Geographic population structure analysis of worldwide human populations infers their biogeographical origins

Eran Elhaik (), Tatiana Tatarinova, Dmitri Chebotarev, Ignazio S. Piras, Carla Maria Calò, Antonella De Montis, Manuela Atzori, Monica Marini, Sergio Tofanelli, Paolo Francalacci, Luca Pagani, Chris Tyler-Smith, Yali Xue, Francesco Cucca, Theodore G. Schurr, Jill B. Gaieski, Carlalynne Melendez, Miguel G. Vilar, Amanda C. Owings, Rocío Gómez, Ricardo Fujita, Fabrício R. Santos, David Comas, Oleg Balanovsky, Elena Balanovska, Pierre Zalloua, Himla Soodyall, Ramasamy Pitchappan, ArunKumar GaneshPrasad, Michael Hammer, Lisa Matisoo-Smith and R. Spencer Wells
Additional contact information
Eran Elhaik: University of Sheffield
Tatiana Tatarinova: Keck School of Medicine and Children’s Hospital Los Angeles, University of Southern California
Dmitri Chebotarev: T.T. Chang Genetic Resources Center, International Rice Research Institute
Ignazio S. Piras: University of Cagliari
Carla Maria Calò: University of Cagliari
Antonella De Montis: Research Laboratories, bcs Biotech S.r.l.
Manuela Atzori: Research Laboratories, bcs Biotech S.r.l.
Monica Marini: Research Laboratories, bcs Biotech S.r.l.
Sergio Tofanelli: University of Pisa
Paolo Francalacci: University of Sassari
Luca Pagani: The Wellcome Trust Sanger Institute
Chris Tyler-Smith: The Wellcome Trust Sanger Institute
Yali Xue: The Wellcome Trust Sanger Institute
Francesco Cucca: University of Cagliari
Theodore G. Schurr: University of Pennsylvania
Jill B. Gaieski: University of Pennsylvania
Carlalynne Melendez: University of Pennsylvania
Miguel G. Vilar: University of Pennsylvania
Amanda C. Owings: University of Pennsylvania
Rocío Gómez: Cinvestav, San Pedro Zacatenco
Ricardo Fujita: Instituto de Genética y Biología Molecular, University of San Martin de Porres
Fabrício R. Santos: Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais
David Comas: Institut de Biologia Evolutiva (CSIC-UPF), Departament de Ciences de la Salut i de la Vida, Universitat Pompeu Fabra
Oleg Balanovsky: Vavilov Institute for General Genetics
Elena Balanovska: Research Centre for Medical Genetics
Pierre Zalloua: The Lebanese American University
Himla Soodyall: National Health Laboratory Service, Sandringham 2131
Ramasamy Pitchappan: The Genographic Laboratory, School of Biological Sciences, Madurai Kamaraj University
ArunKumar GaneshPrasad: The Genographic Laboratory, School of Biological Sciences, Madurai Kamaraj University
Michael Hammer: University of Arizona
Lisa Matisoo-Smith: University of Otago
R. Spencer Wells: National Geographic Society

Nature Communications, 2014, vol. 5, issue 1, 1-13

Abstract: Abstract The search for a method that utilizes biological information to predict humans’ place of origin has occupied scientists for millennia. Over the past four decades, scientists have employed genetic data in an effort to achieve this goal but with limited success. While biogeographical algorithms using next-generation sequencing data have achieved an accuracy of 700 km in Europe, they were inaccurate elsewhere. Here we describe the Geographic Population Structure (GPS) algorithm and demonstrate its accuracy with three data sets using 40,000–130,000 SNPs. GPS placed 83% of worldwide individuals in their country of origin. Applied to over 200 Sardinians villagers, GPS placed a quarter of them in their villages and most of the rest within 50 km of their villages. GPS’s accuracy and power to infer the biogeography of worldwide individuals down to their country or, in some cases, village, of origin, underscores the promise of admixture-based methods for biogeography and has ramifications for genetic ancestry testing.

Date: 2014
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DOI: 10.1038/ncomms4513

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