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Related Experiment Video

Updated: Feb 19, 2026

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA
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Estimating mobility using sparse data: Application to human genetic variation.

Liisa Loog1,2,3,4, Marta Mirazón Lahr5, Mirna Kovacevic6,7

  • 1Research Department of Genetics, Evolution and Environment, University College London, London WC1E 6BT, United Kingdom; LiisaLoog@gmail.com m.thomas@ucl.ac.uk.

Proceedings of the National Academy of Sciences of the United States of America
|November 1, 2017
PubMed
Summary

This study introduces a new method to estimate past human mobility using genetic and archaeological data. The research reveals increased mobility in Holocene farmers compared to hunter-gatherers, occurring in distinct stages linked to technological advancements.

Keywords:
ancient DNAcultural variationmobilitymorphological variationtime-series data

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Area of Science:

  • Archaeogenetics
  • Paleolithic archaeology
  • Population genetics

Background:

  • Inferring past human migration is crucial for understanding spatiotemporal patterns of genetic, morphological, and cultural variation.
  • Current methods for reconstructing migration lack temporal resolution, formal quantification, and are ill-suited for sparse data, limiting comparative analyses.

Observation:

  • A novel estimator was developed, explicitly linking trait differentiation across space and time to quantify past mobility.
  • The estimator's efficacy was validated through spatiotemporally explicit simulations.
  • The method was applied to ancient genomic data from Western Eurasia, spanning the Late Pleistocene to the Iron Age.

Findings:

  • Human mobility patterns in Western Eurasia show significant changes from the Late Pleistocene to the Iron Age.
  • European Holocene farmers exhibited substantially higher mobility than European hunter-gatherers, both before and after the Last Glacial Maximum.
  • The rise in Holocene farmer mobility occurred in at least three distinct phases: early Neolithic, early Bronze Age, and late Iron Age.

Implications:

  • The findings suggest a strong correlation between technological innovation and human mobility throughout Holocene Western Eurasia.
  • This new framework provides a powerful tool for systematically exploring and comparing changes in human mobility across different time periods and geographic regions.