In the near future I will be analyzing the genotype of an individual where all four grandparents have been typed. But this got me thinking about my own situation: is there a way I could “reconstruct” my own grandparents? None of them are living. The easiest way to type them would be to obtain tissue samples from hospitals. This is not totally implausible, though in this case these would be Bangladeshi hospitals, so they might not have saved samples or even have a good record of hem. Another way would be to extract DNA from the burial site. This is not necessarily palatable. But assuming you did this, if you have access to a forensic lab it might be pretty easy (though I think most forensic labs using VNTRs, rather than SNP chips, so I don’t know if they’d touch every chromosome), I’m not sure that the quality would be optimal for more vanilla typing operations, especially for older samples which are likely to be contaminated with a lot of bacteria.
For me the simplest option is to look at relatives. Each of my grandparents happens to have had siblings, so there are many sets of relatives related to just each of those individuals of interest. I also have many cousins, so pooling all the genotypes together and using the information of a pedigree one could ascertain which chromosomal segments are likely to derive from a particular grandparent. To give a concrete example, my mother has a maternal cousin to whom she is quite close. By typing my mother and her cousin one could infer that the segments shared across the two individuals derive from the common maternal grandparents. Of course there’s a problem that cousins have a coefficient of relatedness of only 1/8th, so there is going to be a lot of information missing. But, if you had lots of cousins you could presumably reconstruct the genotypes far better.
There is a new paper in PLoS Genetics out which purports to characterize the ancestry of the populations of northern Africa in greater detail. This is important. The HGDP data set does have a North African population, the Mozabites, but it’s not ideal to represent hundreds of millions of people with just one group. The first author on this new paper is Brenna Henn, who was also first author on another paper with a diverse African data set. Importantly the data was posted online. Unfortunately though most of the populations didn’t have too many markers. This isn’t an issue in an of itself, but it becomes a big deal when trying to combine it with other data sets. If you limit the markers to those which intersect across two data sets you start to thin them down a lot, to the point where they’re not useful. Though the the results of the paper are worth talking about, the authors claim that they’ll be putting the data online. This is important because they used a large number of markers, so the intersections will be nice (I can, for example, envisage exploring the relationship between the North Africans and the IBS Iberian sample in the near future).
As for the paper itself, Genomic Ancestry of North Africans Supports Back-to-Africa Migrations:
Get ready for PGD, the acronym for preimplantation genetic diagnosis. We don’t really talk about “test tube babies” anymore. It’s “IVF,” and as American as apple pie (OK, perhaps as Israeli as falafel). Here’s the Ngrams result:
Hominin increase in cranial capacity, courtesy of Luke Jostins
A few years ago a statistical geneticist at Cambridge’s Sanger Institute, Luke Jostins, posted the chart above using data from fossils on cranial capacity of hominins (the human lineage). As you can see there was a gradual increase in cranial capacity until ~250,000 years before the present, and then a more rapid increase. I should also note that from what I know about the empirical data, mean human cranial capacity peaked around the Last Glacial Maximum. Our brains have been shrinking, even relative to our body sizes (we’re not as large as we were during the Ice Age). But that’s neither here nor there. In the comments Jostins observes:
The data above includes all known Homo skulls, but none of the results change if you exclude the 24 Neandertals. In fact, you see the same results if you exclude Sapiens but keep Neandertals; the trends are pan-Homo, and aren’t confined to a specific lineage….
The genetic model of the “Out of Africa” scenario is getting more complex. There may be two waves, as well as the likelihood of admixture between the Neo-Africans and “archaic” hominins, such the Neandertals and Denisovans. From what I can gather the genetic evidence is now converging upon the sequence of events where African populations diverge >100,000 years ago (e.g., a deep separation between the ancestors of the Bushmen and the ancestors of West Africans), and a radiation of non-Africans at most ~75,000 years ago, and more likely ~50,000 years ago. There are still many holes to be plugged in. While we’re waiting on genetics, here’s an interesting paper using archaeological methods in PLoS ONE, The Nubian Complex of Dhofar, Oman: An African Middle Stone Age Industry in Southern Arabia:
In the middle years of the last decade there were many papers which came out which reported many ‘hard’ selective sweeps reshaping the human genome. By this, I mean that you had a novel mutation arise against the genetic background, and positive selection rapidly increased the frequency of that mutation. Because of the power and rapidity of the sweep many of the flanking regions of the genome would “hitchhike” along, generating long homogenized regions of linkage disequilibrium. If that’s a little dense for you, just understand that very strong selective events tend to result in disorder and distinctiveness in the local genomic region.
But the late aughts and the early years of the teens are shaping up give us a more subtle picture. Instead of classic hard sweeps, researchers are suggesting that there may also be many ‘soft’ sweeps, where selection draws upon the well of standing genic variation. Instead of a novel trait becoming prominent, one tail of the distribution would rise in frequency. The ‘problem’ with this model is that it’s not as tractable as the earlier one of hard sweeps, and selection on quantitative traits with many loci of small effect is more difficult to detect. Its effect on the genome is more subtle and understated, which means that statistical tests often lack the power to grasp onto the underlying dynamics. Naturally this means that there is an extension of statistical techniques to ever greater degrees of sophistication. A new paper in PLoS Genetics attempting to tease apart the various potential selective pressures in the human genome is reflective of that tendency. Signatures of Environmental Genetic Adaptation Pinpoint Pathogens as the Main Selective Pressure through Human Evolution:
Last August I had a post up, The point mutation which made humanity, which suggested that it may be wrong to conceive of the difference between Neanderthals and the African humans which absorbed and replaced them ~35,000 years ago as a matter of extreme differences at specific genes. I was prompted to this line of thinking by Svante Pääbo‘s admission that he and his colleagues were searching for locations in the modern human genome which differed a great deal from Neanderthals as a way through which we might understand what makes us distinctively human. This sort of method has a long pedigree. Much of the past generation of chimpanzee genetics and now genomics has focused on finding the magic essence which differentiates us from our closest living relatives. Because of our perception of massive phenotypic differences between H. sapiens and Pan troglodytes the 95-99% sequence level identity is thought by some to be perplexing. Therefore models have emerged which appeal to gene regulation and expression, or perhaps other forms of variation such as copy number, to clear up how it can be that chimpanzees and humans differ so much. Setting aside that the perception of difference probably has some anthropocentric bias (i.e., would an alien think that chimpanzees and humans are actually surprisingly different in light of their phylogenetic similarities? I’m not so sure), it doesn’t seem to be unreasonable on the face of it to plumb the depths of the genomes of hominids so as to ascertain the source of their phenotypic differentiation.
But can this model work for differentiating different hominin lineages? Obviously there’s going to be a quantitative difference. The separation between chimpanzees and modern humans is on the order of 5 million years. The separation between Neanderthals and modern humans (or at least the African ancestors of modern humans ~50,000 years B.P.) is on the order of 500,000 years. An order of magnitude difference should make us reconsider, I think, the plausibility of fixed differences between two populations explaining phenotypic differences.
But the other big feature is that the lake-filling events that occurred after 50,000 years ago were much smaller than those which occurred before. Climactically, the conditions 10,000 years ago should have been the same as the conditions 115,000 years ago. But the lake was only a fraction of the size. The authors find no natural causes which can explain this. So they suggest that the aridity starting around 50,000 years ago is related to the reduction in forest and increase in grasslands which occurred at this time. This vegetation change was a result of a huge increase in the frequency of fire in central Australia, which allowed fire-adapted plants to prosper at the expense of moisture-retaining forest. The increase in fire at this time is generally associated with the arrival of the first people on the Australian continent. It is known that of Australia’s megafauna went extinct at this time, but Magee et al. (2004) show that even the tropical rains were effected by human migration, with drastic changes to the continent’s largest river basin.
If you read some of the academic literature on fire ecology you have a hard time not coming to the conclusion that modern humans terraformed the planet Earth! The hallmark of modern H. sapiens seems to be extinction of large organisms, a propensity to go where no hominin has gone before, and copious utilization of the “red flower.”
The Pith: The Bushmen branch of the human family tree diverged ~130,000 years ago. The non-Africans branched off from the Africans ~50,000 years ago. The Europeans and East Asians diverged ~35,000 years ago.
One of the terms in paleoanthropology which can confuse is that of archaic Homo sapiens (AHS). This is in contrast to anatomically modern humans (AMH). A simple Out of Africa “recent-origin-with-replacement” model allowed to sidestep the semantic imprecision in tossing disparate populations into a generic category such as AHS (similarly, the term “animal” as opposed to “human” has some colloquial utility, but it’s not scientifically useful). But the possibility of admixture from archaic lineages in modern human populations forces us to grapple with the dichotomy between AHS and AMH, as modern humans may be a compound of these two categories (not to mention the idea of behaviorally modern humans, who are a subset of AMH).
I assume that fleshing out the details of a new paradigm which is both precise and accurate will be a project for the coming years. But before we move on we need to fix more sturdily our understanding of the genealogical relationships of contemporary human populations. Over the past few years there have been major strides in this domain, confirming the broad outline of a dominant African heritage for modern humans. Geneticists have moved from classical markers to SNP data, focusing on hundreds of thousands of genetic variants. But now they’re shifting to whole genome sequences, which with errors excepted encapsulate the totality of the lowest order aspect of human genetic variation.* Earlier this summer I reviewed a paper in Nature which was a foretaste, Inference of human population history from individual whole-genome sequences. Today Nature has published another, Bayesian inference of ancient human demography from individual genome sequences.
The BBC has a news report up gathering reactions to a new PLoS ONE paper, The Later Stone Age Calvaria from Iwo Eleru, Nigeria: Morphology and Chronology. This paper reports on remains found in Nigeria which date to ~13,000 years B.P. that exhibit a very archaic morphology. In other words, they may not be anatomically modern humans. A few years ago this would have been laughed out of the room, but science moves. Here is Chris Stringer in the BBC piece:
“[The skull] has got a much more primitive appearance, even though it is only 13,000 years old,” said Chris Stringer, from London’s Natural History Museum, who was part of the team of researchers.
“This suggests that human evolution in Africa was more complex… the transition to modern humans was not a straight transition and then a cut off.”
Prof Stringer thinks that ancient humans did not die away once they had given rise to modern humans.
They may have continued to live alongside their descendants in Africa, perhaps exchanging genes with them, until more recently than had been thought.
I’ve been chewing on the modern human range expansion into Neandertal territory paper for a few days now. But I haven’t been able to bring myself to say much. There are two reasons. First, it’s a simulation paper, and I don’t exactly know what I can say besides being skeptical of the plausibility of some of their results and their assumptions, unless I bother to replicate their simulations. There’s something of a “black-box” aspect from the outside operationally in the case of these sorts of research. Second, Ed Yong has boiled down the paper to its essence rather well, while John Hawks and Dienekes have offered their critiques. Dienekes and John get at one of my gnawing worries about all these sorts of models about deep history. Here’s John:
I’m going to address two points in this post. The next possible target for getting an undersampled population, and the Malagasy results.
First, lots of great submissions in regards to populations which are undersampled. Some of them are actually already in the data sets. For example, the Burusho and Kalash are in the HGDP. There has been a major dump of data from the Americans recently as well. Zack Ajmal at HAP has the most systematic description online about where to find these that I know of. Additionally, I’m looking for stuff which is interesting where N = 1 would make a difference. I think that was the case for the Tutsi sample, as well as the Malagasy. When you have no prior information, adding one data point is notable. Obviously I can’t afford the money, time, and energy, required to get a good representative sample from a given region. Though I hope researchers who have a gusher of grant money might look at the above thread for ideas.
I think the next population to look for is someone with Ainu ancestry. This is easier said that done, so I need to think about it (both because of dilution and the language barrier). But then again, the Tutsi and Malagasy requests had a much more positive and faster turnaround than I had expected. So I’m not going to get all down about the likelihood.
Even if the odds of successful interbreeding were just 5 percent, Neanderthal genes would make up the majority of the human genome today. As it is, a lack of viable sex explains why none of the Neanderthals’ mitochondrial DNA made its way into modern humans, and why so little of their main genome did.
Currat and Excoffier suggest that either modern humans and Neanderthals didn’t have sex very often, or their hybrids weren’t very fit. They favour the first idea. According to their model, it would only have taken between 197 and 430 liaisons between ancient humans and Neanderthals to fill 1-3 percent of modern Eurasian genomes with Neanderthal DNA. Considering that they two groups probably interacted for 10,000 years or so, it would have been enough for one human to sleep with one Neanderthal every 23 to 50 years.
From what I gather in the comments this is due to the fact that if there was a wave of advance very small levels of admixture per unit of advance can build up rather rapidly. I think this is easy to express in temporal rather than spatial terms.
For example, let’s imagine a population of modern humans expanding into a population of Neandertals. The original source population doesn’t receive any more contributions after the initial push, so you have a series of admixture events over time. Assuming 5% admixture per generation, this is the dilution of the “original ancestry” which would occur over 30 generations, or 750 years:
Unlike in some Asian societies dairy products are relatively well known in South Asia. Apparently at some point my paternal grandmother’s family operated a milk production business. This is notable because Bengal is not quite the land of pastoralists. In much of North India milk and milk-products loom larger, in particular ghee. People don’t tend to consume what makes them ill, and even accounting for some processing in the form of butter, most researchers have assumed a substantial number of South Asians must be lactase persistent. That is, they can extract nutritive value out of the lactose sugar present in milk (in addition to fat and protein). Additionally, many South Asians have the well known -13910 C>T common in Western Eurasia. How do I know this? Because I share my genetic information with lots of South Asians, and some of them, especially Punjabis, come up as “lactose tolerant” on that allele.
A new paper in Molecular Biology and Evolution confirms this with a larger data set, over 2000 samples from South Asia. The geographical pattern is exactly what you’d expect:
One thing that came to the fore in late 2008 was the worry that a financial regulatory regime which had been exceeding lax was now more conscious of the excesses of the previous era. The problem being that one will not necessarily be prepared for the next crisis. Similarly, terrorist actions such as those of the 9/11 hijackers are probably unlikely in their specific details, because the element of surprise is gone. That’s what makes much of the TSA “security” measures so frustrating for many people, there is a strong suspicion that the authorities are aiming to prevent the previous operation, when real terrorists will naturally alter tactics.
I thought of that when forwarded a link to a new book by a friend, Race and the Genetic Revolution: Science, Myth, and Culture. Here’s the summary:
Do advances in genomic biology create a scientific rationale for long-discredited racial categories? Leading scholars in law, medicine, biology, sociology, history, anthropology, and psychology examine the impact of modern genetics on the concept of race. Contributors trace the interplay between genetics and race in forensic DNA databanks, the biology of intelligence, DNA ancestry markers, and racialized medicine. Each essay explores commonly held and unexamined assumptions and misperceptions about race in science and popular culture.
This collection begins with the historical origins and current uses of the concept of “race” in science. It follows with an analysis of the role of race in DNA databanks and racial disparities in the criminal justice system. Essays then consider the rise of recreational genetics in the form of for-profit testing of genetic ancestry and the introduction of racialized medicine, specifically through an FDA-approved heart drug called BiDil, marketed to African American men. Concluding sections discuss the contradictions between our scientific and cultural understandings of race and the continuing significance of race in educational and criminal justice policy.
“There were giants in the earth in those days; and also after that, when the sons of God came in unto the daughters of men, and they bare [children] to them, the same [became] mighty men which [were] of old, men of renown.”
The Pith: Pygmies and Khoisan have admixture from a distinct population at the level of ~2%. This population diverged from the other ~98% of their ancestry ~700,000 years before the present, and the hybridization occurred ~30-40,000 years before the present. Most other African groups have only traces of this element, with some West Africans lacking it.
I have read the paper in PNAS which I referred to below. There isn’t that much I can add at this point. A lot of the guts were pushed into the supplements, which aren’t on the web yet. I was correct that the Mbuti Pygmies of the eastern Congo likely have a special place in this possible admixture event. In particular, they seem to possess the diverged variants found in the western Pygmies, the Biaka, and the Khoisan populations of southern Africa. As assumed the pattern of admixture seems to be such that the two Pygmy groups and the Khoisan exhibit elevated signatures of archaic contributions, while other African groups manifest admixture in direct proportion to their known admixture to the aforementioned populations. For example, the Bantu group with the highest proportion of admixture are the Xhosa, who also have the most Khoisan ancestry of non-Khoisan populations. The West African Mandenka seem to have trivial admixture from this archaic group. What does this mean?
Last year when discussing the possible admixture of Neandertals with the ancestors of modern non-Africans I joked that Sub-Saharan Africans were “pure humans.” This was tongue-in-cheek in part because the results from the Neandertal genome shifted my assessment of the probability of archaic admixture within Africa as well. In other words, there may never have been a pure “human” type which expanded and assimilated archaic ancestry on the margins of its range. Species Platonism may be very misleading for our particular lineage. Rather, what it means to be human has always been in flux, a compromise between extremely different ancestral components.
I first heard about Rwanda in the 1980s in relation to Dian Fossey’s work with mountain gorillas. The details around this were tragic enough, but obviously what happened in 1994 washed away the events dramatized in Gorillas in the Mist in terms of their scale and magnitude. That period was a time when the idea of “ancient hatreds” leading to internecine conflict was in the air. It was highlighted by the series of wars in the former Yugoslavia, and the Tutsi–Hutu civil wars in Rwanda, Burundi, and Congo. Of the latter the events in 1994 in Rwanda were only the most prominent and well known.
After having read Dancing in the Glory of Monsters: The Collapse of the Congo and the Great War of Africa I am relatively conscious of the broader canvas of what occurred in Central and East Africa in the 1990s. Not only was there a conflict between Tutsi and Hutu in Rwanda, but a similar dynamic also flared up in Burundi. The tensions are more complex in Congo and Uganda, in large part because there are many ethnic players, and the Hutu role as the antagonists with the Tutsi is divided among many different populations. In trying to distill the complex ethnography of this region in setting the structural parameters of the landscape into which the violence of the late 20th century emerged many pundits have pointed to the role of the Belgian colonial authorities in crystallizing, sharpening, and perhaps even originating the distinction between Tutsis and Hutus. This is not totally unreasonable if you don’t know much. A quick “look up” will confirm that there is no linguistic or religious distinction between the two groups; they share a common culture in many ways. Rather, the differences seem more of class and ecology. The Tutsi minority had a much stronger pastoral element to their economy. The Hutus were conventional farmers, clear legacies of the Bantu expansion which swept from West-Central Africa east and south, all the way to the Cape of Good Hope and the Indian Ocean. As is not uncommon in the history of humankind the pastoral Tutsi tended to dominate the Hutu peasant. This is where the class dimensions are clearest, as the modest Hutu were traditionally ruled by the wealthier Tutsi aristocracy.
The class human or H. sapiens refers to a set of individuals. On the grand scale it’s really not all that clear and distinct. When do “archaic” humans become “modern” humans? Taking into account human variation, what is a “human universal”? A set of organisms are given a name which denotes the reality that they may share common ancestry, and interact behaviorally, and are potential mates. But many of these phenomenon are fuzzy on the margins. Many of the same issues which emerge in the “species concept” debates are rather general up and down the scales of natural complexity. A similar problem crops up when we conflate the history of genes with the history of populations. Such a conflation has value and utility to a first approximation. The story of mitochondrial Eve was actually the history of one particular locus, the mitochondrial genome. But it did tell us quite a bit about the history of the human species, even if in hindsight it looks as if some scientists overinterpreted those findings. One of the major issues I’ve noticed over the past year, with the heightened likelihood of archaic admixture in the modern human genome, is that people regularly get confused by the difference between total genome ancestry, and the evolutionary history of one particular gene.
Back in the 1990s there was a lot of controversy around the Human Genome Diversity Project. In fact there were whole books devoted to the sociology of the project. Though on some of the details critics of the project may have had a point, their overall aim of stalling scientific inquiry in this area failed in totality. A few years ago a team out of the University of Chicago even produced a web browser so you can explore the data yourself. To my knowledge this hasn’t resulted in massive genocidal action against indigenous peoples; the human race doesn’t seem to need any scientific backing for that, alas.
But, if I was a Lefty the-man-is-racist type I think I might assert that the chips which were used to generate the 600,000 markers for the HGDP public data set are racist! I’m not one of those types, so what I really am concerned about is ascertainment bias. From what I have heard many of the SNP chips floating around today are looking for variants found in Europeans most often. That’s because so many study populations in medical genetics are of European descent. This is not a total deal breaker, a lot of European variation is useful in understanding world wide patterns of variation. But ultimately it’s not optimal.