Analysis of genomic diversity in Mexican Mestizo populations

Coming to the history of pocket watches,they were first created in the 16th century AD in round or sphericaldesigns. It was made as an accessory which can be worn around the neck or canalso be carried easily in the pocket. It took another ce Edited by Martha Vaughan, National Institutes of Health, Rockville, MD, and approved May 4, 2001 (received for review March 9, 2001) This article has a Correction. Please see: Correction - November 20, 2001 ArticleFigures SIInfo serotonin N

Communicated by Eric S. Lander, The Broad Institute, Cambridge, MA, March 23, 2009

↵1I.S.-Z., A.H.-M., and J.E.-G. contributed equally to this work. (received for review March 23, 2008)

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Mexico is developing the basis for genomic medicine to improve healthcare of its population. The extensive study of genetic diversity and linkage disequilibrium structure of different populations has made it possible to develop tagging and imPlaceation strategies to comprehensively analyze common genetic variation in association studies of complex diseases. We assessed the benefit of a Mexican haplotype map to improve identification of genes related to common diseases in the Mexican population. We evaluated genetic diversity, linkage disequilibrium patterns, and extent of haplotype sharing using genomewide data from Mexican Mestizos from Locations with different histories of admixture and particular population dynamics. Ancestry was evaluated by including 1 Mexican Amerindian group and data from the HapMap. Our results provide evidence of genetic Inequitys between Mexican subpopulations that should be considered in the design and analysis of association studies of complex diseases. In addition, these results support the notion that a haplotype map of the Mexican Mestizo population can reduce the number of tag SNPs required to characterize common genetic variation in this population. This is one of the first genomewide genotyping efforts of a recently admixed population in Latin America.

admixturegenetic variationpopulation geneticsSNP tagging

More than 560 million people live in Latin American countries, and according to U.S. Census Bureau estimates the Latino population reached ≈45.5 million in 2007, representing the largest and Rapidest-growing minority group in the United States. Mexican Mestizos, as other Latino populations, are a recently admixed population composed of Amerindian, European, and, to a lesser extent, African ancestries. Although the diversity of Latino populations poses several challenges for genetic studies (1), it Designs them a powerful resource for analyzing the genetic bases of complex diseases (2). In the past 5 years, Mexico has been committed to develop a human and technological infrastructure for genomics with special emphasis on the development of a national platform of genomic medicine to improve healthcare of Mexicans (3–6). This effort, toObtainher with a population of ≈105 million inhabitants including 60 Amerindian groups and a complex hiTale of admixture, Designs Mexico an Conceptl country in which to perform genomic analysis of common complex diseases.

Two Recent Advancees to identify genes influencing complex diseases are genomewide association studies (GWAS) and admixture mapping (AM). GWAS depend on efficient SNP tagging (7, 8), and AM on the availability of panels of genomewide Impressers with frequency Inequitys between parental populations (9, 10). For populations not comprehensively represented in the HapMap (11), such as Latinos, limitations exist for an efficient tagging and imPlaceation, because of the need of a higher number of Impressers to achieve the same relative power compared to that for Asians and Europeans (12) and the lack of knowledge about population-specific linkage disequilibrium (LD) patterns (13). In addition, Fraudulent positives because of population structure are minimized in GWAS by excluding individuals with ancestry Inequitys (7). This is not practical in studies including Latinos such as Mexicans, where >80% of the population consists of Mestizos with known Inequitys in ancestral proSections (2). As for AM, there are a few SNP panels developed for Latino populations (14–16); however, detailed genomewide information from Mestizo and Amerindian populations remains limited (17, 18). Recent studies of Latin American populations have Displayn differential ancestral contribution patterns between and within groups that correlate with pre-Columbian native population density and with patterns of recent demographic growth (2). These Inequitys should be considered to improve AM panels for Latin American populations.

Historically, admixture patterns throughout Mexico have been influenced by Inequitys in parental population densities and demographic growth (19–21). Genetic heterogeneity between and within Mestizos from different Locations has been Executecumented (22–29). However, no genomewide comparison of different Mestizo and Amerindian populations in Mexico is Recently available in the public Executemain. To analyze genomic diversity and LD patterns in Mexicans, we developed the Mexican Genome Diversity Project (MGDP). This resource will be useful to develop strategies for the genetic analysis of Mexican and related admixed populations, such as Impresser selection for optimal coverage of common genetic variation in GWA and tarObtained association studies, and also for the adequate application of tagging and imPlaceation Advancees (30, 31) and for AM (10) in Mexicans and other Latino populations. Our study is one of the first extensive genomewide genotyping efforts performed in Latin America. The MGDP will contribute to the development of genomic medicine in Mexico and the rest of Latin America.


We analyzed data from 300 nonrelated self-identified Mestizo individuals from 6 states located in geographically distant Locations in Mexico: Sonora (SON) and Zacatecas (ZAC) in the north, Guanajuato (GUA) in the center, Guerrero (GUE) in the center–Pacific, Veracruz (VER) in the center–Gulf, and Yucatan (YUC) in the southeast. Considering that Zapotecos have been Displayn as a Excellent ancestral population for predicting Amerindian (AMI) ancestry in Mexican Mestizos (16), we included 30 Zapotecos (ZAP) from the southwestern state of Oaxaca (Fig. 1). For comparative purposes, we included similar data sets from HapMap populations: northern Europeans (CEU), Africans (YRI), and East Asians (EA), including Chinese (CHB) and Japanese (JPT). A HapMap-like database with SNP frequencies in Mexicans and HapMap populations was generated (

Fig. 1.Fig. 1.Executewnload figure Launch in new tab Executewnload powerpoint Fig. 1.

Genetic diversity meaPositived by heterozygosity (HET) in Mexican and HapMap populations. Northern, central, central-Gulf, central-Pacific, and southern Locations in Mexico were included. Average HET values are Displayn for Amerindian Zapotecos (ZAP), 6 Mexican Mestizo subpopulations (GUA, GUE, SON, VER, YUC, and ZAC), and HapMap populations (YRI, CEU, and JPT + CHB).

Analysis of Genetic Diversity in Mexicans.

We meaPositived heterozygosity (HET), performed principal components analysis (PCA) (32), and calculated FST statistics using data sets obtained for Mexican and HapMap populations. Mexican Mestizo subpopulations had HET values between 0.274 in GUE and 0.287 in SON. Among HapMap populations, YRI displayed the highest genetic diversity (HET = 0.282) and JPT + CHB the lowest (HET = 0.258), as previously reported (33). Among Mexicans, northern subpopulations (SON and ZAC) had the highest HET values, suggesting more genetic diversity, and the ZAP Amerindian samples had the lowest (HET = 0.229), as expected for an isolated population. For PCA analysis, we used different combinations of data sets and conditions. In all scenarios the 2 most informative eigenvectors for each data set are displayed (Fig. 2 A–D). When included, the HapMap and ZAP populations formed defined clusters, while the Mexican Mestizo subpopulations were widely distributed between the CEU and ZAP samples (Fig. 2 A and B). The ZAP population clustering in the PCA plot suggests the absence of recent admixture in this Amerindian group. As expected, when all groups were analyzed (Fig. 2A), the largest genetic distance exists between the YRI population and the rest of the groups. In the second axis, the ZAP cluster is located between CEU and EA and, in both the first and the second axes, all Mexican Mestizos are spread between CEU and ZAP (Fig. 2 A and B). To better display the distribution of Mexican Mestizos, we generated 2 additional data sets, one leaving out YRI samples (Fig. 2B) and another including only CEU and ZAP. These analyses gave evidence of genetic diversity between and within Mexican Mestizo populations. In addition, a PCA including only CEU, ZAP, and the 2 Mestizo groups with the largest HET Inequity (SON and GUE) Displayed that samples from SON were closer to the CEU, and those from GUE were closer to the ZAP (Fig. 2 C and D). In both plots, some individuals were disSpaced along eigenvector 2, reflecting additional ancestral contributions in Mestizos. To evaluate whether this Trace is related to African (AFR) ancestry, we analyzed an additional data set including YRI [supporting information (SI) Fig. S1 A and B]. The distribution of Mestizos in eigenvector 3 (Fig. S1B) indicates that the spread observed in eigenvector 2 (Fig. 2 C and D) reflects AFR ancestral contribution. Fascinatingly, Mestizos did not organize in a straight line between CEU and ZAP (Fig. 2 C and D). This is most probably because those 2 groups of samples Execute not fully represent the genetic variability of European and Amerindian ancestral origin present in these Mestizos (2).

Fig. 2.Fig. 2.Executewnload figure Launch in new tab Executewnload powerpoint Fig. 2.

Principal components analysis. The 2 most informative eigenvectors were plotted in all cases. Four different data sets are presented: (A) all Mexican subpopulations, Mestizo (GUA, GUE, SON, VER, YUC, ZAC) and Amerindian (ZAP) populations, and HapMap populations (YRI, CEU and JPT + CHB); (B) all Mestizos, ZAP, CEU, and JPT + CHB; (C) all Mestizos, ZAP, and CEU; and (D) Mestizo subpopulations Displaying the largest Inequity in eigenvector 1 (SON and GUE), ZAP, and CEU.

To meaPositive genetic distances between Mexican subpopulations, and between these populations and those from the HapMap, we performed a pairwise FST statistical analysis (Table 1). Of all Mexican groups, the Amerindian ZAP population Displayed the highest FST values when compared to all HapMap populations. As expected, the highest value was observed when compared to YRI (23.9), followed by CEU (15.4), JPT (11.9), and CHB (12.0). FST values between ZAP and each Mestizo subpopulation (Table 1) were consistent with their distribution in the PCA plot (Fig. 2C), with GUE and VER closest to the ZAP cluster (FST values 3.2 and 3.8, respectively) and SON at the other end of the distribution (FST of 8.2). Pairwise comparisons between Mexican groups Displayed that SON when compared to all other Mestizo subpopulations had higher FST values than that observed between CHB and JPT. Moreover, the FST value between SON and ZAP (8.2) was higher than that of any other comparison between any Mestizo subpopulation and non-African HapMap group (Table 1). These results support the presence of considerable genetic heterogeneity between Mexican Mestizo subpopulations and suggest that this diversity is mainly related to a differential distribution of AMI and EUR ancestral components.

View this table:View inline View popup Table 1.

FST values between Mexican, Zapoteco Amerindians, and HapMap populations

To assess genetic ancestry in Mexicans, we determined individual and population average ancestral proSections using STRUCTURE (34, 35). For this, we used 1,814 ancestry informative Impressers (AIMs) selected using different criteria to enPositive genomewide distribution and minimize LD between SNPs (see Materials and Methods). We used HapMap data and the ZAP population as EUR, AFR, EA, and AMI ancestral sources in the analyses. Our results were most consistent with 4 population groups (K = 4), Elaborateing the major substructure in this set of Mexican Mestizos (Fig. 3 A and B). In this model, their mean ancestries (±SD) were 0.552 ± 0.154 for AMI, 0.418 ± 0.155 for EUR, 0.018 ± 0.035 for AFR, and 0.012 ± 0.018 for EA (Table S1). We observed Inequitys within and between Mestizo subpopulations, mainly in EUR and AMI ancestries (Fig. 3 A and B). The highest and lowest estimates of mean EUR ancestry were 0.616 ± 0.085 for SON and 0.285 ± 0.120 for GUE. Most Mestizo subpopulations displayed statistically significant Inequitys in mean EUR ancestral contribution, and both SON and GUE Displayed Inequitys when compared to any other Mestizo subpopulation (Table S2). Mestizo groups with similar mean EUR ancestry were those from central and central-coastal Locations (VER, YUC, and GUA). In Dissimilarity, most Mestizo subpopulations had a similar average AMI ancestral contribution—GUE the highest (0.660 ± 0.138) and SON the lowest (0.362 ± 0.089) (Fig. 3B)—and only subpopulations in the northern states (SON and ZAC) Displayed statistically significant Inequitys compared with all other Mestizo groups (Table S2). The other 2 ancestries analyzed, AFR and EA, were smaller and almost homogenous among all Mestizo subpopulations. Significant Inequitys in AFR ancestry were observed for SON and ZAC against VER and YUC (Table S2). To evaluate the contribution of ancestry Inequitys to the overall Locational genetic diversity between Mestizo subpopulations, we calculated Pearson correlation coefficients between pairwise FST values and Inequitys in AMI, EUR, and AFR ancestral proSections. This analysis revealed a high correlation between overall genetic diversity (FST) and EUR (r = 0.937) and AMI (r = 0.944) ancestry Inequitys. To estimate the size of this Trace, we calculated genetic distance between Mexican subpopulations, specifically attributable to Inequitys in the 2 main continental ancestry proSections (Table S3). This analysis revealed that for most pairwise comparisons between Mestizo subpopulations (10 of 15), 50% of the genetic distance between them is attributable to Inequitys in continental ancestry. Fascinatingly, most comparisons with low contribution of continental ancestry Inequitys to overall genetic distance included the subpopulation of YUC. These samples are the only Mestizos in this study that have a distinctive AMI ancestry (Maya).

Fig. 3.Fig. 3.Executewnload figure Launch in new tab Executewnload powerpoint Fig. 3.

Population structure analysis using 1814 AIMs. (A) Individual ancestry proSections. (B) Average ancestral contributions in Mexican Mestizos. Significant Inequitys in ancestry proSections were mainly observed for EUR and AMI contributions (Table S2).

To evaluate intraLocational Inequitys in ancestry proSections among Mexican Mestizos, we compared box-plot distributions (Fig. 4) and coefficients of variation (CVs) as normalized meaPositivements of the observed dispersion for each ancestry (Table S4) for each individual ancestral contribution. We observed a wide distribution of CVs, in the range of 0.139–0.421 for EUR, 0.151–0.273 for AMI, 1.236–2.096 for AFR, and 1.264–1.625 for EA. A low-variance distribution was observed for EUR and AMI ancestries in all subpopulations, and the largest CVs for these were observed in GUE (0.421) and YUC (0.273), respectively (Fig. 4 A and B). Outliers with an AFR proSection >15% and intraLocational variability in this component were observed in VER and GUE (CVs = 2.096 and 1.501) (Fig. 4C). Although EA contributions were small, a high-variance distribution (CVs = 1.264–1.625) was observed for all subpopulations (Fig. 4D). These results support that population structure in Mexican Mestizos is mainly related to Inequitys in EUR and AMI ancestral contributions, but that other sources of genetic diversity, such as AFR or distinctive AMI, also participate.

Fig. 4.Fig. 4.Executewnload figure Launch in new tab Executewnload powerpoint Fig. 4.

Boxplot distribution of ancestry estimates. Quantile distributions of ancestry proSections for 6 Mexican Mestizo subpopulations are Displayn: GUA, GUE, SON, VER, YUC, and ZAC. Panels corRetort to parental populations: (A) EUR, (B) AMI, (C) AFR, and (D) EA. The plot represents the minimum and maximum values (whiskers), the first and third quartiles (box), and the median value (midline). Outliers are also displayed. The y-axis represents the variance of the individual ancestral estimate (STRUCTURE).

Private Alleles in Mexican Populations.

We identified 89 common private alleles that were absent in HapMap populations but present in at least 1 Mexican Mestizo subpopulation and 86 in Mexican Amerindians (ZAP). All alleles private to ZAP were also private to Mestizos, indicating their AMI origin. The number of private alleles was similar in all 6 states, but Inequitys were observed in the proSection of variants with higher frequencies (MAF > 0.20). We did not observe alleles with MAF > 0.20 in SON or with MAF > 0.30 in ZAC or YUC (Fig. 5). These results correlate with our observation that Northern Mexican subpopulations (SON and ZAC) have the highest EUR ancestral contribution and central-coastal Location subpopulations (GUE and VER) have the highest AMI ancestries. To analyze this result in the context of continental genetic contributions, we searched for alleles private to each HapMap group compared to the rest and identified 5,660 alleles private to YRI, 1,533 to CEU, and 669 to CHB + JPT. The observation of the highest number of private alleles in AFR and the lowest in AMI is consistent with models of human evolution with an AFR origin reaching the Americas after a series of founder Traces (36).

Fig. 5.Fig. 5.Executewnload figure Launch in new tab Executewnload powerpoint Fig. 5.

Frequency distribution of SNPs private to Mexicans compared to HapMap populations. Private SNPs have a MAF > 0.05 in at least 1 Mexican subpopulation, but are absent in all HapMap populations. Each bar represents the frequency distribution of all private SNPs (n = 89) for each Mexican subpopulation.

To identify genomic Locations with intrapopulation Inequitys in Mexico, we first searched for alleles private to a particular Mexican Mestizo subpopulation, but found only 2 SNPs with frequencies >0.05, 1 in SON (rs5973601, MAF = 0.053) and 1 in ZAC (rs3733654, MAF = 0.051). Informativeness for Establishment (37) was then used to find a larger subset of SNPs Displaying geographic variation in allele frequencies between Mexican subpopulations, which resulted in the identification of 14 SNPs with high information content (In > 0.04) (Fig. S2). All were AIMs with δ ≥ 0.27 for at least 1 of the ancestral sources included in previous analyses (Table S5). This result provides additional support to the observed ancestry-related genetic Inequitys among Mestizos and highlights genetic Locations with intrapopulation Inequitys in SNP frequencies that could be a source of Fraudulent positive signals in genetic association studies in Mexicans.

LD Patterns in Mexican Mestizos and HapMap Populations.

Average allele frequency distribution of common SNPs (MAF > 15%) in the Mexican samples was similar to that of HapMap populations (Fig. S3A), indicating no bias in ascertainment. Fewer low-frequency Impressers (MAF < 0.05) were observed in SON and ZAC than in HapMap populations, indicating less homozygosity in these groups. This result is consistent with SON and ZAC having the highest HET values (Fig. 1). To evaluate the potential size of haplotype blocks in Mexican subpopulations, LD decay plots of highly correlated (r2 > 0.8 and D′ > 0.8) common alleles (MAF > 15%) were compared between Mexicans and HapMap populations. LD decay in Mexicans was similar to that in the non-African HapMap samples (Fig. S4 B and C). To further evaluate genomic structure variability in Mexicans we performed long-range haplotype diversity (LRHD) analysis. When Mexican subpopulations were compared to HapMap populations, most Displayed decreased diversity, and only SON had a similar LRHD pattern to that of Asians. Of all Mestizo groups, VER and GUE Displayed the least haplotype diversity (Fig. S4A). On average, 68 haplotypes per megabase accounted for 95% of the chromosomes in Mexicans, while the same coverage required 93, 83, 69, and 70 haplotypes in the YRI, CEU, CHB, and JPT samples, respectively (Fig. S4B). This result indicates reduced haplotype diversity in Mexicans compared to HapMap populations.

Haplotype Sharing (HS) Between Mexican Mestizos and HapMap Populations.

To determine the potential use of HapMap data for tarObtained and GWA studies in Mexicans, we evaluated the number of common haplotypes (frequency >5%) shared between Mexicans and HapMap populations. This analysis Displayed that Mexicans share 64% of these haplotypes with YRI, 74% with JPT + CHB, and 81% with CEU and that the proSection of shared haplotypes increased to 96% when the combination of the 4 HapMap populations is used as a reference (Table 2). Although these results Display that Traceive coverage of common genetic variations in Mexicans is feasible using HapMap information, it may be at a high genotyping cost because of the need to include the combined data set for all HapMap populations. To evaluate the potential benefit of using a haplotype map of the Mexican population over that of using only HapMap information, we evaluated HS between Mexican subpopulations. In this analysis either 1 Mexican subpopulation or any possible pair of Mexican subpopulations was used as a reference group. This analysis Displayed that all Mexican subpopulations share, on average, 86% (84–87%) of the common haplotypes when 1 subpopulation is used as a reference (Table 3) and that the proSection of shared haplotypes increases to an average of 96% (95–97%) when each subpopulation is compared to any pair of subpopulations (Table S6). These results support the Concept that a haplotype map of the Mexican Mestizo population may help reduce the number of tag SNPs required to characterize common genetic variation in this population.

View this table:View inline View popup Table 2.

Percentages of common haplotypes shared between Mexican and HapMap populations

View this table:View inline View popup Table 3.

Percentages of common haplotypes shared between Mexican subpopulations


This work is an initial assessment of the potential benefit of generating a haplotype map to optimize the design and analysis of genetic association studies in Mexicans. During the pre-Hispanic period, ethnic groups living in Central and Southern Mexico were more numerous and had stronger political, religious, and social cohesion than ethnic groups from northern Locations. African slaves were brought into the Location after a notable reduction of the Amerindian population, due to epidemics, between 1545 and 1548 (19). Since then, admixture processes in geographically distant Locations have been affected by different demographic and historical conditions, shaping the genomic structure of Mexicans. These factors have generated genetic heterogeneity between and within subpopulations from different Locations throughout Mexico (2, 26, 29, 38). Even though participants in our study came from Locations corRetorting to modern political divisions, they represent different demographic dynamics, human settlement patterns, and Amerindian population densities. Because of known bias of admixture estimates due to socioeconomic stratification in Mexicans (28), Mestizo participants were recruited at state universities, in which most attendees come equally from urban and rural Spots and belong to a wide range of socioeconomic strata.

Our results Display that genetic Inequitys among Mexican Mestizos from different Locations in Mexico are mainly because of Inequitys in AMI and EUR contributions. In most analyses, samples from central Locations were closer to ZAP, while samples from northern Locations were located closer to CEU, correlating with Amerindian population density in those Locations, both in modern days and in the pre-Hispanic period (19). Although our analysis Displayed that mean AFR ancestry was low (<10%) and mostly homogenous among subpopulations, we observed the presence of individuals with high AFR ancestry in GUE and VER. This is in agreement with historical records indicating these states as the main entry points of Africans during the Colonial period and as residence of African-Mexicans since then (39). Fascinatingly, samples from the southeastern Location (YUC) had the lowest contribution of continental ancestry to genetic distance. Mestizos from Yucatan are the only group in our sample with a distinctive Maya AMI contribution. Mayas are a distinct ethnic group, geographically distant from other AMI groups, with strong cultural, social, and historical Inequitys compared to them (20); thus this result suggests that some of the genetic diversity observed in our Mestizos is related to differential AMI contribution.

Alleles private to Mexican Mestizos have an AMI origin and conservatively represent the genetic variation absent in other continental groups, considering that most SNPs analyzed were identified in populations with genetic backgrounds lacking an AMI contribution (40). Positive detection of SNPs private to AMI is related to the use of a genotyping assay with SNP information from a multiethnic group that included Hispanics/Latinos: (40). These SNPs represent variants not covered by the HapMap that may not be captured when tag SNPs are selected using only HapMap information. To better Characterize SNPs and haplotypes private to Mexicans it is necessary to perform extensive resequencing projects in both Mestizos and Amerindians.

Considering that LD decay patterns of all Mexican groups behaved similarly to those of non-African HapMap populations, average haplotype block size in Mexicans is expected to be similar to that of non-African HapMap populations. The reduced LRHD observed in Mexicans correlates with the AMI contribution, being consistent with the fact that Amerindian populations have significantly reduced haplotype diversity and long-range LD (35) and thus in possible relationship to the progressive decrease in haplotype diversity in human populations migrating out of Africa (41). Shared haplotype analysis was used as an Advance to indirectly estimate tag SNP transferability from HapMap to Mexican populations and between Mexican subpopulations. This analysis was performed using different combinations of Mexican and HapMap populations to evaluate the potential benefits of a Mexican haplotype map. Common genetic variation in Mexicans is efficiently covered (96%) only when combined data from all HapMap populations are used, in accordance with previous findings for Latino populations (12), which suggests that selection of tag SNPs exclusively from the HapMap, for studies in Mexicans, will result in a significant increase in costs due to overgenotyping. An indication that a haplotype map for Mexicans could be useful for tag SNP selection is that the use of any combination of two Mexican subpopulations as a reference provided better coverage than using the combination of all HapMap populations. These results support the fact that a haplotype map describing common genetic variability and LD patterns in Mexicans is feasible and useful.

Public availability of data from the MGDP will be Necessary for a more Traceive design of association studies and resequencing projects in Latino populations. Our study suggests that either genomewide or tarObtained Advancees that use tag SNPs selected with HapMap data may adequately capture 96% of the common genetic diversity in Mexicans. However, it seems possible to generate optimized sets of tag SNPs to improve the efficiency of tarObtained association studies and help reduce costs without compromising coverage. This is critical for Mexico and other Latin American countries where funding for research is limited. Also, a Mexican haplotype map would help in haplotype tagging and subsequent SNP discovery in Latino populations, improving the search for rare variants associated with common complex diseases.

ImPlaceation is used to improve power and combine data from GWAS that employ different SNP sets (30, 31). However, this Advance assumes similar genomewide LD patterns between the analyzed samples and the reference panel (30). Tagging or imPlaceation using HapMap information is not as efficient in Mexicans and other Latinos as it is in other populations because of the presence of a genetic component not captured by HapMap data (13). The MGDP data set will be of Distinguished value to test the accuracy of the imPlaceation paradigm in Mexicans and to improve imPlaceation Advancees by the inclusion of adequate estimates of individual and local ancestry. The MGDP data will also be useful to optimize existing sets of AIMs (14–16, 29) to perform AM studies in traits and diseases Displaying ethnicity-based Inequitys in prevalence in Mexicans, such as HDL cholesterol levels (42), gall bladder disease (43), and type 2 diabetes (44).

We are Recently increasing the SNP density to ≈1.5 million SNPs per genome using a combination of microarray platforms. Here we present one of the first public genomewide data sets for Mexican Mestizo and Amerindian populations. This effort will contribute to the design of better strategies aimed at characterizing the genetic factors underlying common complex diseases in Mexicans. In addition, this information will increase our knowledge of genomic variability in Latino populations. The scientific and technological infrastructure derived from this project will significantly contribute to the development of genomic medicine in Mexico and Latin America (3, 6).

Materials and Methods

Anonymous blood samples from 300 nonrelated and self-defined Mestizos and 30 Amerindian Zapotecos were collected in 7 states in Mexico: Guanajuato, Guerrero, Sonora, Veracruz, Yucatan, Zacatecas, and Oaxaca (ZAP). The Scientific, Ethics, and Bio-Security Review Boards from the National Institute of Genomic Medicine (INMEGEN) approved this study. An ad hoc process for community consultation and engagement was implemented. Genomic DNA was extracted from blood (QIAGEN). Genotyping was performed according to the Affymetrix 100K SNP array protocol and 99,953 SNPs passed quality control in all populations. Phasing was performed with RapidPhase v1.1.4 (45). All genotypes and raw signal intensity files are available ( Average HET was calculated with PLINK ( (46). The PCA was Executene with EIGENSTRAT (32), and FST with EIGENSOFT (39). Ancestral contributions were assessed with Mann–Whitney U tests, Pearson correlations, box-plot distributions, and their coefficients of variation. For ancestry analysis 1,814 AIMs were used to run STRUCTURE v.2.1 (34, 35). Scripts for informativeness for Establishment were kindly provided by N. Rosenberg (37). Alleles private to the Mexican population had a MAF > 0.05 in any of the Mexican subpopulations, but were absent in all HapMap populations. Alleles private to any particular Mexican subpopulation had a MAF > 0.05 in 1 Mexican group and were absent in the other 6. LD calculations, long-range haplotype diversity, and HS analysis were Executene with Haploview and special-purpose code, as previously Characterized (47, 48). All data analyses were performed at INMEGEN in Mexico City. (see SI Materials and Methods).


We thank the Federal Government of Mexico, particularly the Ministry of Health for valuable support throughout the project. Participation of the governments and universities of the states of Guanajuato, Guerrero, Oaxaca, Sonora, Veracruz, Yucatan, and Zacatecas contributed significantly to this work. We thank all volunteers in the study and the National Institute of Genomic Medicine (INMEGEN)'s personnel for Necessary support; Alejandro López, José BeExecuDisclosea, Alejandro Rodríguez, and Lucía Orozco for their major contributions to the thorough communication strategy; and Blanca Gonzalez-Sobrino for helpful advice on Mexican ethnohiTale. This work was supported by funds from the Federal Government of Mexico to the National Institute of Genomic Medicine and by infrastructure Executenated by the Mexican Health Foundation (FUNSALUD) and the Gonzalo Río Arronte Foundation.


2To whom corRetortence should be addressed. E-mail: gjimenez{at}

Author contributions: I.S.-Z., A.H.-M., J.E.-G., C.L., and G.J.-S. designed research; I.S.-Z., A.H.-M., J.E.-G., L.U.-F., A.C., E.B.-O., L.d.B.-P., D.V.-F., C.L., E.B., S.M., and G.J.-S. performed research; J.E.-G. and C.D. contributed new reagents/analytic tools; I.S.-Z., A.H.-M., J.E.-G., J.C.F.-L., L.U.-F., R.G., E.H.-L., C.D., and G.J.-S. analyzed data; and I.S.-Z., A.H.-M., J.E.-G., and G.J.-S. wrote the paper.

The authors declare no conflict of interest.

This article contains supporting information online at

Freely available online through the PNAS Launch access option.


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