The background and legacy of Lewontin's apportionment of human genetic diversity

Lewontin's 1972 article 'The apportionment of human diversity' described a key feature of human genetic diversity that would have profound impacts on conversations regarding genetics and race: the typical genetic locus varies much less between classical human race groupings than one might infer from inspecting the features historically used to define those races, like skin pigmentation. From this, Lewontin concluded: 'Human racial classification … is now seen to be of virtually no genetic or taxonomic significance' (p. 397). Here, 50 years after the paper's publication, the goal is to understand the origins and legacy of the paper. Aided by insights from published papers and interviews with several of Lewontin's contemporaries, I review the 1972 paper, asking about the intellectual background that led to the publication of the paper, the development of its impact, the critiques of the work and the work's application and limitations today. The hope is that by gaining a clearer understanding of the origin and reasoning of the paper, we might dispel various confusions about the result and sharpen an understanding of the enduring value and insight the result provides. This article is part of the theme issue 'Celebrating 50 years since Lewontin's apportionment of human diversity'.

Re-situations of scientific knowledge: a case study of a skirmish over clusters vs clines in human population genomics

We track and analyze the re-situation of scientific knowledge in the field of human population genomics ancestry studies. We understand re-situation as a process of accommodating the direct or indirect transfer of objects of knowledge from one site/situation to (one or many) other sites/situations. Our take on the concept borrows from Mary S. Morgan's work on facts traveling while expanding it to include other objects of knowledge such as models, data, software, findings, and visualizations. We structure a specific case study by tracking the re-situation of these objects between three research projects studying human population diversity reported in three articles in Science, Genome Research and PLoS Genetics between 2002 and 2005. We characterize these three engagements as a unit of analysis, a "skirmish," in order to compare: (a) the divergence of interests in how life-scientists answer similar research questions and (b) to track the challenging transformation of workflows in research laboratories as these scientific objects are re-situated individually or in bundles. Our analysis of the case study shows that an accurate understanding of re-situation requires tracking the whole bundle of objects in a project because they interact in particular key ways. The absence or dismissal of these interactions opens the door to unforeseen trade-offs, misunderstandings and misrepresentations about research design(s) and workflow(s) and what these say about the questions asked and the findings produced.

Implications of the apportionment of human genetic diversity for the apportionment of human phenotypic diversity

Researchers in many fields have considered the meaning of two results about genetic variation for concepts of "race." First, at most genetic loci, apportionments of human genetic diversity find that worldwide populations are genetically similar. Second, when multiple genetic loci are examined, it is possible to distinguish people with ancestry from different geographical regions. These two results raise an important question about human phenotypic diversity: To what extent do populations typically differ on phenotypes determined by multiple genetic loci? It might be expected that such phenotypes follow the pattern of similarity observed at individual loci. Alternatively, because they have a multilocus genetic architecture, they might follow the pattern of greater differentiation suggested by multilocus ancestry inference. To address the question, we extend a well-known classification model of Edwards (2003) by adding a selectively neutral quantitative trait. Using the extended model, we show, in line with previous work in quantitative genetics, that regardless of how many genetic loci influence the trait, one neutral trait is approximately as informative about ancestry as a single genetic locus. The results support the relevance of single-locus genetic-diversity partitioning for predictions about phenotypic diversity.

Human neutral genetic variation and forensic STR data

The forensic genetics field is generating extensive population data on polymorphism of short tandem repeats (STR) markers in globally distributed samples. In this study we explored and quantified the informative power of these datasets to address issues related to human evolution and diversity, by using two online resources: an allele frequency dataset representing 141 populations summing up to almost 26 thousand individuals; a genotype dataset consisting of 42 populations and more than 11 thousand individuals. We show that the genetic relationships between populations based on forensic STRs are best explained by geography, as observed when analysing other worldwide datasets generated specifically to study human diversity. However, the global level of genetic differentiation between populations (as measured by a fixation index) is about half the value estimated with those other datasets, which contain a much higher number of markers but much less individuals. We suggest that the main factor explaining this difference is an ascertainment bias in forensics data resulting from the choice of markers for individual identification. We show that this choice results in average low variance of heterozygosity across world regions, and hence in low differentiation among populations. Thus, the forensic genetic markers currently produced for the purpose of individual assignment and identification allow the detection of the patterns of neutral genetic structure that characterize the human population but they do underestimate the levels of this genetic structure compared to the datasets of STRs (or other kinds of markers) generated specifically to study the diversity of human populations.

A population-genetic perspective on the similarities and differences among worldwide human populations

Recent studies have produced a variety of advances in the investigation of genetic similarities and differences among human populations. Here, I pose a series of questions about human population-genetic similarities and differences, and I then answer these questions by numerical computation with a single shared population-genetic data set. The collection of answers obtained provides an introductory perspective for understanding key results on the features of worldwide human genetic variation.

A Markov chain Monte Carlo method for estimating population mixing using Y-chromosome markers: mixing of the Han people in China

We present a new approach for estimating mixing between populations based on non-recombining markers, specifically Y-chromosome microsatellites. A Markov chain Monte Carlo (MCMC) Bayesian statistical approach is used to calculate the posterior probability distribution of population parameters of interest, including the effective population size and the time to most recent common ancestor (MRCA). To test whether two populations are homogeneously mixed we introduce a "mixing" statistic defined for each coalescent event that weights the contribution of that ancestor's descendants to the two subpopulations, and an associated population "purity" statistic. Using simulated data with low levels of migration between two populations, we demonstrate that our method is more sensitive than other commonly used distance-based methods such as R(ST) and D(SW). To illustrate our method, we analysed mixing between 11 pre-defined Chinese ethnic/regional populations, using 5 microsatellite markers from the non-recombining region of the Y-chromosome (NRY), demonstrating a significant clustering of a subset of subpopulations with a high mutual relative degree of mixing (homogeneous mixing with support >0.99). Our analysis suggests that there is a strong correlation between effective population size and mixing with other subpopulations. Thus, despite considerable mixing between these groups, the purity statistic still identifies significant heterogeneity, suggesting that periods of historical isolation continue to leave a recoverable signal despite modern introgression.

Standardized subsets of the HGDP-CEPH Human Genome Diversity Cell Line Panel, accounting for atypical and duplicated samples and pairs of close relatives

The HGDP-CEPH Human Genome Diversity Cell Line Panel is a widely-used resource for studies of human genetic variation. Here, pairs of close relatives that have been included in the panel are identified. Together with information on atypical and duplicated samples, the inferred relative pairs suggest standardized subsets of the panel for use in future population-genetic studies.

The genetic structure of human populations studied through short insertion-deletion polymorphisms

In a landmark study Rosenberg et al. (2002) analyzed human genome diversity with 377 microsatellites in the HGDP-CEPH Genome Diversity Panel and reported that the populations were structured into five geographical regions: America, Sub-Saharan Africa, East Asia, Oceania and a cluster composed of Europe, the Middle East and Central Asia. They also observed that the within-population component accounted for 93-95%, and that the among-regions portion was only 3.6%, of the total genetic variance. We have also studied the HGDP-CEPH Diversity Panel (1,064 individuals from 52 populations) with a set of 40 biallelic slow-evolving short insertion-deletion polymorphisms (indels). We confirmed the partition of worldwide diversity into five genetic clusters that correspond to major geographic regions. Using the indels we have also disclosed an among-regions component of genetic variance considerably larger (12.1%) than had been estimated using microsatellites. Our study demonstrates that a set of 40 well-chosen biallelic markers is sufficient for the characterization of human population structure at the global level.

Race and IQ: Molecular genetics as deus ex machina

During the last hundred years, the debate over the meaning of race has retained a highly consistent core, despite evolution of the technical details. Non-Europeans, and in particular, Africans, are assigned the role of deviants and outcasts, whose claim on our common humanity remains in doubt. Each time the technical facade of these racialist arguments is destroyed, the latest jargon and half-truths from the margins of science are used to rebuild them around the same core belief in Black inferiority. Because race is in part a genetic concept, the advent of molecular DNA technology has opened an important new chapter in this story. Unfortunately, the article by D. Rowe (2005, this issue, see record 2005-00117-007) begins from mistaken premises and merely restates the racialist view using the terminology of molecular genetics. No technology--even the awe-inspiring tools now available to DNA science--can overcome the handicap of fundamental conceptual errors. Race is not a concept that emerged from within modern genetics; rather, it was imposed by history, and its meaning is inseparable from that cultural origin. By ignoring its cultural meaning the reductionist narrative about race fails--both in the narrow terms of science and as a contribution to the broader social discourse.

Statistical tests for admixture mapping with case-control and cases-only data

Admixture mapping is a promising new tool for discovering genes that contribute to complex traits. This mapping approach uses samples from recently admixed populations to detect susceptibility loci at which the risk alleles have different frequencies in the original contributing populations. Although the idea for admixture mapping has been around for more than a decade, the genomic tools are only now becoming available to make this a feasible and attractive option for complex-trait mapping. In this article, we describe new statistical methods for analyzing multipoint data from admixture-mapping studies to detect "ancestry association." The new test statistics do not assume a particular disease model; instead, they are based simply on the extent to which the sample's ancestry proportions at a locus deviate from the genome average. Our power calculations show that, for loci at which the underlying risk-allele frequencies are substantially different in the ancestral populations, the power of admixture mapping can be comparable to that of association mapping but with a far smaller number of markers. We also show that, although "ancestry informative markers" (AIMs) are superior to random single-nucleotide polymorphisms (SNPs), random SNPs can perform quite well when AIMs are not available. Hence, researchers who study admixed populations in which AIMs are not available can perform admixture mapping with the use of modestly higher densities of random markers. Software to perform the gene-mapping calculations, "MALDsoft," is freely available on the Pritchard Lab Web site.

Robustness of the inference of human population structure: a comparison of X-chromosomal and autosomal microsatellites

In this paper, data on 20 X-chromosomal microsatellite polymorphisms from the HGDP-CEPH cell line panel are used to infer human population structure. Inferences from these data are compared to those obtained from autosomal microsatellites. Some of the major features of the structure seen with 377 autosomal markers are generally visible with the X-linked markers, although the latter provide less resolution. Differences between the X-chromosomal and autosomal results can be explained without requiring major differences in demographic parameters between males and females. The dependence of the partitioning on the number of individuals sampled from each region and on the number of markers used is discussed.

Informativeness of genetic markers for inference of ancestry

Inference of individual ancestry is useful in various applications, such as admixture mapping and structured-association mapping. Using information-theoretic principles, we introduce a general measure, the informativeness for assignment (I(n)), applicable to any number of potential source populations, for determining the amount of information that multiallelic markers provide about individual ancestry. In a worldwide human microsatellite data set, we identify markers of highest informativeness for inference of regional ancestry and for inference of population ancestry within regions; these markers, which are listed in online-only tables in our article, can be useful both in testing for and in controlling the influence of ancestry on case-control genetic association studies. Markers that are informative in one collection of source populations are generally informative in others. Informativeness of random dinucleotides, the most informative class of microsatellites, is five to eight times that of random single-nucleotide polymorphisms (SNPs), but 2%-12% of SNPs have higher informativeness than the median for dinucleotides. Our results can aid in decisions about the type, quantity, and specific choice of markers for use in studies of ancestry.