Unraveling ancestry, kinship, and violence in a Late Neolithic mass grave
Research output: Contribution to journal › Journal article › Research › peer-review
- Unraveling ancestry kinship and violence in a Late Neolithic mass grave_(version_of_record)
Final published version, 2.13 MB, PDF document
The third millennium BCE was a period of major cultural and demographic changes in Europe that signaled the beginning of the Bronze Age. People from the Pontic steppe expanded westward, leading to the formation of the Corded Ware complex and transforming the genetic landscape of Europe. At the time, the Globular Amphora culture (3300-2700 BCE) existed over large parts of Central and Eastern Europe, but little is known about their interaction with neighboring Corded Ware groups and steppe societies. Here we present a detailed study of a Late Neolithic mass grave from southern Poland belonging to the Globular Amphora culture and containing the remains of 15 men, women, and children, all killed by blows to the head. We sequenced their genomes to between 1.1- and 3.9-fold coverage and performed kinship analyses that demonstrate that the individuals belonged to a large extended family. The bodies had been carefully laid out according to kin relationships by someone who evidently knew the deceased. From a population genetic viewpoint, the people from Koszyce are clearly distinct from neighboring Corded Ware groups because of their lack of steppe-related ancestry. Although the reason for the massacre is unknown, it is possible that it was connected with the expansion of Corded Ware groups, which may have resulted in competition for resources and violent conflict. Together with the archaeological evidence, these analyses provide an unprecedented level of insight into the kinship structure and social behavior of a Late Neolithic community.
|Journal||Proceedings of the National Academy of Sciences of the United States of America|
|Publication status||Published - 2019|
Copyright © 2019 the Author(s). Published by PNAS.
Number of downloads are based on statistics from Google Scholar and www.ku.dk