characterization of the LBD family. Please add this comment in the article, so that the readers are aware that this may not be the full list of LBDs in Kiwifruit. Overall, it is a strong piece of molecular research that lays excellent groundwork for future functional studies.

And thanks for uploading the raw data (image) files. Much appreciated!

Author Response

Comments 1: This is a well-structured and comprehensive study on the LBD transcription factor family in Actinidia valvata, a kiwifruit rootstock prized for its waterlogging tolerance. The research is methodologically sound, effectively integrating multiple techniques from bioinformatics and molecular biology, including transcriptome-wide analysis, gene expression profiling, and protein-protein interaction assays. The primary merit of the paper is its novel findings regarding the molecular regulation of stress response. The identification of a specific transcriptional module where LBD41_7 interacts with both the activator ERF75 and the repressor HRA1 is a significant contribution. Furthermore, the research has clear agricultural relevance (an edible fruit and stress response). By identifying some of the key regulators of waterlogging tolerance, it provides valuable molecular targets for breeding more resilient kiwifruit varieties.

However, the study's main demerit is the absence of in vivo functional validation. While the molecular interactions are convincingly demonstrated, the ultimate proof of function, such as using stable transgenic plants to show that altering LBD41 expression changes waterlogging tolerance, is missing. Having said that, I do understand that asking this would be beyond the scope of this research work.

Response 1: We sincerely thank you for the positive appraisal of our work and for acknowledging the value and novelty of our findings. Thank you for pointing the study's main demerit. We agree with this comment. Therefore, to strengthen the applied relevance of our study, we have added new functional experiments demonstrating the utility of the AvLBD41_7 promoter and its derived PCR marker. These data (new Fig. 11 & 12) show that the promoter fragment can be potentially used to screening the waterlogging tolerant kiwifruit accessions, while the PCR marker accurately distinguishes A. valvata from A. deliciosa accessions. Together, these tools provide breeders with a rapid, low-cost means to pre-select waterlogging-resilient genotypes, substantially accelerating the development of waterlogging-tolerant kiwifruit cultivars.  We fully agree that in vivo validation is essential to consolidate our conclusions. We have now initiated over-expression lines for AvLBD41_7, and the first transgenic plantlets are currently being acclimatised. Detailed phenotyping under controlled waterlogging conditions will be performed in the next growing season, and the results will be included in a follow-up manuscript. This functional characterization will close the current gap and provide definitive evidence of AvLBD41_7’s role in waterlogging tolerance. Comments 2: A minor limitation is that identifying genes from a transcriptome dataset, not a full genome, may well have resulted in an incomplete characterization of the LBD family. Please add this comment in the article, so that the readers are aware that this may not be the full list of LBDs in Kiwifruit. Overall, it is a strong piece of molecular research that lays excellent groundwork for future functional studies. Response 2: We fully agree with this insightful comment. As suggested, we have now explicitly acknowledged the limitations of our study in the revised Methods section (lines 128–130). We have also outlined how these shortcomings will be addressed in the discussion part (lines 491-492). Lines 128-130: A chromosome-scale genome assembly with systematic annotation of A. valvata remains unavailable, consequently, full-length transcriptome sequencing can partially characterize the LBD gene family. Lines491-492: A plausible explanation is that the LBD family is still incompletely annotated in A. valvata at the transcript level.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

Dear Editor,

I am pleased to have reviewed the manuscript “Transcriptome-Wide Survey of LBD Transcription Factors in Actinidia valvata under Waterlogging Stress and Functional Analysis of Two AvLBD41 Members” provided by Zhi Li, Ling Gan, Xinghui Wang, Wenjing Si, Haozhao Fang, Jinbao Fang, Yunpeng Zhong, Yameng Yang, Fenglian Ma, Xiaona Ji, Qiang Zhang, Leilei Li, and Tao Zhu. I have some comments that may help the authors address certain gaps in the manuscript.

 

Abstract

This section contains important information; it would be advisable for the authors to include at the end of the abstract what the practical usefulness of the study would be, beyond merely mentioning an interpretation.

Introduction

The introduction provides good context regarding the involvement of different Transcription Factors; however, it is advisable to correct the writing to allow rapid interpretation of the ideas. For example, between lines 50 and 67 the effects and functions of various TFs are listed, but the text reads more like a descriptive list than an interpretative synthesis that articulates their biological relevance. A specific example is LBD37, whose mention lacks a clear context within the paragraph's flow. In this sense, the functions described for different LBDs (LBD9, LBD25, LBD37, etc.) appear as isolated cases, without explaining whether they are conserved or specific functions. LBD37 is mentioned in two different contexts (metabolism and stress) without clarification of relevance or connection between the two mentions.

It must be justified why the LBD family would be a candidate to modulate waterlogging tolerance in Actinidia. The relationship between LBD and crosstalk with ERFs or bHLHs is mentioned, but its importance for the specific phenomenon of waterlogging is not substantiated.

The paragraphs are too independent; there is no logical connection between them. In addition, LBD37/LBD41 are mentioned several times in different contexts (nitrogen, anthocyanins, hypoxia) without clarifying whether we are discussing conserved or species-specific functions. It is advisable to explicitly indicate what is unknown about LBDs in A. valvata and why this is important (for example, functional studies are scarce; paralogy of AvLBD41 is uncharacterized).

It would be important to include information on agronomic losses due to waterlogging to establish a framework of urgency worth studying. In this regard, it would be important to relate adaptive traits; that is, to explain mechanistically why LBDs could modulate waterlogging tolerance. Currently, the manuscript provides basic agronomic information that justifies the economic importance of the kiwifruit crop, but does not mention data on the real impact of waterlogging or associated losses that contextualize the problem. Likewise, Actinidia valvata is described as tolerant, but it is not explained why it is agronomically used as a rootstock, nor its importance within the production system.

It would be interesting to have an explanation of why the paralogs (AvLBD41_11 and AvLBD41_7) were chosen; were they the most induced in previous studies? Do they show recent duplication? etc., and to suggest what functional validations are missing. The characterization of two paralogs seems arbitrary, since their relevance compared to other identified LBDs is not explained. The degree of evolutionary conservation of the LBD family is mentioned, but it is not analyzed whether this allows for inferring functions in Actinidia.

Something important is that the introduction does not identify the exact knowledge gap, so it is not clear what remains to be discovered. There is an extensive description of TFs involved in Actinidia valvata, but it is not clear what among all this has already been resolved and what remains uncharacterized.

It is important that the introduction better cohesively connects the information, highlighting the need to study a specific crop, relating it to the urgency of the study, as well as current, well-characterized evidence on how this problem can be addressed, and the impact it may have on agriculture.

 

Materials and Methods

This section is partially complete; under the current conditions, although it provides important information, it does not allow replication of the experiment. Below, I mention some gaps that must be filled:

Section 3.1

Mention what the criteria/threshold were for considering a “putative LBD” (E-value, Pfam score, domain coverage). Parameters used in ScanProsite (default or customized). The authors must provide the exact process to “remove duplicates and incomplete sequences”: definition of duplicate (99% identity?), criteria for incomplete (fragment < % of the domain?), version and parameters used in NCBI CD-Search; criteria for acceptance/rejection of the domain, version of TBtools and commands/settings for visualization. Versions of ExPASy-ProtParam (or web confirmation) and whether default values were used; version of Cell-PLoc 2.0 and parameters; whether multiple prediction (plant/cell-type) was used.

2.2

In this section, the version of LBDs from Arabidopsis and rice is missing, as well as the ClustalW parameters (gap open/extend, substitution matrix). The use of MEGA 11 is appropriate, but indicate the substitution model used for ML (e.g., JTT, WAG), any corrections (gamma, invariant), and whether partitioning was used. Regarding the bootstrap, what seed or algorithm was used? And whether the tree was rooted, and with which outgroup.

2.3

The authors may provide information on the exact parameters in DNAMAN 9.0 (algorithm/score, etc.). In MEME, what was the model (zoops/oops/anr) and the E-value? How were motifs filtered/visualized?

2.4

This section in particular requires more information. Although it provides information that the RNA-seq was obtained from a previous study, it is important to mention the details of the waterlogging experiment and the number of replicates, in order to prevent readers from having to search for previous studies that may not be available at the moment. Also, the RNA-seq processing pipeline: tools and versions (FastQC, Trimmomatic/fastp), mapper (HISAT2/STAR) with parameters, reference index (genome or transcriptome used).

If qRT-PCR validates the same samples, what was the extraction protocol and which samples corresponded to each time point? Indicate the number of technical replicates in qRT-PCR.

Subsequent sections

The methodology, although it provides relevant information, is insufficiently described to allow replication of the experiment; important information is often omitted, and this must be addressed. Software versions, parameters, and homology mapping methods are missing. In section 2.6 the construction of the plasmid is mentioned, but they do not indicate what region or sites the CDS was inserted into, nor under which regulatory regions it is located, the length of the CDS, whether it was transformed into yeast, and if so, which strain? Under what culture conditions? In what medium? Temperatures? etc.

These are some examples of what is observed in the manuscript. This section in particular is written in such a way that, under the current conditions, it does not allow replication of the experiments.

 

Results and Discussion

These sections are generally well-written and coherent. However, the Discussion in particular presents weaknesses in depth, functional interpretation, critical comparison between species, and connection with biological hypotheses. Under the current conditions, the manuscript explains what was observed in the study, but does not discuss why it happens or what it means. For example:

No biological reasons are presented for why LBDs are relevant in waterlogging; it is lacking an explanation of what was previously known about the role of LBD41 in hypoxia and what GAPS were being filled. There is no conceptual model that links LBD–hypoxia–molecular response.

In the manuscript, it is mentioned that there are fewer genes than in Arabidopsis and that Class Ie is missing, but it does not explain what functional or evolutionary implications this has. The lack of a genome is mentioned, but there is no discussion of how this affects interpretation.

It is not discussed whether induction levels are strong, moderate, or weak compared to known hypoxia genes (ADH1, PDC1, SUS1, etc.). It is also not discussed whether the response is early, transient, or sustained, nor what this means biologically. It would be advisable to include why there is no HRPE even though they are induced (this is important and unusual).

There is a lack of biochemical discussion about what it implies that it interacts with ERF75 but not with ERF73, differences in AP2 domains? motifs? The same goes for ERF, WRKY, Trihelix, could they form a multi-protein complex network?

Regarding localization, the discussion is superficial. Nuclear localization is not surprising; this paragraph contributes little. It is missing consideration of whether localization changes in response to stress, as occurs with some TFs.

Finally, the discussion does not land on a conceptual message nor is an integrative model presented, nor limitations or future experiments, which is important.

The document is very interesting and provides relevant information; however, it still needs improvement regarding the context of why the research was necessary, why a specific crop is used, and especially the methodological conditions require greater care, as the information required for replication of the experiments is not being provided.

 

Comments for author File: Comments.pdf

Author Response

Comments 1: Abstract This section contains important information; it would be advisable for the authors to include at the end of the abstract what the practical usefulness of the study would be, beyond merely mentioning an interpretation.

Response 1: Thank you for pointing this out. We agree with this comment. Therefore, in the new MS (lines 34-37), we have included the practical usefulness of the study at the end of the abstract. Lines 34-37: Collectively, these findings provide a comprehensive functional annotation of the LBD gene family in A. valvata and establish AvLBD41_7 as a potential molecular target for future kiwifruit breeding programs aimed at waterlogging resilience.

Comments 2: The introduction provides good context regarding the involvement of different Transcription Factors; however, it is advisable to correct the writing to allow rapid interpretation of the ideas. For example, between lines 50 and 67 the effects and functions of various TFs are listed, but the text reads more like a descriptive list than an interpretative synthesis that articulates their biological relevance. A specific example is LBD37, whose mention lacks a clear context within the paragraph's flow. In this sense, the functions described for different LBDs (LBD9, LBD25, LBD37, etc.) appear as isolated cases, without explaining whether they are conserved or specific functions. LBD37 is mentioned in two different contexts (metabolism and stress) without clarification of relevance or connection between the two mentions.

Response 2: Thank you for this helpful comment. We have rewritten the Introductions. In the new MS, only ERF and LBD links to waterlogging stress were mentioned. The effects and functions of various TFs were not described. LBD37 is only mentioned in the stress context. As advised, the writing fouses on the biological relevance of senstences.   Comments 3: It must be justified why the LBD family would be a candidate to modulate waterlogging tolerance in Actinidia. The relationship between LBD and crosstalk with ERFs or bHLHs is mentioned, but its importance for the specific phenomenon of waterlogging is not substantiated. Response 3: Thank you for this helpful suggestion. In the revised manuscript, we now emphasize that LBD41 is conservedly up-regulated by waterlogging in both Arabidopsis and kiwifruit (A. valvata and A. polygama, lines 75-77; 97-99; 106-108), where AtLBD41 activates the hypoxia-responsive gene AtHB1 (lines 99-100). We further highlight the LBD family’s established role in shaping root architecture and document their direct physical interaction with core ERF-VII regulators, thereby positioning LBD proteins at the center of the low-oxygen response network in kiwifruit (lines 96-98). Lines 75-77: Strikingly, several AvLBD41 unigenes are co-induced, physically interact with AvERF75, and thus represent their immediate involvements of the ERF-VII pathway. Lines 96-98: Collectively, these data underscore the pivotal roles of the LBD family in regulating root system architecture. Lines 97-99: In Arabidopsis, transcript levels of LBD4, LBD37, LBD39, LBD40 and LBD41 were significantly altered under hypoxic stress. Lines 106-108: Likewise, AcLBD was strongly up-regulated in leaves of the waterlogging-tolerant A. polygama genotype ‘Zhemizhen 1’, upon waterlogging stress. Lines 99-100: Among them, AtLBD41 regulates the expression of AtHB1, a non-symbiotic hemoglobin gene, under hypoxia.

Comments 4: The paragraphs are too independent; there is no logical connection between them. In addition, LBD37/LBD41 are mentioned several times in different contexts (nitrogen, anthocyanins, hypoxia) without clarifying whether we are discussing conserved or species-specific functions. It is advisable to explicitly indicate what is unknown about LBDs in A. valvata and why this is important (for example, functional studies are scarce; paralogy of AvLBD41 is uncharacterized). Response 4: Thank you for pointing this out. We have rewritten the paragraphs, emphasizing more about their logical connections in the new MS. To avoid any ambiguity, LBD37/LBD41 was mentioned only in the waterlogging stress context. As advised, we explicitly indicate what is known about the functions of LBD41 in Arabidopsis (lines 101-105). In concise, over-expressing AtLBD41 alters floral morphology and root nitrogen metabolism, yet if it affects hypoxia survival remains unknown. Whereas, the lbd41 T-DNA insertional mutant (SALK_078678C) exhibits WT-level responses to low oxygen. For LBDs in A. valvata, we have supplemmented that the roles of LBD proteins during waterlogging stress remains largely uncharacterised (lines 89-90). In the new MS, we introduced more about that LBD41 is a conserved, waterlogging-responsive node that integrates hypoxia signals with root architectural changes (lines 112-114), making it a prime candidate for functional dissection in A. valvata. Lines 89-90: In kiwifruit, however, the LBD family remains not systematically characterized. Lines 101-105: Nevertheless, the homozygous T-DNA insertional mutants of AtLBD41 (SALK_078678C) display no visible phenotype relative to Col-0 in low-oxygen assays. Although constitutive over-expression of AtLBD41 alters floral architecture and root nitrogen metabolism, its influence on waterlogging tolerance remains essentially unexplored. Lines 112-114: Because LBD genes control adventitious rooting and low-oxygen signalling across taxa, we hypothesised that AvLBD members are key players in the waterlogging tolerance of A. valvata.

Comments 5: It would be important to include information on agronomic losses due to waterlogging to establish a framework of urgency worth studying. In this regard, it would be important to relate adaptive traits; that is, to explain mechanistically why LBDs could modulate waterlogging tolerance. Currently, the manuscript provides basic agronomic information that justifies the economic importance of the kiwifruit crop, but does not mention data on the real impact of waterlogging or associated losses that contextualize the problem. Likewise, Actinidia valvata is described as tolerant, but it is not explained why it is agronomically used as a rootstock, nor its importance within the production system.

Response 5: Thank you for this helpful suggestion. In the revised Introduction, we now emphasize that waterlogging has become increasingly frequent, why waterlogging causes agronomic losses, and mention the data on the real impact of waterlogging in kiwifruit production (lines 44-49). These informations underscore the urgent need to dissect the molecular basis of waterlogging tolerance in kiwifruit, providing the rationale for the present study. Lines 44-49: Climate change, however, has increased the frequency of extreme rainfall events that leave soils waterlogged and oxygen-deficient for days or even weeks. Roughly 16 % of the world’s cropland is afflicted by waterlogging, cutting yields by about one-fifth. Waterlogging stress suppresses root function, reduces fruit quality and yield, and causes huge economic losses of kiwifruit production.   In the revised manuscript, we now provide a detailed rationale for employing A. valvata as rootstock, highlighting its superior waterlogging tolerance relative to A. deliciosa and the enhanced agronomic performance (vigour, yield and fruit quality) of scions grafted upon it, explaining why it is increasingly favoured in flood-prone kiwifruit orchards (lines 58-60; 64-66). Lines 58-60: By contrast, A. valvata develops a robust, woody, highly aerated root system and survives prolonged waterlogging far better than A. deliciosa. Lines 64-66: The superior waterlogging tolerance is maintained when A. valvata is used as a rootstock for commercial scions. A. valvata rootstock also can boost scion vigor, fruit size and quality, highlighting its potential to raise yields. By linking the waterlogging-adaptive outgrowth of adventitious roots in A. valvata with the known role of LBD proteins in orchestrating root architecture, we hypothesise that LBD genes are key regulators of kiwifruit waterlogging tolerance (lines: 62-63; 92-97). Lines 62-63: One adaptive morphology trait is the rapid development of adventitious roots, structures that enable internal oxygen diffusion under hypoxic conditions.

Lines 92-97: In Arabidopsis, AtLBD16 and AtLBD18 interact with auxin response factors to drive lateral root emergence. In peach, LBD genes (PpBSBRLs) function as positive regulators of lateral and adventitious root initiation. In rice, LBD12-1 protein is essential for adventitious root formation and was regulated by auxin signaling under submergence stress in coleoptiles. Collectively, these data underscore the pivotal roles of the LBD family in regulating root system architecture.

 

Comments 6: It would be interesting to have an explanation of why the paralogs (AvLBD41_11 and AvLBD41_7) were chosen; were they the most induced in previous studies? Do they show recent duplication? etc., and to suggest what functional validations are missing. The characterization of two paralogs seems arbitrary, since their relevance compared to other identified LBDs is not explained. The degree of evolutionary conservation of the LBD family is mentioned, but it is not analyzed whether this allows for inferring functions in Actinidia.

Response 6: Thank you for this helpful question. We prioritised AvLBD41_7 (corresponding to Acc04000) and AvLBD41_11 (corresponding to Acc02240, because they showed the strongest expression after 12 h of waterlogging in roots (lines 116-118; 360-362). Our current data do not indicate whether AvLBD41_7 and AvLBD41_11 arose from a recent duplication. After the genome of hexaploid A. valvata is published, collinearity and Ks analyses will reveal any recent segmental or tandem duplication event between this two unigenes. In the Disscussion, we now state that functional validations of AvLBD_41-7 via stable genetic transformation is underway and will be reported in a follow-up study.

Lines 116-118: Two unigenes, AvLBD41_11 and AvLBD41_7, exhibited the strongest up-regulation after 12 h of waterlogging, and were subjected to detailed functional dissection.

Lines 360-362: Among the AvLBD41 paralogues corresponding to Acc04000 and Acc02240, AvLBD41_11 and AvLBD41_7 exhibited the strongest up-regulation after 12 h of waterlogging, respectively.

Comments 7: Something important is that the introduction does not identify the exact knowledge gap, so it is not clear what remains to be discovered. There is an extensive description of TFs involved in Actinidia valvata, but it is not clear what among all this has already been resolved and what remains uncharacterized.

Response 7: Thank you for this insightful comment. We have now rewritten the Introduction to explicitly state the knowledge gap. Although transcriptome surveys have identified waterlogging-induced LBD transcripts in A. valvata, their paralogy, promoter architecture, protein-protein interactions, and practical usefulness remain uncharacterised. This gap is highlighted on this revised MS (lines 77-80; 89-90; 110-111).

Lines 77-80: Yet, the roles of LBD proteins during waterlogging stress remains largely uncharacterised in kiwifruit. Transcriptome-wide identification and functional screening of key LBD genes are helpful for elucidating the waterlogging-adaptaive signalling in kiwifruit.

Lines: 89-90: In kiwifruit, however, the LBD family remains not systematically characterized.

Lines 110-111: Despite these findings, the functional roles and regulatory network of LBDs under waterlogging stress, particularly in kiwifruit, remain limited.

 

Comments 8: It is important that the introduction better cohesively connects the information, highlighting the need to study a specific crop, relating it to the urgency of the study, as well as current, well-characterized evidence on how this problem can be addressed, and the impact it may have on agriculture.

Response 8: Thank you very much for this constructive suggestion. We have completely rewritten the Introduction to create a cohesive narrative.

 

Comments 9: This section is partially complete; under the current conditions, although it provides important information, it does not allow replication of the experiment. Below, I mention some gaps that must be filled:

Section 2.1

Mention what the criteria/threshold were for considering a “putative LBD” (E-value, Pfam score, domain coverage). Parameters used in ScanProsite (default or customized). The authors must provide the exact process to “remove duplicates and incomplete sequences”: definition of duplicate (99% identity?), criteria for incomplete (fragment < % of the domain?), version and parameters used in NCBI CD-Search; criteria for acceptance/rejection of the domain, version of TBtools and commands/settings for visualization. Versions of ExPASy-ProtParam (or web confirmation) and whether default values were used; version of Cell-PLoc 2.0 and parameters; whether multiple prediction (plant/cell-type) was used.

Response 9: Thank you for this detailed comment. As advised, we now have explicitly listed every parameter, software version, and threshold used for LBD identification, duplicate removal, domain validation, physicochemical analysis, and visualization to ensure full reproducibility (lines 132-146).

Lines 132-146: Putative LBD protein sequences were retrieved from annotation results and screened for the presence of the LOB domain (Pfam PF03159) using the ScanProsite online tool (https://prosite.expasy.org/scanprosite/) with default parameters. After removing duplicate (100% identity) and incomplete sequences (lacking a full open reading frame, pfam score < 15.0, or domain coverage < 83.0%), the final candidate sequences were validated with the NCBI Conserved Domain Search (CD Search v3.21, https://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi) with default parameters using an E value cut-off of 10 -2. The CD Search output was then imported into TBtools v2.363, and the conserved LOB domain was visualized using the ‘Visualize Domain Pattern’ command [42]. Fundamental properties of AvLBD proteins, including amino acid length, molecular weight (MW), and theoretical isoelectric point (pI), were calculated using ExPaSy-ProtParam (accessed October 5, 2025, https://web.expasy.org/protparam/) with default parameters. Subcellular localization was predicted with Cell-PLoc 2.0 (http://www.csbio.sjtu.edu.cn/bioinf/Cell-PLoc-2/) using the Plant-mPLoc predictor with default parameters.

 

Comments 10: In this section, the version of LBDs from Arabidopsis and rice is missing, as well as the ClustalW parameters (gap open/extend, substitution matrix). The use of MEGA 11 is appropriate, but indicate the substitution model used for ML (e.g., JTT, WAG), any corrections (gamma, invariant), and whether partitioning was used. Regarding the bootstrap, what seed or algorithm was used? And whether the tree was rooted, and with which outgroup.

Response 10: Thank you for this helpful comment. We have now uploaded the complete set of LBD protein sequences from Arabidopsis and rice in the Table S2, together with a supplement of every search parameter, software version, threshold, and command used for domain identification, duplicate removal, and downstream analyses (lines 149-161).

Lines 149-161: LBD sequences from Arabidopsis and rice were retrieved from the Plant Transcription Factor Database (http://planttfdb.gao-lab.org/index.php), and their ID and protein sequence is provided in Supplementary Table S2. Multiple sequence alignment of all LBD proteins from A. valvata, Arabidopsis, and rice was conducted using ClustalW with default parameters (gap open penalty equal to 10.0, gap extend penalty equal to 0.10, and the Gonnet protein weight matrix). A phylogenetic tree was generated in MEGA 11.0 with the maximum likelihood (ML) method and 1000 bootstrap replicates. The Jones-Taylor-Thornton model was used as the amino acid substitution model, with 5 discrete gamma categories for rate variation among sites, and partial deletion was applied to handle gaps and missing data. The random seed and algorithm used for the bootstrap were set to the default values. The resulting unrooted evolutionary tree was visualized with iTOL (https://itol.embl.de/).

 

Comments 11: The authors may provide information on the exact parameters in DNAMAN 9.0 (algorithm/score, etc.). In MEME, what was the model (zoops/oops/anr) and the E-value? How were motifs filtered/visualized?

Response 11: Thank you for this helpful comment. We have now added the exact parameters in the revised Methods (liines 164-171).

Lines 164-171: Conserved domains of multiple LBD protein sequences were aligned in DNAMAN 9.0 (Lynnon BioSoft) using the ClustalW algorithm (Feng-Doolittle and Thompson) for optimal alignment. Putative motifs were subsequently identified with the MEME online suite (http://meme-suite.org/tools/meme) under the following parameters: minimum width 6, maximum width 50, and a maximum of 10 motifs. The zero or one occurrence per sequence model was used to expect motif sites which are distributed in sequences. The MEME XML output was then imported into TBtools v2.363, and the motifs were visualized using the ‘Visualize Motif Pattern’ command.

Comments 12: This section in particular requires more information. Although it provides information that the RNA-seq was obtained from a previous study, it is important to mention the details of the waterlogging experiment and the number of replicates, in order to prevent readers from having to search for previous studies that may not be available at the moment. Also, the RNA-seq processing pipeline: tools and versions (FastQC, Trimmomatic/fastp), mapper (HISAT2/STAR) with parameters, reference index (genome or transcriptome used).

Response 12: Thank you for this helpful comment. We have now explicitly states the exact plant material, biological replicates, RNA extraction and library preparation kits with catalogue numbers, and the NCBI BioProject accession number (PRJNA792211) together with the original publication citation (lines 173-191).

Lines 173-191: In a previous experiment, asexually propagated KR5 plants at five- to six-leaf stage were subjected to waterlogging for 0, 12, 24 or 72 h. The 0-h treatment served as the non-waterlogged control. Two potted plants were immersed in each plastic tray (45 cm × 35 cm × 16 cm) and the water level was kept 2-3 cm above the soil surface. Every time point comprised four pots, and the experiment was replicated three times. Total RNA was isolated from root samples with the RNeasy Mini Kit (Qiagen, Germantown, MD, USA) and quantified for downstream library construction. Strand-specific libraries were prepared with the NEBNext® Ultra™ RNA Library Prep Kit (San Diego, CA, USA) following the manufacturer’s instructions. Paired-end sequencing (2 × 150 bp) was performed on an Illumina HiSeq 2000. Raw reads were quality-assessed with FastQC v0.11.9 and technical sequences were trimmed using Cutadapt (version 1.9.1, TU Dortmund University, TU Dortmund, Germany). RNA-seq raw reads have been deposited in the NCBI Sequence Read Archive under BioProject PRJNA792211 [41]. Clean reads were then aligned to the reference full-length transcriptome (accession number PRJNA796628) with HISAT2 v2.0.4, and transcript abundances were quantified with RSEM v1.2.12 [41]. The differential expression analysis was performed using the DESeq2 v1.4.5 at Q value ≤ 0.05. A heatmap of AvLBD expression was generated in TBtools v2.363 using log2-transformed Fragments Per Kilobase per Million mapped fragments (FPKM ) values.

 

Comments 13: If qRT-PCR validates the same samples, what was the extraction protocol and which samples corresponded to each time point? Indicate the number of technical replicates in qRT-PCR.

Response 13: Thank you for this helpful comment. These details of qRT-PCR have been summarized in the revised Methods as advised (lines 240-254).

Lines 240-254: To validate the RNA-seq differential-expression results, we quantified six representative LBD genes by qRT-PCR using the same root samples collected at 0, 12, 24 and 72 h of waterlogging (RNA-seq BioProject PRJNA792211). First-strand cDNA was synthesized with the High-Capacity cDNA Reverse Transcription Kit (TOYOBO, Osaka, Japan). Actin primers were taken from a previous study [48]. Reactions were run with 2 x SYBR Green qPCR Premix Kit (KERMEY, Zhengzhou, China) and followed the procedure: initial denaturation at 95 °C for 30 s, followed by 40 cycles of 95 °C for 10 s and 60 °C for 30 s. For tissue-specific expression of AvLBD41_11 and AvLBD41_7, total RNA was isolated from leaf, petiole, stem and stem-end tissues with the RNAprep Pure Plant Plus Kit (TIANGEN, Beijing, China) and subjected to the same qRT-PCR protocol. The relative expression levels of the tested genes were calculated via the 2-ΔΔCt method. Primer sequences are provided in Supplemental Table S3. qRT-PCR was performed with three biological replicates and three technical replicates per sample, and each replicate comprised pooled material from eight plants. Expression differences across the four time points were evaluated by one-way ANOVA test (P < 0.05) using SPSS v19.0.

 

Comments 14: The methodology, although it provides relevant information, is insufficiently described to allow replication of the experiment; important information is often omitted, and this must be addressed. Software versions, parameters, and homology mapping methods are missing. In section 2.6 the construction of the plasmid is mentioned, but they do not indicate what region or sites the CDS was inserted into, nor under which regulatory regions it is located, the length of the CDS, whether it was transformed into yeast, and if so, which strain? Under what culture conditions? In what medium? Temperatures? etc.

These are some examples of what is observed in the manuscript. This section in particular is written in such a way that, under the current conditions, it does not allow replication of the experiments.

Response 14: Thank you for this critical point. We have now added complete experimental details (kits, volumes, incubation times, software versions, thresholds, replicate numbers, and accession codes) throughout the Methods section and supplied step-by-step protocols to ensure full reproducibility.

In section 2.6, we have now added the missing details: the 897 bp CDS was cloned into pGBKT7 (EcoRI/BamHI), placed under the T7 promoter, and transformed into yeast strain AH109 grown on SD/–Trp at 30 °C (lines 200-205).

Lines 200-205: The coding sequence of AvLBD41_7 (819 bp) was inserted into the pGBKT7 vector at the EcoRI/BamHI sites under control of the T7 promoter, and the resulting recombinant plasmid was employed to assess transcriptional activation. The BD empty vector and the BD-AvERF73 fusion plasmid served as negative and positive controls, respectively [45]. All plasmids were transformed into the yeast strain AH109 and cultured on SD/-Trp and SD/-Trp/-His/-Ade media for 3 days at 30 °C.

 

Comments 15: These sections are generally well-written and coherent. However, the Discussion in particular presents weaknesses in depth, functional interpretation, critical comparison between species, and connection with biological hypotheses. Under the current conditions, the manuscript explains what was observed in the study, but does not discuss why it happens or what it means. For example:

No biological reasons are presented for why LBDs are relevant in waterlogging; it is lacking an explanation of what was previously known about the role of LBD41 in hypoxia and what GAPS were being filled. There is no conceptual model that links LBD–hypoxia–molecular response.

Response 15: Thank you for this critical and constructive feedback. We have revised the Discussion to provide mechanistic depth and a clear biological interpretation.

In Arabidopsis, we now highlight that LBD41 is co-induced with ERF-VII factors under hypoxia and is directly activated through binding to the HRPE cis-element, establishing a conserved regulatory module for low-oxygen signaling (lines 499-501). For A. valvata, we mentioned the absence of functional LBD studies (lines 507-510), and we then demonstrate that AvLBD41_7 assembles into a tripartite AvERF75–AvLBD41_7–AvHRA1 module, proposing a regulatory module that fine-tunes waterlogging tolerance (lines 529-531).

Lines 499-501: In Arabidopsis, LBD41 functions as a core hypoxia-responsive gene together with PCO1/2, ADH1, PDC1, and ERF-VII factors, with RAP2.2/2.12 directly activating it via the HRPE cis-element.

Lines 507-510: Previous studies showed that multiple AvLBD41 unigenes were sharply up-regulated under waterlogging [18], pointing to their possible roles in A. valvata. However, the regulatory network of LBDs under waterlogging stress in kiwifruit remains limited.

Lines 524-525: Collectively, these findings suggest that only specific AvLBD41-AvERFVII heterodimers contribute to the regulation of waterlogging adaptation in kiwifruit.

Lines 529-531: In this study, AvLBD41_7 was shown to interact with both the trihelix factor AvHRA1 and AvERF75 (Figures 6, 7), revealing a three-TF regulatory module.

 

Comments 16: In the manuscript, it is mentioned that there are fewer genes than in Arabidopsis and that Class Ie is missing, but it does not explain what functional or evolutionary implications this has. The lack of a genome is mentioned, but there is no discussion of how this affects interpretation.

Response 16: Thank you for this critical suggestion. We now have discussed more about the possible reasons (lines 491-494).

Lines 491-494: Compared with Arabidopsis and rice, the AvLBD family comprises fewer genes and lacks Class Ie members, indicating interspecific divergence [21]. Another plausible explanation is that the LBD family is still incompletely annotated in A. valvata at the transcript level.

 

Comments 17: It is not discussed whether induction levels are strong, moderate, or weak compared to known hypoxia genes (ADH1, PDC1, SUS1, etc.). It is also not discussed whether the response is early, transient, or sustained, nor what this means biologically. It would be advisable to include why there is no HRPE even though they are induced (this is important and unusual).

Response 17: Thank you for this critical suggestion. We now have discussed the comparison, relationship and predicted biological meanings (lines 539-544). Besides, we include more about the possible regulatory elements (502-504).

Lines 502-504: Although the HRPE motif is absent from kiwifruit promoters, both AvLBD41_11 and AvLBD41_7 harbor multiple ERF-binding GCC-core and WRKY-binding W-boxes (Figure 10), indicating possible regulation by waterlogging-induced ERF and WRKY TFs.

Lines 539-544: Interestingly, AvLBD41_7, i1_LQ_K_c67155/f1p0/1459 (ADH1) and i1_LQ_K_c38965/f1p0/1342 (ADH2) all showed an abrupt peak at 12 h of waterlogging and declined thereafter [41], suggesting that AvLBD41_7 may acts as a transcriptional rheostat that sustains, rather than initiates, ADH expression. Its lower induction amplitude may curb excessive ethanol fermentation, and this dosage-dependent hypothesis need more direct functional testings.

 

 

Comments 18: There is a lack of biochemical discussion about what it implies that it interacts with ERF75 but not with ERF73, differences in AP2 domains? motifs? The same goes for ERF, WRKY, Trihelix, could they form a multi-protein complex network?

Response 18: Thank you for this helpful question. We now have discussed the possible reasons why AvLBD41_7 interacts with ERF75 but not with ERF73 (lines 521-523). Although pairwise ERF–WRKY and ERF–Trihelix interactions have been reported in Arabidopsis, no study has yet demonstrated that all three factors can form a single ternary complex. This tripartite interaction remains to be experimentally tested. In this study, we mentioned a possible role of WRKY, except LBD and ERF (lines 536-539).

Lines 521-523: AvERF73 and AvERF75 protein share 84.53 % amino-acid identity. Sequence differences within their AP2 domain or adjacent motifs presumably specify their distinct interaction partners.

Lines 536-539: In kiwifruit, WRKYs have been identified as pivotal regulators of the waterlogging response [15, 60]. Whether WRKYs physically associate with LBD proteins to co-regulate waterlogging responses in A. valvata remains to be investigated.

 

Comments 19: Regarding localization, the discussion is superficial. Nuclear localization is not surprising; this paragraph contributes little. It is missing consideration of whether localization changes in response to stress, as occurs with some TFs.

Response 19: Thank you for this helpful suggestion. Now we discuss a possible role of liquid-liquid phase separation of AvLBD41_7 protein during waterlogging stress in kiwifruit (lines 550-554).

Lines 550-554：Liquid-liquid phase separation is emerging as a key mechanism by which plants sense and respond to environmental stress [64]. In A. valvata, AvLBD41_7 formed protein condensates during subcellular-localization assays, implying that its response to waterlogging is possibly mediated by liquid-liquid driven compartmentalization.

 

Comments 20: Finally, the discussion does not land on a conceptual message nor is an integrative model presented, nor limitations or future experiments, which is important.

The document is very interesting and provides relevant information; however, it still needs improvement regarding the context of why the research was necessary, why a specific crop is used, and especially the methodological conditions require greater care, as the information required for replication of the experiments is not being provided.

Response 20: Thank you for this helpful suggestion. We now end the Discussion with a concise summary: an AvLBD41-7-centred network model, its practical marker value, and stated future work to address current limitations (lines 577-583).

Lines 577-583: In this study, AvLBD41_7 was established as a master regulator of waterlogging tolerance in A. valvata. It physically links the hypoxia sensors AvHRA1 and AvERF75, revealing more about the waterlogging transcriptional network in kiwifruit. AvLBD41_7 promoter and its PCR marker are helpful tools for molecular assisted kiwifruit breeding. The main demerit is the lack of in vivo function validation. In the future, stable transgenic lines that over-express or silence AvLBD41_7 are required to prove if it directly affects waterlogging survival.

Author Response File: Author Response.pdf

Reviewer 4 Report

Comments and Suggestions for Authors

It is frustrating to have so much molecular data presented without being able to relate it to the actual plant phenotype. Changes in genetic/molecular content do not always make themselves known at the whole-plant level. How do we know what these genetic changes mean in real life?

For that matter, the analysis of the genetic information is also lacking. Th authors suggest that Fig 11 shows distinct expression patterns, but have not done a statistical analysis of differences at different times of sampling. Some of the supposed differences look like they overlap with each other. In Figure 12, the authors seem to have left (except in one case) a 'W' on the X-axis, when the stress being tested is not waterlogging. Again. claims are made of differences that may not stand up to ANOVA testing.

A revision of this mss should show links between the extent of physiological damage from salt, alkalinity, or waterlogging and the hypothesized molecular mechanisms.

Author Response

Comments 1: It is frustrating to have so much molecular data presented without being able to relate it to the actual plant phenotype. Changes in genetic/molecular content do not always make themselves known at the whole-plant level. How do we know what these genetic changes mean in real life?

Response 1: Thank you for pointing this out. We agree with this comment.An in vivo validation is essential to relate the expression changes of AvLBD41_7 to waterlogging survival in kiwifruit. We have now initiated over-expression lines for AvLBD41_7, and the first transgenic plantlets are currently being acclimatised. Detailed phenotyping under controlled waterlogging conditions will be performed in the next growing season, and the results will be included in a follow-up manuscript. This functional characterization will close the current gap and prove what these molecular content changes mean in real life.

To strengthen the applied relevance of our study, new functional experiments demonstrating the utility of the AvLBD41_7 promoter and its derived PCR marker have been added in the new MS. These data (new Fig. 11 & 12) show that the promoter fragment can be potentially used to screening the waterlogging tolerant kiwifruit accessions, while the PCR marker accurately distinguishes A. valvata from A. deliciosa accessions. In real-life breeding: nursery technicians can use the AvLBD41_7 PCR marker to obtain a definitive genotype (A. valvata vs. A. deliciosa) without costly waterlogging assays.

Comments 2: For that matter, the analysis of the genetic information is also lacking. Th authors suggest that Fig 11 shows distinct expression patterns, but have not done a statistical analysis of differences at different times of sampling. Some of the supposed differences look like they overlap with each other. In Figure 12, the authors seem to have left (except in one case) a 'W' on the X-axis, when the stress being tested is not waterlogging. Again. claims are made of differences that may not stand up to ANOVA testing.

Response 2: Thank you for highlighting the lack of statistical analysis. We have now added significance tests (P < 0.05) to the Fig. 11. We have thoroughly revised the Results section to address your comments, incorporating the new statistical analyses and removing all outdated content (lines 468-475). To avoid any ambiguity, we have removed all salt- and alkali-stress treatments, and Fig. 12 has been removed.

Lines 468-475: In leaves, both genes displayed comparable low-level expression that remained largely unaffected by waterlogging. In the petiole, AvLBD41_11 transcripts increased significantly at 24 h, whereas AvLBD41_7 was significantly induced at 12 h. In the stem, both AvLBD41_11 and AvLBD41_7 transcripts peaked sharply at 12 h before returning to baseline levels. In the stem end, both genes were significantly up-regulated at 24 h, but AvLBD41_7 accumulated to substantially higher levels than AvLBD41_11, suggesting a predominant role for AvLBD41_7 in waterlogging responses.

Comments 3: A revision of this mss should show links between the extent of physiological damage from salt, alkalinity, or waterlogging and the hypothesized molecular mechanisms

Response 3: Thank you for this insightful suggestion. To maintain a clear focus, the revised manuscript now concentrates exclusively on waterlogging stress. Salt- and alkali-related datasets have been removed to avoid dilution of the main message.

Phylogenetic analysis of the AvLBD41_7 promoter places the waterlogging-tolerant accessions of A. valvata, A. macrosperma and A. polygama in a single, well-supported clade (New, Fig. 11), indicating that genotypes exhibiting limited growth inhibition under waterlogging cluster with AvLBD41_7. Consistent with this, the PCR marker derived from the same locus yields a diagnostic band pattern: waterlogging-tolerant A. valvata (little injury) produces Band 1, whereas waterlogging-sensitive A. deliciosa (severe injury) produces Band 2, enabling instant genotypic separation of the two groups.

In the next step, transgenic kiwifruit plants (over-expressing of AvLBD41_7) will be subjected to controlled waterlogging. Phenotypic comparisons (survival rate, root ROS damage, photosynthetic recovery) combined with time-course qPCR of AvLBD41_7 will clarify how expression dynamics link to waterlogging-tolerance types.

 

Author Response File: Author Response.pdf

Round 2

Reviewer 3 Report

Comments and Suggestions for Authors

Dear Editor,

I am pleased to have reviewed the manuscript “Transcriptome-Wide Survey of LBD Transcription Factors in Actinidia valvata under Waterlogging Stress and Functional Analysis of Two AvLBD41 Members” provided by Zhi Li, Ling Gan, Xinghui Wang, Wenjing Si, Haozhao Fang, Jinbao Fang, Yunpeng Zhong, Yameng Yang, Fenglian Ma, Xiaona Ji, Qiang Zhang, Leilei Li, and Tao Zhu. The authors have considered all my previous comments, and the gaps that were observed in the first review have been resolved. The manuscript now provides sufficient information for its replication.