Transcriptional Modulation of Resistance against Xanthomonas oryzae pv. oryzae Korean Race K2 in japonica Rice

Round 1

Reviewer 1 Report

Authors of present manuscript had done some impressive analysis of microarray data generated from susceptible and resistant rice cultivars 48 hpi Xoo K2. They have also identified putative DEGs which could be responsible for resistance shown by JB cultivar. Further, they have also over-expressed these DEGs in the rice and have analysed the transgenic plants for resistance.

1. What was the reason behind the selection of 13 DEGs from the highly expressed transcripts. A cluster of genes which were exclusively highly expressing in the JB 0 hours samples became silent post 48h of infection. Could this be the reason behind failure of all 13 genes to increase the resistance shown by DJ cultivars against the Xoo K2. 
2. Authors have not shown the expression pattern of these 13 DEGs in the infected/non-infected conditions. Authors should figure out some way to represent the microarray and qPCR data of these 13 selected DEGs. If not, can authors atleast indicate or mention the heatmap clusters from where these genes were taken?

Author Response

Reviewer 1:

Authors of present manuscript had done some impressive analysis of microarray data generated from susceptible and resistant rice cultivars 48 hpi Xoo K2. They have also identified putative DEGs which could be responsible for resistance shown by JB cultivar. Further, they have also over-expressed these DEGs in the rice and have analyzed the transgenic plants for resistance.

1. What was the reason behind the selection of 13 DEGs from the highly expressed transcripts. A cluster of genes which were exclusively highly expressing in the JB 0 hours samples became silent post 48h of infection. Could this be the reason behind failure of all 13 genes to increase the resistance shown by DJ cultivars against the Xoo K2. 

Ans. Two things: First, the expression value was inferred as the log2FC=Log2(B)-Log2(A) where B is the treatment value (48 hpi) and A is the reference value (0 hpi). The selected DEGs are the first 13 DEGs with the highest expression value. This point was highlighted in result section under the paragraph “Selection of DEGs for validation, cloning, and ectopic expression”. There were no other reasons other than having the highest expression value.  Second, although none of the 13 DEGs showed resistance comparable to JB, there are four overexpression transgenic (TAT, P450, and 2 EXPs) showing significantly lower lesion length (partial resistance) compared to the wildtype parent DJ as shown in Figure 8.

1. Authors have not shown the expression pattern of these 13 DEGs in the infected/non-infected conditions. Authors should figure out some way to represent the microarray and qPCR data of these 13 selected DEGs. If not, can authors at least indicate or mention the heatmap clusters from where these genes were taken?

Ans. We have added a table (Table 2) reflecting the expression values of these 13 DEGs determined by microarray and validated using qRT-PCR.

Reviewer 2 Report

The manuscript by Nino and Cho describes a microarray analysis between two rice cultivars Jinbaek and Dongjin against Bacterial blight disease resistance, where the one cultivar is resistant and the other susceptible, respectively. Moreover, the authors verify the DEGs identified, and construct overexpressor lines of the most upregulated DEGs on the resistant cultivar into the susceptible and test for disease resistance. The manuscript and the findings are very interesting.

Figure 1C: Follow the series used in A and B where you first show JB and then DJ, to be consistent. Or change A and B, whatever is easier

Figure 2C: In each comparison made, the number of DEG genes should be added in a parenthesis right after the name (eg. JB 48 vs DJ 48 (200)). The way the data and the Venn diagram is presented now is confusing. The authors could also use colours for each comparison and the cycles, to help the reader interpret the data.

“To identify the gene-linked annotation associated with the K2-induced genes, the gene list was uploaded to DAVID Functional Annotation Bioinformatics Microarray Analysis [23], and corresponding GO terms were obtained (Figure 3) “ : which gene list is this?  how did the authors filter the DEGs? A diagram (workflow) of the criteria and how the dataset was filtered is crucial.

“The expression patterns of 13 selected DEGs, which were subsequently used in ectopic overexpression study”: Again, how did the authors chose these 13 genes? Which were the criteria?

On the next paragraph the authors state “For identification of candidate genes conferring resistance against Xoo K2, 13 DEGs with the highest expression level (log2 fold-change value) were selected for cloning and characterization through ectopic expression in rice”. This should come first. The authors should clearly state how they chose their genes (highest expression) and then go ahead to the confirmation and further analysis  section. I think these two paragraphs of the manuscript need to be rewritten a little more carefully.

Figures 5, 6 and Table S3: I would recommend instead of using the codes (B2, C3, H10, etc) to use the actual gene names (P450, or whatever). It’s totally confusing this way. Also, at the end of paragraph “Spatio-temporal expression of K2-DEGs in wild type rice” a final sentence with some conclusions should be added. This way it is totally descriptive.

An introductory sentence should also be added on the next paragraph “Exogenous application of SA and JA induces mRNA expression of K2-DEGs”. Why did the authors perform this experiment anyway? This is a general comment to help improve the manuscript, the authors should add one or two introductory sentences in the sections.

I think that a workflow describing the microarray analysis and how this was filtered to close to the 13 DEGs selected is really important. The authors should also pay a little more attention on how the manuscript is written and how they go from one section to another (introductory and concluding sentences between the sections).

The experimental design and data interpretation is very good, so I think if they improve the points above, will make the manuscript even better.

Author Response

Reviewer 2:

Comments and Suggestions for Authors

The manuscript by Nino and Cho describes a microarray analysis between two rice cultivars Jinbaek and Dongjin against Bacterial blight disease resistance, where the one cultivar is resistant and the other susceptible, respectively. Moreover, the authors verify the DEGs identified, and construct overexpressor lines of the most upregulated DEGs on the resistant cultivar into the susceptible and test for disease resistance. The manuscript and the findings are very interesting.

1. Figure 1C: Follow the series used in A and B where you first show JB and then DJ, to be consistent. Or change A and B, whatever is easier.

Ans. We modified the order of samples DJ and JB in three different figures which comprised Figure 1, as suggested.

2. Figure 2C: In each comparison made, the number of DEG genes should be added in a parenthesis right after the name (eg. JB 48 vs DJ 48 (200)). The way the data and the Venn diagram is presented now is confusing. The authors could also use colours for each comparison and the cycles, to help the reader interpret the data.

Ans. We improved the figure by assigning different color for each group and the number of DEG genes is also indicated (in a parenthesis) as suggested. See figure 2.

3. “To identify the gene-linked annotation associated with the K2-induced genes, the gene list was uploaded to DAVID Functional Annotation Bioinformatics Microarray Analysis [23], and corresponding GO terms were obtained (Figure 3)“ : which gene list is this?  how did the authors filter the DEGs? A diagram (workflow) of the criteria and how the dataset was filtered is crucial.

Ans. The DEGs inferred for each genotype was used as the genes list for the subsequent functional annotation. DEGs were derived through a sequential process as shown in Figure 2 which was briefly described in the result as follows: “Expression values inferred from the scanned hybridization signals were normalized and data were further processed for fold change and statistical filtering (Figure 2). Probes with values that passed both filter thresholds were inferred as the differentially expressed genes (DEGs) or gene lists of a corresponding genotype.”

4. “The expression patterns of 13 selected DEGs, which were subsequently used in ectopic overexpression study”: Again, how did the authors chose these 13 genes? Which were the criteria?

Ans. These 13 DEGs were the ones with the highest expression value (fold change value) as determined by microarray. To clarify this, we have modified the section in the result with the subtitle “Selection of DEGs for validation, cloning, and ectopic expression”. In this section we mentioned the purpose of screening these DEGs using ectopic expression. Further, we stated that the basis of selection was the high expression value.

5. On the next paragraph the authors state “For identification of candidate genes conferring resistance against Xoo K2, 13 DEGs with the highest expression level (log2 fold-change value) were selected for cloning and characterization through ectopic expression in rice”. This should come first. The authors should clearly state how they chose their genes (highest expression) and then go ahead to the confirmation and further analysis section. I think these two paragraphs of the manuscript need to be rewritten a little more carefully.

Ans. We have already improved the paragraph prior to this section in the result part, highlighting the basis of selection of these DEGs. For the paragraph titled “Generation of overexpression transgenic plants, we mentioned the intent to perform ectopic expression and the selection of transgenic plants for each construct with single copy gene identified using TaqMan qPCR.

6. Figures 5, 6 and Table S3: I would recommend instead of using the codes (B2, C3, H10, etc) to use the actual gene names (P450, or whatever). It’s totally confusing this way. Also, at the end of paragraph “Spatio-temporal expression of K2-DEGs in wild type rice” a final sentence with some conclusions should be added. This way it is totally descriptive.

Ans. We modified the codes using the abbreviation of the actual gene name as indicated in the figure. Also, a concluding sentence stating the implication of the differences in background expression and the importance of overexpression study, was added.  

7. An introductory sentence should also be added on the next paragraph “Exogenous application of SA and JA induces mRNA expression of K2-DEGs”. Why did the authors perform this experiment anyway? This is a general comment to help improve the manuscript, the authors should add one or two introductory sentences in the sections.

Ans. A brief introductory statement mentioning the relevance of this experiment, such that both SA and JA play important role in the regulation of immunity in plants, was added in the paragraph. The codes of the genes were also changed based on their actual gene name in consistent with the prior figures and tables.

8. I think that a workflow describing the microarray analysis and how this was filtered to close to the 13 DEGs selected is really important. The authors should also pay a little more attention on how the manuscript is written and how they go from one section to another (introductory and concluding sentences between the sections).

Ans. A figure (Figure 2) depicting the microarray analysis was added and a brief discussion was added as introductory in “Differentially expressed genes between JB and DJ in response to Xoo K2 paragraph.

9. The experimental design and data interpretation is very good, so I think if they improve the points above, will make the manuscript even better.

Reviewer 3 Report

The manuscript by Niño and Cho is focused on the studies of transcriptional modulation of resistance against Xanthomonas oryzae pv. oryzae Korean race K2 in japonica rice. The manuscript contains a lot of novel interesting data, well written and easy to follow. However, I have several suggestions that I hope would improve the manuscript.
- Statistical analysis is missed for a key experiments, results of which are presented on fig. 7. It is unclear from this figure expression of which transgenes resulted in statistically significant reduction of bacterial blight disease progress.
- In the experiments with overexpression the authors used three different transgenes for each DEG. In some cases, they detected quite a significant differences in responses to bacterial blight in different transgenes expressing the same DEG. If there is also a similar correlation in transgenes expression levels for these plants?
- General analysis of function for DEGs, expression of which reduce bacterial blight disease progress, is missed.
- General: the sizes of fonts used by authors within the figures should be increased for most of the figures.
- The definition for green boxes within fig.4 should be added to the legend.

Author Response

Reviewer 3:

The manuscript by Niño and Cho is focused on the studies of transcriptional modulation of resistance against Xanthomonas oryzae pv. oryzae Korean race K2 in japonica rice. The manuscript contains a lot of novel interesting data, well written and easy to follow. However, I have several suggestions that I hope would improve the manuscript.

1. Statistical analysis is missed for a key experiments, results of which are presented on Fig. 7. It is unclear from this figure expression of which transgenes resulted in statistically significant reduction of bacterial blight disease progress. 

Ans. Statistical analysis was performed and significant difference was indicated as superscript letters above the bars (Figure 8). There were few transgenic plants that showed significant reduction of bacterial blight.

2. In the experiments with overexpression the authors used three different transgenes for each DEG. In some cases, they detected quite significant differences in responses to bacterial blight in different transgenes expressing the same DEG. If there is also a similar correlation in transgenes expression levels for these plants? 

Ans. Two things were observed, first, transgenic plants showing higher transcript level did not necessarily translate to higher reduction of the disease lesions. Second, variation in the lesion reduction degree did not correlate well with the differences in the level of expression among lines of the same transgene construct. 

4. General analysis of function for DEGs, expression of which reduce bacterial blight disease progress, is missed. 

Ans. This has been discussed in the concluding part of the discussion, wherein, of the four DEGs conferring partial resistance to Xoo K2, only Cytochrome P450s have been previously demonstrated/reported to participate in the reduction of the disease through synthesis of plant defense compounds such as DIMBOA and antimicrobial triterpenes. However, the other three DEGs including TAT and 2 expressed proteins have never been reported to play important role in immunity in plants.

5. General: the sizes of fonts used by authors within the figures should be increased for most of the figures.

Ans. We have increased the fonts as suggested.

6. The definition for green boxes within fig.4 should be added to the legend.

Ans. We have added the definition for green boxes in the legend part.

Round 2

Reviewer 2 Report

All of my concerns and suggestions are properly addressed.

Reviewer 3 Report

all concerns have been addressed properely