The Mining for Flowering-Related Genes Based on De Novo Transcriptome Sequencing in the Endangered Plant Phoebe chekiangensis

1. Summary

Thank you for handling our review process and for the reviewers' comments on our manuscript entitled " The mining for flowering-related genes based on de novo transcriptome sequencing in the endangered plant Phoebe chekiangensis" (ijms-3370882). These comments were valuable and very helpful. We have carefully studied these comments and have made changes that we hope will meet with your approval. Based on the instructions you provided in your letter, we have uploaded the files of the revised manuscript. We have made revisions to the manuscript and the changes in the text are highlighted in yellow to improve the presentation at all levels of the manuscript. We have endeavoured to respond carefully to the reviewers' comments.

2.Point-by-point response to Comments and Suggestions for Authors

Comments 1: Results of the Figure 1 does not correspond with the experimental design of the Material and Methods section. Authors must clarify the, meaning of the assayed samples.

Response 1: Thank you for your reminder. Wecollected leaves samples at four different development stages and three floral organs at different stages flowering . The samples were used for analyzing plant hormone content and related-genes expression levels. Relevant details have been added to the plant materials section Line 310-323

Comments 2: Results of the Figure 4 does not correspond with the experimental design of the Material and Methods section. Authors must clarify the ,meaning of the assayed samples.

Response 2: Thank you for your suggestion. We used three stages of leaf samples and floral organ samples with notable differences in GA content for qPCR analysis. Relevant details have been added to the plant materials section：“The qPCR data were analyzed to assess significant differences in gene expression lev-els across the samples, with EF1α serving as the reference gene. A one-way analysis of variance (ANOVA) was conducted, using expression levels as the dependent variable and sample groups as the independent factor. Subsequently, Tukey's Honest Significant Difference (HSD) test was applied as a post hoc analysis to identify pairwise dif-ferences between the groups. A p-value < 0.01 was considered indicative of significant differences between the samples.”

Comments 3: Quality of Figure 2 is very poor. The legend also must be stribglky revised to be self-readable.

Response 3: Thank you for your suggestion. We have redrawn Figure 2, enlarged the image, removed unnecessary legends, and added more detailed annotations to the image content in lines 171-180: ' Transcriptome sequencing and annotation results of P. chekiangensis.(a) GC content and distribution: The GC content distribution of the assembled unigenes, indicating the overall sequence composition. The majority of unigenes show a balanced GC content, ranging from 40-50%.(b) Length distribution of all unigenes: The unigene length distribution, with a significant number of unigenes in the 300-1000 bp range, reflecting the diversity of gene sizes in the transcriptome.(c) GO enrichment analysis: Gene Ontology (GO) term categorization, highlighting enriched functions in biological processes, molecular functions, and cellular components.(d) KEGG annotation analysis: KEGG pathway mapping showing the involvement of unigenes in various metabolic and signaling pathways.(e) KOG annotation results: KOG functional classification revealing key roles in signal transduction, protein modification, and general cellular functions.'

Comments 4: In the description of the results in section 2.2 authors must describe the repository and the bioproject with the reads and the obtained results.

Response 4: Thank you for pointing this out. The data used here were  from the article "Development of EST-SSR markers and analysis of genetic diversity in natural populations of endemic and endangered plant Phoebe chekiangensis." Relevant information can be found in this source.

Comments 5: Correlation between phenology, hormones and gene expression is very confuse and need a more intensive analysis to be discussed.

Response 5: We sincerely appreciate you pointing this out. We have added content in Section 2.4 to describe the relationship between plant hormones and gene expression in Figure 4b. The analysis results demonstrate the correlation between different genes and the three types of GA content, clarifying the association between genes and plant hormones.

Comments 6: Experimental design is poorly described in the Section 4.1 and Figure 5. Author must clarify the assayed tissues and the technical and biological replications evaluated.

Response 6: Thank you for your valuable suggestions. We collected samples from different plant tissues, including leaves, roots, and stems, for RNA-seq, aiming to obtain as complete mRNA data as possible. Since our focus is on plant hormones that affect flowering, we selected leaves and floral organs for plant hormone content analysis and qPCR analysis. Each experiment included three biological and technical replicates, and the RNA-seq sequencing depth was 30x. Relevant descriptions have been added to the appropriate sections Line 320-323

Comments 7: Additionally, a detailed description of the time, the period and the climatic conditions of the assya must be included. At this moment this experimental design represeting the flowering development is very poor.

Response 7: Thank you for your reminder. We collected leaf and floral organ samples every two weeks between March and April, resulting in four stages of leaf samples and three stages of floral organ samples. All samples were used for plant hormone content analysis. Since the GA pathway is a key flowering-related pathway, we selected samples with significant differences in GA levels—three stages of leaves (L1-L3 in Figure 5) and three stages of floral organs (F1-F3 in Figure 5)—for qPCR analysis, with the aim of identifying genes involved in GA biosynthesis. This information has been added to the Materials section.

Comments 8: Analysis of the hormone contents is very week. The method and the assayed hormones must be clarified. Number of replications is missing.

Response 8: Thank you for your suggestions. Endogenous hormone content was analyzed using an AB Qtrap 6500 mass spectrometer in triple quadrupole-ion mode, with separation performed on an Agilent 1290 HPLC. Detection was carried out in MRM mode, and quantification was achieved using the ESI-HPLC-MS/MS method. Hormone concentrations were analyzed by one-way ANOVA, with pairwise differences identified using Tukey's HSD test. Each sample included three biological and technical replicates. We have revised the hormone content analysis section and provided specific details regarding the samples used for each experiment in the plant materials section.

Comments 8: qPCR analysis must also be better described. reference genes and statistical analysis must be incorporated. In this analysis and in the RNA-Seq study authros must clarify biological and technical replications.

Response 8: We sincerely appreciate you pointing this out. qPCR data were analyzed to assess gene expression differences, using EF1α as the reference gene. One-way ANOVA was performed with expression levels as the dependent variable and sample groups as the independent factor. Tukey's HSD test was then used for pairwise comparisons, and a p-value < 0.01 was considered significant. For RNA-seq, we have three biological replicates with a sequencing depth of 30x. We have added the corresponding descriptions in the relevant sections line 344~350

Comments 9: A better description of the RNA-Seq analysi must be introduced.

Response 9: Thank you for your valuable suggestions. We have updated the relevant description of the RNA-seq process in M&M sections line 364-375. “Raw reads were preprocessed using Trimmomatic with default parameters to re-move low-quality reads and Illumina adapters, resulting in clean reads. The reads were then de novo assembled using Trinity with default parameters, and the assembly quality was evaluated through length distribution, N50, and average length analyses. The best candidate coding sequences (CDS) for each contig were identified, resulting in a set of Unigenes. These Unigenes were annotated via BLASTx alignment (E-value <1E-5) against public protein databases, including Nr, Swiss-Prot, and TREMBL. Gene Ontology (GO) terms were assigned using Blast2GO, categorizing them into molecular function, cellular component, and biological process. Metabolic pathways were identi-fied using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Transcript abundance (Unigene) was calculated in reads per kilobase per million mapped reads (RPKM) using Bowtie 0.12.8 software. The E-value threshold used ensures the reliabil-ity of functional annotations.”

1. Summary

Thank you for handling our review process and for the reviewers' comments on our manuscript entitled " The mining for flowering-related genes based on de novo transcriptome sequencing in the endangered plant Phoebe chekiangensis" (ijms-3370882). These comments were valuable and very helpful. We have carefully studied these comments and have made changes that we hope will meet with your approval. Based on the instructions you provided in your letter, we have uploaded the files of the revised manuscript. We have made minor revisions to the manuscript and the changes in the text are highlighted in yellow to improve the presentation at all levels of the manuscript. We have endeavoured to respond carefully to the reviewers' comments.

Comments 1: In Figure 1, the legend for "samples" should be removed, and the figure footnote for the statistical analysis (ANOVA and post-hoc test) applied must be included, as well as the significance difference code.

Response 1: Thank you for pointing this out. We first performed an analysis of variance (ANOVA), followed by a Tukey's HSD test to calculate the P-value. A P-value less than 0.01 was considered statistically significant, and different letters were used to annotate the plot. This information has been added to the footnote of the figure line 130-131:’ P values were calculated using Tukey's HSD test, and different letters indicate a p value < 0.01. ’.

Comments 2: In line 168, change "(3.31%" to "(23.58%)".

Response 2: We sincerely appreciate you pointing this out. We have corrected this error in the text line 168.