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Peer-Review Record

Identification of Specific Pathogen-Infected sRNA-Mediated Interactions between Turnip Yellows Virus and Arabidopsis thaliana

Curr. Issues Mol. Biol. 2023, 45(1), 212-222; https://doi.org/10.3390/cimb45010016
by Ruiyang Yu, Xinghuo Ye *, Chenghua Zhang, Hailong Hu, Yanlei Kang and Zhong Li *
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Curr. Issues Mol. Biol. 2023, 45(1), 212-222; https://doi.org/10.3390/cimb45010016
Submission received: 22 November 2022 / Revised: 13 December 2022 / Accepted: 28 December 2022 / Published: 30 December 2022
(This article belongs to the Section Molecular Plant Sciences)

Round 1

Reviewer 1 Report

Comments:

In this article entitled “Identification of specific pathogen-infected sRNA-mediated interactions between turnip yellows virus and Arabidopsis thaliana” authors have attempted to identify and characterize the sRNA of TuYV in A. thaliana. Authors have analysed the sRNA profile and identified 247 sRNA originating from TuYV genome and targets different pathways in A thaliana. Any kind of gene expression data should be validated by other approaches such quantities real time PCR, etc. however, authors have not validated any gene expression data. Also, significance of findings from this study is not highlighted.

Specific comments:

Line 10: Replace “Turnip Yellows Virus” with “Turnip yellow virus” here and throughout the ms.

Line 11: “…….cause diseases such as yellowing and curling of leaves and root chlorosis”. Yellowing, curling, and chlorosis are symptoms not disease. Rephrase it.

Line 207: “Samples were obtained from Arabidopsis wild plants before infection and 16 days after infection by the TuYV virus.”

How many samples were used for each treatment?

Why samples were collected at 16 dpi, why not any early dpi?

Author Response

Please see the attachment

Author Response File: Author Response.pdf

Reviewer 2 Report

Ruiyang Yu and coworkers presented here a manuscript entitled „Identification of specific pathogen-infected sRNA-mediated interactions between turnip yellows virus and Arabidopsis thaliana“.

The manuscript deals with a machine learning applied to the sequencing data from siRNA analysis of the pathosystem turnip yellows virus – Arabidopsis thaliana.

The manuscript brings important results and also new questions on understanding the process of virus infection processes in plants.

However, the manuscript must be improved before publication.

There are seriously misleading sentences:

 Page 1, lines 33-35. The sentence „Other plants can significantly benefit from the regulatory mechanisms it develops in response to challenges such as viruses“ cannot be true, as other plants have their own regulatory mechanisms, they are not developed by A. thaliana.

 Page 2, lines 48-50. The sentence „One of the two sRNAs then forms RISCs (RNA-induced silencing complexes), which inhibit protein synthesis.“ trying to shorten the text leads to a bias of the information - the effect of RISC is on the RNA level, which must be mentioned here.

 Put „for example“ before sentences in page 2, lines 52-56.

 Page 2, lines 58-60. The sentence „Based on the above findings, it is safe to infer that sRNAs generated by TuYV infection in Arabidopsis may have cross-kingdom regulatory roles.“ cannot be true, as the mentioned findings give no support for the statement.

 Page 2, line 69. „...to provide a small idea.“ please explain

 Page 2, line 78: „Furthermore, the cross-kingdom regulatory role of sRNAs...“ „Cross-kingdom“ again. Where is other kingdom then plants? This mechanism is only in plant kingdom, there is no cross-kingdom influence.

 Page 10, line 334: „This study explored the cross-kingdom regulation..“. Cross-kingdom again. There are only plants here, see also my comment above.

 

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

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