An unusual suspect: the mutation landscape as a determinant of local variation in nucleotide diversity
The landscape of nucleotide diversity in Drosophila melanogaster is shaped by mutation rate variation
Recommendation: posted 13 April 2023, validated 13 April 2023
Racimo, F. (2023) An unusual suspect: the mutation landscape as a determinant of local variation in nucleotide diversity. Peer Community in Evolutionary Biology, 100636. 10.24072/pci.evolbiol.100636
Sometimes, important factors for explaining biological processes fall through the cracks, and it is only through careful modeling that their importance eventually comes out to light. In this study, Barroso and Dutheil introduce a new method based on the sequentially Markovian coalescent (SMC, Marjoran and Wall 2006) for jointly estimating local recombination and coalescent rates along a genome. Unlike previous SMC-based methods, however, their method can also co-estimate local patterns of variation in mutation rates.
This is a powerful improvement which allows them to tackle questions about the reasons for the extensive variation in nucleotide diversity across the chromosomes of a species - a problem that has plagued the minds of population geneticists for decades (Begun and Aquadro 1992, Andolfatto 2007, McVicker et al., 2009, Pouyet and Gilbert 2021). The authors find that variation in de novo mutation rates appears to be the most important factor in determining nucleotide diversity in Drosophila melanogaster. Though seemingly contradicting previous attempts at addressing this problem (Comeron 2014), they take care to investigate and explain why that might be the case.
Barroso and Dutheil have also taken care to carefully explain the details of their new approach and have carried a very thorough set of analyses comparing competing explanations for patterns of nucleotide variation via causal modeling. The reviewers raised several issues involving choices made by the authors in their analysis of variance partitioning, the proper evaluation of the role of linked selection and the recombination rate estimates emerging from their model. These issues have all been extensively addressed by the authors, and their conclusions seem to remain robust. The study illustrates why the mutation landscape should not be ignored as an important determinant of local variation in genetic diversity, and opens up questions about the generalizability of these results to other organisms.
Andolfatto, P. (2007). Hitchhiking effects of recurrent beneficial amino acid substitutions in the Drosophila melanogaster genome. Genome research, 17(12), 1755-1762. https://doi.org/10.1101/gr.6691007
Barroso, G. V., & Dutheil, J. Y. (2021). The landscape of nucleotide diversity in Drosophila melanogaster is shaped by mutation rate variation. bioRxiv, 2021.09.16.460667, ver. 3 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2021.09.16.460667
Begun, D. J., & Aquadro, C. F. (1992). Levels of naturally occurring DNA polymorphism correlate with recombination rates in D. melanogaster. Nature, 356(6369), 519-520. https://doi.org/10.1038/356519a0
Comeron, J. M. (2014). Background selection as baseline for nucleotide variation across the Drosophila genome. PLoS Genetics, 10(6), e1004434. https://doi.org/10.1371/journal.pgen.1004434
Marjoram, P., & Wall, J. D. (2006). Fast" coalescent" simulation. BMC genetics, 7, 1-9. https://doi.org/10.1186/1471-2156-7-16
McVicker, G., Gordon, D., Davis, C., & Green, P. (2009). Widespread genomic signatures of natural selection in hominid evolution. PLoS genetics, 5(5), e1000471. https://doi.org/10.1371/journal.pgen.1000471
Pouyet, F., & Gilbert, K. J. (2021). Towards an improved understanding of molecular evolution: the relative roles of selection, drift, and everything in between. Peer Community Journal, 1, e27. https://doi.org/10.24072/pcjournal.16
The recommender in charge of the evaluation of the article and the reviewers declared that they have no conflict of interest (as defined in the code of conduct of PCI) with the authors or with the content of the article. The authors declared that they comply with the PCI rule of having no financial conflicts of interest in relation to the content of the article.
This work was supported by a grant from the German Research Foundation (Deutsche Forschungsgemeinschaft) attributed to JYD, within the priority program (SPP) 1590 “probabilistic structures in evolution”
Evaluation round #2
DOI or URL of the preprint: https://doi.org/10.1101/2021.09.16.460667
Version of the preprint: 2
Author's Reply, 02 Apr 2023
Decision by Fernando Racimo, posted 20 Mar 2023, validated 20 Mar 2023
The reviewers have read your replies to them and are (mostly) satisfied with them. Thank you for your answers to the queries by me and the reviewers.
I don't think it will be necessary for the reviewers to see you manuscript again, as long as the points below are addressed.
1. It's unclear whether Supplemental Figure S1 is a direct result of your inference, or a "sketch" (inspired by what?) that you then used in simulations. As reviewer 2 rightly points out (R2.3), there should be a global TMRCA emerging from this analysis, even if not the central focus of your study. If this can't be produced for some reason, a better explanation for that reason should be available in the text.
2. Please improve the resolution of Supplemental Figure S1 so that the x-axis can be read.
3. Figure 5 warrants more explanation as to what is being depicted here exactly. For example, does "mu block ~500kb" imply that the mutation rate was simulated so as to vary in blocks of (approximately?) 500 kb? In the text it says exactly 500 kb. Also, could you replace "TMRCA" for "tau", and use the greek symbols in the figure as you use in the text?
4. Can you draw horizontal lines in Table 1 and Table S2 to help the reader figure out when one model ends and another begins?
5. Can you address this comment by the anonymous reviewer in your text? "Couldn’t lower autocorrelation instead result not from frequent variation in recombination rate window-to-window, but relatively few windows with extreme shifts in recombination rate relative to their neighboring windows?"
Reviewed by David Castellano, 17 Mar 2023
Reviewed by anonymous reviewer 1, 17 Mar 2023
Evaluation round #1
DOI or URL of the preprint: https://doi.org/10.1101/2021.09.16.460667
Version of the preprint: 1
Author's Reply, 16 Feb 2023
Decision by Fernando Racimo, posted 09 Dec 2022, validated 13 Dec 2022
In this manuscript, Barroso & Dutheil present a new method for co-estimating local recombination rates, local mutation rates and local effective population sizes along the genome, and then apply it to a Drosophila melanogaster haploid genome panel from Zambia. They find a strong role for local variation in mutation rate on variation in local patterns of diversity along the genome - a finding that appears to reach contradictory conclusions to previous approaches to the question of the major determinants of local diversity. The paper is well written, and I agree with the reviewers that the approach is innovative and elegant. I also think the methodology is very well explained. I have some concerns about the robustness of the biological conclusions, and their dependence on particular decisions by the authors. The first reviewers' point about the size of analysis windows should be further explored, and the authors could do a more thorough test into the role of linked selection using simulations. The second reviewer also raised some important points about how the chosen shape for the DFE could influence parameters estimation, and about how the recombination rate estimates could be compared to empirical estimates. I would be happy to recommend this manuscript once these concerns are addressed.