As soon as fundamental principles of genetic inheritance were clearly established in the early twentieth century, anthropologists began using these principles and new empirical data to illuminate long-standing problems of human variation and primate phylogeny. Initially focusing on human blood characteristics, geneticists quantified regional differences in ABO genotype, and tried to correlate these differences with more traditional osteometric assessments of variation. Anthropologists were especially interested in alleles like the sickling trait, which had adaptive significance. When blood samples became available from other primates, in midcentury, it became possible to construct phylogenetic trees based on genetic data, and to compare these results with the fossil record. After World War II, field expeditions were organized by anthropological geneticists to collect far-flung samples of human genetic material, along with new cultural and linguistic data, in the hope of finding correlations, thereby detecting evolutionary trends and reconstructing human migration. With the addition of ancient DNA techniques to the anthropological repertoire in the 1980s, all four fields of anthropology – cultural anthropology, archaeology, linguistics, and biological anthropology – became intimately involved in genetics research, both individually and in cross-disciplinary research. The immediate research agenda for anthropological genetics includes (1) human origins; (2) prehistoric migration; (3) coevolution of biology, language, and culture; and (4) variation and adaptation to modern environments.
The fields of anthropology and genetics maintained a tense coexistence throughout the twentieth century, sometimes complementary to one another (as in the decades immediately following World War II) and sometimes antithetical to one another (as in the eugenics movement of the 1920s and the genetic essentialism of the 1990s). The reason is that the self-interest of geneticists is sometimes perceived to lie in the assumption that genetics determines the most important aspects of a person’s life or identity (Nelkin and Lindee, 1995), which would run counter to the anthropological focus on culture. Normative human genetics after World War II, led by Theodosius Dobzhansky, James V. Neel, and Luca Cavalli- Sforza, tended rather to emphasize the complementarity of the two fields. Here, human genetics would form a foundation for the study of human microevolution, and its primary data would be biochemical ‘markers’ of ancestry, or intergenerational continuity. Within anthropology, then, normative genetic research came to incorporate four kinds of questions: (1) patterns of human variation; (2) the phylogenetic relationships among humans and other primate species; (3) the migration and adaptation of human populations, or microevolution; and (4) the relationships among biological variation and other kinds of human variation, especially in language and culture. Additionally, there are areas of overlap between genetics and humanistic anthropology, including medical anthropology (Taussig, 2009), economic anthropology (Pálsson, 2007), bioethics (Brodwin, 2005), and political ecology (Stone, 2010).
When laboratory techniques for studying Mendelian traits first became available, international anthropology had just emerged from a controversy over racial typology during which Franz Boas, recognized by many as the founding father of American anthropology, had repudiated to the satisfaction of most anthropologists the racial theories to explain civilization that had been popular in the late nineteenth century. Originally trained as a physicist, Boas presented data and arguments between 1910 and 1913 showing that ‘race,’ ‘language,’ and ‘culture’ were three independent phenomena that, he asserted, should all be studied by anthropologists, but using different kinds of theories and techniques.
Shortly after World War I, the earliest population genetic studies of human blood groups seemed to undermine the ideas about race that physical anthropology had traditionally employed, although it would be several decades before the meaning of this discordance became clarified (Marks, 2012). After World War II, as human genetics became increasingly redirected toward real genetically based medical pathologies (such as sickle-cell anemia), rather than imaginary genetically based social pathologies (such as feeblemindedness), it became clear that the simple rules of Mendelian inheritance applied only to the inheritance of biochemical variants and pathological conditions resulting from the breakdown of specific genes (the repository for medical genetic conditions is Online Mendelian Inheritance in Man, https://www.ncbi.nlm.nih.gov/omim). The interesting physical attributes of human variation (such as height, complexion, facial form, hair form, and body build), however, are all the result of more complex hereditary and developmental physiologies, involving the coordinated activities of several genes and regulation of their products, in specific environmental, genetic, and cultural contexts.
For anthropologists, the major theoretical model that emerged to describe human genetic variation in this period was the cline, the gradual geographic change in the frequency of an allele, which also served to undermine further the idea of racial typology. Both physical form and genetic variation seemed to vary across the human species in a continuous, quantitative fashion.
Some patterns that emerged from the analysis of clines conformed to more general biological principles pertaining to other animals. It was found, for example, that Gloger’s, Bergmann’s, and Allen’s Rules for variation within a mammalian species (pertaining to pigmentation, mass, and limb length, respectively) were also crudely valid for the human species, reflecting adaptation to the different latitudes, climates, and environments inhabited by local human populations. Since these traits were so clearly adaptive, it was suspected that other patterned traits, with definite clines, likewise reflected genetic adaptation to local conditions. Alternatively, they might be the track of large-scale migrations of ancient peoples.
The most forceful new example of human genetic adaptation was presented by Livingstone (1958) with his study of sickle-cell disease, especially as it existed in Africa. In addition to presenting convincing evidence of several types to prove that sickled blood cells were a long-term genetic response to the presence of malaria, Livingstone’s work illustrated several other lessons in anthropological genetics. First of all, it was the heterozygote (a person with two different alleles for a specific gene) or carrier of hemoglobin S (HbS) who had the adaptive advantage, not the HbS homozygote (possessing two identical alleles for a specific gene), who suffered from sickle-cell anemia. The second lesson was that an apparent ‘disease,’ sickle-cell anemia, was on closer inspection actually a successful genetic solution to a largely human-made environmental problem, namely, malaria – stimulated by the widespread presence of mosquitoes, which in turn were attracted by large areas of standing water that were promoted by early agricultural practices. The story does not end in the past, however, as medical anthropology and history are now illuminating complementary anthropological aspects of sickle-cell anemia (Wailoo and Pemberton, 2006; Fullwiley, 2011).
Another highly visible connection between genetic variability, culture, and environment concerns the ability of human adults to digest milk and milk products from dairy animals, an ability that seems to be under genetic control. When mapped geographically, the alleles responsible for adult lactose tolerance in human populations seem to be correlated, in the Old World, with the present and past locations of pastoral peoples (Durham, 1991). Lactose tolerance has arisen in parallel in several different areas, and the most common mutation in Europeans probably spread with the descendants of early dairy farmers (Ingram et al., 2009).
Many correlations have been found between pathogenic diseases and genetic variations. None, however, has been established as firmly as the relationship between malaria and sickle-cell anemia, and other related blood diseases. Different patterns of genetic variation among populations are explained as accidents of demographic history, or founder effects, rather than as adaptive responses of the gene pool. The most famous examples here are genetic diseases that are rare elsewhere but have attained an anomalously high frequency in a particular population, for example, porphyria variegata among the Boers of South Africa and Ellis–van Creveld syndrome among the Pennsylvania Amish – both of which have elevated frequencies because a single seventeenth-century immigrant was both a carrier of the genetic disease and an ancestor of the modern populations. In the absence of plausible and reliable physiology (as in the case of sickle-cell or thalassemia) or plausible and reliable historical records, most other diseases associated with genetic variants show more ambiguous patterns.
More generally, understanding the role that genetic variation may play in health care involves the analysis of risk factors and consequent probabilities (Terwilliger and Göring, 2000). Nevertheless, the presumption of a genetic basis for health disparities carries strong political implications and can hardly be taken at face value (Fullerton et al., 2012) Moreover, the saturation of medical genomics with modern capitalism may compromise the reliability of the scientific information it produces. BiDil, promoted as a cardiac medicine specifically for black patients, was actually supported by no valid evidence that it worked differently or better in blacks than in whites. Nevertheless, racializing the drug extended its patent protection. And far from being a public health service, BiDil’s manufacturers charged their black patients far more than they needed to pay for it, since the drug itself was simply a mixture of two other generic drugs (Kahn, 2008).
With increased funding for science in the United States after World War II, and increased access to field sites, anthropologists began to investigate isolated, small-scale human populations with renewed vigor, often including a biological anthropologist in the research team. The most visible of these joint enterprises was probably the comprehensive study of the Yanomamö, who live in the upper drainage of the Orinoco River in Venezuela and Brazil. In the 1960s, James Neel of the University of Michigan organized a comprehensive multidisciplinary series of field expeditions that investigated the environment, ecology, biology, culture, and social organization of these then little-known people. After a series of books and articles was published over the next two decades, the Yanomamö became not the least known, but one of the best-known tribal societies in the world.
For the genetic part of the research, Neel and Ward (1970) examined six blood systems relatively well known at the time (MNS, Rh, Kidd, Duffy, Diego, and haptoglobin) among 7 villages of Yanomamö, 7 villages of nearby Makiritare, and 12 other tribes of Central and South America. After comparing the different groups, the authors concluded that human evolution might have been proceeding at a pace ‘100 times more rapid’ than previously thought, if these smallscale societies could be taken as analogs of earlier Pleistocene or Paleolithic human peoples.
In the same period, other biological anthropologists were proceeding with similar investigations elsewhere in the world. Working in the Solomon Islands from 1966 to 1973, Jonathan Friedlaender simultaneously undertook studies of demography, anthropometry, genetics, and social structure, seeking to integrate his results into some general conclusions that cut across these traditional fields of research. Like Neel and Ward, he emphasized the genetics of blood systems, in this case ABO, MNS, Rh, Kell, and Duffy. From this kind of data, Friedlaender calculated phenotype frequency and then allele frequency by techniques described in his major ethnographic work, Patterns of Human Variation (Friedlaender, 1975). His most general conclusion, combining results from anthropometry, dermatoglyphics (the study of fingerprints), genetics, and demography, was simply that Bougainville communities tended to exhibit high biological variability within the group, but low variability among the groups, and that some traits, such as skin color, eye color, and hair form, were ‘monotonous’ on the island, while dermatoglyphic characteristics and some blood system alleles were discontinuous from village to village.
Those expecting that these early studies would provide fundamental insights into the mechanisms of human evolution were soon disappointed. Summarizing a widely shared consensus of opinion in 1974, Henry Harpending concluded that (1974: p. 229)
… studies of the genetic structure of small populations have made particular and incidental contributions to formal genetics, to regional history and prehistory, to epidemiology, and to several other fields to which they are peripheral, but . they have not advanced our understanding of human evolution in a global sense. The sample sizes available have been too small to allow reliable inferences about natural selection; the extensive occurrence of what is presumably local random genetic drift has little or no consequence for evolution over long time periods over large areas; and the presumed selective agents in the various environments of these peoples differ greatly so that few of the generalizations which have been put forward hold for many groups.
Evolution of Primates
Early in the twentieth century, it was appreciated that the relations of primate blood appeared to replicate the relations of primate bodies; that is to say, animals who appeared more similar physically tended to have more similar biochemical properties discernible in their blood. Further, the blood of humans was especially similar to the blood of apes; indeed, by the 1920s, human blood was known to be even more similar to chimpanzee blood than horse blood was to donkey blood.
In the 1960s, Allan Wilson and Vincent Sarich (1967) showed that the biochemical variation distinguishable immunologically in the blood tended to track the time since the species being examined diverged from one another, rather than their degree of adaptive physical difference from one another. In the ensuing decades, this generalization has held up remarkably well over diverse kinds of genetic comparisons. Consequently, genetics tends to show how similar humans are to chimpanzees, not how different we are. The reason is that we do not know how to build a four-dimensional body (an organism) from a one-dimensional set of instructions for it (the DNA). Absenting that information, detectable DNA changes are largely uncorrelated with the adaptive physical variations that characterize the ‘major features’ of the history of life. Consequently, we know rather a lot about how similar genetically we are to chimpanzees, but almost nothing about the genetic basis of bipedality, language, evaporative heat loss, cooperative breeding, or any of the other significant ways in which we differ strikingly from the apes.
Sarich and Wilson (1967) used the primate molecular data in the 1960s to demonstrate convincingly that Ramapithecus, considered to be on a human line 14 million years ago, on the basis of teeth and jaw fragments, was about three times older than the human line itself was, and therefore could not be on the human line. Morris Goodman invoked the genetic similarity of humans and chimpanzees to argue for classifying them together as members of the genus Homo (Wildman et al., 2003). This would involve privileging the genetic relationships (in which chimpanzees and humans are extremely similar) over anatomical, behavioral, cognitive, and ecological relationships (in which they are considerably less similar).
Modern studies of primate genetics incorporate inferences about not only systematics and divergence times (Steiper and Young, 2006), but also demography, paternity, conservation, and microevolution.
The production of genomic data climbed so precipitously beginning in the 1980s that a new specialty, bio-informatics, had to be developed in order to detect patterns in genomic data and to make quantitative, statistical sense out of them.
The most fundamental tools used in genomic comparisons involve (1) the acquisition, isolation, manipulation, and amplification of genetic sequences to be studied; (2) the qualitative and quantitative assessment of patterns of similarity among the samples, for example, inferring the kinds and numbers of mutations needed to transform one DNA sequence into another; and (3) an explanation for the patterns in the history of the organisms.
The study of the human genome has revealed that traditionally defined genes (containing the DNA code for a specific protein) constitute only a small percentage of the total DNA in a human cell. About 90% of the human genome is intergenic, that is to say, lying between genes and thus not classically functional. Moreover, most of a gene itself does not actually code for a protein; it may be transcribed into RNA without being translated into protein. Two obvious conclusions are (1) our classical ideas about the functions of DNA were too narrow and (2) there are some interesting structural features of noncoding DNA. Some noncoding DNA is localized, and consists of simple sequences repeated side-by-side millions of times. Other repetitive DNA is interspersed among the genes, and consists of millions of sequences, each one hundreds or even thousands of bases long, and shot through the genome in apparently random places. This redundancy is characteristic of the genome. Genes themselves are commonly found in clusters, the ancient products of a ‘rubber-stamp’ process of gene duplication, followed by the mutation-mediated inactivation or alteration of the duplicate gene. Other sites in the genome differ from person to person in the number of segments of a short repetitive motif that may be present. These polymorphisms are known as variable numbers of tandem repeats (VNTRs) and are particularly valuable in forensic contexts, where a match of several highly variable sites can provide a statistical basis for identifying the person that a particular DNA sample came from.
We can generally measure the intensity of selection on a particular genomic region by its rate of change. Noncoding sequences invariably are more different across species than coding sequences are. The simple reason is that coding sequences are expressed as phenotypes, and have evolved by natural selection to produce a functioning body. Any random change within them (mutation) is far more likely to make that body run worse than better. Consequently, mutations that occur in coding sequences are far more likely than mutations in unexpressed DNA sequences to be ‘weeded out’ by selection. Establishing the background extent of genetic difference between two species helps to identify regions that are evolving ‘too slowly’ and may thus be under selective constraints. More rarely, a genomic site may be of interest for evolving ‘too fast’ and thus possibly be related to the adaptive differences that arose between the species.
As soon as chromosomes could be observed directly through microscopes, attempts were made to stain them chemically so that bands would appear that might show differences in structure. Initially, the purpose was to discriminate among the different chromosomes of the human karyotype, or suite of chromosomes (22 pairs of autosomes, and a pair of sex chromosomes), so they could be counted and identified. During the course of this research, it also became apparent that patterns of stains on a particular chromosome might vary from one individual to another within a population. In addition, when it was noted that certain patterns of staining were characteristic of particular species, yet another method became available for evaluating the phylogenetic relationships among apes and humans. Although several correlations have been established between the observable banding pattern of chromosomes and the DNA sequences they contain, the staining difference presumably results from a higher-order property of DNA (i.e., its three-dimensional folding).
The age of biotechnology was made possible by the development of several laboratory methods. The first was the discovery that biomolecules migrate in an electric field, and can be separated from one another and isolated; this is known as electrophoresis. The phosphates in DNA give it a negative charge. Embedded in a semisolid matrix, then, DNA moves toward a positive pole, its shortest fragments moving fastest. Being able to separate DNA molecules from one another forms the basis of all subsequent DNA research.
The second technical breakthrough involved the isolation and purification of naturally occurring enzymes that modify DNA, and can be used to manipulate it in predictable ways. One such class of enzymes is endonucleases, which cut DNA at specific sites (such as GAATTC for the enzyme called EcoR1). Many such enzymes became available in the 1980s, permitting the construction of ‘maps’ of the DNA where different enzyme cut sites are located.
Another class of enzymes permitted the development of the third technical breakthrough, the polymerase chain reaction. Here, the enzyme is a DNA polymerase, which adds the appropriate complementary nucleotide to produce a stable, double helix from a single-stranded DNA template. By alternating cycles of heating (to dissociate the double helix into single strands of DNA) and replication (using the polymerase to fill in the opposite strand), small amounts of DNA can be amplified sufficiently to be analyzed (Hillis et al., 1996). This is applicable in modern forensic contexts as well as for organic remains that are thousands of years old.
A major objective of human genetics research is to locate all genes on their respective chromosomes as well as to identify all the other functional regions of DNA, including some formerly dismissed as ‘junk.’ One technique for gene mapping involves the use of genetic markers, like the restriction enzyme sites described in this article, or other DNA sequence variants. Because many of these are relevant to diagnosing human disease, high levels of funding were made available to the Human Genome Project to identify the location of these variable sequences or ‘polymorphisms.’ This support has led to the development of very fast computer and molecular technology and machinery, and much of the resultant data appear in easily searched form on the World Wide Web.
Most human genes reside in the nucleus of the cell and occur in two copies, one each inherited from the mother and the father. However, the body or cytoplasm of each cell also contains structures known as mitochondria, which are involved in the production of energy for the cell and contain their own DNA. This DNA is special in many ways. At fertilization, the mitochondria of the ovum are transmitted to the offspring, but the mitochondria of the sperm are not. Thus, mitochondrial DNA (mtDNA) is inherited in a strictly maternal manner, such that (unlike chromosomal DNA, in which a child is equally related to father and mother), mitochondrially a child is a clone of its mother and unrelated to its father.
Since mtDNA is haploid (contributed by only one parent) rather than diploid (from both parents) in form, it does not recombine during replication, and over time, as sequence variations accumulate through mutation, it produces distinct, diverging lineages of mtDNA sequences. This variation can be used to reconstruct the mtDNA of the common ancestor (the coalescent sequence) from a sample of mtDNAs collected from individuals alive today. Because the mitochondria are so numerous in the cell, mtDNA can be recovered much more easily than DNA from the nucleus.
The mtDNA chromosome takes the form of a small ring of 16 500 base pairs (16.5 kB), which was entirely sequenced by 1981. In a famous 1987 study, the structure of the mtDNA tree from 147 people was announced, which ‘coalesced’ on a woman nicknamed ‘mitochondrial Eve,’ deduced to have lived in Africa about 200 000 years ago, and whose ‘modern human’ progeny had emigrated from Africa and repopulated the world, which was at that time occupied entirely by earlier forms of human, such as Neanderthals (Cann et al., 1987).
mtDNA has become very popular in ‘recreational ancestry studies,’ in which a client’s mtDNA is matched against a global reference sample, and clients receive information on their genetic ancestry. However, since (1) the matches are very nonspecific, (2) the world is poorly sampled, and (3) seven of your eight great-grandparents are invisible to this analysis (it only studies your mother’s mother’s mother), this kind of study has proven somewhat more valuable commercially than scientifically (Bolnick et al., 2007).
Certain regions of the Y chromosome are very stable and do not recombine during meiosis, but are passed on clonally from father to son. Again, while it has some scientific value, by comparing the geographical distributions of mtDNA and Ychromosome lineages in attempts to reconstruct the migratory practices of prehistoric peoples, much of its use is commercial. Here, clients can learn, for a price, whether they have a Y chromosome inferred (often dubiously) to have belonged to Genghis Khan, Thomas Jefferson, or Moses (Thomas et al., 1998; Jobling, 2012).
Although the picture is constantly changing, researchers at this point recognize three general categories of tandemly repeated sequences (VNTRs), which are classified by length. They are satellites, the longest sequences; minisatellites, defined as sequences that are 500–40 000 base pairs in length, usually consisting of five or fewer repeated nucleotides; and microsatellites, which tend to be short and simple in motif, even consisting of repeats of a single base pair, or a doublet or triad of nucleotides (e.g., CACACA or CAGCAG).
These short, apparently neutral sequences are useful to anthropologists because their rate of mutational change is much higher than the single nucleotide mutation of DNA, so that more variation is detectable across humans and human populations. Thus, minisatellites and microsatellites, like mtDNA, may provide a finer control of historical relationships among individuals and the populations they represent than variation in the nuclear DNA.
The history of gene pools is the history of the interaction of several biological and cultural forces. The first is mutation, or the production of new alleles; that is to say, the genetic variation on which the rest of microevolution rests. The second is natural selection, in which certain genetic variations come to predominate in descendant gene pools on account of the superior fit they consistently provide their bearers to some aspect of the environment. This is the cause of genetic adaptation. The third is genetic drift, in which certain genetic variations come to predominate in the descendant gene pool for nonadaptive reasons, simply blind chance. This would have the strongest effects in small populations, which are of course the kinds of populations that characterize most of human prehistory. For example, a mother who has 10 sons and no daughters will be unrepresented in the next generation’s mitochondrial gene pool, while a mother who has only one son and one daughter will be represented; that is to say, the composition of the mtDNA pool is more strongly affected by sex ratio bias than by adaptive selection. The fourth is gene flow, the transformation of gene pools due to interbreeding (or admixture) among members of different communities (Cabana and Clark, 2011). The fifth is inbreeding, mating with genetic relatives, which increases the proportion of homozygotes in a population. If the population includes rare recessive alleles, inbreeding will increase the probability of a single individual inheriting two copies of them. Since we are all to some extent related, all populations are to some extent inbred. Small, circumscribed populations, however, would have higher amounts of genetic drift (randomly elevating the frequencies of rare alleles) and inbreeding (elevating the chances of those recessive alleles being expressed phenotypically).
While in principle the effects of these processes are mathematically distinctive, in practice it is often difficult to distinguish their different effects, except in extreme, rare cases. To establish selection requires not just genetic data but also physiology; to establish founder effect (genetic drift) requires demography. As noted in this article, sickle-cell anemia and thalassemia are solid cases of adaptation, where the selective regime is the endemic threat of malaria; Ellis–van Creveld syndrome in the Pennsylvania Amish and variegated porphyria among the South African Boers are well-established cases of founder effect. Most distinctive genetic variation in human populations lies somewhere in between, such as Tay–Sachs disease in Ashkenazi Jews.
Problems and Prospects
Reconstructions of human prehistory are commonly attempted with genetic data, and are useful for testing hypotheses generated with other kinds of data (Cavalli-Sforza et al., 1994; MacEachern, 2000; Terrell, 2000). The analysis of genetic data often contains hidden assumptions about the demography of ancient populations. Thus, standing alone, genetic conclusions about human history are often model dependent, and may be affected by the strength of selection operating on the DNA sequences being studied; the contractions, expansions, movements, and contacts of the prehistoric populations; the mutation rate; the relationship between the inferred ancestral gene pools and the descendant gene pools being studied; the inferred degree of homogeneity of ancient populations; the inferred modes of evolution (splitting and merging of lineages); and the complex relationship between modern ethnicities (the cultural labels that often guide the sampling process) and ancient gene pools.
The analysis of ancient DNA from human fossils is generating new information on human prehistory and evolution, but to retrieve usable DNA from scarce and damaged human bones of great antiquity requires extensive precautions against contamination (Hermann and Hummel, 1994). Neanderthal DNA is especially similar to that of living Europeans and Asians, but also different from other archaic human samples (Hofreiter, 2011). We do not know whether the modern human gene pool provides a useful model for understanding the gene pool of our ancestors a few hundred thousand years ago.
Admixture mapping uses carefully chosen polymorphisms that differ significantly across indigenous populations to estimate the degree of relatedness of an unknown sample to each of them. These estimates can then be used to study the heterogeneous ancestry of recently admixed populations. Its applicability is limited, though, for the method uses living populations as proxies for ancestral gene pools, and makes assumptions that are probably unrealistic about the homogeneity (purity) and autochthony (static indigeneity) of ancestral populations.
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