Periodic Reporting for period 2 - MICROSCOPE (Zooming into the Population History of Iron Age Europe with Rare Genetic Variants.)
Período documentado: 2021-05-01 hasta 2022-10-31
Humans are connected to the past through their family trees, and our genetic ancestry reflects this past. Events in human history affect this ancestry and determine how it gets distributed across geography and ethnicities. This is why genetic analyses can be used to trace historical events, such as migrations or mixture processes that happened in the past. While such analyses have become routine in living people, they are becoming increasingly more advanced also for ancient DNA from human remains that are hundreds or thousands of years old. The field behind this technology, Archaeogenetics, allows us to investigate the human migratory past in exquisit detail. For example, we now know that the invention of farming in Europe was driven by large-scale migrations, between 8000 and 6000 years ago from the Near East, and that most Europeans today derive up to 50% of their ancestry from these early pioneers.
At the core of such reconstructions of the human past from genetic data lies the ability to identify population structure among individuals and groups. When such structure changes through time, it shows that people must have been moving and mixing in between. This core idea is simple, but the ability to identify, quantify and model population structure is often challenged by the close relatedness of human groups to each other. This is in particular true for population structure within the last 3000 years in Europe, where population sizes have been large and stable, and even relatively large-scale events, for example involving movements of large numbers of people, did often not anymore affect genetic profiles enough to be quantifiable.
In the ERC-funded project MICROSCOPE, we are developing new ways to identify subtle patterns of genetic ancestry differences between people and between groups, both from ancient and modern DNA. The key idea in MICROSCOPE for this development is to use rare genetic variation, consisting of genetic variants that each are carried by only few people. While any single one of these variants carries much less information about population structure than a single common variant, their much larger total count provides more power to identify extremely subtle ancestry differences than common variants. Two individuals who share a recent common ancestor in their family trees (perhaps due to migration events in the past) will inevitably share more rare genetic variants with each other than expected if they were unrelated. Such rare allele sharing, especially when seen between groups in different places at different times, can therefore be indicative about when and where people moved.
One time period in which the traditional methods to measure population structure, based on common genetic variants, are often insufficient to see differences and similarities, is the pre-Roman Iron Age. This is a time period where we have few or no written sources at all, and most of our knowledge about human connectivity and mobility comes from archaeology. What we do know, for example from Roman and Greek historical accounts, is that people in a vast region from the Iberian peninsula to the Balkans shared common features of art, industry and language, which collectively was termed “Celtic”. Because of the difficulty of standard genetic methods, not much is known so far about population structure and -history during this time. This includes the so-called “Celtic migrations”, a set of historically described events that presumably spread Celtic culture across the continent.
In MICROSCOPE, we set out to genetically analyse over 500 individuals from this time period, and use our new methods to zoom into the population structure, and to model human mobility and migration history.
At the core of such reconstructions of the human past from genetic data lies the ability to identify population structure among individuals and groups. When such structure changes through time, it shows that people must have been moving and mixing in between. This core idea is simple, but the ability to identify, quantify and model population structure is often challenged by the close relatedness of human groups to each other. This is in particular true for population structure within the last 3000 years in Europe, where population sizes have been large and stable, and even relatively large-scale events, for example involving movements of large numbers of people, did often not anymore affect genetic profiles enough to be quantifiable.
In the ERC-funded project MICROSCOPE, we are developing new ways to identify subtle patterns of genetic ancestry differences between people and between groups, both from ancient and modern DNA. The key idea in MICROSCOPE for this development is to use rare genetic variation, consisting of genetic variants that each are carried by only few people. While any single one of these variants carries much less information about population structure than a single common variant, their much larger total count provides more power to identify extremely subtle ancestry differences than common variants. Two individuals who share a recent common ancestor in their family trees (perhaps due to migration events in the past) will inevitably share more rare genetic variants with each other than expected if they were unrelated. Such rare allele sharing, especially when seen between groups in different places at different times, can therefore be indicative about when and where people moved.
One time period in which the traditional methods to measure population structure, based on common genetic variants, are often insufficient to see differences and similarities, is the pre-Roman Iron Age. This is a time period where we have few or no written sources at all, and most of our knowledge about human connectivity and mobility comes from archaeology. What we do know, for example from Roman and Greek historical accounts, is that people in a vast region from the Iberian peninsula to the Balkans shared common features of art, industry and language, which collectively was termed “Celtic”. Because of the difficulty of standard genetic methods, not much is known so far about population structure and -history during this time. This includes the so-called “Celtic migrations”, a set of historically described events that presumably spread Celtic culture across the continent.
In MICROSCOPE, we set out to genetically analyse over 500 individuals from this time period, and use our new methods to zoom into the population structure, and to model human mobility and migration history.
In the first 30 months of the project, we have focused on developing new statistical tools and software to work with rare genetic variants from present-day and ancient genomes. We can now show that our new statistics are substantially better powered than traditional methods to detect subtle signs of population structure. To achieve this, we have in particular set up large-scale computer simulations that help us understand how closely related populations can be distinguished from each other in terms of their genetic information. As we tune the simulation towards closer and closer genetic relationships between simulated groups, our new statistics based on rare variation maintain power to distinguish them where traditional methods based on common variation already fail.
We have also developed new methodology to estimate mobility in the past from genetic data. To this end, we built models that are able to track genetic changes explicitly through space and time, much like a weather maps. Such ancestry-maps in space and time reveal periods in the human past where humans moved a lot, perhaps due to political or environmental changes, or periods where populations remained more static and stable.
We have also engaged in a large-scale sampling effort of Iron Age cemeteries throughout Europe, ranging from Ireland, Northern Spain through Southwestern Germany, Italy, Austria, Slovenia, Czechia, Slovakia, Croatia, Serbia, Hungary, and Romania. In total, we have sampled skeletal remains (teeth and bones) from a total of 638 individuals that we gained access to from our partners in the fields of archaeology and anthropology.
We have already gained fascinating insights from these data. In England, for example, we are about to publish a large study on population transformations in the last 2000 years, showing how England has undergone several large-scale population turnovers since the Iron Age until today. These changes are correlated with change from Celtic languages (today spoken only in Wales, Scotland and Ireland) to a Germanic language, English, as it is spoken today. We have also gained fascinating insights into family relationships among the ruling elite in Celtic Southwestern Germany.
We have also developed new methodology to estimate mobility in the past from genetic data. To this end, we built models that are able to track genetic changes explicitly through space and time, much like a weather maps. Such ancestry-maps in space and time reveal periods in the human past where humans moved a lot, perhaps due to political or environmental changes, or periods where populations remained more static and stable.
We have also engaged in a large-scale sampling effort of Iron Age cemeteries throughout Europe, ranging from Ireland, Northern Spain through Southwestern Germany, Italy, Austria, Slovenia, Czechia, Slovakia, Croatia, Serbia, Hungary, and Romania. In total, we have sampled skeletal remains (teeth and bones) from a total of 638 individuals that we gained access to from our partners in the fields of archaeology and anthropology.
We have already gained fascinating insights from these data. In England, for example, we are about to publish a large study on population transformations in the last 2000 years, showing how England has undergone several large-scale population turnovers since the Iron Age until today. These changes are correlated with change from Celtic languages (today spoken only in Wales, Scotland and Ireland) to a Germanic language, English, as it is spoken today. We have also gained fascinating insights into family relationships among the ruling elite in Celtic Southwestern Germany.
Work in this project has moved us beyond the state of the art in several aspects:
1.) Our new ancient DNA data generation, for example in England, has lead to the first large-scale investigation of population changes in England since the late Iron Age, in particular during the early Medieval period.
2.) Our new ancient DNA sampling across Europe fills important gaps in the archaeogenetic record and will provide new insights into population transformation during the Celtic period and beyond. Until the end of the project, we expect several new publications describing population changes during the Iron Age to come out of this project (with two already being in manuscript preparation phase).
3.) Several new methods present new perspectives on archaeogenetic data. First, our new method to estimate human mobility from archaeogenetic data allows a quantitative estimate of human mobility through time with unprecedented detail (see Schmid and Schiffels, biorxiv, 2021). Second, our new methodology to use rare genetic variation, currently still in development, could already be shown to greatly increase power of formal tests of population structure. We expect these developments to be published and available for adoption in other laboratories early 2023.
1.) Our new ancient DNA data generation, for example in England, has lead to the first large-scale investigation of population changes in England since the late Iron Age, in particular during the early Medieval period.
2.) Our new ancient DNA sampling across Europe fills important gaps in the archaeogenetic record and will provide new insights into population transformation during the Celtic period and beyond. Until the end of the project, we expect several new publications describing population changes during the Iron Age to come out of this project (with two already being in manuscript preparation phase).
3.) Several new methods present new perspectives on archaeogenetic data. First, our new method to estimate human mobility from archaeogenetic data allows a quantitative estimate of human mobility through time with unprecedented detail (see Schmid and Schiffels, biorxiv, 2021). Second, our new methodology to use rare genetic variation, currently still in development, could already be shown to greatly increase power of formal tests of population structure. We expect these developments to be published and available for adoption in other laboratories early 2023.