An analysis of 204 genomes across Europe and the Mediterranean has given significant evidence of high mobility and minimal genetic admixture between the dawn of the Roman Empire and now, despite predictions from models.
This web page was produced as an assignment for an undergraduate course at Davidson College.
Since the initial growth of genome sequencing technology, the evolution of modern humans has been a question looking to be answered. Geneticists have created theories on initial human migration through genetic similarity and carbon-dating (Shriner et al. 2016), and from those theories more specific studies have been carried out on certain ancestries or locations. Despite this wave of interest in human migration and genetic evolution, there has been a surprising lack of focus on migration and genetic diversity from post-Bronze age civilizations such as the Roman Empire. This gap in historical sequencing was solved by Antonio et al. in this study, by sequencing 204 genomes across Europe and the Mediterranean in order to learn more about migration, genetic diversity, and their relationship (Antonio et al. 2024). In this study, it was found that migration rates were significantly higher during this historical period. This was hypothesized to have resulted from trade routes over land and sea, massive empires allowing for easy long distance travel, and potential military presence in large cities such as Rome. As this was occurring throughout history, it was also observed that population structure was relatively stable in the same locations. A stable population structure indicates a similar genetic makeup across a time period. In this instance, the genetic variation of individuals from different ancestries during the Roman Empire was very similar to that of individuals today. The same factors can be used to discern different ancestries from each other.
Once this data was collected, a model known as the Wright-Fisher model was used to determine the likelihood of stable population structure given the amount of migration present. The Wright-Fisher model is a predictive model used to determine changes in genetic diversity over time, assuming independent generations, constant population size, random-mating patterns, and no natural selection (Tataru et al. 2016). When running this model given the migration patterns and population structure, it predicted that the stability would collapse, and individuals from different ancestries would no longer be differentiable. Given the actual occurrences, questions were raised about the discrepancy between the prediction and reality. The authors believe that the cause of this large difference lies in the assumptions, specifically the random-mating assumption. One aspect that may explain the disagreement is affinity bias, which states that people tend to gravitate towards others who are similar to themselves. In more recent history through present day, this can be seen in many US cities. When people migrate to the US from other countries, rather than randomly dispersing throughout the cities, they tend to assimilate with other migrants from the same area. The comfort of similar language, culture, customs, and other factors influences their decision on where to live and therefore it is not random. Results of this can be seen today in sectors of cities, and are known by titles such as Chinatown or Little Italy due to the culture and ancestry of the shops, decor, restaurants, and people. It is observed in the genetic analysis that migration rates were very high around the Mediterranean, especially within large cities such as Rome. These areas boasted high genetic diversity and they remained diverse. It is hypothesized that the residents of these large cities were similar to large cities today. The affinity bias leads people to live near others of similar ancestry, which in turn increases the likelihood that they reproduce with others of similar ancestry, preserving genetic diversity in the population.
This hypothesis stems from the assumption that the discrepancy was due to the difference in mating tendencies, but is not necessarily the explanation for the difference. Many questions that genetics can’t solely answer can be asked as a result of this study. How did the genetic diversity arise within these cities? Did every group travel to these locations willingly? Were there classes based on ancestry? These questions arise from more recent historical trends, such as slavery and the treatment of immigrants. For example, there is no indication based on the genomes alone that genetic ancestries were not present due to an influx of slaves or servants from areas under Roman rule. In this case, the genetic diversity within the city would be high, but the different ancestries would not have much interaction due to social classes, allowing for preservation of discernible genetic ancestries. In order to research this, geneticists could collaborate with historians, and corroborate ancient texts and artifacts with ancient DNA studies. This could explain social happenings with genetics, or vice versa. While engaging in these studies, it is important to be aware of potential ethical implications. Each ancestry in the study has a population of descendants today. When trying to explain certain genomic trends with social occurrences, it could have adverse effects. For example, if genetic research unveils the migration of a specific ancestry, and corroboration with ancient texts/artifacts associates that ancestry to indentured servants or slaves, the findings could impact descendants of these ancestries. Descendants could be discriminated against due to their relatives’ role in the history of the city.
Overall, this paper analyzed many diverse bone samples across Europe and the Mediterranean, and compared their genomes to determine migration and genetic diversity. After they obtained their findings, they ran multiple predictive models to understand whether or not the observed trends were expected or not. Upon finding the discrepancy between model and reality, the authors speculated possible reasons behind the trends and formulated new hypotheses for future research. These hypotheses require further studies in order to be proven or disproven.
References
- Margaret L Antonio, Clemens L Weiß, Ziyue Gao, et al. (2024) Stable population structure in Europe since the Iron Age, despite high mobility eLife 13:e79714. https://doi.org/10.7554/eLife.79714
- Shriner D, Tekola-Ayele F, Adeyemo A, Rotimi CN. Ancient Human Migration after Out-of-Africa. Sci Rep. 2016 May 23;6:26565. doi: 10.1038/srep26565. PMID: 27212471; PMCID: PMC4876373.
- Tataru P, Simonsen M, Bataillon T, Hobolth A. Statistical Inference in the Wright-Fisher Model Using Allele Frequency Data. Syst Biol. 2017 Jan 1;66(1):e30-e46. doi: 10.1093/sysbio/syw056. PMID: 28173553; PMCID: PMC5837693.
Charlie Elliott
© Copyright 2022 Department of Biology, Davidson College, Davidson, NC 28036.
This is a very interesting article! Thinking back at my own experience and identity, it would be important to put into context what does it mean by being mediterranean? Is it also in the coasts of the Middle East, and the northern coasts of Africa? Or are we taking into consideration only the European coasts? These questions come to my mind when I see the diversity of people back home, who have different ancestry groups, different ethnicities, and clearly different phenotypes. A lot of the people in the Middle East and North Africa are very far from being homogenous. At the same time, I think this is my own bias and desire to have “higher” genetic diversity (just to be cool). Regardless, I think this paper is an interesting one that it puts it really pushes forward the idea and questions the notion of diversity brought by globalization. One of the things that we have been learning through class is that the diversity as a social definition is not necessarily what it looks like in nature. Great article!
I love how you’ve written this article, it is engaging and very accessible so that anyone interested in this topic could read it without having to know about genomic studies and jargon. I also like how you’ve tied in this concepts from the paper with modern examples, I think it makes it all the more easy to read and follows a very intuitive flow of ideas. Your inclusion of complicated ethical questions is also appreciated and something that could definitely be given more consideration in the future, I’d be interested to know if anything like what described in terms of discrimination based on genetic ancestry has already happened in the past, given the novelty of these techniques.