In Silico Evaluation of Coding and Non-Coding nsSNPs in the Thrombopoietin Receptor (MPL) Proto-Oncogene: Assessing Their Influence on Protein Stability, Structure, and Function

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The paper by Al-nakhle et al uses an extensive in silico approach to predict the effects of nsSNPs present in the human MPL gene on the efficiency of its translation and on the biological functions of the corresponding protein. The study expands and complete information published in 2019 (reference 9).

The study has clinical relevance given the pivotal role of MPL as a regulator of the hematopoietic  stem cells and of their differentiation toward the megakaryocyte lineage. In addition, inherited mutations in the MPL gene are often associated with alterations of platelet production while its acquired mutations are found in some of the patients with myeloproliferative disorders. In addition, the CARL mutations associated with myeloproliferative disorders induce constitutive activation of MPL and, last but not list, thrombopoietin mimetics are currently used as therapy of aplastic anemia.

I have no concern with the in silico data. It is extensive and accurate. I found, however, that a summary Figure pinpointing in color-code format the location on the various SNPs on the structure of the protein, their function and their eventual oncogenicity is badly missing.

The discussion, however, is badly disappointing. It goes in circle and is terribly over-speculative. The discussion should reflect the fact that this is an in-silico and that all the predictions made by this analysis must be functionally validated. When biochemical/biological data validation data already exist, they should be carefully discussed. As an example, The proteins that interact with MPL identified by the STRING program are already known. For most of these proteins, the location of the interaction has been already identified. Whether the SNPs that potentially affect the interactions are located in domains of MPL already known to interact with that particular protein should be discussed.

Another point that should be discussed is the location of the SNPs identified by this study with the known MPL mutations found in congenic and acquired disorders.

The SNPs that affect the interaction between CARL and MPL are particularly intriguing. Binding between the wild-type CARL/MPL proteins regulates the folding of MPL in the cytoplasm. By contrast, the mutated CARL proteins found in some of the myeloproliferative neoplasms interact with MPL on the cell surface and induce MPL activation. It would be extremely useful to the field to discuss whether the SNPs predicted to affect binding of MPL with CARL affect the binding with the wild.type or oncogenic CARL protein.

Last but not least, it would be important to discuss whether the frequency of the SNPs with functional consequences changes with ethnicity and to pinpoint the diseases where it is expected that exert co-morbidity effects in association with driver mutations.

The bottom line is that the Discussion needs to be carefully revised to include relevant literature with functional validation data already available.  

Minor comments

All the abbreviations should be spelled out in the abstract and the first time they are used in the main text.  

The quality of Figure 2 is poor. As presented, most of Figure 2A may not be read.

There are two Figures 2. The second Figure 2 on page 11 may not be read.

 

Comments on the Quality of English Language

No relevant comment

Author Response

For Reviewer #1

November 12, 2023 

Dr. Jianwen Fang  Editor-in-Chief, CIMB Journal - Special Issue on " Structure and Function of Proteins: From Bioinformatics Insights "

Subject: Submission of Manuscript titled "In Silico Evaluation of Coding and Non-Coding nsSNPs in the Thrombopoietin Receptor (MPL) Proto-Oncogene: Assessing Their Influence on Protein Stability, Structure and Function" for the Special Issue " Structure and Function of Proteins: From Bioinformatics Insights "

 

Dear Dr. Jianwen Fang,

I hope this letter finds you well. I am writing in response to the invaluable comments and suggestions provided by the reviewers on our manuscript titled " In Silico Evaluation of Coding and Non-Coding nsSNPs in the Thrombopoietin Receptor (MPL) Proto-Oncogene: Assessing Their Influence on Protein Stability, Structure and Function." We are grateful for the constructive feedback, and we would like to express our sincere appreciation for the time and effort invested in reviewing our work. We have carefully considered each comment and have made the necessary revisions to enhance the quality and clarity of our manuscript.

Reviewer #1 acknowledged the extensive and accurate in silico data presented in our study. We are pleased that there are no concerns in this regard. In response to the suggestion regarding a summary figure, we have now included a comprehensive figure (Figure 2) that highlights the location of various SNPs, los of function(LOFM) and gain of function (GOF) mutations  on the MPL protein structure represented in a color-coded format. We believe this addition will significantly improve the visual clarity of our findings.

Regarding the discussion section, we acknowledge the reviewer's concerns about its organization and speculation. We have extensively revised the discussion to address these issues. Specifically, we have emphasized that our study is in silico and that experimental validation is essential. Additionally, we have discussed the location of the identified SNPs in relation to known MPL mutations in congenital and acquired disorders, providing a more comprehensive context for our findings as indicated in lines 446-489.

The reviewer also pointed out the intriguing SNPs affecting the interaction between CARL and MPL. We have expanded on this topic, discussing how these SNPs may impact binding with wild-type and oncogenic CARL proteins, providing valuable insights into potential mechanisms of action as indicated in lines 547-582.

Moreover, we have not included information on the ethnic variability of these SNPs because such data is unavailable in the database.

Finally, we have addressed the minor comments by expanding all abbreviations in the abstract and providing their full form upon their initial use in the main text. Furthermore, we have enhanced the quality of Figure 2A and relocated it to the supplementary materials as Figure S1 to enhance readability.

In conclusion, we believe that these revisions have significantly strengthened our manuscript and addressed the valuable input from the reviewer. We are confident that the updated version of our paper is now better positioned for publication in the CIMB Journal. We kindly request that you re-evaluate our manuscript based on these revisions, and we look forward to your feedback.

Thank you once again for your consideration and for providing us with the opportunity to improve our work.

Sincerely,

Hakeemah

Hakeemah Al-nakhle

Medical Laboratory Technology Department, College of Applied Medical Sciences,

Taibah University, Al-Madinah Al-Munawara, Saudi Arabia.

00966544440961

 [email protected]

 

 

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The article “In Silico Evaluation of Coding and Non-Coding nsSNPs in the  Thrombopoietin Receptor (MPL) Proto-Oncogene: Assessing Their Influence on Protein Stability, Structure and Function” by Hakeemah H Al-nakhle et al., is an informative bioinformatics analysis of the thrombopoietin receptor gene structure and function and its association with a range of haematological disorders. The authors have employed a range of bioinformatics tools to define the in silico predictions about mutations that could be pathogenic, could alter the structure or the function of MPL gene product. Signaling from thrombopoietin receptor is critical not only for megakaryocytes-platelet differentiation but also in the hematopoietic stem cell maintenance and function. Therefore, the detailed predictive mutational analysis of the MPL gene could shed new light on the development and function of multiple hematopoietic cells if the mutations happen in vivo. The author’s structured analysis by employing various bioinformatics tools and the description of the results in a simple manner makes the article useful for the readers. Overall, it is a good attempt to expand our knowledge about the possible functional and structural changes that could occur in thrombopoietin signalling because of any of the predicted mutations in the various domains of the MPL gene.

However, looking at the article it is evident that the authors are not very particular about details and have not checked the manuscript thoroughly before submission. There are several omissions in terms of referring to correct Figure or Table throughout the manuscript. Starting from Table 1 in line 249 till the end wrong Figure and Table numbers are referred in the text. This reflects the lack of seriousness in preparing the manuscript. The authors need to correct these throughout.

In the Table 1, the title says High risk nsSNPs identified by sex in silico programs, but it is not clear from the Table which sex is more or less affected by the predicted mutations. The authors need to look into it.

Lines 255-259, what are the four domains the authors mentioned in the text. They refer two times to the aa 490/491-513 region. They are the same domain as indicated by the aa numbers. What is the third domain?

Figure 2 needs better description to exactly represent what it shows. The current figure legend is not appropriate.

Table 2 is not mentioned in the text. Mention it at the appropriate place.

Lines 325-326. What are these and to what these refer?

 

The study is useful and overall written well except for the lapses I have pointed out. The authors need to improve on these counts.

Author Response

For Reviewer #2

November 12, 2023 

Dr. Jianwen Fang  Editor-in-Chief, CIMB Journal - Special Issue on " Structure and Function of Proteins: From Bioinformatics Insights "

Subject: Submission of Manuscript titled "In Silico Evaluation of Coding and Non-Coding nsSNPs in the Thrombopoietin Receptor (MPL) Proto-Oncogene: Assessing Their Influence on Protein Stability, Structure and Function" for the Special Issue " Structure and Function of Proteins: From Bioinformatics Insights "

 

Dear Dr. Jianwen Fang,

I hope this letter finds you well. I would like to express my gratitude for the insightful feedback provided by the reviewer on our manuscript titled "In Silico Evaluation of Coding and Non-Coding nsSNPs in the Thrombopoietin Receptor (MPL) Proto-Oncogene: Assessing Their Influence on Protein Stability, Structure, and Function." We greatly appreciate the time and effort invested in reviewing our work, and we are committed to addressing the concerns raised by the reviewer to improve the quality of our manuscript.

We are pleased that the reviewer found our article informative and acknowledged the significance of our bioinformatics analysis in understanding the thrombopoietin receptor gene's structure and function in relation to hematological disorders. We concur with the reviewer's assessment that the predictions presented in our study could shed new light on the development and function of hematopoietic cells affected by mutations in the MPL gene. We also appreciate the recognition of our efforts to employ various bioinformatics tools and present our findings in a clear and accessible manner.

However, we acknowledge the reviewer's valid concerns regarding certain omissions and issues in our manuscript. Specifically, the reviewer pointed out the following areas that require attention:

1. The incorrect referencing of Figure and Table numbers throughout the manuscript. We apologize for the oversight and  diligently corrected all these references to ensure accuracy.
2. The lack of clarity in the title of Table 1 regarding "High risk nsSNPs identified by sex in silico programs." We revised the table title to provide a more precise description of the data it contains to eliminate any confusion.
3. We have resolved the confusion regarding the four domains mentioned in lines 255-259, as well as the repetition of the aa 490/491-513 region. In the revised manuscript, we have provided a more detailed and accurate description of these domains as indicated in figure 2.
4. The need for a better description of Figure 2 to accurately represent its content. We improved the figure legend to enhance clarity and understanding.
5. The unmentioned reference to Table 2 in the text, which we ensure to appropriately reference within the manuscript.
6. Regarding the query about lines 325-326 and their reference, these lines contain abbreviations related to the table 2.

We greatly appreciate the reviewer's feedback, and we are fully committed to addressing these issues to enhance the quality and accuracy of our manuscript. We thoroughly reviewed the entire manuscript, make the necessary corrections, and provide a revised version that addresses all of the concerns raised.

Once again, we thank the reviewer for their valuable input, and we look forward to the opportunity to resubmit our improved manuscript for consideration in the CIMB Journal. We remain dedicated to ensuring the highest standards of quality in our work.

Sincerely,

Hakeemah

Hakeemah Al-nakhle

Medical Laboratory Technology Department, College of Applied Medical Sciences,

Taibah University, Al-Madinah Al-Munawara, Saudi Arabia.

00966544440961

 [email protected]

 

 

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

Background: The authors studied the MPL gene due to its crucial role in hematopoiesis. Disruptions to this gene can lead to hematological disorders. The objective was to identify the most detrimental nsSNPs affecting MPL and predict the structural changes that might hinder its regular protein-protein interactions.

Methods: The authors employed a suite of bioinformatics tools to assess the impact of 635 nsSNPs in the MPL gene.

Results: Of the 635 nsSNPs, 28 were deemed notably pathogenic. Four vital MPL functional domains were pinpointed. Ten nsSNPs showed strong conservation scores, suggesting potential structural and functional repercussions, and 14 appeared to compromise MPL's protein stability. Although the most damaging nsSNPs didn't directly alter PTM sites, 14 could substantially change the protein's physicochemical properties. Some mutations might endanger pivotal protein-protein interactions with MPL, and three SNPs in the non-coding region showed significant regulatory potential. Moreover, 13 of the 21 evaluated nsSNPs were categorized as high-risk pathogenic variants. The amino acid changes C291S, T293N, D295G, and W435C, impactful for protein stability, were not considered oncogenic.

Conclusions: The authors highlight the significant influence of nsSNPs on MPL protein function and structure. Given MPL's essential role in hematopoiesis, these mutations can result in hematological abnormalities. The high-risk pathogenic nsSNPs identified may become key biomarkers or treatment targets for hematological conditions, paving the way for future research into the MPL gene's role in hematological health.

• Thrombopoietin (TPO) is the ligand that binds to the MPL receptor discussed in the paper. Explaining how TPO also promotes angiogenesis through MPL signaling could provide additional biological context for MPL's role.

• Angiogenesis, the formation of new blood vessels, is crucial for hematopoiesis and development of the blood and immune systems. Discussing how MPL/TPO signaling promotes angiogenesis would link it to broader hematopoietic processes beyond just platelet production.

• MPL is expressed on hematopoietic stem/progenitor cells as well as endothelial cells. Explaining how TPO/MPL signaling promotes angiogenesis through effects on both cell types could provide a more comprehensive view of MPL's multifaceted functions.

• MPL mutations discussed in the paper could have implications for angiogenesis and vascular development in addition to hematopoietic disorders. Relating mutations to their potential effects on angiogenesis may help understand pathogenesis more fully.

• Therapies targeting the TPO/MPL pathway are used for thrombocytopenia and other conditions. Discussing the pathway's role in angiogenesis could inspire new therapeutic strategies aiming to modulate angiogenesis.

• Angiogenesis is important in cancer development and progression. Linking MPL/TPO signaling to this process may help explain the oncogenic potential of some MPL mutations discussed in the paper(thrombopoietin, angiogenesis, myeloma represent crucial aspects to be discussed in this field).

Comments on the Quality of English Language

Background: The authors studied the MPL gene due to its crucial role in hematopoiesis. Disruptions to this gene can lead to hematological disorders. The objective was to identify the most detrimental nsSNPs affecting MPL and predict the structural changes that might hinder its regular protein-protein interactions.

Methods: The authors employed a suite of bioinformatics tools to assess the impact of 635 nsSNPs in the MPL gene.

Results: Of the 635 nsSNPs, 28 were deemed notably pathogenic. Four vital MPL functional domains were pinpointed. Ten nsSNPs showed strong conservation scores, suggesting potential structural and functional repercussions, and 14 appeared to compromise MPL's protein stability. Although the most damaging nsSNPs didn't directly alter PTM sites, 14 could substantially change the protein's physicochemical properties. Some mutations might endanger pivotal protein-protein interactions with MPL, and three SNPs in the non-coding region showed significant regulatory potential. Moreover, 13 of the 21 evaluated nsSNPs were categorized as high-risk pathogenic variants. The amino acid changes C291S, T293N, D295G, and W435C, impactful for protein stability, were not considered oncogenic.

Conclusions: The authors highlight the significant influence of nsSNPs on MPL protein function and structure. Given MPL's essential role in hematopoiesis, these mutations can result in hematological abnormalities. The high-risk pathogenic nsSNPs identified may become key biomarkers or treatment targets for hematological conditions, paving the way for future research into the MPL gene's role in hematological health.Limitations:

1. Database Reliability: The results heavily rely on the integrity and accuracy of databases like ENSEMBL, NCBI, and InterPro. The limitation here is that if there are inaccuracies or updates to the data, they may affect the conclusions drawn.

2. PredictSNP Reliability: PredictSNP amalgamates outputs from multiple prediction tools. It's possible that some of these tools have inherent biases or errors, which might affect the collective output.

3. Domain Identification: While InterPro amalgamates several databases, it might not cover all known protein motifs or domains.

4. Evolutionary Assumptions: ConSurf bases its analysis on evolutionary conservation. This assumes that evolutionary conservation directly correlates with functional importance, which may not always be the case.

5. Protein Stability Predictions: Both I-mutant 3.0 and MUpro offer predictions on protein stability based on machine learning models. Like any model, there can be false positives and negatives.

6. STRING Database: Predicting protein-protein interactions with STRING heavily depends on existing knowledge. Newly discovered or less studied proteins might not have comprehensive interaction data.

7. Non-coding SNP Analysis: The analysis assumes that SNPs in the 5' and 3' UTR regions with a MAF below 0.001 have potential regulatory significance. However, the true significance of such SNPs is more complex and isn't solely based on MAF.

8. Project HOPE: This tool provides a model, not the actual structure. Homology models are based on existing known structures and might not always accurately represent the true protein structure.

9. MutPred2 Limitations: While comprehensive, it can't predict every potential effect of a mutation. Some subtle or complex effects might be missed.

10. CScape and CScape Somatic: While they have high accuracy rates, they are not 100%. Some false positive or negative predictions can occur.

Suggestions:

1. Database Cross-Validation: Cross-validate data from one database with another to ensure accuracy.

2. Supplement PredictSNP: Complement PredictSNP with other prediction tools not covered in its amalgamation to ensure broader insight.

3. Experimental Validation: Whenever possible, validate computational predictions with laboratory experiments to ensure real-world applicability.

4. Consider Protein Interactions: It might be beneficial to consider not only individual protein changes but how those changes might affect interaction networks as a whole.

5. Dynamic Simulation: Consider using molecular dynamics simulations to understand the dynamic nature of proteins and how mutations might affect protein behavior over time.

6. Enrich Non-coding SNP Analysis: Consider other factors like the local DNA structure, chromatin state, or potential interaction with non-coding RNAs when evaluating the importance of non-coding SNPs.

7. Functional Assays: Use functional assays to test the effects of mutations on protein function, especially for those predicted to be deleterious or oncogenic.

8. Continuous Update: Given the rapid advancement in the field of genomics and proteomics, regularly update the methods and databases to stay current.

9. Include Clinical Data: Whenever possible, integrate clinical and phenotypic data with genetic data to offer a more holistic view of the implications of mutations.

10. Some suggestion regarding the discussion that can boost the interest for a broad readership from the hemonc. field:

•  

Author Response

For Reviewer #3

November 12, 2023 

Dr. Jianwen Fang  Editor-in-Chief, CIMB Journal - Special Issue on " Structure and Function of Proteins: From Bioinformatics Insights "

Subject: Submission of Manuscript titled "In Silico Evaluation of Coding and Non-Coding nsSNPs in the Thrombopoietin Receptor (MPL) Proto-Oncogene: Assessing Their Influence on Protein Stability, Structure and Function" for the Special Issue " Structure and Function of Proteins: From Bioinformatics Insights "

 

Dear Dr. Jianwen Fang,

I hope this letter finds you well. I am writing in response to the invaluable comments and suggestions provided by the reviewer on our manuscript titled "In Silico Evaluation of Coding and Non-Coding nsSNPs in the Thrombopoietin Receptor (MPL) Proto-Oncogene: Assessing Their Influence on Protein Stability, Structure, and Function." We are immensely grateful for the constructive feedback and appreciate the time and effort invested in reviewing our work. We have carefully considered each comment and are committed to incorporating the necessary revisions to improve the quality and comprehensiveness of our manuscript.

The reviewer has made several valuable suggestions for enhancing the biological context and relevance of our study, particularly in relation to thrombopoietin (TPO), MPL signaling, and angiogenesis. We recognize the importance of these aspects in understanding MPL's multifaceted functions and potential implications for hematopoietic and vascular processes. In response to these suggestions, we madethe following amendments:

1. Explaining the Role of TPO in Angiogenesis: We included  a section in the manuscript (introduction part) to elucidate how TPO, through MPL signaling, also contributes to angiogenesis. This additional information will provide readers with a broader biological context for MPL's role as indicated in lines 55-76.
2. Highlighting MPL's Expression on Hematopoietic Stem/Progenitor Cells and Endothelial Cells: We  expand on the introduction to explain how TPO/MPL signaling impacts angiogenesis through its effects on both hematopoietic stem/progenitor cells and endothelial cells. This comprehensive view will enhance our readers' understanding of MPL's multifaceted functions.
3. Linking MPL Mutations to Angiogenesis and Vascular Development: We explored the potential implications of some MPL , JAK and CALR mutations discussed in our study on angiogenesis and vascular development as indicated in lines 583-598. Relating mutations to their effects on angiogenesis will help elucidate their broader roles beyond hematopoietic disorders.
4. Therapeutic Implications and Modulation of Angiogenesis: We discussed how gaining insights into the role of MPL/TPO signaling in angiogenesis could serve as inspiration for developing novel therapeutic strategies aimed at modulating angiogenesis.This discussion may provide avenues for therapeutic interventions in various medical conditions.
5. MPL/TPO Signaling in Cancer: We were unable to fulfill the reviewer's suggestion to investigate the connection between MPL/TPO signaling and oncogenesis due to a lack of available studies in this particular research area.

Additionally, we acknowledge the limitations highlighted by the reviewer and addressed them as follows:

Responses to Reviewer's Comments on Limitations:

1. Database Reliability: We acknowledge the importance of database reliability in our analysis. We have utilized widely recognized databases such as ENSEMBL, NCBI, and InterPro. However, as you rightly pointed out, our conclusions are based on the current versions of these databases at the time of our study. We recommend regular updates and cross-referencing with other data sources to maintain the relevancy of our findings.
2. PredictSNP Reliability: We concur with your observation. PredictSNP amalgamates results from various tools, each with its strengths and potential biases. In our study, we have tried to consider the collective outcome rather than being heavily reliant on a single tool to minimize this limitation.
3. Domain Identification: We recognize that while InterPro is an invaluable resource, it might not encompass all known protein motifs or domains. This is a limitation inherent to the current state of domain identification databases, and we have taken care to interpret our findings in this light.
4. Evolutionary Assumptions: We agree with your assessment. While evolutionary conservation often correlates with functional importance, there are exceptions. Our use of ConSurf was to provide an additional layer of analysis, and we have taken care not to overinterpret its findings.
5. Protein Stability Predictions: The potential for false positives and negatives in I-mutant 3.0 and MUpro is a valid concern. We have endeavored to combine these predictions with other tools and biological insights to mitigate these limitations.
6. STRING Database: Your point is well taken. STRING's predictions rely on existing knowledge, and proteins that are relatively new or less studied may have limited interaction data available. Our analysis serves as an initial screening tool, and we recommend conducting further functional assays to achieve a comprehensive understanding.
7. Non-coding SNP Analysis: We acknowledge the complexity surrounding the significance of SNPs in 5' and 3' UTR regions. While MAF is a factor, it is not the sole determinant. Our analysis serves as an initial screening tool, and we recommend further functional assays for a comprehensive understanding.
8. Project HOPE: We are in agreement with your comment. Homology models are indeed approximations based on known structures. We have used Project HOPE as a reference tool, and any definitive conclusions about protein structures should be derived from direct experimental evidence.
9. MutPred2 Limitations: Your observation is apt. While MutPred2 is a comprehensive tool, some mutations, especially those with subtle or complex effects, might escape its prediction capabilities. We've noted this limitation in our discussions.
10. CScape and CScape Somatic: We concur with the potential for false positives or negatives even with high accuracy tools. We have interpreted the results from CScape and CScape Somatic with caution and have cross-referenced them with other findings to provide a holistic view.

We appreciate the thorough review and the opportunity to address these limitations. Our study aims to provide insights based on the best available tools and databases, and we believe that acknowledging these limitations strengthens the integrity and transparency of our research.

 

Furthermore, we acknowledge the suggestions highlighted by the reviewer and have addressed them as follows:

Responses to Reviewer's Comments on Suggestions:

1. Database Cross-Validation: We appreciate this suggestion. Cross-validation among databases is indeed essential to enhance the reliability of our data. We considerd implementing this in our future analyses to further authenticate our findings.
2. Supplement PredictSNP: Your suggestion is valuable. Incorporating other prediction tools not included in PredictSNP's amalgamation can indeed provide a more comprehensive insight. We will explore the addition of these tools in our subsequent work.
3. Experimental Validation: We concur with the importance of experimentally validating computational predictions. While our current study is primarily computational, we aim to collaborate with experimental groups or utilize available experimental data in the future to validate key findings.
4. Consider Protein Interactions: You raise a valid point. Analyzing the potential implications of protein changes on interaction networks can offer deeper insights. We will incorporate this perspective in our future endeavors.
5. Dynamic Simulation: Molecular dynamics simulations can indeed provide valuable insights into the dynamic behavior of proteins. We will explore the feasibility of incorporating such simulations in our subsequent research to enhance our understanding of mutation effects.
6. Enrich Non-coding SNP Analysis: Thank you for highlighting this aspect. We recognize the importance of considering factors like local DNA structure and potential non-coding RNA interactions. In future studies, we will seek to integrate these factors into our non-coding SNP evaluations.
7. Functional Assays: We acknowledge the critical role of functional assays in understanding mutation effects. We will explore opportunities to incorporate these assays, especially for mutations that our computational tools predict to be of high impact.
8. Continuous Update: We couldn't agree more. The rapid advancements in genomics and proteomics necessitate the regular updating of methods and databases. We are committed to periodically revisiting and refining our tools and data sources to ensure they remain current.
9. Include Clinical Data: Incorporating clinical and phenotypic data is indeed beneficial for a comprehensive view of mutation implications. We will endeavor to integrate such data in our future analyses, either through collaborations or accessing available datasets.

We are grateful for the insightful suggestions provided. They will undoubtedly help refine our research approach, making our findings more robust and comprehensive. Your feedback is essential in driving the quality and relevance of our research forward.

In conclusion, we are committed to addressing these comments and suggestions to enhance the quality and relevance of our manuscript. We believe that these revisions will significantly strengthen our work and make it more informative and valuable to the scientific community. We kindly request that you re-evaluate our manuscript based on these revisions, and we look forward to your feedback.

Thank you once again for your consideration, and we appreciate the opportunity to improve our research for publication in the CIMB Journal.

Sincerely,

Hakeemah

Hakeemah Al-nakhle

Medical Laboratory Technology Department, College of Applied Medical Sciences,

Taibah University, Al-Madinah Al-Munawara, Saudi Arabia.

00966544440961

 [email protected]

 

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

My comments were addressed. 

Thanks

Comments on the Quality of English Language

The manuscript still contains numerous typos that require attention. 

Reviewer 3 Report

Comments and Suggestions for Authors

The authors have clarified several of the questions I raised in my previous review. Most of the major problems have been addressed by this revision.

Comments on the Quality of English Language

The authors have clarified several of the questions I raised in my previous review. Most of the major problems have been addressed by this revision.