Professional Education

  • Master of Science, Stanford University, ANSCI-MS (2006)
  • Bachelor of Science, Stanford University, MUSIC-MIN (2006)
  • Bachelor of Science, Stanford University, BIOL-BS (2006)

Stanford Advisors

Research & Scholarship

Lab Affiliations


All Publications

  • Reconstructing the population genetic history of the Caribbean. PLoS genetics Moreno-Estrada, A., Gravel, S., Zakharia, F., McCauley, J. L., Byrnes, J. K., Gignoux, C. R., Ortiz-Tello, P. A., Martínez, R. J., Hedges, D. J., Morris, R. W., Eng, C., Sandoval, K., Acevedo-Acevedo, S., Norman, P. J., Layrisse, Z., Parham, P., Martínez-Cruzado, J. C., Burchard, E. G., Cuccaro, M. L., Martin, E. R., Bustamante, C. D. 2013; 9 (11)


    The Caribbean basin is home to some of the most complex interactions in recent history among previously diverged human populations. Here, we investigate the population genetic history of this region by characterizing patterns of genome-wide variation among 330 individuals from three of the Greater Antilles (Cuba, Puerto Rico, Hispaniola), two mainland (Honduras, Colombia), and three Native South American (Yukpa, Bari, and Warao) populations. We combine these data with a unique database of genomic variation in over 3,000 individuals from diverse European, African, and Native American populations. We use local ancestry inference and tract length distributions to test different demographic scenarios for the pre- and post-colonial history of the region. We develop a novel ancestry-specific PCA (ASPCA) method to reconstruct the sub-continental origin of Native American, European, and African haplotypes from admixed genomes. We find that the most likely source of the indigenous ancestry in Caribbean islanders is a Native South American component shared among inland Amazonian tribes, Central America, and the Yucatan peninsula, suggesting extensive gene flow across the Caribbean in pre-Columbian times. We find evidence of two pulses of African migration. The first pulse--which today is reflected by shorter, older ancestry tracts--consists of a genetic component more similar to coastal West African regions involved in early stages of the trans-Atlantic slave trade. The second pulse--reflected by longer, younger tracts--is more similar to present-day West-Central African populations, supporting historical records of later transatlantic deportation. Surprisingly, we also identify a Latino-specific European component that has significantly diverged from its parental Iberian source populations, presumably as a result of small European founder population size. We demonstrate that the ancestral components in admixed genomes can be traced back to distinct sub-continental source populations with far greater resolution than previously thought, even when limited pre-Columbian Caribbean haplotypes have survived.

    View details for DOI 10.1371/journal.pgen.1003925

    View details for PubMedID 24244192

  • Factors associated with degree of atopy in Latino children in a nationwide pediatric sample: The Genes-environments and Admixture in Latino Asthmatics (GALA II) study JOURNAL OF ALLERGY AND CLINICAL IMMUNOLOGY Kumar, R., Nguyen, E. A., Roth, L. A., Oh, S. S., Gignoux, C. R., Huntsman, S., Eng, C., Moreno-Estrada, A., Sandoval, K., Penaloza-Espinosa, R. I., Lopez-Lopez, M., Avila, P. C., Farber, H. J., Tcheurekdjian, H., Rodriguez-Cintron, W., Rodriguez-Santana, J. R., Serebrisky, D., Thyne, S. M., Williams, L. K., Winkler, C., Bustamante, C. D., Perez-Stable, E. J., Borrell, L. N., Burchard, E. G. 2013; 132 (4): 896-?


    BACKGROUND: Atopy varies by ethnicity, even within Latino groups. This variation might be due to environmental, sociocultural, or genetic factors. OBJECTIVE: We sought to examine risk factors for atopy within a nationwide study of US Latino children with and without asthma. METHODS: Aeroallergen skin test responses were analyzed in 1830 US Latino subjects. Key determinants of atopy included country/region of origin, generation in the United States, acculturation, genetic ancestry, and site to which subjects migrated. Serial multivariate zero-inflated negative binomial regressions stratified by asthma status examined the association of each key determinant variable with the number of positive skin test responses. In addition, the independent effect of each key variable was determined by including all key variables in the final models. RESULTS: In baseline analyses African ancestry was associated with 3 times (95% CI, 1.62-5.57) as many positive skin test responses in asthmatic participants and 3.26 times (95% CI, 1.02-10.39) as many positive skin test responses in control participants. Generation and recruitment site were also associated with atopy in crude models. In final models adjusted for key variables, asthmatic patients of Puerto Rican (exp[?] [95% CI], 1.31 [1.02-1.69]) and mixed (exp[?] [95% CI], 1.27 [1.03-1.56]) ethnicity had a greater probability of positive skin test responses compared with Mexican asthmatic patients. Ancestry associations were abrogated by recruitment site but not region of origin. CONCLUSIONS: Puerto Rican ethnicity and mixed origin were associated with degree of atopy within US Latino children with asthma. African ancestry was not associated with degree of atopy after adjusting for recruitment site. Local environment variation, represented by site, was associated with degree of sensitization.

    View details for DOI 10.1016/j.jaci.2013.02.046

    View details for Web of Science ID 000325096500017

    View details for PubMedID 23684070

  • Gene flow from North Africa contributes to differential human genetic diversity in southern Europe PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA Botigue, L. R., Henn, B. M., Gravel, S., Maples, B. K., Gignoux, C. R., Corona, E., Atzmon, G., Burns, E., Ostrer, H., Flores, C., Bertranpetit, J., Comas, D., Bustamante, C. D. 2013; 110 (29): 11791-11796


    Human genetic diversity in southern Europe is higher than in other regions of the continent. This difference has been attributed to postglacial expansions, the demic diffusion of agriculture from the Near East, and gene flow from Africa. Using SNP data from 2,099 individuals in 43 populations, we show that estimates of recent shared ancestry between Europe and Africa are substantially increased when gene flow from North Africans, rather than Sub-Saharan Africans, is considered. The gradient of North African ancestry accounts for previous observations of low levels of sharing with Sub-Saharan Africa and is independent of recent gene flow from the Near East. The source of genetic diversity in southern Europe has important biomedical implications; we find that most disease risk alleles from genome-wide association studies follow expected patterns of divergence between Europe and North Africa, with the principal exception of multiple sclerosis.

    View details for DOI 10.1073/pnas.1306223110

    View details for Web of Science ID 000322086100040

    View details for PubMedID 23733930

  • An integrated map of genetic variation from 1,092 human genomes NATURE Altshuler, D. M., Durbin, R. M., Abecasis, G. R., Bentley, D. R., Chakravarti, A., Clark, A. G., Donnelly, P., Eichler, E. E., Flicek, P., Gabriel, S. B., Gibbs, R. A., Green, E. D., Hurles, M. E., Knoppers, B. M., Korbel, J. O., Lander, E. S., Lee, C., Lehrach, H., Mardis, E. R., Marth, G. T., McVean, G. A., Nickerson, D. A., Schmidt, J. P., Sherry, S. T., Wang, J., Wilson, R. K., Gibbs, R. A., Dinh, H., Kovar, C., Lee, S., Lewis, L., Muzny, D., Reid, J., Wang, M., Wang, J., Fang, X., Guo, X., Jian, M., Jiang, H., Jin, X., Li, G., Li, J., Li, Y., Li, Z., Liu, X., Lu, Y., Ma, X., Su, Z., Tai, S., Tang, M., Wang, B., Wang, G., Wu, H., Wu, R., Yin, Y., Zhang, W., Zhao, J., Zhao, M., Zheng, X., Zhou, Y., Lander, E. S., Altshuler, D. M., Gabriel, S. B., Gupta, N., Flicek, P., Clarke, L., Leinonen, R., Smith, R. E., Zheng-Bradley, X., Bentley, D. R., Grocock, R., Humphray, S., James, T., Kingsbury, Z., Lehrach, H., Sudbrak, R., Albrecht, M. W., Amstislavskiy, V. S., Borodina, T. A., Lienhard, M., Mertes, F., Sultan, M., Timmermann, B., Yaspo, M., Sherry, S. T., McVean, G. A., Mardis, E. R., Wilson, R. K., Fulton, L., Fulton, R., Weinstock, G. M., Durbin, R. M., Balasubramaniam, S., Burton, J., Danecek, P., Keane, T. M., Kolb-Kokocinski, A., McCarthy, S., Stalker, J., Quail, M., Schmidt, J. P., Davies, C. J., Gollub, J., Webster, T., Wong, B., Zhan, Y., Auton, A., Gibbs, R. A., Yu, F., Bainbridge, M., Challis, D., Evani, U. S., Lu, J., Muzny, D., Nagaswamy, U., Reid, J., Sabo, A., Wang, Y., Yu, J., Wang, J., Coin, L. J., Fang, L., Guo, X., Jin, X., Li, G., Li, Q., Li, Y., Li, Z., Lin, H., Liu, B., Luo, R., Qin, N., Shao, H., Wang, B., Xie, Y., Ye, C., Yu, C., Zhang, F., Zheng, H., Zhu, H., Marth, G. T., Garrison, E. P., Kural, D., Lee, W., Leong, W. F., Ward, A. N., Wu, J., Zhang, M., Lee, C., Griffin, L., Hsieh, C., Mills, R. E., Shi, X., von Grotthuss, M., Zhang, C., Daly, M. J., DePristo, M. A., Altshuler, D. M., Banks, E., Bhatia, G., Carneiro, M. O., del Angel, G., Gabriel, S. B., Genovese, G., Gupta, N., Handsaker, R. E., Hartl, C., Lander, E. S., McCarroll, S. A., Nemesh, J. C., Poplin, R. E., Schaffner, S. F., Shakir, K., Yoon, S. C., Lihm, J., Makarov, V., Jin, H., Kim, W., Kim, K. C., Korbel, J. O., Rausch, T., Flicek, P., Beal, K., Clarke, L., Cunningham, F., Herrero, J., McLaren, W. M., Ritchie, G. R., Smith, R. E., Zheng-Bradley, X., Clark, A. G., Gottipati, S., Keinan, A., Rodriguez-Flores, J. L., Sabeti, P. C., Grossman, S. R., Tabrizi, S., Tariyal, R., Cooper, D. N., Ball, E. V., Stenson, P. D., Bentley, D. R., Barnes, B., Bauer, M., Cheetham, R. K., Cox, T., Eberle, M., Humphray, S., Kahn, S., Murray, L., Peden, J., Shaw, R., Ye, K., Batzer, M. A., Konkel, M. K., Walker, J. A., MacArthur, D. G., Lek, M., Sudbrak, R., Amstislavskiy, V. S., Herwig, R., Shriver, M. D., Bustamante, C. D., Byrnes, J. K., De La Vega, F. M., Gravel, S., Kenny, E. E., Kidd, J. M., Lacroute, P., Maples, B. K., Moreno-Estrada, A., Zakharia, F., Halperin, E., Baran, Y., Craig, D. W., Christoforides, A., Homer, N., Izatt, T., Kurdoglu, A. A., Sinari, S. A., Squire, K., Sherry, S. T., Xiao, C., Sebat, J., Bafna, V., Ye, K., Burchard, E. G., Hernandez, R. D., Gignoux, C. R., Haussler, D., Katzman, S. J., Kent, W. J., Howie, B., Ruiz-Linares, A., Dermitzakis, E. T., Lappalainen, T., Devine, S. E., Liu, X., Maroo, A., Tallon, L. J., Rosenfeld, J. A., Michelson, L. P., Abecasis, G. R., Kang, H. M., Anderson, P., Angius, A., Bigham, A., Blackwell, T., Busonero, F., Cucca, F., Fuchsberger, C., Jones, C., Jun, G., Li, Y., Lyons, R., Maschio, A., Porcu, E., Reinier, F., Sanna, S., Schlessinger, D., Sidore, C., Tan, A., Trost, M. K., Awadalla, P., Hodgkinson, A., Lunter, G., McVean, G. A., Marchini, J. L., Myers, S., Churchhouse, C., Delaneau, O., Gupta-Hinch, A., Iqbal, Z., Mathieson, I., Rimmer, A., Xifara, D. K., Oleksyk, T. K., Fu, Y., Liu, X., Xiong, M., Jorde, L., Witherspoon, D., Xing, J., Eichler, E. E., Browning, B. L., Alkan, C., Hajirasouliha, I., Hormozdiari, F., Ko, A., Sudmant, P. H., Mardis, E. R., Chen, K., Chinwalla, A., Ding, L., Dooling, D., Koboldt, D. C., McLellan, M. D., Wallis, J. W., Wendl, M. C., Zhang, Q., Durbin, R. M., Hurles, M. E., Tyler-Smith, C., Albers, C. A., Ayub, Q., Balasubramaniam, S., Chen, Y., Coffey, A. J., Colonna, V., Danecek, P., Huang, N., Jostins, L., Keane, T. M., Li, H., McCarthy, S., Scally, A., Stalker, J., Walter, K., Xue, Y., Zhang, Y., Gerstein, M. B., Abyzov, A., Balasubramanian, S., Chen, J., Clarke, D., Fu, Y., Habegger, L., Harmanci, A. O., Jin, M., Khurana, E., Mu, X. J., Sisu, C., Li, Y., Luo, R., Zhu, H., Lee, C., Griffin, L., Hsieh, C., Mills, R. E., Shi, X., von Grotthuss, M., Zhang, C., Marth, G. T., Garrison, E. P., Kural, D., Lee, W., Ward, A. N., Wu, J., Zhang, M., McCarroll, S. A., Altshuler, D. M., Banks, E., del Angel, G., Genovese, G., Handsaker, R. E., Hartl, C., Nemesh, J. C., Shakir, K., Yoon, S. C., Lihm, J., Makarov, V., Degenhardt, J., Flicek, P., Clarke, L., Smith, R. E., Zheng-Bradley, X., Korbel, J. O., Rausch, T., Stuetz, A. M., Bentley, D. R., Barnes, B., Cheetham, R. K., Eberle, M., Humphray, S., Kahn, S., Murray, L., Shaw, R., Ye, K., Batzer, M. A., Konkel, M. K., Walker, J. A., Lacroute, P., Craig, D. W., Homer, N., Church, D., Xiao, C., Sebat, J., Bafna, V., Michaelson, J. J., Ye, K., Devine, S. E., Liu, X., Maroo, A., Tallon, L. J., Lunter, G., McVean, G. A., Iqbal, Z., Witherspoon, D., Xing, J., Eichler, E. E., Alkan, C., Hajirasouliha, I., Hormozdiari, F., Ko, A., Sudmant, P. H., Chen, K., Chinwalla, A., Ding, L., McLellan, M. D., Wallis, J. W., Hurles, M. E., Ben Blackburne, Li, H., Lindsay, S. J., Ning, Z., Scally, A., Walter, K., Zhang, Y., Gerstein, M. B., Abyzov, A., Chen, J., Clarke, D., Khurana, E., Mu, X. J., Sisu, C., Gibbs, R. A., Yu, F., Bainbridge, M., Challis, D., Evani, U. S., Kovar, C., Lewis, L., Lu, J., Muzny, D., Nagaswamy, U., Reid, J., Sabo, A., Yu, J., Guo, X., Li, Y., Wu, R., Marth, G. T., Garrison, E. P., Leong, W. F., Ward, A. N., del Angel, G., DePristo, M. A., Gabriel, S. B., Gupta, N., Hartl, C., Poplin, R. E., Clark, A. G., Rodriguez-Flores, J. L., Flicek, P., Clarke, L., Smith, R. E., Zheng-Bradley, X., MacArthur, D. G., Bustamante, C. D., Gravel, S., Craig, D. W., Christoforides, A., Homer, N., Izatt, T., Sherry, S. T., Xiao, C., Dermitzakis, E. T., Abecasis, G. R., Kang, H. M., McVean, G. A., Mardis, E. R., Dooling, D., Fulton, L., Fulton, R., Koboldt, D. C., Durbin, R. M., Balasubramaniam, S., Keane, T. M., McCarthy, S., Stalker, J., Gerstein, M. B., Balasubramanian, S., Habegger, L., Garrison, E. P., Gibbs, R. A., Bainbridge, M., Muzny, D., Yu, F., Yu, J., del Angel, G., Handsaker, R. E., Makarov, V., Rodriguez-Flores, J. L., Jin, H., Kim, W., Kim, K. C., Flicek, P., Beal, K., Clarke, L., Cunningham, F., Herrero, J., McLaren, W. M., Ritchie, G. R., Zheng-Bradley, X., Tabrizi, S., MacArthur, D. G., Lek, M., Bustamante, C. D., De La Vega, F. M., Craig, D. W., Kurdoglu, A. A., Lappalainen, T., Rosenfeld, J. A., Michelson, L. P., Awadalla, P., Hodgkinson, A., McVean, G. A., Chen, K., Tyler-Smith, C., Chen, Y., Colonna, V., Frankish, A., Harrow, J., Xue, Y., Gerstein, M. B., Abyzov, A., Balasubramanian, S., Chen, J., Clarke, D., Fu, Y., Harmanci, A. O., Jin, M., Khurana, E., Mu, X. J., Sisu, C., Gibbs, R. A., Fowler, G., Hale, W., Kalra, D., Kovar, C., Muzny, D., Reid, J., Wang, J., Guo, X., Li, G., Li, Y., Zheng, X., Altshuler, D. M., Flicek, P., Clarke, L., Barker, J., Kelman, G., Kulesha, E., Leinonen, R., McLaren, W. M., Radhakrishnan, R., Roa, A., Smirnov, D., Smith, R. E., Streeter, I., Toneva, I., Vaughan, B., Zheng-Bradley, X., Bentley, D. R., Cox, T., Humphray, S., Kahn, S., Sudbrak, R., Albrecht, M. W., Lienhard, M., Craig, D. W., Izatt, T., Kurdoglu, A. A., Sherry, S. T., Ananiev, V., Belaia, Z., Beloslyudtsev, D., Bouk, N., Chen, C., Church, D., Cohen, R., Cook, C., Garner, J., Hefferon, T., Kimelman, M., Liu, C., Lopez, J., Meric, P., O'Sullivan, C., Ostapchuk, Y., Phan, L., Ponomarov, S., Schneider, V., Shekhtman, E., Sirotkin, K., Slotta, D., Xiao, C., Zhang, H., Haussler, D., Abecasis, G. R., McVean, G. A., Alkan, C., Ko, A., Dooling, D., Durbin, R. M., Balasubramaniam, S., Keane, T. M., McCarthy, S., Stalker, J., Chakravarti, A., Knoppers, B. M., Abecasis, G. R., Barnes, K. C., Beiswanger, C., Burchard, E. G., Bustamante, C. D., Cai, H., Cao, H., Durbin, R. M., Gharani, N., Gibbs, R. A., Gignoux, C. R., Gravel, S., Henn, B., Jones, D., Jorde, L., Kaye, J. S., Keinan, A., Kent, A., Kerasidou, A., Li, Y., Mathias, R., McVean, G. A., Moreno-Estrada, A., Ossorio, P. N., Parker, M., Reich, D., Rotimi, C. N., Royal, C. D., Sandoval, K., Su, Y., Sudbrak, R., Tian, Z., Timmermann, B., Tishkoff, S., Toji, L. H., Tyler-Smith, C., Via, M., Wang, Y., Yang, H., Yang, L., Zhu, J., Bodmer, W., Bedoya, G., Ruiz-Linares, A., Ming, C. Z., Yang, G., You, C. J., Peltonen, L., Garcia-Montero, A., Orfao, A., Dutil, J., Martinez-Cruzado, J. C., Oleksyk, T. K., Brooks, L. D., Felsenfeld, A. L., McEwen, J. E., Clemm, N. C., Duncanson, A., Dunn, M., Green, E. D., Guyer, M. S., Peterson, J. L., Abecasis, G. R., Auton, A., Brooks, L. D., DePristo, M. A., Durbin, R. M., Handsaker, R. E., Kang, H. M., Marth, G. T., McVean, G. A. 2012; 491 (7422): 56-65


    By characterizing the geographic and functional spectrum of human genetic variation, the 1000 Genomes Project aims to build a resource to help to understand the genetic contribution to disease. Here we describe the genomes of 1,092 individuals from 14 populations, constructed using a combination of low-coverage whole-genome and exome sequencing. By developing methods to integrate information across several algorithms and diverse data sources, we provide a validated haplotype map of 38?million single nucleotide polymorphisms, 1.4?million short insertions and deletions, and more than 14,000 larger deletions. We show that individuals from different populations carry different profiles of rare and common variants, and that low-frequency variants show substantial geographic differentiation, which is further increased by the action of purifying selection. We show that evolutionary conservation and coding consequence are key determinants of the strength of purifying selection, that rare-variant load varies substantially across biological pathways, and that each individual contains hundreds of rare non-coding variants at conserved sites, such as motif-disrupting changes in transcription-factor-binding sites. This resource, which captures up to 98% of accessible single nucleotide polymorphisms at a frequency of 1% in related populations, enables analysis of common and low-frequency variants in individuals from diverse, including admixed, populations.

    View details for DOI 10.1038/nature11632

    View details for Web of Science ID 000310434500030

    View details for PubMedID 23128226

  • Limited Evidence for Classic Selective Sweeps in African Populations GENETICS Granka, J. M., Henn, B. M., Gignoux, C. R., Kidd, J. M., Bustamante, C. D., Feldman, M. W. 2012; 192 (3): 1049-?


    While hundreds of loci have been identified as reflecting strong-positive selection in human populations, connections between candidate loci and specific selective pressures often remain obscure. This study investigates broader patterns of selection in African populations, which are underrepresented despite their potential to offer key insights into human adaptation. We scan for hard selective sweeps using several haplotype and allele-frequency statistics with a data set of nearly 500,000 genome-wide single-nucleotide polymorphisms in 12 highly diverged African populations that span a range of environments and subsistence strategies. We find that positive selection does not appear to be a strong determinant of allele-frequency differentiation among these African populations. Haplotype statistics do identify putatively selected regions that are shared across African populations. However, as assessed by extensive simulations, patterns of haplotype sharing between African populations follow neutral expectations and suggest that tails of the empirical distributions contain false-positive signals. After highlighting several genomic regions where positive selection can be inferred with higher confidence, we use a novel method to identify biological functions enriched among populations' empirical tail genomic windows, such as immune response in agricultural groups. In general, however, it seems that current methods for selection scans are poorly suited to populations that, like the African populations in this study, are affected by ascertainment bias and have low levels of linkage disequilibrium, possibly old selective sweeps, and potentially reduced phasing accuracy. Additionally, population history can confound the interpretation of selection statistics, suggesting that greater care is needed in attributing broad genetic patterns to human adaptation.

    View details for DOI 10.1534/genetics.112.144071

    View details for Web of Science ID 000310793900019

    View details for PubMedID 22960214

  • Admixture mapping identifies a locus on 6q25 associated with breast cancer risk in US Latinas HUMAN MOLECULAR GENETICS Fejerman, L., Chen, G. K., Eng, C., Huntsman, S., Hu, D., Williams, A., Pasaniuc, B., John, E. M., Via, M., Gignoux, C., Ingles, S., Monroe, K. R., Kolonel, L. N., Torres-Mejia, G., Perez-Stable, E. J., Burchard, E. G., Henderson, B. E., Haiman, C. A., Ziv, E. 2012; 21 (8): 1907-1917


    Among US Latinas and Mexican women, those with higher European ancestry have increased risk of breast cancer. We combined an admixture mapping and genome-wide association mapping approach to search for genomic regions that may explain this observation. Latina women with breast cancer (n= 1497) and Latina controls (n= 1272) were genotyped using Affymetrix and Illumina arrays. We inferred locus-specific genetic ancestry and compared the ancestry between cases and controls. We also performed single nucleotide polymorphism (SNP) association analyses in regions of interest. Correction for multiple-hypothesis testing was conducted using permutations (P(corrected)). We identified one region where genetic ancestry was significantly associated with breast cancer risk: 6q25 [odds ratio (OR) per Indigenous American chromosome 0.75, 95% confidence interval (CI): 0.65-0.85, P= 1.1 × 10(-5), P(corrected)= 0.02]. A second region on 11p15 showed a trend towards association (OR per Indigenous American chromosome 0.77, 95% CI: 0.68-0.87, P= 4.3 × 10(-5), P(corrected)= 0.08). In both regions, breast cancer risk decreased with higher Indigenous American ancestry in concordance with observations made on global ancestry. The peak of the 6q25 signal includes the estrogen receptor 1 (ESR1) gene and 5' region, a locus previously implicated in breast cancer. Genome-wide association analysis found that a multi-SNP model explained the admixture signal in both regions. Our results confirm that the association between genetic ancestry and breast cancer risk in US Latinas is partly due to genetic differences between populations of European and Indigenous Americans origin. Fine-mapping within the 6q25 and possibly the 11p15 loci will lead to the discovery of the biologically functional variant/s behind this association.

    View details for DOI 10.1093/hmg/ddr617

    View details for Web of Science ID 000302302400019

    View details for PubMedID 22228098

  • Development of a Panel of Genome-Wide Ancestry Informative Markers to Study Admixture Throughout the Americas PLOS GENETICS Galanter, J. M., Carlos Fernandez-Lopez, J., Gignoux, C. R., Barnholtz-Sloan, J., Fernandez-Rozadilla, C., Via, M., Hidalgo-Miranda, A., Contreras, A. V., Uribe Figueroa, L., Raska, P., Jimenez-Sanchez, G., Silva Zolezzi, I., Torres, M., Ruiz Ponte, C., Ruiz, Y., Salas, A., Nguyen, E., Eng, C., Borjas, L., Zabala, W., Barreto, G., Rondon Gonzalez, F., Ibarra, A., Taboada, P., Porras, L., Moreno, F., Bigham, A., Gutierrez, G., Brutsaert, T., Leon-Velarde, F., Moore, L. G., Vargas, E., Cruz, M., Escobedo, J., Rodriguez-Santana, J., Rodriguez-Cintron, W., Chapela, R., Ford, J. G., Bustamante, C., Seminara, D., Shriver, M., Ziv, E., Burchard, E. G., Haile, R., Parra, E., Carracedo, A. 2012; 8 (3)


    Most individuals throughout the Americas are admixed descendants of Native American, European, and African ancestors. Complex historical factors have resulted in varying proportions of ancestral contributions between individuals within and among ethnic groups. We developed a panel of 446 ancestry informative markers (AIMs) optimized to estimate ancestral proportions in individuals and populations throughout Latin America. We used genome-wide data from 953 individuals from diverse African, European, and Native American populations to select AIMs optimized for each of the three main continental populations that form the basis of modern Latin American populations. We selected markers on the basis of locus-specific branch length to be informative, well distributed throughout the genome, capable of being genotyped on widely available commercial platforms, and applicable throughout the Americas by minimizing within-continent heterogeneity. We then validated the panel in samples from four admixed populations by comparing ancestry estimates based on the AIMs panel to estimates based on genome-wide association study (GWAS) data. The panel provided balanced discriminatory power among the three ancestral populations and accurate estimates of individual ancestry proportions (R˛ > 0.9 for ancestral components with significant between-subject variance). Finally, we genotyped samples from 18 populations from Latin America using the AIMs panel and estimated variability in ancestry within and between these populations. This panel and its reference genotype information will be useful resources to explore population history of admixture in Latin America and to correct for the potential effects of population stratification in admixed samples in the region.

    View details for DOI 10.1371/journal.pgen.1002554

    View details for Web of Science ID 000302254800030

    View details for PubMedID 22412386

  • Rapid, global demographic expansions after the origins of agriculture PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA Gignoux, C. R., Henn, B. M., Mountain, J. L. 2011; 108 (15): 6044-6049


    The invention of agriculture is widely assumed to have driven recent human population growth. However, direct genetic evidence for population growth after independent agricultural origins has been elusive. We estimated population sizes through time from a set of globally distributed whole mitochondrial genomes, after separating lineages associated with agricultural populations from those associated with hunter-gatherers. The coalescent-based analysis revealed strong evidence for distinct demographic expansions in Europe, southeastern Asia, and sub-Saharan Africa within the past 10,000 y. Estimates of the timing of population growth based on genetic data correspond neatly to dates for the initial origins of agriculture derived from archaeological evidence. Comparisons of rates of population growth through time reveal that the invention of agriculture facilitated a fivefold increase in population growth relative to more ancient expansions of hunter-gatherers.

    View details for DOI 10.1073/pnas.0914274108

    View details for Web of Science ID 000289413600029

    View details for PubMedID 21444824

  • Hunter-gatherer genomic diversity suggests a southern African origin for modern humans PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA Henn, B. M., Gignoux, C. R., Jobin, M., Granka, J. M., Macpherson, J. M., Kidd, J. M., Rodriguez-Botigue, L., Ramachandran, S., Hon, L., Brisbin, A., Lin, A. A., Underhill, P. A., Comas, D., Kidd, K. K., Norman, P. J., Parham, P., Bustamante, C. D., Mountain, J. L., Feldman, M. W. 2011; 108 (13): 5154-5162


    Africa is inferred to be the continent of origin for all modern human populations, but the details of human prehistory and evolution in Africa remain largely obscure owing to the complex histories of hundreds of distinct populations. We present data for more than 580,000 SNPs for several hunter-gatherer populations: the Hadza and Sandawe of Tanzania, and the ?Khomani Bushmen of South Africa, including speakers of the nearly extinct N|u language. We find that African hunter-gatherer populations today remain highly differentiated, encompassing major components of variation that are not found in other African populations. Hunter-gatherer populations also tend to have the lowest levels of genome-wide linkage disequilibrium among 27 African populations. We analyzed geographic patterns of linkage disequilibrium and population differentiation, as measured by F(ST), in Africa. The observed patterns are consistent with an origin of modern humans in southern Africa rather than eastern Africa, as is generally assumed. Additionally, genetic variation in African hunter-gatherer populations has been significantly affected by interaction with farmers and herders over the past 5,000 y, through both severe population bottlenecks and sex-biased migration. However, African hunter-gatherer populations continue to maintain the highest levels of genetic diversity in the world.

    View details for DOI 10.1073/pnas.1017511108

    View details for Web of Science ID 000288894800009

    View details for PubMedID 21383195

  • Characterizing the Time Dependency of Human Mitochondrial DNA Mutation Rate Estimates MOLECULAR BIOLOGY AND EVOLUTION Henn, B. M., Gignoux, C. R., Feldman, M. W., Mountain, J. L. 2009; 26 (1): 217-230


    Previous research has established a discrepancy of nearly an order of magnitude between pedigree-based and phylogeny-based (human vs. chimpanzee) estimates of the mitochondrial DNA (mtDNA) control region mutation rate. We characterize the time dependency of the human mitochondrial hypervariable region one mutation rate by generating 14 new phylogeny-based mutation rate estimates using within-human comparisons and archaeological dates. Rate estimates based on population events between 15,000 and 50,000 years ago are at least 2-fold lower than pedigree-based estimates. These within-human estimates are also higher than estimates generated from phylogeny-based human-chimpanzee comparisons. Our new estimates establish a rapid decay in evolutionary mutation rate between approximately 2,500 and 50,000 years ago and a slow decay from 50,000 to 6 Ma. We then extend this analysis to the mtDNA-coding region. Our within-human coding region mutation rate estimates display a similar, though less rapid, time-dependent decay. We explore the possibility that multiple hits explain the discrepancy between pedigree-based and phylogeny-based mutation rates. We conclude that whereas nucleotide substitution models incorporating multiple hits do provide a possible explanation for the discrepancy between pedigree-based and human-chimpanzee mutation rate estimates, they do not explain the rapid decline of within-human rate estimates. We propose that demographic processes such as serial bottlenecks prior to the Holocene could explain the difference between rates estimated before and after 15,000 years ago. Our findings suggest that human mtDNA estimates of dates of population and phylogenetic events should be adjusted in light of this time dependency of the mutation rate estimates.

    View details for DOI 10.1093/molbev/msn244

    View details for Web of Science ID 000261681900021

    View details for PubMedID 18984905

  • Y-chromosomal evidence of a pastoralist migration through Tanzania to southern Africa PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA Henn, B. M., Gignoux, C., Lin, A. A., Oefner, P. J., Shen, P., Scozzari, R., Cruciani, F., Tishkoff, S. A., Mountain, J. L., Underhill, P. A. 2008; 105 (31): 10693-10698


    Although geneticists have extensively debated the mode by which agriculture diffused from the Near East to Europe, they have not directly examined similar agropastoral diffusions in Africa. It is unclear, for example, whether early instances of sheep, cows, pottery, and other traits of the pastoralist package were transmitted to southern Africa by demic or cultural diffusion. Here, we report a newly discovered Y-chromosome-specific polymorphism that defines haplogroup E3b1f-M293. This polymorphism reveals the monophyletic relationship of the majority of haplotypes of a previously paraphyletic clade, E3b1-M35*, that is widespread in Africa and southern Europe. To elucidate the history of the E3b1f haplogroup, we analyzed this haplogroup in 13 populations from southern and eastern Africa. The geographic distribution of the E3b1f haplogroup, in association with the microsatellite diversity estimates for populations, is consistent with an expansion through Tanzania to southern-central Africa. The data suggest this dispersal was independent of the migration of Bantu-speaking peoples along a similar route. Instead, the phylogeography and microsatellite diversity of the E3b1f lineage correlate with the arrival of the pastoralist economy in southern Africa. Our Y-chromosomal evidence supports a demic diffusion model of pastoralism from eastern to southern Africa approximately 2,000 years ago.

    View details for DOI 10.1073/pnas.0801184105

    View details for Web of Science ID 000258308500015

    View details for PubMedID 18678889

  • Male parentage in dependent-lineage populations of the harvester ant Pogonomyrmex barbatus MOLECULAR ECOLOGY Suni, S. S., Gignoux, C., Gordon, D. M. 2007; 16 (24): 5149-5155


    We investigated the extent to which workers reproduce in a dependent-lineage population of the monogynous harvester ant Pogonomyrmex barbatus. Dependent-lineage populations contain two interbreeding, yet genetically distinct mitochondrial lineages, each associated with specific alleles at nuclear loci. Workers develop from matings between lineages, and queens develop from matings within lineages, so queens must mate with males of both lineages to produce daughter queens and workers. Males develop from unfertilized eggs and are haploid. Worker production of males could lead to male-mediated gene flow between the lineages if worker-produced males were reproductively capable. This could result in the loss of the dependent-lineage system, because its persistence depends on the maintenance of allelic differences between the lineages. To investigate the extent of worker reproduction in P. barbatus, we genotyped 19-20 males and workers from seven colonies, at seven microsatellite loci, and 1239 additional males at two microsatellite loci. Our methods were powerful enough to detect worker reproduction if workers produced more than 0.39% of males in the population. We detected no worker-produced males; all males appeared to be produced by queens. Thus, worker reproduction is sufficiently infrequent to have little impact on the dependent-lineage system. These results are consistent with predictions based on inclusive fitness theory because the effective queen mating frequency calculated from worker genotypes was 4.26, which is sufficiently high for workers to police those that attempt to reproduce.

    View details for DOI 10.1111/j.1365-294X.2007.03492.x

    View details for Web of Science ID 000251671700005

    View details for PubMedID 18092991

  • History of click-speaking Populations of Africa inferred from mtDNA and Y chromosome genetic variation MOLECULAR BIOLOGY AND EVOLUTION Tishkoff, S. A., Gonder, M. K., Henn, B. M., Mortensen, H., Knight, A., Gignoux, C., Fernandopulle, N., Lema, G., Nyambo, T. B., Ramakrishnan, U., Reed, F. A., Mountain, J. L. 2007; 24 (10): 2180-2195


    Little is known about the history of click-speaking populations in Africa. Prior genetic studies revealed that the click-speaking Hadza of eastern Africa are as distantly related to click speakers of southern Africa as are most other African populations. The Sandawe, who currently live within 150 km of the Hadza, are the only other population in eastern Africa whose language has been classified as part of the Khoisan language family. Linguists disagree on whether there is any detectable relationship between the Hadza and Sandawe click languages. We characterized both mtDNA and Y chromosome variation of the Sandawe, Hadza, and neighboring Tanzanian populations. New genetic data show that the Sandawe and southern African click speakers share rare mtDNA and Y chromosome haplogroups; however, common ancestry of the 2 populations dates back >35,000 years. These data also indicate that common ancestry of the Hadza and Sandawe populations dates back >15,000 years. These findings suggest that at the time of the spread of agriculture and pastoralism, the click-speaking populations were already isolated from one another and are consistent with relatively deep linguistic divergence among the respective click languages.

    View details for DOI 10.1093/molbev/msm155

    View details for Web of Science ID 000250437000004

    View details for PubMedID 17656633

  • SNPSTRs: Empirically derived, rapidly typed, autosomal Haplotypes for inference of population history and mutational processes GENOME RESEARCH Mountain, J. L., Knight, A., Jobin, M., Gignoux, C., Miller, A., Lin, A. A., Underhill, P. A. 2002; 12 (11): 1766-1772


    Each independently evolving segment of the genomes of a sexually reproducing organism has a separate history reflecting part of the evolutionary history of that organism. Uniparentally or clonally inherited DNA segments such as the mitochondrial and chloroplast genomes and the nonrecombining portion of the Y chromosome have provided, to date, most of the known data regarding compound haplotypic variation within and among populations. These comparatively small segments include numerous polymorphic sites and undergo little or no recombination. Recombining autosomes, however, comprise the major repository of genetic variation. Technical challenges and recombination have limited large-scale application of autosomal haplotypes. We have overcome this barrier through development of a general approach to the assessment of short autosomal DNA segments. Each such segment includes one or more single nucleotide polymorphisms (SNPs) and exactly one short tandem repeat (STR) locus. With dramatically different mutation rates, these two types of genetic markers provide complementary evolutionary information. We call the combination of a SNP and a STR polymorphism a SNPSTR, and have developed a simple, rapid method for empirically determining gametic phase for double and triple heterozygotes. Here, we illustrate the approach with two SNPSTR systems. Although even one system provides insight into population history, the power of the approach lies in combining results from multiple SNPSTR systems.

    View details for DOI 10.1101/gr.238602

    View details for Web of Science ID 000179058300016

    View details for PubMedID 12421764

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