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

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.

Using mathematical constraints to explain narrow ranges for allele-sharing dissimilarities

Allele-sharing dissimilarity (ASD) statistics are measures of genetic differentiation for pairs of individuals or populations. Given the allele-frequency distributions of two populations-possibly the same population-the expected value of an ASD statistic is computed by evaluating the expectation of the pairwise dissimilarity between two individuals drawn at random, each from its associated allele-frequency distribution. For each of two ASD statistics, which we termD 1 andD 2 , we investigate the extent to which the expected ASD is constrained by allele frequencies in the two populations; in other words, how is the magnitude of the measure bounded as a function of the frequency of the most frequent allelic type? We first consider dissimilarity of a population with itself, obtaining bounds on expected ASD in terms of the frequency of the most frequent allelic type in the population. We then examine pairs of populations that might or might not possess the same most frequent allelic type. Across the unit interval for the frequency of the most frequent allelic type, the expected allele-sharing dissimilarity has a range that is more restricted than the [0, 1] interval. The mathematical constraints on expected ASD assist in explaining a pattern observed empirically in human populations, namely that when averaging across loci, allele-sharing dissimilarities between pairs of individuals often tend to vary only within a relatively narrow range.

The Importance of Cultural Awareness in the Management of Heart Failure: A Narrative Review

Heart failure is a commonly encountered clinical syndrome arising from a range of etiologic cardiovascular diseases and manifests in a phenotypic spectrum of varying degrees of systolic and diastolic ventricular dysfunction. Those affected by this life-limiting illness are subject to an array of burdensome symptoms, poor quality of life, prognostic uncertainty, and a relatively onerous and increasingly complex treatment regimen. This condition occurs in epidemic proportions worldwide, and given the demographic trend in societal ageing, the prevalence of heart failure is only likely to increase. The marked upturn in international migration has generated other demographic changes in recent years, and it is evident that we are living and working in ever more ethnically and culturally diverse communities. Professionals treating those with heart failure are now dealing with a much more culturally disparate clinical cohort. Given that the heart failure disease trajectory is unique to each individual, these clinicians need to ensure that their proposed treatment options and responses to the inevitable crises intrinsic to this condition are in keeping with the culturally determined values, preferences, and worldviews of these patients and their families. In this narrative review, we describe the importance of cultural awareness across a range of themes relevant to heart failure management and emphasize the centrality of cultural competence as the basis of appropriate care provision.

Genetic Testing and Other Healthcare Use by Black and White Individuals in a Genomic Sequencing Study

INTRODUCTION

Early adopters play a critical role in the diffusion of medical innovations by spreading awareness, increasing acceptability, and driving demand. Understanding the role of race in the context of other characteristics of potential early adopters can shed light on disparities seen in the early implementation of genomic medicine. We aimed to understand the association between self-identified race and individual experience with genetic testing outside of the research context.

METHODS

We assessed factors associated with the odds of having ever received genetic testing prior to enrollment in a genomic sequencing study among 674 self-identified white and 407 self-identified African, African American, or Afro-Caribbean ("Black") individuals.

RESULTS

Controlling for individual determinants of healthcare use (demographics, personality traits, knowledge and attitudes, and health status), identifying as Black was associated with lower odds of prior genetic testing (OR = 0.43, 95% CI [0.27-0.68], p < 0.001). In contrast, self-identified race was not associated with the use of non-genetic clinical screening tests (e.g., echocardiogram, colonoscopy). Black and white individuals were similar on self-reported personality traits tied to early adoption but differed by sociodemographic and resource facilitators of early adoption.

CONCLUSION

Persistent racial disparities among early adopters may represent especially-entrenched disparities in access to and knowledge of genomic technologies in clinical settings.

A rarefaction approach for measuring population differences in rare and common variation

In studying allele-frequency variation across populations, it is often convenient to classify an allelic type as "rare," with nonzero frequency less than or equal to a specified threshold, "common," with a frequency above the threshold, or entirely unobserved in a population. When sample sizes differ across populations, however, especially if the threshold separating "rare" and "common" corresponds to a small number of observed copies of an allelic type, discreteness effects can lead a sample from one population to possess substantially more rare allelic types than a sample from another population, even if the two populations have extremely similar underlying allele-frequency distributions across loci. We introduce a rarefaction-based sample-size correction for use in comparing rare and common variation across multiple populations whose sample sizes potentially differ. We use our approach to examine rare and common variation in worldwide human populations, finding that the sample-size correction introduces subtle differences relative to analyses that use the full available sample sizes. We introduce several ways in which the rarefaction approach can be applied: we explore the dependence of allele classifications on subsample sizes, we permit more than two classes of allelic types of nonzero frequency, and we analyze rare and common variation in sliding windows along the genome. The results can assist in clarifying similarities and differences in allele-frequency patterns across populations.

Sequence-based allelic variations and frequencies for 22 autosomal STR loci in the Lebanese population

This is the first study that characterizes the sequence-based allelic variations of 22 autosomal Short Tandem Repeat (aSTR) loci in a population dataset collected from Lebanon. Genomic DNA extracts from 195 unrelated Lebanese individuals were amplified with PowerSeq 46GY System Prototype. Targeted amplicons were subjected to DNA library preparation and sequenced on the Verogen MiSeq FGx Sequencing System. Raw FASTQ data files were processed by STRait Razor v3. Sequence strings were annotated according to the considerations of the DNA Commission of the International Society for Forensic Genetics (ISFG) and tabulated herein with their respective allelic frequencies and GeneBank accession and version numbers. The sequenced Lebanese dataset resulted in 429 distinct allelic sequences as compared to the 236 alleles identified by length only. The increase in the number of alleles was observed at 18 out of 22 aSTR loci and was attributed to the sequence variations residing in both the STR repeat motifs and flanking regions. The study uncovered 25 novel aSTR allelic sequences across 12 loci for which GenBank records did not previously exist in the STRSeq BioProject, PRJNA380127. For a concordance check, the length-based allelic calls derived from the full sequences were compared to those genotyped using capillary electrophoresis (CE) methods. Population genetic parameters relevant to the evaluation of forensic DNA evidence were assessed for the sequence-based data and compared to the parameters generated from the length-based information. Using the sequence-based data, Analysis of MOlecular VAriance (AMOVA), genetic distances, and population genetic structure were evaluated for 1231 individuals sampled from the Lebanese and four U.S. populations (African American, Asian, Caucasian, and Hispanic). The results were tabulated and visualized in a population tree, multidimensional scaling scatter plots, and bar plots. This newly established sequence-based database for the Lebanese population can be beneficial for extending NGS applicability to casework or paternity testing and assessing the strength of evidence for NGS-STR profiles. The described novel sequence variants at certain loci can further help in the effort to characterize the sequence diversity of STR markers from different populations around the world.

Regulating genetic engineering guided by human dignity, not genetic essentialism

How might a liberal democratic community best regulate human genetic engineering? Relevant debates widely deploy the usually undefined term "human dignity." Its indeterminacy in meaning and use renders it useless as a guiding principle. In this article, I reject the human genome as somehow invested with a moral status, a position I call "genetic essentialism." I explain why a critique of genetic essentialism is not a strawman and argue against defining human rights in terms of genetic essentialism. As an alternative, I propose dignity as the decisional autonomy of future persons, held in trust by the current generation. I show why a future person could be expected to have an interest in decisional autonomy and how popular deliberation, combined with expert medical and bioethical opinion, could generate principled agreement on how the decisional autonomy of future persons might be configured at the point of genetic engineering.

Science, Society, and Dismantling Racism

As a foundational pillar of the Truth, Racial Healing & Transformation framework, Narrative Change involves reckoning with our historical and current realities regarding "race" and racism, uprooting dominant narratives that normalize injustice and sustain oppression, and advancing narratives that promote equity and collective liberation. Narrative Change is vital to creating communal recognition and appreciation of the interconnectedness and equality of all humans and dismantling the ideology and structures of racial hierarchy. Telling new or more truthful and complete stories must include improving our understanding and messaging about what race is and what it is not as well as the relationship between race and racism. Ideas about the existence of biological human races have long been discredited by scientists and scholars in various fields. Yet, false beliefs about natural and fixed biological differences within the human species persist in some scientific studies, in aspects of health care, and in the political and legal architectures of the United States and other countries, thereby reproducing and maintaining social hierarchies. Efforts to eradicate racism and its pernicious effects are limited in their potential for sustained positive transformation unless simultaneous endeavors are undertaken to reframe people's thinking about the very concept of race. This brief provides an overview of the origins of racial hierarchy, distinguishes between biological concepts of race and socially defined race, reviews perspectives on the meanings and uses of race, and describes ongoing and potential efforts to address prevailing misunderstandings about race and racism.

When is the allele-sharing dissimilarity between two populations exceeded by the allele-sharing dissimilarity of a population with itself?

Allele-sharing statistics for a genetic locus measure the dissimilarity between two populations as a mean of the dissimilarity between random pairs of individuals, one from each population. Owing to within-population variation in genotype, allele-sharing dissimilarities can have the property that they have a nonzero value when computed between a population and itself. We consider the mathematical properties of allele-sharing dissimilarities in a pair of populations, treating the allele frequencies in the two populations parametrically. Examining two formulations of allele-sharing dissimilarity, we obtain the distributions of within-population and between-population dissimilarities for pairs of individuals. We then mathematically explore the scenarios in which, for certain allele-frequency distributions, the within-population dissimilarity - the mean dissimilarity between randomly chosen members of a population - can exceed the dissimilarity between two populations. Such scenarios assist in explaining observations in population-genetic data that members of a population can be empirically more genetically dissimilar from each other on average than they are from members of another population. For a population pair, however, the mathematical analysis finds that at least one of the two populations always possesses smaller within-population dissimilarity than the value of the between-population dissimilarity. We illustrate the mathematical results with an application to human population-genetic data.

Addressing Racism in Human Genetics and Genomics Education

This installment of Current Insights summarizes recent research and scholarship in genetics and genomics education in order to stimulate critical discussions of the impact of genetics and genomics education on scientific racism. While it has been uncommon for genetics instruction to address issues of race explicitly, researchers suggest that a more humane, anti-racist approach to genetics and genomics education is needed and have begun to describe what it might look like. The articles in this set draw attention to the ongoing need for instructional design, careful research, and critical scholarship addressing racism in human genetics and genomics education.

Open-Access Worldwide Population STR Database Constructed Using High-Coverage Massively Parallel Sequencing Data Obtained from the 1000 Genomes Project

Achieving accurate STR genotyping by using next-generation sequencing data has been challenging. To provide the forensic genetics community with a reliable open-access STR database, we conducted a comprehensive genotyping analysis of a set of STRs of broad forensic interest obtained from 1000 Genome populations. We analyzed 22 STR markers using files of the high-coverage dataset of Phase 3 of the 1000 Genomes Project. We used HipSTR to call genotypes from 2504 samples obtained from 26 populations. We were not able to detect the D21S11 marker. The Hardy-Weinberg equilibrium analysis coupled with a comprehensive analysis of allele frequencies revealed that HipSTR was not able to identify longer alleles, which resulted in heterozygote deficiency. Nevertheless, AMOVA, a clustering analysis that uses STRUCTURE, and a Principal Coordinates Analysis showed a clear-cut separation between the four major ancestries sampled by the 1000 Genomes Consortium. Except for larger Penta D and Penta E alleles, and two very small Penta D alleles (2.2 and 3.2) usually observed in African populations, our analyses revealed that allele frequencies and genotypes offered as an open-access database are consistent and reliable.

Including diverse and admixed populations in genetic epidemiology research

The inclusion of ancestrally diverse participants in genetic studies can lead to new discoveries and is important to ensure equitable health care benefit from research advances. Here, members of the Ethical, Legal, Social, Implications (ELSI) committee of the International Genetic Epidemiology Society (IGES) offer perspectives on methods and analysis tools for the conduct of inclusive genetic epidemiology research, with a focus on admixed and ancestrally diverse populations in support of reproducible research practices. We emphasize the importance of distinguishing socially defined population categorizations from genetic ancestry in the design, analysis, reporting, and interpretation of genetic epidemiology research findings. Finally, we discuss the current state of genomic resources used in genetic association studies, functional interpretation, and clinical and public health translation of genomic findings with respect to diverse populations.

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'.

Apportioning archaic variants among modern populations

The apportionment of human genetic diversity within and between populations has been measured to understand human relatedness and demographic history. Likewise, the distribution of archaic ancestry in modern populations can be leveraged to better understand the interaction between our species and its archaic relatives. Resolving the interactions between modern and archaic human populations can be difficult, as archaic variants in modern populations have been shaped by genetic drift, bottlenecks and gene flow. Here, we investigate the distribution of archaic variation in Eurasian populations. We find that archaic ancestry coverage at the individual- and population-level present distinct patterns in modern human populations: South Asians have nearly twice the number of population-unique archaic alleles compared with Europeans or East Asians, indicating that these populations experienced differing demographic and archaic admixture events. We confirm previous observations that East Asian individuals have more Neanderthal ancestry than European individuals, but surprisingly, when we compare the number of single nucleotide polymorphisms with archaic alleles found across a population, Europeans have more Neanderthal ancestry than East Asians. We compare these results to simulated models and conclude that these patterns are consistent with multiple admixture events between modern humans and Neanderthals.

This article is part of the theme issue ‘Celebrating 50 years since Lewontin's apportionment of human diversity’.

Diversity and its causes: Lewontin on racism, biological determinism and the adaptationist programme

Lewontin's 1972 paper (RC Lewontin, 1972 The apportionment of human diversity, in Evolutionary biology, vol. 6 (eds T Dobzhansky, MK Hecht, WC Steere), pp. 381–398) can be viewed as one foray in his battle against biological determinism. Our paper shows where Lewontin, The apportionment of human diversity, fits in the debate over human classification that it stimulated. We outline three assumptions inherent in the biological deterministic view of human phenotypic diversity and show how the 1972 paper, as well as Lewontin's papers in 1970 and 1974 on the problems with the heritability statistic and his 1979 criticism of naive pan-selectionism, invalidate these assumptions. These papers were crucial components of his campaign against biological determinism and the racism with which it was associated. In the current climate of widespread racism and the rise of sociogenomics, it is important to revisit Lewontin's writings and to disseminate the messages they contain.

This article is part of the theme issue ‘Celebrating 50 years since Lewontin's apportionment of human diversity’.

Ending genetic essentialism through genetics education

Genetic concepts are regularly used in arguments about racial inequality. This review summarizes research about the relationship between genetics education and a particular form of racial prejudice known as genetic essentialism. Genetic essentialism is a cognitive form of prejudice that is used to rationalize inequality. Studies suggest that belief in genetic essentialism among genetics students can be increased or decreased based on what students learn about human genetics and why they learn it. Research suggests that genetics education does little to prevent the development of genetic essentialism, and it may even exacerbate belief in it. However, some forms of genetics education can avert this problem. In particular, if instructors teach genetics to help students understand the flaws in genetic essentialist arguments, then it is possible to reduce belief in genetic essentialism among biology students. This review outlines our knowledge about how to accomplish this goal and the research that needs to be done to end genetic essentialism through genetics education.

Revisiting the malaria hypothesis: accounting for polygenicity and pleiotropy

The malaria hypothesis predicts local, balancing selection of deleterious alleles that confer strong protection from malaria. Three protective variants, recently discovered in red cell genes, are indeed more common in African than European populations. Still, up to 89% of the heritability of severe malaria is attributed to many genome-wide loci with individually small effects. Recent analyses of hundreds of genome-wide association studies (GWAS) in humans suggest that most functional, polygenic variation is pleiotropic for multiple traits. Interestingly, GWAS alleles and red cell traits associated with small reductions in malaria risk are not enriched in African populations. We propose that other selective and neutral forces, in addition to malaria prevalence, explain the global distribution of most genetic variation impacting malaria risk.

Correlated population genetic structure in a three-tiered host-parasite system. The potential for coevolution and adaptive divergence

Three subspecies of Northern Bahamian Rock Iguanas, Cyclura cychlura, are currently recognized: C. c. cychlura, restricted to Andros Island, and C. c. figginsi and C. c. inornata, native to the Exuma Island chain. Populations on Andros are genetically distinct from Exuma Island populations, yet genetic divergence among populations in the Exumas is inconsistent with the two currently recognized subspecies from those islands. The potential consequences of this discrepancy might include the recognition of a single subspecies throughout the Exumas rather than two. That inference also ignores evidence that populations of C. cychlura are potentially adaptively divergent. We compared patterns of population relatedness in a three-tiered host-parasite system: C. cychlura iguanas, their ticks (genus Amblyomma, preferentially parasitizing these reptiles), and Rickettsia spp. endosymbionts (within tick ectoparasites). Our results indicate that while C. c. cychlura on Andros is consistently supported as a separate clade, patterns of relatedness among populations of C. c. figginsi and C. c. inornata within the Exuma Island chain are more complex. The distribution of the hosts, different tick species, and Rickettsia spp., supports the evolutionary independence of C. c. inornata. Further, these patterns are also consistent with two independent evolutionarily significant units within C. c. figginsi. Our findings suggest coevolutionary relationships between the reptile hosts, their ectoparasites, and rickettsial organisms, suggesting local adaptation. This work also speaks to the limitations of using neutral molecular markers from a single focal taxon as the sole currency for recognizing evolutionary novelty in populations of endangered species.

Common host variation drives malaria parasite fitness in healthy human red cells

The replication of Plasmodium falciparum parasites within red blood cells (RBCs) causes severe disease in humans, especially in Africa. Deleterious alleles like hemoglobin S are well-known to confer strong resistance to malaria, but the effects of common RBC variation are largely undetermined. Here, we collected fresh blood samples from 121 healthy donors, most with African ancestry, and performed exome sequencing, detailed RBC phenotyping, and parasite fitness assays. Over one-third of healthy donors unknowingly carried alleles for G6PD deficiency or hemoglobinopathies, which were associated with characteristic RBC phenotypes. Among non-carriers alone, variation in RBC hydration, membrane deformability, and volume was strongly associated with P. falciparum growth rate. Common genetic variants in PIEZO1, SPTA1/SPTB, and several P. falciparum invasion receptors were also associated with parasite growth rate. Interestingly, we observed little or negative evidence for divergent selection on non-pathogenic RBC variation between Africans and Europeans. These findings suggest a model in which globally widespread variation in a moderate number of genes and phenotypes modulates P. falciparum fitness in RBCs.

Evaluating population affinity estimates in forensic anthropology: Insights from the forensic anthropology database for assessing methods accuracy (FADAMA)

Using a sample of anonymized U.S. forensic anthropology cases (n = 251) from the FADAMA database, we assess the degree of concordance between decedents' social identifiers and anthropologists' continental-based classifications. We report high success rates (>90%) that generally support previous findings, yet we acknowledge the limitations of assessing "ancestry" accuracy based on resolved cases and draw attention to situations in which our methods fail. For example, forensic anthropologists achieve just 20% accuracy when classifying individuals as "other" or "mixed"-problematic categories that we argue should be rejected. Leveraging our findings, we ask: what are we really estimating when we perform a skeletal assessment of "ancestry" in the US context? We argue that the "ancestry estimates" historically and routinely produced in forensic anthropology instead give information on population affinity: a measure of how similar a given case is to one among several socially relevant groups of interest. Distancing forensic anthropology from genetics and other disciplines that estimate ancestry, the approach of population affinity assesses similarities to both social and biological groupings, potentially at a fine-grained level, attempting to account for the complex histories, shared biologies, and wide ranges of diversity that characterize our communities and our casework. Population affinity is a flexible and inclusive approach that more accurately describes current forensic anthropological analyses of human variation. Going forward, we must acknowledge and build on the contributions of previous scholars as we work together toward our shared goal of theoretically grounded analyses of human variation that accurately and equitably serve all casework decedents.

A variant-centric perspective on geographic patterns of human allele frequency variation

A key challenge in human genetics is to understand the geographic distribution of human genetic variation. Often genetic variation is described by showing relationships among populations or individuals, drawing inferences over many variants. Here, we introduce an alternative representation of genetic variation that reveals the relative abundance of different allele frequency patterns. This approach allows viewers to easily see several features of human genetic structure: (1) most variants are rare and geographically localized, (2) variants that are common in a single geographic region are more likely to be shared across the globe than to be private to that region, and (3) where two individuals differ, it is most often due to variants that are found globally, regardless of whether the individuals are from the same region or different regions. Our variant-centric visualization clarifies the geographic patterns of human variation and can help address misconceptions about genetic differentiation among populations.

[Racism and mental health]

Der Beitrag gibt einen Überblick zu Rassismusdiskursen in Forschung und Praxis im Gesundheitsbereich und erörtert individuelle und institutionelle Auswirkungen von Rassismus und Diskriminierung auf die psychische Gesundheit. Daran anschließend wird erörtert, welche rassismuskritischen Transformationen in den Versorgungsstrukturen für psychisch erkrankte Personen notwendig sind, um eine gleichberechtigte Teilhabe von Menschen, die von Diskriminierung und Rassismus betroffen sind, zu ermöglichen.

Association and interaction of the FTO rs1421085 with overweight/obesity in a sample of Pakistani individuals

PURPOSE

Genetic variants determine the predisposition of an individual to obesity in a given environment. The present study was conducted to seek an association of the FTO variant rs1421085 with overweight/obesity and related traits in 612 Pakistani subjects in a case-control manner (overweight/obese = 306 and non-obese = 306). Moreover, interaction effects of the rs1421085 and overweight/obesity on multiple metabolic traits were also investigated, which were never explored before in Pakistani as well as in any other population.

MATERIALS AND METHODS

Anthropometric traits were measured by standard procedures, while metabolic parameters were determined by biochemical assays. Genotyping of the rs1421085 was carried out by TaqMan allelic discrimination assay. The data were analysed using SPSS software version 19.

RESULTS

The study revealed a significant association of the rs1421085 with overweight/obese phenotype with respect to over-dominant model indicated by h-index. The CT genotype of the rs1421085 was observed to increase the risk of being overweight/obese by 1.583 times (95% CI 1.147-2.185, p = 0.005). The CT genotype was also found to be associated with higher values of all anthropometric variables (except height and waist-to-hip ratio). Moreover, the interaction between the CT genotype of the rs1421085 and overweight/obesity was found to influence several metabolic parameters (raised blood pressure, product of triglyceride and glucose index, triglyceride levels, LDL-C, VLDL-C, coronary risk index, atherogenic index, and triglyceride-to-HDL-C ratio).

CONCLUSION

In conclusion, the rs1421085 was found to be associated with overweight/obesity and related anthropometric traits independent of age and gender in Pakistani population. Moreover, this variant was found to influence various metabolic traits in the presence of overweight/obesity.

LEVEL OF EVIDENCE

Level III, case-control analytic study.

Brazilian cohort and genes encoding for drug-metabolizing enzymes and drug transporters

Background & aim: Genetic variability in drug absorption, distribution, metabolism and excretion (ADME) genes contributes to the high heterogeneity of drug responses. The present study investigated polymorphisms of ADME genes frequencies and compared the findings with populations from other continents, available in the 1000 Genome Project (1 KGP) and the Exome Aggregation Consortium (ExAC) databases. Methodology & results: We conducted a study of 100 patients in Brazil and a total of 2003 SNPs were evaluated by targeted next-generation sequencing in 148 genes, including Phase I enzymes (n = 50), Phase II enzymes (n = 38) and drug transporters (n = 60). Overall, the distribution of minor allele frequency (MAF) suggests that the distribution of 2003 SNPs is similar between Brazilian cohort, 1 KGP and ExAC; however, we found moderate SNP allele-frequency divergence between Brazilian cohort and both 1000 KGP and ExAC. These differences were observed in several relevant genes including CYP3A4, NAT2 and SLCO1B1. Conclusion: We concluded that the Brazilian population needs clinical assessment of drug treatment based on individual genotype rather than ethnicity.

Using Culturally Relevant Pedagogy to Reconsider the Genetics Canon

In this article, we explore culturally relevant pedagogy (CRP) to work toward alleviating persistent underrepresentation in STEM fields of oppressed minorities. We argue that biology instructors can practice agency, or the capacity to act in ways that undermine opportunity gaps that lead to underrepresentation, by developing themselves into culturally relevant pedagogues who are committed to underrepresented minority (URM) students' learning and career success, who demonstrate cultural competence, and who develop a sociopolitical consciousness regarding the culturally laden nature of their discipline. We then explore Gregor Mendel's story to demonstrate the culturally laden nature of the history of science as well as the nature of our current curricular canon. The article concludes with a postulated alternative method to genetics education in a general biology course that reflects the culturally laden nature of our genetics knowledge, as well as our current understanding of inheritance.

Network-based hierarchical population structure analysis for large genomic data sets

Analysis of population structure in natural populations using genetic data is a common practice in ecological and evolutionary studies. With large genomic data sets of populations now appearing more frequently across the taxonomic spectrum, it is becoming increasingly possible to reveal many hierarchical levels of structure, including fine-scale genetic clusters. To analyze these data sets, methods need to be appropriately suited to the challenges of extracting multilevel structure from whole-genome data. Here, we present a network-based approach for constructing population structure representations from genetic data. The use of community-detection algorithms from network theory generates a natural hierarchical perspective on the representation that the method produces. The method is computationally efficient, and it requires relatively few assumptions regarding the biological processes that underlie the data. We show the approach by analyzing population structure in the model plant species Arabidopsis thaliana and in human populations. These examples illustrate how network-based approaches for population structure analysis are well-suited to extracting valuable ecological and evolutionary information in the era of large genomic data sets.

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.

Genetic Ancestry for Sleep Research: Leveraging Health Inequalities to Identify Causal Genetic Variants

Recent evidence has highlighted the health inequalities in sleep behaviors and sleep disorders that adversely affect outcomes in select populations, including African-American and Hispanic-American subjects. Race-related sleep health inequalities are ascribed to differences in multilevel and interlinked health determinants, such as sociodemographic factors, health behaviors, and biology. African-American and Hispanic-American subjects are admixed populations whose genetic inheritance combines two or more ancestral populations originating from different continents. Racial inequalities in admixed populations can be parsed into relevant groups of mediating factors (environmental vs genetic) with the use of measures of genetic ancestry, including the proportion of an individual's genetic makeup that comes from each of the major ancestral continental populations. This review describes sleep health inequalities in African-American and Hispanic-American subjects and considers the potential utility of ancestry studies to exploit these differences to gain insight into the genetic underpinnings of these phenotypes. The inclusion of genetic approaches in future studies of admixed populations will allow greater understanding of the potential biological basis of race-related sleep health inequalities.

Human phylogeography and diversity

Homo sapiens phylogeography begins with the species' origin nearly 200 kya in Africa. First signs of the species outside Africa (in Arabia) are from 125 kya. Earliest dates elsewhere are now 100 kya in China, 45 kya in Australia and southern Europe (maybe even 60 kya in Australia), 32 kya in northeast Siberia, and maybe 20 kya in the Americas. Humans reached arctic regions and oceanic islands last-arctic North America about 5 kya, mid- and eastern Pacific islands about 2-1 kya, and New Zealand about 700 y ago. Initial routes along coasts seem the most likely given abundant and easily harvested shellfish there as indicated by huge ancient oyster shell middens on all continents. Nevertheless, the effect of geographic barriers-mountains and oceans-is clear. The phylogeographic pattern of diasporas from several single origins-northeast Africa to Eurasia, southeast Eurasia to Australia, and northeast Siberia to the Americas-allows the equivalent of a repeat experiment on the relation between geography and phylogenetic and cultural diversity. On all continents, cultural diversity is high in productive low latitudes, presumably because such regions can support populations of sustainable size in a small area, therefore allowing a high density of cultures. Of course, other factors operate. South America has an unusually low density of cultures in its tropical latitudes. A likely factor is the phylogeographic movement of peoples from the Old World bringing novel and hence, lethal diseases to the New World, a foretaste, perhaps, of present day global transport of tropical diseases.

Mathematical Constraints on FST: Biallelic Markers in Arbitrarily Many Populations

[Formula: see text] is one of the most widely used statistics in population genetics. Recent mathematical studies have identified constraints that challenge interpretations of [Formula: see text] as a measure with potential to range from 0 for genetically similar populations to 1 for divergent populations. We generalize results obtained for population pairs to arbitrarily many populations, characterizing the mathematical relationship between [Formula: see text] the frequency M of the more frequent allele at a polymorphic biallelic marker, and the number of subpopulations K We show that for fixed K, [Formula: see text] has a peculiar constraint as a function of M, with a maximum of 1 only if [Formula: see text] for integers i with [Formula: see text] For fixed M, as K grows large, the range of [Formula: see text] becomes the closed or half-open unit interval. For fixed K, however, some [Formula: see text] always exists at which the upper bound on [Formula: see text] lies below [Formula: see text] We use coalescent simulations to show that under weak migration, [Formula: see text] depends strongly on M when K is small, but not when K is large. Finally, examining data on human genetic variation, we use our results to explain the generally smaller [Formula: see text] values between pairs of continents relative to global [Formula: see text] values. We discuss implications for the interpretation and use of [Formula: see text].

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.

Variability among individuals is generated at the gene expression level

Selection acts on individuals, specifically on their differences. To understand adaptation and responses to change therefore requires knowledge of how variation is generated and distributed across traits. Variation occurs on different biological scales, from genetic through physiological to morphological, yet it is unclear which of these carries the most variability. For example, if individual variation is mainly generated by differences in gene expression, variability should decrease progressively from coding genes to morphological traits, whereas if post-translational and epigenetic effects increase variation, the opposite should occur. To test these predictions, we compared levels of variation among individuals in various measures of gene expression, physiology (including activity), and morphology in two abundant and geographically widespread Antarctic molluscs, the clam Laternula elliptica and the limpet Nacella concinna. Direct comparisons among traits as diverse as heat shock protein QPCR assays, whole transcription profiles, respiration rates, burying rate, shell length, and ash-free dry mass were made possible through the novel application of an established metric, the Wentworth Scale. In principle, this approach could be extended to analyses of populations, communities, or even entire ecosystems. We found consistently greater variation in gene expression than morphology, with physiological measures falling in between. This suggests that variability is generated at the gene expression level. These findings have important implications for refining current biological models and predictions of how biodiversity may respond to climate change.

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.

Philosophy of race meets population genetics

In this paper, I respond to four common semantic and metaphysical objections that philosophers of race have launched at scholars who interpret recent human genetic clustering results in population genetics as evidence for biological racial realism. I call these objections 'the discreteness objection', 'the visibility objection', 'the very important objection', and 'the objectively real objection.' After motivating each objection, I show that each one stems from implausible philosophical assumptions about the relevant meaning of 'race' or the nature of biological racial realism. In order to be constructive, I end by offering some advice for how we can productively critique attempts to defend biological racial realism based on recent human genetic clustering results. I also offer a clarification of the relevant human-population genetic research.

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.

Insights into HLA-G Genetics Provided by Worldwide Haplotype Diversity

Human leukocyte antigen G (HLA-G) belongs to the family of non-classical HLA class I genes, located within the major histocompatibility complex (MHC). HLA-G has been the target of most recent research regarding the function of class I non-classical genes. The main features that distinguish HLA-G from classical class I genes are (a) limited protein variability, (b) alternative splicing generating several membrane bound and soluble isoforms, (c) short cytoplasmic tail, (d) modulation of immune response (immune tolerance), and (e) restricted expression to certain tissues. In the present work, we describe the HLA-G gene structure and address the HLA-G variability and haplotype diversity among several populations around the world, considering each of its major segments [promoter, coding, and 3′ untranslated region (UTR)]. For this purpose, we developed a pipeline to reevaluate the 1000Genomes data and recover miscalled or missing genotypes and haplotypes. It became clear that the overall structure of the HLA-G molecule has been maintained during the evolutionary process and that most of the variation sites found in the HLA-G coding region are either coding synonymous or intronic mutations. In addition, only a few frequent and divergent extended haplotypes are found when the promoter, coding, and 3′UTRs are evaluated together. The divergence is particularly evident for the regulatory regions. The population comparisons confirmed that most of the HLA-G variability has originated before human dispersion from Africa and that the allele and haplotype frequencies have probably been shaped by strong selective pressures.

Increased genetic diversity of ADME genes in African Americans compared with their putative ancestral source populations and implications for pharmacogenomics

BACKGROUND

African Americans have been treated as a representative population for African ancestry for many purposes, including pharmacogenomic studies. However, the contribution of European ancestry is expected to result in considerable differences in the genetic architecture of African American individuals compared with an African genome. In particular, the genetic admixture influences the genomic diversity of drug metabolism-related genes, and may cause high heterogeneity of drug responses in admixed populations such as African Americans.

RESULTS

The genomic ancestry information of African-American (ASW) samples was obtained from data of the 1000 Genomes Project, and local ancestral components were also extracted for 32 core genes and 252 extended genes, which are associated with drug absorption, distribution, metabolism, and excretion (ADME) genes. As expected, the global genetic diversity pattern in ASW was determined by the contributions of its putative ancestral source populations, and the whole profiles of ADME genes in ASW are much closer to those in YRI than in CEU. However, we observed much higher diversity in some functionally important ADME genes in ASW than either CEU or YRI, which could be a result of either genetic drift or natural selection, and we identified some signatures of the latter. We analyzed the clinically relevant polymorphic alleles and haplotypes, and found that 28 functional mutations (including 3 missense, 3 splice, and 22 regulator sites) exhibited significantly higher differentiation between the three populations.

CONCLUSIONS

Analysis of the genetic diversity of ADME genes showed differentiation between admixed population and its ancestral source populations. In particular, the different genetic diversity between ASW and YRI indicated that the ethnic differences in pharmacogenomic studies are broadly existed despite that African ancestry is dominant in Africans Americans. This study should advance our understanding of the genetic basis of the drug response heterogeneity between populations, especially in the case of population admixture, and have significant implications for evaluating potential inter-population heterogeneity in drug treatment effects.

Nine things to remember about human genome diversity

Understanding how and why humans are biologically different is indispensable to get oriented in the ever-growing body of genomic data. Here we discuss the evidence based on which we can confidently state that humans are the least genetically variable primate, both when individuals and when populations are compared, and that each individual genome can be regarded as a mosaic of fragments of different origins. Each population is somewhat different from any other population, and there are geographical patterns in that variation. These patterns clearly indicate an African origin for our species, and keep a record of the main demographic changes accompanying the peopling of the whole planet. However, only a minimal fraction of alleles, and a small fraction of combinations of alleles along the chromosome, is restricted to a single geographical region (and even less so to a single population), and diversity between members of the same population is very large. The small genomic differences between populations and the extensive allele sharing across continents explain why historical attempts to identify, once and for good, major biological groups in humans have always failed. Nevertheless, racial categorization is all but gone, especially in clinical studies. We argue that racial labels may not only obscure important differences between patients but also that they have become positively useless now that cheap and reliable methods for genotyping are making it possible to pursue the development of truly personalized medicine.

Disentangling the effects of geographic and ecological isolation on genetic differentiation

Populations can be genetically isolated both by geographic distance and by differences in their ecology or environment that decrease the rate of successful migration. Empirical studies often seek to investigate the relationship between genetic differentiation and some ecological variable(s) while accounting for geographic distance, but common approaches to this problem (such as the partial Mantel test) have a number of drawbacks. In this article, we present a Bayesian method that enables users to quantify the relative contributions of geographic distance and ecological distance to genetic differentiation between sampled populations or individuals. We model the allele frequencies in a set of populations at a set of unlinked loci as spatially correlated Gaussian processes, in which the covariance structure is a decreasing function of both geographic and ecological distance. Parameters of the model are estimated using a Markov chain Monte Carlo algorithm. We call this method Bayesian Estimation of Differentiation in Alleles by Spatial Structure and Local Ecology (BEDASSLE), and have implemented it in a user-friendly format in the statistical platform R. We demonstrate its utility with a simulation study and empirical applications to human and teosinte data sets.

Population structure in a comprehensive genomic data set on human microsatellite variation

Over the past two decades, microsatellite genotypes have provided the data for landmark studies of human population-genetic variation. However, the various microsatellite data sets have been prepared with different procedures and sets of markers, so that it has been difficult to synthesize available data for a comprehensive analysis. Here, we combine eight human population-genetic data sets at the 645 microsatellite loci they share in common, accounting for procedural differences in the production of the different data sets, to assemble a single data set containing 5795 individuals from 267 worldwide populations. We perform a systematic analysis of genetic relatedness, detecting 240 intra-population and 92 inter-population pairs of previously unidentified close relatives and proposing standardized subsets of unrelated individuals for use in future studies. We then augment the human data with a data set of 84 chimpanzees at the 246 loci they share in common with the human samples. Multidimensional scaling and neighbor-joining analyses of these data sets offer new insights into the structure of human populations and enable a comparison of genetic variation patterns in chimpanzees with those in humans. Our combined data sets are the largest of their kind reported to date and provide a resource for use in human population-genetic studies.

A quantitative comparison of the similarity between genes and geography in worldwide human populations

Multivariate statistical techniques such as principal components analysis (PCA) and multidimensional scaling (MDS) have been widely used to summarize the structure of human genetic variation, often in easily visualized two-dimensional maps. Many recent studies have reported similarity between geographic maps of population locations and MDS or PCA maps of genetic variation inferred from single-nucleotide polymorphisms (SNPs). However, this similarity has been evident primarily in a qualitative sense; and, because different multivariate techniques and marker sets have been used in different studies, it has not been possible to formally compare genetic variation datasets in terms of their levels of similarity with geography. In this study, using genome-wide SNP data from 128 populations worldwide, we perform a systematic analysis to quantitatively evaluate the similarity of genes and geography in different geographic regions. For each of a series of regions, we apply a Procrustes analysis approach to find an optimal transformation that maximizes the similarity between PCA maps of genetic variation and geographic maps of population locations. We consider examples in Europe, Sub-Saharan Africa, Asia, East Asia, and Central/South Asia, as well as in a worldwide sample, finding that significant similarity between genes and geography exists in general at different geographic levels. The similarity is highest in our examples for Asia and, once highly distinctive populations have been removed, Sub-Saharan Africa. Our results provide a quantitative assessment of the geographic structure of human genetic variation worldwide, supporting the view that geography plays a strong role in giving rise to human population structure.

The spatial pattern of human genetic variation provides a basis for investigating the history of human migrations. Statistical techniques such as principal components analysis (PCA) and multidimensional scaling (MDS) have been used to summarize spatial patterns of genetic variation, typically by placing individuals on a two-dimensional map in such a way that pairwise Euclidean distances between individuals on the map approximately reflect corresponding genetic relationships. Although similarity between these statistical maps of genetic variation and the geographic maps of sampling locations is often observed, it has not been assessed systematically across different parts of the world. In this study, we combine genome-wide SNP data from more than 100 populations worldwide to perform a formal comparison between genes and geography in different regions. By examining a worldwide sample and samples from Europe, Sub-Saharan Africa, Asia, East Asia, and Central/South Asia, we find that significant similarity between genes and geography exists in general in different geographic regions and at different geographic levels. Surprisingly, the highest similarity is found in Asia, even though the geographic barrier of the Himalaya Mountains has created a discontinuity on the PCA map of genetic variation.

Two complementary perspectives on inter-individual genetic distance

This paper examines population structure through the prism of pairwise genetic distances. Two complementary perspectives, framed as two simple questions, are explored: Q1: What is the probability that a random pair of individuals from the same local population is more genetically dissimilar than a random pair from two distinct populations? Q2: On average, how genetically different are two individuals from the same local population, in comparison with two individuals chosen from any two distinct populations? Models are developed to provide quantitative answers for the two questions, given allele frequencies across any number of markers from two diploid populations. The probability from Q1 is shown to drop to zero with increasing number of genetic markers even for very closely-related populations and rare alleles. The average genetic dissimilarity of two individuals from distinct populations diverges from the average dissimilarity of two individuals from the same population by a percentage dependent on estimates of population differentiation. This perspective also suggests a measure of population distance based on the intuitive notion of pairwise genetic distance, along with a simple method of estimation. Results from recent empirical research on inter-individual genetic distance in human populations are analyzed in the context of the theoretical framework.