Peer review of: Purging of highly deleterious mutations through severe bottlenecks in Alpine ibex (2019)

Reviewers' Comments: 
 
Reviewer #1: 
Remarks to the Author: 
The manuscript by Grossen et al. examines patterns of deleterious mutations in six ibex species. They 
find several interesting patterns, including more putatively weakly deleterious and nearly neutral 
alleles and homozygous genotypes in more bottlenecked populations. However, strongly deleterious 
mutations appear to be reduced in the more bottlenecked populations, consistent with the effects of 
purging of deleterious mutations. This study combines whole genome sequence data with detailed 
population genetic modeling. As such, it takes a comprehensive approach to addressing important 
questions in an intriguing study system. 
 
I have a number of major comments with some of the technical aspects of the manuscript: 
 
1) The authors examine 6 populations. This is indeed a strength of the paper. However, the number of 
genomes sampled from each population varies considerably. For example, 29 Alpine ibex were 
sampled, while only 4 Iberian ibex were sampled. Some of the analyses presented here are sensitive 
to sample size and, as such, it is hard to draw meaningful conclusions with such disparate sample 
sizes. The authors should downsample the populations with a large number of individuals to make 
things more comparable across populations. Specifically, the results in Figure 1E, the SFSs in Figure 2, 
and the frequency plots in Figure 5 will be especially sensitive to sample size. It’s not really 
meaningful to compare SFS of different sample sizes to each other. 
 
2) SFS comparison in Figure 2: The authors conclude the fact that in the Alpine Ibex, more deleterious 
mutations are skewed more toward low frequency constitutes evidence of purging. I do not think that 
this difference in the SFS constitutes evidence of purging. Rather, this skew in the SFS would indicate 
that the high impact mutations are under more purifying selection than the moderate or modifier 
mutations. This finding is what one would expect to see for deleterious mutations. It does not imply 
purging. The fact that this pattern is not seen with the Iberian Ibex could be due to the differences in 
sample size (see my previous comment). Further, Figure 2 uses the proportional SFS here (ie the 
proportions of segregating SNPs at different frequency) rather than the absolute SFS (ie the numbers 
of SNPs at different frequencies). Thus, this figure does not show whether there are more or less high 
impact SNPs. It’s just saying that of the SNPs that are there, they are skewed toward lower frequency. 
We would expect fewer strongly deleterious mutations to be segregating at all and this would not be 
picked up in the proportional SFS. 
 
3) Comparisons of derived alleles and homozygous genotypes across populations can be sensitive to 
missing data. How was missing data dealt with here? Are levels of missing data similar across 
populations? 
 
4) How were fixed sites dealt with in the counts of homozygous derived genotypes across populations? 
Specifically, if there was a site where all individuals in a population were homozygous for the derived 
allele, yet in other population, there were 2 alleles segregating, how would this site be counted? What 
if there are sites that are fixed for different alleles in different populations? How were these counted? 
 
5) Lines 137-144 (and associated figures): The authors compare the numbers of homozygous 
deleterious mutations and derived alleles across different populations. Are these differences 
statistically significant? Some sort of statistical test should be presented here. Similarly, in the Ryx 
plots (e.g. Figure 2E), what are the distributions over? How was statistical significance assessed here? 
 
6) Figure 6 and forward simulations: I like how the authors include forward simulations with realistic 

demographic parameters. However, on line 251, the authors indicate that “Alpine ibex carry an overall 
higher mutation burden than related species”. This can be directly computed from the model. 
Specifically, the mean fitness of each of the populations can be computed given the numbers of 
segregating deleterious mutations, their selection coefficients, and their dominance coefficients. It 
would be good to compute this actual genetic load from the simulations and see how it compares. 
There can be differences between the load computed from simulations vs. what’s seen empirically 
when counting mutations (e.g. see Pedersen et al. 2017 Genetics). 
 
7) Simulations: Do the simulated Alpi Maritime have fewer homozygotes for high impact mutations 
than do the gp? It’s hard to tell from Figure 6c. This finding is important for demonstrating purging. 
 
8) It would be good to better related Figure 6B-D to the empirical patterns. Right now it’s hard to see 
which simulated pattern goes with which empirical pattern. 
 
9) Figure S13: Here when GERP scores are used to predict which mutations are likely to be 
deleterious, in the 6+ category, it does not appear that “am” have fewer homozygous genotypes or 
derived alleles. Based on this figure there does not appear to be any evidence of purging (ie the more 
inbred or bottlenecked population having fewer deleterious alleles). Some reasons for this discrepancy 
with Figure 4 in the main text should be presented. One possibility is that GERP is not doing a good 
job at distinguishing strongly deleterious mutations from more moderately deleterious ones. I think 
this needs to be highlighted and discussed more in the main text. This also motivates the need to 
consider examining mean fitness directly from the simulations, in addition to relying on bioinformatics 
predictions of fitness effects on empirical data. 
 
Additionally, I have several minor suggestions to improve the paper: 
 
1) Lines 55-59: There is some conflating between the effects of genetic drift allowing weakly 
deleterious mutations to increase in frequency and the effects of inbreeding (ie mating between close 
relatives) throughout the manuscript. Though they can often occur together, especially in small 
populations, these are distinct processes, and can have different effects on weakly deleterious vs. 
strongly deleterious mutations as well as additive vs. recessive mutations. Thus, I would urge the 
authors to use the terminology more carefully and precisely throughout the paper. Also, line 162 is 
problematic for this same reason. 
 
2) Line 65: Some additional references to cite here include: Do et al. 2015 Nature Genetics; 
Lohmueller 2014 Curr Opinion Genet Dev; Fu et al 2014 AJHG. 
 
3) Figure 5: I like this figure for showing the locations of the highly deleterious mutations in the 
proteins. However, I’m not sure what I’m supposed to conclude form the panel at the right showing 
the frequencies of these mutations in the different populations. More context and interpretation should 
be provided. 
 
4) Lines 257-259: Here the authors seem to imply that bottlenecks may be good because they allow 
for purging of deleterious mutations. However, this is conditional on the population surviving and not 
going extinct due to inbreeding depression in the meantime. The Isle Royale wolves offer a counter 
example. Here, small population size combined with strong inbreeding led to severe inbreeding 
depression. Robinson et al 2019 (Science Advances) provides a description and analysis of this 
system. 
 
5) Lines 309: The authors detect ROHs using BCFtools. As this method relies on allele frequencies, I 
would suggest that it would be good to also compare to the ROHs seen using other programs, like 

PLINK. (I do agree that BCFtools is the preferred approach, but as a sanity check, it would be good to 
see whether the broad qualitative trends hold with PLINK too). 
 
6) Line 396: Is this initial frequency of the deleterious mutations at mutation-selection balance used at 
the start of the burn in? 
 
7) Figure S6: The GERP score thresholds presented here are a bit confusing. The figure says “only 
retain high quality deleterious mutations: GERP>-2”. Many mutations with GERP>-2 won’t be 
deleterious. Also, a few lines down in this figure, it would be better to order the GERP and the snpEFF 
functional predictions in the same order (e.g. low to high for both). 
 
 
 
Reviewer #2: 
Remarks to the Author: 
The authors sequenced and analyzed 60 complete genomes of six ibex species and the domestic goat 
to investigate the relation between bottleneck strength and mutation load. These ibex species 
experienced the most dramatic bottlenecks among the successfully restored species. For instance, 
Alpine ibex were reduced to ~100 individuals in the 19th century and now about 50’000 individuals 
have been re-established in Alps. They concluded that historic bottlenecks, temporary reductions in 
population size, induced by human activity impacts levels of genome-wide variation and caused both 
relaxed selection and purging that reshaped landscape of deleterious mutation load. This study also 
proposed that for ensuring long-term survivability of endangered species, conservation efforts should 
model bottleneck intensity. In their study, defining the phenotypic effects of variants is an important 
issue, and the authors defined the mutational effects using snpEff toolbox and GERP conservation 
scores for genes with evidence for transcription. However, two major problems exist in defining high-
confidence deleterious mutations. 
Major comments: 
1. Four categories proposed by snpEff are HIGH, MODERATE, LOW, and MODIFIER, which is a simple 
estimation of putative impact/deleteriousness for the Sequence Ontology terms. For instants, snpEff 
categories stop-gain, frameshift or start-lost variants as high putative impact, and missense variant, 
in-frame deletion and insertion with moderate impact. As we know, many missense mutations can 
cause diseases. Generally, the possibility or the fraction of variants with high putative impact to be 
deleterious mutations should be higher than moderate or low impact mutations. However, the 
sequencing results show that the number of high impact mutations by snpEff is much less than other 
categories. In Table S4, the number of SNPs is 614 and 70,873 classified as high and moderate 
respectively for all ibex species. Even though 1% of moderate variants suggested by snpEff have the 
possibility to be deleterious mutations, the number of it is about 708. Therefore, the authors should 
provide a more rigorous definition for the phenotypic effects of variants. For instance, using several 
other popular prediction methods (such as Revel, Vest or CADD) to find the deleterious mutations in 
moderate category and then do further analysis. 
2. The authors assessed the severity of a variant using GERP conservation score. There are another 
two popular conservation scores, phyloP and phastCons, and I suggest the authors to validate their 
conclusion using one of these scores. 
 
Minor comments: 
 
1. I cannot find GERP scores from http://mendel.stanford.edu/SidowLab that the authors provided. 
2. Please illustrate why the authors choose the cutoffs of GERP > -2 and the minimal distance to the 
next SNP of 3bp. 
 

 
 
Reviewer #3: 
Remarks to the Author: 
Authors here report a genomic study on the Alpine Ibex in the Alps. This species can be seen as a 
model species for investigating the role of bottlenecks on demography as well as shaping genomic 
structure. Thus the study set provides a unique opportunity for investigating the role of purging under 
in natural populations when the species has been facing strong bottlenecks. So far only very few 
studies have actually been undertaken trying to identify the role of selection and estimating the 
mutation load in natural systems and the current study does fills an important gap. The strength of 
the manuscript is the combination of a well documented demographic history and thus the 
combination of population sizes, bottleneck history and the genomic analyses. Relating purging to the 
different history and population scenarios definitely is highly relevant for a conservation perspective. 
Analyses are novel and appropriate and the appendix provides a massive amount of background data. 
Thus I do think the paper will make a significant contribution not only to the field of Conservation 
Biology and Genetics but also to understand evolutionary processes in the wild. 
I have two points, I think, authors should address, though: 
Sample size and distribution is not equal for all investigated populations. While I understand that the 
populations in the Alps have been in the focus also of previous studies and thus most material comes 
from this population I wonder how representative the sampled genomes of the other species are. 
Some have only two genomes and probably are opportunistically be sampled, but as information is 
missing on population sizes of the other Ibex species (Table S1A and TableS1B are only for Alps and 
Iberian Ibex) it is a bit unclear to me, if those few samples from the other populations are good 
representatives and if and how authors have dealt with that fact. I would also recommend to add not 
only rough population sizes for the other species, but also to include sampling dates for all genomes in 
the appendix. 
 
line32: sentence reads as if something is missing here 
line46/47: at several places I found the use of tenses inconsistently, as e.g. in the first and second 
sentence of the introduction – please check. 
line 55: “purging.Purging” more a stylistic remark, but could be reworded 
Figure 1: line 78: in addition to the IUCN conservation status it would be good to add rough 
population sizes in the boxes for each species as well 
line 80/87: how do sample sizes match – in the figure N=29 is mentioned for Alpine Ibex, in the text 
you refer to 60 genomes (which is probably rather a matter of wording, but I first was confusing that 
with 60 Alpine Ibex samples) 
line116/117: So what is the explanation for this? I did not find that afterwards. 
line120: I can understand the rationale of contrasting Iberian Ibex to Alpine Ibex in that graph, 
however, I would like to see a comparison to the other species (probably in appendix and domestic 
goat species as well) 
line143/144: is this true also when you analyse the different alpine Ibex populations separately? 
line259/261: can you provide a reference here? I do think your empiricial evidence is pretty strong, so 
you would not necessarily need to include an additional theoretical modelling approach for your 
selection, but the statement here is somehow isolated. The link to theory could be a bit stronger.