During meiosis, crossover rates are not randomly distributed along the chromosome and their location may have a strong impact on the functioning and evolution of the genome. To date, the broad diversity of recombination landscapes among plants has rarely been investigated and a formal comparative genomic approach is still needed to characterize and assess the determinants of recombination landscapes among species and chromosomes. We gathered genetic maps and genomes for 57 flowering plant species, corresponding to 665 chromosomes, for which we estimated large-scale recombination landscapes. We found that the number of crossover per chromosome spans a limited range (between one to five/six) whatever the genome size, and that there is no single relationship across species between genetic map length and chromosome size. Instead, we found a general relationship between the relative size of chromosomes and recombination rate, while the absolute length constrains the basal recombination rate for each species. At the chromosome level, we identified two main patterns (with a few exceptions) and we proposed a conceptual model explaining the broad-scale distribution of crossovers where both telomeres and centromeres play a role. These patterns correspond globally to the underlying gene distribution, which affects how efficiently genes are shuffled at meiosis. These results raised new questions not only on the evolution of recombination rates but also on their distribution along chromosomes. Meiotic recombination is a universal feature of sexually reproducing species. During meiosis, crossovers play a fundamental role for the proper segregation of chromosomes during meiosis and reshuffles alleles among chromosomes. How much variation in recombination is expected within a genome and among different species remains a central question for understanding the evolution of recombination. We characterized and compared recombination landscapes in a large set of plant species with a wide range of genome size. We found that the number of crossovers varied little among species, from one mandatory to no more than five or six crossovers per chromosomes, whatever the genome size. However, we identified two main patterns of variation along chromosomes (with a few exceptions) that can be explained by a new conceptual model where chromosome length, chromosome structure and gene density play a role. The strong association between gene density and recombination was already known, but raised new questions not only about the evolution of recombination rates but also on their distribution along chromosomes. Meiotic recombination is a universal feature of sexually reproducing species. New haplotypes are passed on to offspring by the reciprocal exchange of DNA between maternal and paternal chromosomes, known as crossovers (COs). However, recombination landscapes—the variation in recombination rates along the chromosome—are not homogeneous across the genome and vary among species –4. MeiotIn addition to their function in meiosis, variations in recombination rates affect genome structure, functioning and evolution through direct effects–such as mutagenic effects, bias-conversion, and ectopic exchanges–and indirect effects by modulating the efficacy of selection , and it In plants, recombination rates are believed to be higher in species with smaller genomes because the linkage map length is independent of genome size and the number of chromosomes explain more variation than genome size . SeveralRecently, a meta-analysis explored large-scale recombination landscapes among eukaryotes and paved the way for identifying general patterns . They foTo overcome these limitations we gathered the largest recombination landscape dataset in flowering plants, to the best of our knowledge. We started from raw data by combining genetic mapping from pedigree data and chromosome scale genome assemblies, from which we estimated recombination maps–more precisely the sex-averaged rate of COs along chromosomes–using the same standardised method in all species, in order to ask the following questions. What is the range of COs per chromosome in plants? Is the distribution of COs shaped by genome structure  and if so is there a universal pattern? Since recombination is negatively associated with TEs and recombination hotspots have been found in gene regulatory, are recombination landscapes always associated with gene density? What are the consequences of recombination heterogeneity on the extent of genetic shuffling? Overall, we found that recombination landscapes in plants are more diverse and more complex than previously thought. We identified two main patterns that are correlated with, and which may emerge from, the gene density distribution. We show that the positive association between gene density and recombination rates globally improves the genetic shuffling of coding regions, which raises new questions about the evolution of recombination.Capsella rubella, which had a high-quality scaffold-level assembly of pseudo-chromosomes). We remapped markers on the reference genome for 14 species for which genomic positions were not known or were mapped to an older assembly. After making a selection based on the number of markers, marker density, and genome coverage, and after filtering out the outlying markers (see Nelumbo nucifera), 15 monocot species and 41 eudicots. From the literature, we also obtained data on the centromeric index for 37 species, defined as the ratio of the short arm length divided by the total chromosome length . Estimates at a scale of 1 Mb yielded very similar results  to 16.9 cM/Mb in squash (Cucurbita maxima). In agreement with previous studies We are sorry that we cannot be more positive about your manuscript at this stage. Please do not hesitate to contact us if you have any concerns or questions.Yours sincerely,Ian HendersonAssociate EditorPLOS GeneticsKirsten BombliesSection Editor: EvolutionPLOS GeneticsReviewer's Responses to QuestionsComments to the Authors:Please note here if the review is uploaded as an attachment.Reviewer #1: It is now possible to analyse genetic and physical maps of organisms, as the literature now contains suitable data from multiple species. This manuscript analyses such data from larger numbers of plant species than previous studies , and describes results for the broad-scale recombination landscapes. However, it does not actually use the analyses to ask interesting questions, which I had hope to see. Some questions might include the followingDo chromosome arms have an obligate crossover?How often do chromosome arms have multiple crossovers, versus a single one (as I believe is the case in C. elegans)?Do related species differ . This question is discussed near the very end of the text, but is not mentioned as a question earlier, making it appear that the ms is entirely descriptive. The ms does not seem to mention that some of the species studied are close relatives, and that this can be helpful in studying such questions.How large are pericentromeric regions with low recombination rates in plants, and how much do they differ between related species?Do selfers have higher recombination rates per physical length of chromosome than closely related outcrossers?Are recombination rates the same in male versus female meiosis? This is finally mentioned in line 574, but it is not made clear until then that the data analysed are sex-averaged rates.Instead, the ms presents rather dull statistical analyses. The results have value, but they appear mainly to confirm findings that were already well established, and the ms does not make very clear what new findings now emerge, or show what we can now understand from the results that was not already known. More than once in the text “new insights” are claimed, but it is difficult to find them, partly because of the length of the text, which is also long-winded and repetitive in several places. These problems could be ameliorated by outlining in the Introduction what questions the authors set out to study. As written, this section gives the impression that their aims were purely descriptive, which is not an encouragement to read the text. The ms also tries to interest the reader by making claims to novelty, rather than describing some interesting questions. For example, I feel that it is too strong to say that “the broad diversity of recombination landscapes among plants has rarely been investigated… and the diversity of the resulting landscapes among species and chromosomes still need[s] to be assessed“, although a formal comparative genomic approach may be new and valuable. A further value from analysing more species is that exceptions to accepted generalisations may be detected, and this study did produce a few examples of such exceptions. Overall, I doubt that readers need a length Introduction to tell them that recombination patterns are interesting in relation to evolution, including evolution of patterns in genomes, such as regions with different repetitive sequence density, and consequently gene density, and with differences in GC content. A shorter Introduction could give a better idea of what is new from this study.At least several of the conclusions are just confirmations of what was already known. The following examples illustrate this problem, and my comments also include some other issues for some of them  that a distal bias is “universal for chromosomes larger than 30 Mb” . The main advance seems to be that this study finds that Nelumbo nucifera and Camellia sinensis are exceptions to this pattern, with the highest recombination rates found in the middle of their chromosomes.The result is described in a rather unhelpful manner, without taking chromosomes morphology into account. The text states that, for larger chromosomes, crossovers tend to occur (not “accumulate”) at the ends of chromosome, while the central regions have less. However, this would be correct only for metacentrics, and the centres of chromosome presumably means centromeric and pericentromeric regions, but this is not made clear. It is also not made clear that these are completely recombination-free regions.The extent of a larger pericentromeric region  is known to vary greatly between species, but it is not well described in the ms, and only examples are shown, with rather subjective criteria to define the different regions. It would, in principle, be possible to define them less subjectively, though this might not be easy. At least, it would be good to mention whether this was attempted. A further problem is that regions are shown in figures, rather than tables giving estimates of genome region sizes and recombination rates, and as relative sizes are often used, it is difficult to understand what sizes of pericentromeric regions (for example) are found in plants.It is also not a new discovery that low recombination regions tend to have low gene density. The Discussion acknowledges this, but it is strange to first describe this as if it is a new result, only to later mention that it is not. If the Introduction had laid out some questions, this could be avoided. Problems like this also make the text longer than necessary.2. Recombination is unevenly distributed in genomes. Therefore one should not write that “We showed that” this is the case. Once can write “We confirmed that” (or something similar). This text also uses vague terminology “how genetic variation is shuffled during meiosis”, but the word recombination already exists, so it would be better to be precise. If at some point the meaning is gene conversion, this should be used. However, I think that the text mentions conversion only in passing, and it is not considered seriously.In line 538, I am not sure why thw word “prediction” is used . Is this really a prediction, or are you trying to say that you did not confirm the view that this pattern is shared by all plants? If so, references are needed to assertions that all plants share this pattern.The Discussion section need not repeat so much of the results. It might also mention that recombination rates vary between individuals of the same species, including from the effects of rearrangements, especially inversions, so it would be good to mention that the data are currently often from just a single maternal and paternal parental individual of each species . Hotspots should also be mentioned, if only to make clear that this study did not attempt to detect them.474 It is proposed that in angiosperms crossovers may be initiated in gene regulatory sequences, and it is suggested that this “sheds new light on the evolution of recombination landscapes”, but without saying what new light is shed, other than this suggestion. The suggestion is not evaluated further, and I did not understand if it is a speculation, based on the correlation between recombination and gene density mentioned in this paragraph (or on some other observations). However, based on later text (line 613), I suspect that the intended meaning is that the results are consistent with such a proposal that was already published by others.However, as the correlation must be strongly affected by the lower gene densities in genome regions with low recombination rates, which lead to accumulation of transposable elements and other repetitive sequences, it would seem difficult to disentangle this from the suggested mechanism. Line 628 states that “The positive association of COs and gene regulatory sequences, including fine-scale correlations, appears more robust”, which is too vague. It seems unlikely that the effect is stronger than the very marked and consistent effect of low recombination rates on repetitive sequence density .Regions with high recombination rates may, however, allow patterns in crossover localisation to be detectable, and I believe that this has been studied, for example in maize (e.g. papers by Dooner and colleagues) and also in Mimulus guttatus . Line 621 finally mentions the problem of other correlated factors. I think that the authors should revise their text so that it does not first set up an untestable idea and then mention that it is untestable. Instead, it will be preferable to set up some interesting questions early in the text, tell readers what is currently known, and then describe analyses that help understand things better than before.Dooner, H., & He, L. (2008). Maize genome structure variation: Interplay between retrotransposon polymorphisms and genic recombination. Plant Cell, 20(2), 249-258. doi:10.1105/tpc.107.057596Fengler, K., Allen, S. M., Li, B., & Rafalski, A. (2007). Distribution of genes, recombination, and repetitive elements in the maize genome. Crop Science, 47(Supplement), S-83-S-95.Yao, H., Zhou, Q., Li, J., Smith, H., Yandeau, M., Nikolau, B. J., & Schnable, P. S. (2002). Molecular characterization of meiotic recombination across the 140-kb multigenic a1-sh2 interval of maize. Proceedings of the National Academy of Sciences of the USA, 99, 6157-6162.Tenaillon, M. I., Sawkins, M. C., Anderson, L. K., Stack, S. M., Doebley, J. F., & Gaut, B. S. (2002). Patterns of diversity and recombination along chromosome 1 of maize (Zea mays ssp. mays L.). Genetics, 162, 1401-1413.Another comment that applies throughout the text is that recent papers are cited for concepta and understanding that are not new. In such cases, the text should make clear that the citation is to a review paper. For example, the text gives the impression that Marand et al. (2019) discovered that gene density and recombination rates are both correlated with transposable elements (meaning densities of transposable elements). This has been known for a long time, and was reviewed in 1994 by Charlesworth et al. .In first mentioning heterochiasmy, it seems strange not to mention whether the papers cited refer to plants or just to studies in animal species. It is explained later that Melamed-Bessudo et al. (2016) showed that it is not universal in plants, but the text does not explain what the term might mean in plants, and that hermaphrodites may have different crossover patterns in male and female meiosis, so readers may be puzzled.3. Similarly, I was surprised to read that “We were intrigued to notice that [within species]the chromosome-wide recombination rate is proportional to the relative size of the chromosome”. I was under the impression that this was already known.It is illustrated in Figure 2D, which shows the new results, which are potentially interesting, as they relate to the question of how often arms have multiple crossovers. This figure analyses the excess of crossovers, defined as the linkage map length minus the 50 cM expected if one crossover per arm is obligate), and shows that it correlates positively with the chromosome’ physical sizes divided by the average chromosome size for the species, which they term the “relative chromosome size”. Such an effect is not a new result.However, as I understand it, an obligate crossover is expected on each arm. If so, the number of excess crossovers, in addition to this one, should be analysed per arm. Even if my recollection about this is incorrect, the text should make clear what is known from previous studies, and why the present study uses chromosome, not arm, lengths. Line 136 mentions that the centromeric index was known for the chromosomes of 37 species, but then it remains unclear how these data were used, and also whether results can be used from the species where no such data were available. Line 285 mentions that recombination rates were negatively correlated with the distance to the nearest telomere, which seems to suggest that metacentrics may have been analysed as such, but I could not see this clearly explained.Line 300 states that that (in my wording) the centromere regions almost universally showed low recombination rates, but this is not completely clear in Figure 4, where large low recombination rate regions in several species, for example Vigna unguiculata, appear not to overlap the centromeres. If this is a real biological observation, the statement seems incorrect.Given these possible problems with the data, I was not convinced of the value of the formal modelling analysis of the effect of the centromere in suppressing recombination, and the comparison with less simple models that suggest that telomeres may also affect patterns. Such effects are plausible, but I feel that some of these plant data do not add valuable and solid support.Another weakness is the lack of any mention of differences between male and female meiosis, and another is the lack of any mention of outcrossing rates.I wondered why these papers were not cited, or other papers about Arabidopsis lyrate or helleri, which may have genetic map information.Hellsten, U., Wright, K. M., Jenkins, J., Shu, S., Yuan, Y., Wessler, S. R., . . . Rokhsar, D. S. (2013). Fine-scale variation in meiotic recombination in Mimulus inferred from population shotgun sequencing. Proceedings of the National Academy of Sciences of the United States of America, 110(48), 19478–19482. doi:10.1073/pnas.1319032110Kawabe, A., Hansson, B., Forrest, A., Hagenblad, J., & Charlesworth, D. (2006). Comparative gene mapping in Arabidopsis lyrata chromosomes 6 and 7 and A. thaliana chromosome IV: evolutionary history, rearrangements and local recombination rates. Genetical Research, 88, 45-56.Hansson, B., Kawabe, A., Preuss, S., Kuittinen, H., & Charlesworth, D. (2006). Comparative gene mapping in Arabidopsis lyrata chromosomes 1 and 2 and the corresponding A. thaliana chromosome 1: recombination rates, rearrangements and centromere location. Genetical Research, 87(2), 75-85. doi:10.1017/S0016672306008287Minor problems with the English, or vague wording or unclear statements1. In English, it should be “correlated with” (not “to”).2. The word ‘drive’ should be avoided, as it is very vague. For example, the meaning is not clear in the phrase “Chromosome length drives the basal recombination rate for each species”3. In line 182, it should read “regression lines for species with at least 5 chromosomes mapped, 5-26 chromosomes per species, 55 species).4. Line 232 Genomic distances (Mb) were scaled between 0 and 1 (divided by chromosome size) to compare chromosomes with different sizes.5. It is difficult to make out the meaning of the text starting in line 247. I think it means the following: “Each chromosome was divided in (it should read “into”) ten bins, each one 10th of the chromosome’s total physical size.” The relative recombination rate is the log-transformed ratio of the expected relative genetic length  divided by the observed relative genetic length of the bin  on the left correspond to each broken stick chromosome” — maybe it means “each chromosome”. Also (in line 244) “Relative recombination rates along the chromosome were estimated in ten bins using the broken stick model.6. In English, one needs to say “divided into” (not “in”). Also “pooled into” , which refers to associations between two or more liked variants. Line 57 should be corrected, as the text refers to the latter, but uses the former (“Recombination…. breaking the linkage between neighbouring sites and creating new genetic combinations”). The sites remain linked, but not in LD. The sentence is also confusing by adding “upon which selection can act”, because selection acts on single variants, and the authors are trying to say that new genetic combinations might be more (or less) favoured by selection than the non-recombinant combinations .8. It is a sweeping statement to say that “Plant genomes contain large regions with suppressed recombination”, depending strongly on how many plants have good data on physical and genetic maps, so line 92 ought to mention the number on which this is based, and give readers at least a rough idea of what is meant by “large”. There is no need to add the obvious remark that this impacts genomic averages .9. Phrases that are unnecessary . After filtering based on the marker numbers, densities, and genome coverage, and after filtering out the outlying markers (maybe meaning outlier markers by a criterion that needs to be explained), we produced 665 Marey maps (reference needed) for 57 species (2-26 chromosomes per species); marker numbers per chromosome  ranged from 31 to 49,483..Reviewer #2: In this paper, the authors seek to decipher genomic patterns of recombination across a large (57 species) dataset of sequenced plant genomes coupled with genetic maps. Their meta-analyses lead to several novel observations.I thoroughly enjoyed reading this manuscript, and I congratulate the authors on a really fine paper. It will be, in my view, a very welcome addition to the literature. In the surest sign of flattery, I’m a jealous that I did not think of doing such a neat analysis.Accordingly, I have only minor comments that the authors may wish to address in revision. Most of the comments are very minor, indeed. They are offered both as an attempt to clarify the few areas of the text that I found difficult to digest and probably out of an abundance of enthusiasm for this work. I leave it to the authors to decide if my suggestions offer improvements or are better ignored…Minor Comments:- Line 48 – Unlike most of the rest of the paper, I found this sentence hard to read and digest. Reword, rework or shorten? Btw I’d use “in” instead of “to” (“in the production”)- Line 79 – This last sentence of the paragraph is really indirect and therefore pretty tough to read. I’m not really sure what manipulations are being considered here… Rewrite?- Line 100 – as a reader, I found that a better link between the two sentences on this line could have been helpful. Maybe something as simple as “Haenel et al. considered chrosomome length, found blah blah blah and suggested a simpler telomere-led model. That model included a universal bias…”- Line 118 – I’d use “about” instead of “on”- Line 125 – If this is reasonable, I’d love to see the filter characteristics hinted at here, even though there is a good description in the methods. That is something like “… marker density (at least 50 per chromosome), genome coverage (blah blah)”- Line 701 – I’m a bit confused by the what was done when marker sequences were not available and also how many species fell into this category. I’m not concerned at all – this is a careful study – but it’d be nice understand better.- Figure 2 – It might be helpful to have X-axis say “Mean chromosome size” where appropriate . The legend is very clear, though.- I love Figure 3. It blows my mind how consistent the patterns are between the dashed lines (genome wide) and an individual chromosome. It is bizarre and neat and thought provoking. It might be nice to report mean chromosome size (in the legend or in the figure), given that the species are ordered in that matter. It just makes me curious…- Figure 4, since patterns seem to correlated with mean chromosome size, would it be worth adding that value after each species name? As a reader, it would help me to see the pattern and better digest the text from ~lines 213 to 227 and figure 5a, etc).- Figure 5A – this may make the graph too crowded, but it’d be nice to be able to compare dots in 5A to figure 4. So, it’d be nice to have the dots labelled. If that is too much, the authors might want to consider labelling a few species . Personally, I’d love to know what the outliers are in this graph!- Lines 284 and following. It’d be nice to cite Figure 6A and Figure 6B separately after the word descriptions of the patterns.- Line 296. I could not figure out what the “species correlation” referred to. Sorry if I missed this, but it’s worth another look to be sure it is clear.- I’m kind of shocked that M3 is favored over M2, as isn’t one CO per arm necessary for mechanism? Hence, I’d a priori predict M2 > M3. I don’t think this contrast is explicitly discussed in the Discussion , but I think it should be.- Figure 8: It’d be nice if the legend clearly stated which graph is which. I think Figure 8b is the distal recombination pattern, but I’m not 100% sure. It’d be great to have sample sizes on the graph too .- It’s pretty clear in the M&M, but on line 419, it might be nice to mention that rintra is a single value per chromosome. On my first reading, I was thinking it was some sort of transformation of cM between genes...- The analysis of gene distances is very thought provoking!- Line 488 – What the heck is going on with fungi and animals! It’s certainly not necessary, but can the authors provide a quick description or explanation. They have piqued my curiousity.Again, I do not consider any of my comments to be critical for publication, and I want to again congratulate the authors on a thorough and interesting study.Reviewer #3: This manuscript by Brazier and Glémin uses a comparative approach to investigate variation in recombination landscapes in flowering plants. Their study used genetic map data from 665 chromosomes in 57 species of angiosperms. At the whole chromosomal level, they found a negative correlation between chromosome size and recombination rate (cM/Mb) with a strong species-specific effect. They also found that CO excess on chromosomes was more correlated with their relative size to other chromosomes in the genome rather than their absolute size, and that this effect was consistent across species. When investigating crossover landscapes, they found that landscapes were similar within species but strongly varied between species. CO rates were not uniform across chromosomes and were often more likely to occur at the distal ends of the chromosomes, with larger chromosomes tending to have a higher “periphery bias” of COs. However (as with most things in nature), this general pattern did have a number of exceptions. The authors then investigated the joint effect of telomeres and centromeres on CO distribution, finding the strongest support for a model that incorporated the effects of the telomere, centromere and one CO per chromosome. The authors found that recombination rate increased with gene density. Finally, the authors showed that genetic shuffling was positively correlated with linkage map length, and that there was a small negative effect of the periphery-bias ratio. These effects were slightly higher when modelling genetic shuffling in terms of gene distances. Whilst the investigations here are largely correlative rather than revealing mechanisms, this study provides a useful foundation for further investigation of broad drivers of recombination rate and landscape variation across a wide range of taxa.This paper is the most comprehensive and well analysed that I have read on this topic, and generally it is well-written and well structured, particularly the introduction and discussion. I’m impressed by the sheer breadth of analyses. Nevertheless, there are parts of the methods & results that lack clarity, which in turn leads to issues with reproducibility. In particular, a lot of the statistical models are not well described – model structures should be made explicit in the methods and/or results, rather than providing a general text for statistical analyses at the end of the methods. I would emphasise that providing code and data (where possible) would improve these issues.I had many comments and suggestions - those marked ** should be addressed by the authors in a revised version.ABSTRACT/INTRODUCTIONLines 32-33: The authors should be clearer what they mean by “relative size” here (i.e. relative to the rest of the genome) and why this result is interesting.Lines 48-52: In the first sentence, I would add the term “crossing-over” or “crossover” here to set up the rest of the introduction. In the second sentence, I would briefly define landscape Lines 61 – 63: Indicate that you are defining assurance in this sentence.Line 73: Can the authors briefly mention how recombination landscapes shape the distribution of TEs?**Lines 98 – 100: I found this statement confusing, as I can’t understand how independence between linkage map length and genome size means that recombination rates will be higher in smaller genomes. I also can’t make the link between this statement and the Stapley paper – I think they found that linkage map lengths were smaller in smaller genomes, but also that chromosome number explained more variation (i.e. increased chromosome number lead to longer maps due to a higher minimum bound of recombination due to crossover assurance). Perhaps I am wrong, but regardless, it might be worth double-checking this statement and explaining it more clearly.Line 100: on recombination rate, or landscape? Or both?**Line 102: Based on your argument here, it is not clear how chromosome length links to biases of CO towards the peripheries – please clarify.Line 117: Briefly define genetic shuffling and why it’s interesting – could even be mentioned earlier e.g. around lines 56 – 58.RESULTS**Lines 130 – 132: I don’t think this is described in the methods. Is there information on the number of progeny? I was curious about this but couldn’t find the information in the supplementary tables.Line 143: This header could be interpreted that smaller chromosomes have more crossover events rather than more crossovers per unit length. Perhaps “Smaller chromosomes have higher recombination rates than larger ones”?**Lines 153 – 169: Where are the methods for this LMER and what is the model structure? Is this what is being described in lines 831 – 850 of the methods? Throughout the paper, it needs to be clearer what models were run and what their fixed & random effect structures were in order to better interpret them.Line 155: Does this mean that there is no/low phylogenetic signal of recombination rate?Figure 1: This figure is busy. A suggestion for panel A: perhaps the dashed lines could be fit from axis to axis, to visually demarcate the 1 – 4CO expectations a bit better? For panel B, since this is the same data plotted twice, perhaps only the regression lines need to be visualised here rather than all of the points.**Figure 2: I found this figure confusing. Some suggested edits:Panel A could be wider to allow discerning of the slopes. I also struggled to understand what the isolines on the graph are showing even after reading several times. When using isolines, perhaps there is a need to define their values  – or perhaps they can be removed if making things too busy.Panel B: I cannot interpret what this is showing – are there really lines in panel A that have intercepts of less than zero?Panels B & C: I am very curious to see the error on these estimates.Panels B & C: maybe these panels might be better suited in the supplementary?Panel D: Again, very busy. Perhaps use of transparency of points or lines could make things clearer.**Figure 4: Accessibility issue for colour-blindness - the red dots may not be visible on the green background. The visual scale for the chromosome size is a unclear, particularly as appears to be log – could there be line traces instead of colours here? Also – perhaps I have misunderstood – but if the chromosomes were split into ten bins, then why does the resolution of recombination rate estimation look to be much higher than 1/10th of the chromosome on the horizontal lines?**Line 282 – 298: It seems that chromosome size was a strong correlate of recombination pattern, but I was curious if the authors tested other factors to rule out potential artefacts (e.g. differences in marker density) or to identify other biological correlates, such as ploidy? Was there a phylogenetic signal of this distal vs subdistal pattern?Figure 6: There is a lot of text to wade through in the legend - it would help the reader to put annotations, sample sizes, key on the figures to allow for faster interpretation. For example, putting A: Distal pattern, N = XX, B: Subdistal pattern, N = XX on the panels make it easier to interpret. The dashed lines for the unclassified patterns are very distracting – why not include this as another panel, or put it in the supplementary material? Panel C is tiny and needs a key, or at least x-axis labels. I like the schematics of the crossover distributions but it’s so tiny – perhaps include this as its own figure as it explains the model really well.Figure 7: A & B. There needs to be a higher contrast between the colours as it’s difficult to see the differences between blue and black. C. What do the colours represent here? Adjusting the point transparency and slight x jitter may improve the visualisation here.Figure 8: Same as Figure 6 – annotating the panels would be helpful.**Line 414 – I think it’s important for the authors to briefly define what genetic shuffling is and why it’s interesting to look at from an evolutionary perspective.Line 419: On the same chromosomeLine 422: less efficient = resulted in less genomic shuffling?Figure 9: see comments on Figure 7.DISCUSSIONLines 477 – 488: I’m a little puzzled by some of the statements here, so perhaps clarification is needed. I think it could be mentioned that crossover assurance will give a basal rate per chromosome of 50cM regardless of size, and then the authors can expand how the findings outlined here add to this established fact. Furthermore, I believe that in animals, larger chromosomes do have lower recombination rates within species… if I have misinterpreted this, perhaps the authors need to clarify their point better.Line 519: clarify what “association” means here… does chromosome pairing begin at the telomeres?Line 570: put “beam-film” in inverted commas and indicate that you are about to describe it.Line 582 – 583: It depends on the number of gametes measured and how many were male and female, which is easily done in dioecious species. I think authors should specify here “in angiosperms” and iterate here why heterochiasmy is difficult to investigate for the less plant-literate reader.METHODS**Lines 700 – 704: Indicate that this was from cytogenetic data. How is this information orientated correctly to the linkage map/genome sequence?**Lines 709 – 723: I think this paragraph requires a few improvements in reproducibility. Was this all done in the MareyMap package in the next paragraph? What was a ballpark criteria/example for anything that was outside the global trend?**Lines 724 – 737: Related to the previous comment, when looking at the plotted Marey maps , are the methods/results affected in any way by the “jitter” of Mb vs cM distances? I imagine that if the markers were not in the correct order in the linkage map , then the cM length of the chromosome may be overestimated, meaning that recombination rates would be consistently inflated. For example, in Camellia sinensis, the maps seems to be messier and therefore may accumulate local overestimations in recombination rate that will lead to a longer cM map than the true one, compared to Arabidopsis where the orders appear to be highly conserved between the genome and the linkage map. The potential impact of this should be discussed.**Lines 738 – 749: Please clarify here how the relative recombination rate is calculated – is this done for each segment? i.e. if the chromosome is 100cM and 80Mb, and the first segment is e.g. 10cM & 20Mb, then how would the value be calculated? The verbal argument is unclear.**Lines 831 – 850: The way this is written, it isn’t connected to any specific models. It is important to describe what was modelled here and to be explicit about the model structures to ensure reproducibility.**********Have all data underlying the figures and results presented in the manuscript been provided?PLOS Geneticsdata availability policy, and numerical data that underlies graphs or summary statistics should be provided in spreadsheet form as supporting information.Large-scale datasets should be made available via a public repository as described in the Reviewer #1: YesReviewer #2: YesReviewer #3: Yes**********what does this mean?). 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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 us at figures@plos.org.While revising your submission, please upload your figure files to the Similarity Check, powered by iThenticate, into its journal-wide submission system in order to screen submitted content for originality before publication. Each PLOS journal undertakes screening on a proportion of submitted articles. You will be contacted if needed following the screening process.PLOS has incorporated To resubmit, use the link below and 'Revise Submission' in the 'Submissions Needing Revision' folder.[LINK]We are sorry that we cannot be more positive about your manuscript at this stage. Please do not hesitate to contact us if you have any concerns or questions.Yours sincerely,Ian R. HendersonAssociate EditorPLOS GeneticsKirsten BombliesSection Editor: EvolutionPLOS GeneticsReviewer's Responses to QuestionsComments to the Authors:Please note here if the review is uploaded as an attachment.Reviewer #1: The revised manuscript still requires extensive revision of the English, which is frequently hard to understand (I attach an annotated pdf file as well as comments below). The Discussion also seems unduly long (7 pages) and could be shorter and clearer if unnecessary repetition of results were removed.Another general comment is that the text frequently ignores the state of the art in the field. When a concept is already well-established, I feel that, if one cites a recent paper, the citation should make clear that this is a review of the topic. As written, without doing this, or citing the early literature, the manuscript misleadingly gives the impression that these things are new discoveries. My comments on Lines 56 and 127 below are in a category that I consider “not so minor”.The chief question remains whether the present study represents an advance sufficient for acceptance by PLoS Genetics, as opposed to being better suited for a journal like G3 or Heredity. In other words, what new discovery does it provide?It is correct that the size of the dataset is an improvement on previous analyses, and I consider it improvements in quality to describe recombination patterns, not just total map lengths, and to describe centromere locations . Clearly, these points should be emphasised. My criticisms did not dispute the value of such improvements, or of re-analysing the data to make results comparable between species.The authors’ responses make clear that several of the most interesting questions could not be studied, and it would be helpful to readers to mention these explicitly, perhaps in a brief “Future directions” section at the end. This would help readers understand how difficult it is to reach conclusions about these questions, and that the right kind of data are now obtainable, albeit with considerable effort.The issue of family sizes appears not to be mentioned, but surely the ability to detect recombinants will depend on the family size, and, in small families, none may be detected in regions with infrequent crossing over even if crossovers can occasionally occur. At present, the genetic maps are taken as facts, not estimates. This problem extends beyond the issue of family sizes, and I believe that it also affects the analysis of the models. As crossovers happen in the 4-strand stage, the genetic map distances don’t directly tell us the number of crossovers per bivalent, and so it is difficult to infer anything clear about the number that is required for correct segregation. It might be nice to know whether the evidence supports a requirement for a crossover per chromosome, or whether this requirement is enforced for each chromosome arm. However, it is well-established that, despite some such requirement, crossover numbers show a distribution that includes zero events, yet correct segregation is possible.However, my major criticism of the manuscript is still that the main new conclusion (line 434 onwards) does not seem justified. In my wording, this is that recombination between coding regions occurs more (“was more efficient”) than among regions randomly sampled from the genome, especially for longer chromosomes, which tend to have distal crossover localisation, and consequently the most heterogeneous recombination rates. The reasoning used to reach the conclusion that this is an important evolutionary observation seems to overlook an “elephant in the room” — the accumulation of repetitive sequences in low recombination regions of genomes. A direct outcome of this tendency is that regions with low recombination rates tend also have low gene densities. I don’t think that this has (in my edited wording) “implications for the evolution of crossover landscapes and whether the distribution of COs is optimal for the efficacy of genetic recombination”.Following Haenel et al. (2018), the authors show that recombination rates correlate positively with gene density. This is unsurprising, as gene density goers down as repetitive content goes up, and the latter increases in genome regions with low crossover rates. This has been established in many species, including plants. Line 373 onwards says “the strength of the relationship greatly varied across species and did not correlate with usual predictors such as the chromosome length or the genome-wide recombination rate”. But surely the usual predictors of gene density are not chromosome length or the genome-wide recombination rate, but local recombination rates, with clear effects of proximity to centromeres. This is because these effects are pronounced only in genome regions with pretty low recombination rates, and cannot be detected from correlations using minor or local recombination rate differences.By writing that recombination rates “consistently increased with the number of genes” in 100 kb windows, the text suggests in the readers mind that the causative factor is the number of genes .Marey maps most often appeared more homogeneous when the x axis measures distances in terms of cumulative number of genes along the chromosome instead of base pair distances. When genes are sparse, a small value of this “gene distance” corresponds to a large physical distance, so the inhomogeneity of the maps is diminished, as a direct arithmetical consequence (provided that the annotation of the genes is accurate). This has no special biological significance.If I have misunderstood the authors’ reasoning, I am happy to be corrected. Certainly, the writing needs to make the meaning clearer if what I have understood them to be saying is not their meaning.Not so minorLines 56 and 127: The text should not give the impression that an association between gene density and recombination is a new observation. Line 127 says “are recombination landscapes generally associated with gene density?” , but such a relationship is already extremely well established, because it is known that repetitive sequences accumulate in low recombination regions of genomes. If this is to be mentioned in the Introduction, it needs to be changed to make clear that this well-known pattern is confirmed by these new analyses. The fact that recombination hotspotshave been found in gene regulatory sequences is a minor contributor to such a pattern.Line 66: It is strange to cite de Massy, 2013 and later papers for the discovery that recombination rates are not homogeneous across the genome and vary among species, as this has been known for a very long time. Centromeric and pericentromeric regions with low rates were known for plants at least since work on maize in the 1930s, and work on tomatoes shortly afterwards, showing the heterochromatic regions physically surrounding centromeres are recombinationally inert.Similarly, in line 294, it reads strangely that “we observed that the centromeres had an almost universal local suppressor effect”, as this is such a well-known phenomenon (since Beadle’s work in Drosophila in 1932), and is known to act in addition to the effect of heterochromatin. It would be better to write that thewell-known phenomenon of centromeric low crossover rates is confirmed. In this paragraph, a caveat should be expressed to the statement about “completely recombination-free in the centromere” , as surely the ability to detect recombinants will depend on the family size, and none may be detected in small families, even if crossovers occasionally occur.Line 192: Figure 1 shows that most of the 57 plant species analysed have estimated cM/Mb rates >1. This is a valuable result, but the text doesn’t mention it. I would have liked to see the value of 1 indicated by a horizontal line, as it is not shown on the y axis. From the figure, it appears that 4 species consistently have values < 0.5. Their names should be mentioned, as such low values are unusual, and these results should be examined to find out whether they are trustworthy, of if terminal markers may be lacking. Figure 2A seems to show that these same species may have very long chromosomes. This too seems worthy of explicit remark, as many readers will be interested to learn that plant chromosomes can be larger than 500 Mb . As presented, the reader does not even know whether these are related species .This comment exemplifies my previous concern that only relationships between quantities are studied, when in fact some of the values are of interest in themselves. Omitting to even mention them makes the findings hard to understand, as it is easy to “miss the wood for the trees”, or understand clearly what the complicated relationships might mean.Line 222: the text is still not clear . Do “proximal and distal regions” mean centromere-proximal versus distal positions (on both arms for metacentrics), respectively? (and I think that the correct phrase is “sensu strictu”). And does “middle” or “centre” refer to the middle of an arm in a metacentric, or to the centromeric region and its neighbourhood . Clarification is still needed.I also did not understand which landscapes were homogeneous along chromosomes — it would be helpful to name explicitly the species in Figure 3 that fall into the different categories, and mention the test for homogeneity that was used. The differences are not obvious to me.Line 265 states that the confidence interval for the periphery bias is 2.06 - 2.32., indicating that recombination rates are highest in the tips of chromosomes., though the differences are not usually extreme. Confusingly, the text earlier in this section strongly emphasised that a bias towards the periphery was not ubiquitous across species. These things are not necessarily contradictory, but they give the impression of being so. In fact, if I have understood correctly, it appears from Figure 5 that Haenel et al. were correct in thinking that this is a common pattern. If so, this should be clearly stated in the text, as it is an important conclusion, and readers should not be left with the impression that they were wrong .Minor commentsA minor, but general, issue is the failure to distinguish between physical positions in the chromosome assemblies and genetic map positions. Although the text makes use of both these measures, it is sometimes unclear which one is meant , so that the meaning is not clear (e.g. lines 313 to 315).It is simplistic to write that recombination “increases genetic diversity and the adaptive potential of a species”. Most readers will know that genetic recombination is interesting and worthy of study.Line 51: what genomic characteristics? It would be better to say “genome size and ….” specifying the other characteristics.Line 83: It is too sweeping to say that recombination hotspots are general. Some organisms don’t have them, so please write more cautiously. In addition, please make clear what definitions were used for the plant hotspots cited, as many authors use this term extremely loosely, to mean any region where they detect higher recombination than other regions, even if the regions are large, unlike the original definition of hotspots.Line 87: it is too vague to just say that recombination affects genome structure, functioning and evolution. Please be explicit. For example, recombination events can affect genome structure by causing ectopic recombination between similar sequences, including repeats, in different locations. As written, readers will not understand what you have in mind.Line 107: the meaning is unclear of “positively driven by chromosome length”Line 119: the phrase “to our knowledge” is in the wrong place in the sentence.Line 128: the question “What are the consequences of recombination heterogeneity on the extent of genetic shuffling?” is hard to understand, as “genetic shuffling” is usually just “baby language” for recombination . Is this an attempt to mention that recombination can involve both crossing over and gene conversion? If so, it is certainly not clear enough. I would advise a different term for the sub-heading in line 405.Line 169: Are the crossover numbers means? It is difficult to understand what is meant by “234 chromosomes had between one and two COs”, as a chromosome has a definite number. This, and the preceding sentence should be revised to make the meaning clear.Line 173: The meaning of a “species random effect” is not clear enough.Line 263: what does “ex on Fig 3A and 3E” mean?Line 289: the meaning is unclear. The text reads “chromosomes from species classified as having a distal pattern were significantly larger than chromosomes with a sub-distal pattern”. Does this mean “species classified as having the distal pattern had significantly larger chromosomes than those of species assigned to the set with the sub-distal pattern”.Line 313: The meaning is unclear for “equal distribution of crossovers on both sides of thechromosome”,Line 321: This reads “At least one CO in each chromosome arm (50 cM) is mandatory in M2 whereas only one CO is mandatory for the entire chromosome in M3”, which is difficult to understand. Does it mean “In M2, at least one CO in each chromosome arm (50 cM) is mandatory, whereas in M3 only a single CO is mandatory for the entire chromosome, even if it has two arms”?Reviewer #2: I want to congratulate the authors again on an excellent paper. All my (minor) suggestions were met very aptly, and overall the paper is improved with the revisions.Reviewer #3: Thank you for addressing our suggested revisions. In my opinion, this paper is much improved from the previous draft. It is so much easier to follow the different analyses and findings this time around. It made me really appreciate the discussion as an excellent synthesis of all the findings of this paper in a broader context. The figures look much better and do justice to all the work that is being presented.A few small corrections:• Throughout the Abstract/Summary/Intro, I would use “crossover” rather than “crossing-over” when referring to the process as a noun e.g. number of crossovers vs. during crossing-over (verb). • Line 24: characterise• Line 35: correspond globally• Lines 63 – 64: might make more sense to say something like “New haplotypes are passed on to offspring by the reciprocal exchange of DNA between maternal and paternal chromosomes, known as crossovers (COs)” and then remove “(COs)” on line 74• Line 68: specific pairing sites implies that recombination always takes place in the same spot• Lines 84-85: naïve question for you to check – is it in regulatory regions rather that sequence? Promotor regions?• Lines 172 – 174: can you get at how much of the variance species explains?• Figure 6: Define pattern “E” in the legend• For my comment about the local linkage order potentially inflating map length, I thought your response was good – could it be included in the methods in case another reader had the same concern?**********Have all data underlying the figures and results presented in the manuscript been provided?PLOS Geneticsdata availability policy, and numerical data that underlies graphs or summary statistics should be provided in spreadsheet form as supporting information.Large-scale datasets should be made available via a public repository as described in the Reviewer #1: YesReviewer #2: YesReviewer #3: Yes**********what does this mean?). 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The aim of this study was to explore the experiences of hope people had after undergoing treatment for a hepatitis C virus infection (HCV). Between October 2019 and May 2020, 19 one-on-one interviews were conducted with people who inject drugs and had undergone HCV treatment. All participants had completed treatment and were documented as being virus-free. Data were audio recorded and then transcribed verbatim and analysed; a method inspired by reflexive thematic analysis. Those interviewed conveyed rich and nuanced descriptions of experiences of a life with HCV. Through the course of the analysis we developed four themes. The themes were formulated as metaphors aimed at capturing commonalities about how the participants seemed to “turn their gaze” after receiving HCV treatment: (1) turning their gaze backward; (2) turning their gaze inwards; (3) turning their gaze toward others and (4) turning their gaze forward. Participants’ descriptions of their experiences relating to HCV were somewhat gloomy, and HCV treatment seemed to inspire hope and a brighter outlook on several areas of life.  Many of those struggling with substance problems experience co-occurring problems related to both mental and somatic health ,2,3,4. ABeyond a range of somatic symptoms and risks, HCV has also been reported to have psychosocial consequences ,17,18,19Until recently, key treatment for HCV was interferon-based, with moderate efficacy and considerable adverse effects, in addition to low treatment uptake among persons who inject drugs (PWID) . In receThe concept of recovery has gained a stronger foothold within the fields of substance abuse and mental health over recent years ,29. WithHope is central to overcoming a wide range of challenges and illnesses, e.g., ,32,33,34HVC can have an impact on one’s quality of life and living conditions, as well as one’s outlook on the future. However, pure medical effects are often the main focus of investigation, and less is known on whether or not undergoing such treatment can change life perspectives and social roles. New treatment approaches are currently gaining foothold and are becoming more accessible. Exploring different dimensions of how new treatment methods affect recipients, and expanding knowledge through various methodological approaches, are important contributions in developing future practices. There is limited research on the influence of treatment of HVC on hope in the era of modern direct-acting antiviral HCV treatment. Thus, our aim is to explore participants’ experiences of hope after HCV treatment with direct-acting antiviral medications.The present study is part of a qualitative project aiming to explore how participants experience HCV treatment through focus groups and individual interviews. In the initial analysis of the data material, hope was an important topic that came up in the individual interviews. Hence, in this part study we have analyzed the individual interviews to explore how participants experiences of hope were influenced after HCV treatment. Qualitative methods aim to provide in-depth insights and are based on theories of human experience and are therefore well suited for this study . As therOur recruitment process was purposive and criterion-based, aimed to obtain participants that could contribute to the information needed for the project . This enA total of 19 participants were interviewed individually. Among them were twelve men and seven women aged between 32–65 years. All participants came from Bergen. The participants had a range of 10 to 40 years of injecting substances. All participants had completed treatment and were reported as being virus-free. To ensure their confidentiality, we referred to them as ‘participants’ in the presentation of the findings. In the source population, most received social security benefits as main source of income, around one in six were homeless, and around half had less than 10 years of education , and manQualitative semi-structured individual interviews were used for data collection. The semi-structured interview examines themes that are largely decided beforehand, whilst still allowing the process and dynamics of the interview to determine how strictly the interviewer follows the script . We invoThe interview templates for the individual interviews were co-constructed within the project group of the research project. The project group consists of researchers with broad interdisciplinary experience from research on substance use, welfare services, family therapy and professionals .The interview templates for the individual interviews focused on four main topics: (1) quality of life, (2) self-perception, (3) relations, and (4) substance use. For example, the participants were asked “How did treatment affect your everyday life?” and “Has the treatment affected your intake of substances when treatment was ongoing?” The interviews lasted between 30 and 50 min. The interviews were conducted by five research nurses involved in the project . They alTo generate a phenomenological and hermeneutical understanding of the participants experiences, we used reflexive thematic analysis, as described by Braun and Clarke (2019). Thematic analysis allows flexibility with regard to philosophical and theoretical stance. During the analysis we used Word for Windows to handle the data. The approach is a systematic, yet flexible, way of identifying and coding themes in qualitative data . When coThe study was conducted in accordance with the Declaration of Helsinki and approved by the Norwegian Regional Committees for Medical and Health Research Ethics . All participants were informed about the option of withdrawing from the research project at any stage without the need for explanation, signed a consent form and received copies of the ethical approvals for the research project. Transcripts of the interviews were anonymized and stored on an encrypted server owned by the regional health authority.Participants in this study shared stories of stigma and loss related to hepatitis C. Being aware that they had the disease gave rise to experiences of hopelessness and a lack of faith in the future. The interviews presented rich and nuanced descriptions of experiences from a variety of people, all with their own individual life story. Yet, through our analysis, we were able to develop four themes that seemed to capture some common and similar experiences described by participants in their interviews that were relevant to the focus of our study. One central common factor was how in a number of ways the participants seemed to experience HCV treatment as an opportunity to reorient, and to some extent influence how they perceived both their understanding of both their past and future. With the aim of capturing and to some extent abstracting the rich material, the themes were formulated as different metaphors revolving around how the participants seemed to “turn their gaze”: (1) turning their gaze backward; (2) turning their gaze inwards; (3) turning their gaze toward others and (4) turning their gaze forward. Common to all the themes is that they involve “turning” the participants’ gaze in various ways. Though they should not be understood literally, they nonetheless capture experiences of the reorientation towards and hopes for the future that were conveyed in the participants’ stories.The participants described being infected with HCV as having the “addict’s disease”. If you told anyone about the illness you were automatically labelled a junkie. One participant said that: “By turning yellow you are branded as having the junkie disease”, referring to yellow tanning related with advanced chronic liver disease. Another participant stated that “when you have hepatitis C, people know that you are an addict”. Being “branded” was a description several of the participants used. “The colour yellow” was perceived as an obvious sign of who they were, and what kind of life they had lived. As “branded”, they were afraid of being outcast, both by others who use drugs, and by “significant others” who are not part of an illicit drug scene. The fear of being an outcast made several of the participants keep the infection a secret. When in contact with public health services, however, the diagnosis was noted and known by those involved. Because of this, many of the participants felt “branded” and considered as an infectious “junkie”. They experienced this, for instance, as there being a lack of respect for them as a person and a lack of knowledge about hepatitis C. One of the participants revealed that a doctor had refused to offer him treatment. The participants ascribed this as a combination of being part of a stigmatized group, and an obvious lack of knowledge among health workers and the general public on how hepatisis C transmits. As a person who was infected, they had all experienced shame. The shame was experienced not only in encounters with the general public, but also within the social and cultural environment of people who inject drugs. Solely by being a person having a substance abuse problem, they were already part of a stigmatized group. Being infected with hepatitis C, they were at the lowest step of the “social ladder”, including among those who they considered as their peers. They were stigmatized in an already stigmatized group. This confirmed the negative thoughts participants already had about themselves and led them down a destructive spiral were they felt that they had little reason to live. Hopes for the future were diminished, as one participant put it: “You do not have much to live for. Your mind is set on the next fix, you no longer have any visions for the future”.Participants shared stories of stigma involving encounters with both the general public and persons who use illicit drugs, and what may be defined as internalized stigma. One participant said: “It’s just like the word ‘addict’ is inscribed inside me”. Most participants described being infected as making them feel nasty and filthy, something they wanted to distance themselves from. Yet, considering hepatitis C is potentially lethal, the result was that initiating changes seemed pointless since they were bound to die at a young age regardless. Being “dirty inside, yellow and identified as sick” by society became part of a negative identity. A negative identity which was constantly confirmed through stigmatization and being rejected by acquaintances in the illicit drugs scene, professional helpers, and “significant others” “outside of the drugs scene”.The participants described the experience of being prioritized to receive the costly HCV treatment as giving them a sense that had worth as a person. Their interactions during the treatment were also described as very positive. They were treated respectfully, and treatment was adjusted according to their needs. Mastering the treatment influenced their perception of themselves in a positive way. A participant described that “mastering the treatment gave me faith that it’s possible to overcome trouble in life”. This notion of challenges being manageable made the participants believe that they could influence their future. This, in turn, inspired participants’ sense of hope.Through their treatment, recipients obtained new knowledge about HCV and how the infection spreads. Some participants in our study had passed this knowledge on to others in the illicit drug scene. For some, this had altered their roles, from being stigmatized in a stigmatized group, to being regarded as a resource, all of which improved their perception of themselves. This improved self-perception also made them more aware of their own health. No longer did they perceive themselves as “dirty on the inside”. They were more aware of the ways in which everyday decisions influenced their health. Despite the HCV treatment not being considered a substance abuse treatment, it changed participants’ view on their ability to control their substance use. Even though substances were still part of most of the participants’ lives, their attitudes to substance use had changed. Being what they described as a “worn out and tired drug addict”, they had not been watchful to their intake of substances. As one participant said: “If you’re worn out, you do not give a shit about anything, including infections”. Now that they had hopes of an improved future, they no longer wanted to share drug-taking equipment. Participant 6 said that “after I got well, I quit sharing equipment and became very cautious about hygiene”. The participants were also conscious with regard to buying their substances from the safest source possible, something which few had cared about before treatment. In general, the majority also declined offers of substances to a greater extent. This was an obvious step toward setting limits on their own behalf. As one participant put it: “I am more conscious about how far I go in terms of putting pressure and expectations on myself. Now, if I experience a negative thing in life, I feel I can weed it away”.When successfully treated for HCV, they no longer felt “marked” by the “junkie disease”. Furthermore, shame, guilt, and experiences of stigma seemed to diminish. The experience of getting well was of great importance to how they perceived themselves and how they interacted with others. Through seeing themselves more positively, they gradually saw their self-confidence, courage and feeling of energy to act in life improve.Improved self-confidence and not being infectious gave the participants an opportunity to reconnect with significant others. Many had felt excluded and unwanted when infected with HCV. Experiences of not getting to spend time with family members such as grandchildren, or not being allowed to use the toilet when vising their family, underpinned the feeling of unwantedness and that others were afraid of infection.After recovering, several participants had experienced greater awareness and reflexivity related to how their behavior influenced their interactions with others. These changes were also noticed in their surroundings, such as with their family and other significant others, and one of the participants stated that: “My family has said that I seem more confident in myself”. Another participant spoke about changes in their use of language: “The language, ethical language. It flies out the window when you do not feel good about yourself”.Spending time with significant others, like family and friends, led to an upward spiral of encouragement, as one participant put it: “It’s always nice to meet new people. The way they treat you is feedback in itself”. Positive feedback challenged how they had previously perceived themselves as persons with substance abuse problems with little hope for the future, a perception which may be interpreted as internalized stigma. Positive feedback, in turn, gave them the confidence to seek and establish acquaintances beyond their “inner circle”. Through such experiences when meeting new people, the participants felt that they were being acknowledged in a way that they described as “normal”. Along with improved self-esteem, their raised consciousness about their own actions, and the fact that they were no longer contagious, made it possible to initiate intimate relations. Shame, stigma, fear of contagion, and/or rejection, had resulted in some of the participants avoiding intimate relations while having HVC. One participant described it like this: “Intimate relations and having sex was not considered possible when being ill [with hepatitis C]”. In addition, impaired bodily functions made it difficult to participate in sexual relationships. The participants experienced opportunities for intimate relationships due to improved health and reduced impairments. Furthermore, it made it easier to relax, feel confident, and approach others, as one participant said: “In sexual relations, I can now relax and feel safe that I do not need to use a condom”. People in established relationships, described feeling closer to their partners after successful treatment of hepatitis C. Another participant said that: “Our relationship has become more mature”.Since reaching old age was regarded as unattainable, changing behavior viewed as unhealthy was perceived as meaningless when infected with HVC. This changed after successful treatment. One participant stated that: “It feels good to know that is not the [hepatitis C] disease that will end my life”. Participants were now less concerned about dying from a substance related disease. Their thoughts on who they were and how they would be remembered were now altered.As death was no longer considered imminent, it was possible to look forwards. The future was now viewed in a more hopeful manner. A hope that change and a better life were possible. Hope also made it possible to face problems which in the past had affected their mental health and finances, but at earlier times seemed unfeasible. As expressed by one of the participants: “After the treatment [for hepatitis C], I can look forwards. It is possible to work on my own mental health and participate in treatment programmes”. While some initiated treatment and follow-up of somatic disease and mental health problems, others experienced that their problems vanished after their HVC treatment. For some, getting well resulted in an improved ability to concentrate and higher levels of energy, which made it possible to fill their lives with meaningful activities, which in turn enhanced their mental health. Participants described bodily changes, such as less sweating, and improved tolerance for physical activity. As one said: “I think of it like ripples in the water, positive changes lead to more positive changes”.After experiencing that their mental and somatic health problems had lessened, some of the participants described their thoughts as focusing less on substance use and more on building a future. They also expressed feeling acceptance of their current situation and its opportunities. Many participants described using substances less and that they could do more work that contributed to improving their financial situation that for many had been difficult for years. As stated by one participant: “Now we have money to get through the month. We can even put some money aside. Earlier, we only waited for an imminent death”.The presentation of our findings may give the impression that “turning your gaze” is straight forward, and that treatment represents a linear, tidy, and neat journey. That is not our intention. Life is rarely linear and tidy, and stories of hope or recovery are certainly not .Hepatitis C differs from mental health problems and substance abuse in many regards. Yet, their interconnectedness is apparent, including for those participating in the present study. Our aim was to explore experiences of hope after receiving HVC treatment. The stories that the participants shared may seem embossed with despair, yet they carry testimonies of hope as well. Weingarten  puts forBiong and Herrestad  describeclinical recovery is often contrasted to personal and social recovery and deemed the hegemony of medicine and its experts [understanding and accepting self as central for recovery (p. 8), along with renewing hope, confidence, and commitment [clinical recovery somehow sparked what often is categorized as personal and social recovery [Within the field of mental health and/or substance abuse,  experts ,44. When experts . Richmon experts  explored experts  (p. 7).  experts ,48. When experts  list undmmitment . Drawingrecovery ,44. The recovery , and ourthe yellow colour was literally comprehended as a brand, signalling that you were “an addict” or a “junkie”. This is in line with Butt [Based on our findings, there are several parallels between how hepatitis C impacts peoples’ lives, and experiences of mental health and substance abuse problems. Among them are stigma and the lack of comprehension that often goes hand in hand, both in the general public and within professional services, e.g., . For thoith Butt  who wrotthe yellow colour. Not only did they ascribe this to a lack of respect, but also to a lack of knowledge among professionals. Such negative experiences related to stigma and HVC are by no means unique to our study, but in line with what Butt [When seeking professional help, participants had received substandard treatment because of what they referred to as hat Butt  has founhat Butt  found thhat Butt . Some ofhat Butt . Our aimhat Butt ,51.The yellow colour had become part of the participants’ identity and getting rid of it was literally a means of altering ones’ identity, away from someone associated with injecting drugs, toward what several of the participants described as normal. Participants in the above-mentioned study by Richmond et al. [For persons having experiences that might be considered extraordinary, and life stories embossed by defeat and disappointment, what can appear mainstream may represent something to aspire to and the idea of becoming a part of it may inspire hope. What is considered mainstream is as diverse as life itself, yet a sense of security and belonging seems central . One wayd et al.  expressed et al. . The simd et al.  described et al.  exploredd et al. .the yellow colour, their self-esteem improved, and they were more sensitive to how they interacted with, and influenced, others. Belonging to new fellowships seemed more within reach.Despite the conception of reasonable hope as relational, Weingarten  makes itHope does not entail certain outcomes, and hope is influenced by the past, yet oriented towards the future ,55. OfteKoehn and Cutcliffe  describeParticipants in the present study had achieved one important goal: treatment for hepatitis C. In hindsight, or when analysing qualitative data, it sometimes seems straightforward to identify themes, patterns, or somehow connect the dots. In the midst of a chaotic life-situation, this is seldom the case. We are in line with Davidson et al.  who wishSearching for patterns and connections in the data reduces complex and rich stories into overarching and common themes. We do not claim that these are valid across what may at first glance seem like similar situations, nonetheless they convey parts of stories we consider important. Rather than representing experiences, our findings may contribute to discussions and practices related to hepatitis C treatment and the experiences that may go hand in hand. Despite our efforts to conduct a credible and transparent analysis of data, thematic analysis has its weaknesses, and applying the criteria described by Nowell et al.  could haFor those participating in this study, life had at times involved bleak future outlooks, or seemingly no future at all. Receiving treatment for hepatitis C was by no means a quick fix regarding complex and intertwined challenges that can go hand in hand with illicit drug (ab)use. Treatment gave rise to hopes of a more positive future. Much like treatment, hope is no quick fix, but should not be underestimated. The ripple effects that treatment seemed to have on participants lives were striking. Not only had treatment affected participants’ health in numerous ways, but it also influenced how they perceived their interactions with others and how they were treated differently by their surroundings. The consequences of stigma and sub-standard treatment relating to hepatitis C cannot be underestimated, and yet it seems that counteracting such devastating consequences must involve societal factors alongside health care services. Implications from this study include that diverse and multidisciplinary approaches are likely to be beneficial for persons struggling with substance related problems and HCV. Further, treatment for HCV affects health in a broad sense, and succeeding in meeting the target group’s needs is of great importance. The socio-economic gains should not be undervalued, neither should the positive effects of strengthening and reestablishing relations with loved ones. This further adds to the importance of scaling up treatment of hepatitis C.


Mexico’s obesity rates are alarming, and experts project drastic increases in the next thirty years. There is growing interest in understanding how remote acculturation and globalization processes influence health behaviors. The present study used focus group data from a central state, San Luis Potosí, in Mexico to explore mothers’ perspectives on factors that influence family mealtime routines. Thematic analysis was used to identify barriers and facilitators to healthy mealtime routines and diet within families. Twenty-one mothers participated in the focus groups; 76% were full-time stay at home mothers, the majority were low-income (65%), and fewer than half reached a high school education. Three major themes emerged: (1) mothers do most of the visible work involving mealtime routines; (2) family meals are different today, and globalization is a contributing factor; and (3) family mealtimes are shifting to weekend events. Empowering mothers to negotiate diet with family members to build healthy routines, navigate challenges due to changing environments, and set family boundaries around technology use during mealtimes should be taken into consideration when promoting healthy behaviors with Mexican families. The Organization of Economic Co-operation and Development (OECD) reported that more than 70% of adults are overweight (32% are obese) in Mexico, with one in three children overweight. Mexico is ranked third among all countries studied under the OECD . This alCultural norms and practices include food and meal choices and how families share meals . A systeSeveral factors present challenges to these traditional patterns. Household dynamics, such as financial burdens, have also been associated with difficulty allocating time and energy to execute daily meals . FurtherApart from these micro-level family cultural shifts, western media may also play a role in the rising overweight and obesity rates among children and adolescents around the world . Across Exploring Mexican mothers’ perceptions of mealtime routines and the changing food environment may reveal familial and cultural factors that are important in understanding the rapid increase in obesity rates in Mexico. The ways in which families continually share meals, including discussion that takes place during meals, and the patterns that emerge from shopping, cooking, mealtime preparation, and mealtime rules, roles, and expectations all contribute to family mealtime routines , and areThe study participants came from an ongoing collaboration between the University of Illinois in Urbana and the Autonomous University of San Luis Potosi in Mexico. The city of San Luis Potosi (SLP), Mexico, is the capital and most populous town of the Mexican state of San Luis Potosi. There are approximately 800,000 people who live in San Luis Potosi, and the city is historically known as a mining community. Study procedures incorporated recommendations for research with immigrants and vulnerable families  and wereThe 21 participants ranged in age from 28 to 41 years old (m = 34.9). Seventeen mothers were married (85%), and more than half of the participants were full-time stay-at-home mothers (76%). Less than half of the sample (47.6%) completed secundaria (which equates to nine years of education), with 28.6% completing only primaria (up to six years of education). According to the Secretary of Labor and Social Welfare in the Mexican Republic, the average income per day for those living in San Luis Potosí was 326.80 pesos a day, which equates to $17 USD  . ,27. 26,2n = 21, focus groups lasted an average of 50 min). All mothers received $10 USD in cash for their participation. A light snack and free child-care were also provided.All focus groups were conducted in Spanish. Six culturally competent and bilingual Hispanic interviewers who matched on participant ethnicity and sex conducted the focus groups, taking notes and audiotaping. Sessions took place at local schools or community centers. There were four focus groups conducted with an average of five participants  were Hispanic bilingual/bicultural graduate and undergraduate students who underwent extensive training. Each interviewer provided written field notes for each group, yielding additional insights about social and paralinguistic dynamics. Data quality was enhanced through peer debriefing, an activity aimed to provide an external check on the inquiry process by involving peers to explore potential bias and test working hypotheses . Peer deThe thematic analysis resulted in three major themes and four corresponding subthemes: 1. Mothers do most of the visible work involving mealtime routines; subtheme 1: children influence the food environment; subtheme 2: fathers can present barriers to healthy eating. 2. Family meals are different today, and globalization is a contributing factor; subtheme 1: technology and electronics are distractions to shared family time; subtheme 2: work barriers and the changing workforce impact family meals. 3. Family mealtimes are shifting to weekend events.Mothers discussed how they are typically the main person in the family to cook and shop. Mothers said things like, “During the week no one helps me [shop or cook]. During the week normally I decide, and I know what I’m going to make because they are not there, so there is no way for them to give me a hand”. Mothers contribute a large amount of both time and effort to prepare food and meals for their family; however, mothers acknowledged that they are not the only ones contributing to the decision-making around mealtimes.Children emerged as a persistent driving force in mealtime patterns and cooking, as mothers shared how children are major influencers of what is being purchased and made for meals at home. Mothers discussed how their children influence their mealtime practices, “It’s very difficult that the majority of kids don’t like vegetables, and for my son it is quite difficult because he doesn’t like it, so we battle too much for them to eat vegetables”. One mother would make vegetables or healthy options but end up being the only one who would eat them. She shared, “I just make the nopales and I end up eating them myself because no one wants them”.Mothers also talked about how shopping with kids can become burdensome because they ask for certain foods and it can become difficult to deny their requests. Consequently, some mothers feel like they are in constant battles and/or negotiation with their children; for example, “she [my daughter] tells me, ‘I don’t like the meat, mama’. Then I battle a lot with her, but I end up buying her a filet of fish one in a while”.Mothers discussed how fathers can often present challenges to making healthy food changes within the home. For example, several mothers discussed how their husbands did not want to eat vegetables. One mother said, “my husband is thin. My son and I are the only chubby ones, so he [my husband] doesn’t want veggies”. Another shared, “my husband doesn’t like vegetables either, but I tell him I am not giving you poison so you have to eat it all”.Globalization is believed to play a role in the development of unhealthy eating habits. Most of the mothers in this study grew up in an era with a rapidly changing food landscape that they found difficult to navigate now that they are parents. Mothers discussed how food availability, cooking patterns, and preparation are different today compared to the past. They shared how their own mothers would cook with natural products and take time to sit together for family meals when they were growing up. Now, frozen food and preservatives have usurped the more natural products of the past. These changes were especially contrasted with their lives as children when they were growing up. Several mothers discussed how their mothers took the time to make healthier, natural, home-cooked meals. One mother shared, “All the meals with my parents were with vegetables, chicken, soup, and water, but now… the truth is the easiest is soda, and that which is fried, and sometimes I try not to make things like that but they don’t want vegetables”.Mothers discussed how the foods today are less fresh compared to the past and also how foods that are consumed are less traditional, replaced easily by quick and unhealthy meals. One mother described, “now we have a lot of junk food and it’s what we find in the supermarkets. Before everything was more natural”. Mothers also feel that time constraints make the convenience of readily available foods especially appealing, and as such they often choose the fastest option even if it is unhealthy, as this mother shared, “More than anything it’s the economy because in my time [as a child] they didn’t take us to eat burgers or things like that. Now mothers go for the fastest option. Which is food like burgers, tacos, and all that, but it wasn’t like this before”.Technology was mentioned as commonly present during family mealtimes. Most mothers in the study were not happy about this, discussing how technology use, such as television, phones, or tablets impeded family time during a shared meal. Despite this, it was frequently allowed at the dinner table. Mothers recognized their frustration with technology, even though it tended to be a common practice that families were often reluctant to give up. For instance, “yes, we eat with the T.V. on. I don’t want to lose the telenovela. Well, and the little ones don’t want to miss the cartoons”.In addition to eating in front of the T.V., families also recognized that the programming they watched could have an influence on their dietary behaviors, as one mother points out, “television [influences my kids’ preferences] because they will see pizza and then they want pizza. They see fries, then they want fries. They don’t promote salad, or water, or juice”.Some mothers also attributed changes in family mealtime practices to reduced time availability and employment compared to what their own mothers experienced when they were growing up. A large reason for this added barrier was that some mothers in these focus groups were involved in paid work, and they contrasted this with how their mothers never worked outside the home and stayed home as caregivers. One mother shared, “The biggest barrier is lack of money, if I didn’t work it would be another thing, we would have more time to dedicate to my kids, to cook for them more healthily…to eat healthily it costs, for me that is the major problem, the economy”. Conflicting work schedules were also recognized as limiting the frequency of shared mealtimes for many mothers. For instance, “well we eat together on the weekends because on weekdays some of us work. I work different shifts compared to my husband, but on the weekends, we try to eat together”.Several families discussed shifting shared mealtimes to the weekend when there were fewer obligations, and everyone could get together. For example, one mother stated, “well during the week it is different because my husband is not there during the meal hour, neither is he there in the morning so I eat breakfast alone. Though at mealtime my husband isn’t there, my kids are there. Only on the weekends, on Sunday is when we are all there for the three meals together”. Mothers shared that they tended to make an effort to eat together over the weekend, usually with extended family. Eating out was often coupled with eating together as a family on the weekends. Some families however could not afford to eat out due to the cost and large family size, “since we are six, well if I buy them all tacos… it’s just more feasible to make them at home because we are a lot in the family, so I buy them [meals outside the home], but very rarely”.The purpose of this study was to examine Mexican mothers’ perceptions of mealtime routines and changes in the family food environment. Findings from this study highlight the intersection of culture and gender norm changes, and how this appears to be influencing mealtime routines within the family household. Mothers shared that fathers and children play a larger role in mealtime logistics and the home food environment today, determining the types of foods eaten in the home and often creating barriers to healthy eating. This builds upon other research conducted with Hispanics that have migrated to the United States, in which mothers play a fundamental role in household shopping and cooking  may support the adaptation for Mexican audiences of successful health promotion interventions evaluated in the US. For example, the program n the US ,51. The Some limitations should be considered. First, we did not measure remote acculturation or family health variables, such as obesity status. Future studies should assess how remote acculturation influences health and family mealtime routines using validated remote acculturation measures ,5. Addit