Abstract
The genetic makeup of Indigenous populations inhabiting Mexico has been strongly influenced by geography and demographic history. Here, we perform a genome-wide analysis of 716 newly genotyped individuals from 60 of the 68 recognized ethnic groups in Mexico. We show that the genetic structure of these populations is strongly influenced by geography, and our demographic reconstructions suggest a decline in the population size of all tested populations in the last 15–30 generations. We find evidence that Aridoamerican and Mesoamerican populations diverged roughly 4–9.9 ka, around the time when sedentary farming started in Mesoamerica. Comparisons with ancient genomes indicate that the Upward Sun River 1 (USR1) individual is an outgroup to Mexican/South American Indigenous populations, whereas Anzick-1 was more closely related to Mesoamerican/South American populations than to those from Aridoamerica, showing an even more complex history of divergence than recognized so far.
| Originalsprog | Engelsk |
|---|---|
| Artikelnummer | 5942 |
| Tidsskrift | Nature Communications |
| Vol/bind | 12 |
| Antal sider | 12 |
| ISSN | 2041-1723 |
| DOI | |
| Status | Udgivet - 2021 |
Bibliografisk note
Funding Information:This study was designed in accordance with the Declaration of Helsinki and approved by the Research, Ethics, and Biosafety Human Committees of the Instituto Nacional de Medicina Genómica (INMEGEN) in Mexico City (protocol number 31/2011/I) with the support of the National Commission for the Development of Indigenous Communities (CDI, from the Spanish Comisión Nacional para el Desarrollo de Pueblos Indígenas) and with the agreement of the Indigenous leaders from each community. All participants provided written informed consent, and authorities or community leaders participated as translators when necessary. To perform our estimations, we generated several data sets merging our genotype data with those previously published for several worldwide populations and modern and ancient Native American individuals as follows. For data generated using only an SNV array, we performed the data handling and quality control procedures in Plink v1.961. Each data set was processed individually, including per marker and per sample examinations. We removed SNVs with genotyping rates <98% and those with a minor allele frequency of 1%, and then removed mitochondrial and sex chromosome SNVs. Finally, we excluded individuals with missing rates >3% and with discordant gender information.
Funding Information:
We thank the volunteers who donated their DNA samples for the realization of this project. This study was supported by the Consejo Nacional de Ciencia y Tecnología (http://www.conacyt.mx/) grant S008-2014-1 No. 233970 (L.O.). The funder had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. P.B. and M.F.-H. were supported by Consejo Nacional de Ciencia y Tec-nología (http://www.conacyt.mx/) fellowships (nos. 607882 and 596612, respectively). This article is dedicated to the memory of our colleagues José Concepción Jiménez-López and José Sánchez-Corona.
Publisher Copyright:
© 2021, The Author(s).