Nubian Complex reduction strategies in Dhofar, southern Oman (Usik et al. 2012)

From the paper:

If there was no Nubian Complex occupation in Egypt during the MIS 5de5b hiatus, from where did the Egyptian Late Nubian, dating no earlier than MIS 5a, come? Did it spread north from Sudan or was there an expansion of Arabian Nubian Complex toolmakers back into Africa? Certainly, the striking similarities between the Classic Dhofar Nubian and Egyptian Late Nubian, as compared with the Sudanese Late Nubian, might indicate such a scenario. Again, greater chronological resolution in African and Arabian Nubian assemblages is required to answer these questions.   

It seems overly simplistic to expect the expansion of Nubian Complex toolmakers into Arabia was a single migration or event; rather, it was more likely a process of recurring bidirectional movements across the Red Sea linked to consecutive phytogeographic range expansions and contractions. At the same time, the presence of technologically distinct, non-Nubian industries elsewhere in Arabia from MIS 5a to MIS 3 indicates separate, autochthonous culture groups and/or input from other adjacent regions (Marks, 2009; Armitage et al., 2011; Petraglia et al., 2011; Delagnes et al., 2012). In the case of the Wadi Surdud stratified assemblages in Yemen, dated tow60e40 ka BP (Delagnes et al., 2012), and Jebel Faya successive assemblages B and A, bracketed within MIS 3 (Armitage et al., 2011), both archaeological sequences are thought to be the products of local lithic traditions. Clearly, Late Pleistocene demography in Arabia was far more complex than one population emanating from a single source area.   

For now, it is clear that the Afro-Arabian Nubian Complex exhibits a robust archaeological signature on both sides of the Red Sea, in terms of site density, distribution, and long-term technological variability, always based on the core principal of opposed platform exploitation. This is likely the result of populations who were well and truly established in their respective regions for an extended period of time. Perhaps we have made too much of tracking routes of expansion and the timing of sea crossings into Arabia. The Red Sea may be more of a barrier for scholars today than it ever was for humans in the Middle Stone Age. 

Related comment (my emphasis):

Nubian technology has been found in association with a modern human child within occupation Phase 3 at the site of Taramsa 1 in Egypt. Science would suggest they're modern. Unless, of course, one is willing to propose an entirely new species that occupied NE Africa 100,000 years ago? 

Nubian technology has now been identified in central Arabia (article in press by Crassard and Hilbert) and seems to be spread across central and eastern Yemen as well. The Mudayyan Industry, published in Usik et al. 2012, falls sometime after the Nubian occupation of Dhofar and is clearly derived from Nubian Levallois technology. Moreover, this particular technology governed by bidirectional recurrent Levallois blank production is interpreted as the transition from Middle Palaeolithic Levallois to Upper Palaeolithic blade reduction as exemplified at Initial Upper Palaeolithic sites in the Levant such as Boker Tachtit and Ain Difla. Essentially, the Nubians in Arabia have provided the technological missing link for the MP-UP transition in the Levant. 

So, Nubians entered Arabia sometime between 130 - 100 ka and appear to have subsequently expanded northward during the early MIS 3 wet phase that would have facilitated north-south demographic exchange throughout the Peninsula. As for the Out of Arabia expansion eastward, this is still anyone's guess. We can be sure it wasn't related to Nubian Complex toolmakers.

Quaternary International doi:dx.doi.org/10.1016/j.quaint.2012.08.2111

Nubian Complex reduction strategies in Dhofar, southern Oman

Vitaly I. Usik et al.

Between 2010 and 2012, the Dhofar Archaeological Project has located and mapped 260 Nubian Complex occurrences across Dhofar, southern Oman. Many of these lithic assemblages are technologically homologous to the Late Nubian Industry found in Africa, while others may represent a local industry derived from classic Nubian Levallois technology. The purpose of this paper is to describe the various reduction strategies encountered at a sample of Nubian Complex sites from Dhofar, to explore inter-assemblage variability, and, ultimately, to begin to articulate technological units within the “Dhofar Nubian Tradition.” To achieve this aim, we have developed an analytical scheme with which to describe variability among Nubian Levallois reduction strategies. From our analysis, we are able to discern at least two distinct industries within a regional lithic tradition. Demographic implications of the enduring Dhofar Nubian Tradition are considered in light of new evidence found throughout the Arabian Peninsula.

Link

Differences and similarities between Greek and European HapMap populations

Not surprisingly, TSI captued Greek genomic structure better than CEU did, although not always:

The TSI outperform the CEU as reference for the Greek population in 10 regions. However, there are four regions where the CEU are actually better reference samples than the TSI, contrary to what one might expect based on geographic proximity of the populations. Among them, the most notable are a region of chromosome 7 (100% coverage using the CEU as reference vs. 91.7% using the TSI as reference) and the chromosomal region around COMT (100% coverage using the CEU as reference vs. 93% coverage using the TSI as reference). The Chromosome 7 region spans the TAS2R38 gene (responsible for the PTC taster/nontaster phenotype), as well as the CLEC5A gene. The latter gene has been found to have a role in immune response and interact with dengue virus. Finally, the SLC44A5 regions (discussed in previous sections as one of the most population-differentiating regions in our study) were also captured more accurately in Greeks when the CEU were used as the reference population as opposed to the TSI.

Annals of Human Genetics DOI: 10.1111/j.1469-1809.2012.00730.x

Exploring Genomic Structure Differences and Similarities between the Greek and European HapMap Populations: Implications for Association Studies

Vasileios Stathias et al.

Studies of the genomic structure of the Greek population and Southeastern Europe are limited, despite the central position of the area as a gateway for human migrations into Europe. HapMap has provided a unique tool for the analysis of human genetic variation. Europe is represented by the CEU (Northwestern Europe) and the TSI populations (Tuscan Italians from Southern Europe), which serve as reference for the design of genetic association studies. Furthermore, genetic association findings are often transferred to unstudied populations. Although initial studies support the fact that the CEU can, in general, be used as reference for the selection of tagging SNPs in European populations, this has not been extensively studied across Europe. We set out to explore the genomic structure of the Greek population (56 individuals) and compare it to the HapMap TSI and CEU populations. We studied 1112 SNPs (27 regions, 13 chromosomes). Although the HapMap European populations are, in general, a good reference for the Greek population, regions of population differentiation do exist and results should not be light-heartedly generalized. We conclude that, perhaps due to the individual evolutionary history of each genomic region, geographic proximity is not always a perfect guide for selecting a reference population for an unstudied population.

Link

The winding road to agriculture

Antiquity Volume: 86 Number: 333 Page: 707–722

Did Neolithic farming fail? The case for a Bronze Age agricultural revolution in the British Isles

Chris J. Stevens1 and Dorian Q Fuller2

This paper rewrites the early history of Britain, showing that while the cultivation of cereals arrived there in about 4000 cal BC, it did not last. Between 3300 and 1500 BC Britons became largely pastoral, reverting only with a major upsurge of agricultural activity in the Middle Bronze Age. This loss of interest in arable farming was accompanied by a decline in population, seen by the authors as having a climatic impetus. But they also point to this period as the time of construction of the great megalithic monuments, including Stonehenge. We are left wondering whether pastoralism was all that bad, and whether it was one intrusion after another that set the agenda on the island.

Link

Göbekli Tepe: feasting, beer, and the emergence of the Neolithic

This is a very interesting paper which suggests that collective work accompanied by feasting played an important role in the creation of Göbekli Tepe. The site taxed hunter-gatherer resources, since it required the combined labor of many people from a wide area to erect. The "work events" associated with its building were occasions for feasting, which combined the consumption of many different types of prey, as well as beer fermented from wild crops.

From the paper:

The sediments used to backfill the monumental enclosures at the end of their use consist of limestone rubble from the quarries nearby, flint artefacts and surprisingly large amounts of animal bones smashed to get to the marrow, clearly the remains of meals. Their amount exceeds everything known from contemporary settlements, and can be taken as a strong indication of large-scale feasting. The species represented most frequently are gazelle, aurochs and Asian wild ass, a range of animals typical for hunters at that date in the region. 

...  

In concordance with Hayden’s thoughts, it seems obvious that repetitive feasts of the amplitude implied at G¨obekli Tepe must have placed stress on the economic production of hunter-gatherer groups.Maybe in response to the demand, new food sources and processing techniques were explored. In this scenario, religious beliefs and practices may have been a key factor in the adoption of intensive cultivation and the transition to agriculture. Archaeological and chemical evidence further suggests that this innovation may have been fuelled by alcoholic beverages, giving a new response to Braidwood’s question ‘Did man once live by beer alone?’ Probably not, but beer—and wine—may have played an important role in one of the most significant turning points in the history of mankind. 

Personally, I am undecided whether the shift to agriculture was primarily ideological or utilitarian. Is Cauvin right about agriculture following the "birth of gods", being a dictate of some primordial religious-symbolic ideology, or did agriculture appear as a consequence of some ecological crisis that led Near Eastern hunter-gatherers to seek new reliable sources of sustenance? Or, was it more like a side product of an unrelated event, not dictated by a New Religion, but serving it indirectly by making possible the large-scale feasting exhbited in Göbekli Tepe?


Antiquity Volume: 86 Number: 333 Page: 674–695

The role of cult and feasting in the emergence of Neolithic communities. New evidence from Göbekli Tepe, south-eastern Turkey

Oliver Dietrich1, Manfred Heun2, Jens Notroff1*, Klaus Schmidt1 and Martin Zarnkow3

Göbekli Tepe is one of the most important archaeological discoveries of modern times, pushing back the origins of monumentality beyond the emergence of agriculture. We are pleased to present a summary of work in progress by the excavators of this remarkable site and their latest thoughts about its role and meaning. At the dawn of the Neolithic, hunter-gatherers congregating at Göbekli Tepe created social and ideological cohesion through the carving of decorated pillars, dancing, feasting—and, almost certainly, the drinking of beer made from fermented wild crops.

Link

Differential relationship of ANI to Caucasus populations

The observation in Reich et al. (2009) that Ancestral North Indians (ANI) and CEU (HapMap White Utahns) form a clade to the exclusion of Adygei (a NW Caucasian HGDP population) has always puzzled me, because in my ADMIXTURE experiments, the dominant West Eurasian component in South Asia has always been one centered in the Caucasus rather than Europe, an observation also confirmed by Metspalu et al. (2011).

I have now used the qpDstat program of ADMIXTOOLS to calculate some D-statistics using a wide variety of West Asian populations that have appeared in the literature since 2009 (mainly Behar et al. 2010, and Yunusbayev et al. 2011), in addition to the Adygei. This analysis is based on 87,925 SNPs. I have kept SNPs included in the Rutgers map for Illumina chips, since most of the datasets merged with the Reich et al. (2009) dataset were genotyped on such chips, and applied a --geno 0.01 flag after merging the various datasets.

The following populations were considered:

North_Kannadi, Sindhi, Pathan, Kashmiri_Pandit, Brahmins_from_Uttar_Pradesh_M, Iyer_D, Iyengar_D, CEU30, Onge, Adygei, Lezgins, Georgians, Ukranians_Y, Abhkasians_Y, Chechens_Y, North_Ossetians_Y, Armenians_Y, Kurds_Y, Iranians_19, Romanians_14, Bulgarians_Y, Greek_D

I calculated D-statistics of the form:

D(CEU30, non-CEU West Eurasian; South Asian, Onge)

I report, for each South Asian population, the score for non-CEU West Eurasian being Adygei, and the most negative Z-score:

It is clear, that while CEU are more related to Indian cline populations than Adygei are, at least for the case of the Pathans, they are less related to them than Georgians are. The Georgian population is one of the modal populations of the West Asian autosomal component.

The full set of results can be found here. It appears that North Ossetians (who are also from the NW Caucasus) follow the Adygei pattern, while Abkhazians, Lezgins, and Armenians appear more related to ANI than CEU are, similar to the Georgian pattern.

Interestingly, D(CEU, Iranian; South Asian, Onge) appear positive, and this is probably not because CEU are more related to ANI than Iranians, but because Iranians also have ASI admixture.

Ukrainians do not appear more closely related to ANI than CEU are, rather the opposite. This is consistent with the recent f3-statistics analysis of South Indian Brahmins, in which the strongest signals of admixture involved populations from Western Europe, the Balkans, and West Asia, but not from eastern Europe.

All the available evidence suggests that ANI is most related to populations of the South and NE Caucasus, and not to those of the NW Caucasus like Adygei. To confirm this, I calculated some additional D-statistics (also included in the spreadsheet):

All in all, this seems to be very consistent with my working model of Eurasian prehistory. It is also in agreement with proposals for a genetic relationship between Indo-European and NE Caucasian/Hurrian and/or early contacts between it and Kartvelian. No such relationship, as far as I can tell, has been seriously advanced with respect to NW Caucasian languages.

A valuable lesson from this analysis is that now that multiple West Asian populations have been genotyped, caution must be exercised when using the HGDP Adygei, because they are clearly not representative of the different language families (NE/S Caucasian and Indo-European) present in West Asia. Surprises may lurk even at the sub-1000km scale in a region as diverse as the Caucasus.

An estimate of the admixture time for Finns

Using a similar procedure as in my recent post on the Baltic (Update II), I used 15 FIN individuals from the 1000 Genomes together with 12 Nganasans from Rasmussen et al. (2010) as reference populations, and 15 other FIN individuals to estimate admixture LD in a rolloff analysis. Three outlier Nganasan individuals (GSM558800, GSM558802, GSM558807) were removed.

The estimated time of admixture is 86.095 +/- 10.187 generations, or 2500 +/- 300 years. It corresponds rather well to the beginning of the Iron Age in northern Europe.

As I mention in my previous post, there is evidence for intrusive cultures (Battle Axe and Seima Turbino) converging on the area from different directions during the preceding Bronze Age. If the above date is accurate, it will suggest a rather late admixture event between the Europeoid and Siberian elements of Finns. The former may have included both the descendants of Mesolithic European hunter-gatherers and intruders from Central Europe (Corded Ware/Battle Axe); the latter may have included both Comb Ceramic and the descendants of the Seima Turbino metallurgists.

From Skulls and Scans (Monge & Aguirre @ Penn)

An interesting talk on the uses and abuses of science.

 

I find this excerpt particularly offensive to my open science sensibilities (29:40 ff):

We were able to, after 10 years, actually get it published in PLoS Biology, took us 10 years, yeah, we were rejected every single place that we ever sent the manuscript. I find that interesting too, and we even had editors say to us that they didn't want to say anything against Stephen J Gould. Isn't that interesting?

Interesting indeed. As I wrote in my review of the Lewis et al. (2011) paper on the Gould vs. Morton affair:

It is remarkable that 30 years after the Mismeasurement of Man Gould's errors are uncovered. Why did it take so long? While one could understand why the (totally unfounded but -on the surface- plausible) idea of measurement bias could have gone unnoticed until someone actually re-measured the skulls, but the statistical error that Gould committed was there for anyone to see.

We now know why it took at least 10 out of these 30 years: stuck in journal limbo.

Ann Gibbons on slower mutation rate

I have covered several studies on the slower mutation rate and its implications, including a couple of recent overviews by Hawks and Scally and Durbin. Ann Gibbons has come up with yet another take on the matter in Science. There is also a freely available podcast on the topic; you can read the transcript. A couple of quotes from this interview:

Eight new studies in the past three years, and an older study, have all calculated the  mutation rate directly.  This is sort of the result of new high-throughput genome  sequencing methods that give you high-quality coverage of the entire genome.  So we’re  able to get the more precise rate, which we sort of said is about an average of 36  mutations in each newborn.  That’s something like a chance of getting 1.2 mutations per  nucleotide site per 100 million years, okay?  So when you think about spreading 36  mutations over three billion nucleic acids or bases in your genome, it comes out to not  very many mutations per generation.  This is the average rate in modern humans per  generation, and it can be converted into a rate per year.  Now there’s a little debate about  how you do that because you have to know exactly how long each generation is.  But new  studies done by Linda Vigilant and her team – a number of primatologists in Germany – have studied the actual generation times using DNA and observations in the field of  chimpanzees and gorillas, and we know them in modern humans.  What this comes out to  is about half the rate that researchers have been using for the past 15 years.  One study by  David Reich at Harvard and his colleagues comes up with a slower rate, but it isn’t half  the rate.  And that raises some questions about whether the new genome methods are  actually catching all the mutations.  We’re sort of at the limits of their resolution.  I think  most geneticists think that the rate is definitely slower.  There is still some debate about  precisely how much slower.  Is it half or a little bit less?   

...   

Yes.  So if you apply the new mutation rate, you get a human-chimpanzee split of about  8.3 million to about 10.1 million years ago, instead of 4-7 million years ago.  So that’s  quite a bit older.  And the earliest fossils of the human family only are about 6-7 million  years, so there’s a problem there.  The human-Neandertal split used to be 250,000 to  350,000 years ago.  Now it’s about 400-600 thousand years ago.  That fits with fossils  that look like they’re ancestral to Neandertals that show up around 500,000 years ago in  Europe.  So that’s a little better fit.  And finally, we date the out-of-Africa migration to  earlier, that we have our modern human ancestors coming out of Africa 90,000-130,000  years ago instead of less than 60,000 years ago.  That would mean some of the fossils that  have been discounted as modern human ancestors – especially in North Africa and  Arabia – might actually be ancestral to modern humans if that’s accurate.  There will be  some debate.  I would say at this point anthropologists and paleogeneticists who use these  dates are quite confused, and they’re taking a wait-and-see attitude to see what geneticists  end up deciding about applying these dates back in time.  

One good thing to come out of the coming upheaval, as anthropologists scramble to update their models, is that the appearance of modern symbolic behavior and art. during the Upper Paleolithic will finally be decoupled from the Out-of-Africa event.

This will help us understand both: the ancestors of non-Africans did not come forth fully formed, like Athena from Zeus's head, having spent millennia of perfecting their craft and honing their minds by perforating shells and scratching lines in some South African cave. Instead, they may been plain old-style hunter-gatherers who stumbled into Asia by doing what they always did: following the food. At the same time, the UP/LSA revolution may not have been effected by a new and improved type of human bursting into the scene and replacing Neandertals and assorted dummies, but rather as a cultural revolution that spread across a species that already had the genetic potential for it, and was already firmly established in both Africa and Asia.

Science 12 October 2012:
Vol. 338 no. 6104 pp. 189-191
DOI: 10.1126/science.338.6104.189

Turning Back the Clock: Slowing the Pace of Prehistory

Ann Gibbons

Researchers have used the number of mutations in DNA like a molecular clock to date key events in human evolution. Now it seems that the molecular clock ticks more slowly than anyone had thought, and many dates may need to be adjusted. Over the past 3 years, researchers have used new methods to sequence whole human genomes, allowing them to measure directly, for the first time, the average rate at which new mutations arise in a newborn baby. Most of these studies conclude that the mutation rate in humans today is roughly half the rate that has been used in many evolutionary studies since 2000, which would make genetic estimates of dates older than previously believed. The question now is how much older?

Link

Levels of genetic diversity and economic prosperity (?)

Ewen Callaway tips me on the controversy surrounding a new paper which proposes a link between levels of genetic diversity and economic prosperity. I am linking to a version of the paper that is available online, as well as to a response by several geneticists, and a response to the response.

From the abstract, it seems that the authors are suggesting that there is an optimum level of genetic diversity, with either too little or too much of it being harmful for economic development.

Here are my own ideas on the general topic, prior to reading either the paper or the response letter.

Genetic diversity is, in general, a good thing for a population, for a simple reason: adaptation via natural selection depends on the existence of variation (there cannot be selection in the absence of alternatives). Other things being equal, a population possessing a greater amount of genetic diversity has a greater probability of already possessing adaptive alleles that might be necessary to meet new environmental challenges (e.g., pathogens).

But, we must also remember that genetic diversity can be partitioned to what is useful, neutral, or deleterious. We ought to be thankful that our Major Histocompatibility Complex (MHC) region is diverse, largely indifferent whether neutrally involving microsatellite loci have higher or lower allele variance in two populations, and a little concerned if there is an abundance of mildly deleterious rare variants sprinkled in our genomes, or a strong-effect disease-causing variant in one locus.

It is by no means clear whether human populations differ, and how they differ in each of these three components. Too much "neutral" diversity is patently irrelevant for economic prosperity; too much "useful" diversity may be helpful, and too much "deleterious" harmful, but I see no particular reason why populations would substantially differ in these two categories.

And, indeed, even the boundaries between the useful/neutral/deleterious categories are blurred. Deleterious anaemia-causing mutations are known to have benefits of malaria-resistance. Neutral variants may be "useful" ones in waiting: for example, lactase persistent mutants may have existed in the human species for hundreds of thousands of years, appearing and re-appearing by mutation, but it is when they encountered cow's milk and the need to drink it that they shifted from "neutral" to "useful". And, even useful alleles can cease to be so, e.g., the eradication of swamps and malaria in Greece has removed the benefit of malaria-resistence, and left only the harm of anaemia.

A different idea that one might consider is that diversity is sometimes harmful: for example, if you are picking a 4x100 relay team or hiring lumberjacks, or recruiting violinists, you don't especially want a genetically diverse group, but rather a restricted subset of phenotypes, and, inasmuch as phenotypes are influenced by genotypes, a restricted subset of genotypes as well: those with efficient fast twitch muscles, upper-body strength, and good pitch/finger dexterity respectively.

But, society is not a one-trick pony, and economies depend on an assortment of abilities. There is no "optimal human phenotype" that is good for all occupations, and most working societies have found ways to channel their diversity profitably, restricting it when necessary (e.g., picking a particular subset to be soccer players, and another subset to be figher pilots), or expanding it when necessary (e.g., assembling test groups that might mirror society, or the world at large).

Personally, I am sceptical of explanations that invoke long-standing evolutionary differences between populations. Such explanations (e.g., involving differences established during Out-of-Africa, as in this paper) have a hard time explaining "sign changes" in the direction of differences over the last few thousand years: China and Mesopotamia, were, by all accounts much more prosperous than most of Europe within historical memory, and the situation is now reversed -although it may be reversed yet again, if current trends continue, at least in the case of China. The people who erected massive monuments on the Americas do not appear to have been poorer than the Japanese of the time. Egypt used to be a breadbasket of Rome, but is now much poorer than Italy. In ancient times, Germans migrated to southern Europe, and during the 20th century many southern Europeans migrated into Germany.

If Out-of-Africa, 100 thousand years ago, sowed the seeds of differential economic prosperity, then these shifts in fortunes over the last few centuries or millennia are difficult to explain.

But, we also don't know that the pattern of genetic diversity observed in modern humans today is the result of Out-of-Africa. Evidence has been slowly and steadily accumulating, that people who live in different parts of the world today are not necessarily the same people of the ones who lived there a few thousand years ago. Migration and admixture have changed the landscape of human genetic variation: migration by expanding "narrow" genetic pools into much wider territories, and admixture by increasing diversity in contact zones.

So, to summarize:

1. Genetic diversity can be positive, neutral, or deleterious; boundaries between these categories are fluid, and their apportionment in different populations is uncertain.
2. Current differences in economic development are in contrast with such differences in the recent historical past, weakening the case that they stem from events that took place in the distant past (such as Out-of-Africa)
3. Current population differences in genetic diversity may have been established by migration and admixture in the recent past, rather than reflecting on events that took place in the distant past.

So, I am rather unconvinced of the hypothesis advanced by Ashraf and Galor. If I find something to add after reading their paper, I will add it here as an update.

RePEc:bro:econwp:2010-7

The "Out of Africa" Hypothesis, Human Genetic Diversity, and Comparative Economic Development

Quamrul Ashraf, Oded Galor

This research argues that deep-rooted factors, determined tens of thousands of years ago, had a significant effect on the course of economic development from the dawn of human civilization to the contemporary era. It advances and empirically establishes the hypothesis that in the course of the exodus of Homo sapiens out of Africa, variation in migratory distance from the cradle of humankind to various settlements across the globe affected genetic diversity and has had a direct long-lasting effect on the pattern of comparative economic development that could not be captured by contemporary geographical, institutional, and cultural factors. In particular, the level of genetic diversity within a society is found to have a hump-shaped effect on development outcomes in the pre-colonial era, reflecting the trade-off between the beneficial and the detrimental effects of diversity on productivity. Moreover, the level of genetic diversity in each country today (i.e., genetic diversity and genetic distance among and between its ancestral populations) has a similar non-monotonic effect on the contemporary levels of income per capita. While the intermediate level of genetic diversity prevalent among the Asian and European populations has been conducive for development, the high degree of diversity among African populations and the low degree of diversity among Native American populations have been a detrimental force in the development of these regions. Further, the optimal level of diversity has increased in the process of industrialization, as the beneficial forces associated with greater diversity have intensified in an environment characterized by more rapid technological progress.

Link

Response to Ashraf and Galor 'The Out of Africa Hypothesis, Human Genetic Diversity and Comparative Economic Development'

Jade D'Alpoim Guedes et al.

Abstract:

This short reply summarizes the concerns of the anthropological community about Ashraf and Galor's (Forthcoming) article in the American Economic Review.

Link

Response to Comments made in a Letter by Guedes et al. on “The Out of Africa Hypothesis, Human Genetic Diversity and Comparative Development”

Link (pdf)

DNA half-life + Old Hobbits

New Scientist reports on a new paper that attempts to quantify the "half-life" of DNA. This bit caught my eye:

Unfortunately, Bunce thinks the new calculations will be difficult to apply to specific sites. "A host of other factors come into play," he says, including the season the organism died. In fact, although the moa bones in the analysis had been buried in a similar environment, the age of the specimens could account for only about 40 per cent of the variation in DNA preservation – in other words, the half-life signal is noisy. 

Alan Cooper, director of the Australian Centre for Ancient DNA at the University of Adelaide, South Australia, agrees. "The rotting process after death is very seasonal and context dependent, and has a major impact on DNA survival." 

Cooper has attempted to extract DNA from Homo floresiensis remains, but is beginning to think that none will ever be found. He says that recent unpublished dating estimates indicate that "the hobbit material may be considerably older than currently suggested".

The paper probably has implications for many areas of biology, but the recent sequencing of the Denisova hominin at high coverage, leaves me hopeful that we will have some type of ancient DNA evidence for at least the last 100 thousand years, quite a lot of it for the time since the inception of the Upper Paleolithic, and nearly everything for the time since the beginning of the Neolithic.

Proc. R. Soc. B doi: 10.1098/rspb.2012.1745

The half-life of DNA in bone: measuring decay kinetics in 158 dated fossils

Morten E. Allentoft et al.

Claims of extreme survival of DNA have emphasized the need for reliable models of DNA degradation through time. By analysing mitochondrial DNA (mtDNA) from 158 radiocarbon-dated bones of the extinct New Zealand moa, we confirm empirically a long-hypothesized exponential decay relationship. The average DNA half-life within this geographically constrained fossil assemblage was estimated to be 521 years for a 242 bp mtDNA sequence, corresponding to a per nucleotide fragmentation rate (k) of 5.50 ? 10–6 per year. With an effective burial temperature of 13.1°C, the rate is almost 400 times slower than predicted from published kinetic data of in vitro DNA depurination at pH 5. Although best described by an exponential model (R2 = 0.39), considerable sample-to-sample variance in DNA preservation could not be accounted for by geologic age. This variation likely derives from differences in taphonomy and bone diagenesis, which have confounded previous, less spatially constrained attempts to study DNA decay kinetics. Lastly, by calculating DNA fragmentation rates on Illumina HiSeq data, we show that nuclear DNA has degraded at least twice as fast as mtDNA. These results provide a baseline for predicting long-term DNA survival in bone.

Link

The Indo-European invasion of the Baltic

In some recent posts, I showed that South Asian populations (North Indian Brahmins, South Indian Brahmins) can be seen as mixtures of West Eurasian and South Indian populations, but also that West Eurasians (Bulgarians, Greeks, Armenians, and French) can be seen as mixtures of South Asian and Sardinian populations.

This may seem strange, but can be explained if we understand how f3-statistics and rolloff actually work. These methods do not require pure or unadmixed ancestral populations, but exploit allele frequency differences in the reference populations together with either (i) allele frequencies in the mixed population, in the case of f3-statistics, or (ii) admixture linkage disequilibrium in the mixed population, in the case of rolloff.

If a and b are allele frequencies in two ancestral populations A and B that mix, then:

• The frequency of a will shift towards b if A experiences gene flow from B
• The frequency of a will randomly shift if A experiences gene flow from an "outgroup" population
• The frequency of a will shift towards b if A experiences gene flow from a third population that is geographically and genetically intermediate between A and B

An application to the Europe-South Asia cline

I took the following set of populations, and calculated all 1,365 possible f3-statistics:

"FIN30"         "Lithuanians"   "Russian"       "Pathan"        "Balochi"       "North_Kannadi" "Polish_D"      "Russian_D"     "Mixed_Slav_D"  "Bulgarian_D"   "Serb_D"        "Ukrainian_D"   "Belorussian"   "Bulgarians_Y"  "Ukranians_Y"

In the following table, I report the lowest Z-scores for each target population (third column). So, for example, Polish_D can be seen as a mixture of Lithuanians and Balochi. Only negative scores are indicative of admixture. I highlight in bold the significant negative scores (Z less than -3)


Lithuanians North_Kannadi FIN30 0.001606 0.000259 6.193 280043
Ukrainian_D Belorussian Lithuanians 0.00078 0.000299 2.614 268493
Lithuanians North_Kannadi Russian -0.002738 0.000248 -11.045 279965
North_Kannadi Polish_D Pathan -0.006959 0.000229 -30.344 280220
North_Kannadi Bulgarians_Y Balochi -0.003636 0.000246 -14.781 281604
Pathan Ukrainian_D North_Kannadi 0.033802 0.000623 54.237 271858
Lithuanians Balochi Polish_D -0.001171 0.000178 -6.581 279519
Lithuanians Pathan Russian_D -0.001829 0.000166 -11.026 280658
Lithuanians Pathan Mixed_Slav_D -0.001715 2e-04 -8.594 277635
Lithuanians Balochi Bulgarian_D -0.001247 0.000313 -3.979 272342
Lithuanians Balochi Serb_D -0.00091 0.000377 -2.416 270807
Lithuanians Balochi Ukrainian_D -0.002222 0.000358 -6.211 270399
Lithuanians Balochi Belorussian -0.000897 0.00027 -3.325 273076
Balochi Polish_D Bulgarians_Y -0.001198 0.000185 -6.481 279632
Lithuanians Balochi Ukranians_Y -0.001727 0.000187 -9.236 278677

It is clear, that what I have described holds here: European populations appear like mixtures of Lithuanians and South Asians; conversely, South Asian populations appear like mixtures of Europeans and North Kannadi.

This does not mean that the populations that appear unadmixed (FIN30, Lithuanians, North_Kannadi, and Serbs) are in fact so, for at least two reasons:

1. The f3 statistic confirms, but does not reject the presence of admixture; in particular, it fails to find real admixture in highly drifted populations
2. The f3 statistics exploits allele frequency correlations between populations: but the North Kannadi and Lithuanians/Finns occupy opposite ends of the studied cline, so their lack of signal of admixture may be due to the non-existence of populations that are even more unadmixed than themselves.

In the case of South Indians, we are completely sure that this is the case. Reich et al. (2009) managed to show this not because there are any unadmixed Ancestral South Indians (ASI) left, but because they exploited the existence of the Onge, an isolated group from the Andaman Islands that was a sister group to the ASI. So, we can be fairly sure that southern Indians themselves have West Eurasian-like admixture, even the ones that are at the end of the West Eurasia-South India cline on its southern end.

The problem is: there is no isolated group of unadmixed Europeans left in existence that might serve a similar proxy function as the Onge did for South Asians.

Enter Pickrell et al. (2012) to the rescue. In that paper, the authors studied admixture in the Khoe-San of South Africa. Now, many of the Khoe-San sub-groups appeared to be admixed, but the "Juj'hoan North" population appeared to be at the "end of the cline": it's impossible to detect admixture in them using alelle frequency differences, because, quite simply, there are no populations that are less unadmixed than them: they're as pure descendants of "Ancestral Bushman" as exist on the earth today.

But, the clever thing is, that we don't have to detect admixture only using allele frequency differences, but also using admixture LD, i.e., by exploiting the correlation between linkage disequilibrium (the co-inheritance of physically separated markers on a chromosome) and allele frequency differences between populations. Pickrell el al. were able to do this not by conjuring up a more unadmixed population than the "Juj'hoan North" one available to them, but by splitting up that population, and using one half to find allele frequency differences, and the other half to detect admixture LD.

Admixture LD signal in Lithuanians

Using the aforementioned idea, I set out to see whether Lithuanians, who occupy the European end of the Europe-South Asia cline present such a signal of admixture LD. I used the Lithuanian_D sample from the Dodecad Project and the Balochi HGDP sample as reference populations (to calculate allele frequency differences), and the Behar et al. (2010) Lithuanians for admixture LD. There were only ~300k SNPs usuable in this set, but sufficient to detect the signal of admixture LD:

The admixture time estimate is 200.350 +/- 61.608 generations, or 5,810 +/- 1790 years. This is not very precise, probably because of the small number of SNPs and individuals used, but it certainly points to the Neolithic-to-Bronze Age for the occurrence of this admixture. The date is certainly reminiscent of the expansion of the Kurgan culture out of eastern Europe, or, the later Corded Ware culture of northern Europe.

So, it may well appear that at least some of the people participating in these groups of cultures, were indeed influenced by the Indo-Europeans as they expanded from their West Asian homeland. These intruders mixed with eastern Europeans who vacillated during the late Neolithic between a northern Europeoid pole akin to Mesolithic hunter gatherers from Gotland and Iberia, and a widely dispersed Sardinian-like population that is in evidence at least in the Sweden-Italian Alps-Bulgaria triangle. The gradual appearance of non-mtDNA U related lineages in Siberia and Ukraine is most likely related to this phenomenon.

It would seem that the Proto-Indo-Europeans mixed with different substrata in the four directions of their expansion: Sardinian-like people in southern Europe, Lithuanian-like people in northern Europe, South Indian-like people in South Asia, and East Eurasians in Siberia and east central Asia. Extant groups are descendants of divergent Neolithic population groups, brought closer together (genetically) because of variable admixture with the PIE population and its early offshoots.

Conclusion

There are mutual signals of admixture across a Europe-South Asia cline: Europeans appear to be mixed with South Asians, and South Asians appear to be mixed with Europeans. The simplest explanation for this pattern involves expansion of a third, geographically and genetically intermediate population that affected both Europe and South Asia. We can use the signal of admixture LD to prove that this expansion affected some of the most unadmixed populations in Europe (e.g., Lithuanians), just as it did the most unadmixed populations of India (e.g., Dravidians).

It will be interesting to use these techniques to study signals of admixture in other "end of the line" populations such as Sardinians, South Indians, etc.

UPDATE I (rolloff analysis of Poles):

I have carried out rolloff analysis of my 25-strong Polish_D sample using Lithuanians and Pathans as references:

The signal is fairly distinct, and corresponds to 149.296 +/- 38.783 generations or 4330 +/- 1120 years. I am guessing that either the different reference population (Pathans vs. Balochi), or, more likely the increased number of target individuals (25 vs. 10) have contributed to the narrowing down of the uncertainty. It will be interesting to explore this signal further with more population pairs.

UPDATE II (rolloff analysis of Finns):

I have also used the 1000 Genomes Finnish sample (FIN) in a similar manner as Lithuanians, using 15 individuals to estimate allele frequency differences, and 15 ones for admixture LD, and using the Pathans as a South Asian reference population. There is a clear signal of admixture:

This dates to 104.967 +/- 14.797 generations, or 3,040 +/- 430 years. Finland came under the influence of both Europeans (and likely Indo-Europeans) during the Bronze Age period (a mixture of Battle Axe with local Comb Ceramic seems to have occurred), as well as likely non-European (and likely Uralic) intrusions during the same time frame, as part of the Seima-Turbino phenomenon. It will be interesting to repeat this analysis with an East Eurasian reference population to isolate potential signals of admixture dating to either the Comb Ceramic or Seima-Turbino episodes of migration.

(Note; added Oct 14): I carried out rolloff analysis using Nganassans as suggested in the above paragraph here.

UPDATE III (rolloff analysis of Ukrainians):

I have used the Yunusbayev et al. sample of Ukrainians, and estimated its admixture time using Lithuanians and Balochi as reference populations:

The admixture time estimate is 191.078 +/- 35.079 generations, or 5,540 +/- 1,020 years. It seems very similar to that in Lithuanians, with a smaller standard error, perhaps on account of either the larger number of SNPs or larger number of individuals.

It is tempting to associate this admixture signal with the Maikop culture which appeared at around this time. Assuming that North_European/West_Asian (or Lithuanian-like and Balochi-like) gene pools existed north and south of the Pontic-Caspian-Caucasus set of geographical barriers, then the Maikop culture which shows links to both the early Transcaucasian culture and those of Eastern Europe would have been an ideal candidate region for the admixture picked up by rolloff to have taken place. There are, of course, other possibilities.

UPDATE IV (rolloff analysis of Lithuanians with Pathan reference):

I repeated the first analysis of this post, but this time, I used Pathans, rather than Balochi as a reference population:

The admixture time estimate of 217.501 +/- 51.170 generations, or 6,310 +/- 1,480 years appears to be similar with the original estimate of 5,810 +/- 1790 years, so it does not appear that the use of Balochi or Pathan as a reference population much affects this result.

3D laser scan of Stonehenge reveals axehead graffiti

Stonehenge up close: digital laser scan reveals secrets of the past

The first complete 3D laser scan of the stone circle has also revealed tool marks made 4,500 years ago, scores of little axehead graffiti added when the enormous slabs were already 1,000 years old, and damage and graffiti contributed by Georgian and Victorian visitors. 

...

Long after the monument was built, when Bronze Age burial mounds rich in grave goods began to be scattered across the plain around Stonehenge, and the archaeological evidence suggests those who could make or trade in metal goods had an almost shamanic status, people carved little images of daggers and axes, many now invisible to the naked eye, into the stones. Scores more have been revealed by the scan, including 71 new axe heads, bringing the total to 115 – doubling the number ever recorded in Britain.

"It is wonderful to have discovered so many more, but what is fascinating is that they are carved without regard to the importance or the siting of the stones – almost as if the people who carved them could no longer quite remember the significance of the monument and how it worked," Greaney said.

They probably could no longer remember, because they were Indo-European newcomers, and not the same people as the Megalithic folk who built Stonehenge.

A little history:

Craniologists of the time used a ratio based on length and width measurements, known as the cranial index, to divide skulls into two basic types: 'dolichocephalic', long and narrow in shape, and 'brachycephalic', broad and round in shape. Based on his observations at sites like Belas Knap, Thurnam established his famous axiom, 'long barrows, long skulls; round barrows, round skulls'. The long skulls were found in long barrows and never in association with metallic artefacts, while round skulls were found in round barrows sometimes with metalwork. 

... 

Thurnam's and Rolleston's theories gained considerable credibility in the late Victorian period and survived well into the earlier 20th century. Such racist theories failed to stand up, however, in the face of Gordon Childe's arguments for the definition of an archaeological culture based on shared social characteristics and material culture rather than race or biological type. In addition, the considerable moral repugnance felt towards Victorian anthropology and its role in the rise of fascist ideology in the 1930s caused the argument over long and round skulls to be sidelined and eventually dismissed. The identification of the Bronze Age incomers based on their material culture, including metalwork and Beaker pottery vessels, remained a more acceptable alternative.
In the 1990s, however, the archaeologist Neil Brodie took a fresh look at the craniological evidence and concluded that there was undeniably a difference between the shape of skulls from Neolithic long barrows and Bronze Age round barrows. A trend from long to round skull shape was clearly shown. 

The differences, he argued, could be caused by cultural practices, such as the binding of infants' heads, as well as by diet and a range of climatic or environmental factors. Looking at the totality of human history, he showed that head shape fluctuates in populations over long periods of time, and that extremes of head types occur in successive prehistoric populations as a matter of historical chance.

We don't have DNA evidence from British round barrows yet, but Beaker burials from Germany show the first R1b ever found, while Neolithic Western Europe shows a mix of I2a and G2a. Difference in material culture? check. Difference in physical anthropology? check. Difference in time of appearance? check. Difference in genetics? preliminary check.

So, it seems like a good bet that the people who carved axehead graffiti on Stonehenge were simply invaders who took over the site from the previous inhabitants, and, as is so often the case, used it for their own purposes.

Mediterranean ornaments in the Hungarian Neolithic

The use of Spondylus ornaments by European Neolithic cultures is well known, and is one of the characteristics tracking the spread of the Neolithic into Europe. A new study has looked at late Neolithic Hungary, to track the origin of these ornaments, confirming that they did indeed come from the Mediterranean (Adriatic or Aegean), and not the Black Sea or fossil shells from the Carpathian Basin.

Given the evidence that late Neolithic European farmers, even as far north as Sweden were indeed of Mediterranean origin, their continued use of these ornaments possibly reflects a tradition going back to their origins in the Aegean, rather than simply a fashion that spread simply for its decorative properties.

Journal of Archaeological Science, doi:10.1016/j.jas.2012.09.022

Tracing the source of Late Neolithic Spondylus shell ornaments by stable isotope geochemistry and cathodoluminescence microscopy

Bernadett Bajnoczi et al.

Determination of the source of Spondylus objects is essential for the interpretation of Late Neolithic exchange systems and the social role of shell ornaments. We performed stable isotope analysis combined with cathodoluminescence microscopy study on ornaments (beads, bracelets) made of Spondylus shells excavated at the Aszod-Papi foldek archaeological site in Hungary, to define their origin. For comparison Spondylus finds from Neolithic sites of Greece, modern Spondylus shells from the Aegean and the Adriatic, as well as fossil Spondylus and Ostrea shells from the Carpathian Basin were also examined. Oxygen isotope composition of Spondylus finds from Aszod ranges between -1.9 and 2.1 ‰ and overlaps with the oxygen isotope range of shell objects from other Neolithic sites. Modern Spondylus shells from the Aegean and the Adriatic show overlapping δ18O values with one another and with the Neolithic objects; while recent shells of the Black Sea clearly are separate isotopically from the Mediterranean ones and most of archaeological artefacts. Spondylus shells from the Aszod site have Mediterranean origin; their source can be the Aegean or the Adriatic. Based on a former strontium isotope study the use of fossil Spondylus shells is excluded as raw material used for ornaments, however, in recent years the use of fossil shells was reintroduced. The shell ornaments from Aszod-Papi foldek and the fossil oyster shells collected from the Carpathian Basin exhibit some overlapping oxygen isotope values; however, cathodoluminescence microscopy indicates that the Spondylus objects retained their original aragonite material. Diagenetic calcite, which occurs typically in the fossil shells, was not detected in the ornaments suggesting that the studied objects were made of recent shells. Calcitic parts observed in some Spondylus objects are not related to fossilisation.

Link

rolloff analysis of North Indian Brahmins as Orcadian+North Kannadi

In a previous experiment, I tested the Dodecad Project South Indian Brahmin sample (Iyer and Iyengar) using Orcadians and North Kannadi as reference populations. In the current one, I use the same references to investigate admixture in the Uttar Pradesh Brahmins included in the Metspalu et al. (2011) dataset. A total of 473,837 SNPs are used in this experiment.

I first verified that f3(Brahmins_from_Uttar_Pradesh_M; Orcadian, North_Kannadi) is negative, using qp3Pop:

 Source 1 Source 2 Target f_3 std. err Z SNPs
 result: Orcadian North_Kannadi Brahmins_from_Uttar_Pradesh_M -0.007882 0.000359 -21.951 463297

The exponential fit can be seen below:

The estimated age is 79.706 +/- 9.197 generations, or 2,310 +/- 270 years.

This is about a thousand years younger than the signal observed for the South Indian Brahmin group. A possible explanation has to do with the fact that South Indian Brahmins migrated to South India, and hence did not intermarry with successive waves of invaders into India in historical times. Uttar Pradesh, on the other hand, received multiple invasions from the direction of Central Asia:

Most of the invaders of North India passed through the Gangetic plains of what is today Uttar Pradesh. Control over this region was of vital importance to the power and stability of all of India's major empires, including the Maurya (320–200 BC), Kushan (100–250 CE), Gupta (350–600 CE), and Gurjara-Pratihara (650–1036 CE) empires.[11] Following the Huns invasions that broke the Gupta empire, the Ganges-Yamuna Doab saw the rise of Kannauj.[12] During the reign of Harshavardhana (590–647 CE), the Kannauj empire reached its zenith.[12]

It will be interesting to see whether a young admixture signal also exists in my 5-strong sample of Jatts, since that population has traditions of "Scythian" origins.

rolloff analysis of Bulgarians as Sardinian+Pathan

Continuing my rolloff experiments, I have taken the Yunusbayev et al. sample of Bulgarians. This is interesting because of the recent evidence of a Sardinian-like individual from Iron Age Bulgaria, and also as a complement to a similar analysis on the Greeks. Bulgarians are Slavic speaking, but their ethnogenesis owes a great deal to the Bulgars, adding another potential element of complication. However, the paucity of East Eurasian admixture in Bulgarians, together with their Slavic language, probably suggests that this element represented a small elite that did not have a substantial role in the genetic formation of the Bulgarian population.

The top f3 statistics can be seen below:

Kshatriya_M Sardinian Bulgarians_Y -0.003813 0.000295 -12.918 237507
Velamas_M Sardinian Bulgarians_Y -0.003783 0.000285 -13.287 238276
Piramalai_Kallars_M Sardinian Bulgarians_Y -0.003693 0.000306 -12.061 238106
Kanjars_M Sardinian Bulgarians_Y -0.003643 0.000298 -12.227 237838
GIH30 Sardinian Bulgarians_Y -0.003638 0.000259 -14.028 240548
North_Kannadi Sardinian Bulgarians_Y -0.00355 0.000317 -11.187 237882
Muslim_M Sardinian Bulgarians_Y -0.003542 0.000333 -10.632 236964
Chamar_M Sardinian Bulgarians_Y -0.003505 0.000303 -11.585 238882
INS30 Sardinian Bulgarians_Y -0.003467 0.000264 -13.153 240279
Dharkars_M Sardinian Bulgarians_Y -0.003452 0.000309 -11.155 238211
Brahmins_from_Uttar_Pradesh_M Sardinian Bulgarians_Y -0.003448 0.000278 -12.42 238041
Indian_D Sardinian Bulgarians_Y -0.003411 0.000256 -13.308 241225
Iyer_D Sardinian Bulgarians_Y -0.003364 0.000291 -11.568 237509
Jatt_D Sardinian Bulgarians_Y -0.003327 0.000289 -11.513 236735
Pathan Sardinian Bulgarians_Y -0.003212 0.000239 -13.444 240969
Iyengar_D Sardinian Bulgarians_Y -0.003209 0.000308 -10.416 236840
Dusadh_M Sardinian Bulgarians_Y -0.003181 0.000313 -10.172 237512
Sindhi Sardinian Bulgarians_Y -0.003094 0.000239 -12.919 241268
Balochi Sardinian Bulgarians_Y -0.002804 0.00024 -11.686 240924

To maximize the number of SNPs and number of individuals, I used the Sardinian+Pathan pair as reference populations. 509,395 SNPs were used for this experiment. The exponential fit can be seen below:

There was a technical issue with the jackknife which I am currently investigating, but the mean time of the admixture was estimated at 126.83004 generations, or 3,680 years. This is similar to the value of 3,850 years I obtained on the Greek sample.

If this date is accepted, then the interesting issue is why an individual from Bulgaria was Sardinian-like during the Iron Age. Possibly, either this individual was Sardinian-like in the broad sense, despite having  minority West Asian admixture, or a few centuries after the admixture event, there was still an uneven distribution of the constituent elements, with most individuals still predominantly Sardinian-like. Given that the indigenous element was probably most numerous, so only part of it would have the opportunity to admix with the intrusive West Asian-like population, and this influence would spread to the population-at-large over time.

In any case, this evidence, such as it is, appears consistent with my idea about a Bronze Age invasion of Europe from Asia.

Naturally, only a broad sampling of ancient DNA variation from the Balkans, perhaps targeting different sites, cultures, times, social status, and physical types will be sufficient to track the early appearance of an intrusive population.

Effects of ancestry and admixture on human variation (Kidd et al. 2012)

AJHG Volume 91, Issue 4, 5 October 2012, Pages 660–671

Population Genetic Inference from Personal Genome Data: Impact of Ancestry and Admixture on Human Genomic Variation

Jeffrey M. Kidd et al.

Full sequencing of individual human genomes has greatly expanded our understanding of human genetic variation and population history. Here, we present a systematic analysis of 50 human genomes from 11 diverse global populations sequenced at high coverage. Our sample includes 12 individuals who have admixed ancestry and who have varying degrees of recent (within the last 500 years) African, Native American, and European ancestry. We found over 21 million single-nucleotide variants that contribute to a 1.75-fold range in nucleotide heterozygosity across diverse human genomes. This heterozygosity ranged from a high of one heterozygous site per kilobase in west African genomes to a low of 0.57 heterozygous sites per kilobase in segments inferred to have diploid Native American ancestry from the genomes of Mexican and Puerto Rican individuals. We show evidence of all three continental ancestries in the genomes of Mexican, Puerto Rican, and African American populations, and the genome-wide statistics are highly consistent across individuals from a population once ancestry proportions have been accounted for. Using a generalized linear model, we identified subtle variations across populations in the proportion of neutral versus deleterious variation and found that genome-wide statistics vary in admixed populations even once ancestry proportions have been factored in. We further infer that multiple periods of gene flow shaped the diversity of admixed populations in the Americas—70% of the European ancestry in today’s African Americans dates back to European gene flow happening only 7–8 generations ago.

Link