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Estimating mobility using sparse data: Application to human genetic variation
Mobility is one of the most important processes shaping spatiotemporal patterns of variation in genetic, morphological, and cultural traits. However, current approaches for inferring past migration episodes in the fields of archaeology and population genetics lack either temporal resolution or forma...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
National Academy of Sciences
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5699029/ https://www.ncbi.nlm.nih.gov/pubmed/29087301 http://dx.doi.org/10.1073/pnas.1703642114 |
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author | Loog, Liisa Mirazón Lahr, Marta Kovacevic, Mirna Manica, Andrea Eriksson, Anders Thomas, Mark G. |
author_facet | Loog, Liisa Mirazón Lahr, Marta Kovacevic, Mirna Manica, Andrea Eriksson, Anders Thomas, Mark G. |
author_sort | Loog, Liisa |
collection | PubMed |
description | Mobility is one of the most important processes shaping spatiotemporal patterns of variation in genetic, morphological, and cultural traits. However, current approaches for inferring past migration episodes in the fields of archaeology and population genetics lack either temporal resolution or formal quantification of the underlying mobility, are poorly suited to spatially and temporally sparsely sampled data, and permit only limited systematic comparison between different time periods or geographic regions. Here we present an estimator of past mobility that addresses these issues by explicitly linking trait differentiation in space and time. We demonstrate the efficacy of this estimator using spatiotemporally explicit simulations and apply it to a large set of ancient genomic data from Western Eurasia. We identify a sequence of changes in human mobility from the Late Pleistocene to the Iron Age. We find that mobility among European Holocene farmers was significantly higher than among European hunter–gatherers both pre- and postdating the Last Glacial Maximum. We also infer that this Holocene rise in mobility occurred in at least three distinct stages: the first centering on the well-known population expansion at the beginning of the Neolithic, and the second and third centering on the beginning of the Bronze Age and the late Iron Age, respectively. These findings suggest a strong link between technological change and human mobility in Holocene Western Eurasia and demonstrate the utility of this framework for exploring changes in mobility through space and time. |
format | Online Article Text |
id | pubmed-5699029 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | National Academy of Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-56990292017-11-27 Estimating mobility using sparse data: Application to human genetic variation Loog, Liisa Mirazón Lahr, Marta Kovacevic, Mirna Manica, Andrea Eriksson, Anders Thomas, Mark G. Proc Natl Acad Sci U S A Biological Sciences Mobility is one of the most important processes shaping spatiotemporal patterns of variation in genetic, morphological, and cultural traits. However, current approaches for inferring past migration episodes in the fields of archaeology and population genetics lack either temporal resolution or formal quantification of the underlying mobility, are poorly suited to spatially and temporally sparsely sampled data, and permit only limited systematic comparison between different time periods or geographic regions. Here we present an estimator of past mobility that addresses these issues by explicitly linking trait differentiation in space and time. We demonstrate the efficacy of this estimator using spatiotemporally explicit simulations and apply it to a large set of ancient genomic data from Western Eurasia. We identify a sequence of changes in human mobility from the Late Pleistocene to the Iron Age. We find that mobility among European Holocene farmers was significantly higher than among European hunter–gatherers both pre- and postdating the Last Glacial Maximum. We also infer that this Holocene rise in mobility occurred in at least three distinct stages: the first centering on the well-known population expansion at the beginning of the Neolithic, and the second and third centering on the beginning of the Bronze Age and the late Iron Age, respectively. These findings suggest a strong link between technological change and human mobility in Holocene Western Eurasia and demonstrate the utility of this framework for exploring changes in mobility through space and time. National Academy of Sciences 2017-11-14 2017-10-30 /pmc/articles/PMC5699029/ /pubmed/29087301 http://dx.doi.org/10.1073/pnas.1703642114 Text en Copyright © 2017 the Author(s). Published by PNAS. This is an open access article distributed under the PNAS license (http://www.pnas.org/site/aboutpnas/licenses.xhtml) . |
spellingShingle | Biological Sciences Loog, Liisa Mirazón Lahr, Marta Kovacevic, Mirna Manica, Andrea Eriksson, Anders Thomas, Mark G. Estimating mobility using sparse data: Application to human genetic variation |
title | Estimating mobility using sparse data: Application to human genetic variation |
title_full | Estimating mobility using sparse data: Application to human genetic variation |
title_fullStr | Estimating mobility using sparse data: Application to human genetic variation |
title_full_unstemmed | Estimating mobility using sparse data: Application to human genetic variation |
title_short | Estimating mobility using sparse data: Application to human genetic variation |
title_sort | estimating mobility using sparse data: application to human genetic variation |
topic | Biological Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5699029/ https://www.ncbi.nlm.nih.gov/pubmed/29087301 http://dx.doi.org/10.1073/pnas.1703642114 |
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