MirtronStructDB: A Comprehensive Database of Mirtrons with Predicted Secondary Structures

Shumin Li; Franklin Wang-Ngai Chow; Lei Chen; Junhao Su; Syed Shakeel Ahmed; Ruibang Luo

doi:10.12688/f1000research.153905.1

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MirtronStructDB: A Comprehensive Database of Mirtrons with Predicted Secondary Structures

[version 1; peer review: 2 approved with reservations]

Shumin Li ¹, Franklin Wang-Ngai Chow², Lei Chen¹, Junhao Su¹, Syed Shakeel Ahmed¹, Ruibang Luo ¹

Shumin Li ¹, Franklin Wang-Ngai Chow², [...] Lei Chen¹, Junhao Su¹, Syed Shakeel Ahmed¹, Ruibang Luo ¹

PUBLISHED 06 Aug 2024

Author details Author details

¹ Computer Science, The University of Hong Kong, Hong Kong, Hong Kong
² Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, Hong Kong

Shumin Li
Roles: Formal Analysis, Validation, Writing – Original Draft Preparation

Franklin Wang-Ngai Chow
Roles: Resources, Supervision

Lei Chen
Roles: Software, Validation

Junhao Su
Roles: Software, Validation

Syed Shakeel Ahmed
Roles: Investigation, Resources

Ruibang Luo
Roles: Conceptualization, Software, Supervision, Validation, Writing – Original Draft Preparation, Writing – Review & Editing

OPEN PEER REVIEW

REVIEWER STATUS

Abstract

Motivation

Mirtrons, a vital category of non-canonical microRNAs (miRNAs) originating from exon-intron boundaries through splicing mechanisms, play crucial roles in cellular processes. However, existing databases lack the latest data and structural information, hindering understandings of mirtron formation and functions.

Results

We introduce MirtronStructDB, an online database addressing these gaps by incorporating over 350 novel mirtrons. Significantly, it provides corresponding predicted RNA secondary structures, offering a deeper understanding of the functional roles and mechanisms of all mirtrons. This enhances previous repositories, offering a total of 4,209 mirtron records spanning 25 species from 46 publications. Our database contributes for unraveling patterns and functions in mirtrons across species and diverse structural features. MirtronStructDB allows users to freely browse, search, visualize, and download data via a user-friendly interface.

Availability

MirtronStructDB is accessible at: http://www.bio8.cs.hku.hk/msdb/.

Contact

lishumin@connect.hku.hk, rbluo@cs.hku.hk

Keywords

Mirtron, Secondary Structure

Corresponding authors: Shumin Li, Ruibang Luo

Competing interests: No competing interests were disclosed.

Grant information: Hong Kong Research Grants Council
GRF (17113721), TRS (T21- 705/20-N),Shenzhen Municipal Government General Program
JCYJ20210324134405015,The University of Hong Kong
URC fund
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Copyright: © 2024 Li S et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to cite: Li S, Chow FWN, Chen L et al. MirtronStructDB: A Comprehensive Database of Mirtrons with Predicted Secondary Structures [version 1; peer review: 2 approved with reservations]. F1000Research 2024, 13:899 (https://doi.org/10.12688/f1000research.153905.1) First published: 06 Aug 2024, 13:899 (https://doi.org/10.12688/f1000research.153905.1) Latest published: 06 Aug 2024, 13:899 (https://doi.org/10.12688/f1000research.153905.1)

Introduction

Mirtrons are a vital category of non-canonical microRNAs (miRNAs). MicroRNAs represent a crucial class of small RNAs that play significant roles in various post-transcriptional cellular processes.¹ Conventionally, miRNAs are processed from longer primary transcripts, known as pri-miRNAs, via sequential enzymatic cleavage steps involving the Drosha or Dicer proteins. However, a distinct class of miRNAs, termed mirtrons, have been identified that they follow an alternative processing pathway. Mirtrons originate from exon-intron boundaries through splicing and are independent of Drosha or Dicer cleavage. The initial detection of mirtrons occurred in D. melanogaster and C. elegans² and subsequent studies confirmed their presence in mammals,³ plants,⁴ and viruses.⁵ Notably, mirtrons have demonstrated involvement in diverse biological processes, including cell development and cancer.⁶ To facilitate the exploration of mirtrons, an organized database, MirtronDB, was launched in 2019, collecting 3,833 precursors or mature mirtrons across 18 species.⁷ However, MirtronDB is limited by the absence of the latest data and, more significantly, structural information—a critical factor in miRNA maturation and distinguishing canonical and non-canonical miRNAs.⁸

To address these limitations, we present MirtronStructDB, an updated database that offers corresponding secondary structures of all mirtrons, along with an addition of over 350 novel mirtrons that are currently unavailable in existing databases. Furthermore, our user-friendly web interface provides browsing, searching, visualization, and downloading of all stored data. Through timely updates and comprehensive structural information, MirtronStructDB aims to contribute to the advancement of mirtron research and facilitate investigations into their functional roles and mechanisms. MirtronStructDB is publicly accessible at: http://www.bio8.cs.hku.hk/msdb/.

Methods

Implementation

Data collection and processing

MirtronStructDB was constructed through a two-fold data collection strategy (Figure 1A). Initially, we obtained the data from mirtronDB⁷ by downloading their available information as a primary source. Subsequently, we conducted a comprehensive literature search using the term ‘mirtron OR mirtrons’ from PubMed to collect additional publications related to mirtron discoveries. All the collected data underwent a standardization process and was integrated into MirtronStructDB. In cases where certain fields were missing from the original papers, temporarily placeholders (‘tbu’ indicating ‘to be updated’) were employed. To augment the database and investigate the functions and mechanisms of diverse mirtrons, we predicted the RNA secondary structures for all the collected data with sequence information. This prediction was performed through the RNAstructure Web Server with default parameters.⁹

Figure 1. Data collection and web interface of MirtronStructDB.

A) Workflow of data collection and preprocessing. B) Main modules of MirtronStructDB: search and filter, browse by species, demonstration and download.

In summary, MirtronStructDB offers a comprehensive dataset comprising 1,569 precursors and 2,640 mature mirtrons spanning 25 species, sourced from 46 publications. Of these, 163 precursors and 223 mature mirtrons were first documented in a dedicated mirtron database. And 9 species were first collected and reported in MirtronStructDB. In addition, a total of 12,555 RNA secondary structures were predicted for better understandings of the functional roles and mechanisms of mirtrons. Detailed information was provided in Data availability statement.

Web application implementation

The online web server was developed with the Flask web framework (v1.1.4) (https://github.com/pallets/flask) as the backend. It is deployed on an Ubuntu Linux server equipped with 48 Intel Xeon CPUs and 189GB of memory. All data is stored in a SQLite database, managed by the SQLAlchemy toolkit (v2.5.1) (https://www.sqlalchemy.org/).

The frontend of MirtronStructDB with a user-friendly design, crafted using Bootstrap (v3) (https://getbootstrap.com/) and adminLTE (v2.4.18) (https://github.com/ColorlibHQ/AdminLTE), and dynamically generated through the JINJA2 templating engine (v2.11.3) (https://jinja.palletsprojects.com/en/3.1.x/templates/). The web service is hosted by Apache2 and Gunicore modules, guaranteeing high performance and stability.

Operation

MirtronStructDB is available to the community through its web-based interface and is freely available. It can also be run locally with a typically 2GB RAM and a dual-core CPU. It is compatible with popular web browsers, including Microsoft Edge, Google Chrome, Firefox and Safari.

The web portal has three primary modules: search and filter, browse by species, and demonstration and download. The overview is shown in Figure 1B. Users can either start with search and filter or browse by species to get the mirtron list and then select individual mirtrons to view their details. Usages listed below:

Search and filter: To facilitate the use of MirtronStructDB, a search and filter can be performed through clicking the ‘Search’ button from the top navigation bar. Users can type the IDs of mirBase, host gene symbols, DOIs or keywords of papers in the search box to retrieve all relevant mirtrons. Additionally, users can apply filters based on preferred species and sources to customize their search results.

Browse by species: We also provide a gallery page which categorizing mirtrons by species. Users can access it through clicking ‘Browse’ button of the navigation bar. Mirtron summaries for each species are presented, and users can explore detailed information by clicking on individual species.

Demonstration and download: Individual mirtrons can be accessed through the mirtron detail page. Two sections were shown: The first section includes basic information including the species, corresponding precursors or mature mirtrons, sequences, strand, chromosome position, source papers, etc. The second section displays predicted secondary structures. Users are flexible to explore and download data based on their own needs.

Discussion

MirtronStructDB is a comprehensive database with an extensive collection of over 350 novel mirtrons accompanied by their predicted secondary structures. This database not only presents an updated catalog of mirtrons across diverse species but also provide structural insights into the entire spectrum of mirtrons. MirtronStructDB make it feasible for experimental biologists seeking identification of relevant mirtrons for distinct species, sources, or specific research requirements. Furthermore, MirtronStructDB offers computational biologists an opportunity to delve into its rich information, particularly the sequence contexts and structural features it provides. With the accumulated data of mirtronStructDB, we anticipate the emergence of novel computational methods to expedite the prediction and identification of mirtrons across a broader spectrum of species. This advancement is expected to deepen our understanding of the unique formation mechanisms and functions of mirtrons.

Ethics and consent

Ethical approval and consent were not required.

Author contributions

R. L. And S. L. conceived the study. S. L. designed the web interface and the analyses. F. W. C., L. C., J. S., and S. S. A. evaluated the analysis results. All authored drafted and approved the manuscript.

Data availability

Zenodo: Source data of Mirtronstructdb - A comprehensive database of mirtrons with predicted secondary structure. https://zenodo.org/doi/10.5281/zenodo.13118506.¹⁰

The project contains the following underlying data:

- msdb_data.csv (the mirtron collection table, including the following columns: Unique ID, mirtron name, type, species, hairpin arm, sequence, chromosome, start, end, strand, host gene, 3p-arm mature miRNAs, 5p-arm mature miRNAs, precursor name, data source, PMID, paper title, DOI, other information).
- msdb_structures.tar.gz (the SVG images of the predicted secondary structures based on the mirtron sequences).

Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).

Software availability

Database available from: http://www.bio8.cs.hku.hk/msdb/ Source code available from: https://github.com/HKU-BAL/msdb-flask/.

Archived software available from https://zenodo.org/doi/10.5281/zenodo.13118891.¹¹

License: MIT

References

1. Bartel DP: MicroRNAs: genomics, biogenesis, mechanism, and function. Cell. 2004; 116(2): 281–297. Publisher Full Text
2. Ruby JG, Jan CH, Bartel DP: Intronic microRNA precursors that bypass Drosha processing. Nature. 2007; 448(7149): 83–86. PubMed Abstract | Publisher Full Text | Free Full Text
3. Berezikov E, Chung WJ, Willis J, et al.: Mammalian mirtron genes. Mol. Cell. 2007; 28(2): 328–336. PubMed Abstract | Publisher Full Text | Free Full Text
4. Zhu QH, Spriggs A, Matthew L, et al.: A diverse set of microRNAs and microRNA-like small RNAs in developing rice grains. Genome Res. 2008; 18(9): 1456–1465. PubMed Abstract | Publisher Full Text | Free Full Text
5. Rasschaert P, Figueroa T, Dambrine G, et al.: Alternative splicing of a viral mirtron differentially affects the expression of other microRNAs from its cluster and of the host transcript. RNA Biol. 2016; 13(12): 1310–1322. PubMed Abstract | Publisher Full Text | Free Full Text
6. Salim U, Kumar A, Kulshreshtha R, et al.: Biogenesis, characterization, and functions of mirtrons. Wiley Interdiscip. Rev. RNA. 2022; 13(1): e1680. PubMed Abstract | Publisher Full Text
7. Da Fonseca BHR, Domingues DS, Paschoal AR: mirtronDB: a mirtron knowledge base. Bioinformatics. 2019; 35(19): 3873–3874. PubMed Abstract | Publisher Full Text | Free Full Text
8. Titov II, Vorozheykin PS: Comparing miRNA structure of mirtrons and non-mirtrons. BMC Genomics. 2018; 19(3): 114. PubMed Abstract | Publisher Full Text | Free Full Text
9. Reuter JS, Mathews DH: RNAstructure: software for RNA secondary structure prediction and analysis. BMC Bioinformatics. 2010; 11(1): 129. PubMed Abstract | Publisher Full Text | Free Full Text
10. Li S, Chow F, Chen L, et al.: Source data of Mirtronstructdb - A comprehensive database of mirtrons with predicted secondary structure. Zenodo. 2024. Publisher Full Text
11. Li S, Chow F, Chen L, et al.: Source code of Mirtronstructdb - A comprehensive database of mirtrons with predicted secondary structure. Zenodo. 2024. Publisher Full Text

Comments on this article Comments (0)

Version 1

VERSION 1 PUBLISHED 06 Aug 2024

Author details Author details

¹ Computer Science, The University of Hong Kong, Hong Kong, Hong Kong
² Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, Hong Kong

Shumin Li
Roles: Formal Analysis, Validation, Writing – Original Draft Preparation

Franklin Wang-Ngai Chow
Roles: Resources, Supervision

Lei Chen
Roles: Software, Validation

Junhao Su
Roles: Software, Validation

Syed Shakeel Ahmed
Roles: Investigation, Resources

Ruibang Luo
Roles: Conceptualization, Software, Supervision, Validation, Writing – Original Draft Preparation, Writing – Review & Editing

Competing interests

No competing interests were disclosed.

Grant information

Hong Kong Research Grants Council
GRF (17113721), TRS (T21- 705/20-N),Shenzhen Municipal Government General Program
JCYJ20210324134405015,The University of Hong Kong
URC fund
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Article Versions (1)

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Published: 06 Aug 2024, 13:899

https://doi.org/10.12688/f1000research.153905.1

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© 2024 Li S et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Li S, Chow FWN, Chen L et al. MirtronStructDB: A Comprehensive Database of Mirtrons with Predicted Secondary Structures [version 1; peer review: 2 approved with reservations]. F1000Research 2024, 13:899 (https://doi.org/10.12688/f1000research.153905.1)

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Reviewer Report 19 Sep 2024

Lachlan Coin, The University of Melbourne, Melbourne, Victoria, Australia

Approved with Reservations

https://doi.org/10.5256/f1000research.168861.r312746

Shunmin Li and co-authors have developed a database for Mirton structures, which looks like a useful resource for the community. Mirtons are an important subclass of micro-RNA and new resources for exploring their role in biology and medicine are valuable.
... Continue reading

Shunmin Li and co-authors have developed a database for Mirton structures, which looks like a useful resource for the community. Mirtons are an important subclass of micro-RNA and new resources for exploring their role in biology and medicine are valuable.

The database is at first glance, quite similar to http://mirtrondb.cp.utfpr.edu.br/index.php, which is where the authors have obtained the bulk of the data for MirtonstructDB. The main novelty of MirtonStructDB is that it has calculated RNA secondary structure for Mirtons in the database, which are shown when the user looks at a specific Mirton page. Additionally the authors point out the MirtonDB has not been updated for some years and they increase the number of species annotated, and identify new Mirtons via a literature search. The authors say that MirtonStructDB will continue to be updated, but its not clear to me that this will not run into the same problem , and there is not a clear plan to ensure the database is up to date.

I have some suggestions to improve this paper, and also the utility of the database

1. Could the authors describe the quality control processes to ensure that Mirtons reported in the literature satisfy the criteria to be classified as Mirtons. What other quality control / verification processes are in place.
2. The authors describe a standardization process before integration into MirtonStructDB, could they describe this?
3. Have any de-duplication processes been carried out on the data
4. Could the authors provide the reference genome used for each of the species.
5. can the authors better describe the procedure to keep this database up-to-date
6. I felt that there were some important details about Mirtons which could have been explained better. For example, in the introduction, the authors mention canonical vs non-canonical .. what does this mean? Also why is secondary structure important in this distinction. Can canonical vs non canonical be indicated in the record, as well as the evidence supporting this?
7. Since the main novelty of this database is the secondary structure, it would be good to be able to download this information across all entries in a machine readable form, in order to enable AI/ML applications (rather than just access the image through each entry). There are a number of formats for representing this, such as dot bracket notation, or washington university notation.
8. Can the authors provide some stats on the reliability of the entries they provide .e.g how many false positive entries are there

Is the rationale for developing the new software tool clearly explained?

Yes
Is the description of the software tool technically sound?

No
Are sufficient details of the code, methods and analysis (if applicable) provided to allow replication of the software development and its use by others?

No
Is sufficient information provided to allow interpretation of the expected output datasets and any results generated using the tool?

Partly
Are the conclusions about the tool and its performance adequately supported by the findings presented in the article?

Partly

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Bioinformatics, genomics and transcriptomics

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

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19

Reviewer Report 21 Aug 2024

Panos Kakoulidis, National and Kapodistrian University of Athens, Athens, Greece

Approved with Reservations

https://doi.org/10.5256/f1000research.168861.r312748

The authors have created an up-to-date online database that hosts data about mirtrons. The dataset of the database is an extension of a previously published database. The user can browse the data by species. Alternatively, the user can search for ... Continue reading

The authors have created an up-to-date online database that hosts data about mirtrons. The dataset of the database is an extension of a previously published database. The user can browse the data by species. Alternatively, the user can search for a particular entry by entering keywords (Gene Symbol or miRBase ID) and filtering results by species or source publication. Each entry displays sequence information and includes figures of alternative RNA secondary structure predictions, deriving from the established RNAStructure package. The data are available for download in CSV format. The source code of the website is available on GitHub.

I believe that this is a valuable resource which will aid the research of mirtrons. The website is user-friendly with a clean design and effectively guides the user to the sought information. The information can be exported to a user-friendly format with appropriate headers. This is a resource that I would personally use.

My concerns/suggestions are stated below:

1) RNA structure data

a) I think that the text should include the rationale behind selecting RNAStructure for this task. Since RNA structure is a central aspect of this work (the database is named 'MirtronStructDB'), I would expect more details and insights to be provided about the procedure, its limitations and the data produced.

b) It would be very helpful to include the CT outputs from RNAStructure in your database in addition to the figures. Ideally, a new field in the data could be dedicated to the predicted secondary structure in dot-bracket notation based on the CT outputs.

c) During last years, there has been progress on RNA 3D structure prediction and I would suggest you to consider including 3D structures in your data. Mirtrons are short sequences without the intricacies of e.g. rRNA, therefore it should be feasible in terms of resources and accuracy to produce such structural 3D models.

2) Web page

a) Input checking:

When selecting species (e.g. Homo Sapiens) and source (Discovery of hundreds of mirtrons in mouse and human small RNA data) the system either returns an internal error message or zero results if the user has not entered anything in the search field. I would suggest either freezing the submission button or returning all results from the selected source (the latter might be more useful).

b) Are there any tailed mirtrons in the data? It would be interesting to have a distinction between mirtron types if it is possible, such as conventional and tailed mirtrons

c) Please consider adding a note in the UI explaining the 'to be updated' ('tbu') abbreviation in the data. Alternatively, you could just hide the abbreviation for less noise on what the user is seeing.

d) I noticed that the hsa-mirtron-1230 entry of the examples is missing a MaxExpect figure. Also, the ptr-mir-1226 entry includes two Fold Structure figures, however the RNAStructure web server outputs a single one. Maybe you should double-check these cases, if this output shown is not the intended one.

Overall, I believe this work will be helpful to the community and promote the research on this topic. The modern and simple design of the website offers increased accessibility to the presented information and with minimal polishing of the code, the usability will reach its intended maximum. However, I would expect from an RNA structure database to offer structural information in more data forms than the ones that are currently provided. I look forward to seeing updates on this work.

Is the rationale for developing the new software tool clearly explained?

Partly
Is the description of the software tool technically sound?

Yes
Are sufficient details of the code, methods and analysis (if applicable) provided to allow replication of the software development and its use by others?

Yes
Is sufficient information provided to allow interpretation of the expected output datasets and any results generated using the tool?

Partly
Are the conclusions about the tool and its performance adequately supported by the findings presented in the article?

Yes

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Structural Bioinformatics, RNAi

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

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Panos Kakoulidis, National and Kapodistrian University of Athens, Athens, Greece
Lachlan Coin, The University of Melbourne, Melbourne, Australia

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19 Sep 2024 | for Version 1

Lachlan Coin, The University of Melbourne, Melbourne, Victoria, Australia

7 Views Cite this report Responses(0)

Approved With Reservations

Shunmin Li and co-authors have developed a database for Mirton structures, which looks like a useful resource for the community. Mirtons are an important subclass of micro-RNA and new resources for exploring their role in biology and medicine are valuable.

The database is at first glance, quite similar to http://mirtrondb.cp.utfpr.edu.br/index.php, which is where the authors have obtained the bulk of the data for MirtonstructDB. The main novelty of MirtonStructDB is that it has calculated RNA secondary structure for Mirtons in the database, which are shown when the user looks at a specific Mirton page. Additionally the authors point out the MirtonDB has not been updated for some years and they increase the number of species annotated, and identify new Mirtons via a literature search. The authors say that MirtonStructDB will continue to be updated, but its not clear to me that this will not run into the same problem , and there is not a clear plan to ensure the database is up to date.

I have some suggestions to improve this paper, and also the utility of the database

1. Could the authors describe the quality control processes to ensure that Mirtons reported in the literature satisfy the criteria to be classified as Mirtons. What other quality control / verification processes are in place.
2. The authors describe a standardization process before integration into MirtonStructDB, could they describe this?
3. Have any de-duplication processes been carried out on the data
4. Could the authors provide the reference genome used for each of the species.
5. can the authors better describe the procedure to keep this database up-to-date
6. I felt that there were some important details about Mirtons which could have been explained better. For example, in the introduction, the authors mention canonical vs non-canonical .. what does this mean? Also why is secondary structure important in this distinction. Can canonical vs non canonical be indicated in the record, as well as the evidence supporting this?
7. Since the main novelty of this database is the secondary structure, it would be good to be able to download this information across all entries in a machine readable form, in order to enable AI/ML applications (rather than just access the image through each entry). There are a number of formats for representing this, such as dot bracket notation, or washington university notation.
8. Can the authors provide some stats on the reliability of the entries they provide .e.g how many false positive entries are there

Is the rationale for developing the new software tool clearly explained?

Yes
Is the description of the software tool technically sound?

No
Are sufficient details of the code, methods and analysis (if applicable) provided to allow replication of the software development and its use by others?

No
Is sufficient information provided to allow interpretation of the expected output datasets and any results generated using the tool?

Partly
Are the conclusions about the tool and its performance adequately supported by the findings presented in the article?

Partly

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Bioinformatics, genomics and transcriptomics

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

Respond to this report

Responses (0)

Back to all reports

Reviewer Report

19 Views

21 Aug 2024 | for Version 1

Panos Kakoulidis, National and Kapodistrian University of Athens, Athens, Greece

19 Views Cite this report Responses(0)

Approved With Reservations

The authors have created an up-to-date online database that hosts data about mirtrons. The dataset of the database is an extension of a previously published database. The user can browse the data by species. Alternatively, the user can search for a particular entry by entering keywords (Gene Symbol or miRBase ID) and filtering results by species or source publication. Each entry displays sequence information and includes figures of alternative RNA secondary structure predictions, deriving from the established RNAStructure package. The data are available for download in CSV format. The source code of the website is available on GitHub.

I believe that this is a valuable resource which will aid the research of mirtrons. The website is user-friendly with a clean design and effectively guides the user to the sought information. The information can be exported to a user-friendly format with appropriate headers. This is a resource that I would personally use.

My concerns/suggestions are stated below:

1) RNA structure data

a) I think that the text should include the rationale behind selecting RNAStructure for this task. Since RNA structure is a central aspect of this work (the database is named 'MirtronStructDB'), I would expect more details and insights to be provided about the procedure, its limitations and the data produced.

b) It would be very helpful to include the CT outputs from RNAStructure in your database in addition to the figures. Ideally, a new field in the data could be dedicated to the predicted secondary structure in dot-bracket notation based on the CT outputs.

c) During last years, there has been progress on RNA 3D structure prediction and I would suggest you to consider including 3D structures in your data. Mirtrons are short sequences without the intricacies of e.g. rRNA, therefore it should be feasible in terms of resources and accuracy to produce such structural 3D models.

2) Web page

a) Input checking:

When selecting species (e.g. Homo Sapiens) and source (Discovery of hundreds of mirtrons in mouse and human small RNA data) the system either returns an internal error message or zero results if the user has not entered anything in the search field. I would suggest either freezing the submission button or returning all results from the selected source (the latter might be more useful).

b) Are there any tailed mirtrons in the data? It would be interesting to have a distinction between mirtron types if it is possible, such as conventional and tailed mirtrons

c) Please consider adding a note in the UI explaining the 'to be updated' ('tbu') abbreviation in the data. Alternatively, you could just hide the abbreviation for less noise on what the user is seeing.

d) I noticed that the hsa-mirtron-1230 entry of the examples is missing a MaxExpect figure. Also, the ptr-mir-1226 entry includes two Fold Structure figures, however the RNAStructure web server outputs a single one. Maybe you should double-check these cases, if this output shown is not the intended one.

Overall, I believe this work will be helpful to the community and promote the research on this topic. The modern and simple design of the website offers increased accessibility to the presented information and with minimal polishing of the code, the usability will reach its intended maximum. However, I would expect from an RNA structure database to offer structural information in more data forms than the ones that are currently provided. I look forward to seeing updates on this work.

Is the rationale for developing the new software tool clearly explained?

Partly
Is the description of the software tool technically sound?

Yes
Are sufficient details of the code, methods and analysis (if applicable) provided to allow replication of the software development and its use by others?

Yes
Is sufficient information provided to allow interpretation of the expected output datasets and any results generated using the tool?

Partly
Are the conclusions about the tool and its performance adequately supported by the findings presented in the article?

Yes

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Structural Bioinformatics, RNAi

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

Respond to this report

Responses (0)

[1] 1. Bartel DP: MicroRNAs: genomics, biogenesis, mechanism, and function. Cell. 2004; 116(2): 281–297. Publisher Full Text

[2] 2. Ruby JG, Jan CH, Bartel DP: Intronic microRNA precursors that bypass Drosha processing. Nature. 2007; 448(7149): 83–86. PubMed Abstract | Publisher Full Text | Free Full Text

[3] 3. Berezikov E, Chung WJ, Willis J, et al.: Mammalian mirtron genes. Mol. Cell. 2007; 28(2): 328–336. PubMed Abstract | Publisher Full Text | Free Full Text

[4] 4. Zhu QH, Spriggs A, Matthew L, et al.: A diverse set of microRNAs and microRNA-like small RNAs in developing rice grains. Genome Res. 2008; 18(9): 1456–1465. PubMed Abstract | Publisher Full Text | Free Full Text

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MirtronStructDB: A Comprehensive Database of Mirtrons with Predicted Secondary Structures

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Figure 1. Data collection and web interface of MirtronStructDB.

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