Who We Are and How We Got Here

by David Reich

  20. David W. Anthony, The Horse, the Wheel, and Language: How Bronze-Age Riders from the Eurasian Steppes Shaped the Modern World (Princeton, NJ: Princeton University Press, 2007).

  21. W. Haak et al., “Massive Migration from the Steppe Was a Source for Indo-European Languages in Europe,” Nature 522 (2015): 207–11; M. E. Allentoft et al., “Population Genomics of Bronze Age Eurasia,” Nature 522 (2015): 167–72.

  22. E. Murphy and A. Khokhlov, “A Bioarchaeological Study of Prehistoric Populations from the Volga Region,” in A Bronze Age Landscape in the Russian Steppes: The Samara Valley Project, Monumenta Archaeologica 37, ed. David W. Anthony, Dorcas R. Brown, Aleksandr A. Khokhlov, Pavel V. Kuznetsov, and Oleg D. Mochalov (Los Angeles: Cotsen Institute of Archaeology Press, 2016), 149–216.

  23. Marija Gimbutas, The Prehistory of Eastern Europe, Part I: Mesolithic, Neolithic and Copper Age Cultures in Russia and the Baltic Area (American School of Prehistoric Research, Harvard University, Bulletin No. 20) (Cambridge, MA: Peabody Museum, 1956).

  24. Haak et al., “Massive Migration.”

  25. R. S. Wells et al., “The Eurasian Heartland: A Continental Perspective on Y-Chromosome Diversity,” Proceedings of the National Academy of Sciences of the U.S.A. 98 (2001): 10244–49.

  26. R. Martiniano et al., “The Population Genomics of Archaeological Transition in West Iberia: Investigation of Ancient Substructure Using Imputation and Haplotype-Based Methods,” PLoS Genetics 13 (2017): e1006852.

  27. M. Silva et al., “A Genetic Chronology for the Indian Subcontinent Points to Heavily Sex-Biased Dispersals,” BMC Evolutionary Biology 17 (2017): 88.

  28. Martiniano et al., “West Iberia”; unpublished results from David Reich’s laboratory.

  29. J. A. Tennessen et al., “Evolution and Functional Impact of Rare Coding Variation from Deep Sequencing of Human Exomes,” Science 337 (2012): 64–69.

  30. A. Keinan, J. C. Mullikin, N. Patterson, and D. Reich, “Accelerated Genetic Drift on Chromosome X During the Human Dispersal out of Africa,” Nature Genetics 41 (2009): 66–70; A. Keinan and D. Reich, “Can a Sex-Biased Human Demography Account for the Reduced Effective Population Size of Chromosome X in Non-Africans?,” Molecular Biology and Evolution 27 (2010): 2312–21.

  31. P. Verdu et al., “Sociocultural Behavior, Sex-Biased Admixture, and Effective Population Sizes in Central African Pygmies and Non-Pygmies,” Molecular Biology and Evolution 30 (2013): 918–37.

  32. S. Mallick et al., “The Simons Genome Diversity Project: 300 Genomes from 142 Diverse Populations,” Nature 538 (2016): 201–6.

  33. L. G. Carvajal -Carmona et al., “Strong Amerind/White Sex Bias and a Possible Sephardic Contribution Among the Founders of a Population in Northwest Colombia,” American Journal of Human Genetics 67 (2000): 1287–95.

  34. Bedoya et al., “Admixture Dynamics in Hispanics: A Shift in the Nuclear Genetic Ancestry of a South American Population Isolate,” Proceedings of the National Academy of Sciences of the U.S.A. 103 (2006): 7234–39.

  35. P. Moorjani et al., “Genetic Evidence for Recent Population Mixture in India,” American Journal of Human Genetics 93 (2013): 422–38.

  36. M. Bamshad et al., “Genetic Evidence on the Origins of Indian Caste Populations,” Genome Research 11 (2001): 994–1004; D. Reich et al., “Reconstructing Indian Population History,” Nature 461 (2009): 489–94.

  37. Bamshad et al., “Genetic Evidence”; I. Thanseem et al., “Genetic Affinities Among the Lower Castes and Tribal Groups of India: Inference from Y Chromosome and Mitochondrial DNA,” BMC Genetics 7 (2006): 42.

  38. M. Kayser, “The Human Genetic History of Oceania: Near and Remote Views of Dispersal,” Current Biology 20 (2010): R194–201; P. Skoglund et al., “Genomic Insights into the Peopling of the Southwest Pacific,” Nature 538 (2016): 510–13.

  39. F. M. Jordan, R. D. Gray, S. J. Greenhill, and R. Mace, “Matrilocal Residence Is Ancestral in Austronesian Societies,” Proceedings of the Royal Society B—Biological Sciences 276 (2009): 1957–64.

  40. Skoglund et al., “Genomic Insights.”

  41. I. Lazaridis and D. Reich, “Failure to Replicate a Genetic Signal for Sex Bias in the Steppe Migration into Central Europe,” Proceedings of the National Academy of Sciences of the U.S.A. 114 (2017): E3873–74.

  11 The Genomics of Race and Identity

  1. Centers for Disease Control and Prevention, “Prostate Cancer Rates by Race and Ethnicity,” https://www.cdc.gov/​cancer/​prostate/​statistics/​race.htm.

  2. N. Patterson et al., “Methods for High-Density Admixture Mapping of Disease Genes,” American Journal of Human Genetics 74 (2004): 979–1000; M. W. Smith et al., “A High-Density Admixture Map for Disease Gene Discovery in African Americans,” American Journal of Human Genetics 74 (2004): 1001–13.

  3. M. L. Freedman et al., “Admixture Mapping Identifies 8q24 as a Prostate Cancer Risk Locus in African-American Men,” Proceedings of the National Academy of Sciences of the U.S.A. 103 (2006): 14068–73.

  4. C. A. Haiman et al., “Multiple Regions within 8q24 Independently Affect Risk for Prostate Cancer,” Nature Genetics 39 (2007): 638–44.

  5. Freedman et al., “Admixture Mapping Identifies 8q24.”

  6. M. F. Ashley Montagu, Man’s Most Dangerous Myth: The Fallacy of Race (New York: Columbia University Press, 1942).

  7. R. C. Lewontin, “The Apportionment of Human Diversity,” Evolutionary Biology 6 (1972): 381–98.

  8. J. M. Stevens, “The Feasibility of Government Oversight for NIH-Funded Population Genetics Research,” in Revisiting Race in a Genomic Age (Studies in Medical Anthropology), ed. Barbara A. Koenig, Sandra Soo-Jin Lee, and Sarah S. Richardson (New Brunswick, NJ: Rutgers University Press, 2008), 320–41; J. Stevens, “Racial Meanings and Scientific Methods: Policy Changes for NIH-Sponsored Publications Reporting Human Variation,” Journal of Health Policy, Politics and Law 28 (2003): 1033–87.

  9. N. A. Rosenberg et al., “Genetic Structure of Human Populations,” Science 298 (2002): 2381–85.

  10. D. Serre and S. Pääbo, “Evidence for Gradients of Human Genetic Diversity Within and Among Continents,” Genome Research 14 (2004): 1679–85; F. B. Livingstone, “On the Non-Existence of Human Races,” Current Anthropology 3 (1962): 279.

  11. J. Dreyfuss, “Getting Closer to Our African Origins,” The Root, October 17, 2011, www.theroot.com/​getting-closer-to-our-african-origins-1790866394.

  12. N. A. Rosenberg et al., “Clines, Clusters, and the Effect of Study Design on the Inference of Human Population Structure,” PLoS Genetics 1 (2005): e70.

  13. E. G. Burchard et al., “The Importance of Race and Ethnic Background in Biomedical Research and Clinical Practice,” New England Journal of Medicine 348 (2003): 1170–75.

  14. J. F. Wilson et al., “Population Genetic Structure of Variable Drug Response,” Nature Genetics 29 (2001): 265–69.

  15. D. Fullwiley, “The Biologistical Construction of Race: ‘Admixture’ Technology and the New Genetic Medicine,” Social Studies of Science 38 (2008): 695–735.

  16. Lewontin, “The Apportionment of Human Diversity”; A. R. Templeton, “Biological Races in Humans,” Studies in History and Philosophy of Biological and Biomedical Science 44 (2013): 262–71.

  17. Razib Khan, www.razib.com/​wordpress.

  18. Dienekes’ Anthropology Blog, dienekes.blogspot.com.

  19. Eurogenes Blog, http://eurogenes.blogspot.com.

  20. Léon Poliakov, The Aryan Myth: A History of Racist and Nationalist Ideas in Europe (New York: Basic Books, 1974).

  21. B. Arnold, “The Past as Propaganda: Totalitarian Archaeology in Nazi Germany,” Antiquity 64 (1990): 464–78.

  22. J. K. Pritchard, J. K. Pickrell, and G. Coop, “The Genetics of Human Adaptation: Hard Sweeps, Soft Sweeps, and Polygenic Adaptation,” Current Biology 20 (2010): R208–15; R. D. Hernandez et al., “Classic Selective Sweeps Were Rare in Recent Human Evolution,” Science 331 (2011): 920–24.

  23. M. C. Turchin
et al., “Evidence of Widespread Selection on Standing Variation in Europe at Height-Associated SNPs,” Nature Genetics 44 (2012): 1015–19.

  24. Y. Field et al., “Detection of Human Adaptation During the Past 2000 Years,” Science 354 (2016): 760–64.

  25. A. Okbay et al., “Genome-Wide Association Study Identifies 74 Loci Associated with Educational Attainment,” Nature 533 (2016): 539–42.

  26. To compute the expected difference in number of years of education between the highest 5 percent and lowest 5 percent of genetically predicted educational attainment based on the numbers in the 2016 study by Benjamin and colleagues, I performed the following computation: (1) The number of years of education in the cohort analyzed by Benjamin and colleagues is quoted as 14.3 ± 3.7. I estimated the standard deviation of 3.7 years from the fact that the study estimates the effect size in weeks to be “0.014 to 0.048 standard deviations per allele (2.7 to 9.0 weeks of schooling).” These numbers translate to 188 ( = 9.0 / 0.048) to 193 ( = 2.7 / 0.014) weeks. Dividing by 52 weeks per year gives 3.7. (2) Benjamin and colleagues also report a genetic predictor of number of years of education that explains 3.2 percent of the variance of the trait. Therefore, the correlation between the predicted value and the actual value is √0.032 = 0.18. We can model this mathematically using a two-dimensional normal distribution. (3) The probability that a person who is in the bottom 5% of the predicted distribution (more than 1.64 standard deviations below the average) has more than 12 years of education is then given by the proportion of people who are in the bottom 5 percent of the predicted distribution and also have more than 12 years of education (which can be calculated by measuring the area of the two-dimensional normal distribution that matches these criteria), divided by 0.05. This gives a probability of 60 percent. A similar calculation for the proportion of people in the top 5 percent of the predicted distribution gives a probability of 84 percent. (4) The Benjamin study also suggests that with enough samples it would be possible to build a reliable genetic predictor that accounts for 20 percent of the variance. Redoing the calculation using 20 percent instead of 3.2 percent leads to a prediction that 37 percent of people in the bottom 5 percent of the predicted distribution would complete twelve years of education compared to 96 percent of the top 5 percent.

  27. A. Kong et al., “Selection Against Variants in the Genome Associated with Educational Attainment,” Proceedings of the National Academy of Sciences of the U.S.A. 114 (2017): E727–32.

  28. Kong et al., “Selection Against Variants,” estimate that the genetically predicted number of years of education has decreased by an estimated 0.1 standard deviations over the last century under the pressure of natural selection.

  29. G. Davies et al., “Genome-Wide Association Study of Cognitive Functions and Educational Attainment in UK Biobank (N=112 151),” Molecular Psychiatry 21 (2016): 758–67; M. T. Lo et al., “Genome-Wide Analyses for Personality Traits Identify Six Genomic Loci and Show Correlations with Psychiatric Disorders,” Nature Genetics 49 (2017): 152–56.

  30. S. Sniekers et al., “Genome-Wide Association Meta-Analysis of 78,308 Individuals Identifies New Loci and Genes Influencing Human Intelligence,” Nature Genetics 49 (2017): 1107–12.

  31. I. Mathieson et al., “Genome-wide Patterns of Selection in 230 Ancient Eurasians,” Nature 528 (2015): 499–503; Field et al., “Detection of Human Adaptation.”

  32. N. A. Rosenberg et al., “Genetic Structure of Human Populations,” Science 298 (2002): 2381–85.

  33. S. Ramachandran et al., “Support from the Relationship of Genetic and Geographic Distance in Human Populations for a Serial Founder Effect Originating in Africa,” Proceedings of the National Academy of Sciences of the U.S.A. 102 (2005): 15942–47; B. M. Henn, L. L. Cavalli-Sforza, and M. W. Feldman, “The Great Human Expansion,” Proceedings of the National Academy of Sciences of the U.S.A. 109 (2012): 17758–64.

  34. J. K. Pickrell and D. Reich, “Toward a New History and Geography of Human Genes Informed by Ancient DNA,” Trends in Genetics 30 (2014): 377–89.

  35. M. Raghavan et al., “Upper Palaeolithic Siberian Genome Reveals Dual Ancestry of Native Americans,” Nature (2013): doi: 10.1038/nature 12736.

  36. I. Lazaridis et al., “Genomic Insights into the Origin of Farming in the Ancient Near East,” Nature 536 (2016): 419–24.

  37. Nicholas Wade, A Troublesome Inheritance: Genes, Race and Human History (New York: Penguin Press, 2014).

  38. G. Coop et al., “A Troublesome Inheritance” (letters to the editor), New York Times, August 8, 2014.

  39. G. Cochran, J. Hardy, and H. Harpending, “Natural History of Ashkenazi Intelligence,” Journal of Biosocial Science 38 (2006): 659–93.

  40. P. F. Palamara, T. Lencz, A. Darvasi, and I. Pe’er, “Length Distributions of Identity by Descent Reveal Fine-Scale Demographic History,” American Journal of Human Genetics 91 (2012): 809–22; M. Slatkin, “A Population-Genetic Test of Founder Effects and Implications for Ashkenazi Jewish Diseases,” American Journal of Human Genetics 75 (2004): 282–93.

  41. H. Harpending, “The Biology of Families and the Future of Civilization” (minute 38), Preserving Western Civilization, 2009 Conference, audio available at www.prese​rving​weste​rnciv.com/​audio/​07%20Prof._Henry_Harpending--The_Biology_of_Families_and_the_Future_of_Civilization.mp3 (2009).

  42. G. Clark, “Genetically Capitalist? The Malthusian Era, Institutions and the Formation of Modern Preferences” (2007), www.econ.ucdavis.edu/​faculty/​gclark/​papers/​Capitalism%20Genes.pdf; Gregory Clark, A Farewell to Alms: A Brief Economic History of the World (Princeton, NJ: Princeton University Press, 2007).

  43. Wade, A Troublesome Inheritance.

  44. C. Hunt-Grubbe, “The Elementary DNA of Dr. Watson,” The Sunday Times, October 14, 2017.

  45. Coop et al. letters, New York Times.

  46. David Epstein, The Sports Gene: Inside the Science of Extraordinary Athletic Performance (New York: Current, 2013).

  47. Ibid.

  48. I performed this computation as follows. (1) The 99.9999999th percentile of a trait corresponds to 6.0 standard deviations from the mean, whereas the 99.99999th percentile corresponds to 5.2 standard deviations. Thus a 0.8-standard-deviation shift corresponds to a hundredfold enrichment of individuals. (2) I assumed that the 1.33-fold higher genetic variation in sub-Saharan Africans applies not just to random mutations in the genome, but also to mutations modulating biological traits. The standard deviation is thus expected to be 1.15 = √1.33-fold higher in sub-Saharan Africans based on a formula in J. J. Berg and G. Coop, “A Population Genetic Signal of Polygenic Adaptation,” PLoS Genetics 10 (2014): e1004412, so the 6.0-standard-deviation cutoff in non-Africans corresponds to 5.2 = 6.0 / 1.15 of that in sub-Saharan Africans, leading to the same predicted hundredfold enrichment above the 99.9999999th percentile.

  49. W. Haak et al., “Massive Migration from the Steppe Was a Source for Indo-European Languages in Europe,” Nature 522 (2015): 207–11; M. E. Allentoft et al., “Population Genomics of Bronze Age Eurasia,” Nature 522 (2015): 167–72.

  50. D. Reich et al., “Reconstructing Indian Population History,” Nature 461 (2009): 489–94; Lazaridis et al., “Genomic Insights.”

  51. Michael F. Robinson, The Lost White Tribe: Explorers, Scientists, and the Theory That Changed a Continent (New York: Oxford University Press, 2016).

  52. Alex Haley, Roots: The Saga of an American Family (New York: Doubleday, 1976).

  53. “Episode 4: (2010) Know Thyself” (minute 17) in Faces of America with Henry Louis Gates Jr., http://www.pbs.org/​wnet/​facesofamerica/​video/​episode-4-know-thyself/​237/.

  54. African Ancestry, “Frequently Asked Questions,” “About the Results,” question 3 (2016), http://www.africanancestry.com/​faq/.

  55. Dreyfuss, “Getting Closer to Our African Origins.”

  56. S. Sailer, “African Ancestry Inc. Traces DNA Roots,” United Press International, April 28, 2003, www.upi.com/​inc/​view.php?Sto
ryID=20030428-074922-7714r.

  57. Unpublished results from David Reich’s laboratory.

  58. H. Schroeder et al., “Genome-Wide Ancestry of 17th-Century Enslaved Africans from the Caribbean,” Proceedings of the National Academy of Sciences of the U.S.A. 112 (2015): 3669–73.

  59. R. E. Green et al., “A Draft Sequence of the Neanderthal Genome,” Science 328 (2010): 710–22.

  60. E. Durand, 23andMe: “White Paper 23-05: Neanderthal Ancestry Estimator” (2011), https://web.stanford.edu/​class/​gene210/​files/​readings/​23andme_Neanderthal_Ancestry.pdf; S. Sankararaman et al., “The Genomic Landscape of Neanderthal Ancestry in Present-Day Humans,” Nature 507 (2014): 354–57.

  61. Sankararaman et al., “Genomic Landscape.”

  62. https://customercare.23andme.com/​hc/​en-us/​articles/​212873707-Neanderthal-Report-Basics, #13514.

  12 The Future of Ancient DNA

  1. J. R. Arnold and W. F. Libby, “Age Determinations by Radiocarbon Content—Checks with Samples of Known Age,” Science 110 (1949): 678–80.

  2. Colin Renfrew, Before Civilization: The Radiocarbon Revolution and Prehistoric Europe (London: Jonathan Cape, 1973).

  3. Lewis R. Binford, In Pursuit of the Past: Decoding the Archaeological Record (Berkeley: University of California Press, 1983).

  4. M. Rasmussen et al., “Ancient Human Genome Sequence of an Extinct Palaeo-Eskimo,” Nature 463 (2010): 757–62; M. Rasmussen et al., “The Genome of a Late Pleistocene Human from a Clovis Burial Site in Western Montana,” Nature 506 (2014): 225–29; M. Raghavan et al., “Upper Palaeolithic Siberian Genome Reveals Dual Ancestry of Native Americans,” Nature (2013): doi: 10.1038/nature 12736.

  5. P. Skoglund et al., “Genomic Insights into the Peopling of the Southwest Pacific,” Nature 538 (2016): 510–13.

  6. J. Dabney et al., “Complete Mitochondrial Genome Sequence of a Middle Pleistocene Cave Bear Reconstructed from Ultrashort DNA Fragments,” Proceedings of the National Academy of Sciences of the U.S.A. 110 (2013): 15758–63; M. Meyer et al., “A High-Coverage Genome Sequence from an Archaic Denisovan Individual,” Science 338 (2012): 222–26; Q. Fu et al., “DNA Analysis of an Early Modern Human from Tianyuan Cave, China,” Proceedings of the National Academy of Sciences of the U.S.A. 110 (2013): 2223–27; R. Pinhasi et al., “Optimal Ancient DNA Yields from the Inner Ear Part of the Human Petrous Bone,” PLoS One 10 (2015): e0129102.