Emotional prospective mental imagery, in which we simulate possible future events within our minds, have a pronounced impact on behavior. For example, repeated engagement in positive prospective imagery can lead to behavioral activation, while negative prospective imagery can lead to catastrophizing and avoidance. Physiological arousal boosts memory consolidation, creating emotional memories. Thus, if emotional prospective imagery produces an arousal response, the memory consolidation of these simulations of the future may be boosted, offering a possible underlying mechanism for the impact of emotional prospective imagery on behavior. In order to examine the feasibility of arousal as a possible mechanism behind the impact of emotional prospective imagery on behavior, sixty participants produced autobiographical prospective imagery of 30 scenes , during which arousal responses (skin conductance) were measured, and ratings for subjective arousal, valence, and imagery vividness were collected. Moreover, because vividness of prospective imagery has been related to anxiety and depression, the study examined this relation also for event-related autobiographical prospective imagery. The results showed that emotional prospective imagery were associated with higher subjective arousal ratings as compared to neutral imagery. Physiological arousal responses showed a similar pattern, but further data is needed for a firm conclusion. Nevertheless, arousal-boosted consolidation remains a possible contributing mechanism for the impact of emotional prospective imagery on behavior. Moreover, results suggest both anxiety and depression may entail a reduced ability to invent prospective life situations. However, only anxiety was associated with less vivid imaginations, unless the imaginations were of negative content. Hence, anxious individuals may experience negative prospective imagery more vividly than imagery with neutral and positive content. Mental imagery are perceptual sensory experiences in the absence of sensory input ,2. MentaProspective imagery affect our mood and motivation, and thus, our behavior. Hence, prospective imagery is also of clinical interest. Positive prospective imagery can be helpful. For example, prospective imagery of positive activities increase motivation and anticipated reward for these events, as well as the probability that these activities will be performed , and menIn contrast to positive prospective imagery, negative prospective imagery can be detrimental . For exaThe mechanisms underlying the effects of prospective imagery on behavior are unclear. One possible mechanism is that mental imagery utilizes its ability to carry emotion  and evokMental imagery can indeed evoke arousal responses. For example, mental imagery of fear conditioned stimuli can stand in for the visual stimuli and evoke arousal responses –19. MentThe aim of this study is to examine, in an event-related manner, physiological and subjective arousal responses during prospective imagery with different emotional valence . A trial of the experiment consists of presenting participants with a description of a scene (e.g. you will have a serious disagreement with a good friend). Then, the participant must construct the scene, that is, choose friend and disagreement . Once thIn addition to arousal response, the study also examines other aspects of mental imagery. Imagery vividness is a central measure in mental imagery research, and high imagery vividness has been associated to higher arousal response ,23. ThusIn order to address these research questions, participants performed prospective mental imagery with different emotional valence , while physiological arousal was measured with skin conductance responses (SCRs), and ratings of imagery vividness and subjective arousal were measured on a trial-by-trial basis.https://osf.io/hr5df/). Seven participants were excluded from analysis of skin conductance data; four because of technical difficulties, two because they were non-responders (no response above 0.05 μS), and one was an outlier (using tukeys fences with k = 3), making N = 53 in analysis involving skin conductance. One participant did not fill in the questionnaires on anxiety and depression, making N = 59 for analysis involving those.Sixty non-clinical participants  were recruited through advertisements on campus billboards and social media. Exclusion criteria were self-reported current psychiatric disorder, and current use of psychotropic medication. Participants were reimbursed with two cinema tickets, corresponding to about 200 SEK (20 USD). Ethical approval was granted by the Swedish Ethical Review Authority (2019–06507). All participants provided their written informed consent. Clinical trial registration can be found at Clinicaltrials.gov (2019–06507). The study was pre-registered at Open Science Framework, where data can be found , 10 negative (e.g. people will find you dull and boring), and 10 neutral (e.g. you are having breakfast). The 10 positive and 10 negative instructions were taken from the Prospective Imagery Task (PIT)  and tranSkin conductance responses were measured using BIOPAC MP 160  and two disposable 8mm Ag/AgCL-electrodes prepared with isotonic electrolyte gel , which were attached to the hypothenar eminence of the left hand.State and Trait Anxiety Inventory–Trait (STAI-T) Reviewers' comments:Reviewer's Responses to Questions  Comments to the Author1. 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: PartlyReviewer #2: Yes**********  2. Has the statistical analysis been performed appropriately and rigorously?   Reviewer #1: NoReviewer #2: Yes**********  3. Have the authors made all data underlying the findings in their manuscript fully available?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.  The Reviewer #1: YesReviewer #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: YesReviewer #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. Reviewer #1: I appreciate the opportunity to review this manuscript titled “Physiological and subjective arousal to prospective imagery: a mechanism for behavioral change?”.In this study, the authors assessed the association of arousal and depressive and anxiety symptoms with autobiographic emotional prospective imagery. I think this is an interesting study. Nevertheless, I have some concerns that need to be addressed before its acceptance for publication.ABSTRACTThe abstract consists mainly of an introduction to the objective of the study. There is no sample description or methodology. And the results and discussion are limited to a short concluding paragraph.The authors should restructure the abstract by cutting the introductory part and adding brief but necessary information about the methodology and the sample. The results and their implications should also be a bit more developed.INTRODUCTION- Line 100: “ The authors also examines if subjective arousal, imagery vividness and scene construction time, differ….”. Why scene construction time is important in the study? Albeit briefly, the introduction offers information on how arousal or vividness can influence mood and motivations, but nowhere does it mention the effect that scene construction time can have. Authors should explain why this variable is important enough to include it in the study.- Lines 104-107: Taking into account that the study sample does not present clinical anxiety or depression, the assertion that the the results will contribute to discovering the relationship between prospective imagery and anxiety and depression may be somewhat risky.MATERIALS AND METHODSParticipants- Was a prior estimate of the minimum sample size necessary to carry out the study?Materials- Were the prospective imageries generated by the participants recorded somehow? Was there a control measure to ensure that all prospective mental imagery instructions generated an image in all participants?- What was the procedure carried out to generate the neutral instructions? Was there a pilot study than ensured its emotional neutrality?Questionnaires- Questionnaires need to be better described .Procedure:- Procedure need to be better describe.o Line 156-157: Was there a maximum number of practice rounds? Did the practice continue until it was certain that the participant had understood the task?o The experiment had 30 trials : where the trial randomized?o Was there any distraction/break between rehearsals? For example, if after a high vivid negative prospective imagery, a positive instruction appears, the participant may have difficulties generating a positive image if they were unable to disconnect from the previous image.- Mood can affect the generation of prospective autobiographical images. It would have been appropriate to have a measure of mood prior to the start of the experiment  as a control measure as it could be influencing the results.RESULTS- Manipulation checkso Results of mean comparisons should be accompanied by their corresponding effect size (Cohen’s d).- P values of 0.07 or 0.09 are not statistically significant so follow-up tests are not indicated in these cases because there is not a significant effect.- Figure 2 is not clearly visible. Its quality should be improved.- Anxiety and depression groups:o the descriptive characteristics of the high and low symptoms groups are not described . Are there significant differences between the groups?o The range and mean (SD) of anxiety and depression scores in the groups with low and high level of symptoms (anxiety and depression) do not appear either. T tests are significant? Without this information it is difficult to see if there really is a clear difference between groups in the level of symptoms.o Repeated measures ANOVA: When interaction effects are significant, there are not post hoc analysis of this interaction. Post hoc analysis in these cases is necessary to assess how the variables interact between them.DISCUSSIONThe authors comment on a part of the results in the discussion when some of them have not really reached statistical significance (p = 0.07 or 0.09). In this sense, I consider that it cannot be affirmed that there are differences, for example, at the level of physiological arousal between emotional conditions, as for the rest of the effects with p equal to 0.07 or 0.09. For this reason, I think that a part of the conclusions reached by the authors do not really correspond to the results found.There are hardly any bibliographical references in the discussion. In this section, the results must be elaborated by relating them to those of the previous scientific literature. In this sense, the authors should make a greater effort in the elaboration of the discussion.Discussions should not include statistical results (t tests -line 379- or correlations -line 405-).Lines 380-381 and lines 388-391. Perhaps the results are different simply because the study was carried out with a non-clinical population.Reviewer #2: Dear Authors, This is a good experiment that studied the effects of prospective mental imagery of different types of emotional valence on the subjective evaluation of vividness of imagery. The study also correlated these findings with the effects on depression and anxiety rating and correlated it with physiological effects of skin conductance responses.There are, however, some minor comments that need to be addressed, specifically:1. In the abstract section, the sentence: 'Emotional prospective mental imagery, in which we simulate possible futures within our minds, have a pronounced impact on behavior.' Suggest to change to: Emotional prospective mental imagery, in which we simulate possible future events within our minds, have a pronounced impact on behavior.2. Please define the abbreviation SCR when it first appears in the text in the methodology section. Kindly make sure that the plural version is correctly and consistently stated as SCRs.3. In the results section, please state the range of scores for depression and anxiety scores of the participants. Were any of them in the clinical range of mood disorder?4. In lines 351-353: 'This, even in everyday life, because participants were instructed to construct autobiographical prospective imagery of an event that could happen within six months in their own lives.'. The sentence appears incomplete. Suggest revising the sentence.**********  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: NoYes: Subapriya SuppiahReviewer #2: **********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.While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool,  6 May 2023Response to reviewers can be found in an attached file, but is also pasted belowPONE-D-22-32397Physiological and Subjective Arousal to Prospective Mental Imagery: a mechanism for behavioral change?PLOS ONEDear Dr. Agren, 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.Both reviewers and myself agree that your study is interesting. However before it can be published all aspects of the manuscript must be revised.I outline some key issues here but you must address all points raised by the reviewers. First the abstract must be more comprehensive and include information about the methods and sample..Second the introduction does not explain or justify why scene construction time is included in the study. You should also acknowledge that your study is discussing symptoms of depression and anxiety and therefore the implications for clinical depression and anxiety must be qualified. Further much more detail is needed about the methods. I agree with Reviewer1 that it would have been useful to have a measure of state mood at the start of the experiment but this could be discussed as a limitation. You need to report a power analysis.When reporting the results effect sizes must be described. You should also describe differences between your two groups with t tests. When reporting interactions you must do follow up tests when the interactions are significant. 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 submit your revised manuscript by April 30 2023. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at We look forward to receiving your revised manuscript.Kind regards,Barbara Dritschel, PhDAcademic EditorPLOS ONEThanks you for your interest in our study, and for the opportunity to submit a revision. Reviewers comments have triggered a thorough overhaul of the manuscript, which we believe has improved its quality. As the requirements you mentioned above are also brought up by the reviewers, we have put the details of our actions below in our response to reviewers, in order to avoid the same answer in two places.Kind regards,Thomas Agren.Journal Requirements:When submitting your revision, we need you to address these additional requirements.https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and 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=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdfThank you for these clarifying links. We have endeavoured to follow these guidelines. 2. Please provide additional details regarding participant consent. In the ethics statement in the Methods and online submission information, please ensure that you have specified what type you obtained . If your study included minors, state whether you obtained consent from parents or guardians. If the need for consent was waived by the ethics committee, please include this informationWe have now specified that we collected written informed consent, which can be found on page 6 L138-:“Ethical approval was granted by the Swedish Ethical Review Authority (2019-06507). All participants provided their written informed consent.”3. We note that you have stated that you will provide repository information for your data at acceptance. Should your manuscript be accepted for publication, we will hold it until you provide the relevant accession numbers or DOIs necessary to access your data. If you wish to make changes to your Data Availability statement, please describe these changes in your cover letter and we will update your Data Availability statement to reflect the information you provide.Understood! We will publicly release data and provide you with a DOI at osf.io directly, if the ms should be accepted.http://journals.plos.org/plosone/s/supporting-information.4. Please include captions for your Supporting Information files at the end of your manuscript, and update any in-text citations to match accordingly. Please see our Supporting Information guidelines for more information: There are now captions for the Supporting Information files included at the end of the manuscript. Reviewers' comments:Reviewer #1: I appreciate the opportunity to review this manuscript titled “Physiological and subjective arousal to prospective imagery: a mechanism for behavioral change?”.In this study, the authors assessed the association of arousal and depressive and anxiety symptoms with autobiographic emotional prospective imagery. I think this is an interesting study. Nevertheless, I have some concerns that need to be addressed before its acceptance for publication.Thank you for your interest in the study, and for your comments. In our response to your comments, we believe the quality of the ms has improved considerably. Please find our responses and changes below.ABSTRACTThe abstract consists mainly of an introduction to the objective of the study. There is no sample description or methodology. And the results and discussion are limited to a short concluding paragraph. The authors should restructure the abstract by cutting the introductory part and adding brief but necessary information about the methodology and the sample. The results and their implications should also be a bit more developed.We have endeavoured to rewrite the abstract along the lines suggested above. We hope that this new version is acceptable. See below:Emotional prospective mental imagery, in which we simulate possible future events within our minds, have a pronounced impact on behavior. For example, repeated engagement in positive prospective imagery can lead to behavioral activation, while negative prospective imagery can lead to catastrophizing and avoidance. Physiological arousal boosts memory consolidation, creating emotional memories. Thus, if emotional prospective imagery produces an arousal response, the memory consolidation of these simulations of the future may be boosted, offering a possible underlying mechanism for the impact of emotional prospective imagery on behavior. In order to examine the feasibility of arousal as a possible mechanism behind the impact of emotional prospective imagery on behavior, sixty participants produced autobiographical prospective imagery of 30 scenes , during which arousal responses (skin conductance) were measured, and ratings for subjective arousal, valence, and imagery vividness were collected. Moreover, because vividness of prospective imagery has been related to anxiety and depression, the study examined this relation also for event-related autobiographical prospective imagery. The results showed that emotional prospective imagery were associated with higher subjective arousal ratings as compared to neutral imagery. Physiological arousal responses showed a similar pattern, but further data is needed for a firm conclusion. Nevertheless, arousal-boosted consolidation remains a possible contributing mechanism for the impact of emotional prospective imagery on behavior. Moreover, results suggest both anxiety and depression may entail a reduced ability to invent prospective life situations. However, only anxiety was associated with less vivid imaginations, unless the imaginations were of negative content. Hence, anxious individuals may experience negative prospective imagery more vividly than imagery with neutral and positive content. INTRODUCTION- Line 100: “ The authors also examines if subjective arousal, imagery vividness and scene construction time, differ….”. Why scene construction time is important in the study? Albeit briefly, the introduction offers information on how arousal or vividness can influence mood and motivations, but nowhere does it mention the effect that scene construction time can have. Authors should explain why this variable is important enough to include it in the study.We apologize for the very brief explanation to why these outcome variables were included. This is now expanded in the introduction on page 4 Line 102 and forward, and can be found below. We hope this is satisfactory.The aim of this study is to examine, in an event-related manner, physiological and subjective arousal responses during prospective imagery with different emotional valence . A trial of the experiment consists of presenting participants with a description of a scene (e.g. you will have a serious disagreement with a good friend). Then, the participant must construct the scene, that is, choose friend and disagreement (23). Once the participant has chosen the scene, a button is pressed and mental imagery of the scene is produced for a short time. During the production of mental imagery, physiological arousal response is measured, and afterwards, subjective arousal response is rated. In addition to arousal response, the study also examines other aspects of mental imagery. Imagery vividness is a central measure in mental imagery research, and high imagery vividness has been associated to higher arousal response . Thus, participants rated imagery vividness for every prospective imagery produced. Moreover, it appears that the time during which the participants choose the details of a scene (scene construction time), may be an interesting, unexplored, outcome variable. For example, perhaps it takes longer for participants to construct a negative scene as compared to a neutral. Perhaps an anxious individual are quick to construct negative scenes, finding that they pop into mind easily, but struggle to find positive scenes. Thus, scene construction time is measured for each trial, so that its’ usefulness as an outcome variable can be examined. Because of the above reasons, this study examines if imagery vividness and scene construction time differ between prospective imagery with different emotional valence, and if imagery vividness correlate with the other reported measures. Finally, this study examines whether our measures of prospective imagery are related to symptoms of anxiety and depression, in order to contribute to the growing literature on the relationship between prospective imagery and anxiety and depression. - Lines 104-107: Taking into account that the study sample does not present clinical anxiety or depression, the assertion that the the results will contribute to discovering the relationship between prospective imagery and anxiety and depression may be somewhat risky.We agree that the present study’s contributions to the relationship between prospective imagery and anxiety and depression is limited by the fact that participants are mostly not in the clinical range of anxiety and depression. Nevertheless, it seemed to us worthwhile doing, as it at least examines possible associations between prospective imagery and symptoms of anxiety and depression in the general population. We have no stated this as a limitation on page 19 Line 466:It should also be noted that these results, collected from a normal population, might not be generalizable to individuals with clinical anxiety or depression.And mentioned it in discussing our results on page 18 Line 432-:The difference compared to previous data may be caused by previous data being collected from clinical populations (12). However, because the same difference was found also towards larger studies with comparable populations , they can perhaps be attributed to methodological differences, as the previous studies did not contain the stringent time constrains needed for event-related skin conductance measures, that were used in the present study.MATERIALS AND METHODSParticipants- Was a prior estimate of the minimum sample size necessary to carry out the study?Well yes, but according to power calculating tool Gpower, we would only need N=22 to detect a medium effect size. We couldn’t find another event-related study using SCR to emotional mental imagery for comparison, and with our previous studies on event-related SCR to mental imagery of conditioned stimuli in mind , this number of participant seemed small to me. Hence, I decided to go for the sample size more similar to our previous studies, N=60, which according to Gpower, would be enough to find much smaller effect sizes. This is now described on page 9 Line 220-, and pasted below:An a priori power analysis was conducted using G*power version 3.1.9.7 (30), which determined the minimum sample size required for a discovering a medium effect with 80% power to N = 22. This number of participants appeared small to us in light of our previous studies employing skin conductance measures. Hence, we opted for N = 60, which is more than adequate to test the study hypothesis.Materials- Were the prospective imageries generated by the participants recorded somehow? Was there a control measure to ensure that all prospective mental imagery instructions generated an image in all participants?The prospective imageries were not recorded, because we thought it would take too much time to have the participant describe it after each trial. What we have, is the ratings of imagery vividness after each trial. If someone failed to produce imagery, it would show in our data as having low imagery vividness. Our imagery vividness measures strongly correlated with VVIQ, which suggests that participants in most trials produced mental imagery. If a participant generally produced mental imagery, and then for some reason failed for a specific scene, this would show as a dip in imagery vividness. We will consider improvements on this in future experimental design. - What was the procedure carried out to generate the neutral instructions? Was there a pilot study than ensured its emotional neutrality?The neutral instructions were discussed with two independent researchers that had previously worked with the Prospective Imagery task. We ran a few pilot participants before the start of the study and it seemed like the neutral instructions did score a neutral valence and low arousal. I am afraid that was all we did. Luckily, the results appear to show that the scenes were neutral as compared to positive and negative (see page 10 Line 228- and below), but as discussed, they may have differed in other ways.The valence ratings showed that positive scenes received higher ratings than neutral, t(59) = 16.41, p < 0.001, d = 2.11, which in turn received higher ratings than negative scenes, t(59) = 25.66, p < 0.001, d = 3.13, confirming that the scenes in the different categories  had different emotional valence.Questionnaires- Questionnaires need to be better described .This is now done on page 7 Line 161-, and the new text can also be found below.“The State and Trait Anxiety Inventory – Trait (STAI-T) (24), a 20 item questionnaire where participants rate from 1-4 to what degree they agree with statements regarding experience of anxiety, was used to measure anxiety symptoms. The Patient Health Questionnaire-9 (PHQ-9) (25), a 9 item questionnaire where participants rate from 1  to 4 (nearly every day) how often they have been bothered by symptoms associated to depression, was used to measure symptoms of depression. The Vividness of Visual Imagery Questionnaire (VVIQ) (26), a 16-item questionnaire where participants perform mental imagery and rate their vividness from 1  to 5 , was used to measure the general propensity for mental imagery. Instructions for positive and negative prospective imagery were taken from the Prospective Imagery task (PIT) (23). Emotional valence ratings and subjective arousal ratings were collected using Self-Assessment Manikins (27) and moving a visual slider below the manikins to a position that represented the rating, which was recorded as a number from 1-100 .”Procedure:- Procedure need to be better describe.o Line 156-157: Was there a maximum number of practice rounds? Did the practice continue until it was certain that the participant had understood the task?The initial practice round was three trials. All of the participants claimed that they understood the task after these trials and did not need more. This is now clarified at page 8 Line 183 and pasted below:After conducting a set of three practice rounds, all participants claimed to understand the procedure, and the experiment was startedo The experiment had 30 trials : where the trial randomized?They were pseudo-randomized in such a way that a positive, negative, and neutral instance were randomly drawn and randomized, before a new such triplet was drawn. We apologize for omitting this in the methods and it is now added in page 8, Line 187 and below:The trials were pseudo-randomized in such a way that a triplet of trials, one positive, one negative, and one neutral, were randomly drawn and presented in a random order before a new such triplet was drawn.o Was there any distraction/break between rehearsals? For example, if after a high vivid negative prospective imagery, a positive instruction appears, the participant may have difficulties generating a positive image if they were unable to disconnect from the previous image.No, there were no such breaks. After all of the ratings regarding an instance of mental imagery was completed, there was a 3 second break, after which a new instruction would appear. We will consider using a break or distraction in the future. Maybe this will have an impact on measurements.- Mood can affect the generation of prospective autobiographical images. It would have been appropriate to have a measure of mood prior to the start of the experiment  as a control measure as it could be influencing the results.Yes, that would have been a good idea. Sadly, we did not take such a measure, but I will be sure to do it in future studies.RESULTS- Manipulation checkso Results of mean comparisons should be accompanied by their corresponding effect size (Cohen’s d).We apologize for this oversight. It has now been corrected. See page 10 Line 228- and below:The valence ratings showed that positive scenes received higher ratings than neutral, t(59) = 16.41, p < 0.001, d = 2.11, which in turn received higher ratings than negative scenes, t(59) = 25.66, p < 0.001, d = 3.13, confirming that the scenes in the different categories  had different emotional valence.- P values of 0.07 or 0.09 are not statistically significant so follow-up tests are not indicated in these cases because there is not a significant effect.We realize that follow-up t-tests to near-significant results are controversial. We left them in because we thought they were clarifying. They are now removed. However, we feel it is important that the figures are consistent with the use of the different symbols (e.g. “*”), which is why the figures are left as is. In order to provide the statistics for all our “*” and such symbols, the corresponding pairwise comparisons can now be found in the supplementary materials. We hope this is acceptable.- Figure 2 is not clearly visible. Its quality should be improved.We are not sure what have happened here. To us, it appears crisp. Maybe it was somehow changed during the construction of the proof? We have re-produced the image and are ready to communicate with the editors at PLOS in order to ensure the quality of the image. Anxiety and depression groups:o the descriptive characteristics of the high and low symptoms groups are not described . Are there significant differences between the groups? See answer below.o The range and mean (SD) of anxiety and depression scores in the groups with low and high level of symptoms (anxiety and depression) do not appear either. T tests are significant? Without this information it is difficult to see if there really is a clear difference between groups in the level of symptoms.The ranges and means of STAI-T and PHQ-9 among the participants are now included. So are t-tests. See page 12 Line 279- for STAI:STAI was collected from all participants but one (N = 59) and revealed a group level of anxiety corresponding to a normal population  (24).And Line 281-First, a median split was performed (median = 38), creating two anxiety groups . These groups significantly differed on STAI score as expected, t(57) = 9.60, d = 2.51, and did not differ in age, t(57) = -1.31, p = 0.20, or sex, χ2(1) < 0.01, p = 0.99.And page 14 line 330 for PHQ-9:PHQ-9 was collected from all participants but one .And Line 331-First, a median split was performed (median = 4), creating two groups . These groups significantly differed on PHQ score as expected, t(57) = 9.15, p < 0.001, d = 2.39, and did not differ in age, t(57) = -1.33, p = 0.19, or sex, χ2(1) = 0.11, p = 0.75.See also answer to comment from Reviewer #2 below.o Repeated measures ANOVA: When interaction effects are significant, there are not post hoc analysis of this interaction. Post hoc analysis in these cases is necessary to assess how the variables interact between them.I apologize that interaction effects were not always followed by all the post-hoc pairwise comparisons. We have now added pairwise comparisons where they were missing. Added at line 306:…but no difference on negative imagery, t(57) = 0.84, p = 0.40, d = 0.22…And at line 314Follow-up t-tests showed a no difference between low and high anxiety on either the arousal ratings of positive imagery, t(57) = 1.31, p = 0.20, d = 0.34, neutral imagery, t (57) = -1.10, p = 0.28, d = 0.29, or negative imagery, t(57) = 1.25, p = 0.22, d = 0.33.And line 357Follow-up t-tests showed a near-significant difference between low and high depressive symptoms for the vividness ratings of neutral imagery, t(57) = 1.71, p = 0.09, d = 0.45, but not for positive, t(57) = 0.28, p = 0.78, d = 0.07, or negative imagery, t(57) = -0.70, p = 0.49, d = -0.18.And line 366Follow-up t-tests showed a difference between low and high depressive symptoms for the arousal ratings of neutral imagery, t(57) = 3.63, p = 0.001, d = 0.95, but not positive, t(57) = -1.40, p = 0.17, d = -0.36, or negative imagery, t(57) = -0.17, p = 0.87, d = -0.04DISCUSSIONThe authors comment on a part of the results in the discussion when some of them have not really reached statistical significance (p = 0.07 or 0.09). In this sense, I consider that it cannot be affirmed that there are differences, for example, at the level of physiological arousal between emotional conditions, as for the rest of the effects with p equal to 0.07 or 0.09. For this reason, I think that a part of the conclusions reached by the authors do not really correspond to the results found.We apologize if the results on SCRs were presented as strong in the previous version, when they are not. We have now tried to present the results in a more balanced manner in a major re-write of the discussion.See for example on page 16 line 391-:Results showed higher arousal ratings to positive and negative prospective imagery, as compared to neutral imagery. Although the results for physiological arousal did not quite reach statistical significance, responses showed a similar pattern . Thus, the present results suggest a similar response to emotional prospective imagery for subjective and physiological arousal, and physiological arousal remains a possible contributing mechanism to the impact of prospective imagery on behavior, but further data are needed for a firm conclusion. We hope this is acceptable.There are hardly any bibliographical references in the discussion. In this section, the results must be elaborated by relating them to those of the previous scientific literature. In this sense, the authors should make a greater effort in the elaboration of the discussion.We have now made a stronger effort to compare our results to previous results, and reference those results. See:Line 398:Imagery vividness was higher for neutral imagery, as compared to positive and negative imagery, suggesting that emotional imagery were experienced as less vivid, which is contrary to previous data (31).Line 408:However, for emotional content (positive and negative), but not neutral content, vividness correlated positively with subjective arousal, suggesting that imagery vividness does matter for arousal response, mirroring previous research .Line 428:These results are at odds with previous results reporting that anxious individuals show increased vividness for negative imagery (10–12), although the present results do suggest that anxious individuals are better at negative prospective imagery as compared to neutral and positive imagery. The difference compared to previous data may be caused by those being collected from clinical populations (12). However, because the same difference was found also towards larger studies with comparable populations , they can perhaps be attributed to methodological differences, as the previous studies did not contain the stringent time constrains needed for event-related skin conductance measures, that were used in the present study.Line 441:In contrast to previous results (10–12), the participants with more symptoms of depression did not report lower vividness to positive imagery, or increased vividness to negative imageryDiscussions should not include statistical results (t tests -line 379- or correlations -line 405-).The discussion is now purged from statistical results. The correlation of anxiety (STAI) and symptoms of depression (PHQ-9) can now be found in the results section on line 339:Anxiety (STAI) and symptoms of depression (PHQ-9) were correlated, r(58) = 0.82, p<0.001Lines 380-381 and lines 388-391. Perhaps the results are different simply because the study was carried out with a non-clinical population.This is of course a possibility. However, the results of the present study also differ from other studies with non-clinical populations. We have added this in several places in the discussion.At line 431:The difference compared to previous data may be caused by those being collected from clinical populations (12). However, because the same difference was found also towards larger studies with comparable populations , they can perhaps be attributed to methodological differences, as the previous studies did not contain the stringent time constrains needed for event-related skin conductance measures, that were used in the present study.and line 466:It should also be noted that these results, collected from a normal population, might not be generalizable to individuals with clinical anxiety or depression.Reviewer #2: Dear Authors, This is a good experiment that studied the effects of prospective mental imagery of different types of emotional valence on the subjective evaluation of vividness of imagery. The study also correlated these findings with the effects on depression and anxiety rating and correlated it with physiological effects of skin conductance responses.There are, however, some minor comments that need to be addressed, specifically:Thank you for your interest in our study. We hope that we have responded in a satisfactory way to your comments below.1. In the abstract section, the sentence: 'Emotional prospective mental imagery, in which we simulate possible futures within our minds, have a pronounced impact on behavior.' Suggest to change to: Emotional prospective mental imagery, in which we simulate possible future events within our minds, have a pronounced impact on behavior.Thank you for this suggested clarification. It has been changed.2. Please define the abbreviation SCR when it first appears in the text in the methodology section. Kindly make sure that the plural version is correctly and consistently stated as SCRs.We have gone through the manuscript and made sure that that the term “SCRs” is used. 3. In the results section, please state the range of scores for depression and anxiety scores of the participants. Were any of them in the clinical range of mood disorder?We have added the range for STAI, see line 279:“STAI was collected from all participants but one (N = 59) and revealed a group level of anxiety corresponding to a normal population  (24).”A closer look reveals that according to Spielberger 1983, 35 participants had low axiety (20-39), 21 participants had moderate anxiety (40-59) and 3 participants had high anxiety (60-80).We have corrected an error concerning the mean value of PHQ-9 and added the range. See line 330-:PHQ-9 was collected from all participants but one .A closer look reveals that according to, for example Kroenke et al, that, 31 participants were classified as ‘no noticeable depression’ (0-4), 17 participants were classified as ‘mild depression’ (5-9), 8 participants were classified as ‘moderate depression’, and 3 participants as ‘moderately severe depression’.4. In lines 351-353: 'This, even in everyday life, because participants were instructed to construct autobiographical prospective imagery of an event that could happen within six months in their own lives.'. The sentence appears incomplete. Suggest revising the sentence.Thank you for spotting this. In the re-write of the discussion, this sentence was simply removed.Attachmentresponse_to_reviewers.docxSubmitted filename: Click here for additional data file. 7 Nov 2023Physiological and Subjective Arousal to Prospective Mental Imagery: a mechanism for behavioral change?PONE-D-22-32397R1Dear Dr. Agren,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. 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The Mountainous Meihua chicken is a unique regional germplasm resource from Tongjiang County, Bazhong City, China, but its genetic structure and evolutionary relationships with other native chicken breeds in the Sichuan region remain unclear. Here, we analyzed a total of 469 sequences, including 199 Mountainous Meihua chicken sequences generated in this study, together with 30 sequences representing 13 clades and 240 sequences from seven different Sichuan local chicken breeds downloaded from NCBI. These sequences were further used to analyze genetic diversity, patterns of population differentiation, and phylogenetic relationships between groups. We show that Mountainous Meihua chicken mtDNA sequences have high haplotypic and nucleotide diversity  and with a T bias that is suggestive of good breeding potential. Phylogenetic analysis showed that Mountainous Meihua chickens belong to clades A, B, E, and G and have a low affinity to other chicken breeds, with a moderate degree of differentiation. A non-significant Tajima’s D indicates that no demographic expansions occurred in the past. Finally, the four maternal lineages identified in Mountainous Meihua chicken showed unique genetic characteristics. Galus galus domesticus) is a local genetic resource with ~2000 years of history in the Qinba mountain region [The Bazhong Mountainous Meihua chicken  has low relative molecular weights, high copy numbers, maternal inheritance, and no/rare recombination events, which means that it is often used as a marker in many molecular studies ,7,8,9. IUsing mtDNA information, previous studies indicated that domestic chickens independently originated from a group of red jungle poultry found in forests in Southeast Asia and India and gradually distributed throughout the world with continuous domestication and transmission, resulting in many new breeds . ResearcMountainous Meihua chickens have been genetically characterized in the past, in particular for phenotypes associated with growth and development and muscle and egg quality . HoweverThe collection of blood samples from Mountainous Meihua chickens was performed according to the Guidelines for Experimental Animals established by the Ministry of Science and Technology . Ethical approval was provided by the Ethics Committee of the Sichuan Agricultural University (protocol number 2020202010).Blood samples were collected from 199 Mountainous Meihua chickens via wing veins. These chickens were all adult males in the Mountainous Meihua chickens breeding base in the Shuangquan Township, Tongjiang County. The blood samples were stored at −20 degrees to ensure the integrity of genomic DNA. These samples were then sent to the College of Animal Science and Technology at Chengdu Campus of Sichuan Agricultural University for genomic DNA and further genetic analysis. A proteinase-K/Phenol-chloroform standard procedure was used to extract genomic DNA, as previously described . Isolate2O. After incubation at 95 °C for 3 min, 33 cycles were performed, as follows: 94 °C for 35 s, 58.4 °C for 35 s, and 72 °C for 1 min, with a final extension at 72 °C for 10 min. PCR products were purified using the gel recovery kit and sequenced using an ABI 3730 automated sequencer .The following forward (5′-AGGACTACGGCTTGAAAAGC-3′)  and reveThe Nucleotide Basic Local Alignment Search Tool (BLASTN) was used to ensure the accuracy of the sequenced DNA fragments. The mitochondrial D-loop sequences of seven other Sichuan chicken breeds  were dowThe mtDNA of 439 individuals from eight chicken breeds was truncated to 482 bp. The observed base compositions of the mtDNA D-Loop in MH were 30.51% (T), 28.09% (C), 28.38% (A), and 13.02% (G) , showingWe identified 46 polymorphic sites, of which 39 were parsimony informative ones, and seven were singleton variable sites. These polymorphisms defined a total of 44 haplotypes , rangingSubsequently, we analyzed the overall genetic diversity indices in MH  and contp < 0.01).The genetic variation within and between population was quantified via AMOVA based on Kimura-2 parameter distances  and showWe analyzed the average number of nucleotide substitutions per site (Dxy) and the net divergence (Da) between populations based on the mtDNA control region . We estiWe also estimated the coefficient of genetic differentiation (Gst) and gene flow (Nst) between eight populations  and founPhylogenetic analysis was conducted to estimate evolutionary genetic distances using the maximum composite likelihood method available in the MEGA6.0 software. Phylogenetic analysis  revealedA maximum parsimony median-joining network was constructed based on the 44 haplotypes to further determine the phylogenetic relationship and genetic distances among the eight native chicken breeds. Network analysis depicts the minimum mutational distances among the haplotypes, and these are consistent with features observed in the neighbor-joining tree . By contHere, we presented an examination of the genetic diversity and maternal origin of Mountainous Meihua chickens (MH) and explored the genetic differentiation and evolutionary relationships between MH and seven other Sichuan chicken breeds. The analysis of the base composition of the mitochondrial D-loop indicated an A/T bias across all eight chicken breeds, which is consistent with studies in some other chicken breeds ,34. MostStudies have shown that commercial breeds have relatively low genetic diversity, as only a few sires produce many offspring . Native Tajima’s D values were not significant across all chicken breeds, indicating that neither balancing nor purifying selection occurred in these chicken breeds , and thuGst and Nst are commonly used to characterize genetic differentiation and gene exchanges between populations. Here, we found the highest degree of differentiation between MH and JY, and the lowest one between MH and MY. Similarly, while gene exchanges between MH and MC were frequent, those between MH and JS were rare. Our results showed large differences between MH and MY, and little diversification between MH and JY. In addition, we observed the highest Da value between MH and MC, and the lowest one between MH and EM. These differences may result from different living conditions, selection pressures, geographical isolation, and breeding histories ,48,49,50According to Liu  and MiaoIn summary, our study suggests that Mountainous Meihua chickens have a relatively high level of genetic diversity and present a certain degree of genetic differentiation from seven other native breeds from China. The results also showed that there were four maternal lineages in this breed, specifically belonging to clades A, B, and E. Further genomic analyses should be conducted in the future to provide further understanding of this unique breed.


Olea europaea L.) range. A unique collection of common olive’s cultivars and hybrids has been collected in the Nikitsky Botanical Gardens (NBG). The aim of this study was to assess the genetic diversity of 151 samples  using the ddRAD sequencing method. Structural analysis showed that the studied samples are divided into ten groups, each of which mainly includes cultivars of the same origin. Cultivars introduced to the Crimean Peninsula from different regions formed separate groups, while local cultivars joined different groups depending on their origin. Cultivars of Crimean origin contain admixtures of mainly Italian and Caucasian cultivars’ genotypes. Our study showed that the significant number of Crimean cultivars contains an admixture of the Italian cultivar “Coreggiolo”. Genetic analysis confirmed the synonymy for the cv. “Otur” and “Nikitskaya 2”, but not for the other four putative synonyms. Our results revealed the genetic diversity of the olive collection of NBG and provided references for future research studies, especially in selection studies for breeding programs.In different countries, interest in the commercial cultivation of the olive has recently greatly increased, which has led to the expansion of its range. The Crimean Peninsula is the northern limit of the common olive ( Olea europaea L.) is one of the oldest cultivated plants, the history of domestication of which began in the east of the Mediterranean approximately five to seven thousand years ago [Common olive  is the northern limit of the olive range, the coastal strip of the SCC provides good conditions for the cultivation of this crop . Olive cThe genetic analysis of olive cultivars from the NBG collection is being carried out for the first time. For this purpose, high-resolution SNP markers were used, allowing a thorough characterization of the genetic structure of populations, assessment of variability, and genotyping of available cultivars. We applied restriction site-associated DNA sequencing (RAD-sequencing), which has the advantages of next-generation sequencing (NGS) technology for population studies at a relatively low cost . To datePerennial plants of the olive cultivars growing in the collection plots of the Nikita Botanical Gardens—National Scientific Center of the RAS  in the same climatic and soil conditions were used for the studies. The locations of the sampling and experimentation sites are indicated by the  GPS coordinates. The area has a subtropical climate with dry and hot summers and humid winters, with rainfall mainly concentrated in the autumn and winter seasons. Annual average sunshine is 2285 h, and precipitation is 188 mm between May and September, and 595 mm for the whole year.The absolute maximum temperature is 39.0 °C, and the absolute minimum is −14.6 °C. The average annual temperature is +12.4 °C, and the average annual air humidity is 67%. The soil is brown, weakly calcareous, and has heavy loamy clay shales and limestone .In this study, 151 samples  from the NBG collection were collected and analyzed. A total of 29 cultivars were represented by olive introduced to the territory of the Crimean Peninsula , while the remaining 17 were local autochthonous cultivars. Selected cultivars have the most accurate morphoanatomical description; they differ in their habitats and are planned for use in consequent breeding studies by NBG. Accession information, including cultivar name, country of origin, and pedigree, is provided in The genomic DNA of 151 samples was subjected to double cleavage with restriction endonucleases MspI and PstI. The adapters were ligated (complementary to the restriction sites on one side and containing a unique barcode) at the same time at 30 °C for 3 h. Then, samples with different combinations of internal barcodes were pooled equimolarly into pools of 12 samples, and each pool was purified from the remaining reaction components using Agencourt AMPure XP magnetic beads . For each pool, a target distribution of 600 to 800 nucleotide fragments was collected on a BluePippin instrument . Next, PCR was performed to enrich the libraries and to attach external unique TruSeq indices with consequent purification on AMPureXP beads . The quahttps://www.bioinformatics.babraham.ac.uk/projects/fastqc/ accessed on 26 February 2023). Further, from the original readings, filtering by the quality and length of the sequence was performed using the Trim Galore software package  (Version 0.6.5). To align reads to the reference genome of O. europaea var. sylvestris (GCF_002742605.1) and to search for variable loci, bowtie2 and gstacks [To demultiplex the reads of 151 samples according to the given barcodes, the process_radtags program (Version 2.64)  was used gstacks  were use gstacks ; poorly  gstacks . The pri gstacks , in whic gstacks . To anal gstacks  using thO. europaea var. sylvestris, and the distribution of mapping percentage between accessions ranged from 59.97% to 89.33% with a mean MAPQ = 23.0585. The total number of variable loci was 695.385. A total of 110,152 SNP were left after DP and GQ filtering for population and subsequent analyzes, each of which was present in at least 95% of the samples. To assess the structure of genetic diversity within the entire common olive collection, principal component analysis (PCA) was used. Its results are presented in The sequencing of 151 common olive samples was performed with 226,627,595 paired reads in total and an average of 1,500,845 per sample  with a mean base sequence quality of 36. In total, after filtering for quality, 191,160,376 (84.35%) reads were mapped to the reference genome of Of the introduced cultivars, Italian ones formed five separate groups , and cultivars in the genome of which only one ancestral form (one color segment) was detected .We performed cluster analysis based on Euclidean distances using a filtered set of SNPs obtained by RAD-sequencing using the Neighbor-Joining (NJ) method . ClusterAs a result of the discriminatory analysis of principal components (DAPC), the analyzed sample of olives was divided into nine groups , which iFor the clusters that were formed by the sample of olive cultivars analyzed in the study based on the results of structural analysis, the fixation index (Fst) for the clusters was calculated . The higO. europaea cultivars in this study were further investigated by evaluating the common allele values of identity by state (IBS) and identity by descent (IBD); the results are shown in In addition, fixation indices (Fst) were determined in pairs for all analyzed cultivars . Also, tBased on the paired values of the IBD coefficients calculated for all cultivars of olives, a heat map was obtained . This maFor successful breeding and obtaining new cultivars, it is necessary to understand the genetic structure of the existing collection, adapted to specific growing conditions. The olive collection of the Nikitsky Botanical Gardens occupies the northernmost limits of the range. The absolute minimum temperature here reaches −14.6 degrees Celsius, with an average January temperature of +3.1 degrees Celsius .We studied the genetic diversity and structure of the common olive population, consisting of local and introduced cultivated olives. Several replicates for each cultivar were included in the study in order to neutralize the influence of intravarietal differences and confirm varietal identity.Analysis of the SNP markers of the NBG olive collection made it possible to divide it into 10 groups. At the same time, most of the groups included cultivars characterized by a common origin, and also contained admixture cultivars close to them. Only one group—V4—consisted of one cultivar, “Tavlinskaya”, which had no admixtures and was introduced to the NBG from the Caucasus from the Artvinsky olive nursery of the Batumi region in 1910. The Fst index, which describes the genetic differentiation between subpopulations, showed the highest values for this cultivar. In terms of phenotype, the cultivar “Tavlinskaya” has a higher oil content compared to other cultivars of the garden collection , which, According to the results of the discriminant analysis, the distribution of olive samples on the plot correlates with geographical origin, similar to the data obtained by other authors . Olive cThe analysis of the population structure made it possible to study in more detail the genetic interactions between all samples. “Kolhoznitsa”, “Obilnaya”, “Chernaya Rannyaya”, “Nikitskaya 37”, and “Skorospelaya” were obtained by open pollination of the Italian cultivar “Coreggiolo” . Based oThe genotype of the “Nikitskaya 33” olive has admixtures of other Italian cultivars and the Albanian cultivar . For twoThe spread of cultivated plants is often associated with human migrations, while cultivars of olives could be propagated by cuttings, distributed throughout the Crimean Peninsula, and renamed regardless of the name of the original cultivar. Phenotypic descriptions and studies based on a small number of genetic markers such as SSR and AFLP ,58 do no“Nikitskaya 2” is presumably a synonym for “Otur”, imported from the Caucasus. Genetic analysis showed that “Nikitskaya 2” and “Otur” have a high similarity of genotypes. The IBS value was more than 0.95 (0.97) on the phylogenetic tree these cultivars, represented by several biological replicates, formed a separate branch . The dif“Nikitskaya 5” and its putative synonym “Tolgomskaya” are characterized by the same phenotypic manifestations of traits , but theAccording to the results of the structural analysis of the population and phylogenetic analysis, a separate subgroup was formed by two cultivars found during the examination of the plantations of the peninsula (“Nikitskaya” and “Miskhorskaya”), the Caucasian cultivar “Gorvala”, imported in 1902 from the Artvinsky oilseed nursery, and an olive tree growing on the territory of the garden which is more than 1000 years old (“ancient olive”) . It is nThree pairs of cultivars from our study showed the highest IBD ratios: 1.03, 0.70, and 0.91. These are landraces, once introduced to the territory of the peninsula from Italy (“Piangente” and “Razzo”) and Albania (“Bidza” and “Vajsi i Peqinit”), as well as from Dalmatia and the Caucasus . The close relationship of Albanian cultivars is confirmed by the studies of A. Dervishi, indicating their autochthonous origin. In addition, as noted by A. Belaj and G. Besnard, there is a high genetic similarity between cultivars from the same or close geographical area ,65.As a result of our work, the genetic characteristics of common olive cultivars from the unique collection of the Nikitsky Botanical Gardens were obtained. The ddRAD sequencing method has proven to be effective for this kind of research. A case of synonymy was confirmed for two olive cultivars, while for others that were considered synonymous in phenotype, these data were not confirmed. In such cases, in our opinion, it is necessary to further refine the phenotypic data.The results of genotyping obtained in our work provide valuable information and will become the basis for further extended studies on the diversity and varietal characterization of the common olive collection in order to develop breeding programs and obtain new cultivars with improved properties, taking into account the genetic characteristics of the existing ones.


Rhinolophus ferrumequinum), a species with a wide geographical distribution that has three distinct genetic lineages in China. First, increased genetic differentiation at the MHC locus among populations compared using microsatellites indicated diversifying selection. Second, the genetic differentiation of MHC and microsatellites were significantly correlated, suggesting that demographic processes exist. However, MHC genetic differentiation was significantly correlated with geographical distance among populations, even after controlling for the neutral markers, suggesting a major effect of selection. Third, although the MHC genetic differentiation was larger than that for microsatellites, there was no significant difference in the genetic differentiation between the two markers among genetic lineages, indicating the effect of balancing selection. Fourth, combined with climatic factors, MHC diversity and supertypes showed significant correlations with temperature and precipitation, but not with the phylogeographic structure of R. ferrumequinum, suggesting an effect of local adaptation driven by climate on MHC diversity. Moreover, the number of MHC supertypes varied between populations and lineages, suggesting regional characteristics and support for local adaptation. Taken together, the results of our study provide insights into the adaptive evolutionary driving forces at different geographic scales in R. ferrumequinum. In addition, climate factors may have played a vital role in driving adaptive evolution in this species.Heterogeneous pathogenic stress can shape major histocompatibility complex (MHC) diversity by influencing the functional plasticity of the immune response. Therefore, MHC diversity could reflect environmental stress, demonstrating its importance in uncovering the mechanisms of adaptive genetic variation. In this study, we combined neutral microsatellite loci, an immune‐related MHC II‐DRB locus, and climatic factors to unravel the mechanisms affecting the diversity and genetic differentiation of MHC genes in the greater horseshoe bat ( As the The patterns of selection on MHC genes are simultaneously affected by multiple factors. In addition to mate choice selection and individual or kin recognition, MHC polymorphism is thought to be maintained primarily by non‐mutually exclusive pathogen‐mediated balancing selection , as a pool of pathogens, are transmitters of various pathogens and can adapt to diverse habitats  is a suitable species for elucidating the effects of various evolutionary forces on the MHC genes. First, R. ferrumequinum is widely distributed among different elevations and latitudes in China, suggesting that high habitat heterogeneity likely renders them susceptible to a diverse array of pathogens. Bats living at high latitudes face prolonged low temperatures in winter, while bats living at relatively low altitudes in temperate monsoon climates may experience relatively high temperatures in summer. In addition, the Qinling Mountains provide significant geographical isolation and limited gene flow between central and eastern populations of greater horseshoe bats , central east , and southwest (SW) based on neutral genetic markers , Henan (HeN), Shanxi , Shandong (SD), Shanxi (SX), Zhejiang (ZJ), Jilin , Yunnan (YN), and Gansu (GS) provinces  and gene cloning were used to amplify full‐length MHC class II‐DRB exon 2 in each bat from gDNA. More details are described in Li et al.  following the manufacturer's standard protocol. Different bat species  were aligned using Geneious 9.0 to complement the conserved regions of intron 1 and intron 2. Then, species‐specific primers (0702‐1F: 5’‐GGGCGGATTAAAGATGAA‐3′) of intron 1 and intron 2 (0702‐1R: 5’‐ACACTGTGTCCCGAGCAT‐3′) were designed manually in Primer 5.0  to amplify the whole exon 2 region by using the gene sequence of i et al. . We treaR. ferrumequinum; the details are described in the supplemental information  to distinguish real sequence variants from sequencing errors or PCR chimeras .The paired‐end reads were merged using FLASH v1.2.11  were used from a previous study  and populations (12 populations)  , 19 Rhinolophus episcopus alleles, and 13 Rhinolophus siamensis alleles  and nonsynonymous (dN) substitutions per synonymous and nonsynonymous sites  , z2 (steric bulk), z3 (polarity), z4, and z5 (electronic effects)  with a correction for sample size was estimated using a rarefaction method with the “hierfstat” package  using FSTAT 2.9.4 , and then used the p.adjust function of the “fdrci” R package to adjust the To investigate whether spatial variation in selection has influenced the geographical variation of MHC class II DRB genes, we compared the genetic structures between MHC and microsatellites across populations. First, for both markers, population differentiation was calculated using Jost's D (Dest) , we performed Mantel tests to estimate the relationships between Dest/(1 − Dest) and geographic distances for MHC and microsatellites independently. We also tested whether the slopes of the regression between Dest/(1 − Dest) and geographical distance based on the two markers were significantly different by using the “simba” package  retained in DAPC was chosen to maximize the α‐score (using the optim.a.score function of adegenet). According to the α‐score optimization, 35 PCs and 11 discriminant functions were retained for MHC, and 11 PCs and 2 discriminant functions were retained for microsatellites.2.10Climatic parameters were considered to reflect pathogenic landscape variation to an extent. To determine the relative contributions of geographical distance and climatic factors to the genetic differentiation and MHC variants, we first downloaded 19 bioclimatic variables (refer to Table 2) of <0.5 as indicating that no multicollinearity existed. Thus, the parameters of MHC variations  and the number of supertypes  were retained for the following analysis with ρ2 values <0.5  .Fourth, we used multinomial log‐linear (MNL) models to further verify the influence of each climate factor on different MHC variant parameters in the R package “nnet,” and analysis of variance was used to obtain the R. ferrumequinum may be correlated with climate variables, we conducted two analyses. (1) The partial Mantel test (Spearman statistics) was used to estimate the correlation between climate factors and MHC diversity with 9999 permutations using the “vegan” package , indicating the presence of at least four class II loci in R. ferrumequinum. The number of MHC alleles (h) varied substantially across populations, from 6 in ZJ to 68 in FD and JL2. The NaI of R. ferrumequinum ranged from 0.17 to 0.565 per population. However, other MHC polymorphism parameters showed little difference between populations  in all lineages, and SW also had the highest number of private alleles, but the NaI value was the lowest. The NE lineage tended to have the lowest numbers of private alleles and AR values, and the CE lineage showed the highest number of private alleles and AR, NaI values  and non‐ABS (dN/dS range: 1.06–3.669) in all populations, but no significant difference was found in BJ or ZJ. In total, significant positive selection was detected at the ABS of R. ferrumequinum , and no significant negative selection (Z = 0.35) was detected at the non‐ABS  to 1 (JL1 vs ZJ) Figure . NMDS alr = 0.375, p = 0.017). The pattern of isolation by distance was significant for MHC . The partial Mantel test showed that there was still a strong relationship between pairwise Dest (MHC) and geographic pairwise distances, even after controlling for the effects of neutral microsatellites .The Mantel test showed a significant correlation between Dest values of MHC and microsatellites  and relatively low differentiation between CE and SW (Dest = 0.232). Genetic differentiation of microsatellites showed different patterns, with medium differentiation between CE, NE, and SW lineages  and low differentiation between CE and NE (Destmicrosatellites = 0.167). In both markers, medium differentiation occurred between NE and SW. However, the genetic differentiation was higher between CE and NE for MHC than for microsatellites, and the level of genetic differentiation was lower between CE and SW for MHC than for microsatellites. Although the MHC genetic differentiation was greater than in microsatellites, pairwise Dest values of MHC fell within the 95% confidence interval of microsatellites (microsatellite 95% CI: 0–0.714), and no significant difference was shown by the bootstrap method for either of the markers.For genetic lineages of R. ferrumequinum.The results of DAPC based on MHC showed an admixture structure between populations but three distinct clusters of genetic lineages. For microsatellite loci, the results of DAPC showed no clear structural characteristics between populations but separated the SW lineage along the first  axis and showed partial overlapping between NE and CE lineages Figure . In cont3.6R. ferrumequinum from the current study range. Significant relationships were detected between P and three climate factors , ST2 and BIO15, ST5, and BIO2, as well as ST6 and BIO3  between MHC diversity and climate factors when controlling for the genetic structure of microsatellites.Genetic differentiation of MHC was not correlated with any climate factor or geographic distance in the MRM analysis. Moreover, the partial Mantel test showed a significant correlation  affected ST2, ST5, ST6, and P. In addition, the effect of climate factors on ST2 and ST5 was not influenced by phylogenetic signal (λ around 0)  than in northern China (Jilin and Liaoning) , suggesting regional and climate effects , a clear positive effect of the temperature factor on the presence of MHC genotypes was found, and the MHC heterozygous individuals were more often found at locations with lower temperatures during the wettest period of the year (Stefanović et al., Moreover, a previous study has already found significant effects of mean annual temperature and precipitation on the distribution of some MHC proteins/alleles in hares (R. ferrumequinum, with widespread geographical distribution and three genetic lineages. Through comparing an adaptive genetic marker with a neutral marker, we found that diversifying selection has had a major effect on MHC genes rather than demographic processes among populations, and some homogenization selection may have influenced the genetic lineages of R. ferrumequinum. By integrating climate factors, genetic structure, and MHC variation and supertypes, it appears that ambient temperature and humidity may act as putative fitness factors affecting MHC variants. This will increase our understanding of the importance of adaptive genetic variation in wild animal populations and the relationship with climate factors, and the supertypes analysis also provides new ideas for animal conservation. The results may help to conserve wild populations to cope with climate change or improve the disease resistance of wild animals through genetic manipulation technology (Johnson et al., In conclusion, we investigated the adaptive MHC gene of We declare that we do not have any commercial or associative interest that represents a conflict of interest in connection with the work submitted.Appendix S1.Click here for additional data file.


Panax quinquefolius L., is an important medicinal plant with multiple pharmacological effects and high nutritional value. American ginseng from different geographical origins varies in quality and price. However, there was no approach for discriminating American ginseng from different geographical origins to date. In this study, a metabolomic method based on the UPLC–Orbitrap fusion platform was established to comprehensively determine and analyze metabolites of American ginseng from America and Canada, Heilongjiang, Jilin, Liaoning, and Shandong provinces in China. A total of 382 metabolites were detected, including 230 saponins, 30 amino acids and derivatives, 27 organic acids and derivatives, 25 lipids, 17 carbohydrates and derivatives, 10 phenols, 8 nucleotides, and derivatives, as well as 35 other metabolites. Metabolite differences between North America and Asia producing areas were more obvious than within Asia. Twenty metabolites, contributed most to the differentiation of producing areas, were identified as potential markers with prediction accuracy higher than 91%. The results provide new insights into the metabolite composition of American ginseng from different origins, which will help discriminate origins and promote quality control of American ginseng.American ginseng,  Metabolite differences between North America and Asia producing areas were more obvious than within Asia. Twenty metabolites, contributed most to the differentiation of producing areas, were identified as potential markers with prediction accuracy higher than 91%. The results provide new insights into the metabolite composition of American ginseng from different origins, which will help discriminate origins and promote quality control of American ginseng. American ginseng began to be cultivated in China since the 1980s , HLJ (Heilongjiang province), JL (Jilin province), LN (Liaoning province), and SD (Shandong province), we established a metabolomics approach based on UPLC Q–Orbitrap MS to comprehensively analyze the chemical composition of American ginseng. Furthermore, multivariate statistical tools were used to investigate the differences in metabolites that could contribute to the geographical origin of American ginseng. The results will provide more foundation and reference for evaluation and discrimination of American ginseng.22.1The samples for the discrimination of geographical origin were taken from five producing areas which were the main cultivating regions of American ginseng . Each producing area selected 3–6 sampling points. The sampling points were scattered in each producing area, which can represent the main regions of American ginseng products. The sampling principle and design are described in detail in Supplementary Information Section 1 Figure .Nineteen origins of American ginseng were collected from five different producing areas in October 2021. Ninety individual plants were randomly harvested in each origin, and each 15 individual plants were mixed as one replication. All the voucher specimens were deposited in the laboratory of Institute of Special Animals and Plants, Chinese Academy of Agricultural Sciences, Changchun, China. Each sample's detailed information is given in Table 2.2The samples were washed and dried at 38°C until a constant weight was achieved, then main roots were separated and pulverized into powder, and passed through a 60‐mesh sieve. A quantity of 0.1 g accurately weighed fine powder was extracted with 10 mL of 70% (v/v) methanol in an ultrasonic water bath for 60 min , equipped with an ACQUITY Premier HSS T3 column . The column oven was maintained at 35°C. The mobile phases consisted of 0.1% formic acid in water (A) and 0.1% formic acid in acetonitrile (B). The mobile phase system was run in the following gradient program: 0–2 min, 0% B; 2–4 min, 0%–3% B; 4–6 min, 3%–15% B; 6–8 min, 15–25% B; 8–25 min, 25%–39% B; 25–32 min, 39%–60% B; 32–39 min, 60%–99% B; 39–41 min, 99% B; 41–42 min, 99%–0% B; 42–45 min, 0% B. The flow rate was 0.3 mL/min, and the injection volume was 2 μL.1 scan and a resolution of 15,000 for HCD‐MS2 scan. The MS/MS product ions under mixed NCE  of 30%, 40%, and 55% were recorded to acquire more fragmentation information.High‐resolution MS data were recorded on an Orbitrap Fusion mass spectrometer (Thermo Fisher Scientific). Spray voltages were set at 3.7 kV and 2.7 kV for positive and negative modes, respectively. Other source parameters were set as follows: Ion Transfer Tube temperature, 320°C; Vaporizer temperature, 320°C; Sheath gas, 40 arbitrary units; Auxiliary gas, 5 arbitrary units. The Orbitrap analyzer scanned over a mass range of m/z 85–1500 at a resolution of 60,000 for MS2.4tR‐m/z pair) and normalized peak area, was finally obtained. Then, preprocessed data were imported into SIMCA‐14.1 (Umetrics) for PCA and OPLS‐DA analysis. Volcano plot was constructed on a cloud platform (https://cloud.metware.cn). Venn and heatmaps were generated by TBtools software .The acquired mass data were imported to Compound Discoverer 3.1 (Thermo Fisher Scientific) for peak detection and alignment. A data matrix, involving the information of the sample name, peak number . The score plot Figure  shows thclosely related species of P. quinquefolius L., Panax ginseng from Gangwon, Gaeseong, Punggi, Chungbuk, Jeonbuk, and Anseong in Korean could also be differentiated by metabolites based on LC–MS data  was a type of supervised classification tool, which can effectively eliminate irrelevant influences and screen for differential metabolites among comparison groups , the original R2Y and Q2Y are always substantially higher than the corresponding permutation values, indicating the models were not overfitting  and variable importance in projection (VIP≥1) score ‐3‐(3‐hydroxy‐4‐methoxyphenyl)‐prop‐2‐enoyl] oxy} cyclohexane‐1‐carboxylic acid (M127), and PPD‐(Glc‐Glc)‐Glc‐Glc‐Butenoyl‐Mal (M261). Four shared differential metabolites were identified between JL and the other four producing areas, including Pseudo‐ginsenoside‐RT5 (M208) and three isomers of PPT‐(Glc‐Glc)‐Glc . Moreover, caffeic acid (M94) and PPD‐20‐Glc‐3‐Glc‐Glc‐Butenoyl (M341) was the only shared differential metabolites identified for LN and SD, respectively, compared with the other four producing areas.Venn diagram showed the shared differential metabolites of comparisons between a certain producing area versus the other four Figure . A total1 (PPT‐20‐Glc‐6‐Glc) with two sugar units and Re (PPT‐20‐Glc‐6‐Glc‐Rha) with three sugar units was visibly lower in four origins compared to other six . As shown in the heatmap Figure , the sam3.32, ginsenoside Rg5, pseudo‐ginsenoside F11, and quinquenoside R1 were the typical compounds for distinguishing Wisconsin American ginseng (USA) samples from other areas. Among them, quinquenoside R1 (PPD‐Glc‐Glc‐Glc‐Glc‐Ac) with four glucose units had higher content in USA samples in both Chen et al. and our work. However, quinquenoside R1 was not gained very high VIP score in our study. Compared with Chen's results, three new chemical markers were found for the discrimination of American ginseng between UC and China.Based on the results of HCA Figure , only UCE)‐3‐(3‐hydroxy‐4‐methoxyphenyl)prop‐2‐enoyl]oxy}cyclohexane‐1‐carboxylic acid (M127), 4‐Oxoproline (M44), and PPT‐(Glc‐Glc)‐Glc (M133) were identified as potential markers for discrimination of Heilongjiang and Jilin samples ‐9,12,13‐Trihydroxy‐15‐octadecenoic acid (M271) were identified as potential markers for discrimination of Jilin and Liaoning samples , and 491‐20‐Glc‐6‐Glc (M120) were identified for discrimination of Jilin and Shandong samples , and PPT‐(Glc‐Glc)‐Glc‐Glc (M163) were identified for discrimination of Heilongjiang and Shandong samples  analysis was used to evaluate prediction accuracy. Ultimately, based on the criteria for the area under the curve (AUC) value over 0.9 which provided excellent prediction accuracy ‐Ginsenoside Rg2 makes a more obvious distinction between the two regions in our study. Si (It was reported that the content of 20(S)‐Ginsenoside Rgtudy. Si  screened4In this study, a metabolomic method based on the UPLC–Orbitrap fusion platform was established to comprehensively determine and analyze metabolites of American ginseng. Totally, 382 metabolites were identified in American ginseng from five producing areas. There are larger number of differential metabolites between UC and Chinese producing areas than within four Chinese producing areas. Twenty potential chemical markers were identified for the first time, which could effectively discriminate (ROC >91%) American ginseng from different producing areas. The results provide new insights into the metabolite composition of American ginseng from different origins, which greatly benefits the quality control and geographical origins discrimination of American ginseng.Shifeng Pang: Data curation (lead); investigation (lead); software (lead); visualization (lead); writing – original draft (lead); writing – review and editing (lead). Xiangmin Piao: Data curation ; software . Xiaohao Zhang: Writing – review and editing . Xiaolin Chen: Data curation (supporting); visualization (supporting); writing – review and editing (supporting). Hao Zhang: Project administration ; supervision ; writing – review and editing . Yinping Jin: Writing – review and editing . Zheng Li: Software ; visualization ; writing – review and editing . Yingping Wang: Project administration ; resources (lead); supervision (lead); writing – review and editing .This work was supported by grants from the Science and Technology Development Project of Jilin Province, Grant/Award Number: 20230505028ZP; the Scientific and Technological Innovation Project of the Chinese Academy of Agricultural Science, Grant/Award Number: CAAS‐ASTIP‐ISAPS‐2021‐ISAPS; and the National Key Research and Development Program of China, Grant/Award Number: 2021YFD1600901.The authors declare that there is no conflict of interest.This study does not involve any human or animal testing.Table S1Click here for additional data file.Table S2Click here for additional data file.Table S3Click here for additional data file.Appendix S1Click here for additional data file.