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; Arun Kumar Ganesh Prasad; Michael Hammer; Lisa Matisoo-Smith; R. Spencer Wells; Oscar Acosta; Syama Adhikarla; Christina J. Adler; Jaume Bertranpetit; Andrew C. Clarke; Alan Cooper; Clio S.I. Der Sarkissian; Wolfgang Haak; Marc Haber; Li Jin; Matthew E. Kaplan; Hui Li; Shilin Li; Begoña Martínez-Cruz; Nirav C. Merchant; John R. Mitchell; Laxmi Parida; Daniel E. Platt; Lluis Quintana-Murci; Colin Renfrew; Daniela R. Lacerda; Ajay K. Royyuru; Jose Raul Sandoval; Arun Varatharajan Santhakumari; David F.Soria Hernanz; Pandikumar Swamikrishnan; Janet S. Ziegle

doi:10.1038/ncomms4513

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 GómezRicardo Fujita, Fabrício R. Santos, David Comas, Oleg Balanovsky, Elena Balanovska, Pierre Zalloua, Himla Soodyall, Ramasamy Pitchappan, Arun Kumar Ganesh Prasad, Michael Hammer, Lisa Matisoo-Smith, R. Spencer Wells, Oscar Acosta, Syama Adhikarla, Christina J. Adler, Jaume Bertranpetit, Andrew C. Clarke, Alan Cooper, Clio S.I. Der Sarkissian, Wolfgang Haak, Marc Haber, Li Jin, Matthew E. Kaplan, Hui Li, Shilin Li, Begoña Martínez-Cruz, Nirav C. Merchant, John R. Mitchell, Laxmi Parida, Daniel E. Platt, Lluis Quintana-Murci, Colin Renfrew, Daniela R. Lacerda, Ajay K. Royyuru, Jose Raul Sandoval, Arun Varatharajan Santhakumari, David F.Soria Hernanz, Pandikumar Swamikrishnan, Janet S. Ziegle

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Resumen

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.

Idioma original	Inglés
Número de artículo	3513
Publicación	Nature Communications
Volumen	5
DOI	https://doi.org/10.1038/ncomms4513
Estado	Publicada - 29 abr. 2014

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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., ... Ziegle, J. S. (2014). Geographic population structure analysis of worldwide human populations infers their biogeographical origins. Nature Communications, 5, Artículo 3513. https://doi.org/10.1038/ncomms4513

@article{8e42c71f33274237a29187dc8a396b05,

title = "Geographic population structure analysis of worldwide human populations infers their biogeographical origins",

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.",

author = "Eran Elhaik and Tatiana Tatarinova and Dmitri Chebotarev and Piras, {Ignazio S.} and Cal{\`o}, {Carla Maria} and {De Montis}, Antonella and Manuela Atzori and Monica Marini and Sergio Tofanelli and Paolo Francalacci and Luca Pagani and Chris Tyler-Smith and Yali Xue and Francesco Cucca and Schurr, {Theodore G.} and Gaieski, {Jill B.} and Carlalynne Melendez and Vilar, {Miguel G.} and Owings, {Amanda C.} and Roc{\'i}o G{\'o}mez and Ricardo Fujita and Santos, {Fabr{\'i}cio R.} and David Comas and Oleg Balanovsky and Elena Balanovska and Pierre Zalloua and Himla Soodyall and Ramasamy Pitchappan and Prasad, {Arun Kumar Ganesh} and Michael Hammer and Lisa Matisoo-Smith and Wells, {R. Spencer} and Oscar Acosta and Syama Adhikarla and Adler, {Christina J.} and Jaume Bertranpetit and Clarke, {Andrew C.} and Alan Cooper and {Der Sarkissian}, {Clio S.I.} and Wolfgang Haak and Marc Haber and Li Jin and Kaplan, {Matthew E.} and Hui Li and Shilin Li and Bego{\~n}a Mart{\'i}nez-Cruz and Merchant, {Nirav C.} and Mitchell, {John R.} and Laxmi Parida and Platt, {Daniel E.} and Lluis Quintana-Murci and Colin Renfrew and Lacerda, {Daniela R.} and Royyuru, {Ajay K.} and Sandoval, {Jose Raul} and Santhakumari, {Arun Varatharajan} and Hernanz, {David F.Soria} and Pandikumar Swamikrishnan and Ziegle, {Janet S.}",

note = "Funding Information: 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.",

year = "2014",

month = apr,

day = "29",

doi = "10.1038/ncomms4513",

language = "Ingl{\'e}s",

volume = "5",

journal = "Nature Communications",

issn = "2041-1723",

publisher = "Nature Publishing Group",

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Elhaik, E, Tatarinova, T, Chebotarev, D, Piras, IS, Calò, CM, De Montis, A, Atzori, M, Marini, M, Tofanelli, S, Francalacci, P, Pagani, L, Tyler-Smith, C, Xue, Y, Cucca, F, Schurr, TG, Gaieski, JB, Melendez, C, Vilar, MG, Owings, AC, Gómez, R, Fujita, R, Santos, FR, Comas, D, Balanovsky, O, Balanovska, E, Zalloua, P, Soodyall, H, Pitchappan, R, Prasad, AKG, Hammer, M, Matisoo-Smith, L, Wells, RS, Acosta, O, Adhikarla, S, Adler, CJ, Bertranpetit, J, Clarke, AC, Cooper, A, Der Sarkissian, CSI, Haak, W, Haber, M, Jin, L, Kaplan, ME, Li, H, Li, S, Martínez-Cruz, B, Merchant, NC, Mitchell, JR, Parida, L, Platt, DE, Quintana-Murci, L, Renfrew, C, Lacerda, DR, Royyuru, AK, Sandoval, JR, Santhakumari, AV, Hernanz, DFS, Swamikrishnan, P & Ziegle, JS 2014, 'Geographic population structure analysis of worldwide human populations infers their biogeographical origins', Nature Communications, vol. 5, 3513. https://doi.org/10.1038/ncomms4513

TY - JOUR

T1 - Geographic population structure analysis of worldwide human populations infers their biogeographical origins

AU - Elhaik, Eran

AU - Tatarinova, Tatiana

AU - Chebotarev, Dmitri

AU - Piras, Ignazio S.

AU - Calò, Carla Maria

AU - De Montis, Antonella

AU - Atzori, Manuela

AU - Marini, Monica

AU - Tofanelli, Sergio

AU - Francalacci, Paolo

AU - Pagani, Luca

AU - Tyler-Smith, Chris

AU - Xue, Yali

AU - Cucca, Francesco

AU - Schurr, Theodore G.

AU - Gaieski, Jill B.

AU - Melendez, Carlalynne

AU - Vilar, Miguel G.

AU - Owings, Amanda C.

AU - Gómez, Rocío

AU - Fujita, Ricardo

AU - Santos, Fabrício R.

AU - Comas, David

AU - Balanovsky, Oleg

AU - Balanovska, Elena

AU - Zalloua, Pierre

AU - Soodyall, Himla

AU - Pitchappan, Ramasamy

AU - Prasad, Arun Kumar Ganesh

AU - Hammer, Michael

AU - Matisoo-Smith, Lisa

AU - Wells, R. Spencer

AU - Acosta, Oscar

AU - Adhikarla, Syama

AU - Adler, Christina J.

AU - Bertranpetit, Jaume

AU - Clarke, Andrew C.

AU - Cooper, Alan

AU - Der Sarkissian, Clio S.I.

AU - Haak, Wolfgang

AU - Haber, Marc

AU - Jin, Li

AU - Kaplan, Matthew E.

AU - Li, Hui

AU - Li, Shilin

AU - Martínez-Cruz, Begoña

AU - Merchant, Nirav C.

AU - Mitchell, John R.

AU - Parida, Laxmi

AU - Platt, Daniel E.

AU - Quintana-Murci, Lluis

AU - Renfrew, Colin

AU - Lacerda, Daniela R.

AU - Royyuru, Ajay K.

AU - Sandoval, Jose Raul

AU - Santhakumari, Arun Varatharajan

AU - Hernanz, David F.Soria

AU - Swamikrishnan, Pandikumar

AU - Ziegle, Janet S.

N1 - Funding Information: 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.

PY - 2014/4/29

Y1 - 2014/4/29

N2 - 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.

AB - 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.

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U2 - 10.1038/ncomms4513

DO - 10.1038/ncomms4513

M3 - Artículo

C2 - 24781250

AN - SCOPUS:84899845427

SN - 2041-1723

VL - 5

JO - Nature Communications

JF - Nature Communications

M1 - 3513

ER -

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

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