Prisoners of Abstraction? The Theory and Measure of Genetic Variation, and the Very Concept of “Race”

Abstract

It is illegitimate to read any ontology about “race” off of biological theory or data. Indeed, the technical meaning of “genetic variation” is fluid, and there is no single theoretical agreed-upon criterion for defining and distinguishing populations given a particular set of genetic variation data. By analyzing three formal senses of “genetic variation,” viz., diversity, differentiation, and heterozygosity, we argue that the use of biological theory for making claims about race inevitably amounts to a pernicious reification. Biological theory does not force the concept of “race” upon us; our social discourse, social ontology, and social expectations do. We become prisoners of our abstractions at our own hands, and at our own expense.

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Fig. 1

Notes

  1. 1.

    This position may seem initially implausible (consider the facts about the relationship between socially identified race and, e.g., health outcomes, noted below), but Mills notes that a certain kind of Marxist, committed to the view that class is explanatory of all important differences in life prospects, might deny the existence of race as a category with any real impact, collapsing the life-prospect issues that follow race into those that follow class (Mills 1988, p. 49).

  2. 2.

    Lewontin (1972) does not explicitly deny the existence of population structure in humans—indeed, we are unaware of any biologist who has done so. But his statistical results and criticism of the “race” concept as socially destructive and as (nearly) biologically useless are often interpreted this way, and it is this interpretation that Edwards seems to have in mind. See Kaplan (2011) for discussion.

  3. 3.

    Contemporary humans vary, on average, by about 1:1,000 nucleotides; this is around an order of magnitude less variation than occurs in many other species (see, e.g., Li and Sadler 1991; Cognato 2007). All the measures of genetic variation discussed below rely on this small amount of variation when applied to humans. This variation is not distributed equally in humans; people whose ancestors are of recent African origin, for example, differ on average by about 1:900 nucleotides; people whose ancestors were of recent European origin differ by only about 1:1,600 nucleotides. Edwards is correct when he notes that “It is not true, as Nature claimed, that ‘two random individuals from any one group are almost as different as any two random individuals from the entire world’” (2003, p. 801) but not perhaps in the way he intended; interestingly, the “average” person of recent African descent is more likely to share an arbitrary allele with an “average” person of recent European descent (will differ less) than he or she is with another arbitrarily chosen person of African descent (African v. European difference is about 1:1050, compared with 1:900 difference within Africa) (see Yu et al. 2002).

  4. 4.

    Even in the professional literature, there is substantial confusion surrounding these concepts and associated measures. Consider the following, from a “Correction” published by Kronholm et al. (2010b): “In the introduction of Kronholm et al. (2010a), we discuss what properties a differentiation measure, like FST, should or was assumed to have. Recent developments have shown that FST in fact does not have these properties.” The authors cite and thank Jost, who we also believe has helped identify and publicize some of the conceptual difficulties and problematic assumptions associated with these measures.

  5. 5.

    Ecological genetics has been more explicit about these distinctions (n.b., Lou Jost is an ecological geneticist), perhaps because it has to be clear about whether token numbers or token frequencies, within or across types, for genes or for species, are being measured. For example, a textbook in the field dedicates a whole chapter to “Genetic diversity and differentiation” (Lowe et al. 2004, Ch. 3). Some of the distinctions drawn are broadly similar to those we prefer, e.g., they note that “Genetic diversity measures estimate the amount of variation that is found in a population, while genetic differentiation measures describe how this variation is partitioned among populations.” However, we suggest a narrower definition of differentiation than the one Lowe et al. actually employ, and believe it is important to more carefully distinguish measures of heterozygosity from other measures of variation.

  6. 6.

    This point is made forcefully by Jost (2008).

  7. 7.

    This kind of example is used by Jost (2008) and others to show why measures like G ST should not be interpreted as measures of diversity. The equations for calculating the Shannon Entropy measure and G ST are below, and it is a worthwhile exercise to compute the heterozygosity partitions for a variety of circumstances in order to get a sense of how the measures in fact behave. Note that for loci with relatively low overall diversity—which were the kind that Lewontin’s 1972 analysis in fact focused on—measures like the Shannon Entropy measure and G ST do not usually produce such misleading results, and so this should not be taken to imply that the estimates of within- and between-population diversity (in the sense we describe below) in humans are necessarily very different than that implied by Lewontin’s analysis. Nevertheless, the analysis used is inappropriate if one is trying to measure diversity.

  8. 8.

    While Jost’s D has several features that make it a convenient example of a diversity measure, our use of it as an example should not be taken as an endorsement of it as the only or the best measure and associated partition. For discussion, see e.g., Hoffmann and Hofmann 2008, Gabriele et al. 2010, Whitlock 2011, and cites therein.

  9. 9.

    Nei’s standard distance, for example, assumes that populations diverge because of genetic mutations and drift, whereas Reynold’s distance assumes only drift and purposefully excludes mutation. See Libiger et al. (2009).

  10. 10.

    The SMEO-P model—i.e., “set-up, mathematically manipulate, explain, objectify—pluralize”—developed in Winther (2006) is useful here.

  11. 11.

    These debates surrounding the ontology of socially identified races take place against a background where basic life prospects (income, life expectancy, morbidity, standards of living, and quality of life more generally) are strongly correlated with socially identified race. The question: “What accounts for these differences?” lurks behind these debates, but the implications of that question are not always obvious, nor is it obvious what the answers to that question the various positions in the debate suggest. But at least some of the dangers in biological explorations of human population structure that, e.g., Kitcher (2007) points towards, and that Kaplan (2010) highlights, are wrapped up in these issues.

  12. 12.

    We ignore here the complexities of developmental biology and non-genetic heritable resources.

  13. 13.

    In various forms, this position, or one very much like it, has been defended by Appiah and Gutmann (1996), Hacking (2005), Haslanger (2010), Omi and Winant (1989), and others.

References

  1. Andreasen RO (2000) Race: biological reality or social construct? Phil Sci 67:S653–S666

    Article  Google Scholar 

  2. Andreasen RO (2004) The cladistic race concept: a defense. Biol Philos 19:425–442

    Article  Google Scholar 

  3. Appiah KA, Gutmann A (1996) Color conscious: the political morality of race. Princeton University Press. Princeton, NJ

  4. Cavalli-Sforza LL, Edwards AWF (1967) Phylogenetic analysis: models and estimation procedures. Am J Hum Genet 19:233–257

    Google Scholar 

  5. Cognato AI (2007) A standard DNA taxonomy for insects? USDA Forest Service Proceedings RMRS-P-45, pp 11–12

  6. Edwards AWF (2003) Human genetic diversity: Lewontin’s fallacy. BioEssays 25:798–801

    Article  Google Scholar 

  7. Giuliano P, Spilimbergo A,Tonon G (2007) Genetic, cultural and geographical distances. IZA Discussion Paper No. 2229. http://www.economics.harvard.edu/files/faculty/97_Genetics_August2007.pdf. Accessed 3 Nov 2011

  8. Hacking I (2005) Why race still matters. Dædalus 134(1):102–116

    Google Scholar 

  9. Haslanger S (2010) Language, politics, and “the folk”: looking for “the meaning” of “race”. Monist 93:169–187

    Article  Google Scholar 

  10. Hoffmann S, Hoffmann A (2008) Is there a “true” diversity? Ecol Econ 65:213–215

    Article  Google Scholar 

  11. Jost L (2008) GST and its relatives do not measure differentiation. Mol Ecol 17:4015–4026

    Article  Google Scholar 

  12. Kalinowski ST (2011) The computer program STRUCTURE does not reliably identify the main genetic clusters within species: simulations and implications for human population structure. Heredity 106:625–632

    Article  Google Scholar 

  13. Kaplan JM (2010) When socially determined categories make biological realities: understanding Black/White health disparities in the U.S. Monist 93:281–297

    Article  Google Scholar 

  14. Kaplan JM (2011) “Race”: what biology can tell us about a social construct. In: Encyclopedia of life sciences. Wiley, Chichester. doi:10.1002/9780470015902.a0005857

  15. Kitcher P (2007) Does “race” have a future? Philos Public Aff 35:293–317

    Article  Google Scholar 

  16. Kronholm I, Loudet O, de Meaux J (2010a) Influence of mutation rate on estimators of genetic differentiation-lessons from Arabidopsis thaliana. BMC Genet 11:33

    Article  Google Scholar 

  17. Kronholm I, Loudet O, de Meaux J (2010b) Correction: influence of mutation rate on estimators of genetic differentiation: lessons from Arabidopsis thaliana. BMC Genet 11:88

    Article  Google Scholar 

  18. Levins R, Lewontin RC (1980) Dialectics and reductionism in ecology. Synthese 43:47–78

    Article  Google Scholar 

  19. Lewontin RC (1972) The apportionment of human diversity. Evol Biol 6:381–398

    Article  Google Scholar 

  20. Lewontin RC, Rose S, Kamin LJ (1984) Not in our genes: biology, ideology, and human nature. Pantheon Books. New York

  21. Li W-H, Sadler LA (1991) Low nucleotide diversity in man. Genetics 129:513–523

    Google Scholar 

  22. Libiger O, Nievergelt CM, Schork NJ (2009) Comparison of genetic distance measures using human SNP genotype data. Hum Biol 81:389–406

    Article  Google Scholar 

  23. Livingstone FB, Dobzhansky T (1962) On the non-existence of human races. Curr Anthropol 3:279–281

    Article  Google Scholar 

  24. Lowe A, Harris S, Ashton P (2004) Ecological genetics. Design, analysis, and application. Blackwell, Oxford

    Google Scholar 

  25. McDonald D (2008) Distances summary. http://www.uwyo.edu/dbmcd/molmark/GenDistEqns.pdf. Accessed 3 November 2011

  26. Mills CW (1988) “But What Are You Really? The Metaphysics of Race.” Blackness visible: essays on philosophy and race. Cornell University Press, Ithaca, NY, pp 41–66

  27. Novembre J, Johnson T, Bryc K, Kutalik Z, Boyko AR, Auton A, Indap A, King KS, Bergmann S, Nelson MR, Stephens M, Bustamante CD (2008) Genes mirror geography within Europe. Nature 456:98–101

    Article  Google Scholar 

  28. Omi M, Winant H (1989) Racial formation in the United States: from the 1960s to the 1980s. Routledge, New York

    Google Scholar 

  29. Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959

    Google Scholar 

  30. Provine WB (1986) Sewall Wright and evolutionary biology. University of Chicago Press, Chicago

    Google Scholar 

  31. Rosenberg NA, Pritchard JK, Weber JL, Cann HM, Kidd KK, Zhivotovsky LA, Feldman MW (2002) Genetic structure of human populations. Science 298:2381–2385

    Article  Google Scholar 

  32. Wade MJ (1992) Sewall Wright: gene interaction and the shifting balance theory. In: Antonovics J, Futuyma D (eds) Oxford Surveys of evolutionary biology, vol VI. Oxford University Press, Oxford, pp 35–62

    Google Scholar 

  33. Wade MJ (2002) A gene’s eye view of epistasis, selection, and speciation. J Evol Biol 15:337–346

    Article  Google Scholar 

  34. Wetherell M (1996) Identities, groups, and social issues. Sage, London

    Google Scholar 

  35. Whitlock MC (2011) G’ST and D do not replace FST. Mol Ecol 20:1083–1091

    Article  Google Scholar 

  36. Winther RG (2006) Fisherian and Wrightian perspectives in evolutionary genetics and model-mediated imposition of theoretical assumptions. J Theor Biol 240:218–232

    Article  Google Scholar 

  37. Winther RG (2011) ¿La cosificación genética de la “raza”? Un análisis crítico. In: López-Beltrán C (ed) Genes & mestizos: genómica y raza en la biomedicina Mexicana. UNAM, Mexico City, pp 237–258

    Google Scholar 

  38. Yu N, Chen F-C, Ota S, Jorde LB, Pamilo P, Patthy L, Ramsay M, Jenkins T, Shyue S-K, Li W-H (2002) Larger genetic differences within Africans than between Africans and Eurasians. Genetics 161:269–274

    Google Scholar 

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Acknowledgments

Matthew Kopec, Michael J. Wade, and the editors of this special issue of Biological Theory, Kim Sterelny, Massimo Pigliucci, and Werner Callebaut, kindly provided feedback on this paper. Kaplan would like to thank the participants at the KLI “The Meaning of ‘Theory’ in Biology” workshop for their comments, and the Oregon State University Center for the Humanities, whose support helped make this work possible. Winther thanks Ian Hacking, Carlos López-Beltrán, and Amir Najmi for ongoing discussions on these topics. Kim Sneppen’s support of Winther’s guest research stay at the Biocomplexity Center, Niels Bohr Institute, University of Copenhagen, is also gratefully acknowledged. This paper, written fully jointly, with authors listed alphabetically, is the result of an ongoing collaboration that emerged from an e-mail exchange between the authors that began with Kaplan reading Winther (2011).

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Kaplan, J.M., Winther, R.G. Prisoners of Abstraction? The Theory and Measure of Genetic Variation, and the Very Concept of “Race”. Biol Theory 7, 401–412 (2013). https://doi.org/10.1007/s13752-012-0048-0

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Keywords

  • Biological ontology
  • Differentiation
  • Diversity
  • Models
  • Population genetics
  • Populations
  • Race
  • Reification
  • Variation