A genetic and linguistic analysis of the admixture histories of the islands of Cabo Verde
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Evaluation Summary:
The authors leverage genotyping data from the islands of Cabo Verde to study its admixture history and to gain insights into the onset of the Trans-Atlantic Slave Trade. They find that patterns of ancestry between the islands are not the same, suggesting diversity in the founding populations of these islands. These results provide a nice example of how ancestry patterns vary across admixed populations due in part to their unique local history and social practices of that time.
(This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1 and Reviewer #2 agreed to share their names with the authors.)
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Abstract
From the 15th to the 19th century, the Trans-Atlantic Slave-Trade (TAST) influenced the genetic and cultural diversity of numerous populations. We explore genomic and linguistic data from the nine islands of Cabo Verde, the earliest European colony of the era in Africa, a major Slave-Trade platform between the 16th and 19th centuries, and a previously uninhabited location ideal for investigating early admixture events between Europeans and Africans. Using local-ancestry inference approaches, we find that genetic admixture in Cabo Verde occurred primarily between Iberian and certain Senegambian populations, although forced and voluntary migrations to the archipelago involved numerous other populations. Inter-individual genetic and linguistic variation recapitulates the geographic distribution of individuals’ birth-places across Cabo Verdean islands, following an isolation-by-distance model with reduced genetic and linguistic effective dispersals within the archipelago, and suggesting that Kriolu language variants have developed together with genetic divergences at very reduced geographical scales. Furthermore, based on approximate bayesian computation inferences of highly complex admixture histories, we find that admixture occurred early on each island, long before the 18 th -century massive TAST deportations triggered by the expansion of the plantation economy in Africa and the Americas, and after this era mostly during the abolition of the TAST and of slavery in European colonial empires. Our results illustrate how shifting socio-cultural relationships between enslaved and non-enslaved communities during and after the TAST, shaped enslaved-African descendants’ genomic diversity and structure on both sides of the Atlantic.
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Author Response
Reviewer #1 (Public Review):
Laurent et al. generate genotyping data from 259 individuals from Cabo Verde to investigate the histories and patterns of admixture in the set of islands that make up Cabo Verde. The authors had previously studied admixture in an earlier study but in a smaller set of individuals from two cities on one island (from Santiago) in Cabo Verde. Here, the authors sample from all the islands of Cabo Verde to study admixture in these islands and reveal that there is a varied picture of admixture in that the demographic histories are distinct amongst this set of islands.
I found the article interesting and clearly written, and I like that it highlights that admixture is a dynamic process that has manifested differently in distinct geographical regions, which will be of broad interest. It also …
Author Response
Reviewer #1 (Public Review):
Laurent et al. generate genotyping data from 259 individuals from Cabo Verde to investigate the histories and patterns of admixture in the set of islands that make up Cabo Verde. The authors had previously studied admixture in an earlier study but in a smaller set of individuals from two cities on one island (from Santiago) in Cabo Verde. Here, the authors sample from all the islands of Cabo Verde to study admixture in these islands and reveal that there is a varied picture of admixture in that the demographic histories are distinct amongst this set of islands.
I found the article interesting and clearly written, and I like that it highlights that admixture is a dynamic process that has manifested differently in distinct geographical regions, which will be of broad interest. It also highlights how genetic ancestry patterns are correlated with the populations that were in power/enslaved during colonial times and proposes that certain social practices (e.g. legally enforced segregation) might have affected the distribution/length of runs of homozygosity.
We thank the reviewer for this positive and encouraging appreciation of our work.
My main suggestion is that the authors provide a set of hypotheses regarding admixture that may explain their observations, and it would be nice to see if at least one of these has some support using simulations. Could the authors run simulations under their proposed demographic model for populations in Cabo Verde vs what we would expect in a pseudo-panmictic population with two sources of admixture? The authors probably already have simulations they could use. And then see how pre/post admixture founding events change patterns of ancestry.
As suggested by the reviewer, in the revised version of the manuscript, we conducted the same MetHis-ABC scenario-choice and posterior parameter inference considering the 225 Cabo Verde-born individuals as a single random-mating population, in addition to our main results considering each island of birth separately. Most interestingly, we find that our ABC inferences fail to accurately reconstruct the detailed admixture history of Cabo Verde when considered as a whole instead of per each island of birth separately. This is due to admixture histories substantially differing across islands of birth of individuals, also consistent with the significantly differentiated genetic patterns within Cabo Verde obtained from ADMIXTURE, local-ancestry inferences, ROH, and isolation-by-distance analyses. These results are now implemented throughout the revised version of the manuscript and in supplementary figures and tables. See in particular Results L758-769, and Appendix1-figures and tables, Figure7-figure supplement 1-3, and Appendix 5-table 10.
Reviewer #2 (Public Review):
In this article, the authors leveraged patterns on the empirical genomic data and the power of simulations and statistical inferences and aimed to address a few biologically and culturally relevant questions about Cabo Verde population's admixture history during the TAST era. Specifically, the authors provided evidence on which specific African and European populations contributed to the population per island if the genetic admixture history parallels language evolution, and the best-fitting admixture scenario that answers questions on when and which continental populations admixed on which island, and how that influenced the island population dynamics since then.
Strengths
- This study sets a great example of studying population history through the lens of genetics and linguistics, jointly. Historically most of the genetic studies of population history either ignored the sociocultural aspects of the evidence or poorly (or wrongly) correlated that with genetic inference. This study identified components in language that are informative about cultural mixture (strictly African-origin words versus shared European-African words), and carefully examined the statistical correlation between genetic and linguistic variation that occurred through admixture, providing a complete picture of genetic and sociocultural transformation in the Cabo Verde islands during TAST.
We thank the reviewer for this very enthusiastic and encouraging comment on our work.
- The statistical analyses are carefully designed and rigorously done. I especially appreciate the careful goodness-of-fit checking and parameter error rates estimation in the ABC part, making the inference results more convincing.
Again, we thank the reviewer for this positive comment.
Weaknesses
- Most of the methods in the main analyses here were previously developed (eg. MDS, MetHis, RF/NN-ABC). However, when being introduced and applied here, the authors didn't reinstate the necessary background (strength and weakness, limitations and usage) of these methods to make them justifiable over other methods. For example, why ADS-MDS is used here to examine the genetic relationship between Cabo Verde populations and other worldwide populations, rather than classic PCA and F-statistics?
As mentioned in the answer to the general comments, we extensively modified our manuscript in both Results and Material and Methods, to clarify and justify our reasoning for each one of the analyses conducted, and to discuss pros and cons of the methods used. We warmly thank the reviewers for this request, as we believe it allowed us to strongly improve the accessibility of our work in particular for the less specialized audience, as well as equally crucially improve replicability of our work for specialists. See in particular Results L185-193, L245-250, L368-371, L380-386, L495-511, L567-571, L606-621, and the corresponding Material and Methods sections.
For the particular example of PCA raised by the reviewer: see Results L185-193.
For that of F-statistics, see Results L368-386. Note that we added the F-stat analysis suggested by the reviewer to the revised version of our manuscript (see detailed answers below), Figure 3-figure supplement 2.
We believe that these changes strongly strengthen our manuscript and enlarged its potential readership, and we thank, again, the reviewer for this request.
- The senior author of this paper has an earlier published article (Verdu et al. 2017 Current Biology) on the same population, using a similar set of methods and drew similar conclusions on the source of genetic and linguistic variation in Cabo Verde. Although additional samples on island levels are added here and additional analyses on admixture history were performed, half of the main messages from this paper don't seem to provide new knowledge than what we already learned from the 2017 paper.
We substantially modified the text of the revised version of the manuscript to address the concern raised by the reviewer in numerous locations of the Abstract, Introduction and Results and Discussion sections, thus hoping to highlight better what we think is the profound novelty brought by this study. In particular, see Introduction L128-153.
- Furthermore, there are a few essential factors that could confound different aspects of the major analyses in this article that I believe should be taken into account and discussed. Such factors include the demographic history of source populations prior to admixture, different scenarios of the recipient population size changes, differences in recombination rates across the genome and between African and European populations, etc.
We thank the reviewer for these comments which allowed us to improve the clarity of our manuscript and rise very interesting discussion points that we had overlooked. As indicated in part in the general answer to reviewers above:
We clarified our methods’ design and discussed extensively its limitations with respect to ancestral populations’ sizes mis-specifications. Indeed, ancestral source population sizes are not modelized in our MetHis-ABC approach. Instead, we consider that the observed proxy source populations from Africa and Europe are at the drift-mutation equilibrium and are large since the initial and recent founding of Cabo Verde in the 1460’s, and thus use observed genetic variation patterns in these populations to build virtual gamete reservoirs for the admixture history of Cabo Verde with the MetHis-ABC framework. Therefore, while we cannot evaluate explicitly the influence of ancestral source population sizes differences on our inferences in Cabo Verde, as we now state in the revised version of our manuscript: “we nevertheless implicitly take the real demographic histories of these source populations into account in our simulations, as we use observed genetic patterns themselves the product of this demographic history to create the virtual source populations at the root of the admixture history of each Cabo Verdean island.”. We then discuss the outcome of such an approach which mimics satisfactorily the real data for ABC inference. See in particular the revised versions of the Material and Methods L1454-1491 novel section “Simulating the admixed population from source-populations for 60,000 independent SNPs with MetHis”, and Results L637-649.
Concerning the possibilities for population-size changes in the admixed population in our simulations and ABC inferences, we clarified our Material and Methods and explanations of our Results to better show that we readily consider various possible scenarios (for each island separately). Indeed, with our MetHis simulation design, given values of model-parameters correspond either to a constant, a linearly increasing, or a hyperbolic increase in reproductive size in the admixed population over time. We further clarified our Results and Discussion pointing out that we find, a posteriori, indeed, different demographic regimes among islands.
Nevertheless, reviewers are right that we did not test the possibility for bottlenecks. We thus substantially expanded the Results and Discussion sections in multiple locations to highlight this limitation and the challenges involved in overcoming it in future work. See in particular Material and Methods L1386-1404 section “Hyperbolic increase, linear increase, or constant reproductive population size in the admixed population”, Results L739-742, and Discussion L934-941, and Perspectives.
- Finally, concerning recombination rate, we considered only independent SNPs in our simulation and inference process, as is now clarified in multiple locations throughout the text. Otherwise, we further discuss matters of recombination concern regarding specifically our ROH analyses, as suggested in the detailed reviewer’s comments. In brief, we note that in Figure 8 Pemberton 2012 (AJHG 91:275-292) shows that occurrence of long ROH at the same genomic location across individuals is correlated with low recombination rates, although the effect is relatively weak unless in extreme recombination cold spots. Unless there were many extreme recombination cold spots that were different among the islands or ancestral populations, we anticipate fine-scale recombination rate differences not to matter very much for total ROH levels in these data. Similarly, we do not expect large genome-wide differences in mutation rate, and therefore we don’t anticipate minor local variation in mutation rates to make a systematic difference in total ROH levels. We now refer to these important points in the revised version of our Results L414-415.
Overall, the paper is of interest to the field of human evolutionary genetics - that not only does it tell the story of a historically important population, but also the methodology behind this paper sets a great example for future research to study genetic and sociocultural transformations under the same framework.
We would like to thank the reviewer for this very encouraging conclusion and for the detailed revision of our work which, we believe, helped us to substantially improve our manuscript.
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Evaluation Summary:
The authors leverage genotyping data from the islands of Cabo Verde to study its admixture history and to gain insights into the onset of the Trans-Atlantic Slave Trade. They find that patterns of ancestry between the islands are not the same, suggesting diversity in the founding populations of these islands. These results provide a nice example of how ancestry patterns vary across admixed populations due in part to their unique local history and social practices of that time.
(This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1 and Reviewer #2 agreed to share their names with the authors.)
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Reviewer #1 (Public Review):
Laurent et al. generate genotyping data from 259 individuals from Cabo Verde to investigate the histories and patterns of admixture in the set of islands that make up Cabo Verde. The authors had previously studied admixture in an earlier study but in a smaller set of individuals from two cities on one island (from Santiago) in Cabo Verde. Here, the authors sample from all the islands of Cabo Verde to study admixture in these islands and reveal that there is a varied picture of admixture in that the demographic histories are distinct amongst this set of islands.
I found the article interesting and clearly written, and I like that it highlights that admixture is a dynamic process that has manifested differently in distinct geographical regions, which will be of broad interest. It also highlights how genetic …
Reviewer #1 (Public Review):
Laurent et al. generate genotyping data from 259 individuals from Cabo Verde to investigate the histories and patterns of admixture in the set of islands that make up Cabo Verde. The authors had previously studied admixture in an earlier study but in a smaller set of individuals from two cities on one island (from Santiago) in Cabo Verde. Here, the authors sample from all the islands of Cabo Verde to study admixture in these islands and reveal that there is a varied picture of admixture in that the demographic histories are distinct amongst this set of islands.
I found the article interesting and clearly written, and I like that it highlights that admixture is a dynamic process that has manifested differently in distinct geographical regions, which will be of broad interest. It also highlights how genetic ancestry patterns are correlated with the populations that were in power/enslaved during colonial times and proposes that certain social practices (e.g. legally enforced segregation) might have affected the distribution/length of runs of homozygosity.
My main suggestion is that the authors provide a set of hypotheses regarding admixture that may explain their observations, and it would be nice to see if at least one of these has some support using simulations. Could the authors run simulations under their proposed demographic model for populations in Cabo Verde vs what we would expect in a pseudo-panmictic population with two sources of admixture? The authors probably already have simulations they could use. And then see how pre/post admixture founding events change patterns of ancestry.
-
Reviewer #2 (Public Review):
In this article, the authors leveraged patterns on the empirical genomic data and the power of simulations and statistical inferences and aimed to address a few biologically and culturally relevant questions about Cabo Verde population's admixture history during the TAST era. Specifically, the authors provided evidence on which specific African and European populations contributed to the population per island if the genetic admixture history parallels language evolution, and the best-fitting admixture scenario that answers questions on when and which continental populations admixed on which island, and how that influenced the island population dynamics since then.
Strengths:
This study sets a great example of studying population history through the lens of genetics and linguistics, jointly. Historically most …
Reviewer #2 (Public Review):
In this article, the authors leveraged patterns on the empirical genomic data and the power of simulations and statistical inferences and aimed to address a few biologically and culturally relevant questions about Cabo Verde population's admixture history during the TAST era. Specifically, the authors provided evidence on which specific African and European populations contributed to the population per island if the genetic admixture history parallels language evolution, and the best-fitting admixture scenario that answers questions on when and which continental populations admixed on which island, and how that influenced the island population dynamics since then.
Strengths:
This study sets a great example of studying population history through the lens of genetics and linguistics, jointly. Historically most of the genetic studies of population history either ignored the sociocultural aspects of the evidence or poorly (or wrongly) correlated that with genetic inference. This study identified components in language that are informative about cultural mixture (strictly African-origin words versus shared European-African words), and carefully examined the statistical correlation between genetic and linguistic variation that occurred through admixture, providing a complete picture of genetic and sociocultural transformation in the Cabo Verde islands during TAST.
The statistical analyses are carefully designed and rigorously done. I especially appreciate the careful goodness-of-fit checking and parameter error rates estimation in the ABC part, making the inference results more convincing.
Weaknesses
Most of the methods in the main analyses here were previously developed (eg. MDS, MetHis, RF/NN-ABC). However, when being introduced and applied here, the authors didn't reinstate the necessary background (strength and weakness, limitations and usage) of these methods to make them justifiable over other methods. For example, why ADS-MDS is used here to examine the genetic relationship between Cabo Verde populations and other worldwide populations, rather than classic PCA and F-statistics?
The senior author of this paper has an earlier published article (Verdu et al. 2017 Current Biology) on the same population, using a similar set of methods and drew similar conclusions on the source of genetic and linguistic variation in Cabo Verde. Although additional samples on island levels are added here and additional analyses on admixture history were performed, half of the main messages from this paper don't seem to provide new knowledge than what we already learned from the 2017 paper.
Furthermore, there are a few essential factors that could confound different aspects of the major analyses in this article that I believe should be taken into account and discussed. Such factors include the demographic history of source populations prior to admixture, different scenarios of the recipient population size changes, differences in recombination rates across the genome and between African and European populations, etc.
Overall, the paper is of interest to the field of human evolutionary genetics - that not only does it tell the story of a historically important population, but also the methodology behind this paper sets a great example for future research to study genetic and sociocultural transformations under the same framework.
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