Race and genetics

This article deals with racial concepts defined by genetic distance and not craniofacially (based on skull measurements) or by typology (physical type). Races categorized using alternative methods yield different groups, making them non-concordant.

Views on race and genetics vary considerably between and within academic disciplines. Many views are complex, and are distinguished by subtle differences. Often the significance of differences between views is related to the use of race in biomedicine. This article compares the major contemporary views on race.

Summary of contemporary views

Race as a biological construct

• The term 'race' is usually used as a synonym for subspecies by biologists, though there is a degree of confusion over the term and both terms have a variety of meanings. There is no consensus definition for either subspecies or "race" in biology. Some biologists do not accept the concept of classification below the species level whatsoever, arguing that subspecific classifications are not biological units and that they are subjective and arbitrary.
• Taxonomic: "An aggregate of phenotypically similar populations of a species, inhabiting a geographic subdivision of the range of a species, and differing taxonomically from other populations of the species."
• Population: "Races are genetically distinct Mendelian populations. They are neither individuals nor particular genotypes, they consist of individuals who differ genetically among themselves."
• Lineage: "A [race] is a distinct evolutionary lineage within a species. This definition requires that a [race] be genetically differentiated due to barriers to genetic exchange that have persisted for long periods of time; that is, the [race] must have historical continuity in addition to current genetic differentiation."
• The phylogeographic criteria for 'subspecies' were established in the early 1990s.

  members of a subspecies would share a unique, geographic locale, a set of phylogenetically concordant phenotypic characters, and a unique natural history relative to other subdivisions of the species. Although subspecies are not reproductively isolated, they will normally be allopatric and exhibit recognizable phylogenetic partitioning. ... evidence for phylogenetic distinction must normally come from the concordant distributions of multiple, independent genetically based traits.

Differing scopes and goals of race research

Discussions of race are made more complicated because race research has taken place on at least two scales (global and national) and from the point of view of different research aims. Evolutionary scientists are typically interested in humanity as a whole; and taxonomic racial classifications are often either unhelpful to, or refuted by, studies that focus on the question of global human diversity. Policy-makers and applied professions (such as law-enforcement or medicine), however, are typically concerned only with genetic variation at the national or sub-national scale, and find taxonomic racial categories useful.

These distinctions of research aims and scale can be seen by the example of three major research papers published since 2002: Rosenberg et al. (2002), Serre & Pääbo (2004), and Tang et al. (2005). Both Rosenberg et al. and Serre & Pääbo study global genetic variation, but they arrive at different conclusions. Serre & Pääbo attribute their differing conclusions to experimental design. While Rosenberg et al. studied individuals from populations across the globe without respect to geography, Serre & Pääbo sampled individuals with respect to geography. By sampling individuals from major populations on each continent, Rosenberg et al. find evidence for genetic "clusters" (i.e., races). In contrast, Serre & Pääbo find that with respect to geography human genetic variation is continuous and "clinal". The research interest of Rosenberg et al. is medicine (i.e., epidemiology), whereas the research interest of Serre & Pääbo is human evolution. Tang et al. studied genetic variation within the United States with an interest in whether race/ethnicity or geography is of greater importance to epidemiological research. In contrast to Serre & Pääbo, Tang et al. find that race/ethnicity is of greater importance within the United States. Further recent research correlating self-identified race with population genetic structure echoed the conclusions in Tang. Indeed, the contrasting conclusions between global and national levels of analysis were predicted by Serre & Pääbo:

It is worth noting that the colonization history of the United States has resulted in a "sampling" of the human population made up largely of people from western Europe, western Africa, and Southeast Asia. Thus, studies in which individuals from Europe, sub-Saharan Africa, and Southeast Asia are used... might be an adequate description of the major components of the U.S. population.

Genetic variation and human populations

Multi-Locus Allele Clusters In a haploid population, when a single locus is considered (blue), with two alleles, + and - we can see a differential geographical distribution between Population I (70% +) and Population II (30% +). When we want to assign an individual to one of these populations using this single locus we will assign any + to population I because the probability (p) of this allele belonging to Population I is p = 0.7, the probability (q) of incorrectly assigning this allele to Population I is q = 1 − p, or 0.3. This amounts to a Bernoulli trial because the answer to the question "is this the correct population?" is a simple yes or no. This makes the test binomially distributed but with a single trial. But when three loci per individual are taken into account, each with p = 0.7 for a + allele in Population I the average number of + alleles per individual becomes kp = 2.1 (number of trials (k = 3) × probability for each allele (p = 0.7)) and 0.9 (3 × 0.3) + alleles per individual in Population II. This is sometimes referred to as the population trait value. Because alleles are discrete entities we can only assign an individual to a population based on the number of whole + alleles it contains. Therefore we will assign any individual with three or two + alleles to Population I, and any individual with one or fewer + alleles to population II. The binomial distribution with three trials and a probability of 0.7 shows that the probability of an individual from this population having a single + allele is 0.189 and for zero + alleles it is 0.027, which gives a misclassification rate of 0.189 + 0.027 = 0.216, which is a smaller chance of misclassification than for a single allele. Misclassification becomes much smaller as we use more alleles. When more loci are taken into account, each new locus adds an extra independent test to the binomial distribution, decreasing the chance of misclassification. Using modern computer software and the abundance of genetic data now available, it is possible not only to distinguish such correlations for hundreds or even thousands of alleles, which form clusters, it is also possible to assign individuals to given populations with very little chance of error. It should be noted, however, that genes tend to vary clinally, and there are likely to be intermediate populations that reside in the geographical areas between our sample populations (Population III, for example, may lie equidistantly from Population I and Population II). In this case it may well be that Population III may display characteristics of both population I and Population II and have intermediate frequencies for many of the alleles used for classification, causing this population to be more prone to misclassification.

Genetic variation is structured by geographic origin

Human genetic variation can be used to deduce the geographical origins of an individual's recent ancestors, this is possible because alleles that vary geographically often correlate with alleles for other loci that vary geographically (and form clusters), it is possible to measure this correlation, which enables humans to be successfully grouped into populations, the greater the number of loci studied, the more accurately individuals can be correctly assigned to a group. This is possible because individuals from geographically proximate regions share much more recent common ancestry with each other than they do with individuals from geographically disparate regions, with the result that they are likely to be genetically more similar, therefore close geographical proximity strongly correlates with genetic similarity.

Multilocus Allele Clusters

Human population structure can be inferred from multi locus DNA sequence data. In Rosenberg et al. (2002, 2005), individuals from 52 populations were examined at 993 DNA markers. These data was used to partitioned individuals into K = 2, 3, 4, 5 or 6 clusters. In this figure, the average fractional membership of individuals from each population is represented by horizontal bars partitioned into K colored segments. 2 cluster analysis separated Africa and Eurasia from East Asia, Oceania, and America, 3 clusters separated Africa and Eurasia, 4 clusters separated America, 5 clusters separated Oceania (green), and 6 clusters subdivided native Americans.

Since the 1980s it has been known that human genetic variation is low relative to other species, this is usually attributed to the recent origins of our species, and tends to support the recent single-origin hypothesis (or Out of Africa). It has also been claimed that most of this small variation is distributed at the individual and local level (about 90-94%), with the remaining 6-10% distributed at the continental (or racial) level. This observation has been used to argue that racial classifications are not possible when within group variation so greatly exceeds between group variation.

However, A. W. F. Edwards claimed in 2003 that this conclusion is unwarranted because it assumes that all loci are independent, Edwards argues that this is not the case

The genes at a single locus are hardly informative about the population to which their bearer belongs...Each additional locus contributes equally to the within-population and between-population sums of squares, whose proportions therefore remain unchanged but, at the same time, it contributes information about classification which is cumulative over loci because their gene frequencies are correlated...it will be possible to identify the two clusters with a risk of misclassification which tends to zero as the number of loci increases.

Edwards states that genes should not be taken into account on an individual basis, just as a single characteristic (such as skin colour or eye colour) cannot be used to determine the geographic origin of a person's recent ancestors, so the same for the allelic frequency of an individual locus. Conversely, just as physical features tend to correlate (for example blue eye colour correlates with pale skin colour, that is skin colour and eye colour), and are not independent, so different alleles for several loci tend to correlate and are not independent. This is the basis of multi-locus allele clustering.

It has been argued that the calculation of within group and between group diversity has violated certain assumptions regarding human genetic variation. Calculation of this variation is known as F_ST and Long and Kittles (2003) have questioned the validity of this reproducible statistic. The first problem is that effective population size is assumed to be equal in the calculation of F_ST, if population sizes vary, then allele relatedness among alleles will also vary. The second problem is that F_ST calculation has assumed that each population is evolutionarily independent. Calculation of F_ST can therefore only be made for the set of populations being observed, and generalisations from specific data sets cannot be applied to the species as a whole.

Long and Kittles tested four models for determining F_ST and concluded that the model used most often for estimating this statistic is the simplest and worst fitting. Their best fit model was still a poor fit for the observed genetic variation, and calculation of F_ST for this model can only be made on a population by population basis. They conclude that African populations have the highest level of genetic diversity, with diversity much reduced in populations outside of Africa. They postulate that if an extra-terrestrial alien life form killed the entire human species, but kept a single population which it preserved, the choice of population to keep would greatly effect the level of diversity represented. If an African population were selected then no diversity would be lost, whereas nearly a third of genetic diversity would be lost if a Papuan New Guinea population were chosen. Indeed within population genetic diversity in African populations has been shown to be greater than between population genetic diversity for Asians and Europeans. They conclude that their findings are consistent with the American Association of Physical Anthropologists 1996 statement on race

that all human populations derive from a common ancestral group, that there is great genetic diversity within all human populations, and that the geographic pattern of variation is complex and presents no major discontinuity.

They also state that none of the race concepts they discuss are compatible with their results.

Distribution of variation

Two random humans are expected to differ at approximately 1 in 1000 nucleotides, whereas two random chimpanzees differ at 1 in 500 nucleotide pairs. Therefore with a genome of approximate 3 billion nucleotides, on average two humans differ at approximately 3 million nucleotides. Most of these single nucleotide polymorphisms (SNPs) are neutral, but some are functional and influence the phenotypic differences between humans. It is estimated that about 10 million SNPs exist in human populations, where the rarer SNP allele has a frequency of at least 1% (see International HapMap Project).

In the field of population genetics, it is believed that the distribution of neutral polymorphisms among contemporary humans reflects human demographic history. It is believed that humans passed through a population bottleneck before a rapid expansion coinciding with migrations out of Africa leading to an African-Eurasian divergence around 100,000 years ago (ca. 5,000 generations), followed by a European-Asian divergence about 40,000 years ago (ca. 2,000 generations). Richard G. Klein, Nicholas Wade and Spencer Wells, have postulated that modern humans did not leave Africa and successfully colonize the rest of the world until as recently as 50,000 years B.P., pushing back the dates for subsequent population splits as well.

The rapid expansion of a previously small population has two important effects on the distribution of genetic variation. First, the so-called founder effect occurs when founder populations bring only a subset of the genetic variation from their ancestral population. Second, as founders become more geographically separated, the probability that two individuals from different founder populations will mate becomes smaller. The effect of this assortative mating is to reduce gene flow between geographical groups, and to increase the genetic distance between groups. The expansion of humans from Africa affected the distribution of genetic variation in two other ways. First, smaller (founder) populations experience greater genetic drift because of increased fluctuations in neutral polymorphisms. Second, new polymorphisms that arose in one group were less likely to be transmitted to other groups as gene flow was restricted.

Many other geographic, climatic, and historical factors have contributed to the patterns of human genetic variation seen in the world today. For example, population processes associated with colonization, periods of geographic isolation, socially reinforced endogamy, and natural selection all have affected allele frequencies in certain populations (Jorde et al. 2000b; Bamshad and Wooding 2003). In general, however, the recency of our common ancestry and continual gene flow among human groups have limited genetic differentiation in our species.

Substructure in the human population

File:Admixture triangle plot.png

Triangle plot shows average admixture of five North American ethnic groups. Individuals that self-identify with each group can be found at many locations on the map, but on average groups tend to cluster differently.

New data on human genetic variation has reignited the debate surrounding race. Most of the controversy surrounds the question of how to interpret these new data, and whether conclusions based on existing data are sound. Some researchers endorse the view that continental groups do not constitute different subspecies. However, some still debate whether evolutionary lineages should rightly be called "races". These questions are particularly pressing for biomedicine, where self-described race is often used as an indicator of ancestry (see race in biomedicine below).

Although the genetic differences among human groups are relatively small, these differences in certain genes such as duffy, ABCC11, SLC24A5, called ancestry-informative markers (AIMs) nevertheless can be used to reliably situate many individuals within broad, geographically based groupings or self-identified race. For example, computer analyses of hundreds of polymorphic loci sampled in globally distributed populations have revealed the existence of genetic clustering that roughly is associated with groups that historically have occupied large continental and subcontinental regions (Rosenberg et al. 2002; Bamshad et al. 2003).

Some commentators have argued that these patterns of variation provide a biological justification for the use of traditional racial categories. They argue that the continental clusterings correspond roughly with the division of human beings into sub-Saharan Africans; Europeans, North Africans, Western Asians, and South Asians; Eastern Asians; Polynesians and other inhabitants of Oceania; and Native Americans (Risch et al. 2002). Other observers disagree, saying that the same data undercut traditional notions of racial groups (King and Motulsky 2002; Calafell 2003; Tishkoff and Kidd 2004). They point out, for example, that major populations considered races or subgroups within races do not necessarily form their own clusters. Thus, samples taken from India and Pakistan affiliate with Europeans or eastern Asians rather than separating into a distinct cluster.

Furthermore, because human genetic variation is clinal, many individuals affiliate with two or more continental groups. Thus, the genetically based "biogeographical ancestry" assigned to any given person generally will be broadly distributed and will be accompanied by sizable uncertainties (Pfaff et al. 2004).

In many parts of the world, groups have mixed in such a way that many individuals have relatively recent ancestors from widely separated regions. Although genetic analyses of large numbers of loci can produce estimates of the percentage of a person's ancestors coming from various continental populations (Shriver et al. 2003; Bamshad et al. 2004), these estimates may assume a false distinctiveness of the parental populations, since human groups have exchanged mates from local to continental scales throughout history (Cavalli-Sforza et al. 1994; Hoerder 2002). Even with large numbers of markers, information for estimating admixture proportions of individuals or groups is limited, and estimates typically will have wide CIs (Pfaff et al. 2004).

Biogeographic Ancestry

Anthropology

Biogeographic ancestry is an anthropological concept of lineage that looks at kinship and descent based on biogeography, a combination of biology and geography.

The study of ancestry based mitochondrial DNA, ALU polymorphisms, and other genetic markers has significant implications in law enforcement, medicine, archaeology, and anthropology.

Some scientists believe genetic ancestry can help to focus the search for genes that affect individuals' risks of diseases, as well as prevalence and distribution of disease. Others advocate using it as a means of profiling persons for the purposes of law enforcement. In many of the cases, the term is used synonymously with race and can be used to partially determine the genetic admixture of an individual. However, each individual human may express the same gene differently than another, and each individual is partially a unique mix of genes unlike any other.

The field is sometimes controversial because of the ethical issues raised by DNA profiling and race theories that can be abused for political and social ends. Some critics argue that biogeographic ancestry is simply a means of reification for a social construct. The number of categories and the criteria used to group humans is also very arbitrary and often based on customs or traditions. The results are also only probable, with many individual exceptions.

Opponents of racial groupings argue that a distinct difference is only one of the two conditions for racial classification; the second condition is a lack of significant gene flow between populations. Humans are classified as monotypic, because phenotypes gradually fade into one another in many parts of the world. Although there has historically been little or no gene flow between some human populations such as the aboriginal Australians and black Africans, they argue, one cannot assume there has been little interracial gene flow, as the interbreeding of locally adjacent populations may produce common traits. Some researchers report enough such gene flow has occurred that the most recent common ancestor of all humans alive today may have lived as recently as 3,500 years ago, the work also estimated that everyone alive 7400 years ago was either an ancestor of all humans alive today, or of nobody currently living, before this time all humanity alive today share exactly the same ancestors. although critics say this is not necessarily significant gene flow.

Genetics

An alternative to the use of racial or ethnic categories is to categorize individuals in terms of ancestry. Ancestry may be defined geographically (e.g., Asian, sub-Saharan African, or northern European), geopolitically (e.g., Vietnamese, Zambian, or Norwegian), or culturally (e.g., Brahmin, Lemba, or Apache). The definition of ancestry may recognize a single predominant source or multiple sources. Ancestry can be ascribed to an individual by an observer, as was the case with the U.S. census prior to 1960; it can be identified by an individual from a list of possibilities or with use of terms drawn from that person's experience; or it can be calculated from genetic data by use of loci with allele frequencies that differ geographically, as described above. At least among those individuals who participate in biomedical research, genetic estimates of biogeographical ancestry generally agree with self-assessed ancestry (Tang et al. 2005), but in an unknown percentage of cases, they do not (Brodwin 2002; Kaplan 2003).

Genetic data can be used to infer population structure and assign individuals to groups that often correspond with their self-identified geographical ancestry. The inference of population structure from multilocus genotyping depends on the selection of a large number of informative genetic markers. These studies usually find that groups of humans living on the same continent are more similar to one another than to groups living on different continents. Many such studies are criticized for assigning group identity a priori. However, even if group identity is stripped and group identity assigned a posteriori using only genetic data, population structure can still be inferred. For example, using 993 markers, Rosenberg et al. (2005) were able to assign 1,048 individuals from 52 populations around the globe to one of six genetic clusters, which correspond to major geographic regions.

However, in analyses that assign individuals to group it becomes less apparent that self-described racial groups are reliable indicators of ancestry. One cause of the reduced power of the assignment of individuals to groups is admixture. Some racial or ethnic groups, especially american Hispanic groups, do not have homogenous ancestry. For example, self-described African Americans tend to have a mix of West African and European ancestry. Shriver et al. (2003) found that on average African Americans have ~80% African ancestry. Also, for example, ~30% of students who self identified as white in a Northeastern US college have less than 90% European ancestry.

Nevertheless, recent research indicates that self-described race is a near-perfect indicator of an individual's genetic profile, at least in the United States. Using 326 genetic markers, Tang et al. (2005) identified 4 genetic clusters among 3,636 individuals sampled from 15 locations in the United States, and were able to correctly assign individuals to groups that correspond with their self-described race (white, African American, East Asian, or Hispanic) for all but 5 individuals (an error rate of 0.14%). They conclude that ancient ancestry, which correlates tightly with self-described race and not current residence, is the major determinant of genetic structure in the U.S. population.

Geneticist Neil Risch from Stanford University and 3 other scientists commented on this in their study: "More recently, a survey of 3,899 SNPs in 313 genes based on US populations (Caucasians, African-Americans, Asians and Hispanics) once again provided distinct and non-overlapping clustering of the Caucasian, African-American and Asian samples...The results confirmed the integrity of the self-described ancestry of these individuals" Populations in their research "clustered into the five continental groups"

Genetic techniques that distinguish ancestry between continents can also be used to describe ancestry within continents. However, the study of intra-continental ancestry may require a greater number of informative markers. Populations from neighboring geographic regions typically share more recent common ancestors. As a result, allele frequencies will be correlated between these groups. This phenomenon is often seen as a cline of allele frequencies. The existence of allelic clines has been offered as evidence that individuals cannot be allocated into genetic clusters (Kittles & Weiss 2003). However, others argue that low levels of differentiation between groups merely make the assignment to groups more difficult, not impossible (Bamshad et al. 2004).

Also, clines and clusters, seemingly discordant perspectives on human genetic diversity may be reconciled. A recent comprehensive study has stated:

At the same time, we find that human genetic diversity consists not only of clines, but also of clusters, which STRUCTURE observes to be repeatable and robust.

Despite its seemingly objective nature, ancestry also has limitations as a way of categorizing people (Elliott and Brodwin 2002). When asked about the ancestry of their parents and grandparents, many people cannot provide accurate answers. In one series of focus groups in the state of Georgia, 40% of ∼100 respondents said they did not know one or more of their four grandparents well enough to be certain how that person(s) would identify racially (Condit et al. 2003). Misattributed paternity or adoption can separate biogeographical ancestry from socially defined ancestry. Furthermore, the exponentially increasing number of our ancestors makes ancestry a quantitative rather than qualitative trait—5 centuries (or 20 generations) ago, each person had a maximum of >1 million ancestors (Ohno 1996). To complicate matters further, recent analyses suggest that everyone living today has exactly the same set of genealogical ancestors who lived as recently as a few thousand years in the past, although we have received our genetic inheritance in different proportions from those ancestors (Rohde et al. 2004).

The delicacy of this definition has left the issue much in debate, especially among physical anthropologists, for if clines lead to large areas of near-homogeneity, such as Kenya, Sweden and Japan, then the people in these areas seem marked off by delimiters resembling nothing so much as the traditional physiological touchstones of "race". Currently, the question of whether human genetic variation is better described as clinal (i.e. no races) or cladistic (i.e. races are real) is largely fading.

The problem arises of distinguishing black Africans as a racial group; it doesn't work because it is a paraphyletic classification. In other words, under a phylogenetic classification, considering black Africans as a single racial group would require one to include every living person on Earth within that single African "race", because the genetic variation of the rest of the world represents essentially a single subtree within that of Africa. Also, it has long been known that groups such as the Khoisan were as different from other sub-Saharan groups as are Europeans and Asians (though even with the Khoisan the distinction is no longer so clearcut, as a large amount of intermarriage with both Europeans and Bantu-language speakers has occurred over the last three centuries).

Rachel Caspari (2003) argued that clades are by definition monophyletic groups (a taxon that includes all descendants of a given ancestor); since races are not monophyletic, they cannot be clades.

In the end, the terms "race," "ethnicity," and "ancestry" all describe just a small part of the complex web of biological and social connections that link individuals and groups to each other.

Genetics and the three main races

Numerous studies have claimed to have confirmed the existence of three main races of traditional anthropology (negroids, caucasoids, and mongoloids) in addition to other smaller races, the most extensive being an analysis by Aurthur Jensen:

Jensen's 1998 racial classification based on a varimax rotated Principal component analysis of Nei & Roychoudhury's 1993 genetic data. Jensen asserts: The population clusters are defined by their largest loadings (shown in boldface type) on one of the components. A population's proximity to the central tendency of a cluster is related to the size of its loading in that cluster. Note that some of these groups have major or minor loadings on different components, which represent not discrete categories, but central tendencies. Although the names Jensen assigned to each cluster are arbitrary, Jensen asserts that PC analysis is a wholly objective mathematical procedure. It requires no judgements on anyone's part and yields identical results for everyone who does the calculations correctly.

Population	Mongoloids	Caucasoids	South Asians & Pacific Islanders	Negroids	North & South Amerindindians & Eskimos	aboriginal Australians & Papuan New Guineans
Pygmy				651
Nigerian				734
Bantu				747
San (Bushmen)				465
Lapp		500
Finn		988
German		978
English		948
Italian		989
Iranian		635
Northern Indian		704
Japanese	916		214
Korean	959		229
Tibetan	855
Mongolian	842		357
Southern Chinese	331		771
Thai			814
Filipino			782
Indonesian			749
Polynesian			526			284
Micronesian			521			328
Australian (aborigines)						706
Papuan (New Guineans)						742
North Amerindian					804
South Amerindian					563
Eskimo					726

Noah A. Rosenberg and Jonathan K. Pritchard, geneticists from the laboratory of Marcus W. Feldman of Stanford University, assayed 377 polymorphisms in more than 1,000 people from 52 ethnic groups in Africa, Asia, Europe and the Americas. They looked at the varying frequencies of these polymorphisms and concluded

without using prior information about the origins of individuals, we identified six main genetic clusters, five of which correspond to major geographic regions, and subclusters that often correspond to individual populations.

we found that individuals could be partitioned into six main genetic clusters, five of which corresponded to Africa, Europe and the part of Asia south and west of the Himalayas, East Asia, Oceania, and the Americas

Dr. Neil Risch of Stanford University has shown that self identified ethnic identity correlates with genetic structure, this is different to the previous study in that groups were pre-sorted by self-identification.

Subjects identified themselves as belonging to one of four major racial/ethnic groups (white, African American, East Asian, and Hispanic) and were recruited from 15 different geographic locales within the United States and Taiwan. Genetic cluster analysis of the microsatellite markers produced four major clusters, which showed near-perfect correspondence with the four self-reported race/ethnicity categories.

See also

• Human mitochondrial DNA haplogroups
• Genetic history of Europe

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• Smedley, A. and Smedley, B. D. (2005). "Race as Biology Is Fiction, Racism as a Social Problem Is Real: Anthropological and Historical Perspectives on the Social Construction of Race" (PDF). American Psychologist. 60 (1): 16–26. doi:10.1037/0003-066x.60.1.16. {{cite journal}}: Unknown parameter |month= ignored (help)CS1 maint: multiple names: authors list (link)
• Tang, Hua., Tom Quertermous, Beatriz Rodriguez, Sharon L. R. Kardia, Xiaofeng Zhu, Andrew Brown,7 James S. Pankow,8 Michael A. Province,9 Steven C. Hunt, Eric Boerwinkle, Nicholas J. Schork, and Neil J. Risch (2005) Genetic Structure, Self-Identified Race/Ethnicity, and Confounding in Case-Control Association Studies Am. J. Hum. Genet. 76:268–275.
• Templeton, A.R. (1998). Human races: A genetic and evolutionary perspective. Am. Anthropol. 100, 632–650.Partial access to article. Retrieved 01 January 2007.
• Travassos, C. and Williams, D. R. (2004). The concept and measurement of race and their relationship to public health: a review focused on Brazil and the United States: Cadernos de Saúde Pública v.20 n.3. doi:10.1590/S0102-311X2004000300003
• Nature Genetics (2004). "Implications of biogeography of human populations for 'race' and medicine". 36: S21–S27. {{cite journal}}: Cite journal requires |journal= (help)

External links

• Minorities, Race, and Genomics via Human Genome Project information.