For various sociocultural reasons ancient Egyptians are a big deal. The pyramids of Giza are about as distant from the time of Augustus as Classical Rome is from us. When the pyramids were rising the world was mostly prehistory. Africa was dominated by hunter-gatherers, as was much of Southeast Asia. The genetic cluster which we recognize as Northern Europeans was only coming into focus, while South Asians as we understand them today may not totally have been a coherent group.

It was a very different time. Down to the present day one population can plausibly claim a connection to ancient Egypt, and that population are the Copts. Though now extinct, their language was a direct descendant of ancient Egyptian, which was not a Semitic tongue. As Christians in a nation which as been Muslim for over 1,000 years, with the period after 1000 A.D. likely majority Muslim, they likely have experienced less genetic perturbation than other groups in the area.

The paper The genetics of East African populations: a Nilo-Saharan component in the African genetic landscape has some Coptic, and other, samples. There are 175,000 markers on this chip. Merged with the HGDP populations you get about 30,000.

The PCA shows that Copts are mostly West Eurasian in ancestry. But they seem shifted to Northeast African Sub-Saharan groups The Mozabite Berbers are shifted toward West Africans, but their West Eurasian ancestry looks to be more like that of the Copts than West Asians. Though not shifted toward West Asians, the Copts do seem to have affinities with various Sudanese groups.
This TreeMix graph was run on 30,000 markers, with the Sudan skewed sample and some HGDP populations. Not surprisingly, there are gene flow arrows from the Copts to the others. In particular, the two Nubian groups, who have long been resident right to the south of Egypt. But, there is also gene flow from a position between the Copts and Sub-Saharan Africans. Finally, observe that Northeast African Bantus, who have some Nilotic admixture from the Bantu, receive gene flow from a more “European” like population, while the Copts receive gene flow from near the Sardinians. All this points to a complex population history.

It seems likely that the Eurasian backmigration into Sub-Saharan African over the Holocene involved several distinct events. Some of them probably date to the period of the Pleistocene.

I really admire what 23andMe has done. To a great extent they are the “Uber” of DTC personal genomics. FamilyTree DNA really pioneered the sector in the early 2000s, while The Genographic Project scaled things up massively in the middle 2000s. But in the late 2000s 23andMe brought Silicon Valley “disruption” to the game, pushing into disease and traits in a way that both the two earlier efforts consciously avoided. We know how that ended.

But it wasn’t all in vain. 23andMe is today a healthy company, and its shoot-first-ask-questions later actions in the first half of the teens really brought personal genomics into peoples’ lives.

So what’s going with stories like this, 23andMe Has Abandoned The Genetic Testing Tech Its Competition Is Banking On:

For years, genetic-testing startup 23andMe was working to develop a cutting-edge technology that could dramatically expand what its customers might learn about their DNA. While the company’s core product, a $199 “spit kit,” can tell you about your health and ancestry based on small bits of your genetic code, tests based on the new technology — called next-generation sequencing — could provide much more comprehensive information, including your potential risks for many diseases.

But 23andMe has given up on the technology for now, BuzzFeed News has learned.

I think one way to understand what’s going on is that though the firm’s consumer face is still as a DTC personal genomics outfit, it is really banking on becoming a genetically savvy pharmaceutical corporation. Genomics is the future, but pharm is the present.

23andMe probably has ~1.5 million genotypes now. They’ll confirm more than 1 million. If they had more than 2 million I assume they would tell us they did. What are they doing with those genotypes? It was always understood by most that 23andMe was increasing its database to the point where they could generate associations that academics could not because of lack of statistical power. The problem now, with more than 1 million genotypes, is that they need phenotypes.

It is much more valuable for 23andMe to get rich data on one customer, than it is to gain one hundred more random genotypes. That’s probably why they’re not sweating that the $199 price point discourages people, especially when those people are getting less than they did in the past. That’s also why they are pulling out of the game in next generation sequencing. Sequencing is basically a commodity business now, and just not as good a return on investment as gearing toward the pharmaceutical market. Sequencing deeply has some benefits, but there is no way 23andMe would be able to subsidize the $1,000 cost of a good 30x genome to get enough of a sample size to return the investment.

None of this is a big secret. A friend of mine was talking about this in the broadest sketches at the 23andMe party at ASHG.

A friend of mine introduced me to Mr. Robot a month ago. The show was difficult for me to follow, and I don’t watch much TV in the first place (“watching TV” is like making a “mix tape”; there’s not television involved anymore). But, the star, Rami Malek, had an intriguing look.

It was only later that I realized why: his face resembled the Fayum portraits. These miniatures represented people in Roman Egypt from all walks of life. They are one of the best set of representations we have of normal individuals, albeit, prosperous enough to commission these works.

Malek is from a Coptic family, so presumably genetically representative of people in Roman Egypt during that time. It stands to reason that he’d look quite like many of these ancient Romans.

Anyway, I happen to have some data laying around put it through PCA, Treemix and ADMIXTURE. If you click the plot to the left PC 1 shows a cline from Sardinians to Lithuanians. PC 2 is from (modern) Egyptians to Basques. The Egyptians are clearly being shifted by their Sub-Saharan African admixture, which in other analyses usually comes in at between 10% to 25% depending on the individual. The Assyrian Christian samples, and Cypriots, are much closer to the other populations on PC 2 (several of the Lebanese). Then the Sicilians, Tuscans, Bergamo Northern Italians, and Spanish (before the Basque).

Sometimes Treemix is more informative. Below is a pretty representative graph with 5 migration edges (I set Egyptians to be the root):

And here’s K = 4.

These sorts of plots are a Rorschach test. But, I’m pretty sure ancient DNA will confirm that migration around the Mediterranean during the Classical Era was non-trivial, but, the minor component in the ancestry of most modern populations.

There are some topics which I have some interest in, such as prehistory illuminated by genetics, in which there is constant change and new discoveries every few months. If a new paper doesn’t drop in a six month interval, I think something is wrong.

There are other topics where I don’t perceive much change, and have stopped paying much attention. Psychometrics for example is one area where I basically just stopped paying much attention after reading The g factor. I understand that it’s a live field, but at this point to me the details are academic, as the broad sketch seems well established (this will change in some ways over the next decade due to genomics, but since I think genomics will confirm what we already know it won’t be very revelatory for me).

The scientific study of religion is another topic where I once had a lot of interest, but where I concluded that the basic insights have stabilized. Since I stopped reading much in this area I stopped writing much about it too. To get a sense of where I’m coming from, Scott Atran’s In Gods We Trust: The Evolutionary Landscape of Religion is probably the best place to start. It’s about 15 years old, but I don’t see that much has changed since then in the basics of the field.

And what are those basics? At its fundamental basics religious impulses must be understood as an outcome of our cognitive mental intuitions. All religion operates on top of this basic kernel of our mental OS. Religion may have functional utility as a social system of control, or channeling collective energies, as argued by David Sloan Wilson in Darwin’s Cathedral. Or, one might be able to fruitfully model “religious marketplaces” as argued in Marketplace of the Gods. But these are all basically simply applications installed into on top of the operating system.

Why does this matter? For me this is a personal issue, because I’m one of those people who has never really had a strong religious impulse. Since I didn’t have a religious impulse, my model of religion was as that of an outsider, which led to some confusions. For example, there was a point perhaps around the age of 18 where I thought perhaps if someone just read a book like Atheism: A Philosophical Justification they’d be convinced. Just as if I’d been a Roman Catholic I would have thought a reading of Summa Theologica would have convinced. This was all wrongheaded.

Very few are Roman Catholic because they have read Aquinas’ Five Ways. Rather, they are Roman Catholic, in order of necessity, because God aligns with their deep intuitions, basic cognitive needs in terms of cosmological coherency, and because the church serves as an avenue for socialization and repetitive ritual which binds individuals to the greater whole. People do not believe in Catholicism as often as they are born Catholics, and the Catholic religion is rather well fitted to a range of predispositions to the typical human.

One thing that the typical human does not have is intensive need for rationalization of our daily life, and the totality of their beliefs. There are a non-trivial subset of Catholics who have heard of the Five Ways, or might be conversant in the Ontological Argument. But this is a very small minority of Catholics, and for even these this philosophical element is a sidelight to most of their spiritual practice and orientation.

The reason I am posting this is in response to something Rod Dreher wrote, Mystery Of The Ages:

Here’s something I have never figured out. In theory, Catholics ought to be a lot more theologically conservative on such matters. They have a clear teaching proclaimed by a clear church authority, with a deep Biblical theology behind it. And yet, on the whole, it doesn’t seem to matter to lay Catholics. Evangelicals, on the other hand, have the Bible, but no binding interpretive authority to keep them from diverging. Yet, on these issues, they are more morally conservative than Catholics — even by Catholic standards.

Why is this? I’m asking in a serious way. Any of you have a theory? I’m not going to publish gratuitous Catholic bashing or Evangelical bashing in the comments.

The best book to fully address this paradox would be D. Jason Slone’s Theological Incorrectness: Why Religious People Believe What They Shouldn’t. But that’s the generality. If you want specifics, see Jay P. Dolan’s In Search of an American Catholicism: A History of Religion and Culture in Tension. Though American Catholics retain identity and affiliation with the Roman Catholic Church, it has operationally become Protestantized when it comes to how people view their relationship to the religion (in a similar way, American Reform Jews also transformed their religion to conform with American confessional Protestantism).

There are a subset of believers who are not well captured by the generalizations in books such as Slone’s, or in ethnographic descriptions which trace the assimilation of Catholicism into the American scene. They are usually highly intellectual and analytical in their orientation. Often, they seem to be converts. Rod Dreher was a convert to Catholicism from Methodism, before he became Orthodox. Leah Libresco and Eve Tushnet also seem to fall into this category. Highly intellectual. And, converts to Catholicism.

Because they are analytical and articulate, these sorts of religious people are highly prominent on the public stage, and, they also write the histories that come down to us through the centuries. These are also the type of people who are overrepresented in the clerical apparatus of any organized religion. This is a problem, because their prominence can obscure the reality that they are not as influential as you might think. As a metaphor, imagine mountainous islands scattering amidst a featureless ocean. The islands are salient. But it is the vast ocean which will ultimately be determinative. Similarly, the vast number of believers who move along a nexus of inscrutable social forces, and driven by powerful universal psychologies, may be hidden from our view.

And yet even for the “analytics” reason does not dictate. Both Dreher and Tushnet have made references to mystical and emotional occurrences and impulses which are beyond my ken. I have no need, no wish, no impulse, and no intuition as to what they are talking about in that dimension (Libresco seems a somewhat different case, but I haven’t read much of what she’s written; I suspect I’ve been in the same room with her since she worked for an organization which I have many personal connections with, but I’m not sure).

It isn’t a surprise that I think Hume was onto something when he asserted that “reason is a slave to the passions.” In many instances I suspect theological analysis is simply the analytic engine being applied to a domain whose ultimate rationale is driven by a passion.

Addendum: Leah Libresco seems to have been associated with the broad umbrella group of Bay Area rationalists. I’ve been associated in some fashion with these people as friends and acquaintances for nearly 10 years. I will admit that I’ve generally found the conceit of rationality as an ends, as opposed to a means, somewhat off-putting. Ultimately I’m more of a skeptic than a rationalist I suppose at the root.

Many people have skin problems. Though luckily I’ve never had an issue with acne, most people who know me personally are aware that I suffered from extreme eczema as a child. Most of the major issues occurred when I was under five years of age, and in my first few years, so I have only minimal first hand recollection. The problem runs in my family, though I was the most extreme sufferer. Eczema also correlates with asthma, something I also suffer from.

Naturally I was curious about this new paper in Genome Biology, Atopic Dermatitis Susceptibility Variants In Filaggrin Hitchhike Hornerin Selective Sweep:

Human skin has evolved rapidly, leaving evolutionary signatures in the genome. The filaggrin (FLG) gene is widely studied for its skin-barrier function in humans. The extensive genetic variation in this gene, especially common loss-of-function (LoF) mutations, has been established as primary risk factors for atopic dermatitis. To investigate the evolution of this gene, we analyzed 2,504 human genomes and genotyped the copy number variation of filaggrin repeats within FLG in 126 individuals from diverse ancestral backgrounds. We were unable to replicate a recent study claiming that LoF of FLG is adaptive in northern latitudes with lower ultraviolet light exposure. Instead, we present multiple lines of evidence suggesting that FLG genetic variation, including LoF variants, have little or no effect on fitness in modern humans. Haplotype-level scrutinization of the locus revealed signatures of a recent selective sweep in Asia, which increased the allele frequency of a haplotype group (Huxian haplogroup) in Asian populations. Functionally, we found that the Huxian haplogroup carries dozens of functional variants in FLG and hornerin (HRNR) genes, including those that are associated with atopic dermatitis susceptibility, HRNR expression levels and microbiome diversity on the skin. Our results suggest that the target of the adaptive sweep is HRNR gene function, and the functional FLG variants that involve susceptibility to atopic dermatitis, seem to hitchhike the selective sweep on HRNR. Our study presents a novel case of a locus that harbors clinically relevant common genetic variation with complex evolutionary trajectories.

This shows the importance of whole genomes, as the earlier result correlation variation to climate seems to be due to ascertainment bias in terms of SNP discovery. Additionally, it’s intriguing that the haplotype which eczema-like diseases are associated with is very ancient. It’s found in Africans, and ancient genomes. So it’s been segregating in human populations for a while. That indicates some sort of balancing selection going on, so that it’s never purified.

What they found is that in Chinese samples there has been a recent positive sweep. I don’t really buy their conclusion that the haplotype wasn’t found in European hunter-gatherers, they don’t have a large enough sample. But it does seem to be a case where there is balancing selection maintaining standing genetic variation, which purified may be selected for or purified in some populations.

This may be a more common dynamic than we might realize. Many complex diseases may exhibit risk profiles due to being dragged up in frequency because of associations with a nearby region, or, a genetic-correlation where the positive benefit is greater than the negative.

One of the most incredible journeys that the human species has undergone is the Austronesian expansion of the past 4,000 years. These maritime peoples seem to have emerged from the islands of Taiwan, and pushed forward south, west, and east, so that their expansion pushed to East Africa, and the fringes of South America. There now also some circumstantial evidence that Polynesian contact with the Americas predates the Columbian Exchange. Looking at the map above in hindsight it seems natural to imagine such contacts.

Though where the Austronesians went is incredible, their origins are somewhat more opaque, but rather tantalizing. That is because their original expansion was likely just before the horizon of history. In Guns, Germs, and Steel Jared Diamond alluded to the “express train” vs. “slow boat” models of the expansion. Basically, whether the Lapita peoples rapidly pushed out from Taiwan, or whether there was a long period of coexistence with Melanesians in Near Oceania. Over the past few years genetics seems to have supported the “slow boat” model.

Here is a paper from 2012, Population Genetic Structure and Origins of Native Hawaiians in the Multiethnic Cohort Study:

The “Express Train” and the “Slow Boat” models of Polynesian migration are expected to have uniquely distinct genetic signatures on present day genomes of Native Hawaiians. Under the “Express Train” model, the proportion of admixture in Native Hawaiians of Melanesian and Asian ancestry is expected to be near zero, whereas under the “Slow Boat” model, the proportion of admixture is expected to be substantially greater than zero. To test these two models, we conducted a supervised ADMIXTURE analysis using Papuan and Melanesians as one source population of Polynesians and Han Chinese, She, Cambodian, Japanese, Yakut, and Yi as surrogates for the second source population of Taiwanese aborigines[18],[19]. Importantly, we did not fix ancestry for the Melanesians or Asians and therefore allowed for admixture within either ancestral groups–thus, mitigating bias by earlier admixture processes and allowing for accurate clusters of ancestry membership. We set K = 2 and estimated in 40 100% Native Hawaiians an average of 32% and 68% of their genomes to be derived from Melanesian and Asian origins, respectively (Figure 4). This notable proportion of Melanesian admixture (32%) among Native Hawaiians, substantially greater than zero, lends support of the “Slow Boat” model of ancestral origins.

This is not an isolated study. Y chromosomes indicate substantial Melanesian admixture, while the mtDNA does not. One inference then was a “slow boat” model predicated on matrifocality. That is, expanding Polynesian groups were centered around matrilineal lineages, and absorbed Melanesian men into their communities. The above research was from a Hawaiian data set, but the results are consistent across Polynesia in relation the proportion of Melanesian ancestry.

Case closed? No so fast! Ancient DNA has now been brought to the question, and fundamentally changed our perceptions. Genomic insights into the peopling of the Southwest Pacific:

The appearance of people associated with the Lapita culture in the South Pacific around 3,000 years ago1 marked the beginning of the last major human dispersal to unpopulated lands. However, the relationship of these pioneers to the long-established Papuan people of the New Guinea region is unclear. Here we present genome-wide ancient DNA data from three individuals from Vanuatu (about 3,100–2,700 years before present) and one from Tonga (about 2,700–2,300 years before present), and analyse them with data from 778 present-day East Asians and Oceanians. Today, indigenous people of the South Pacific harbour a mixture of ancestry from Papuans and a population of East Asian origin that no longer exists in unmixed form, but is a match to the ancient individuals. Most analyses have interpreted the minimum of twenty-five per cent Papuan ancestry in the region today as evidence that the first humans to reach Remote Oceania, including Polynesia, were derived from population mixtures near New Guinea, before their further expansion into Remote Oceanian…our finding that the ancient individuals had little to no Papuan ancestry implies that later human population movements spread Papuan ancestry through the South Pacific after the first peopling of the islands.

These results strong indicate that the original Lapita migration did not mix with Melanesians. And, the ancient samples share common ancestry with modern Polynesians, so that their heritage persists down to the present. Looking at the distribution of Melanesian ancestry they concluded this admixture occurred on the order of ~1,500 years before the present (their intervals were wide, but the ancient samples serve as a boundary). Additionally, in line with the Y and mtDNA the X chromosome indicated more of the ancient ancestry than the autosome. The authors conclude that “it is also possible that some of these patterns reflect a scenario in which the later movement of Papuan ancestry into Remote Oceania was largely mediated by males
who then mixed with resident females.”

The take home message than is that we need to be more modest with our models. Without ancient DNA it seems likely that we would not have stumbled onto this result; the ancestry deconvolution methods which date admixture have wide confidence intervals when you go back far in time.

A friend asked me about population structure, and methods to ferret it out and classify it. So here is a quick survey on the major methods I’m familiar with/utilize now and then. I’ll go roughly in chronological order.

First, you have trees. These are pretty popular from macroevolutionary relationships, but on the population genetic scale (intraspecific, microevolutionary) you’re mostly talking about representing distances between groups in a tree format. You saw this in History and Geography of Genes, where genetic distances in the form of Fst values (proportion of genetic variation unique to between two groups) were used as distance inputs.

A problem with trees is that they don’t model gene flow, a major dynamic on a microevolutionary scale. Also, complex relationships can get elided in tree frameworks, and as you add more and more populations you often end up with an incomprehensible fan-like topology.

Then you have principle component analyses (PCA) and related methods (e.g., multidimensional scaling, which is very different in the sausage-making but generates a similar output). Like trees, this is a visualization of the variation, in this case on a two dimensional plot (please don’t bring up three dimensional PCA, there’s no such thing until holograms show up).

The problem with PCA is that different types of dynamics can lead to the same result. For example, someone who is an F1 of two distinct groups occupies the same position as a population which happens to occupy a genetic position between two groups. Additionally, by constraining the variation into two dimensions, one can mislead in terms of relationships. There are many dimensions, but operationally you focus on on two at a time.

A paper of interest, Population Structure and Eigenanalysis.

Next you have model-based clustering introduced in Jonathan Pritchard’s Inference of Population Structure Using Multilocus Genotype Data. There are many flavors of this, but they operate under the same framework. You have a model of population dynamics, and see how the genotype data can be explained by parameters of the model. Of particular interest is assignment to one of K populations, which can be combined to explain the variation in the data.

Unlike PCA these model-based methods are rather good at identifying people who are first generation mixes, as opposed to those from stabilized groups along a cline. But, they also produce artifacts, because they are quite sensitive to the input data, and lend themselves to cherry-picking.

Earlier I said that one problem with the tree methods is that they don’t model gene flow. Joe Pickrell’s TreeMix does so. Like the original tree methods, and unlike PCA or unsupervised model-based clustering, you specify a set of populations. Then you compare the populations in terms of their genetic distance, and fit them to a tree, but add migration parameters to that tree where the fit between the tree and the data is the most tenuous fit.

All visualizations are deformations of reality. TreeMix attempts to mitigate this somewhat by introducing another representation, that of migration.

Next we have local ancestry methods. By local ancestry, basically we mean methods which can assign ancestry to particular regions of the genome. While tree methods measure differences across pooled populations, PCA and model-based methods compare genotypes between individuals (this is a simplification, but bear with me). Local ancestry methods, like RFMix, compare regions of the genome with each other.

Related to, but not exactly the same, as local ancestry methods are haplotype based methods. In particular, I’m thinking of the FineStructure and its related methods. These leverage variation across the genome in terms of haplotypes, rather than just looking at genotypes. They also tend to benefit from phasing, for obvious methods. FineStructure and its relatives tend to need more marker density than model-based methods, which require more marker density than PCA, which requires more marker density that tree based methods. These haplotype based methods allow for correction of and accounting for forces such as genetic drift, which tend to skew results in other methods.

Finally, there is the AdmixTools framework which is good for testing very explicit hypotheses. While many of the above methods, such as TreeMix and unsupervised model-based clustering, explore an almost open-ended space of structure possibilities, the methods in AdmixTools exists in large part to test narrow delimited models. This goes to the fact that many of these methods are complementary, and you should use them together to arrive at a robust result. For example, if you are assigning populations for TreeMix, you should use PCA and model-based clustering to make sure that the populations are clear and distinct, and outliers are removed.

There’s a lot I left out, but many of the other methods are just twists on the ones above.

In The Horse, the Wheel, and Language: How Bronze-Age Riders from the Eurasian Steppes Shaped the Modern World the archaeologist David Anthony outlines the thesis that migrations from the west Eurasian steppe during the Bronze Age reshaped the culture of Northern Europe. When Anthony published the book, which you should really read if you are interested in this topic, it was a somewhat heterodox position. Though his intellectual pedigree is of long standing, arguably going back centuries, and extending down the present with J. P. Mallory’s In Search of the Indo-Europeans, in the past few decades diffusion of different sort has been paramount. In particular, the thesis that Indo-Europeans arrived with the first agriculturalists was of late ascendant, with some support being received from phylogenetic modeling of language evolution.

Anthony’s thesis in a way was a halfway house between early modern migrationism from the Eurasian steppe the newer theories. He proposes that the influence from the steppe via the Kurgan people was due to elite dominance and cultural emulation. An analogy here might be that of Hungary, where a Ugric speaking elite eventually imparted to the people a language, but very few distinct genes.

Eventually Anthony collaborated with some geneticists, and provided samples for DNA analysis. The results ended up resulting in a resurrection of migrationism, Massive migration from the steppe was a source for Indo-European languages in Europe. From what I have heard Anthony’s reaction was one of some shock as the magnitude of the genetic change.

That’s the high level view. But what about the details? Over the past few years I’ve highlighted work that indicates that many Y chromosomal lineages are star-shaped. That is, they underwent recent demographic expansion. Recent as in on the order of ~5,000 years ago in the past. But the Y chromosome is just one locus. I’ve always been curious about results from the X because the X also gives you good sex specific dynamics; 2/3 of the time it is spent in females, and 1/3 of the time in males.

Amy Goldberg has done so, Familial migration of the Neolithic contrasts massive male migration during Bronze Age in Europe inferred from ancient X chromosomes:

Dramatic events in human prehistory, such as the spread of agriculture to Europe from Anatolia and the Late Neolithic/Bronze Age (LNBA) migration from the Pontic-Caspian steppe, can be investigated using patterns of genetic variation among the people that lived in those times. In particular, studies of differing female and male demographic histories on the basis of ancient genomes can provide information about complexities of social structures and cultural interactions in prehistoric populations. We use a mechanistic admixture model to compare the sex-specifically-inherited X chromosome to the autosomes in 20 early Neolithic and 16 LNBA human remains. Contrary to previous hypotheses suggested by the patrilocality of many agricultural populations, we find no evidence of sex-biased admixture during the migration that spread farming across Europe during the early Neolithic. For later migrations from the Pontic steppe during the LNBA, however, we estimate a dramatic male bias, with ~5-14 migrating males for every migrating female. We find evidence of ongoing, primarily male, migration from the steppe to central Europe over a period of multiple generations, with a level of sex bias that excludes a pulse migration during a single generation. The contrasting patterns of sex-specific migration during these two migrations suggest a view of differing cultural histories in which the Neolithic transition was driven by mass migration of both males and females in roughly equal numbers, perhaps whole families, whereas the later Bronze Age migration and cultural shift were instead driven by male migration, potentially connected to new technology and conquest.

The figure to the left shows the inferences made in regards to the quantitative contribution of farmer males and females, and steppe males and females, to Bronze Age European populations. In short, it looks like the population of Northern Europe derives from a fusion of males from the steppe, and native females, who themselves arose out of a group of peoples which synthesized the ancestry of European hunter-gatherers and West Asian farmers.

But one of the more interesting things about this preprint is that the admixture can’t be modeled by a single pulse event. It seems that there were repeated migrations out of the steppe over multiple generations. But, these men did not bring women, at least in large numbers. The preprint lays out the common sense reason: these were mobile groups, probably bands of men with weapons. If your game is predation on other humans, having a baggage train of women and children is not optimal.

There is a historical analog to what might have happened. Argentina is a nation where mitochondrial lineages show a lot of Amerindian heritage. But the whole genome far less. This is because of male biased migration from Europe. One generation of this would result in a mixed population, but many generations would slowly replace the whole genome.

We will never know in concrete terms what social-political organizations the Indo-Europeans set up once they conquered the plains of Northern Europe, because we don’t have writing. But it seems unlikely that we’re talking about only band or clan level scales of organization. Rather, it was likely that a ‘Indo-European commonwealth’ of some sort existed initially, predicated on domination and extraction of value from the natives. In such a fashion one can imagine Europe being a draw for enterprising males from the steppe. This could also explain likely ‘back migration’ over time, leading to ‘European’ ancestry among later steppe cultures.

As you may know in Britain there is a new direct to consumer genetic testing service, Living DNA. Debbie Kennett has a post up where she talks about how it works and why it’s different. For now it is British focused, and leverages haplotype-based methods with the PoBI database to give really fine-grained analysis to their customers on those sceptered isles.

Brought to you by the same people who brought you FineStructure, this is a major offering in this space.

But there’s a more general issue I want to comment on. In the video accompanying the website, one of the presenters states that people are “very surprised how admixed” humans are. This depends on scale.

Let’s start at a time, 0. In the short term you are not very admixed usually. Outside of the Americans and other settler societies admixture is not common on the scale of recent generations. But as you go further back, you become quite admixed. E.g., The Geography of Recent Genetic Ancestry across Europe showed lots of admixture on 1,000 year scales within Europe. David Reich’s lab has shown lots of admixture between very diverged populations on a 5,000 year scale. But as you go further back the ‘admixture’ gets lower and lower, and at some point you hit the species barrier, and you see the same genealogies coalescing again and again through the bottleneck.

Now, look at space. As distance is ~0 you’ll see lots of admixture. But as you push further and further away, the admixture drops. At some point the admixture is quite boring. Ergo, all the “you are 100% European” results from DTC companies.

The two dimensions look quite different. Admixture increases as you go further back in time…until it doesn’t. You’re hitting the “species” taxonomical barrier. In terms of space, admixture decreases the further you go away from your focal point of interest.

There was a time, five years ago or so, when we knew all the humans who had been sequenced. Or at least most of them. But now we’re coming into the period when the first sequenced animals of any given species are starting to die. Above is Cinnamon, the first sequenced cat is no longer with us. And some day the hour will come when Craig Venter, who was a major contributor to the first human genome, will no longer be with us.

Something to consider.