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

Impact of Exon 1 polymorphism in the MBL2 gene on MBL serum levels and infection susceptibility in acute lymphoid leukemia

Polymorphisms in the MBL2 gene exon 1 can decrease serum levels of mannose-binding lectin (MBL), increasing the risk of infection in immunocompromised individuals. This study evaluated the association between the polymorphism in exon 1 of the MBL2 gene, genotypes, serum MBL levels, and infection in 122 patients with acute lymphoid leukemia (ALL). The MBL*A allele exhibited the highest frequency (0.37) within the study population. The MBL*D (0.32) was the predominant variant. The combined frequency of O polymorphic alleles (either B or D) was 0.63. The frequencies of the A/A, A/O and O/O genotypes were 0.13, 0.49 and 0.38, respectively. All patients exhibited consistently low levels of serum MBL, irrespective of their exon 1 genotype. Parasitic infections (n = 103), bacterial (n = 69) and viral (n = 48). A/O genotype (0.49) had higher infection rates, A/A (0.13) had lower rates, and O/O showed increased viral susceptibility (OR: 0.37; 95% CI 0.13-1.06; p = 0.05). Our findings demonstrated that the study population were MBL-deficient, regardless of their MLB2 genotype. Individuals with the A/O genotype had more infections, while those with the O/O genotype appeared more susceptible to viral infections. These findings highlight the impact of MBL levels and genetic variants on infection susceptibility in ALL patients.

Genes, culture, and scientific racism

Quantitative studies of cultural evolution and gene-culture coevolution (henceforth "CE" and "GCC") emerged in the 1970s, in the aftermath of the "race and intelligence quotient (IQ)" and "human sociobiology" debates, as a counter to extreme hereditarian positions. These studies incorporated cultural transmission and its interaction with genetics in contributing to patterns of human variation. Neither CE nor GCC results were consistent with racist claims of ubiquitous genetic differences between socially defined races. We summarize how genetic data refute the notion of racial substructure for human populations and address naive interpretations of race across the biological sciences, including those related to ancestry, health, and intelligence, that help to perpetuate racist ideas. A GCC perspective can refute reductionist and determinist claims while providing a more inclusive multidisciplinary framework in which to interpret human variation.

Human population dynamics in Upper Paleolithic Europe inferred from fossil dental phenotypes

Despite extensive archaeological research, our knowledge of the human population history of Upper Paleolithic Europe remains limited, primarily due to the scarce availability and poor molecular preservation of fossil remains. As teeth dominate the fossil record and preserve genetic signatures in their morphology, we compiled a large dataset of 450 dentitions dating between ~47 and 7 thousand years ago (ka), outnumbering existing skeletal and paleogenetic datasets. We tested a range of competing demographic scenarios using a coalescent-based machine learning Approximate Bayesian Computation (ABC) framework that we modified for use with phenotypic data. Mostly in agreement with but also challenging some of the hitherto available evidence, we identified a population turnover in western Europe at ~28 ka, isolates in western and eastern refugia between ~28 and 14.7 ka, and bottlenecks during the Last Glacial Maximum. Methodologically, this study marks the pioneering application of ABC to skeletal phenotypes, paving the way for exciting future research avenues.

Inferring human neutral genetic variation from craniodental phenotypes

There is a growing consensus that global patterns of modern human cranial and dental variation are shaped largely by neutral evolutionary processes, suggesting that craniodental features can be used as reliable proxies for inferring population structure and history in bioarchaeological, forensic, and paleoanthropological contexts. However, there is disagreement on whether certain types of data preserve a neutral signature to a greater degree than others. Here, we address this unresolved question and systematically test the relative neutrality of four standard metric and nonmetric craniodental data types employing an extensive computational genotype-phenotype comparison across modern populations from around the world. Our computation draws on the largest existing data sets currently available, while accounting for geographically structured environmental variation, population sampling uncertainty, disparate numbers of phenotypic variables, and stochastic variation inherent to a neutral model of evolution. Our results reveal that the four data types differentially capture neutral genomic variation, with highest signals preserved in dental nonmetric and cranial metric data, followed by cranial nonmetric and dental metric data. Importantly, we demonstrate that combining all four data types together maximizes the neutral genetic signal compared with using them separately, even with a limited number of phenotypic variables. We hypothesize that this reflects a lower level of genetic integration through pleiotropy between, compared to within, the four data types, effectively forming four different modules associated with relatively independent sets of loci. Therefore, we recommend that future craniodental investigations adopt holistic combined data approaches, allowing for more robust inferences about underlying neutral genetic variation.

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'.

The apportionment of citations: a scientometric analysis of Lewontin 1972

'The apportionment of human diversity' (1972) is the most highly cited research article published by geneticist Richard Lewontin in his career. This study's primary result-that most genetic diversity in humans can be accounted for by within-population differences, not between-population differences-along with Lewontin's outspoken, politically charged interpretations thereof, has become foundational to the scientific and cultural discourse pertaining to human genetic variation. The article has an unusual bibliometric trajectory in that it is much more salient in the bibliographic record today compared to the first 20 years after its publication. Here, we highlight four factors that may have played a role in shaping the paper's fame: (i) citations in influential publications across several disciplines; (ii) Lewontin's own popular books and media appearances; (iii) the renaissance of population genetics research of the early 1990s; and (iv) the serendipitous collision of scientific progress, influential books and papers, and heated controversies around the year 1994. We conclude with an analysis of Twitter data to characterize the communities and conversations that continue to keep this study at the centre of discussions about race and genetics, prompting new challenges for scientists who have inherited Lewontin's legacy. 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.

The Phenotypic Consequences of Genetic Divergence between Admixed Latin American Populations: Antioquia and Chocó, Colombia

Genome-wide association studies have uncovered thousands of genetic variants that are associated with a wide variety of human traits. Knowledge of how trait-associated variants are distributed within and between populations can provide insight into the genetic basis of group-specific phenotypic differences, particularly for health-related traits. We analyzed the genetic divergence levels for 1) individual trait-associated variants and 2) collections of variants that function together to encode polygenic traits, between two neighboring populations in Colombia that have distinct demographic profiles: Antioquia (Mestizo) and Chocó (Afro-Colombian). Genetic ancestry analysis showed 62% European, 32% Native American, and 6% African ancestry for Antioquia compared with 76% African, 10% European, and 14% Native American ancestry for Chocó, consistent with demography and previous results. Ancestry differences can confound cross-population comparison of polygenic risk scores (PRS); however, we did not find any systematic bias in PRS distributions for the two populations studied here, and population-specific differences in PRS were, for the most part, small and symmetrically distributed around zero. Both genetic differentiation at individual trait-associated single nucleotide polymorphisms and population-specific PRS differences between Antioquia and Chocó largely reflected anthropometric phenotypic differences that can be readily observed between the populations along with reported disease prevalence differences. Cases where population-specific differences in genetic risk did not align with observed trait (disease) prevalence point to the importance of environmental contributions to phenotypic variance, for both infectious and complex, common disease. The results reported here are distributed via a web-based platform for searching trait-associated variants and PRS divergence levels at http://map.chocogen.com (last accessed August 12, 2020).

Skin deep: The decoupling of genetic admixture levels from phenotypes that differed between source populations

OBJECTIVES

In genetic admixture processes, source groups for an admixed population possess distinct patterns of genotype and phenotype at the onset of admixture. Particularly in the context of recent and ongoing admixture, such differences are sometimes taken to serve as markers of ancestry for individuals-that is, phenotypes initially associated with the ancestral background in one source population are assumed to continue to reflect ancestry in that population. Such phenotypes might possess ongoing significance in social categorizations of individuals, owing in part to perceived continuing correlations with ancestry. However, genotypes or phenotypes initially associated with ancestry in one specific source population have been seen to decouple from overall admixture levels, so that they no longer serve as proxies for genetic ancestry. Here, we aim to develop an understanding of the joint dynamics of admixture levels and phenotype distributions in an admixed population.

METHODS

We devise a mechanistic model, consisting of an admixture model, a quantitative trait model, and a mating model. We analyze the behavior of the mechanistic model in relation to the model parameters.

RESULTS

We find that it is possible for the decoupling of genetic ancestry and phenotype to proceed quickly, and that it occurs faster if the phenotype is driven by fewer loci. Positive assortative mating attenuates the process of dissociation relative to a scenario in which mating is random with respect to genetic admixture and with respect to phenotype.

CONCLUSIONS

The mechanistic framework suggests that in an admixed population, a trait that initially differed between source populations might serve as a reliable proxy for ancestry for only a short time, especially if the trait is determined by few loci. It follows that a social categorization based on such a trait is increasingly uninformative about genetic ancestry and about other traits that differed between source populations at the onset of admixture.

Testing the utility of dental morphological trait combinations for inferring human neutral genetic variation

Researchers commonly rely on human dental morphological features in order to reconstruct genetic affinities among past individuals and populations, particularly since teeth are often the best preserved part of a human skeleton. Tooth form is considered to be highly heritable and selectively neutral and, therefore, to be an excellent proxy for DNA when none is available. However, until today, it remains poorly understood whether certain dental traits or trait combinations preserve neutral genomic signatures to a greater degree than others. Here, we address this long-standing research gap by systematically testing the utility of 27 common dental traits and >134 million possible trait combinations in reflecting neutral genomic variation in a worldwide sample of modern human populations. Our analyses reveal that not all traits are equally well-suited for reconstructing population affinities. Whereas some traits largely reflect neutral variation and therefore evolved primarily as a result of genetic drift, others can be linked to nonstochastic processes such as natural selection or hominin admixture. We also demonstrate that reconstructions of population affinity based on many traits are not necessarily more reliable than those based on only a few traits. Importantly, we find a set of highly diagnostic trait combinations that preserve neutral genetic signals best (up to [Formula: see text] _r = 0.580; 95% r range = 0.293 to 0.758; P = 0.001). We propose that these trait combinations should be prioritized in future research, as they allow for more accurate inferences about past human population dynamics when using dental morphology as a proxy for DNA.

Evolutionary perspectives on polygenic selection, missing heritability, and GWAS

Genome-wide association studies (GWAS) have successfully identified many trait-associated variants, but there is still much we do not know about the genetic basis of complex traits. Here, we review recent theoretical and empirical literature regarding selection on complex traits to argue that "missing heritability" is as much an evolutionary problem as it is a statistical problem. We discuss empirical findings that suggest a role for selection in shaping the effect sizes and allele frequencies of causal variation underlying complex traits, and the limitations of these studies. We then use simulations of selection, realistic genome structure, and complex human demography to illustrate the results of recent theoretical work on polygenic selection, and show that statistical inference of causal loci is sharply affected by evolutionary processes. In particular, when selection acts on causal alleles, it hampers the ability to detect causal loci and constrains the transferability of GWAS results across populations. Last, we discuss the implications of these findings for future association studies, and suggest that future statistical methods to infer causal loci for genetic traits will benefit from explicit modeling of the joint distribution of effect sizes and allele frequencies under plausible evolutionary models.

Interpreting polygenic scores, polygenic adaptation, and human phenotypic differences

Recent analyses of polygenic scores have opened new discussions concerning the genetic basis and evolutionary significance of differences among populations in distributions of phenotypes. Here, we highlight limitations in research on polygenic scores, polygenic adaptation and population differences. We show how genetic contributions to traits, as estimated by polygenic scores, combine with environmental contributions so that differences among populations in trait distributions need not reflect corresponding differences in genetic propensity. Under a null model in which phenotypes are selectively neutral, genetic propensity differences contributing to phenotypic differences among populations are predicted to be small. We illustrate this null hypothesis in relation to health disparities between African Americans and European Americans, discussing alternative hypotheses with selective and environmental effects. Close attention to the limitations of research on polygenic phenomena is important for the interpretation of their relationship to human population differences.

Linkage disequilibrium matches forensic genetic records to disjoint genomic marker sets

Combining genotypes across datasets is central in facilitating advances in genetics. Data aggregation efforts often face the challenge of record matching-the identification of dataset entries that represent the same individual. We show that records can be matched across genotype datasets that have no shared markers based on linkage disequilibrium between loci appearing in different datasets. Using two datasets for the same 872 people-one with 642,563 genome-wide SNPs and the other with 13 short tandem repeats (STRs) used in forensic applications-we find that 90-98% of forensic STR records can be connected to corresponding SNP records and vice versa. Accuracy increases to 99-100% when ∼30 STRs are used. Our method expands the potential of data aggregation, but it also suggests privacy risks intrinsic in maintenance of databases containing even small numbers of markers-including databases of forensic significance.

Recent advances in the study of fine-scale population structure in humans

Empowered by modern genotyping and large samples, population structure can be accurately described and quantified even when it only explains a fraction of a percent of total genetic variance. This is especially relevant and interesting for humans, where fine-scale population structure can both confound disease-mapping studies and reveal the history of migration and divergence that shaped our species' diversity. Here we review notable recent advances in the detection, use, and understanding of population structure. Our work addresses multiple areas where substantial progress is being made: improved statistics and models for better capturing differentiation, admixture, and the spatial distribution of variation; computational speed-ups that allow methods to scale to modern data; and advances in haplotypic modeling that have wide ranging consequences for the analysis of population structure. We conclude by outlining four important open challenges: the limitations of discrete population models, uncertainty in individual origins, the incorporation of both fine-scale structure and ancient DNA in parametric models, and the development of efficient computational tools, particularly for haplotype-based methods.

Population Genomics and the Statistical Values of Race: An Interdisciplinary Perspective on the Biological Classification of Human Populations and Implications for Clinical Genetic Epidemiological Research

The biological status and biomedical significance of the concept of race as applied to humans continue to be contentious issues despite the use of advanced statistical and clustering methods to determine continental ancestry. It is thus imperative for researchers to understand the limitations as well as potential uses of the concept of race in biology and biomedicine. This paper deals with the theoretical assumptions behind cluster analysis in human population genomics. Adopting an interdisciplinary approach, it demonstrates that the hypothesis that attributes the clustering of human populations to "frictional" effects of landform barriers at continental boundaries is empirically incoherent. It then contrasts the scientific status of the "cluster" and "cline" constructs in human population genomics, and shows how cluster may be instrumentally produced. It also shows how statistical values of race vindicate Darwin's argument that race is evolutionarily meaningless. Finally, the paper explains why, due to spatiotemporal parameters, evolutionary forces, and socio-cultural factors influencing population structure, continental ancestry may be pragmatically relevant to global and public health genomics. Overall, this work demonstrates that, from a biological systematic and evolutionary taxonomical perspective, human races/continental groups or clusters have no natural meaning or objective biological reality. In fact, the utility of racial categorizations in research and in clinics can be explained by spatiotemporal parameters, socio-cultural factors, and evolutionary forces affecting disease causation and treatment response.

A General Model of the Relationship between the Apportionment of Human Genetic Diversity and the Apportionment of Human Phenotypic Diversity

Models that examine genetic differences between populations alongside a genotype-phenotype map can provide insight about phenotypic variation among groups. We generalize a simple model of a completely heritable, additive, selectively neutral quantitative trait to examine the relationship between single-locus genetic differentiation and phenotypic differentiation on quantitative traits. In agreement with similar efforts using different models, we show that the expected degree to which two groups differ on a neutral quantitative trait is not strongly affected by the number of genetic loci that influence the trait: neutral trait differences are expected to have a magnitude comparable to the genetic differences at a single neutral locus. We discuss this result with respect to population differences in disease phenotypes, arguing that although neutral genetic differences between populations can contribute to specific differences between populations in health outcomes, systematic patterns of difference that run in the same direction for many genetically independent health conditions are unlikely to be explained by neutral genetic differentiation.

Putting humanity back into the teaching of human biology

In this paper, I draw upon debates about race in biology and philosophy as well as the concepts of ineliminable pluralism and psychological essentialism to outline the necessary subject matter knowledge that teachers should possess if they desire to: (i) increase student understanding of scientific research on genetic and behavioral variation in humans; and (ii) attenuate inegalitarian beliefs about race amongst students.

Gould on Morton, Redux: What can the debate reveal about the limits of data?

Lewis et al. (2011) attempted to restore the reputation of Samuel George Morton, a 19th century physician who reported on the skull sizes of different folk-races. Whereas Gould (1978) claimed that Morton's conclusions were invalid because they reflected unconscious bias, Lewis et al. alleged that Morton's findings were, in fact, supported, and Gould's analysis biased. We take strong exception to Lewis et al.'s thesis that Morton was "right." We maintain that Gould was right to reject Morton's analysis as inappropriate and misleading, but wrong to believe that a more appropriate analysis was available. Lewis et al. fail to recognize that there is, given the dataset available, no appropriate way to answer any of the plausibly interesting questions about the "populations" in question (which in many cases are not populations in any biologically meaningful sense). We challenge the premise shared by both Gould and Lewis et al. that Morton's confused data can be used to draw any meaningful conclusions. This, we argue, reveals the importance of properly focusing on the questions asked, rather than more narrowly on the data gathered.