Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The authors conducted a study to reveal the architecture of copy number variations in the Black Bengal goat genome by whole-genome resequencing data.

Studying the genome architecture of local breeds, which are generally well adapted to harsh climates, is an important task, so I believe this study is useful for improving our understanding of the features of the goat genome. I would like to recommend this manuscript for publication in International Journal of Molecular Sciences.

The authors have done a lot of work, but there are still some questions and comments:

1. Were the animals tested for relatedness? Randomly selected animals could have been related. This could have affected the results.
2. Is Figure 1 showing the total sum or the average number of CNVs per chromosome for all animals? Please indicate this in the note to the figure. Additionally, please label the chromosome numbers in Figure 1, as the numbering is not entirely clear. Based on the RefSeq numbers, the chromosomes appear to be arranged in ascending order, but the text states that "The highest CNV densities were observed on chromosomes 1, 2, 6, and 7." However, in the figure, the highest numbers are shown for chromosomes 1, 2, 3, and 4. Please clarify how to interpret this point.
3. Lines 181–187: "…two key reproductive genes—BMPR1B (12.42–12.48 Mb) and GDF9 (24.90–24.94 Mb)—were located within CNVR-enriched segments on chromosome 6. The prevalence of such large, shared duplications suggests selective retention of dosage-sensitive loci associated with folliculogenesis and ovulation rate, contributing to the exceptional prolificacy of the Black Bengal breed. The genes COL6A1 and COL6A3, which aid in the production of collagen, were also found on chromosome 2. LAMC2 and LAMB3 are found in another hotspot on chromosome 2 (22.4–22.5 Mb)…" These results are not evident from Figure 1 or Figure 2. Please add tables or figures that would allow the reader to understand these findings. For example, a table showing the localization of CNVR-enriched segments by chromosome would be helpful.
4. In the supplementary materials, a table could be added showing that gene annotation "...revealed 1,987 unique protein-coding genes overlapped with CNVs and CNVRs, many of which were enriched in multiple biological processes".
5. For Tables 2 and 3, please include the gene localization (chromosome and positions).
6. Lines 244–247:…COL6A1 and COL6A3 (66 kb; samples 786, 795, 796) were linked to the assembly of collagen fibrils, LAMC2 and LAMB3 (83 kb; samples 795, 797) linked to the anchoring of basement membranes, CLDN1 (58 kb; sample 796) contributing to the integrity of the epidermal barrier, and FMN1 (52 kb; sample 795)… The detection of these variants in only a single animal likely does not characterize the breed as a whole. Could you please provide phenotypic data for these animals or otherwise describe them? What might explain the observation that some animals carry CNVRs associated with certain genes, while others carry CNVRs associated with different genes?

Author Response

Author’s Response to Reviewer 1

We sincerely thank the reviewer for the careful evaluation of our manuscript and for the constructive comments. We have revised the manuscript accordingly and addressed all concerns as detailed below.

Comment 1

Were the animals tested for relatedness? Randomly selected animals could have been related. This could have affected the results.

Response:

We thank the reviewer for this important concern. In the present study, whole-genome sequencing (WGS) was performed on eight (n = 8) Black Bengal goats. The animals were carefully selected from unrelated households/farms to minimize the likelihood of close genetic relationships. In addition, we have now performed a genomic relatedness analysis using SNP data derived from the WGS dataset. Genomic relatedness (PI_HAT) estimates were low (<0.05), confirming that the sampled individuals are not closely related. This information has been incorporated into the Materials and Methods section

(Page 03, Lines 114-116) and Results section (Page 4, Lines 194-195).

 

Comment 2

Is Figure 1 showing the total sum or the average number of CNVs per chromosome for all animals? Please indicate this in the note to the figure. Additionally, please label the chromosome numbers in Figure 1, as the numbering is not entirely clear. Based on the RefSeq numbers, the chromosomes appear to be arranged in ascending order, but the text states that "The highest CNV densities were observed on chromosomes 1, 2, 6, and 7." However, in the figure, the highest numbers are shown for chromosomes 1, 2, 3, and 4. Please clarify how to interpret this point.

Response:
Thank you for your suggestion. We have revised Figure 1 and updated the legend to clearly indicate that the plot represents the total number of CNVs per chromosome across all animals, with chromosomes labeled using standard numbering (Chr1–Chr29). The figure has also been improved for clarity and consistency.

Furthermore, we have corrected the interpretation in the text to ensure alignment with the figure. Regarding the discrepancy, we confirm that the chromosomes are arranged in ascending order by RefSeq accession numbers; however, the statement in the text has been corrected. The revised text now accurately reflects the figure, indicating that chromosomes 1, 2, 3, and 4 exhibit the highest CNV counts rather than chromosomes 1, 2, 6, and 7.

(Page 04-05, Lines 206-208; 223-231).

 

Comment 3

Lines 181–187:
"…two key reproductive genes—BMPR1B (12.42–12.48 Mb) and GDF9 (24.90–24.94 Mb)—were located within CNVR-enriched segments on chromosome 6... LAMC2 and LAMB3 are found in another hotspot on chromosome 2 (22.4–22.5 Mb)…"
These results are not evident from Figure 1 or Figure 2. Please add tables or figures that would allow the reader to understand these findings. For example, a table showing the localization of CNVR-enriched segments by chromosome would be helpful.

Response:
Thank you for this important suggestion. We agree that the localization of CNVR-enriched regions and associated candidate genes was not sufficiently illustrated in the original figures. To address this, we have now added a new supplementary table S1 that summarizes the chromosomal positions of CNVR-enriched segments along with annotated genes.

This table was generated directly from the high-confidence CNV annotation datasets, and clearly shows the genomic coordinates and gene content of CNVR hotspots. Importantly, the regions containing BMPR1B and GDF9 on chromosome 6, as well as LAMC2 and LAMB3 on chromosome 2, are now explicitly listed with their corresponding coordinates, enabling direct verification of these findings.

In addition, we have revised the Results section (Lines 212–213) to include a cross-reference to this table, ensuring that readers can easily interpret and validate the reported CNVR-enriched regions and associated functional genes.

Comment 4

In the supplementary materials, a table could be added showing that gene annotation "...revealed 1,987 unique protein-coding genes overlapped with CNVs and CNVRs, many of which were enriched in multiple biological processes".

Response:
As suggested, we have included a new Supplementary Table (Table S2) that lists 9,157 unique protein-coding genes that overlap CNVs/CNVRs, along with their annotations and functional enrichment details.

(Page 06, Lines 251-253).

 

Comment 5

For Tables 2 and 3, please include the gene localization (chromosome and positions).

Response:
We agree with the reviewer. Tables 2 and 3 have been revised to include detailed gene localization information, including chromosome number and genomic coordinates.

Comment 6

Lines 244–247:
“…COL6A1 and COL6A3 (66 kb; samples 786, 795, 796) … FMN1 (52 kb; sample 795) …"
The detection of these variants in only a single animal likely does not characterize the breed as a whole. Could you please provide phenotypic data for these animals or otherwise describe them? What might explain the observation that some animals carry CNVRs associated with certain genes, while others carry CNVRs associated with different genes?

Response:
We thank the reviewer for this valuable suggestion. To address this concern, we have revised our analysis by applying a frequency-based filtering criterion and excluded CNVRs detected in only a single individual. We now focus on CNVRs present in multiple animals (≥2 individuals), which are more likely to represent population-level variation rather than rare or individual-specific events.

As a result, the number of candidate genes has been refined, and the updated tables now include genes supported by multiple samples. This improves the robustness of the findings and avoids overinterpretation of rare variants.

(Page 6,7 tables revised; Lines 301-303)

Reviewer 2 Report

Comments and Suggestions for Authors

This manuscript presents a genome-wide characterization of copy number variations (CNVs) and copy number variation regions (CNVRs) in the Black Bengal goat using whole-genome sequencing data. The study addresses an important topic in livestock genomics, as structural variations represent a major source of genetic diversity influencing adaptation, reproduction, and economically important traits.

The work provides potentially valuable genomic resources for indigenous goat breeds and contributes to understanding structural genomic architecture associated with prolificacy and skin quality. However, the manuscript in its current form requires major revision before it can be considered for publication.

The manuscript frequently attributes phenotypic traits (e.g., prolificacy and superior skin quality) directly to detected CNVs without functional validation. For example, duplications involving GDF9, BMPR1B, and ECM-related genes are interpreted as causal drivers of reproductive performance and dermal strength. However, the study provides only genomic association evidence. No phenotypic correlation analysis. Small sample size (n = 8). Explicit justification of sample size. Discussion of statistical limitations.

Authors should Clearly distinguish correlation vs causation.

The manuscript reports sequencing quality metrics but lacks Reference genome preprocessing steps.

No independent validation (e.g., qPCR or ddPCR) was performed. Given the reliance on read-depth methods at ~10× coverage, validation is strongly recommended.

The dataset is stated to be available only from the corresponding author. For reproducibility and journal standards, sequencing data should ideally be deposited in a public repository (e.g., NCBI SRA). Provide accession numbers.

CNV vs CNVs vs copy number variation inconsistent usage. “Genome sequencing” vs “whole-genome sequencing”. Typographical errors (“QIAGENiagen”).

 

Author Response

Response to Reviewer 2

We sincerely thank the reviewer for the detailed and constructive comments. We have carefully revised the manuscript and addressed each point below.

Comment:

This manuscript presents a genome-wide characterization of copy number variations (CNVs) and copy number variation regions (CNVRs) in the Black Bengal goat using whole-genome sequencing data. The study addresses an important topic in livestock genomics, as structural variations represent a major source of genetic diversity influencing adaptation, reproduction, and economically important traits.

Response:
We thank the reviewer for the positive evaluation and encouragement.

Comment:

The work provides potentially valuable genomic resources for indigenous goat breeds and contributes to understanding structural genomic architecture associated with prolificacy and skin quality. However, the manuscript in its current form requires major revision before it can be considered for publication.

Response:
We appreciate the reviewer’s constructive feedback and have substantially revised the manuscript to improve clarity, rigor, and interpretation of results.

Comment:

The manuscript frequently attributes phenotypic traits (e.g., prolificacy and superior skin quality) directly to detected CNVs without functional validation. For example, duplications involving GDF9, BMPR1B, and ECM-related genes are interpreted as causal drivers of reproductive performance and dermal strength. However, the study provides only genomic association evidence. No phenotypic correlation analysis. Small sample size (n = 8). Explicit justification of sample size. Discussion of statistical limitations. Authors should Clearly distinguish correlation vs causation.

 

Response:
We thank the reviewer for this important observation. We agree that our study provides association-based evidence rather than causal inference. Accordingly, we have revised the manuscript to clearly distinguish correlation from causation throughout the Results and Discussion sections.

Statements implying direct causality have been modified to indicate that the identified CNVs represent putative candidate regions that may influence traits such as prolificacy and skin quality. We now explicitly state that functional validation and genotype–phenotype association analyses are required to confirm these relationships.

Regarding the sample size (n = 8), we acknowledge this limitation and have added a justification in the revised manuscript. The study is designed as an exploratory genome-wide survey to identify candidate CNVRs in Black Bengal goats. We have also included a discussion of statistical limitations associated with small sample sizes on Page 12, in Section 4.9.

(Page 12 ; Lines 492-515)

Comment:

The manuscript reports sequencing quality metrics but lacks Reference genome pre-processing steps.

Response:
We thank the reviewer for this suggestion. The reference genome pre-processing steps have now been clearly described in the Materials and Methods section, including details on reference genome preparation, alignment, and quality control procedures.

(Page 3 ; Lines 103-125)

 

Comment:

No independent validation (e.g., qPCR or ddPCR) was performed. Given the reliance on read-depth methods at ~10× coverage, validation is strongly recommended.

Response:
We agree that experimental validation would strengthen the findings. However, due to resource limitations, independent validation (e.g., qPCR or ddPCR) could not be performed in the current study. This limitation has now been clearly acknowledged in the revised manuscript, and we emphasize that the identified CNVRs should be considered putative and require further validation in future studies.

(Page 12 ; Lines 492-515)

 

Comment:

The dataset is stated to be available only from the corresponding author. For reproducibility and journal standards, sequencing data should ideally be deposited in a public repository (e.g., NCBI SRA). Provide accession numbers.

Response:

We thank the reviewer for highlighting this important aspect of data availability and reproducibility. The sequencing data generated in this study are part of an ongoing Government of India–funded program under the National Livestock Mission (NLM) oproject, and therefore are subject to institutional and governmental data-sharing policies. At present, these datasets are considered restricted and cannot be deposited in a public repository such as NCBI SRA without prior approval from the concerned authorities. However, we fully recognize the importance of data accessibility and transparency. The data will be made available upon reasonable request to the corresponding author

Comment:

CNV vs CNVs vs copy number variation inconsistent usage. “Genome sequencing” vs “whole-genome sequencing”. Typographical errors (“QIAGENiagen”).

Response:
We appreciate the reviewer’s careful reading. The manuscript has been thoroughly revised to ensure:

• Consistent use of terminology (CNV, CNVs, CNVRs)
• Standardization of “whole-genome sequencing (WGS)”
• Correction of typographical errors, including “QIAGEN”

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

Dear authors

Thanks for addressing my comments. I have no more comments