The Eurogenes blog is running a fundraiser. I chipped in mostly to support his continued blogging. I don’t agree with everything he posts, but the site is a good and valuable resource. “Genome blogging” hasn’t gotten as far as I’d have thought it would have in 2010, mostly because the initial burst of enthusiasm wasn’t followed up by a consistent producer community (in addition to the commentariat). But Eurogenes soldiers on….

In any case, as part of the donation I got an analysis of my genotype. I wasn’t super interested in this because I know a fair amount about my genotype, and the analysis isn’t too informative for someone like me who is >10% East Eurasian. But I thought I would post the PCA because it’s interesting. It’s hard to see in the image above (click it for a larger version), but you notice that I am almost equally positioned between the antipodes of Eurasia (Western Europeans vs. East Asians). Most South Asians occupy a position in between, but definitely skewed toward West Eurasians (the green). But you notice I’m nearly the most “eastern” of the main cluster of South Asians. Depending on how you calculate it I’m between 10% and 20% East Eurasian. This “pulls” me in that direction more than almost all other South Asians. Like a colossus I look east, and I look west, and stand athwart Eurasia bridging the gap.

In any case, if you have $12 to spare, think about donating to Eurogenes. Logistics are at the link.

Listened to an interesting interview this morning with the author of a new book, The Latinos of Asia: How Filipino Americans Break the Rules of Race. There was a lot to agree with and disagree with, but it rang true in many ways for me because I have had a fair number of students with roots in the Philippines. An early portion of the interview illustrates an important dynamic. The author himself has parents from the Philippines and when his university was running a study on alcohol consumption and those of “Asian” ancestry. When he approached to be a participant though the researchers said that what they were looking for were people of Japanese, Korean and Chinese ancestry, because they had the right “population structure.”

Naturally this was somewhat offensive. The author pointed that as a sociologist he believes race is a “social construct.” It is also the case that people from the Philippines occupy a someone liminal position of both “Asian” and “Latino” identities. As a South Asian I can relate, as I am “Asian”, but not “typically” Asian.

From what I can gather the research group was rather artless in the way they communicated their necessary conditions for their project, but the researchers probably were correct in excluding the author. Alcohol flush reaction segregates in only a finite set of East Asians. With limited resources it is rational for them to exclude individuals from populations where the variants of interest are not present, or at very low frequencies.

The problem is that the author confuses the terminology, “Asian”, with reality. A common tendency in the “post-modern” style of thought is putting primacy in the power of language to shape our perception of reality. The fact is that people from the Philippines have very distinct genetic structure in relation to Northeast Asians. Whether they are categorized as Asian or Latino does not truly impact that fact, unless one is of Chinese background and from the Philippines. To me it is ironic that so many scholars place into language so much power when language is only an imperfect mapping onto reality.

Would You Want To Know The Secrets Hidden In Your Baby’s Genes? Turns out most people don’t. The article profiles the BabySeq Project, and the offer of whole exome sequencing (exomes are the parts of the genome which code for proteins).

In some ways, the results were discouraging:

One thing Green hadn’t anticipated is how hard it has been to convince new parents to do this screening in the first place. Early research showed the majority of parents were interested in the medical information. But 94 percent of parents Green and his team are approaching are saying no.

So that leaves 6 percent. That’s not a trivial number. There are about 4 million babies born per year, so that would be 240,000 newborns with their exome sequenced. And part of the balking is just fear. People will get over this. Technologies like this have an S-shaped adoption curve. It starts out low at first, and then expands to most of the population. Some portion will always opt-out, and that’s their right.

Probably the bigger issue is that people need to not overreact. A lot of loss-of-function mutations turn out to be innocuous in many people.

There are several reports in the media about a third hominin group besides Denisovans and Neanderthals, and how they contributed to Melanesians. Science News has a sober summary of it all.

Several people have asked me on email and Twitter about this, and I told them to ignore it. The reason I say this is that I was in the room when the presentation was given, and it was clear people were having a hard time following what was going on. Afterward several pretty intelligent statistical human geneticists expressed great confusion.

A few things to take away. First, it was a presentation at a conference. One can’t expect very novel findings to be understood easily in a 15-30 minute talk. Wait for the preprint at least. Second, this was a presentation at a conference. A lot of presentations don’t pan out. If it’s a really surprising theoretical or interpretative finding, as opposed to sequencing a new species (an empirical result), generally I don’t pay close attention. A lot of time the reason that no one else has stumbled onto the surprising results is that they are wrong, or trivial upon further inspection.

Finally, there are complexities of human history we don’t have a good grasp on. There may indeed be other hominins which contributed to the human gene pool to the point of detectable admixture. I think it is likely. But it is a different thing to have specified all the details.

Basically, I wish the press would set a higher bar for presenting on new results from conferences. It’s not even that it’s not been peer reviewed. Often the results are provisional, and they don’t end up turning into the paper that’s promised.

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.

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.

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.