InsectOR—Webserver for sensitive identification of insect olfactory receptor genes from non-model genomes

Snehal Dilip Karpe; Vikas Tiwari; Sowdhamini Ramanathan

doi:10.1371/journal.pone.0245324

Peer Review History

Original SubmissionMay 3, 2020
9 Sep 2020 Decision Letter - Alexie Papanicolaou, Editor PONE-D-20-12954 InsectOR - webserver for sensitive identification of insect olfactory receptor genes from non-model genomes PLOS ONE Dear Dr. Sowdhamini, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Please read through the comments of the two referees but also include the following two additions: - Address the issues of false positives, as explained by reviewer 1. Take attention on your response as this will ensure that your tool is used and the paper is read and cited. - Include a case study of a species that has not been studied before to show how can this software be used - Explain whether the software can be downloaded and used off-line by bioinformaticians and whether the code is open source. If not, then you may wish to consider to do that as it is unlikely the community will use something they cannot validate themselves. Please submit your revised manuscript by Oct 24 2020 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. Please include the following items when submitting your revised manuscript: A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'. An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'. If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter. If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols We look forward to receiving your revised manuscript. Kind regards, Alexie Papanicolaou, PhD Academic Editor PLOS ONE Journal Requirements: When submitting your revision, we need you to address these additional requirements. 1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf 2. Thank you for stating the following financial disclosure: "The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript." At this time, please address the following queries: Please clarify the sources of funding (financial or material support) for your study. List the grants or organizations that supported your study, including funding received from your institution. State what role the funders took in the study. If the funders had no role in your study, please state: “The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.” If any authors received a salary from any of your funders, please state which authors and which funders. If you did not receive any funding for this study, please state: “The authors received no specific funding for this work.” Please include your amended statements within your cover letter; we will change the online submission form on your behalf. [Note: HTML markup is below. Please do not edit.] Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Yes Reviewer #2: Yes ******** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: Yes ****** 3. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes Reviewer #2: Yes ****** 4. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes Reviewer #2: Yes ****** 5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: The authors have created a web tool for semi-automatic identification and annotation of insect Odorant Receptor genes from uncharacterized genomic sequences. This tool would be useful for biologists that lack the bioinfomartics background to perform these queries manually (this reviewer’s perspective). The tool would allow for relatively quick surveys of important olfactory genes in non-model species. These data could complement other types of investigations: behavioral, ecological, etc. A bioinformaticist is needed to validate all methodology (for instance the parameters used for the MAKER comparison, line 226), but the techniques appear well intentioned and designed. The rationale for each case study species makes sense, though I had hoped a completely unstudied species was used for case study #2 to demonstrate the potential power of this web tool. Main Comments: Perhaps the abstract should end with a statement reminding readers of this tool’s value to researchers. The paper does not fully address this web tool’s false positive rate of discovery. Several of the trials run in tables S1-S4 show too many gene hits as compared to what has currently been uncovered. It could be that these hits are undiscovered ORs, but it is likely some or most of these extra hits are false positives. A section needs to be added to the methods that describes how precision and sensitivity were measured, giving more details. The conclusion needs to discuss how to determine false positives in the output files. Line 234 – Be more specific as to how insectOR performed “better.” Line 242 – it would be helpful to include a file listing the 727 non-drosophila ORs used in this step Table 1 – I did not notice a thorough explanation of how “sensitivity” and “precision” were calculated in the case study. The accompanying text is somewhat vague. Line 291 – rather than referencing the 2017 paper, it would be helpful to include a file listing the 1249 ORs used in this step, or at least a brief explanation of how these were chosen Line 307 – change “five other genomes” to “four other genomes” Small corrections by line number: 16 – delete “Hence” 19 – change “sever” to “server” in abstract 39 – remove capital in “Olfaction” 48 – “is” to “are” 56 – delete “only” 285 – change “missed” to “failed” 321-reword? Reviewer #2: The manuscript by Karpe et al. develops a webserver – InsectOR serving as the prediction of gene models of insect ORs. This is a significant work for the preliminary identification of OR genes. This manuscript was well written and easy to be followed. However, I am not an expert in the field of bioinformatics. For the manuscript, I mainly concerned two issues: 1. Insect ORs are a diverse family with some genes exhibiting extremely low identities at the amino acid levels. As I know, some of ORs in one species have no orthologs to ORs from other species. This is difficult for the researchers to identify the exact number or full-length sequences of OR genes. Whether the authors have considered the parameter set of this webserver on low identities or no orthologs of ORs? 2. If one gene was located on two scaffolds or contigs, this webserver enables them merge into one gene? 3. Using ‘InsectOR’, this number of genes is relatively precise. I would like to know whether it will give more full-length sequences? ****** 6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review?** For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No Reviewer #2: No [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step. https://doi.org/10.1371/journal.pone.0245324.r001
Revision 1
5 Nov 2020 Author Response Editor’s comments - 1) Address the issues of false positives, as explained by reviewer 1. Take attention on your response as this will ensure that your tool is used and the paper is read and cited. We have addressed the relevant reviewer question below and also added information to methods and conclusion section as requested by the reviewers. 2) Include a case study of a species that has not been studied before to show how can this software be used We have now added case study 3 with insectOR gene predictions for Apis dorsata genome and provided instructions about further manual curation as well 3) Explain whether the software can be downloaded and used off-line by bioinformaticians and whether the code is open source. If not, then you may wish to consider to do that as it is unlikely the community will use something they cannot validate themselves. We have now uploaded the tool to GitHub and it is open source. It is available at - https://github.com/sdk15/insectOR Comments to the Author Review Comments to the Author 1) Reviewer #1: The authors have created a web tool for semi-automatic identification and annotation of insect Odorant Receptor genes from uncharacterized genomic sequences. This tool would be useful for biologists that lack the bioinformatics background to perform these queries manually (this reviewer’s perspective). The tool would allow for relatively quick surveys of important olfactory genes in non-model species. These data could complement other types of investigations: behavioral, ecological, etc. A bioinformatician is needed to validate all methodology (for instance the parameters used for the MAKER comparison, line 226), but the techniques appear well intentioned and designed. The rationale for each case study species makes sense, though I had hoped a completely unstudied species was used for case study #2 to demonstrate the potential power of this web tool. We have now added case study 3 with insectOR gene predictions for Apis dorsata genome. 2) Perhaps the abstract should end with a statement reminding readers of this tool’s value to researchers. Thank you for this suggestion. We have now added a sentence accordingly. 3) The paper does not fully address this web tool’s false positive rate of discovery. Several of the trials run in tables S1-S4 show too many gene hits as compared to what has currently been uncovered. It could be that these hits are undiscovered ORs, but it is likely some or most of these extra hits are false positives. A section needs to be added to the methods that describes how precision and sensitivity were measured, giving more details. The conclusion needs to discuss how to determine false positives in the output files. Thank you for these suggestions. We have now added relevant information in the methods and the conclusion sections. We have also added a new publication reference [47] for ‘gffcompare’ utility which only existed as a webpage at the time of previous submission. More explanation to reviewer points is given here - The total number of genes/gene regions identified by insectOR cannot be expected to be close to the total number of insect OR genes in the given genome. This is simply because there could be many partial genes, few of which are also isoforms of the nearby complete genes. InsectOR prefers complete and more compact gene models over other overlapping gene predictions. Hence other isoforms are left as partial. This cannot be resolved without further information from antennal transcriptome data. In case of draft and segmented genome assemblies, split OR genes cannot be merged by insectOR. Better measure of the total number of OR genes is the number of 7tm_6 containing OR protein coding genes and it is a good indicator of True Positives. On the contrary, the absence of 7tm_6 cannot be confidently interpreted as a False Positive for the following reasons – a) 7tm_6 HMM was initially built using only Drosophila melanogaster olfactory receptors. As more olfactory receptors are sequenced, it is becoming clearer that certain OR subfamilies also seem to be exclusively present in certain insect taxonomic orders (Hansson & Stensmyr 2011, Karpe SD Ph. D. Thesis 2018). Hence ORs that are distantly related to Drosophila ORs might fail to show presence of this domain using HMMSEARCH. b) The presence of the Pfam domain identified here also depends on the length of the protein provided, with partial ones smaller than a certain length failing the identification altogether. c) In case of pseudogenes and their translated pseudo-proteins (mainly used for phylogenetic reconstructions), key amino acids defining 7tm_6 domains might be missing, again leading to no 7tm_6 identification. Hence, we do not use this information to either filter out any hits or to calculate false discovery rate. We choose to rather inform the users to use it for their benefit while stitching closely spaced partial/pseudo genes, if any. Users can also perform additional analyses looking at the sequence identity with well-known olfactory receptors to decide the fate of gene regions without any identified domain. Next, the prediction by insectOR depends largely on the query sequences used for performing Exonerate. Users are advised to choose these sequences with care. More instructions are given in the ‘How to choose OR protein queries for Exonerate alignment?’ section of the ‘About’ tab of insectOR webserver. Although utmost care was taken while performing the analyses on four additional genomes, we do still see high number of genes predicted. Many of these can be explained by the reasons provided above. Few of these hits can be refined further using the additional information provided by insectOR. This process is difficult to automate without losing sensitivity and defeats the purpose of insectOR, which is to provide preliminary identification of olfactory receptors. 4) Line 234 – Be more specific as to how insectOR performed “better.” We have rewritten this sentence now. 5) Line 242 – it would be helpful to include a file listing the 727 non-drosophila ORs used in this step We have included this file in the supplementary data. 6) Table 1 – I did not notice a thorough explanation of how “sensitivity” and “precision” were calculated in the case study. The accompanying text is somewhat vague. We have now added a paragraph in methods section for better understanding. 7) Line 291 – rather than referencing the 2017 paper, it would be helpful to include a file listing the 1249 ORs used in this step, or at least a brief explanation of how these were chosen We have added explanation regarding these and also included the file in the supplementary data. 8) Line 307 – change “five other genomes” to “four other genomes” We have changed the number of the genomes. 9) Small corrections by line number: 16 – delete “Hence” 19 – change “sever” to “server” in abstract 39 – remove capital in “Olfaction” 48 – “is” to “are” 56 – delete “only” 285 – change “missed” to “failed” 321-reword? We have made the corrections suggested here. For the change on line 48, we have changed ‘is’ to ‘belong to’ as it seemed more appropriate. Reviewer #2: The manuscript by Karpe et al. develops a webserver – InsectOR serving as the prediction of gene models of insect ORs. This is a significant work for the preliminary identification of OR genes. This manuscript was well written and easy to be followed. However, I am not an expert in the field of bioinformatics. For the manuscript, I mainly concerned two issues: 10) Insect ORs are a diverse family with some genes exhibiting extremely low identities at the amino acid levels. As I know, some of ORs in one species have no orthologs to ORs from other species. This is difficult for the researchers to identify the exact number or full-length sequences of OR genes. Whether the authors have considered the parameter set of this webserver on low identities or no orthologs of ORs? It is true that many olfactory receptors do not have orthologs in other species, however their homologs do exist at lower sequence identities. It has been observed that the ORs from various insect orders tend to cluster separately (Hansson & Stensmyr 2011). However, many more insect genomes and antennal transcriptomes have been sequenced since then and now representative ORs from almost all insect taxonomic orders and many taxonomic families are available. In our experience with insectOR, including as diverse sequences of ORs (mainly from the same insect order) helps to improve the number as well as completeness of the genes predicted, clearly due to higher sequence identities. More instruction about selecting query sequences for insectOR run are provided in the ‘How to choose OR protein queries for Exonerate alignment?’ section of the ‘About’ tab of insectOR. However, if users feel that the numbers are still unsatisfactory, they can choose to use PAM250 distance matrix while performing Exonerate alignment. This matrix is suited to identify more distantly related / homologous sequences. More details are provided in the ‘How to generate Exonerate alignment file?’ section of the ‘About’ tab of insectOR. This increases the sensitivity of the search, but it also increases false positives. Hence users need to be careful while analysing results from this search. An alternative to this would be to take output proteins of the first insectOR run, filter them to identify the near-complete 7tm_6 domain containing sequences and use them for the second round of Exonerate-insectOR. Users have reported that this helped them to identify more OR genes. At the level of insectOR algorithm, we do not filter out any potential gene region identified by Exonerate+GeneWise, unless it is overlapped by another more complete gene prediction. We report all of them along with their validations including the presence of 7tm_6 domain, presence of known OR motifs and presence of transmembrane helices. Users can further filter out certain regions which do not pass their own cutoffs for these validations. 11) If one gene was located on two scaffolds or contigs, this webserver enables them merge into one gene? InsectOR provides information of the ‘best’ query sequence that helped to define the genomic location of every predicted gene. This information is available in the tabular output. Although insectOR cannot directly merge a split gene on two scaffolds, users can make use of the information about the shared best query and location of the two partial genomic regions on respective two scaffolds. If they are located near the ends of the two scaffolds in question and two distinct regions of the best query align to them, it is likely that it is a split gene. It should be also noted that there can be duplication of genes in the genome and the same ‘best’ query might identify two such complete or partial regions. Hence this needs to be done cautiously. Currently, it is impossible to confidently merge partial genes on two different scaffolds without use of additional information, say antennal transcriptome assembly data or an improved genome assembly. 12) Using ‘InsectOR’, this number of genes is relatively precise. I would like to know whether it will give more full-length sequences? We use GeneWise for the second level predictions, which helps to improve the number of complete genes significantly than just processing the results from Exonerate alone (P1 predictions). As we did not find de novo or homology-based predictions from tools like MAKER to be comparable in the performance, we do not think that any additional tool might help in this aspect. Secondly, it should be noted that the insectOR gives preference to genes that are most compact and complete. Hence, some of the partial genes/predicted regions might reflect exons belonging to alternative isoforms of the nearby complete genes predicted by insectOR. In the absence of the transcriptome data, it is impossible to declare the isoforms at this stage, and hence they must be declared as a separate partial gene at this time. Thirdly, if the genome assembly is fragmented, it might again lead to multiple partial hits. As noted in the previous answer, a bit of additional work on user’s part might help to merge split genes on two scaffolds. Lastly, some users have reported that complete 7tm_6 containing output sequences from insectOR can be used for a second round of prediction with Exonerate-insectOR. This might help to improve the number and completeness of genes. Attachments Attachment Submitted filename: Response_to_reviewers_14OCT2020_r1.docx https://doi.org/10.1371/journal.pone.0245324.r002
29 Dec 2020 Decision Letter - Alexie Papanicolaou, Editor InsectOR - webserver for sensitive identification of insect olfactory receptor genes from non-model genomes PONE-D-20-12954R1 Dear Dr. Sowdhamini, We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. Kind regards, Alexie Papanicolaou, PhD Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation. Reviewer #1: All comments have been addressed Reviewer #2: All comments have been addressed ******** 2. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Yes Reviewer #2: Yes ****** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: Yes ****** 4. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes Reviewer #2: Yes ****** 5. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes Reviewer #2: Yes ****** 6. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: All changes made in response to first review have been well executed. Thank you for your thorough revision. Particularly helpful are the third case study and the added section explaining 'Precision and Sensitivity.' This works provides a very useful tool to chemical ecologists. Reviewer #2: The authors have responded to my concerns, and I have no additional comments for this manuscript. Thus, I recommend a acception in PLoS One. ******** https://doi.org/10.1371/journal.pone.0245324.r003
Formally Accepted
6 Jan 2021 Acceptance Letter - Alexie Papanicolaou, Editor PONE-D-20-12954R1 InsectOR – webserver for sensitive identification of insect olfactory receptor genes from non-model genomes Dear Dr. Ramanathan: I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org. If we can help with anything else, please email us at plosone@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. Alexie Papanicolaou Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0245324.r004

Open letter on the publication of peer review reports

PLOS recognizes the benefits of transparency in the peer review process. Therefore, we enable the publication of all of the content of peer review and author responses alongside final, published articles. Reviewers remain anonymous, unless they choose to reveal their names.

We encourage other journals to join us in this initiative. We hope that our action inspires the community, including researchers, research funders, and research institutions, to recognize the benefits of published peer review reports for all parts of the research system.

Learn more at ASAPbio .