By analyzing DNA with the help of artificial intelligence (AI), an international research team led by Lund University in Sweden has developed a method that can accurately date up to ten-thousand year-old human remains.

Accurately dating ancient humans is key when mapping how people migrated during world history.1

In a new study published in Cell Reports Methods, a research team has developed a dating method that could be of great interest to archaeologists and paleognomicists.2

The method is called Temporal Population Structure (TPS) and can be used to date genomes that are up to 10,000 years old. In the study, the research team analyzed approximately 5,000 human remains -- from the Late Mesolithic period (10,000-8,000 BC) to modern times. All of the studied samples could be dated with a rarely seen accuracy.

  • 1. The standard dating method since the 1950s has been radiocarbon dating. The method, which is based on the ratio between two different carbon isotopes, has revolutionized archaeology. However, the technology is not always completely reliable in terms of accuracy, making it complicated to map ancient people, how they moved and how they are related.
  • 2. "Unreliable dating is a major problem, resulting in vague and contradictory results. Our method uses artificial intelligence to date genomes via their DNA with great accuracy, says Eran Elhaik, researcher in molecular cell biology at Lund University.

Sara Behnamian, Umberto Esposito, Grace Holland, Ghadeer Alshehab, Ann M. Dobre, Mehdi Pirooznia, Conrad S. Brimacombe, Eran Elhaik. Temporal population structure, a genetic dating method for ancient Eurasian genomes from the past 10,000 years. Cell Reports Methods, 2022; 2 (8): 100270 DOI: 10.1016/j.crmeth.2022.100270

Radiocarbon dating is the gold standard in archeology to estimate the age of skeletons, a key to studying their origins. Many published ancient genomes lack reliable and direct dates, which results in obscure and contradictory reports. We developed the temporal population structure (TPS), a DNA-based dating method for genomes ranging from the Late Mesolithic to today, and applied it to 3,591 ancient and 1,307 modern Eurasians. TPS predictions aligned with the known dates and correctly accounted for kin relationships. TPS dating of poorly dated Eurasian samples resolved conflicting reports in the literature, as illustrated by one test case. We also demonstrated how TPS improved the ability to study phenotypic traits over time. TPS can be used when radiocarbon dating is unfeasible or uncertain or to develop alternative hypotheses for samples younger than 10,000 years ago, a limitation that may be resolved over time as ancient data accumulate.

Graphical Abstract, Temporal population structure, a genetic dating method for ancient Eurasian genomes from the past 10,000 years
Graphical Abstract, Temporal population structure, a genetic dating method for ancient Eurasian genomes from the past 10,000 years

Motivaton: Accurate dating is essential to the interpretation of paleogenomic data. The gold standard method in archeology is radiocarbon dating. However, a major limitation of radiocarbon dating is the high amount of collagen extraction involved in the process. Consequently, almost half of all published ancient genomes lack reliable and direct dates, which results in obscure and contradictory reports. Here, we present the temporal population structure (TPS), a machine learning-based genomic dating method for genomes ranging from the fringes of the Late Mesolithic to modern times.

Keywords: genomics dating; ancient DNA; temporal population structure; TPS; genomic dating; paleogenomics; phenotypic traits; DNA-based dating method; radiocarbon dating; supervised learning; and random forest regression