Review Reports - Uncovering the Molecular Response of Oregano (Origanum vulgare L.) to 12C6+ Heavy-Ion Irradiation Through Transcriptomic and Metabolomic Analyses

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Dear Authors,
This manuscript presents the investigation of oregano response to irradiation on transcriptomic and metabolomic levels. This manuscript requires significant revisions to be published in CIMB.

The abstract is written to the point, but I would advise not to use specific numbers ("69.35%; 6,204") to make it easier for the reader to understand.

Keywords should not duplicate those in the article title; please remove duplicates and replace them with other relevant keywords.

The first sentence of the last paragraph of the introduction is too complex (lines 91–94). I recommend either breaking it into two or rewriting it with clearer wording. Also, the last paragraph is very vague about your research objectives. I also recommend highlighting the novelty of your research here.

Materials and methods
2.1. Line 103: Please at least mention Gy as gray the first time.
Lines 105-107: Can you write exactly how much semi-lethal dose was determined?
How many T0/T2 seeds were used for further experiments?
2.2. Please provide a link to ImageJ and its version.
2.3. Please provide the full wording for SPAD abbreviation here.
2.4. Provide links and versions of all databases and software used.
2.5. What stage/age were the leaves? Did the library include a mixture of several leaves from the same plant or just a selected single leaf?
What data was used as the DESeq2 input? It is incorrect to use FPKM-normalized data to determine DEGs.
Also, in this section, please provide all references to tools and databases and their versions.

Results

3.1 The first paragraph of text is quite long and data about the survival rate would be better presented as a separate subplot to make a clear visualization.
The subplots in Figure 1 (B - G) are very small and almost unreadable. They should be enlarged and placed under Figure 1 A.
3.2. In the second paragraph, it seems to me not entirely correct to calculate the percentages of classes from a total of 62 metabolites; it would be easier to understand calculating their absolute number and also display it in Figure 2 B.
Figure 2: The abundance of class colors in Figure 2 C makes them very difficult to read. I would also recommend creating a two-dimensional plot of Figure 2 B for ease of reading. Overall, all legend text on all subplots in Figure 2 should be enlarged by approximately 1.5–2 times to ensure readability.
3.3. Please, check the value "49.14%" on line 277. I think there is an error here.
Figure 3: It is necessary to increase the size of the subplots themselves and their captions
3.4. Unfortunately, Figure 4 in its current form is also difficult to read. I would recommend leaving the subplots in B, enlarging them, and moving the pie charts to supplements. Or vice versa.
3.5. I'm not entirely clear on the logic behind identifying transcription factors in this section. Do these 250 TFs belong to a specific intersection group from the Venn diagram in Figure 3? Or were they derived from the list of all identified DEGs? In that case, the question of their interpretation and generalization arises. Perhaps it's worth considering the TF compositions for these two groups separately compared to the control?
On the right side of Figure 5 C, the red-blue scale from 0 to 1 appears to be redundant, or its meaning isn't fully explained in the legend. This, along with the Min-Max scale in Figure 5 B, needs clarification.
3.6. In this section, you list not only trivial names but also Unigene identifiers. How informative are these IDs? Will you be able to include the transcript sequences you collected with Unigene IDs in FASTA format in the supplementary data?
In Figure 6, I would recommend using trivial gene names instead of their Unigene IDs, and also increasing the size of all inscriptions.
3.7. What units are used to represent the color scales in Figure 7? This should be explained in the legend. Legends for all figures should be self-explanatory. Please double-check it.

Discussion
Line 428: "These divergent These divergent", Please correct it.
Lines 450-451 "Arabidopsis thaliana" should be written in italics. Please double-check the spellings of all species names in the article.
Also, all gene names like "WRKY33", "PAD3" should be written in italics. Please correct it throughout the whole manuscript.
Also, you should highlight the limitations of your study, such as the fact that you do not know the specific mutations in NZ1 and NZ2 that led to such changes in the phenotype, transcriptome, and metabolome. Your identification of key genes was, after all, based on indirect relationships, and this is also worth mentioning, since non-obvious regulatory interactions may be involved in molecular genetic systems.

Will transcriptomic and/or metabolomic data be published in any database? Can you indicate this in the Data Availability Statement?

Author Response

Dear Editor:

Thanks very much for your comments and suggestions concerning our manuscript (ID: cimb-4022955) entitled "Uncovering the Molecular Response of Oregano (Origanum vulgare L.) to ¹²C⁶⁺ Heavy-Ion Irradiation through Transcriptomic and Metabolomic Analyses". Based on the comments we received, we have made careful modifications to the original manuscript and the revised text in manuscript was marked with blue characters to highlight the changes. Point-by-point responses to the two nice reviewers are listed below this letter.

Reviewer 1 comments:

Dear Authors,

This manuscript presents the investigation of oregano response to irradiation on transcriptomic and metabolomic levels. This manuscript requires significant revisions to be published in CIMB. The abstract is written to the point, but I would advise not to use specific numbers ("69.35%; 6,204") to make it easier for the reader to understand. Keywords should not duplicate those in the article title; please remove duplicates and replace them with other relevant keywords.

Response: We thank the reviewer for this precise suggestion. We have revised the abstract to replace specific numbers with more general descriptions, e.g., "Metabolomic analysis indicated that the differentially accumulated volatile compounds were primarily terpenoids" and " transcriptomic analysis indicated a predominant enrichment of differentially expressed genes in terpenoid biosynthesis". We have also updated the keywords by removing those that duplicated the title and adding new relevant terms such as "plant mutagenesis breeding", "secondary metabolites", and "gene expression profiling".

The first sentence of the last paragraph of the introduction is too complex (lines 91-94). I recommend either breaking it into two or rewriting it with clearer wording. Also, the last paragraph is very vague about your research objectives. I also recommend highlighting the novelty of your research here.

Response: We thank the reviewer for this precise suggestion. We have rewritten the last paragraph of the Introduction to improve clarity. The sentence has been split, and the research objectives are now stated more explicitly. We also emphasized the novelty of applying heavy-ion mutagenesis combined with multi-omics to decipher terpenoid regulation in oregano, a system previously unexplored in this context.

Materials and methods

2.1. Line 103: Please at least mention Gy as gray the first time.

Lines 105-107: Can you write exactly how much semi-lethal dose was determined?

How many T0/T2 seeds were used for further experiments?

Response: We thank the reviewer for this precise suggestion. We have now defined "Gy" (gray) upon its first mention. The semi-lethal dose (LD₅₀) was determined to be 60 Gy, as stated in the text. 500 mutagenized seeds were cultivated as T0 plants, and twenty seeds from each T2 line were selected and planted at the Henan Academy of Agricultural Sciences experimental station in Xinxiang City for cultivation were used for further experiments analyses. This information has been clarified in the revised Methods section.

2.2. Please provide a link to ImageJ and its version.

Response: We sincerely apologize for this omission. We have added the ImageJ version 1.54J in revised text.

2.3. Please provide the full wording for SPAD abbreviation here.

Response: We sincerely apologize for this omission. We have expanded "SPAD" to "Soil Plant Analysis Development " in line 126.

2.4. Provide links and versions of all databases and software used.

Response: We appreciate the reviewer's precise suggestion and provided versions for all software and databases (e.g., Trinity, DESeq2, KEGG, etc.) in the Materials and Methods section.

2.5. What stage/age were the leaves? Did the library include a mixture of several leaves from the same plant or just a selected single leaf?

What data was used as the DESeq2 input? It is incorrect to use FPKM-normalized data to determine DEGs.

Also, in this section, please provide all references to tools and databases and their versions.

Response: We thank the reviewer for highlighting this ambiguity. Leaves were collected at the harvesting Period (oregano is typically harvested before flowering, when its essential oil content is highest and quality is optimal. Specific growth cycles and harvest times may vary depending on climate and cultivation objectives). Collect leaves and extract RNA from all fresh leaves. Additionally, standardize the raw transcriptomic expression matrix (counts) using DESeq2 and perform differential expression analysis—not FPKM values. We have corrected this in the text and clarified the leaf sampling and RNA-seq analysis workflow.

Results

3.1 The first paragraph of text is quite long and data about the survival rate would be better presented as a separate subplot to make a clear visualization.

The subplots in Figure 1 (B - G) are very small and almost unreadable. They should be enlarged and placed under Figure 1 A.

Response: We thank the reviewer for this valuable comment. We have split the first results paragraph for better readability and added a supplementary figure (Fig. S3) showing dose-response survival curves. In revised Figure 1, panels B-G have been enlarged and repositioned below panel A for clarity.

3.2. In the second paragraph, it seems to me not entirely correct to calculate the percentages of classes from a total of 62 metabolites; it would be easier to understand calculating their absolute number and also display it in Figure 2 B.

Figure 2: The abundance of class colors in Figure 2 C makes them very difficult to read. I would also recommend creating a two-dimensional plot of Figure 2 B for ease of reading. Overall, all legend text on all subplots in Figure 2 should be enlarged by approximately 1.5–2 times to ensure readability.

Response: We thank the reviewer for this valuable comment. We have updated the text to include both absolute numbers for metabolite classes. Figure 2B is now a two-dimensional plot showing absolute counts for better contrast. All text elements in Figure 2 have been enlarged to improve readability.

3.3. Please, check the value "49.14%" on line 277. I think there is an error here.

Figure 3: It is necessary to increase the size of the subplots themselves and their captions

Response: We appreciate the questions raised by the reviewers. We have verified the GC content value (49.14%)—it is correct as reported. We have enlarged all subplots and captions in Figure 3.

3.4. Unfortunately, Figure 4 in its current form is also difficult to read. I would recommend leaving the subplots in B, enlarging them, and moving the pie charts to supplements. Or vice versa.

Response: We appreciate the reviewer's precise suggestion and have redesigned Figure 4: the enriched GO are now in supplementary material (Fig. S4), and the enriched KEGG pathways are presented as enlarged bar charts in the main figure

3.5. I'm not entirely clear on the logic behind identifying transcription factors in this section. Do these 250 TFs belong to a specific intersection group from the Venn diagram in Figure 3? Or were they derived from the list of all identified DEGs? In that case, the question of their interpretation and generalization arises. Perhaps it's worth considering the TF compositions for these two groups separately compared to the control?

On the right side of Figure 5 C, the red-blue scale from 0 to 1 appears to be redundant, or its meaning isn't fully explained in the legend. This, along with the Min-Max scale in Figure 5 B, needs clarification.

Response: We sincerely thank the reviewer for this important critique. We have clarified the text and revised the figures and text accordingly.

TF selection logic: The 250 TFs were identified from all DEGs obtained in the pairwise comparisons (NZ1 vs WT, NZ2 vs WT, and NZ2 vs NZ1), not only from a common intersection set. We think that analyzing TF changes separately for each mutant line provides more biologically meaningful insights. Therefore, we have now split the TF analysis per genotype in the revised text and Figure 5B, showing distinct TF family landscapes for NZ1 and NZ2 compared to WT.
Figure 5B: In Figure 5B, the heatmap illustrates the relative expression levels of transcription factor (TF) families across the different samples. Because the absolute expression ranges vary widely among TF families, we applied row-wise Min-Max normalization for visualization purposes. This means that for each TF family, the color scale represents its expression range within that specific family across all samples: the “Max” value corresponds to the highest expression level observed for that family in any sample, while the “Min” value represents the lowest expression level for that same family. This normalization allows for a clear within-family comparison of expression patterns, making it easier to discern which families are upregulated or downregulated in each genotype relative to their own expression baselines.
Figure 5C: We agree with the reviewer's comment that the red–to–blue gradient bar (0–1) is redundant and potentially confusing. In the revised figure, this colour bar has been completely removed. Instead, the Y-axis now directly labels gene expression changes (e.g., “Upregulated in NZ1,” “Downregulated in WT,” etc.), thereby presenting the transcriptional patterns across samples in a clearer and more intuitive manner. We once again thank the reviewer for their valuable suggestions, which have significantly enhanced the readability of the figures.

3.6. In this section, you list not only trivial names but also Unigene identifiers. How informative are these IDs? Will you be able to include the transcript sequences you collected with Unigene IDs in FASTA format in the supplementary data?

In Figure 6, I would recommend using trivial gene names instead of their Unigene IDs, and also increasing the size of all inscriptions.

Response: We thank the reviewer for this valuable comment. We will provide the transcript sequences in FASTA format as supplementary data. In Figure 6, we now use gene symbols instead of Unigene IDs, and all labels have been enlarged.

3.7. What units are used to represent the color scales in Figure 7? This should be explained in the legend. Legends for all figures should be self-explanatory. Please double-check it.

Response: We thank the reviewer for this precise suggestion. We have revised all figure legends to ensure they are self-contained. In Figure 7, the heatmap scale now explicitly states “Relative expression” for gene relative expression and “relative abundance” for metabolites.

Discussion

Line 428: "These divergent These divergent", Please correct it.

Lines 450-451 "Arabidopsis thaliana" should be written in italics. Please double-check the spellings of all species names in the article.

Also, all gene names like "WRKY33", "PAD3" should be written in italics. Please correct it throughout the whole manuscript.

Response: We sincerely apologize for these mistakes and have corrected in revised manuscript.

Also, you should highlight the limitations of your study, such as the fact that you do not know the specific mutations in NZ1 and NZ2 that led to such changes in the phenotype, transcriptome, and metabolome. Your identification of key genes was, after all, based on indirect relationships, and this is also worth mentioning, since non-obvious regulatory interactions may be involved in molecular genetic systems. Will transcriptomic and/or metabolomic data be published in any database? Can you indicate this in the Data Availability Statement?

Response: Thank you for highlighting these important points. We fully acknowledge the limitations noted in our study. Specifically, as the reviewer pointed out, without whole-genome sequencing we cannot identify the exact mutagenic lesions responsible for the observed phenotypic and metabolic changes. Additionally, the association between the identified genes and the accumulation of carvacrol/thymol is indeed based on correlative expression patterns, and further functional validation would be required to confirm direct regulatory relationships.

Regarding data availability: the transcriptomic and metabolomic datasets have not yet been deposited in a public repository. However, all raw and processed data are available upon request. Researchers interested in accessing the data may contact the corresponding author via email. We will promptly share the data to support further research and validation.

Thanks again for your kind help. I look forward to hearing from you.

Sincerely,

Huizhen liang

Institute of Chinese Herbal Medicines

Henan Academy of Agricultural Science

Zhengzhou, 450002, China

Telephone: +86 0371 67509866

mail address: lianghuizhen@hnagri.org.cn

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The manuscript entitled "Uncovering the Molecular Response of Oregano (Origanum vulgare L.) to ¹²C⁶⁺ Heavy-Ion Irradiation through Transcriptomic and Metabolomic Analyses" represents comprehensive study that elucidates the molecular mechanisms underlying metabolic reprogramming induced by heavy-ion irradiation. Heavy-ion beams are accepted as a novel powerful mutagen because they are able to induce mutations with high frequency at a relatively low dose at which virtually all plants survive, and they induce a broad spectrum of phenotypes without affecting other plant characteristics. This research is one step further that leads to the future metabolic engineering and precision breeding. Great idea! The authors engaged several techniques which provided clear results. The work is well described, and the results are placed in an appropriate context. My comments below are intended to strengthen this study.

Were these two, NZ1 and NZ2, the only phenotypes you have observed throw-out generations?
Do you think that selected traits are stable since you observed them for only 2 generations and we should bear in mind that it takes up to M4 to M8 generations for a mutant trait to become stable and reliably inherited after CIB mutagenesis? Can you state that you have homozygous lines?
Could you please rephrase the sentence in the Abstract ‘’ we identified key enzyme-encoding genes, such as GPPS, GGPPS, DXS, and HMGR, involved in the terpenoid backbone biosynthesis pathway, as well as critical candidate genes (TPS3, TPS6A, TPS6C, CYP71D178, CYP71D181, and CYP71D10B) that may regulate the biosynthesis of carvacrol and thymol.’’ - those are well known key genes involved in terpenoid biosynthesis and since you do not have genome sequencing results to be sure where did mutagenesis occurred (are there point mutations in the coding regions of these genes for instance) we could assumed that altered expression of these genes could be also a consequences of mutagenesis itself (stress response) or a description of regulatory networks due to random mutations.

Line 428 – there is a repetition ''These divergent''

Author Response

Dear Editor:

Reviewer 2 comments:

The manuscript entitled "Uncovering the Molecular Response of Oregano (Origanum vulgare L.) to ¹²C⁶⁺ Heavy-Ion Irradiation through Transcriptomic and Metabolomic Analyses" represents comprehensive study that elucidates the molecular mechanisms underlying metabolic reprogramming induced by heavy-ion irradiation. Heavy-ion beams are accepted as a novel powerful mutagen because they are able to induce mutations with high frequency at a relatively low dose at which virtually all plants survive, and they induce a broad spectrum of phenotypes without affecting other plant characteristics. This research is one step further that leads to the future metabolic engineering and precision breeding. Great idea! The authors engaged several techniques which provided clear results. The work is well described, and the results are placed in an appropriate context. My comments below are intended to strengthen this study.

Were these two, NZ1 and NZ2, the only phenotypes you have observed throw-out generations?

Response: We sincerely appreciate the reviewer's valuable question, which prompts us to clarify the scope of phenotypic variations observed in our study.

In fact, NZ1 and NZ2 are not the only mutant phenotypes identified during the multi-generational observation. During the screening process across generations, we initially obtained a total of 18 mutant lines with distinct phenotypic variations after ¹²C⁶⁺ heavy-ion irradiation. These variations covered multiple traits, including plant architecture (e.g., dwarfism, bushy growth), leaf characteristics (e.g., leaf color variation from green to light green, leaf shape changes such as lanceolate to ovate, and leaf thickness differences), and growth cycle (e.g., early flowering and late maturity). However, NZ1 and NZ2 were selected as the focus of this study for the following key reasons: First, they exhibited the most significant and stable differences in both morphological traits (plant height, leaf morphology, biomass) and metabolic profiles (especially the accumulation of target bioactive compounds such as carvacrol and thymol) compared to the wild type (WT). Second, preliminary genetic stability tests showed that their core traits (e.g., terpenoid metabolite composition and key morphological features) maintained consistent expression across two consecutive generations, indicating potential heritability. Third, transcriptomic analysis revealed that these two lines had the most enriched DEGs in terpenoid biosynthesis pathways, which aligned with our research objective of unraveling the molecular mechanisms underlying metabolic reprogramming induced by heavy-ion irradiation.

The other mutant lines either showed unstable phenotypic expression (e.g., trait reversal in the next generation), insignificant changes in target metabolites, or severe growth defects (e.g., low fertility, poor adaptability), making them unsuitable for in-depth multi-omics analysis. We believe that focusing on NZ1 and NZ2, which have clear phenotypic characteristics and metabolic advantages, can more effectively address the core scientific questions of this study. We will supplement the information on the initial screening of mutant lines in the revised manuscript to provide a more comprehensive overview of the phenotypic variation spectrum induced by irradiation.

Do you think that selected traits are stable since you observed them for only 2 generations and we should bear in mind that it takes up to M4 to M8 generations for a mutant trait to become stable and reliably inherited after CIB mutagenesis? Can you state that you have homozygous lines?

Response: We highly agree with the reviewer's insightful comment. The reviewer's reminder about the time required for mutant trait stabilization (M4 to M8 generations) after heavy-ion beam mutagenesis is scientifically rigorous and fully aligns with the general principles of plant mutagenesis breeding. We sincerely appreciate this critical perspective, which helps us improve the rigor of our research conclusions.

In response to the concerns about trait stability and homozygosity, we would like to provide the following explanations: First, regarding trait stability: In our study, the observation of NZ1 and NZ2 across two generations (M2 and M3) showed that their key traits—including morphological indicators (plant height, leaf length/width ratio, biomass accumulation) and metabolic traits (content of 62 differentially accumulated volatile compounds, especially carvacrol and thymol)—exhibited no significant fluctuations between generations. This preliminary stability suggests that the mutations induced by ¹²C⁶⁺ heavy-ion irradiation may have occurred in key functional genes related to these traits, laying a foundation for stable inheritance. However, we fully acknowledge that two generations of observation are insufficient to confirm long-term genetic stability, as the reviewer correctly pointed out that mutant traits typically require M4 to M8 generations to achieve reliable heritability. At present, we have continued to propagate NZ1 and NZ2 to the M4 generation, and ongoing phenotypic and metabolic monitoring shows that their core traits remain consistent with the M2 and M3 generations. We will supplement the M4 generation data in the revised manuscript to provide stronger evidence for trait stability. Second, regarding homozygosity: We currently cannot definitively state that NZ1 and NZ2 are fully homozygous lines. Heavy-ion beam mutagenesis can induce both homozygous and heterozygous mutations in the genome. Given that the study has progressed to the M3 generation, it is plausible that some loci related to the observed traits have achieved homozygosity, while other non-target loci may still be heterozygous. To verify homozygosity, we have initiated genotyping work for key candidate genes (e.g., TPS3, TPS6A, TPS6C, CYP71D178) identified in the transcriptomic analysis. Preliminary sequencing results show that the coding regions of these candidate genes in NZ1 and NZ2 have consistent genotypes across multiple individuals of the same line, suggesting that these key loci may have been homozygous. However, comprehensive genome-wide homozygosity verification (e.g., whole-genome sequencing or SSR marker analysis) is still ongoing.

In summary, we fully recognize the reviewer's concern about trait stability and homozygosity. The current data indicate preliminary stability of the selected traits in NZ1 and NZ2, but long-term multi-generational observation (up to M4-M8) is still needed to confirm reliable inheritance. While key candidate gene loci may be homozygous, comprehensive homozygosity verification is ongoing. In the revised manuscript, we will clearly state the limitations of the current generation of materials and supplement the latest M4 generation phenotypic data and preliminary candidate gene genotyping results. We plan to continue propagating these lines to the M5-M6 generation to further verify trait stability and homozygosity, which will provide a more solid foundation for future metabolic engineering and breeding applications.

Could you please rephrase the sentence in the Abstract ‘’ we identified key enzyme-encoding genes, such as GPPS, GGPPS, DXS, and HMGR, involved in the terpenoid backbone biosynthesis pathway, as well as critical candidate genes (TPS3, TPS6A, TPS6C, CYP71D178, CYP71D181, and CYP71D10B) that may regulate the biosynthesis of carvacrol and thymol.’’ - those are well known key genes involved in terpenoid biosynthesis and since you do not have genome sequencing results to be sure where did mutagenesis occurred (are there point mutations in the coding regions of these genes for instance) we could assumed that altered expression of these genes could be also a consequences of mutagenesis itself (stress response) or a description of regulatory networks due to random mutations.

Response: We thank the reviewer for this valuable comment. We have rephrased the text to more accurately reflect that changes in metabolite levels result from alterations in the transcriptional expression patterns of these genes, rather than necessarily being direct mutagenic targets. The revised wording emphasises their regulatory correlation, rather than a causal mutagenic relationship.

Line 428 – there is a repetition ''These divergent''

Response: We sincerely apologize for the repetition statement and have corrected in revised manuscript.

Thanks again for your kind help. I look forward to hearing from you.

Sincerely,

Huizhen liang

Institute of Chinese Herbal Medicines

Henan Academy of Agricultural Science

Zhengzhou, 450002, China

Telephone: +86 0371 67509866

E-mail address: lianghuizhen@hnagri.org.cn

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

Dear Authors,
After revision, your paper can be accepted for publication by CIMB.
Also, I recommend creating a single gray background for Figure 2D "Volcano plots of DAVs in various comparison groups."