Genetic structure, divergence and admixture of Han Chinese, Japanese and Korean populations


Open access Genetic structure, divergence and admixture of Han Chinese, Japanese and Korean populations, by Wang, Lu, Chung, and Xu, Hereditas (2018) 155:19.

Abstract (emphasis mine):

Han Chinese, Japanese and Korean, the three major ethnic groups of East Asia, share many similarities in appearance, language and culture etc., but their genetic relationships, divergence times and subsequent genetic exchanges have not been well studied.

We conducted a genome-wide study and evaluated the population structure of 182 Han Chinese, 90 Japanese and 100 Korean individuals, together with the data of 630 individuals representing 8 populations wordwide. Our analyses revealed that Han Chinese, Japanese and Korean populations have distinct genetic makeup and can be well distinguished based on either the genome wide data or a panel of ancestry informative markers (AIMs). Their genetic structure corresponds well to their geographical distributions, indicating geographical isolation played a critical role in driving population differentiation in East Asia. The most recent common ancestor of the three populations was dated back to 3000 ~ 3600 years ago. Our analyses also revealed substantial admixture within the three populations which occurred subsequent to initial splits, and distinct gene introgression from surrounding populations, of which northern ancestral component is dominant.

These estimations and findings facilitate to understanding population history and mechanism of human genetic diversity in East Asia, and have implications for both evolutionary and medical studies.

Population level phylogenetic Tree and Principal component analysis (PCA). (A) The maximum likelihood tree was constructed based on pair-wise FST matrix. And the marked number are bootstrap value; (B) The top two PCs of individuals representing six East Asian populations, mapped to their corresponding geographic locations (generated by R 2.15.2 and Microsoft Excel 2010)

Interesting excerpts:

It is obvious that the genetic difference among the three East Asian groups initially resulted from population divergence due to pre-historical or historical migrations. Subsequently, different geographical locations where the three populations are located, mainland of China, Korean Peninsular and Japanese archipelago, respectively, apparently facilitated population differentiation due to physical isolation and independent genetic drift. Our estimations of population divergence time among the three groups, 1.2~ 3.6 KYA, are largely consistent with known history of the three populations and those related. However, considering that recent admixture could have reduced genetic difference between populations, it is likely the divergence time was underestimated.

We detected substantial gene flow among the three populations and also from the surrounding populations. For example, based on our analysis with the F3 test, Korean received gene flow from Han Chinese and Japanese, and gene flow also happened between Han Chinese and Japanese (Additional file 12: Table S3). These gene flows are expected to have reduced the genetic differentiation between the three ethnic groups. On the other hand, we also detected considerable gene flow from surrounding populations to the three populations studied. For instance, an ancestral population represented by Ryukyuan have contributed greater to Japanese than to Han Chinese, while southern ethnic group like Dai have contributed more to continent populations than to island and peninsula populations. Contrary to the gene flow among the three populations, these gene flows from surrounding populations are expected to have increased genetic difference among the three populations if they occurred independently and from different source populations. According to our results, the major source of gene flow to the three ethnic groups were substantially different, for example, the major source of gene flow to Han Chinese was from southern ethnic groups, the major source of gene flow to Japanese was from southern islands, and the major source of gene flow to Korean were from both mainland and islands. Therefore, those gene flows might have significantly contributed to further genetic differentiation of the three populations.

The three populations have similar but not identical demographical history; they all experience a strong population expansion in the last 20,000 years. However, according to different geographic distribution, their effective population size and population expansion are different.

Although based on modern populations, the study is interesting in light of the potential implications for a Macro-Altaic proposal.


Statistical methods fashionable again in Linguistics: Reconstructing Proto-Australian dialects

Reconstructing remote relationships – Proto-Australian noun class prefixation, by Mark Harvey & Robert Mailhammer, Diachronica (2017) 34(4): 470–515


Evaluation of hypotheses on genetic relationships depends on two factors: database size and criteria on correspondence quality. For hypotheses on remote relationships, databases are often small. Therefore, detailed consideration of criteria on correspondence quality is important. Hypotheses on remote relationships commonly involve greater geographical and temporal ranges. Consequently, we propose that there are two factors which are likely to play a greater role in comparing hypotheses of chance, contact and inheritance for remote relationships: (i) spatial distribution of corresponding forms; and (ii) language specific unpredictability in related paradigms. Concentrated spatial distributions disfavour hypotheses of chance, and discontinuous distributions disfavour contact hypotheses, whereas hypotheses of inheritance may accommodate both. Higher levels of language-specific unpredictability favour remote over recent transmission. We consider a remote relationship hypothesis, the Proto-Australian hypothesis. We take noun class prefixation as a test dataset for evaluating this hypothesis against these two criteria, and we show that inheritance is favoured over chance and contact.

I was redirected to this work by my wife – who discovered it reading BBC News – , suspicious of its potential glottochronological content. However, I must say – speaking from my absolute ignorance of the main language family investigated – , that it seemed in general an interesting read, with some thorough discussion and attention to detail.

The statistical analyses, however, seem to disrupt the content, and – in my opinion – do not help support its conclusions.

Map of Non-Pama-Nyungan languages.

Computer Science and Linguistics

We are evidently on alert to tackle dubious research, because of the revival of pseudoscientific methods in linguistic investigation, promoted (yet again) by Nature.

It seems that journals with the highest impact factor, in their search for groundbreaking conclusions supported by any methods involving numbers, are setting a still lower level of standards for academic disciplines.

NOTE. If you think about it – if glottochronology has survived the disgrace it fell into in the 2000s, to come back again now to the top of the publishing industry… How can we expect the “Yamnaya ancestry” concept to be overcome? I guess we will still see certain Eastern Europeans in 2030 arguing for elevated steppe ancestry here and there to support the conclusions of the 2015 papers, no matter what…

I am sure that worse times lie ahead for traditional comparative grammar. For example, it seems that there will be more publications on Proto-Indo-European using novel computer methods: a group led by Janhunen and Pyysalo, from the Department of Languages at the University of Helsinki, promises – under an ever-growing bubble of mistery (or so it seems from their Twitter and Facebook accounts) – a machine-implemented reconstruction (with the generative etymological PIE lexicon project) that will once and for all solve all our previous ‘inconsistencies’…

Spoiler alert for their publications: whether they select to go on mainly with computer-implemented methods, or they use them to support more traditional results, their conclusions will confirm (surprise!) their authors’ previous reactionary theses, such as a renewed support for the traditional monolaryngealism, and a rejection of Kortlandt’s or Kloekhorst’s (i.e. the Leiden School’s) theories on Proto-Indo-European phonology, and thus a PIE relationship to Proto-Uralic, probably stressing yet again an independent origin for both proto-languages.

See also:

Model for the spread of Transeurasian (Macro-Altaic) communities with farming


Austronesian influence and Transeurasian ancestry in Japanese: A case of farming/language dispersal, by Martine Robbeets, Max Planck Institute for the Science of Human History.


In this paper, I propose a hypothesis reconciling Austronesian influence and Transeurasian ancestry in the Japanese language, explaining the spread of the Japanic languages through farming dispersal. To this end, I identify the original speech community of the Transeurasian language family as the Neolithic Xinglongwa culture situated in the West Liao River Basin in the sixth millennium bc. I argue that the separation of the Japanic branch from the other Transeurasian languages and its spread to the Japanese Islands can be understood as occurring in connection with the dispersal of millet agriculture and its subsequent integration with rice agriculture. I further suggest that a prehistorical layer of borrowings related to rice agriculture entered Japanic from a sister language of proto-Austronesian, at a time when both language families were still situated in the Shandong-Liaodong interaction sphere.

Classification of the Transeurasian languages according to Robbeets ( forthcoming)

Another interesting anthropological model to validate with future genomic analyses, although I was never convinced about a grouping (let alone reconstructible proto-language) beyond Micro-Altaic languages.

NOTE. The Max Planck Institute may be a great source of scientific advancement, but in Linguistics you can see from the projects Indo-European languages originate in Anatolia (2012) and A massive migration from the steppe brought Indo-European languages to Europe (2015) (the last one referring to the Corded Ware culture, associated with the study by Haak et al. 2015) that they have not got it quite right with Proto-Indo-European… I like the traditional approach of this paper, though, including a thorough assessment of archaeological and linguistic details.

Featured images: Left. The eastward spread of millet agriculture in association with ancestral speech communities. Right: The spread of agriculture and language to Japan.

See also:

Expansion of peoples associated with spread of haplogroups: Mongols and C3*-F3918, Arabs and E-M183 (M81)


The expansion of peoples is known to be associated with the spread of a certain admixture component, joint with the expansion and reduction in variability of a haplogroup. In other words, few male lineages are usually more successful during the expansion.

Known examples include:

Two recent interesting papers add prehistoric cases of potential expansion of cultures associated with haplogroups:

1. Whole Y-chromosome sequences reveal an extremely recent origin of the most common North African paternal lineage E-M183 (M81), by Solé-Morata et al., Scientific Reports (2017).


E-M183 (E-M81) is the most frequent paternal lineage in North Africa and thus it must be considered to explore past historical and demographical processes. Here, by using whole Y chromosome sequences from 32 North African individuals, we have identified five new branches within E-M183. The validation of these variants in more than 200 North African samples, from which we also have information of 13 Y-STRs, has revealed a strong resemblance among E-M183 Y-STR haplotypes that pointed to a rapid expansion of this haplogroup. Moreover, for the first time, by using both SNP and STR data, we have provided updated estimates of the times-to-the-most-recent-common-ancestor (TMRCA) for E-M183, which evidenced an extremely recent origin of this haplogroup (2,000–3,000 ya). Our results also showed a lack of population structure within the E-M183 branch, which could be explained by the recent and rapid expansion of this haplogroup. In spite of a reduction in STR heterozygosity towards the West, which would point to an origin in the Near East, ancient DNA evidence together with our TMRCA estimates point to a local origin of E-M183 in NW Africa.

Distribution of E-M183 subclades among North Africa, the Near East and the Iberian Peninsula. Pie chart sectors areas are proportional to haplogroup frequency and are coloured according to haplogroup in the schematic tree to the right. n: sample size. Map was generated using R software.

An interesting excerpt, from the discussion:

Regarding the geographical origin of E-M183, a previous study suggested that an expansion from the Near East could explain the observed east-west cline of genetic variation that extends into the Near East. Indeed, our results also showed a reduction in STR heterozygosity towards the West, which may be taken to support the hypothesis of an expansion from the Near East. In addition, previous studies based on genome-wide SNPs reported that a North African autochthonous component increase towards the West whereas the Near Eastern decreases towards the same direction, which again support an expansion from the Near East. However, our correlations should be taken carefully because our analysis includes only six locations on the longitudinal axis, none from the Near East. As a result, we do not have sufficient statistical power to confirm a Near Eastern origin. In addition, rather than showing a west-to-east cline of genetic diversity, the overall picture shown by this correlation analysis evidences just low genetic diversity in Western Sahara, which indeed could be also caused by the small sample size (n = 26) in this region. Alternatively, given the high frequency of E-M183 in the Maghreb, a local origin of E-M183 in NW Africa could be envisaged, which would fit the clear pattern of longitudinal isolation by distance reported in genome-wide studies. Moreover, the presence of autochthonous North African E-M81 lineages in the indigenous population of the Canary Islands, strongly points to North Africa as the most probable origin of the Guanche ancestors. This, together with the fact that the oldest indigenous inviduals have been dated 2210 ± 60 ya, supports a local origin of E-M183 in NW Africa. Within this scenario, it is also worth to mention that the paternal lineage of an early Neolithic Moroccan individual appeared to be distantly related to the typically North African E-M81 haplogroup30, suggesting again a NW African origin of E-M183. A local origin of E-M183 in NW Africa > 2200 ya is supported by our TMRCA estimates, which can be taken as 2,000–3,000, depending on the data, methods, and mutation rates used.

The TMRCA estimates of a certain haplogroup and its subbranches provide some constraints on the times of their origin and spread. Although our time estimates for E-M78 are slightly different depending on the mutation rate used, their confidence intervals overlap and the dates obtained are in agreement with those obtained by Trombetta et al Regarding E-M183, as mentioned above, we cannot discard an expansion from the Near East and, if so, according to our time estimates, it could have been brought by the Islamic expansion on the 7th century, but definitely not with the Neolithic expansion, which appeared in NW Africa ~7400 BP and may have featured a strong Epipaleolithic persistence. Moreover, such a recent appearance of E-M183 in NW Africa would fit with the patterns observed in the rest of the genome, where an extensive, male-biased Near Eastern admixture event is registered ~1300 ya, coincidental with the Arab expansion. An alternative hypothesis would involve that E-M183 was originated somewhere in Northwest Africa and then spread through all the region. Our time estimates for the origin of this haplogroup overlap with the end of the third Punic War (146 BCE), when Carthage (in current Tunisia) was defeated and destroyed, which marked the beginning of Roman hegemony of the Mediterranean Sea. About 2,000 ya North Africa was one of the wealthiest Roman provinces and E-M183 may have experienced the resulting population growth.

2. The Y-chromosome haplogroup C3*-F3918, likely attributed to the Mongol Empire, can be traced to a 2500-year-old nomadic group, by Zhang et al., Journal of Human Genetics (2017)


The Mongol Empire had a significant role in shaping the landscape of modern populations. Many populations living in Eurasia may have been the product of population mixture between ancient Mongolians and natives following the expansion of Mongol Empire. Geneticists have found that most of these populations carried the Y-haplogroup C3* (C-M217). To trace the history of haplogroup (Hg) C3* and to further understand the origin and development of Mongolians, ancient human remains from the Jinggouzi, Chenwugou and Gangga archaeological sites, which belonged to the Donghu, Xianbei and Shiwei, respectively, were analysed. Our results show that nine of the eleven males of the Gangga site, two of the eight males of Chengwugou site and all of the twelve males of Jinggouzi site were found to have mutations at M130 (Hg C), M217 (Hg C3), L1373 (C2b, ISOGG2015), with the absence of mutations at M93 (Hg C3a), P39 (Hg C3b), M48 (Hg C3c), M407 (Hg C3d) and P62 (Hg C3f). These samples were attributed to the Y-chromosome Hg C3* (Hg C2b, ISOGG2015), and most of them were further typed as Hg C2b1a based on the mutation at F3918. Finally, we inferred that the Y-chromosome Hg C3*-F3918 can trace its origins to the Donghu ancient nomadic group.

The development of Mongolia and the frequencies of haplogroup C3* in modern Eurasians. a The development of Mongolia. b The frequencies of haplogroup C3 in modern Eurasians. The dotted line represents the approximate boundary between the Xiongnu and the Donghu. The black and grey arrows denote the migration of the Donghu and Mongolians, respectively

Featured image: Diachronic map of Iron Age migrations ca. 750-250 BC.