Title
Geographic population structure analysis of worldwide human populations infers their biogeographical origins
Date Issued
29 April 2014
Access level
open access
Resource Type
journal article
Author(s)
Elhaik E.
Tatarinova T.
Chebotarev D.
Piras I.S.
Calò C.M.
De Montis A.
Atzori M.
Marini M.
Tofanelli S.
Francalacci P.
Pagani L.
Tyler-Smith C.
Xue Y.
Cucca F.
Schurr T.G.
Gaieski J.B.
Melendez C.
Vilar M.G.
Owings A.C.
Gómez R.
Santos F.R.
Comas D.
Balanovsky O.
Balanovska E.
Zalloua P.
Soodyall H.
Pitchappan R.
Prasad A.K.G.
Hammer M.
Matisoo-Smith L.
Wells R.S.
Adhikarla S.
Adler C.J.
Bertranpetit J.
Clarke A.C.
Cooper A.
Der Sarkissian C.S.I.
Haak W.
Haber M.
Jin L.
Kaplan M.E.
Li H.
Li S.
Martínez-Cruz B.
Merchant N.C.
Mitchell J.R.
Parida L.
Platt D.E.
Quintana-Murci L.
Renfrew C.
Lacerda D.R.
Royyuru A.K.
Santhakumari A.V.
Hernanz D.F.S.
Swamikrishnan P.
Ziegle J.S.
University of San Martin de Porres
University of San Martin de Porres
University of San Martin de Porres
Publisher(s)
Nature Publishing Group
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 700km 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 50km 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. © 2014 Macmillan Publishers Limited. All rights reserved.
Volume
5
Language
English
OCDE Knowledge area
Geografía social, Geografía económica
Scopus EID
2-s2.0-84899845427
PubMed ID
Source
Nature Communications
Sponsor(s)
E.E is supported in part by Genographic grant GP 01-12. L.P, C.T.S and Y.X were supported by The Wellcome Trust (098051). O.B. was supported in part by Presidium RAS (MCB programme) and RFBR (13-04-01711). T.T. was supported by grants from The National Institute for General Medical Studies (GM068968), and the Eunice Kennedy Shriver National Institute of Child Health and Human Development (HD070996). S.T. is supported by a PRIN2009 grant. The Genographic Project is supported by the National Geographic Society IBM and the Waitt Foundation. We are grateful to all Genographic participants who contributed their DNA samples for this study.
Sources of information:
Directorio de Producción Científica
Scopus