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. DENNIS H. O'ROURKE

Anthropological Genetics in the Genomic Era:A Look Back and Ahead

ABSTRACT The use of genetic methods and data has a long history in anthropology. Following dramatic growth in anthropological

genetic field studies in the 1960s and 1970s, the revolution in molecular genetic methods during the 1980~spurred another period ofgrowth and expansion. The earlier emphasis on examination of the role of alternative evolutionary mechanisms in structuring allele fre-

quency variation within and between populations is reflected today in a renewed focus on unraveling demographic history using highly

informative molecular markers. The existence of large, publicly available molecular genetic databases, coupled with advances in ana-

lytical methods, makes it possible to tackle a wide variety of problems in human evolution not possible with classical markers and tra-

ditional analytical methods. These recent advances will help frame the nature of research in the discipline in the near term. [Keywords:

human evolutionary genetics, phylogenetics, molecular markers, genetic variation, population structure]

GENETICDATA, AND INFERENCESthat can be drawn

from these data, have become commonplace inmodern society. With the advent of genetics as "big sci-ence" through the Human Genome Project and subsequentefforts to sequence the genomes of other organisms, it isnearly impossible to read the daily popular press withoutseeing at least one or two references to genetics. From invitro fertilization methods to forensic applications in crimi-nal proceedings, genetics is now a part of popular cultureas well as part of the culture of science. Given its dramati-

cally expanding scope, it is useful to recall that the begin-nings of the modern field of genetics originated barely acentury ago with the rediscovery of Mendel's seminal ex-periments (Orel 1996). The physical structure of the here-ditary material, deoxyribonucleic acid (DNA), was elucidatedonly 50 years ago (Watson and Crick 1953). Between these

two critical events, studies of genetic variation and evolu-tion on a variety of organisms were initiated, a rich andpowerful mathematical theory of the evolutionary genet-ics of populations was developed (Wright 1969), and an-thropologists began using genetic data and analyticalmethods to investigate patterns of human biological vari-ation and evolution (see Crawford 2000a for brief historicalreview).

References to human genetic variation in the Ameri-

can Anthropologist (AA) began appearing relatively early, al-though some of the early entries were unencumbered bygenetic data or analysis and may best be considered fanci-

ful, speculative, and inferential. C. B. Davenport's (1945)

treatment of cross-cultural dietary differences and mobil-

ity patterns as a result of underlying genetic differences

between populations is one such example. However, shortlythereafter, R. Singer (1953) reviewed the then-availabledata on the distribution of the sickle-cell trait in Africa

and its possible locus of origin. Just a year earlier, Theo-

dore D. McCown (1952) had noted the importance of ge-netics training in the education, especially at the graduatelevel, of physical anthropologists.

Discussions of race and racial taxonomy, as well as

genetic data, have been prevalent in AA over the years(e.g., Keita and Kittles 1997; Templeton 1999; see alsoCaspari this issue). Similarly, the journal has been an out-let for discussing the role of genetic data and analyticalmethods in inferring the origins of modern humans (e.g.,D'Andrade and Morin 1996; Stoneking 1994; Templeton1993, 1994). More regionally focused studies on geneticvariation have also appeared that explore both ecological(Clark and Kelly 1993) and social determinants of patternsof genetic diversity (e.g., Boster et al. 1998; Fix 1995; Jack-

son 1986) within and among defined populations.While few in number, the genetic studies appearing in

AA cited above do reflect the diversity of applications ofgenetic data and analyses in anthropology, encompassinghuman origin debates, the role of ecological and diseaseprocesses in human adaptability, and local-regional issuesof population structure, origin, and migration. The com-paratively small number of anthropological genetics arti-cles that have appeared in AA over the past several decades

AMERICAN ANTHROPOLOGIST105(1): 101-1 09. COPYRIGHT@ 2003, AMERICAN ANTHROPOLOGICALASSOCIATION

102 American Anthropologist. Vol. 105, No.1. March 2003

is perhaps not surprising. Many authors choose to placetheir research reports in more specialized journals whosereadership reflects a higher proportion of readers with ge-netic and evolutionary interests. It is worth noting, how-ever, that as research in anthropological genetics expand-ed with the molecular biology revolution of the 1980s(Crawford 2000a), the number of genetics-oriented articlesappearing in AA also increased. It is also worth noting thatmany nongenetics articles published in AA use methodo-logical and analytical approaches derived from evolution-ary genetic and population biology models (e.g., Borger-hoff Mulder et al. 2001; Moore 1994b, 2001) to addressfundamental questions of human behavioral or culturalvariation.

EVOLUTION, POPULATION STRUCTURE, ANDPATTERNED GENETIC VARIATION

The earliest example of the use of genetic data to assesspopulation variation was LeopoldHirszfeldand H. Hirszfeld'ssurvey of ABa types among World War I recruits (Hirsz-feld and Hirszfeld 1919), providing the first evidence forgeographic structure in genetic variation. Subsequently,the recognition that population differences existed for theearliest studied classical genetic markers led to their use inthe construction of a variety of human typologies andclassifications. The role of genetics and anthropology inthe history of racial classification and its ramifications isbeyond the scope this article. (These issues are dealt within detail in this issue by Rachel Caspari.) The broaderabuses of anthropology and genetics as part of the "FinalSolution" in 1930s Nazi Germany are discussed by BennoMuller-Hill (1988). Similarly, the ethical issues raised notonly by these historical events but also by the dramatic ex-pansion of genetic methods in the last two decades are re-viewed elsewhere (e.g., Anderlik and Rothstein 2001;Greely 2001; Juengst 1998; O'Rourke et a1.in press).

Early studies of genetic variation by anthropologistsinclude the classicwork on natural selection on human poly-morphisms by Alice R. Brues (1963, on ABa and maternal-fetal incompatibility) and Frank B. Livingstone (1960, onsickle hemoglobin and malaria). However, by 1966, DerekF. Roberts argued that biological anthropology in theUnited States suffered from a notable malaise that did notcharacterize the other life sciences. Less than a decade

later, he identified what may be characterized as at least apartial cure for that malaise: "a great stimulus by humangenetics" (1973:1). The effective integration of human ge-netic methods into biological anthropological studies ofhuman variation and evolution marked the florescence of

anthropological genetics in the 1970s. The advent of thegrowth of anthropological genetics 30 years ago was morethan simply the borrowing of genetic methods of analy-ses. The genetic approaches were enhanced by the anthro-pological perspective of using the diversity of social pat-terns and human demography to guide genetic analysis

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and inference, and by the undertaking of long-term popu-lation studies.

The focus of most anthropological genetic studies be-ginning in the late 1960s was to document local patternsof genetic variation within and among populations and toexamine the relative effects of evolutionary mechanismsthat gave rise to the observed patterns. In addition to thedifficult quest to document the action of natural selectionin the human genome, this meant a greater emphasis oninvestigating the effects of gene flow (admixture), geneticdrift, and mutation in specific human populations. Thisrepresented a shift away from the traditional classificationand taxonomy of human groups to an investigation ofevolutionary mechanisms at the genetic level in humanpopulations.

Taking advantage of known population histories, Mi-chael H. Crawford and colleagues investigated the rela-tionship between migration, population movement andresettlement, and admixture in Tlaxcaltecan populationsof Central Mexico (Crawford 1976) and among Garifuna(BlackCarib) communities in Belize and Guatemala (Craw-ford 1983, 1984). Numerous investigators also utilizedknowledge of the historical sizes of populations, and in-itial founding of individual communities to assess the roleof drift in structuring allele frequency variation in con-temporary populations. Roberts (1967, 1968) analyzed thehistorical demography and changing genetic structure ofthe island of Tristan da Cunha, while L. Luca Cavalli-Sforza(1969) studied the effects of reduced population size andrelative isolation on the genetic structure of Alpine iso-lates in Italy. Communities whose identities are related tospecific religious traditions such as the Dunkers (Glass1953), Amish (McKusick et a1. 1964), Mennonites (Craw-ford 2000b; Crawford et a1. 1989), and Mormons (O'Brienet a1. 1994; O'Brien et al. 1996) have also been helpful inelucidating the relationship between demographic struc-ture and dynamics, and the generation of the pattern ofgenetic variation within and between populations.

Detailed population histories and records are not ab-solutely essential to the study of human population genet-ics. Based on the mathematical treatment of isolation bydistance and identity by descent (Malt~cot1948), NewtonE. Morton et a1. developed analytical methods, termed"bioassay of kinship," to study the genetic structure ofmany populations and regions, including Micronesia andthe Middle East (e.g., Morton et a1. 1982; Morton andLalouel 1973). Similar population genetic models andmethods were employed by Jonathan S. Friedlaender(1975) in his original study of Bougainville Island, andJames V. Neel (e.g., Neel and Weiss 1975) and colleaguesin an influential series of human population genetic stud-ies among the Yanomama and other groups in lowlandSouth America. -

In addition to studies of individual, local populations,or groups of historically related populations, some anthro-pological genetic studies sought information on broaderpatterns of variation. Cavalli-Sforza et al. (1994) pioneered

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studies seeking regional or continental level patterns of ge-netic variation through the use of synthetic gene fre-quency maps. Several such studies also examined the rela-tionship between patterns of genetic variation and thedistribution of linguistic groups (e.g., Cavalli-Sforza et al.1988). Similarly, Brian K. Suarez et al. (O'Rourke et al.1992; Suarez et al. 1985) examined the effects of geogra-phy and local ecology on gene frequency variation in alarge sample of populations in the Americas.

The attention to the dynamics of individual popula-tions in anthropological genetic studies was based not onlyon the body of theory in evolutionary population geneticsbut also on the anthropological interest in population his-tory. In 1972, Lewontin demonstrated that 85 percent ofobservable genetic variation in the allele frequencies of 15protein loci was found within local populations. A meresix percent of genetic variation could be accounted for bydifferences between continental-level groups. If the studyof evolution was the study of changes in variation overtime, then understanding the roles of evolutionary mech-anisms in the structuring of allele frequency variationwithin individual populations was a likely starting point.Like the majority of anthropological genetic studies, Ri!=h-ard C. Lewontin's (1972) demonstration was based on theexamination of allele frequencies of classical markers-such as red cell antigens, enzymes, and serum proteins.Recently, Guido Barbujani et al. (1997) replicated Lewon-tin's earlier work using a large suite of newer molecularmarkers. Analysis of 30 micro satellite markers and 79 re-striction site markers in 16 populations from around theworld revealed again that 85 percent of the variation wasrepresented by individual diversity within populations,while only about 11 percent of the variation was distrib-uted between major groups.

Results from variation in the mitochondrial genome(mtDNA) are in essential accord with the nuclear data.Gorde et al. 1998; Seielstad et al. 1998), as are craniometric.data (Relethford 2002). Mark T. Seielstad et al. (1998) re-port 81 percent of the variation in mtDNA single nucleo-tide polymorphisms (SNPs) and 85 percent of autosomal(nuclear) SNP variation are found within populations,while approximately twelve percent and eight percent ofthe variation in these genomes, respectively, are found be-tween continental populations. In contrast, only 35 per-cent of the variation in Y-chromosome SNPs is foundwithin local populations, while over 52 percent is ac-counted for by differences between major groups. This dif-ference in the distribution of genetic variance across ma-ternally and paternally derived markers is consistent withan inference that over time females are far more likely tomigrate than males. Indeed, the inferred migration rate forfemales is approximately eight times that for males (Seiel-stad et al. 1998; Stoneking 1998). The inference of greatermobility for females than males is consistent with the an-thropological observation that most agricultural and for-aging societies are patrilocal. Thus, at marriage womenleave their natal communities and move to the place of

O'Rourke. Anthropological Genetics 103

residence of their mate. The displacement between birth-places of parents and offspring, then, is primarily the re-sult of mothers moving, not fathers (Seielstad et al. 1998).

Hiroki Oota et al. (2001) tested the hypothesis thatmtDNA and V-chromosome marker variation are corre-lated to either patrilocality or matrilocality. These investi-gators obtained mtDNA hypervariable sequence data andV-chromosome Short Tandem Repeats (STR) haplotypeson three matrilocal and three patrilocal groups of north-ern Thailand. STRsare short segments of DNA that are re-peated a variable number of times at specific locations inthe genome. Different numbers of repeats at a locus areanalogous to alleles, and variation in repeat number de-fines the polymorphism. As expected, patterns of geneticpopulation differentiation in these haploid genetic sys-tems were strongly correlated with residency practice. Ge-netic distances of the mtDNA sequence data were morethan twice as large as the Y-chromosome-based distancesfor the matrilocal communities. The pattern was reversedfor the patrilocal groups. Here, the genetic distance basedon the Y-chromosome STRswas over three times as largeas the distance based on mtDNA sequence variation. Atleast over short temporal spans, the demographic signal inmolecular genetic data, such as those just described, seemsclear and the relevance to anthropological inquiry obvious.

THE MOLECULAR REVOLUTION

The molecular revolution is essentially a technical one.The ability to generate large quantities of specific DNAsegments for analysis through the Polymerase Chain Reac-tion (PCR),automated sequencing technology for DNAse-quences and high-throughput genotyping, as well as thedevelopment of microarray technology, has revolution-ized the way in which data on genetic variation in popula-tions may be obtained. Classical marker antigens, proteins,and enzymes have been replaced by SNPs, restriction sitepolymorphisms (RSPs),STRs,insertions and deletions (in-dels, e.g., Alus), and direct DNA sequence. The result isdata richness unknown for classical markers. The embar-

rassment of riches afforded by the new molecular genetictechniques in anthropological genetics led Henry Har-pending and Elise Eller to observe that, "Today a singlepublication can present more and better data than thesum of everything available in the literature before 1985or SOli(1999:301). Not only is heterozygosity substantiallygreater for many of the new molecular markers but theyalso exhibit a range of evolutionary rates and alternativemechanisms for the generation of new variants. The sur-feit of data has resulted in a complementary developmentof new analytical methods in phylogenetics, linkage andlinkage disequilibrium analyses, statistical genetics,- andcoalescent models. Not only the data but also the methodsof data analysis in population genetics, including anthro-pological genetics, have undergone dramatic expansion inrecent years (e.g., Bandelt et al. 1999; Hudson 2000; Wall2000).

104 American Anthropologist. Vol. 105, No.1. March 2003

Despite the growth in the number and variety of mo-lecular genetic markers available for analysis, compara-tively few populations have been screened for most ofthem. It is still the case that many more populations havebeen characterized for classical markers than molecularmarkers. Conversely, for those populations that have beenthe subject of molecular genetic study, many more geneticmarkers have typically been determined in each individ-ual sample studied. Thus, the geographic coverage ofworld populations is greater for classical markers, whilemany more loci are available for study in those groupsthat have been characterized by the newer molecularmethods. One difficulty encountered in studying global,or even regional, patterns of variation with classical mark-ers has not changed with the advent of the rapid typing ofmolecular markers. This difficulty is the lack of stand-ardization with respect to which genetic systems to use tocharacterize genetic variation in individual populations.While many populations were characterized for classicalmarker variation during the latter half of the 20th century,comparative studies were hampered by the fact that inmost populations studied, few systems were uniformlytyped. Such comparative studies were frequently reducedto using red cell antigen (blood group) variation as the pri-mary data, solely because blood groups were the mostcommon early genetic markers and had been typed inmore populations than more polymorphic, and, hence,more informative markers such as those of the human leu-cocyte antigen (HLA)system. The lack of comparability re-mains a challenge in the molecular era, where now hun-dreds of SNPS, STRs, indels, etc. are available, with littleeffort being made to establish a common set of markersuseful for population screening for comparative evolution-ary studies.

Nevertheless, the increase in molecular methods forobtaining genetic data, and the expanded analytical arma-mentarium, has facilitated genetic analysis of both humangenomes-nuclear and mitochondrial. The nuclear genomeis characterized by approximately three billion bases; is bi-parentally inherited; has editing functions, both introns(noncoding regions of DNA) and exons (coding regionsthat underlie gene expression); and exhibits recombina-tion. In contrast, the maternally inherited mitochondrialgenome is only about 16.5 kb in size (kb =kilobase, or1,000 nucleotide bases in length); it is almost complete ex-onic with the exception of the Control Region; and it lacksboth transcription editing and recombination. As a result,the evolutionary histories of the nuclear and mitochon-drial genomes need not be concordant. Indeed, they oftenare not (Hey1997;cf.]orde et al. 1998).One reason for possi-ble discordances is the temporal window to evolutionarychange afforded by different markers in the two genomes.Lacking editing capabilities, the non coding region of themitochondrial genome accumulates sequence changes at amuch faster rate than that typically found in the nucleus,thus providing an opportunity to examine differentiationbetween lineages, and perhaps populations, over a rela-

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tively recent time frame. Alternatively, nuclear coding re-gions, characterized by transcription editing and purifyingselection, evolve at a much slower rate, providing a win-dow onto much more ancient evolutionary changes. Non-coding regions of the nucleus may well evolve at even dif-ferent rates, constrained by selection only to the degreethey are linked to conserved coding regions.

Evolutionary rates of nucleic acid sequences are con-strained by much more than selection and molecular edit-ing machinery. The evolutionary history of genetic mark-ers is a reflection of the demographic history of thepopulation under study. Although the action of specificevolutionary mechanisms was inferred from genetic dataon populations whose demographic histories were basi-cally a matter of record as described above, the power ofthe new molecular data and analytical techniques is in in-ferring unknown demographic histories from genetic data(Harpending and Eller 1999). Thus, changes in the demo-graphic structure of a population over time, a change inthe shape of the gene genealogy, may also result inchanges in phylogenetic inference.

Much of the uncertainty regarding evolutionary infer-ences of populations relates to the ephemeral nature ofpopulations and the often arbitrary nature of populationdefinitions (Moore 1994a, 1994b). This difficulty stemsfrom the fluidity of individual and group identities in timeand space. Individuals may change ethnic identities, and,hence, group membership, at will, complicating assump-tions of demographic continuity over time. It is clear thatregional patterns of genetic variation for some genetic sys-tems (e.g., mitochondria) may exhibit temporal stabilityover time, and therefore be indicative of ancestral-descen-dant relationships (O'Rourke et al. 2000a). It is not clearhow long such regional patterns remain temporally andspatially stable, or that the same result would obtain forgenetic systems in the nuclear genome.

The difficulty of precisely and accurately defining hu-man populations in the genetic sense may be one reasonthat early anthropological genetic research was conductedon comparatively isolated, founder populations.

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GENETICSAND HUMAN ORIGINS

In no other area have genetic approaches generated morecontroversy than in human origins research. Vincent M.Sarich and Alan C. Wilson (1967) were among the first touse genetic methods and data to address questions of hu-man origins. Based on differences in albumin variantsamong humans and nonhuman primates, they concludedthat the observed differences would have accumulated in

approximately five to eight million years. This divergencedate was much more recent than the paleontological re-cord indicated, stimulating a lively debate on the timingof the appearance of the hominid lineage. The more recentdate for hominid origins suggested by the genetic data wasultimately supported with newer paleontological data andis uniformly acknowledged today. ~~

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More recently, Rebecca 1. Cann et al. (1987) used vari-ation in mitochondrial DNA to infer that the diversity inthe modem human gene pool is also of very recent vintage,perhaps 200,000 years or less. This view of modem humanorigins, too, was at variance with the general paleontologi-cal picture, which placed human origins much furtherback in time. The two alternative views of human originscrystallized around two competing models, a recent Africanorigin model and the multiregional, or continuity, model.Predictions regarding patterned genetic variation in mod-ern human populations, and the demographic processesthat gave rise to them, are quite different between the twomodels. The recent African origin model predicts an originfrom a single ancestral population in the relatively recentpast. This requires a signature of a population bottleneckin the demographic history of our species followed by adramatic population expansion, and the generation ofspecieswide variation over a relatively short period oftime. The latter inference suggests we should see an excessof rare variants in many human populations since therehas been insufficient time for neutral markers to drift to

high frequency. Alternatively, the multiregional modelpredicts comparatively larger populations of early humansdistributed throughout Eurasia and supposes at least mod-erate gene flow between them. This model does not re-quire a recent population expansion, but such an expan-sion might not be incompatible with the model.

Using genetic data to test the predictions of these al-ternative models has been problematic. Initially, the onlymolecular marker with sufficient comparative data to beuseful was mtDNA. From the early work of Cann et al.(1987) and others (e.g., see Jorde et al. 1998), it seemedclear that there was greater mtDNA variation in Africanpopulations than non-African populations; not an unex-pected result if modern human populations derive from asingle African ancestor relatively recently. Indeed, asmtDNA sequence data accumulated it appeared that thehuman population had experienced a population expan-sion within the last 100,000 years from a comparativelysmall starting population (e.g., 10,000 individuals; data re-viewed in Rogers 2001). However, mtDNA is a single, hap-loid molecule, and markers derived from it constitute ahaplotype, which are not truly independent markers. Assuch, its robusticity for inferring demographic events maybe questioned. For example, if the inference of a popula-tion expansion is incorrect, the greater genetic variation inAfrican populations may reflect larger, long-term popula-tion sizes, weakening the inference of a recent African ori-gin (e.g., Relethford and Harpending 1994; Relethford andJorde 1999). Nuclear markers have yielded more heteroge-neous results (Harpending and Rogers 2000; Rogers 2001).

One difficulty in using molecular data to evaluate al-ternative demographic histories is that it is difficult to dis-tinguish population expansion from a selective sweep.That is, strong selection driving rare variants to higher fre-quencies produces the same effect and is frequently indis-tinguishable from rapid population growth without selec-

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O'Rourke. Anthropological Genetics 105

tion. Selection, of course, is expected to affect only a few,perhaps closely linked, loci while population growth is ex-pected to have uniform effects on the entire genome.Thus, distinguishing selection in a stable, constant popu-lation from population growth in a small founder popula-tion using genetic data requires examination of multipleindependent loci. Wall (2000) recently concluded that50-100 independent nuclear loci will be required to dis-tinguish between the alternative demographic scenarios ofthe recent African origin model and the multiregionalmodel. As more molecular data become available, this willsoon become a reality.

Like mtDNA, the limited data available on the Y-chro-mosome (e.g., Underhill et al. 2000) and widely dispersedautosomal STRloci show evidence for a population expan-sion in the late Pleistocene epoch (Rogers 2001). However,other nuclear sequences present patterns of variation thatare not so uniformly clear. Studies of nuclear DNA se-quences outside known functional genes show evidence ofa population expansion, as do some intronic sequences.Other intronic sequences, along with many sequences incoding regions do not provide evidence for a populationexpansion in our species history. Several investigators nowview these results as an indication that while much of thegenetic data is consistent with a late Pleistocene popula-tion expansion of the species, it is also overlain by pat-terns of variation structured by selection to a greater de-gree than previously suspected (Harpending and Rogers2000; Rogers 2001; Wall and Przeworski 2000). Thus,while contemporary genetic data cannot yet reject eitherof the competing models for modern human origins(Relethford 1998, 2001), the growing body of molecularevidence increasingly supports a recent African origin andprovides insight into the nature of natural selection pres-sures on the maintenance and patterning of variation inthe human genome.

One additional form of genetic data has been used toaddress the problem of modern human origins, ancientDNA (aDNA).Matthias Krings et al. (1997, 1999) extractedmtDNA from the Neandertal-type specimen and demon-strated that it differed from a series of over nine hundredmodern humans by an average of 27 nucleotide differ-ences (N =22-36 substitutions). The range of differencesamong the large modern human series was 1-24 substitu-tions with a mean of eight. This dramatic difference inmtDNA hypervariable sequence between modern humansand an archaic European was taken as evidence that theNeandertals had not contributed to the modern humangene pool and, thus, provided evidence in favor of the re-cent African origin model. However, as a single sample, italone is insufficient to reject the multi regional model withfinality (e.g., Relethford 2001). More recently, additionalarchaic humans have been studied with respect to ancientmtDNA variation producing similar results (Krings et al.2000; Ovchinnikov et al. 2000). Thus, while the aDNAanalyses are also not sufficient to resolve the competingmodels for the origin of modern humans, the aDNA data

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106 American Anthropologist. Vol. 105, No.1. March 20031)"/1

appear to provide less support for multiregional evolutionthan for a single, recent origin,

The role of genetic analyses in human origin researchis illustrative. By focusing on measurement of populationvariation and detailing demographic histories from ge-netic variation, these methods bring an independent lineof inquiry to the problem of human origins that can notbe addressed by paleontological data. Bringing inde-pendent sets of data and methods of analysis to bear on acommon problem is a strength of science, not a weakness.We are still experiencing a dramatic increase in the gen-eration of molecular genetic data on the world's popula-tions, and increasing numbers of paleontological speci-mens are yielding genetic data (reviewed in O'Rourke et al.2000b). This suggests that the increase in data on humangenetic diversity is rapidly bringing an unprecedentedlevel of resolution and analytical power to the problem ofmodern human origins. Unfortunately, the nature of pa-leoanthropological research is such that we cannot antici-pate a comparable increase in available information fromnew fossil forms. This means that the import of geneticmethods and approaches to the study of human origins islikely to grow rather than be diminished.

However, inferences on human origins from geneticdata are not without problems. It seems generally acceptedthat the transition from archaic to modern humans oc-

curred relatively recently (200,000 years ago). The ques-tion of interest is whether this transition was rapid,stemmed from a single source population, and, therefore,could be characterized as a speciation event; or whetherthe transition was rather more gradual over time andspace. The extreme versions of these two alternatives, thereplacement model and the multiregional model, wereused for illustrative purposes above. The reality of our evo-lutionary history may be less clear-cut. If, for example,modern Homo sapiens originated in Africa, and during mi-grations to other continental regions interbred with exist-ing archaic populations, the distinctions between the re-placement and multiregional models become blurred, andthe predictions about patterns of genetic variation basedon such models also become more complex. If, as I havejust argued, existing genetic data are not yet sufficient todistinguish between the extreme forms of the models withfinality, the data are even less adequate to disentangle themore subtle differences expected from intermediate mod-els. This emphasizes the need for appropriate analyticalmethods and close attention to model building. Such ob-servations are not novel (d. Harpending and Rogers 2000;Hawkes and Wolpoff this issue; Hawkes et al. 2000). It isworth repeating, however, that greater attention to devel-oping appropriate models, for example incorporating se-lection, gene flow, and alternative (or dynamic) demo-graphic histories, is necessary to realize the potential ofthe emerging genetic data to aid our understanding of hu-man evolutionary history.

QUANTITATIVEVARIATION

Historically, biological anthropologists have also used quan-titative traits as more indirect measures of genetic vari-ation within and between groups. The assumption is thatquantitative (metric as well as discrete) biological charac-ters (e.g., anthropometrics, skin reflectance, discrete den-tal traits), owe their expression to underlying genes andreflect genetic differences and similarities between bothindividuals and populations in the same way that classicalgenetic markers do. Unfortunately, until recently it has'been difficult and perhaps impossible to know the geneticarchitecture of quantitative traits, although elegant mod-els for the genetic analysis of quantitative variation havebeen developed (Konigsberg2000; Rogers 1986; Rogers andHarpending 1983; Williams-Blangero and Blangero 1992).Alan R. Rogers and Henry Harpending (1983) showed thatthe genetic information content of a quantitative charac-ter was equivalent to that of a single, biallelic locus if thequantitative character were normally distributed, fullyheritable, and neutral with respect to selection. Neutralityand 100-percent heritability are far more difficult to dem-onstrate for a quantitative, morphological character than,for example, DNA markers. These constraints impose limi-tations on the utility of quantitative charactRrs in thestudy of the evolution of human variation.

The recent advances in molecular genetics are now be-ing applied to quantitative traits. Developments in linkageanalyses to identify quantitative trait loci (QTLs),coupledwith the wealth of genetic polymorphisms covering the

human genome, no:-" make possible the analysis of spe-cific quantitative traits to identify and characterize locicontributing to expression of the quantitative phenotype(Almasy and Blangero 1998; Rogers et al. 1999). The ge-netic architecture of such traits as stature (Hirschhorn etal. 2001; Perola et al. 2001), body mass index (Feitosa et al.2002; Hanson et al. 1998; Perola et al. 2001), obesity(Commuzie et al. 1997), the physiology of altitude adapta-tion (Beall 2000), and human pigmentation (Akey et al.2001; Bastiaens et al. 2001a; Bastiaens et al. 2001b; Hard-ing et al. 2000) are now being elucidated by gene functionstudies and linkage analyses using whole genome scans.

A single example will suffice to illustrate the emergingcomplexity of quantitative genetic variation in a simple,well-known continuous trait, skin color. Skin color is de-termined in large measure by the concentration of mela-nin in the skin. The number of genes that influence mela-nin production and concentration has been estimated tobe as small as four to six and as large as several dozen. Atpresent we have no clear evidence to suggest which is themore likely in humans, but the 100 known genes' formouse coat color suggests the system may well be geneti-cally complex Oobling 2001). The one known gene in-volved in normal skin color variation is the melanocortin-

1 receptor, MC1R. This gene is a peptide receptor that.helps in the regulation of production of eumalanin, thedark pigment contributing to skin color (Harding et al. 2000).

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Maarten T. Bastiens et al. (2001a, 20mb) have shown thatvariation in MC1R is also responsible for freckling in themajority of cases, independent of skin and hair color, andthat variants in this gene are also associated with fair skin,red hair, and elevated risk to nonmelanoma skin cancers.Joshua M. Akey et al. (2001) measured skin reflectance in aTibetan sample and found that variation in reflectancewas influenced by the interaction of specific alleles atMC1R and P, which is another gene involved in eumelaninsynthesis. If pleiotropy and epistasis are common in quan-titative variation, as they seem to be in this simple exam-ple for only two loci affecting skin color, then the geneticsof quantitative variation may be complex, indeed. Identi-fying the phylogenetic signal from noise in such complexsystems may be more of a challenge than expected.

Until the advent of aDNA methods (O'Rourke et al.2000b), paleo anthropological inferences of the fossil re-cord were dependent on morphological and morphomet-ric characters. Yet the phylogenetic information contentof these characters is unknown, since we have informationon quantitative genetic variation for few if any such char-acters, much less knowledge of individual genes affectingthe expression of the trait. With the advent of the richmolecular genetic database now being developed, coupledwith new analytical procedures for maximizing the utilityof the molecular database, the future looks brighter forclarifying the nature of genetic variation in many humanquantitative traits.

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CONCLUSION

If anthropological genetics developed from the productive

intersection of biological anthropplogy and human genet-ics three decades ago, its modern descendant is a subdisci-pline that melds not only these two disciplines but alsoportions of molecular biology and bioinformatics. Thisnew hybridity for the field has two fundamental results:One, the way in which we will approach questions of hu-man evolution and variation in the future is likely tochange, and, two, the way in which we prepare studentsfor careers in the discipline must change.

Given the dramatic increase in our understanding ofgenetic variation at the molecular level, it seems inevitablethat future studies will focus less on descriptive studies offrequency variation than on the role of gene function onthe distribution of key phenotypes, functional genomics.As we learn more about gene expression, we will requiremore precise information regarding the timing of expres-sion and developmental genetic studies will be incorpo-rated into our research arsenal, including making use ofthe developing technologies of micro and expression ar-rays. Certainly, molecular quantitative genetics, already inevidence in our research literature, as noted above, hasmuch to contribute.. Finally, the molecular innovationsthat have fueled the recent increase in genetic data havealso spawned the development of numerous new analyti-cal methods and techniques.

O'Rourke. Anthropological Genetics 107

Exploring of the malaise in U.S. physical anthropology40 years ago, Roberts warned that "Subjects do not continueto live merely because they have a history, or because oftheir content. They survive because they are part of the in-tellectual climate of the moment" (1966:165). In this ge-netic era (Weiss 1998), I think the prospects for growthand prosperity of the discipline are as encouraging as theyhave ever been.

DENNISH. O'ROURKELaboratory of Biological Anthropology,University of Utah, Salt Lake City, UT 84112

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