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A Genetic Focus on the Peopling History of East Asia: Critical Views

A Genetic Focus on the Peopling History of East Asia: Critical Views Rice (2011) 4:159–169 DOI 10.1007/s12284-011-9066-y A Genetic Focus on the Peopling History of East Asia: Critical Views Alicia Sanchez-Mazas & Da Di & María Eugenia Riccio Received: 24 October 2011 /Accepted: 2 November 2011 /Published online: 2 December 2011 The Author(s) 2011. This article is published with open access at Springerlink.com Abstract Population genetic studies may provide crucial MDS Multidimensional scaling analysis information for our knowledge on human peopling history AMOVA Analysis of molecular variance and have been extensively applied to reconstruct East Asian MRCA Most recent common ancestor prehistory in the last 10 years. However, different genetic NEAS Northeast Asian populations investigations are not always consistent with each other and SEAS Southeast Asian populations some results are conflicting or misinterpreted. This repre- CAS Central Asians sents a main obstacle for scholars of other disciplines like WAS West Asians archaeologists and linguists who try to relate the genetic information on past human migrations to their own results on the spread of domesticated crops or animals or on the Introduction dispersal of the main language families. In this paper, we review the current genetic evidence related to the peopling East Asia is a very large geographic area of the world history of East Asia with a critical view on some currently inhabited by more than 1.5 billion people, which interpretations. In this way, we hope to provide a useful represents about 22% of the world population. According to reference for further interdisciplinary studies on our past. the current fossil record and as supported by genetic evidence, it is likely that modern humans did not originate . . Keywords East Asia Genetic diversity Human peopling in East Asia (Jin and Su 2000). However, this vast . . . . history Genetic clines Genetic boundaries mtDNA continental region was probably settled very early in the . . . Y chromosomes HLA Pincer model Southern route Paleolithic when the first Homo sapiens spread throughout the world, presumably from East Africa; although southern Abbreviations Africa has recently been proposed as another possible HLA Human leucocyte antigen original homeland (Henn et al. 2011) and very early well- RH Rhesus dated skeletons are also known in the Levant (Stringer et al. GM IgG immunoglobulins’ genetic marker 1989). Old human fossil remains are yet very scarce in East SNPs Single-nucleotide polymorphisms Asia (with a very uncertain date of 68,000 years for the NRY Non-recombining portion of the Y chromosome most ancient fossil known to date, Liujiang, that was found mtDNA Mitochondrial DNA by chance (Shen et al. 2002)) and do not allow on their own STR Short tandem repeat to reconstruct East Asian prehistory. During the last PCA Principal component analysis decades, different disciplines, i.e., archaeology, linguistics and population genetics, have been involved together in the : : A. Sanchez-Mazas (*) D. Di M. E. Riccio reconstruction of human peopling history, bringing some Laboratory of Anthropology, Genetics and Peopling history, indisputable results but also revealing the extraordinary Anthropology Unit, Department of Genetics and Evolution, complexity of East Asian past human settlement history University of Geneva, (Sagart et al. 2005a; Sanchez-Mazas et al. 2008). As a Geneva, Switzerland matter of fact, distinct scenarios of human migrations in e-mail: alicia.sanchez-mazas@unige.ch 160 Rice (2011) 4:159–169 East Asia are still disputed today, like the first arrival of H. between northeastern and southeastern populations as sapiens from West Asia, either through a single southern route well, e.g., for mitochondrial DNA (mtDNA), A, C, D along the sea coast or through two independent routes via the and G haplogroups are more frequent in the north, while B southern and northern edges of the Himalayas. Also, human and F are more frequent in the south (Kivisild et al. 2002; population migrations in East Asia have been investigated in Stoneking and Delfin 2010; Yao et al. 2002). For the Y relation to the spread of agriculture and the main linguistic chromosome, northeastern and southeastern populations families, leading to quite different views on the subject. are clearly discriminated both in a principal component In this paper, our objective is to make clear the current analysis (PCA) using 19 non-recombining Y (NRY) genetic evidence related to East Asian peopling history. To markers (Su et al. 1999) and in a multidimensional scaling that aim, we have described the available information— analysis (MDS) using 52 markers (Karafet et al. 2001). including our own conclusions based on human leucocyte More recently, PCA based on genome-wide analyses of tens antigen (HLA) genetic studies—within two distinct sections of thousands of single-nucleotide polymorphisms (SNPs) to distinguish the raw genetic results from their interpretation, confirm that genetic differentiation vary principally with the latter being more subjective and open to criticism. We also latitude in East Asia (Abdulla et al. 2009; Suo et al. 2011). underline the major limitations of such genetic studies, as a complement to what was previously explained by Blench et Genetic boundaries versus continuous patterns al. (2008). Finally, we propose some perspectives in this area for future genetic studies. We hope that this clarification will Whereas NEAS and SEAS clearly exhibit contrasted genetic be useful to scholars of other disciplines who are often profiles, this result alone does not indicate how genetic confused by the very specialized and often contradictory diversity is structured among the two areas. The existence of a information provided by population genetics studies. clear-cut genetic boundary between northern and southern populations has been debated: based on classical markers, a boundary located at the vicinity of the Yangtze River has been Raw results from population genetic studies suggested (Du et al. 1997;Xiao etal. 2000; Xue et al. 2005). Several significant boundaries are found among northern and North–south genetic differentiations in East Asia southern Han populations according to mtDNA haplogroups, the sharpest genetic contrast appearing along Huai River and One of the most robust results found in genetic studies Qin Mountain that are north to Yangtze River, and two focusing on East Asian populations is the marked others south to Yangtze River and north to Yellow River, genetic differentiation between Northeast Asian and respectively (Xue et al. 2008). On the other hand, no Southeast Asian populations (NEAS and SEAS), respectively significant genetic barrier is found when both Han and non- (Cavalli-Sforza et al. 1994; Chu et al. 1998;Du etal. 1997; Han populations are included. An automatic search for a Xue et al. 2005). This general structure is observed for all genetic frontier has also been performed for HLA, with a genetic markers studied so far and is characterized either by similar result: a significant boundary emerges for HLA-A, - sharp differences of gene frequencies or by the occurrence of B, and -DRB1 only when Han populations alone are distinct genetic lineages. For classical markers, the best considered; in this case, the boundary appears near the specific examples are provided by the distribution of Rhesus Yangtze River (Di and Sanchez-Mazas 2011). Boundaries (RH) and IgG immunoglobulins’ genetic marker (GM) are also detected when using Y chromosome data but in a haplotypes showing very high frequencies of RH*R2, much more fragmented way with no significant uninterrupt- GM*1,17;21 and GM*1,2,17;21 in Northeast Asia, and ed barrier between north and south (Xue et al. 2008). Note RH*R1 and GM*1,3;5* in Southeast Asia (Poloni et al. that the significant level of genetic variation (Φct=0.16) 2005; Sanchez-Mazas 2008). Overall analyses on a set of observed by Karafet et al. (2001) between SEAS and NEAS classical markers have also shown such differentiations for the Y chromosome cannot be interpreted as a genetic (Cavalli-Sforza et al. 1994). At the HLA loci, distinct boundary as it is the result of an analysis of molecular alleles and/or allelic lineages display contrasted frequen- variance (AMOVA) with an a priori choice of the groups cies between NEAS and SEAS, leading to the definition of compared. Through genome-wide association studies, popu- “group 1” and “group 2” alleles (Di and Sanchez-Mazas lation substructure of Han populations into north, central and 2011). Through principal coordinate analyses, a general south subgroups is observed but with very small levels of differentiation between northern and southern populations genetic differentiation (Xu et al. 2009), thus resembling much is also observed at most HLA loci (HLA-A, -B, -C, - more a continuous pattern. Such continuity has clearly been DPB1, -DRB1) (Di and Sanchez-Mazas (2011) The north– put forward by Chen et al. (2009) using over 350,000 south differentiation of East Asian populations;inprepa- genome-wide autosomal SNPs in over 6,000 Han Chinese ration). Gender-specific polymorphisms show a contrast samples from ten provinces of China. Rice (2011) 4:159–169 161 Thus, except in some cases where only Han populations are considered, the genetic pattern of East Asian popula- tions is definitely not a sharp bipartite subdivision. On the contrary, many studies indicate the existence of genetic clines along the latitude. In addition to multidimensional scaling and/or spatial autocorrelation analyses, continuous patterns of gene frequencies have been evidenced by their correlation with latitude for several genetic markers, e.g., HLA (Di D, and Sanchez-Mazas A. 2011 In prep. The north-south differentiation of East Asian populations) and autosomal SNPs (Abdulla et al. 2009; Suo et al. 2011). Frequency clines were also observed for classical markers, e.g., RH and GM haplotypes (Poloni et al. 2005; Sanchez- Mazas 2008) and mtDNA haplogroups like F1, B, and D4 (Yao et al. 2002). North and south substructures This continuous pattern of genetic differentiations in East Asia is also characterized by changes in the levels of genetic diversity and substructure between NEAS and SEAS, although with a hard dispute between different Fig. 1 Graphs showing a high and significant correlation (indicated by authors. On the basis of 19 NRY markers, Su et al. (1999) the coefficient of determination R ) between the number of haplotypes detected and the number of individuals tested for the set of population claim that SEAS are more diversified than NEAS, while samples analyzed by Su et al. (1999) for Y chromosome markers. Top: Karafet et al. (2001) sustain the opposite view on the basis all population samples; bottom: after removing the two samples with of 52 NRY markers. Actually, Su et al. (1999) used more highest sample sizes (82 and 280 individuals, respectively). than two times as many SEAS (20) than NEAS (9); moreover, sample sizes are very small (less than 30 individuals) except in two cases (N=82 for one northern below). Similar methodological problems related to sampling Han and N=280 for one southern Han population), which is occurred in the study of Abdulla et al. (2009)based on clearly a source of bias: in this study, the number of autosomal SNPs; the authors found that haplotype diversity haplotypes detected is highly significantly correlated to the was strongly correlated with latitude (R =0.91, P< number of individuals tested (Fig. 1). 0.0001), with genetic diversity decreasing from south to Shi et al. (2005) reanalyzed Y chromosome markers and north. However, this result was obtained through an sustained Su et al.’s(1999) conclusions. However, because, analysis of 10 “combined” populations (1, Indonesian; 2, as they say, ∼80% of the Chinese ethnic populations live in Malay; 3, Philippine; 4, Thai; 5, Southern Chinese southern regions with inhabitation histories longer than minorities; 6, Southern Han Chinese; 7, Japanese and 3,000 years,(Wang 1994 citedbyShi et al. 2005), Korean; 8, Northern Han Chinese; 9, Northern Chinese populations from southern regions of China were overrep- minorities; and 10, Yakut), with Yakut as the only resented in their study: on the contrary, Hui, Uygur, and population representing Altaic in the north, and several Mongolian, which represented northern populations, were mixed population samples representing southern popula- removed from the analyses because they were considered as tions, the genetic diversity of which being then probably recently established (<1,000 years ago) with extensive inflated. By using a better population sampling, Xue et al. admixture with European and Central Asian populations (2006) found a higher STR diversity in the north than in (Wang 1994 cited by Shi et al. 2005). Likewise, the short the south, a finding that is not easily reconciled with a tandem repeat (STR) network shown in this work was largely or exclusively southern origin for the northern built after excluding the Tibeto-Burman, Altaic, Hmong- populations. More recently, Zhong et al. (2011)also Mien, and southern Han populations to remove the influence suggested that some Y chromosome haplogroups were of relatively recent population admixture; the network then introduced in East Asia through postglacial colonization showed that the major STR haplotypes occurred in southern (around 18,000 years ago) from West Asia via a northern populations (Daic and Austroasiatic), leading them to route. Our recent analysis of the HLA polymorphism in support a southern origin of the O3-M122 lineage in East about 127,000 individuals of 84 populations also indicate Asia, with an age of about 25,000 to 30,000 years (see that when NEAS are accurately represented with no 162 Rice (2011) 4:159–169 preliminary exclusion of particular population samples, found in Central Asian populations (Comas et al. 1998, NEAS exhibit a higher level of internal diversity than SEAS, 2004;Hammeretal. 2001; Quintana-Murci et al. 2004; in agreement with Karafet et al. (2001) and Xue et al. (2006) Wells et al. 2001;Zerjal etal. 2002), compatible with their for the Y chromosome and with our own observations for connection to NEAS through gene flow, Central Asia being classical markers (not shown). In agreement with Zhong et considered either as a source (Wells et al. 2001) orasa al. (2011), this greater diversity is due in part to alleles and/or receiver (Comas et al. 1998, 2004; Quintana-Murci et al. lineages that are also observed in Central Asians (CAS), West 2004; Zerjaletal. 2002) of human migrations. Asian, and Europeans, whereas SEAS exhibit many lineages that are more specifically represented in East Asia. Then, Genetic variation in relation to linguistic diversity when only these “East Asian specific” markers are considered, southern populations are more diversified than northern Current methods in population genetics are not very populations. We conclude that the apparent discrepancies powerful in discriminating between geography and between the studies described above are due to differences in linguistics to explain the observed genetic patterns in either the sets of populations represented or the markers or East Asia, most of all because the distribution of lineages considered for the analyses. Overall, when all linguistic families itself is geographically structured populations and all markers are used, genetic diversity tends (Blench et al. 2008); actually, East Asian populations to be higher in the north. Now, to interpret these results (see tend to display genetic similarities according both to their next section), we have to bear in mind that a high level of linguistic relatedness and geographic proximity (Poloni et al. genetic diversity is not synonymous of an old population 2005; Sanchez-Mazas et al. 2005). However, some peculiar origin or differentiation but may also result from a greater results emerge depending on each linguistic family. permeability to gene flow from genetically diverse populations. This might have been the case for NEAS. Studies – Altaic: Altaic-proper (Altaic hereafter), Korean and Japanese generally segregate together at one end of performed on different genetic markers are indeed congru- ent in showing a genetic relationship with a rather multivariate analyses performed on East Asian popula- tions. However, Altaic populations differ significantly continuous pattern between NEAS and CAS, whereas from Japanese and Koreans. A remarkable result is the SEAS are more peculiar in relation to other geographic very high level of internal genetic diversity within areas. The link between NEAS and CAS is first illustrated Altaic populations at HLA loci, while inter-population by the more widespread distribution of some alleles/ diversity (F ) is relatively low (Sanchez-Mazas et al. lineages in NEAS, as described above. AMOVA analyses ST 2005). According to the predictions that we summa- are also relevant: for the Y chromosome data analyzed by rized in a previous paper (Sanchez-Mazas et al. 2005), Karafet et al. (2001), the among-group variance component these features suggest intensivegeneflowafter between CAS and NEAS is not statistically significant (Φct=0.04), whereas the highest value is found between differentiation from a highly diversified population. – Sino-Tibetan: for HLA, both Sinitic (Han) and Tibeto- SEAS and CAS (Φct=0.28), followed by the value between SEAS and NEAS (Φct=0.16). Clinal variation was observed Burman populations are geographically structured. Han populations are less diversified (lower F )than at classical markers by Barbujani et al. (1994) among Altaic ST Tibeto-Burman but a significant genetic boundary is populations extending over a large area encompassing CAS found between northern (mostly Mandarin-speakers) and NEAS, and by Karafet et al. (2001) in NEAS, while and southern (mostly speakers of Southern languages) random genetic variation is found among SEAS, even at Han populations (Di and Sanchez-Mazas 2011;Poloni small geographic distances. When considering pairwise et al. 2005), although Mandarin populations from differences among Y chromosome haplogroups, larger Southwest China show smaller genetic distances to values are found within NEAS populations, whereas 85% SEAS than to NEAS. According to Wen et al. of SEAS Y chromosomes belong to a few closely related haplogroups (e.g., M175); such a set of highly divergent (2004a), northern Han and southern Han also differ significantly for their maternal mtDNA lineages haplogroups observed in the north may reflect greater −5 contributions from different populations. Altogether, (F =0.006, P<10 ) but not for their paternal Y ST chromosome lineages (F =0.006, P>0.05). Northern these results indicate that the genetic pool of NEAS is ST Tibeto-Burman (Tujia and populations from Tibetan related to that of CAS and exhibits signatures of gene Plateau, i.e., Tibetan, Monba, Luoba, and Lachung) differ flow from multiple sources, while that of SEAS from southern Tibeto-Burman (mainly from Yunnan) for indicates greater isolation and population subdivision, HLA. For mtDNA and the Y chromosome, a sex-biased although with a low level of differentiation among pattern is also observed for Tibeto-Burman (Wen et al. populations. Another crucial result related to these observations is the very high level of genetic diversity 2004b). Rice (2011) 4:159–169 163 – Tai-Kadai and Hmong-Mien from East and Southeast diversity, several independent genetic studies present Asia: inter-population diversity is much higher in both opposite views regarding the geographic origin of this Tai-Kadai and Hmong-Mien than in Han according to haplotype, which has been suggested either in India the Y chromosome, and in Hmong-Mien for mtDNA (Basu et al. 2003; Kumar et al. 2007) or in Southeast (Wen et al. 2005). For HLA, the populations speaking Asia (Chaubey et al. 2011; Sahoo et al. 2006; Sengupta languages of these three linguistic phyla are related et al. 2006). genetically to each other and generally exhibit a low level of internal diversity (except, for example, Thai and Kinh) Times estimation (Di and Sanchez-Mazas 2011). They are also very close to each other according to GM and mtDNA, but more differentiated according to the Y chromosome (Poloni et A key issue in the reconstruction of human peopling history is dating the events related to past human migrations. al. 2005;Sanchez-Mazas 2008; Wen et al. 2004a). A Population genetics is rather limited in this field compared PCA performed at the individual level on the basis of to archaeology and paleoanthropology which can provide genome-wide autosomal SNPs discriminates relatively direct absolute dates of human settlements, although with well the speakers of these linguistic families (Abdulla et large confidence intervals. However, the genetic literature is al. 2009). full of absolute dates for human prehistory. The main reason is – Austroasiatic deserves a specific attention as this that geneticists use the molecular clock theory to infer the time linguistic family is widely distributed between North- to the most recent common ancestor (TMRCA) of each set of east India (in addition to a few other Indian regions like haplotypes clustered together (i.e., each haplogroup) in the Madhya Pradesh) and Southeast Asia. Populations molecular phylogenies obtained for uniparentally inherited speaking languages of different Austroasiatic branches are well differentiated from each other for mtDNA, mtDNA and Y chromosome genetic markers. Depending on differences in frequencies or molecular diversity, a geographic with a pronounced differentiation of the Indian Munda origin and a geographic spread are also often inferred for each which are genetically close to surrounding populations lineage (hence the term “phylogeography” for this kind of in India (Reddy and Kumar 2008). According to HLA, approach). the Munda exhibit a unique genetic profile with a rather Molecular dating may nevertheless result in contrasting low level of polymorphism (Riccio et al. 2011). estimations, as illustrated by some examples given below However, they share common genetic features with (see also Fig. 2): non-Austroasiatic populations in India (at all HLA loci), but also a few characteristics with Austroasiatic populations from Southeast Asia. The analysis of Y – According to Yao et al. (2002a), most mtDNA lineages chromosome markers indicates a high frequency of are very ancient in East Asia, with an age greater than haplogroup M95 (O2a) in Austroasiatic populations 50,000 years, the oldest ones being most frequent in the including the Munda (Chaubey et al. 2011; Kumar et south (81,000 and 75,000 years for R9 and B, al. 2007; Sengupta et al. 2006; Thangaraj et al. 2003). respectively). Thangaraj et al. (2006) also estimate an However, based on different levels of haplotypic old age of 46,300 (±10,900) years for the mtDNA Fig. 2 Some examples of con- trasting results for the dating of mtDNA and Y chromosome lineages (see text). EA East Asian, ky kilo-years, BP before present; confidence intervals are indicated within brackets. 164 Rice (2011) 4:159–169 lineage M31 observed in the Andaman Isles (Bay of sively admixed with Indian populations (Chaubey et al. Bengal). M31 would be derived from lineage M 2011). This latter view is in close agreement with our (TMRCA of 63,000 years) predominant in Eurasia, own results based on the HLA polymorphism (Riccio itself derived from haplogroup L3 which is believed to et al. 2011). originate in Africa 84,000 years ago. Based on these estimations, a rapid coastal dispersal from ∼65,000 years Besides phylogeography, another approach based on genetics to date past events is to estimate population ago around the Indian littoral is suggested (Macaulay et al. 2005). However, Barik et al. (2008) estimate a recent expansion times. This may be performed by using either distributions of pairwise nucleotidic differences among date for Andamanese-specific lineages M31a2 (<12,000 years) and only 24,000 years for lineages DNA sequences (“mismatch” distributions) assuming the shared between Andamanese and Indian populations infinite site mutation model (e.g., in the case of mtDNA (M31a). Based on multiplex SNP mtDNA typing, sequences) or other specific estimators (e.g., the variance in Endicott et al. (2006) also find a coalescent date of repeat length in the case of STR): about 30,000 years before present for the M31a mtDNA lineage shared by populations of the Andaman islands – Asian populations show signals of Pleistocene expan- and the Indian sub-continent. Moreover, by updating the sions about 70,000 years before present (73,000 with M31 phylogenetic tree, a much younger date was 95% confidence interval of 46,000–87,000 years) recently estimated by Wang et al. (2011) for M31a1 according to the mtDNA mismatch distributions analyzed (−7,960±3,910 years), suggesting that Andamanese by Excoffier and Schneider (1999), although the hetero- geneous composition of the “Asian” sample used in this arrived from Southeast Asia across a land-bridge around the Last Glacial Maximum (LGM), but that this study may have inflated the estimated date. Different haplogroup originated in northeast India. expansion times were obtained by Chaix et al. (2008) – On the basis of 19 Y chromosome biallelic loci, Su et depending on the mutation rates used for the analyses: al. (1999) estimate an age of 18,000 to 60,000 years for when using pedigree-based mutation rates, the authors the O-M122T→C mutation shared by “Asian-specific” find expansion times in East Asia of about 29,000– haplotypes H6–H8. However, using both morphologi- 30,000 years for mtDNA and 14,000–19,000 years for cal data analyzed by Turner (1993) and archaeological the Y chromosome; when using phylogeny-based evidence for early settlements in Siberia (Vasil’ev mutation rates, they obtain 61,000–63,000 years for 1993) and New Guinea (Brown et al. 1992; Swisher mtDNA and 31,000–40,000 years for the Y chromo- et al. 1996), they retain the upper boundary of some. In Central Asia, similar expansion times are found for the Y chromosome (16,000 and 36,000 years, 60,000 years for a bottleneck event leading to the entrance of modern humans into eastern Asia through a depending on the model), while slightly younger dates southern route. In contrast with this conclusion, Shi et are obtained for mtDNA (26,000 and 54,000 years). al. (2008, 2005) estimate an older northward expansion – East Asian male demographic history has also been of Y chromosome haplogroup D-M174 (60,000 years investigated by Xue et al. (2006) through a Bayesian full- ago) than the above-mentioned O-M122 haplogroup likelihood analysis to data from 988 men representing (25–30,000 years ago), after an origin in southern East 27 populations from China, Mongolia, Korea, and Japan Asia. An even younger estimate of 4,400 years before typed with 45 SNPs and 16 STR markers from the Y present (BP) was obtained for O-M122 in Balinese chromosome. The authors showed that the northern populations (Karafet et al. 2005). populations started to expand in number between 34,000 – As the Munda exhibit a high frequency and diversity of and 22,000 years ago, thus before the LGM, while the southern populations did so between 18,000 and Y chromosome M95 (O2a) haplotypes (Karafet et al. 2001; Kumar et al. 2007; Reddy and Kumar 2008; 12,000 years ago, but then grew faster. Sengupta et al. 2006; Su et al. 2000, 1999), the origin of the Austroasiatic phylum has been claimed to occur in India around 65,000 years BP according to the age Interpretation of genetic results and methodological estimated for this haplogroup (Kumar et al. 2007), by issues contrast to the young age of 8,800 years previously given by Kayser et al. (2003). More recently, an age of The genetic results described above have been the subject about 20,000 years has been established for O-M95, of multiple interpretations on the peopling history of East Asia. A long-standing debate is that of the first arrival of resulting in an opposite interpretation: Austroasiatic populations would have a Southeast Asian origin, and modern humans in East Asia after their expansion out of those migrating to Northeast India would have exten- Africa, either through a single southern route towards Rice (2011) 4:159–169 165 Southeast Asia with later migrations towards the north (Chu layer of human migrations in East Asia, which was then et al. 1998; Shi et al. 2005, 2008; Su et al. 1999), or taken as the unique migration event (the southern route). through two independent routes, a southern and a northern, Actually, northern populations are found to be genetically with later bi-directional migrations and admixture in East more diverse than southern populations, which of course Asia (pincer and overlapping models) (Cavalli-Sforza et al. does not mean that the peopling of Northeast Asia was 1994; Di and Sanchez-Mazas 2011; Ding et al. 2000; more ancient. Based on different genetic evidence, it merely Karafet et al. 2001; Xiao et al. 2000; Zhong et al. 2011). seems that this diversity reflects a network-like genetic Two kinds of genetic arguments have been used to sustain structure of northeast Asian populations in relation to the first hypothesis: a very old age for the M lineage in Central Asian populations, while Southeast Asia would Southeast Asia and its derivatives M31 and M32 in the have remained more isolated. A pincer or overlapping Andaman islands, and a greater genetic diversity in SEAS, model (Di and Sanchez-Mazas 2011) suggesting indepen- as compared to NEAS. dent migrations along a southern and a northern route, However, none of these arguments constitutes a defini- yet at distinct prehistoric periods (i.e., Paleolithic and tive proof. Firstly, as described above, very different post-glacial periods, respectively) is more compatible with the TMRCAs were obtained for M lineages (Fig. 2). Also, observed data. TMRCA estimates often display very large confidence A remarkable result of most studies cited above is the intervals and, unfortunately, non-genetic (e.g., archaeolog- very old dates inferred from phylogenetic studies for some ical) data are sometimes used to adopt a final estimation molecular lineages, although the estimated dates strongly closer to the upper or lower bond of the interval, as depend upon the method used (Blench et al. 2008). Given exemplified above for the age of the O-M122 T→C allele the estimated time ranges, the oldest dates inferred from (Fig. 2). Secondly, we have shown that the heterogeneity of genetic studies are compatible with old settlements of the sample sets used in different studies may explain modern humans in East Asia attested by fossil or contradictory results concerning the level of genetic archaeological remains (Fig. 3) (Chen et al. 1989; Mijares diversity of northern and southern populations, respectively, et al. 2010; Shang et al. 2007; Shen et al. 2002; Sun et al. with crucial consequences in this debate; in the two 2000; Vasil’ev 1993; Wu et al. 2006). However, ancient examples described above, the study design (in this case, molecular lineages may just represent limited heritages of the choice of the samples, where many northeast Asian undefined ancestral populations rather than real indications populations were excluded) was built according to non- on the origin and migration history of present populations. genetic (e.g., historical) information, thus matching the This illustrates very well one of the main methodological expected result, i.e., the identification of the most ancient problems discussed by Blench et al. (2008), the fact that Fig. 3 Possible route(s) of mod- ern human migrations towards East Asia according to different hypotheses proposed by geneti- cists (“pincer” or “overlapping” model: both the northern and the southern routes; “southern ori- gin” model: only the southern route), along with representative archaeological sites during the critical period (100,000– 20,000 BP), knowing that the shallow parts of the sea (light gray/blue on the map) were postulated as land area with the lower sea level of last ice age (Sun et al. 2000). References for the archaeological sites: Mal’ta: Vasil’ev (1993); Upper Cave: Chen et al. (1989); Tianyuan Cave: Shang et al. (2007); Huanglong Cave: Wu et al. (2006); Liujiang: Shen et al. (2002); Callao Cave: Mijares et al. (2010). 166 Rice (2011) 4:159–169 genetic tree nodes do not correspond to identifiable events between Mandarin and southern Chinese speakers, as pro- in population history, and are generally older than population posed by Sagart et al. (2005b) events. Then such dates might not be useful to depict The overall pattern of genetic variation in East Asia is yet extensive human migrations like those occurring in the continuous, characterized by many genetic clines along the Neolithic. This period was probably characterized by wide latitude, and, to a lesser extent, along the longitude between demographic expansions, long-range migrations and recurrent Central and Northeast Asia. It is tempting, of course, to relate gene flow between neighboring populations, and other kinds those clines to the expansion of specific linguistic families: of genetic signals should be explored. This is why specific e.g., Altaic, to explain the continuous pattern between CAS approaches capable of detecting demographic expansions and NEAS; and Sino-Tibetan, from the Yellow River in the have been used. Here again, however, very old dates have North to southwest and southern regions, corresponding been inferred, i.e., corresponding to Paleolithic times to the expansion of Tibeto-Burman and Sinitic-speakers, (∼70,000 years) or to different periods predating or closely respectively. However, to interpret genetic clines is delicate as following the LGM, but, in any case, older than the Neolithic. such clines may be explained by very different mechanisms Such signals may correspond, respectively, to the first (Fig. 4): demic diffusion with admixture between genetically expansion of modern humans throughout the world and to distinct populations (Ammerman and Cavalli-Sforza 1984), postglacial recolonizations, while more recent events would serial founder effects (Deshpande et al. 2009), isolation-by- not be easily disentangled by using such approaches. Note, distance where gene flow happens between neighboring however, that older signals of population expansions are populations (Novembre and Stephens 2008; Reich et al. detected for northern Asian populations (Xue et al. 2006), and 2008), or even differential adaptation to distinct environ- also for paternally rather than maternally inherited markers ments, including varying prevalence of infectious diseases (Chaix et al. 2008). These results may be relevant for further (Suo et al. 2011). In the current state of research, no inter-disciplinary studies. definitive conclusion on the genetic clines observed in East Descriptive approaches like PCA, MDS, spatial autocorre- Asia has been reached. This issue is yet crucial to understand lation analyses aiming at detecting genetic clines, specific the demographic impact of Neolithic migrations like those statistical analyses used to identify genetic boundaries, as well probably related to the expansion of linguistic families and/ as correlation analyses allowing the comparison of genetic or rice and millet domestication in East Asia. Also, specific variation with either geographic or linguistic data are still very models have to be considered to investigate the expansion useful to understand how the current genetic pool of East patterns of discontinuously dispersed linguistic families like Asian populations is structured. We have stressed the fact that Austroasiatic. Although several independent genetic studies the identification of genetic boundaries is highly dependent sustain a Southeast Asian origin of this family, with later migration to India where populations underwent intensive upon the sample set available for the analyses; that is, significant genetic barriers are susceptible to be detected gene flow, the evidence is still weak as no signals of such through uneven sampling along genetic clines! However, we scenario have been found for mtDNA. may conclude from the different studies cited above that the north to south continuous genetic pattern observed in East Asia crosses a region of sharper variation around the Yangtze Conclusion and perspectives or Huai Rivers; actually, as this boundary appears to be significant only when Han populations are considered, it may We have presented a brief summary of current genetic correspond to a recent (<1,500 years) linguistic subdivision evidence on the peopling history of East Asia by Fig. 4 Four different situations generating genetic clines (see text). Rice (2011) 4:159–169 167 Acknowledgments This work was supported by FNS (Switzerland) dissociating some raw genetic results from their inter- grants: 3100A0-112651 and 31003A_127465 to ASM, and by ESF pretation, and by pointing out some important method- COST (Europe) grant to Action BM0803. We warmly thank Dr. ological problems. A recurrent problem in all kinds of Laurent Sagart for his helpful comments. genetic studies is of course insufficiency in the set of Open Access This article is distributed under the terms of the population samples analyzed and one should be aware Creative Commons Attribution Noncommercial License which permits that this may have crucial consequences on the any noncommercial use, distribution, and reproduction in any medium, interpretation of the results. Also, misinterpretation provided the original author(s) and source are credited. may be due to ascertainment bias in the choice of markers. Another critical issue is the interpretation of molecular phylogenies and TMRCAs; to our view, such References genetic approaches are useful as long as they ask questions adapted to the data to which they apply, i.e., questions related to the genealogy of molecules and not Abdulla MA, Ahmed I, Assawamakin A, Bhak J, Brahmachari SK, Calacal GC, et al. 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A Genetic Focus on the Peopling History of East Asia: Critical Views

Rice , Volume 4 (4) – Dec 2, 2011

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Life Sciences; Plant Sciences; Plant Genetics & Genomics; Plant Breeding/Biotechnology; Agriculture; Plant Ecology
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Abstract

Rice (2011) 4:159–169 DOI 10.1007/s12284-011-9066-y A Genetic Focus on the Peopling History of East Asia: Critical Views Alicia Sanchez-Mazas & Da Di & María Eugenia Riccio Received: 24 October 2011 /Accepted: 2 November 2011 /Published online: 2 December 2011 The Author(s) 2011. This article is published with open access at Springerlink.com Abstract Population genetic studies may provide crucial MDS Multidimensional scaling analysis information for our knowledge on human peopling history AMOVA Analysis of molecular variance and have been extensively applied to reconstruct East Asian MRCA Most recent common ancestor prehistory in the last 10 years. However, different genetic NEAS Northeast Asian populations investigations are not always consistent with each other and SEAS Southeast Asian populations some results are conflicting or misinterpreted. This repre- CAS Central Asians sents a main obstacle for scholars of other disciplines like WAS West Asians archaeologists and linguists who try to relate the genetic information on past human migrations to their own results on the spread of domesticated crops or animals or on the Introduction dispersal of the main language families. In this paper, we review the current genetic evidence related to the peopling East Asia is a very large geographic area of the world history of East Asia with a critical view on some currently inhabited by more than 1.5 billion people, which interpretations. In this way, we hope to provide a useful represents about 22% of the world population. According to reference for further interdisciplinary studies on our past. the current fossil record and as supported by genetic evidence, it is likely that modern humans did not originate . . Keywords East Asia Genetic diversity Human peopling in East Asia (Jin and Su 2000). However, this vast . . . . history Genetic clines Genetic boundaries mtDNA continental region was probably settled very early in the . . . Y chromosomes HLA Pincer model Southern route Paleolithic when the first Homo sapiens spread throughout the world, presumably from East Africa; although southern Abbreviations Africa has recently been proposed as another possible HLA Human leucocyte antigen original homeland (Henn et al. 2011) and very early well- RH Rhesus dated skeletons are also known in the Levant (Stringer et al. GM IgG immunoglobulins’ genetic marker 1989). Old human fossil remains are yet very scarce in East SNPs Single-nucleotide polymorphisms Asia (with a very uncertain date of 68,000 years for the NRY Non-recombining portion of the Y chromosome most ancient fossil known to date, Liujiang, that was found mtDNA Mitochondrial DNA by chance (Shen et al. 2002)) and do not allow on their own STR Short tandem repeat to reconstruct East Asian prehistory. During the last PCA Principal component analysis decades, different disciplines, i.e., archaeology, linguistics and population genetics, have been involved together in the : : A. Sanchez-Mazas (*) D. Di M. E. Riccio reconstruction of human peopling history, bringing some Laboratory of Anthropology, Genetics and Peopling history, indisputable results but also revealing the extraordinary Anthropology Unit, Department of Genetics and Evolution, complexity of East Asian past human settlement history University of Geneva, (Sagart et al. 2005a; Sanchez-Mazas et al. 2008). As a Geneva, Switzerland matter of fact, distinct scenarios of human migrations in e-mail: alicia.sanchez-mazas@unige.ch 160 Rice (2011) 4:159–169 East Asia are still disputed today, like the first arrival of H. between northeastern and southeastern populations as sapiens from West Asia, either through a single southern route well, e.g., for mitochondrial DNA (mtDNA), A, C, D along the sea coast or through two independent routes via the and G haplogroups are more frequent in the north, while B southern and northern edges of the Himalayas. Also, human and F are more frequent in the south (Kivisild et al. 2002; population migrations in East Asia have been investigated in Stoneking and Delfin 2010; Yao et al. 2002). For the Y relation to the spread of agriculture and the main linguistic chromosome, northeastern and southeastern populations families, leading to quite different views on the subject. are clearly discriminated both in a principal component In this paper, our objective is to make clear the current analysis (PCA) using 19 non-recombining Y (NRY) genetic evidence related to East Asian peopling history. To markers (Su et al. 1999) and in a multidimensional scaling that aim, we have described the available information— analysis (MDS) using 52 markers (Karafet et al. 2001). including our own conclusions based on human leucocyte More recently, PCA based on genome-wide analyses of tens antigen (HLA) genetic studies—within two distinct sections of thousands of single-nucleotide polymorphisms (SNPs) to distinguish the raw genetic results from their interpretation, confirm that genetic differentiation vary principally with the latter being more subjective and open to criticism. We also latitude in East Asia (Abdulla et al. 2009; Suo et al. 2011). underline the major limitations of such genetic studies, as a complement to what was previously explained by Blench et Genetic boundaries versus continuous patterns al. (2008). Finally, we propose some perspectives in this area for future genetic studies. We hope that this clarification will Whereas NEAS and SEAS clearly exhibit contrasted genetic be useful to scholars of other disciplines who are often profiles, this result alone does not indicate how genetic confused by the very specialized and often contradictory diversity is structured among the two areas. The existence of a information provided by population genetics studies. clear-cut genetic boundary between northern and southern populations has been debated: based on classical markers, a boundary located at the vicinity of the Yangtze River has been Raw results from population genetic studies suggested (Du et al. 1997;Xiao etal. 2000; Xue et al. 2005). Several significant boundaries are found among northern and North–south genetic differentiations in East Asia southern Han populations according to mtDNA haplogroups, the sharpest genetic contrast appearing along Huai River and One of the most robust results found in genetic studies Qin Mountain that are north to Yangtze River, and two focusing on East Asian populations is the marked others south to Yangtze River and north to Yellow River, genetic differentiation between Northeast Asian and respectively (Xue et al. 2008). On the other hand, no Southeast Asian populations (NEAS and SEAS), respectively significant genetic barrier is found when both Han and non- (Cavalli-Sforza et al. 1994; Chu et al. 1998;Du etal. 1997; Han populations are included. An automatic search for a Xue et al. 2005). This general structure is observed for all genetic frontier has also been performed for HLA, with a genetic markers studied so far and is characterized either by similar result: a significant boundary emerges for HLA-A, - sharp differences of gene frequencies or by the occurrence of B, and -DRB1 only when Han populations alone are distinct genetic lineages. For classical markers, the best considered; in this case, the boundary appears near the specific examples are provided by the distribution of Rhesus Yangtze River (Di and Sanchez-Mazas 2011). Boundaries (RH) and IgG immunoglobulins’ genetic marker (GM) are also detected when using Y chromosome data but in a haplotypes showing very high frequencies of RH*R2, much more fragmented way with no significant uninterrupt- GM*1,17;21 and GM*1,2,17;21 in Northeast Asia, and ed barrier between north and south (Xue et al. 2008). Note RH*R1 and GM*1,3;5* in Southeast Asia (Poloni et al. that the significant level of genetic variation (Φct=0.16) 2005; Sanchez-Mazas 2008). Overall analyses on a set of observed by Karafet et al. (2001) between SEAS and NEAS classical markers have also shown such differentiations for the Y chromosome cannot be interpreted as a genetic (Cavalli-Sforza et al. 1994). At the HLA loci, distinct boundary as it is the result of an analysis of molecular alleles and/or allelic lineages display contrasted frequen- variance (AMOVA) with an a priori choice of the groups cies between NEAS and SEAS, leading to the definition of compared. Through genome-wide association studies, popu- “group 1” and “group 2” alleles (Di and Sanchez-Mazas lation substructure of Han populations into north, central and 2011). Through principal coordinate analyses, a general south subgroups is observed but with very small levels of differentiation between northern and southern populations genetic differentiation (Xu et al. 2009), thus resembling much is also observed at most HLA loci (HLA-A, -B, -C, - more a continuous pattern. Such continuity has clearly been DPB1, -DRB1) (Di and Sanchez-Mazas (2011) The north– put forward by Chen et al. (2009) using over 350,000 south differentiation of East Asian populations;inprepa- genome-wide autosomal SNPs in over 6,000 Han Chinese ration). Gender-specific polymorphisms show a contrast samples from ten provinces of China. Rice (2011) 4:159–169 161 Thus, except in some cases where only Han populations are considered, the genetic pattern of East Asian popula- tions is definitely not a sharp bipartite subdivision. On the contrary, many studies indicate the existence of genetic clines along the latitude. In addition to multidimensional scaling and/or spatial autocorrelation analyses, continuous patterns of gene frequencies have been evidenced by their correlation with latitude for several genetic markers, e.g., HLA (Di D, and Sanchez-Mazas A. 2011 In prep. The north-south differentiation of East Asian populations) and autosomal SNPs (Abdulla et al. 2009; Suo et al. 2011). Frequency clines were also observed for classical markers, e.g., RH and GM haplotypes (Poloni et al. 2005; Sanchez- Mazas 2008) and mtDNA haplogroups like F1, B, and D4 (Yao et al. 2002). North and south substructures This continuous pattern of genetic differentiations in East Asia is also characterized by changes in the levels of genetic diversity and substructure between NEAS and SEAS, although with a hard dispute between different Fig. 1 Graphs showing a high and significant correlation (indicated by authors. On the basis of 19 NRY markers, Su et al. (1999) the coefficient of determination R ) between the number of haplotypes detected and the number of individuals tested for the set of population claim that SEAS are more diversified than NEAS, while samples analyzed by Su et al. (1999) for Y chromosome markers. Top: Karafet et al. (2001) sustain the opposite view on the basis all population samples; bottom: after removing the two samples with of 52 NRY markers. Actually, Su et al. (1999) used more highest sample sizes (82 and 280 individuals, respectively). than two times as many SEAS (20) than NEAS (9); moreover, sample sizes are very small (less than 30 individuals) except in two cases (N=82 for one northern below). Similar methodological problems related to sampling Han and N=280 for one southern Han population), which is occurred in the study of Abdulla et al. (2009)based on clearly a source of bias: in this study, the number of autosomal SNPs; the authors found that haplotype diversity haplotypes detected is highly significantly correlated to the was strongly correlated with latitude (R =0.91, P< number of individuals tested (Fig. 1). 0.0001), with genetic diversity decreasing from south to Shi et al. (2005) reanalyzed Y chromosome markers and north. However, this result was obtained through an sustained Su et al.’s(1999) conclusions. However, because, analysis of 10 “combined” populations (1, Indonesian; 2, as they say, ∼80% of the Chinese ethnic populations live in Malay; 3, Philippine; 4, Thai; 5, Southern Chinese southern regions with inhabitation histories longer than minorities; 6, Southern Han Chinese; 7, Japanese and 3,000 years,(Wang 1994 citedbyShi et al. 2005), Korean; 8, Northern Han Chinese; 9, Northern Chinese populations from southern regions of China were overrep- minorities; and 10, Yakut), with Yakut as the only resented in their study: on the contrary, Hui, Uygur, and population representing Altaic in the north, and several Mongolian, which represented northern populations, were mixed population samples representing southern popula- removed from the analyses because they were considered as tions, the genetic diversity of which being then probably recently established (<1,000 years ago) with extensive inflated. By using a better population sampling, Xue et al. admixture with European and Central Asian populations (2006) found a higher STR diversity in the north than in (Wang 1994 cited by Shi et al. 2005). Likewise, the short the south, a finding that is not easily reconciled with a tandem repeat (STR) network shown in this work was largely or exclusively southern origin for the northern built after excluding the Tibeto-Burman, Altaic, Hmong- populations. More recently, Zhong et al. (2011)also Mien, and southern Han populations to remove the influence suggested that some Y chromosome haplogroups were of relatively recent population admixture; the network then introduced in East Asia through postglacial colonization showed that the major STR haplotypes occurred in southern (around 18,000 years ago) from West Asia via a northern populations (Daic and Austroasiatic), leading them to route. Our recent analysis of the HLA polymorphism in support a southern origin of the O3-M122 lineage in East about 127,000 individuals of 84 populations also indicate Asia, with an age of about 25,000 to 30,000 years (see that when NEAS are accurately represented with no 162 Rice (2011) 4:159–169 preliminary exclusion of particular population samples, found in Central Asian populations (Comas et al. 1998, NEAS exhibit a higher level of internal diversity than SEAS, 2004;Hammeretal. 2001; Quintana-Murci et al. 2004; in agreement with Karafet et al. (2001) and Xue et al. (2006) Wells et al. 2001;Zerjal etal. 2002), compatible with their for the Y chromosome and with our own observations for connection to NEAS through gene flow, Central Asia being classical markers (not shown). In agreement with Zhong et considered either as a source (Wells et al. 2001) orasa al. (2011), this greater diversity is due in part to alleles and/or receiver (Comas et al. 1998, 2004; Quintana-Murci et al. lineages that are also observed in Central Asians (CAS), West 2004; Zerjaletal. 2002) of human migrations. Asian, and Europeans, whereas SEAS exhibit many lineages that are more specifically represented in East Asia. Then, Genetic variation in relation to linguistic diversity when only these “East Asian specific” markers are considered, southern populations are more diversified than northern Current methods in population genetics are not very populations. We conclude that the apparent discrepancies powerful in discriminating between geography and between the studies described above are due to differences in linguistics to explain the observed genetic patterns in either the sets of populations represented or the markers or East Asia, most of all because the distribution of lineages considered for the analyses. Overall, when all linguistic families itself is geographically structured populations and all markers are used, genetic diversity tends (Blench et al. 2008); actually, East Asian populations to be higher in the north. Now, to interpret these results (see tend to display genetic similarities according both to their next section), we have to bear in mind that a high level of linguistic relatedness and geographic proximity (Poloni et al. genetic diversity is not synonymous of an old population 2005; Sanchez-Mazas et al. 2005). However, some peculiar origin or differentiation but may also result from a greater results emerge depending on each linguistic family. permeability to gene flow from genetically diverse populations. This might have been the case for NEAS. Studies – Altaic: Altaic-proper (Altaic hereafter), Korean and Japanese generally segregate together at one end of performed on different genetic markers are indeed congru- ent in showing a genetic relationship with a rather multivariate analyses performed on East Asian popula- tions. However, Altaic populations differ significantly continuous pattern between NEAS and CAS, whereas from Japanese and Koreans. A remarkable result is the SEAS are more peculiar in relation to other geographic very high level of internal genetic diversity within areas. The link between NEAS and CAS is first illustrated Altaic populations at HLA loci, while inter-population by the more widespread distribution of some alleles/ diversity (F ) is relatively low (Sanchez-Mazas et al. lineages in NEAS, as described above. AMOVA analyses ST 2005). According to the predictions that we summa- are also relevant: for the Y chromosome data analyzed by rized in a previous paper (Sanchez-Mazas et al. 2005), Karafet et al. (2001), the among-group variance component these features suggest intensivegeneflowafter between CAS and NEAS is not statistically significant (Φct=0.04), whereas the highest value is found between differentiation from a highly diversified population. – Sino-Tibetan: for HLA, both Sinitic (Han) and Tibeto- SEAS and CAS (Φct=0.28), followed by the value between SEAS and NEAS (Φct=0.16). Clinal variation was observed Burman populations are geographically structured. Han populations are less diversified (lower F )than at classical markers by Barbujani et al. (1994) among Altaic ST Tibeto-Burman but a significant genetic boundary is populations extending over a large area encompassing CAS found between northern (mostly Mandarin-speakers) and NEAS, and by Karafet et al. (2001) in NEAS, while and southern (mostly speakers of Southern languages) random genetic variation is found among SEAS, even at Han populations (Di and Sanchez-Mazas 2011;Poloni small geographic distances. When considering pairwise et al. 2005), although Mandarin populations from differences among Y chromosome haplogroups, larger Southwest China show smaller genetic distances to values are found within NEAS populations, whereas 85% SEAS than to NEAS. According to Wen et al. of SEAS Y chromosomes belong to a few closely related haplogroups (e.g., M175); such a set of highly divergent (2004a), northern Han and southern Han also differ significantly for their maternal mtDNA lineages haplogroups observed in the north may reflect greater −5 contributions from different populations. Altogether, (F =0.006, P<10 ) but not for their paternal Y ST chromosome lineages (F =0.006, P>0.05). Northern these results indicate that the genetic pool of NEAS is ST Tibeto-Burman (Tujia and populations from Tibetan related to that of CAS and exhibits signatures of gene Plateau, i.e., Tibetan, Monba, Luoba, and Lachung) differ flow from multiple sources, while that of SEAS from southern Tibeto-Burman (mainly from Yunnan) for indicates greater isolation and population subdivision, HLA. For mtDNA and the Y chromosome, a sex-biased although with a low level of differentiation among pattern is also observed for Tibeto-Burman (Wen et al. populations. Another crucial result related to these observations is the very high level of genetic diversity 2004b). Rice (2011) 4:159–169 163 – Tai-Kadai and Hmong-Mien from East and Southeast diversity, several independent genetic studies present Asia: inter-population diversity is much higher in both opposite views regarding the geographic origin of this Tai-Kadai and Hmong-Mien than in Han according to haplotype, which has been suggested either in India the Y chromosome, and in Hmong-Mien for mtDNA (Basu et al. 2003; Kumar et al. 2007) or in Southeast (Wen et al. 2005). For HLA, the populations speaking Asia (Chaubey et al. 2011; Sahoo et al. 2006; Sengupta languages of these three linguistic phyla are related et al. 2006). genetically to each other and generally exhibit a low level of internal diversity (except, for example, Thai and Kinh) Times estimation (Di and Sanchez-Mazas 2011). They are also very close to each other according to GM and mtDNA, but more differentiated according to the Y chromosome (Poloni et A key issue in the reconstruction of human peopling history is dating the events related to past human migrations. al. 2005;Sanchez-Mazas 2008; Wen et al. 2004a). A Population genetics is rather limited in this field compared PCA performed at the individual level on the basis of to archaeology and paleoanthropology which can provide genome-wide autosomal SNPs discriminates relatively direct absolute dates of human settlements, although with well the speakers of these linguistic families (Abdulla et large confidence intervals. However, the genetic literature is al. 2009). full of absolute dates for human prehistory. The main reason is – Austroasiatic deserves a specific attention as this that geneticists use the molecular clock theory to infer the time linguistic family is widely distributed between North- to the most recent common ancestor (TMRCA) of each set of east India (in addition to a few other Indian regions like haplotypes clustered together (i.e., each haplogroup) in the Madhya Pradesh) and Southeast Asia. Populations molecular phylogenies obtained for uniparentally inherited speaking languages of different Austroasiatic branches are well differentiated from each other for mtDNA, mtDNA and Y chromosome genetic markers. Depending on differences in frequencies or molecular diversity, a geographic with a pronounced differentiation of the Indian Munda origin and a geographic spread are also often inferred for each which are genetically close to surrounding populations lineage (hence the term “phylogeography” for this kind of in India (Reddy and Kumar 2008). According to HLA, approach). the Munda exhibit a unique genetic profile with a rather Molecular dating may nevertheless result in contrasting low level of polymorphism (Riccio et al. 2011). estimations, as illustrated by some examples given below However, they share common genetic features with (see also Fig. 2): non-Austroasiatic populations in India (at all HLA loci), but also a few characteristics with Austroasiatic populations from Southeast Asia. The analysis of Y – According to Yao et al. (2002a), most mtDNA lineages chromosome markers indicates a high frequency of are very ancient in East Asia, with an age greater than haplogroup M95 (O2a) in Austroasiatic populations 50,000 years, the oldest ones being most frequent in the including the Munda (Chaubey et al. 2011; Kumar et south (81,000 and 75,000 years for R9 and B, al. 2007; Sengupta et al. 2006; Thangaraj et al. 2003). respectively). Thangaraj et al. (2006) also estimate an However, based on different levels of haplotypic old age of 46,300 (±10,900) years for the mtDNA Fig. 2 Some examples of con- trasting results for the dating of mtDNA and Y chromosome lineages (see text). EA East Asian, ky kilo-years, BP before present; confidence intervals are indicated within brackets. 164 Rice (2011) 4:159–169 lineage M31 observed in the Andaman Isles (Bay of sively admixed with Indian populations (Chaubey et al. Bengal). M31 would be derived from lineage M 2011). This latter view is in close agreement with our (TMRCA of 63,000 years) predominant in Eurasia, own results based on the HLA polymorphism (Riccio itself derived from haplogroup L3 which is believed to et al. 2011). originate in Africa 84,000 years ago. Based on these estimations, a rapid coastal dispersal from ∼65,000 years Besides phylogeography, another approach based on genetics to date past events is to estimate population ago around the Indian littoral is suggested (Macaulay et al. 2005). However, Barik et al. (2008) estimate a recent expansion times. This may be performed by using either distributions of pairwise nucleotidic differences among date for Andamanese-specific lineages M31a2 (<12,000 years) and only 24,000 years for lineages DNA sequences (“mismatch” distributions) assuming the shared between Andamanese and Indian populations infinite site mutation model (e.g., in the case of mtDNA (M31a). Based on multiplex SNP mtDNA typing, sequences) or other specific estimators (e.g., the variance in Endicott et al. (2006) also find a coalescent date of repeat length in the case of STR): about 30,000 years before present for the M31a mtDNA lineage shared by populations of the Andaman islands – Asian populations show signals of Pleistocene expan- and the Indian sub-continent. Moreover, by updating the sions about 70,000 years before present (73,000 with M31 phylogenetic tree, a much younger date was 95% confidence interval of 46,000–87,000 years) recently estimated by Wang et al. (2011) for M31a1 according to the mtDNA mismatch distributions analyzed (−7,960±3,910 years), suggesting that Andamanese by Excoffier and Schneider (1999), although the hetero- geneous composition of the “Asian” sample used in this arrived from Southeast Asia across a land-bridge around the Last Glacial Maximum (LGM), but that this study may have inflated the estimated date. Different haplogroup originated in northeast India. expansion times were obtained by Chaix et al. (2008) – On the basis of 19 Y chromosome biallelic loci, Su et depending on the mutation rates used for the analyses: al. (1999) estimate an age of 18,000 to 60,000 years for when using pedigree-based mutation rates, the authors the O-M122T→C mutation shared by “Asian-specific” find expansion times in East Asia of about 29,000– haplotypes H6–H8. However, using both morphologi- 30,000 years for mtDNA and 14,000–19,000 years for cal data analyzed by Turner (1993) and archaeological the Y chromosome; when using phylogeny-based evidence for early settlements in Siberia (Vasil’ev mutation rates, they obtain 61,000–63,000 years for 1993) and New Guinea (Brown et al. 1992; Swisher mtDNA and 31,000–40,000 years for the Y chromo- et al. 1996), they retain the upper boundary of some. In Central Asia, similar expansion times are found for the Y chromosome (16,000 and 36,000 years, 60,000 years for a bottleneck event leading to the entrance of modern humans into eastern Asia through a depending on the model), while slightly younger dates southern route. In contrast with this conclusion, Shi et are obtained for mtDNA (26,000 and 54,000 years). al. (2008, 2005) estimate an older northward expansion – East Asian male demographic history has also been of Y chromosome haplogroup D-M174 (60,000 years investigated by Xue et al. (2006) through a Bayesian full- ago) than the above-mentioned O-M122 haplogroup likelihood analysis to data from 988 men representing (25–30,000 years ago), after an origin in southern East 27 populations from China, Mongolia, Korea, and Japan Asia. An even younger estimate of 4,400 years before typed with 45 SNPs and 16 STR markers from the Y present (BP) was obtained for O-M122 in Balinese chromosome. The authors showed that the northern populations (Karafet et al. 2005). populations started to expand in number between 34,000 – As the Munda exhibit a high frequency and diversity of and 22,000 years ago, thus before the LGM, while the southern populations did so between 18,000 and Y chromosome M95 (O2a) haplotypes (Karafet et al. 2001; Kumar et al. 2007; Reddy and Kumar 2008; 12,000 years ago, but then grew faster. Sengupta et al. 2006; Su et al. 2000, 1999), the origin of the Austroasiatic phylum has been claimed to occur in India around 65,000 years BP according to the age Interpretation of genetic results and methodological estimated for this haplogroup (Kumar et al. 2007), by issues contrast to the young age of 8,800 years previously given by Kayser et al. (2003). More recently, an age of The genetic results described above have been the subject about 20,000 years has been established for O-M95, of multiple interpretations on the peopling history of East Asia. A long-standing debate is that of the first arrival of resulting in an opposite interpretation: Austroasiatic populations would have a Southeast Asian origin, and modern humans in East Asia after their expansion out of those migrating to Northeast India would have exten- Africa, either through a single southern route towards Rice (2011) 4:159–169 165 Southeast Asia with later migrations towards the north (Chu layer of human migrations in East Asia, which was then et al. 1998; Shi et al. 2005, 2008; Su et al. 1999), or taken as the unique migration event (the southern route). through two independent routes, a southern and a northern, Actually, northern populations are found to be genetically with later bi-directional migrations and admixture in East more diverse than southern populations, which of course Asia (pincer and overlapping models) (Cavalli-Sforza et al. does not mean that the peopling of Northeast Asia was 1994; Di and Sanchez-Mazas 2011; Ding et al. 2000; more ancient. Based on different genetic evidence, it merely Karafet et al. 2001; Xiao et al. 2000; Zhong et al. 2011). seems that this diversity reflects a network-like genetic Two kinds of genetic arguments have been used to sustain structure of northeast Asian populations in relation to the first hypothesis: a very old age for the M lineage in Central Asian populations, while Southeast Asia would Southeast Asia and its derivatives M31 and M32 in the have remained more isolated. A pincer or overlapping Andaman islands, and a greater genetic diversity in SEAS, model (Di and Sanchez-Mazas 2011) suggesting indepen- as compared to NEAS. dent migrations along a southern and a northern route, However, none of these arguments constitutes a defini- yet at distinct prehistoric periods (i.e., Paleolithic and tive proof. Firstly, as described above, very different post-glacial periods, respectively) is more compatible with the TMRCAs were obtained for M lineages (Fig. 2). Also, observed data. TMRCA estimates often display very large confidence A remarkable result of most studies cited above is the intervals and, unfortunately, non-genetic (e.g., archaeolog- very old dates inferred from phylogenetic studies for some ical) data are sometimes used to adopt a final estimation molecular lineages, although the estimated dates strongly closer to the upper or lower bond of the interval, as depend upon the method used (Blench et al. 2008). Given exemplified above for the age of the O-M122 T→C allele the estimated time ranges, the oldest dates inferred from (Fig. 2). Secondly, we have shown that the heterogeneity of genetic studies are compatible with old settlements of the sample sets used in different studies may explain modern humans in East Asia attested by fossil or contradictory results concerning the level of genetic archaeological remains (Fig. 3) (Chen et al. 1989; Mijares diversity of northern and southern populations, respectively, et al. 2010; Shang et al. 2007; Shen et al. 2002; Sun et al. with crucial consequences in this debate; in the two 2000; Vasil’ev 1993; Wu et al. 2006). However, ancient examples described above, the study design (in this case, molecular lineages may just represent limited heritages of the choice of the samples, where many northeast Asian undefined ancestral populations rather than real indications populations were excluded) was built according to non- on the origin and migration history of present populations. genetic (e.g., historical) information, thus matching the This illustrates very well one of the main methodological expected result, i.e., the identification of the most ancient problems discussed by Blench et al. (2008), the fact that Fig. 3 Possible route(s) of mod- ern human migrations towards East Asia according to different hypotheses proposed by geneti- cists (“pincer” or “overlapping” model: both the northern and the southern routes; “southern ori- gin” model: only the southern route), along with representative archaeological sites during the critical period (100,000– 20,000 BP), knowing that the shallow parts of the sea (light gray/blue on the map) were postulated as land area with the lower sea level of last ice age (Sun et al. 2000). References for the archaeological sites: Mal’ta: Vasil’ev (1993); Upper Cave: Chen et al. (1989); Tianyuan Cave: Shang et al. (2007); Huanglong Cave: Wu et al. (2006); Liujiang: Shen et al. (2002); Callao Cave: Mijares et al. (2010). 166 Rice (2011) 4:159–169 genetic tree nodes do not correspond to identifiable events between Mandarin and southern Chinese speakers, as pro- in population history, and are generally older than population posed by Sagart et al. (2005b) events. Then such dates might not be useful to depict The overall pattern of genetic variation in East Asia is yet extensive human migrations like those occurring in the continuous, characterized by many genetic clines along the Neolithic. This period was probably characterized by wide latitude, and, to a lesser extent, along the longitude between demographic expansions, long-range migrations and recurrent Central and Northeast Asia. It is tempting, of course, to relate gene flow between neighboring populations, and other kinds those clines to the expansion of specific linguistic families: of genetic signals should be explored. This is why specific e.g., Altaic, to explain the continuous pattern between CAS approaches capable of detecting demographic expansions and NEAS; and Sino-Tibetan, from the Yellow River in the have been used. Here again, however, very old dates have North to southwest and southern regions, corresponding been inferred, i.e., corresponding to Paleolithic times to the expansion of Tibeto-Burman and Sinitic-speakers, (∼70,000 years) or to different periods predating or closely respectively. However, to interpret genetic clines is delicate as following the LGM, but, in any case, older than the Neolithic. such clines may be explained by very different mechanisms Such signals may correspond, respectively, to the first (Fig. 4): demic diffusion with admixture between genetically expansion of modern humans throughout the world and to distinct populations (Ammerman and Cavalli-Sforza 1984), postglacial recolonizations, while more recent events would serial founder effects (Deshpande et al. 2009), isolation-by- not be easily disentangled by using such approaches. Note, distance where gene flow happens between neighboring however, that older signals of population expansions are populations (Novembre and Stephens 2008; Reich et al. detected for northern Asian populations (Xue et al. 2006), and 2008), or even differential adaptation to distinct environ- also for paternally rather than maternally inherited markers ments, including varying prevalence of infectious diseases (Chaix et al. 2008). These results may be relevant for further (Suo et al. 2011). In the current state of research, no inter-disciplinary studies. definitive conclusion on the genetic clines observed in East Descriptive approaches like PCA, MDS, spatial autocorre- Asia has been reached. This issue is yet crucial to understand lation analyses aiming at detecting genetic clines, specific the demographic impact of Neolithic migrations like those statistical analyses used to identify genetic boundaries, as well probably related to the expansion of linguistic families and/ as correlation analyses allowing the comparison of genetic or rice and millet domestication in East Asia. Also, specific variation with either geographic or linguistic data are still very models have to be considered to investigate the expansion useful to understand how the current genetic pool of East patterns of discontinuously dispersed linguistic families like Asian populations is structured. We have stressed the fact that Austroasiatic. Although several independent genetic studies the identification of genetic boundaries is highly dependent sustain a Southeast Asian origin of this family, with later migration to India where populations underwent intensive upon the sample set available for the analyses; that is, significant genetic barriers are susceptible to be detected gene flow, the evidence is still weak as no signals of such through uneven sampling along genetic clines! However, we scenario have been found for mtDNA. may conclude from the different studies cited above that the north to south continuous genetic pattern observed in East Asia crosses a region of sharper variation around the Yangtze Conclusion and perspectives or Huai Rivers; actually, as this boundary appears to be significant only when Han populations are considered, it may We have presented a brief summary of current genetic correspond to a recent (<1,500 years) linguistic subdivision evidence on the peopling history of East Asia by Fig. 4 Four different situations generating genetic clines (see text). Rice (2011) 4:159–169 167 Acknowledgments This work was supported by FNS (Switzerland) dissociating some raw genetic results from their inter- grants: 3100A0-112651 and 31003A_127465 to ASM, and by ESF pretation, and by pointing out some important method- COST (Europe) grant to Action BM0803. We warmly thank Dr. ological problems. A recurrent problem in all kinds of Laurent Sagart for his helpful comments. genetic studies is of course insufficiency in the set of Open Access This article is distributed under the terms of the population samples analyzed and one should be aware Creative Commons Attribution Noncommercial License which permits that this may have crucial consequences on the any noncommercial use, distribution, and reproduction in any medium, interpretation of the results. Also, misinterpretation provided the original author(s) and source are credited. may be due to ascertainment bias in the choice of markers. Another critical issue is the interpretation of molecular phylogenies and TMRCAs; to our view, such References genetic approaches are useful as long as they ask questions adapted to the data to which they apply, i.e., questions related to the genealogy of molecules and not Abdulla MA, Ahmed I, Assawamakin A, Bhak J, Brahmachari SK, Calacal GC, et al. 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