Pros and Cons of local adaptation scans
Separate the wheat from the chaff: genomic analysis of local adaptation in the red coral Corallium rubrum
The preprint by Pratlong et al.  is a well thought quest for genomic regions involved in local adaptation to depth in a species a red coral living the Mediterranean Sea. It first describes a pattern of structuration and then attempts to find candidate genes involved in local adaptation by contrasting deep with shallow populations. Although the pattern of structuration is clear and meaningful, the candidate genomic regions involved in local adaptation remain to be confirmed. Two external reviewers and myself found this preprint particularly interesting regarding the right-mindedness of the authors in front of the difficulties they encounter during their experiments. The discussions on the pros and cons of the approach are very sound and can be easily exported to a large number of studies that hunt for local adaptation. In this sense, the lessons one can learn by reading this well documented manuscript are certainly valuable for a wide range of evolutionary biologists.
More precisely, the authors RAD-sequenced 6 pairs of 'shallow vs deep' samples located in 3 geographical sea areas (Banyuls, Corsica and Marseilles). They were hoping to detect genes involved in the adaptation to depth, if there were any. They start by assessing the patterns of structuration of the 6 samples using PCA and AMOVA  and also applied the STRUCTURE  assignment software. They show clearly that the samples were mostly differentiated between geographical areas and that only 1 out the 3 areas shows a pattern of isolation by depth (i.e. Marseille). They nevertheless went on and scanned for variants that are highly differentiated in the deep samples when compared to the shallow paired samples in Marseilles, using an Fst outliers approach  implemented in the BayeScEnv software . No clear functional signal was in the end detected among the highly differentiated SNPs, leaving a list of candidates begging for complementary data.
The scan for local adaptation using signatures of highly divergent regions is a classical problem of population genetics. It has been applied on many species with various degrees of success. This study is a beautiful example of a well-designed study that did not give full satisfactory answers. Readers will especially appreciate the honesty and the in-depth discussions of the authors while exposing their results and their conclusions step by step.
 Pratlong, M., Haguenauer, A., Brener, K., Mitta, G., Toulza, E., Garrabou, J., Bensoussan, N., Pontarotti P., & Aurelle, D. (2018). Separate the wheat from the chaff: genomic scan for local adaptation in the red coral Corallium rubrum. bioRxiv, 306456, ver. 3 peer-reviewed and recommended by PCI Evol Biol. doi: 10.1101/306456
 Excoffier, L., Smouse, P. E. & Quattro, J. M. (1992). Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics, 131(2), 479-491.
 Pritchard, J. K., Stephens, M., & Donnelly, P. (2000). Inference of population structure using multilocus genotype data. Genetics, 155(2), 945-959.
 Lewontin, R. C., & Krakauer, J. (1973). Distribution of gene frequency as a test of the theory of the selective neutrality of polymorphisms. Genetics, 74(1), 175-195.
 de Villemereuil, P., & Gaggiotti, O. E. (2015). A new FST‐based method to uncover local adaptation using environmental variables. Methods in Ecology and Evolution, 6(11), 1248-1258. doi: 10.1111/2041-210X.12418
Guillaume Achaz (2018) Pros and Cons of local adaptation scans. Peer Community in Evolutionary Biology, 100061. 10.24072/pci.evolbiol.100061
Revision round #22018-11-23
Decision round #2
Please first apologize for the delay in responding to your submission. My agenda has been sadly very compact. I think your revised version is even better than the first one. I will be happy to recommend your preprint for PCI Evol Biol, provided that you can fix few minor details listed below. I believe this would not you very take long. I shall then quickly post my recommendation.
- Gene diversity, although now defined, is used in your ms. Please replace all its occurrences by expected heterozygosisty that is a much more explicit wording.
- Table 3: MAF<1% actually means MA Counts<4 for most sites, unless there are too many missing data. In this last case, could you provide some extra information on missing genotypes ? (maybe mean and 95% of the distribution)
- Table 2, 4 : could you add one letter for the region in parenthesis after the name. This will considerably ease the reading.
- Table 4: remove Tajima's D from the legend. Fourth column head is "number of private alleles" and non integers are reported. Is this a mean. If yes, please use "average number of private alleles". Otherwise please explain.
- Table 5 : disturbing to read that Fst of 0.01 is "highly significant". I guess this is only due to the size of the dataset in terms of loci, that are assumed to be independent.
May I suggest (but feel free to refuse) to change the title from "Separate the wheat from the chaff: genomic analysis of local adaptation in the red coral Corallium rubrum" to "Separate the wheat from the chaff: genomic scan for local adaptation in the red coral Corallium rubrum"
as the ms is not really an "analysis" of local adaptation but rather a quest for it.
Revision round #12018-10-17
Decision round #1
Two external reviewers and myself have carrefully read your ms entitled "Separate the wheat from the chaff: genomic analysis of local adaptation in the red coral Corallium rubrum" and we all agree that this ms is sound, interesting and certainly deserves to be recommded by PCI Evol Biol. As pointed out by the reviewers, the main strength of this ms is the indepth discussion of the pros and cons of the methods and results you provide. I agree with their opinion.
We nonetheless have few suggestions that could potentially improve the overall quality of this ms. I believe the suggested corrections will be easily addressed and that I will be able to recommend the revised version without any further opinion from the two external reviewers. Please revise and respond to all comments (see below) before I can recommend this article.
:: Suggestions from G Achaz ::
Major: (A) can the authors provide basic analysis of within samples diversity (sample size, #sites, paiwise difference, Tajima's D, etc). (B) did the authors try to infer model parameter (using a mix of demography and structure) using appropriate methods like the ones implemented in dadi (or any other equivalent approach). (C) please shorten and/or lower the importance of the detection of selection as there isn't obvious positive conclusions from it.
Minor: l43 "between" is repeated in tandem l70 replace "high" by "strong"? l189, l270, table4 what is gene diversity? pairwise differences (i.e. heterozygosity)? l194 I don't understand what is the meaning here of 'centered' l282-283, l294, l345 this seems surprising. Why would the sex contribute to genetic differentiation? Am I missing something obvious? l309 you mean 20 instead of 10? l357 which axis are you refering to? pc1? l384 I would be more cautious as this pattern is not visible in the Fst analysis.