john hawks weblog

Looking for the vulture assist with Neolithic burials

2020-05-27T00:00:00-05:00

The archaeological site of Çatalhöyük, in present-day Turkey, is one of the most significant early Neolithic villages to have been excavated. It was occupied between around 7100 and 6000 BC, and at its height was occupied by more than 3500 people. An array of human skeletal remains have been found at the site. Many of them were buried in the floors of houses in flexed pit burials.

One interesting aspect of the burials is that many were in an extremely flexed position. Legs were tucked against the chest in a tight position that seems anatomically unlikely if flesh had been on the skeletons at the time they were buried. This has given rise to the hypothesis that the bodies had been defleshed in some way before they were buried.

Marin Pilloud and coworkers in 2016 published a paper suggesting that the Çatalhöyük bodies were possibly defleshed by vultures. A brief excerpt from the conclusion gives the gist of their argument:

The burial practices at Çatalhöyük (i.e., removal of cephalic extremity, limb removal, tight flexion) as observed in the archaeological record are often consistent with some manner of flesh removal prior to interment. It seems possible based on current forensic experimental work that the people of Çatalhöyük may have employed vulture excarnation prior to interment. Based on human studies, vultures are unlikely to leave marks on the bone that would be visible 9000 years later.

It’s an interesting concept. The paper goes into some of the symbolic meanings of vultures and the possibility that bodies were exposed on the roofs of residences for vultures to approach.

Looking for the vulture assist with Neolithic burials was originally published by John Hawks at john hawks weblog on May 27, 2020.

Getting species diagnoses non-destructively from collagen

2020-05-24T00:00:00-05:00

A neat paper by Naomi Martisius and coworkers in Scientific Reports: “Non-destructive ZooMS identification reveals strategic bone tool raw material selection by Neandertals”.

The introduction of the paper presents the problem that the researchers set out to solve. How can we get biological identifications of modified bone fragments without drilling into them to extract protein? The answer is provided by a new method that can examine the trace amounts of collagen that adhere to plastic surfaces after they contact a bone. This includes the plastic bags that are used to store artifacts and archaeological bone samples.

ZooMS has been useful for identifying ancient animal remains when fragmentary bones present a challenge for more traditional methods. The method has been used to identify fragmented animal and human remains from Paleolithic sites, as well as cultural artifacts from various time periods, including bone tools and parchment. Such objects frequently have been significantly altered from their original form making taxonomic identifications based on morphology nearly impossible. At the same time, conventional ZooMS extraction procedures involve drilling or cutting a bone sample (less than 20 mg), thereby altering often unique and fragile artifacts (Supplementary Fig. S1). Recently, a non-destructive approach based on the triboelectric effect occurring between collagen and plastic surfaces has been developed to sample parchment for ZooMS analysis. The concept behind this approach has been applied to plastic storage bags containing bone artifacts as well, as the use of erasers carries the risk of modifying bone surfaces through abrasion. Here, we show that collagen molecules adhering to the plastic surfaces allow us to infer species selection of Middle Paleolithic lissoirs made by Neandertals, which then permits the consideration of competing hypotheses about the selection of ribs as the raw material for making lissoirs.

This is a significant advance. For those of us who grapple with decisions about destructive sampling, every non-destructive approach provides us with the potential of making better decisions. It won’t always be the right thing to use these non-destructive approaches. Some biological and anthropological questions will merit a fuller examination of larger samples. But the availability of a non-destructive method means that we can be deliberate in choosing the best method for each scientific question. We can better leverage the knowledge we gain from some samples to conserve others.

The result of the study is itself interesting. The fact that Neandertals were consistently choosing bovid ribs for these specialized tools, even though bovid remains are rare at the site, gives useful insight into the entire process behind their use of technology. They planned for later use of tools and curated material to make effective use of hides from later kills.

Getting species diagnoses non-destructively from collagen was originally published by John Hawks at john hawks weblog on May 24, 2020.

How mice became house mice

2020-05-23T00:00:00-05:00

A new paper from Thomas Cucchi and coworkers in Scientific Reports probes the early history of the house mouse: “Tracking the Near Eastern origins and European dispersal of the western house mouse”.

A quick taxonomy of house mouse subspecies:

Although often overlooked compared with commensal rats (Rattus rattus, R. norvegicus and R. exulans), this elusive mammal has been a much more successful invasive rodent, becoming almost as ubiquitous as H. sapiens. Originating in the Indo-Pakistan subcontinent and neighbouring Afghanistan and Iran, house mice differentiated during the Pleistocene climatic oscillations into three main Mus musculus subspecies (M. m. domesticus, M. m. musculus and M. m. castaneus). All these subspecies are human commensals, facilitating their long-distance colonization and ultimately their cosmopolitan range.

The authors frame their work as ultimately an inquiry into the domestication and spread of cats:

The earliest and most striking evidence of cat domestication comes from 9,500 cal BP in Pre-Pottery Neolithic (PPN) Cyprus. Its introduction onto the island is thought to be tied to the control of the proliferation of the house mouse populations, present on the island since the Early PPNB26. The appearance of the domestic cat in western European archaeological contexts during the Iron Age, around 3,000 years ago, is synchronous with the strong evidence for the house mouse biological invasion of western Europe. This co-dispersal of cats and house mice has also been mentioned in literary sources, describing the deliberate transport of domestic cats on ships to control rodent pests, inducing its worldwide distribution. This co-phylogeography supports the premise that understanding the house mouse’s origin and dispersal can lead to insights pertaining to the origin of domestic cats and their subsequent dispersal.

Honestly I think that the process by which species become commensal with people is even more interesting than domestication. Humans exert intentional control over domestication. Commensal animals adapt to human-created environments largely on their own with little or no intentional human selection. Many would argue that cats are commensal rather than domesticated, and that may well have been true for much of the early history of domestic cats. Global house mouse (Mus musculus) populations exist in human-created habitats and are specialists within them.

The paper is mostly a straightforward review of first appearance dates and range expansion of the house mouse across the Levant and southeastern Europe. It’s not a full history. The authors have done work to understand which mice were inhabiting pre-agricultural sedentary populations of the Levant, followed by the spread of those mice into the eastern Mediterranean more broadly.

Most interesting, the mice adapted to human settlements before people started keeping granaries:

The earliest commensal populations of M. m. domesticus found in Natufian sedentary settlements (14,500 cal BP) confirm that the impact of sedentism on ecosystems and the ecology of organisms (i.e. reduction of predation and competition pressures, climatic buffer etc) was the catalyst for the commensal relationship between mice and humans rather than the emergence of agriculture systems with large-scale grain storage, which emerged two millennia later. Nevertheless, M. m. domesticus was identified only in the largest, long-term Natufian settlements such as ‘Ain Mallaha in the Southern Levant and Mureybet in the Northern Levant between 14,500 and 12,000 BP. In smaller and shorter term Natufian sites in the Southern Levant, only the native mouse Mus macedonicus was identified. This pattern suggests that dense human occupation in large open air settlements was the prerequisite for M. m. domesticus to eventually outcompete other potential anthropophilous rodent like M. macedonicus from the Natufian ecological niche.

That suggests that the protection that human settlements provided from other nonhuman predators may have been more important than human-accumulated food resources that mattered to mice. Sure, there was plenty of trash to eat around human settlements even without large-scale grain storage. But a reduction in predation from raptors and small carnivores created a very attractive environment for a small rodent.

How mice became house mice was originally published by John Hawks at john hawks weblog on May 23, 2020.

Goat immunity modified by introgression during and after domestication

2020-05-21T00:00:00-00:00

Goat domestication may provide another example in which introgression brought new genetic variations conferring advantages for immunity into a population. A new paper in Science Advances by Zhuqing Zheng and collaborators looks at modern domesticated goats and wild relatives from several species, and also a handful of ancient goat genomes: “The origin of domestication genes in goats”.

Here’s the abstract:

Goat domestication was critical for agriculture and civilization, but its underlying genetic changes and selection regimes remain unclear. Here, we analyze the genomes of worldwide domestic goats, wild caprid species, and historical remains, providing evidence of an ancient introgression event from a West Caucasian tur-like species to the ancestor of domestic goats. One introgressed locus with a strong signature of selection harbors the MUC6 gene, which encodes a gastrointestinally secreted mucin. Experiments revealed that the nearly fixed introgressed haplotype confers enhanced immune resistance to gastrointestinal pathogens. Another locus with a strong signal of selection may be related to behavior. The selected alleles at these two loci emerged in domestic goats at least 7200 and 8100 years ago, respectively, and increased to high frequencies concurrent with the expansion of the ubiquitous modern mitochondrial haplogroup A. Tracking these archaeologically cryptic evolutionary transformations provides new insights into the mechanisms of animal domestication.

The abstract understates the evidence for introgression on genes related to immunity. The mucin gene mentioned in the abstract stands out because the current frequency of the introgressed allele is near fixation, indicating strong selection since its introduction into domesticated goats. But many other genes influencing immunity have also come into domesticated goats by introgression.

A passage later in the paper presents some of the complexity that Zheng and coworkers found:

D statistics reveal that all four ibex-like species have significant signals of allele sharing with ancient and modern goats, indicative of admixture (Fig. 2C and table S8). We then examined this genome-wide pattern of admixture between ibex-like species and domestic goats using D statistics and identity by state in 20-kb sliding windows. We further verified candidate introgressed regions using Sprime and maximum likelihood (ML) phylogenetic trees. Using a conservative criterion (namely, only keeping putative introgressed haplotypes with a frequency higher than 0.1 in goats), we identified 112 genomic segments overlapping with 81 protein-coding genes with signatures of introgression from ibex-like species (Fig. 2D, fig. S16, and data file S1). A Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis for these genes shows that the most significantly enriched category is amoebiasis (hypergeometric test, adjusted P < 5.28 × 10−3: table S10), which is related to parasite invasion and immunosuppression, including four genes (SERPINB3, SERPINB4, CD1B, and COL4A4). Three additional genes (BPI, MAN2A1, and CD2AP) are also involved in immune function (19–21). In these segments, we observed a pronounced signature of putatively introgressed alleles from the West Caucasian tur (fig. S17), consistent with this species showing the greatest genome-wide allele sharing with domestic goats (Fig. 2C).

It’s not obvious to me how the authors ruled out the hypothesis of reverse introgression from domesticated goats into some of the wild relatives as a cause for some similarities that they found. Certainly domesticated goats have been more numerous in recent times than the wild species. The authors did show some evidence for introgression among the wild species prior to domestication. I suspect there is more of a story to be found there.

The evidence from ancient genomes here is very slight. It did, however, show the presence of the introgressed alleles in the domesticated goat material from before 7000 years ago. The complexity of the domestication process seems to have been quite impressive in this case, drawing in adaptive variation from multiple species of wild caprids.

When I wrote about introgression in my 2006 paper, I spent a lot of time investigating the phenomenon in cattle, including the four wild species of cattle and the progressive spread of zebu genes into taurine cattle that followed domestication. I knew very little about goats. Goats seem like an even more complicated scenario in some ways.

Goat immunity modified by introgression during and after domestication was originally published by John Hawks at john hawks weblog on May 21, 2020.

Twins from an adaptive point of view

2020-05-14T00:00:00-00:00

The biological anthropologist Rebecca Sear looks at the evolution of human twinning in a post for This View of Life: “Solving the Evolutionary Puzzle of Twinning”.

She reviews the results of a recent paper modeling the fitness costs and benefits of multiple ovulation in a cycle, or polyovulation.

Twinning is a relatively rare event, varying from around 0.6 to 4% of all births, and this new paper suggests that its rarity is because it is an ‘accident’ arising from a strategy of polyovulation to counteract very high rates of foetal loss. Many questions still remain about this phenomenon: such as why foetal loss is so high, and why twinning rates vary around the world – because of differences in the likelihood of foetal loss, perhaps? But regardless of the explanation for the existence of twins, mythology, literature and the human experience is much richer because of this fascinating phenomenon."

Humans have a very high late of early pregnancy loss, which is itself an evolutionary problem. The idea of a bet-hedging strategy revolving around polyovulation is one possible explanation.

But there are a couple of things that this explanation is less good for. I’m less convinced than the authors of the study about bet-hedging for older mothers. The fact that twinning increases with maternal age seems more consistent with a progressive decline in the strength of selection against it, rather than an adaptation for twinning for older mothers.

More critically in my view is the fact that monozygotic twinning in humans is approximately the same frequency as dizygotic twinning in many populations, even though they originate from very different mechanisms. Polyovulation should have no effect on the rate of monozygotic twins, so why should they be around the same frequency?

Knowing more precise numbers about the rate of these in different populations and the genetic correlates of them will be helpful.

Twins from an adaptive point of view was originally published by John Hawks at john hawks weblog on May 14, 2020.

Link: Online learning metaconversation

2020-05-14T00:00:00-05:00

I’ve been thinking a lot over the last few weeks about how to help students transition more effectively to online learning. Obviously this is a topic on the minds of many teachers and professors this year.

I was pointed to a post where Martin Weller reacts to some conversations he’s seeing in his Ed Techie blog: “It’s forever 1999 for online learning critics”.

Online and distance learning does generally require more self-motivation from the learner, away from the physical cues that prompt learning. It also requires more organization of their time and study environment and so retention may always be an issue compared to f2f. But it also offers opportunities for other forms of teaching. The least interesting thing you can do is replicate the not very effective model of the lecture. We had these discussions back in 1999, and people explored problem based learning, constructivism, collaborative learning, and then later connectivism and flipped learning. I’m not proposing any one of these approaches as a magic bullet, and some students will like them and others hate them. But different approaches are achievable and have been realised for a long time. Just because you’ve been dumped off your lectern and feel aggrieved, is no need for another ‘online learning sucks’ hot take.

I appreciated the (short) comments section on the post, where a commenter made the point that most students have spent more than a dozen years in classrooms learning how to learn. Obviously a shift to online interactions will seem difficult because it is easy to forget how much time students have spent learning to learn in classroom settings.

I find when we teach laboratory sections that many students have a difficult time adjusting to this form of learning. Many are more comfortable sitting back and listening to a teaching assistant, and are hesitant to step forward and explore materials with their hands.

Online learning does sometimes put students into a more comfortable place for exploration. They do not have to explore while other students are watching them. Some of the social fear of making a mistake is taken away. But the obvious problem for a biological anthropology course is that the physical materials are really important for learning. We have to think about the ways that students can learn to do science that do not depend so strongly on handling bones, casts, and other objects first-hand.

Link: Online learning metaconversation was originally published by John Hawks at john hawks weblog on May 14, 2020.

Replicability and archiving of geological samples

2020-05-13T00:00:00-00:00

In Nature this week, Noah Planavsky and coworkers, including the present director of the National Museum of Natural History, Kirk Johnson, have an opinion piece calling for mandatory archiving of geological samples that underlie published research: “Store and share ancient rocks”.

This call is analogous to the work maintaining sequence databases in genetics, or curation of paleontological samples. Planavsky and his coauthors convey the need for seriousness concerning reliability and replicability of biochemical and other examinations of rock and mineral samples.

Attempts over the past decade to answer questions using better tools and larger databases have only amplified disputes. To make matters worse, too often, rock samples are not archived or shared. It is common for samples to be held by researchers in private collections instead of in accessible, curated institutional archives or museums. That’s a problem, because different geoscience teams cannot check each other’s work to test whether published results are robust and can be replicated.

We are fast entering a world where it may be more costly in time and effort to carry out field collection of samples for replication. That means that field studies need to make more effort to record all the context necessary for interpreting the samples they collect. Many scientists have relied upon their own memory, their descriptive ability, and GPS coordinates to document samples. The field should prioritize more precise and replicable methods for collecting context with samples.

Funding agencies should require that researchers’ grant proposals include sample archival procedures and that budgets include curation fees. Critics might argue that archiving will decrease the money available for other scientific endeavours. In our view, a sample stewardship plan should be viewed as equivalent to budget-line items for data archiving, publishing fees or institutional overhead costs that support other essential components of the research workflow.

Over the past decade, funding for biological collections has declined. That has hit many museums and curating institutions hard. The role of institutions who curate and preserve samples is more and more important. We are going to rely on skilled people who know collections, and who can work with outside experts to do apply new methods to these samples. For the future of research, we need to be building these capacities now.

Replicability and archiving of geological samples was originally published by John Hawks at john hawks weblog on May 13, 2020.

Tending museums through the crisis

2020-05-13T00:00:00-00:00

Atlas Obscura has an article by Jessica Leigh Hester looking at how curators and staff are tending museum collections and infrastructure while hallways are empty: “The Strange, Smelly Chores That Keep Natural History Museums Running”.

The tapir bones rest in a solution of diluted ammonium hydroxide, which pulls out marrow and fat and arrests bacterial growth. They are not far from the remains of okapi and goats that are wrapped in tarps, as well as squirrels, bats, and rodents that sit in containers on shelves. In this case, a little bit of the malodorous, milky-white fluid from the tapir’s bin had trickled out and pooled on the floor. Ferguson cleaned it up and went on his way. It wasn’t a crisis, but it was a good reminder: Museums are dynamic environments, and staff members are always doing their damnedest to fend off entropy.

If you wonder about how dermestid beetle colonies are maintained, or the effects of clothing moths on mounted crustaceans, this article is for you. Entropy is a good word for the problems that are constantly sapping away collections of biological specimens.

Tending museums through the crisis was originally published by John Hawks at john hawks weblog on May 13, 2020.

When will we have concerts again?

2020-05-11T00:00:00-00:00

Foo Fighters frontman Dave Grohl has an essay in The Atlantic reflecting on our need for live music: “The Day the Live Concert Returns”.

In today’s world of fear and unease and social distancing, it's hard to imagine sharing experiences like these ever again. I don’t know when it will be safe to return to singing arm in arm at the top of our lungs, hearts racing, bodies moving, souls bursting with life. But I do know that we will do it again, because we have to. It’s not a choice. We’re human. We need moments that reassure us that we are not alone. That we are understood. That we are imperfect. And, most important, that we need each other. I have shared my music, my words, my life with the people who come to our shows. And they have shared their voices with me. Without that audience—that screaming, sweating audience—my songs would only be sound. But together, we are instruments in a sonic cathedral, one that we build together night after night. And one that we will surely build again.

When will we have concerts again? was originally published by John Hawks at john hawks weblog on May 11, 2020.

Hunting the ghost dogs with camera traps

2020-05-09T00:00:00-00:00

Cara Giaimo in the New York Times covers a recent research paper that combines camera trap evidence from across a large swath of the western Amazon to examine an elusive canine: “The Ghost Dogs of the Amazon Get a Bit Less Mysterious”.

Daniel Rocha, a graduate student at the University of California, Davis, and the study’s lead author, became interested in the short-eared dog in 2015, when he began working in the southern part of the Amazon. He and his colleagues set up camera traps to study the local mammal community. As they looked through the footage, “these dogs would appear,” he said. With pricked ears and furrowed brows, they almost look surprised to be caught on camera.

It surprised him, too. Even locals who spend a lot of time in the Amazon don’t often see short-eared dogs, which were assumed to be quite rare. They also evade career researchers focused on this region: Mr. Rocha, who spent years leading this study, said, “I’ve never seen the dog in the jungle, ever.”

The article briefly describes the broad collaboration that is making it possible to collect data on this species and study its distribution.

Hunting the ghost dogs with camera traps was originally published by John Hawks at john hawks weblog on May 09, 2020.

How much of the Neandertal genome came from contemporaries in Africa?

2020-05-06T00:00:00-00:00

Back in June of last year, Melissa Hubisz, Amy Williams, and Adam Siepel coworkers put out a preprint with a new method for looking at introgression using the ancestral recombination graph: “Mapping gene flow between ancient hominins through demography-aware inference of the ancestral recombination graph”.

The paper has not yet appeared in a journal, but at the time I noted one interesting conclusion:

Applying this method to modern and archaic hominins, we confirm that a significant proportion of the Neanderthal genome consists of regions introgressed from ancient humans. While we identified 3% of the Neanderthal genome as introgressed, a rough extrapolation based on our estimated rates of true and false positives suggests that the true amount is around 6%. Thus, the Neanderthal genome was likely more influenced by introgression from ancient humans, than non-African human genomes are by Neanderthal introgression. Our follow-up analysis suggests that the Hum→Nea gene flow occurred between 200-300kya. This time estimate is largely based on the frequency of introgressed elements among the two diploid Neanderthal genomes, and thus will be sensitive to the accuracy of the demographic model we used for simulation, as well as other factors such as mutation rate and generation time.

With the first sequencing of the first Neandertal genome, and for several years afterward, many geneticists promoted a scenario in which gene flow between Neandertals and modern humans had been a one-way arrangement. The idea was that moderns got some DNA from Neandertals, but the Neandertals never got any from modern humans. This conclusion was based on some data, but it was premature. The early methods applied to the Vindija low-coverage genomes could not detect “modern” genetic input into the Neanderthal population unless that modern input came from the ancestors of some modern populations and not others. The data did rule out that the Vindija Neandertals had genetic input from the immediate ancestors of living Europeans. But the analyses could not test for older introgression from African-derived populations not closely related to one living population or another.

In the last year or two, a number of analyses have started to identify introgression of particular segments of the genome. Geneticists have also added larger samples of DNA from today’s African populations. African peoples are still badly underrepresented in genetic datasets, and the recent additions are a drop in the bucket of what is needed. But it’s impressive how a better representation of African variation and better methods have started to illuminate deeper phases of population mixture in human evolution.

One of those is the deep introgression into Neandertals from their African contemporaries. The African origin of Neandertal mitochondrial DNA, revealed a few years ago, was the first major element of our emerging understanding. Mitochondrial DNA was not alone. Neandertals were repeatedly connected to African populations in the time after 350,000 years ago. They derive a substantial fraction of their genetic variation from such contacts with African populations.

The paper from Lu Chen and coworkers earlier this year provided strong evidence of the importance of gene flow from Africans into Neandertals in the period after 150,000 years ago (“Neandertal ancestors of African populations”). This new paper from Hubisz and coworkers is pointing to gene flow in an earlier period of time, more similar to that time when the Neandertal mtDNA introgressed.

How much of the Neandertal genome came from contemporaries in Africa? was originally published by John Hawks at john hawks weblog on May 06, 2020.

The genetic ancestry of modern lions

2020-04-27T00:00:00-00:00

Marc de Manuel and coworkers have a new paper in PNAS that presents some new findings about lion population history from whole-genome sequencing. The paper has the title, “The evolutionary history of extinct and living lions”.

This is a paper on a fascinating biological topic where the title promises a bit more than it delivers. Their sample includes six modern lions from Africa and India, 12 lions from historical populations that are now extinct in Africa and West Asia, and 2 cave lions, one from Siberia and one from Yukon. A truly “evolutionary history of extinct and living lions” would include a larger sample of living lion diversity and at a minimum European cave lions and American lions (Panthera atrox).

Lions have a great fossil record that this paper mostly neglects. I’m more and more dismayed by the intellectual divisions between paleontologists and geneticists on the evolution of familiar mammal groups. In this case, with a title that calls up the “evolutionary history” of lions, it would be nice to have fossils as more a part of the story.

The lion story is fascinating right now precisely because what is emerging from the genetics does not seem to line up with long-standing ideas based on the fossil record. De Manuel and colleagues show that today’s African and Asian lions are markedly limited in their diversity. All living lions appear to stem from a Late Pleistocene common ancestry:

The deepest divergence within modern lions was between the northern and southern lineages (Fig. 1B), which shared an ancestor ca. 70,000 y ago (52,000 to 98,000 y ago; SI Appendix, Table S3 and Fig. S9). This date is consistent with previous estimates based on mtDNA sequence variation (5, 14), although slightly younger than prior estimates based on autosomal markers (9). Interestingly, through a PSMC analysis of the individuals from the northern and southern groups, we inferred a sudden decline in Ne in the northern genetic lineage at roughly the same time as the split between the 2 groups (ca. 70,000 y ago, Fig. 3A). This severe population bottleneck in the northern genetic lineage suggests that regions north of the Sahara were populated by only a few migrants from the southern lineage at some point in the Late Pleistocene (1, 9, 14).

That means that most fossil lions are likely outside the bounds of modern lion diversity. Lions have existed for a long time in Asia, Europe, and North and South America. Cave lions go back to 750,000 years or more in Europe. Not only these but fossil African lions also lie outside of the envelope of today’s African and Asian lions. That’s saying something. Lions have been a hugely successful evolutionary lineage, and they appear to have a population history that is much more constrained than that of modern humans.

It is notable in this study that lion populations that were considered as phenotypically divergent, such as the Cape lions and Berber lions, show no matching genetic differentiation. They are all part of the same Late Pleistocene diversification.

De Manuel and coworkers estimate that the cave lions diverged from modern lions around 500,000 years ago. Their data do not show any evidence of gene flow into cave lions from modern lions after their divergence. This is a bit of an idiosyncracy in comparison to the broader picture of cat phylogeny, which has extensive ancient hybridization among lineages. My impression is that the big story here, that today’s African and Asian lions all derive mostly from Late Pleistocene population diversification, means that gene flow that might once have happened between Asian (or American) lions and these cave lions from Siberia and Yukon is not going to register in today’s data. European lions might be more interesting, but the very recent common ancestry of today’s lion populations predicts that any gene flow between their stem population and cave lions is not going to show up on D-statistic type tests.

A half million years of genetic diversification for cave lions and modern lions is not enough to account for the fossil record of cave lions. Some cave lions have been around since the Early Pleistocene. I would guess that there were multiple dispersals of lions that may have been accompanied by introgression.

Many of the authors of this new paper were also authors of a paper describing the mitochondrial genome of the same Yukon cave lion specimen back in 2016. That paper was “Mitogenomics of the Extinct Cave Lion, Panthera spelaea (Goldfuss, 1810), Resolve its Position within the Panthera Cats” by Barnett and coworkers. In that paper, they provided a divergence date for cave lions and modern lions at 1.89 million years ago. Now, the comparisons of the nuclear genome suggest a much more recent date.

At this point in history, we all know that initial mtDNA comparisons between species may look quite different from later, more complete comparisons using the nuclear genome. Sometimes the divergence of mtDNA appears disproportionately great, Denisovans being an obvious example. This case with the cave lion is a big difference, and it reminds me of the differences we saw early on between chimpanzee mtDNA divergence and the first nuclear genome comparisons.

The difference matters to interpreting the cave lion fossil record, which extends much older than a half million years. De Manuel and coworkers do examine the discrepancy between mtDNA and nuclear comparisons to some degree. They mention in their supplement that previous attempts to date the divergence of cave lions and modern lions used the first appearance date of cave lions in Europe as a calibration point, while this study does not. The use of a fossil calibration assumes that the earliest fossil cave lions are genetic ancestors of later cave lions. That may be a bad assumption. The hominin record is now full of examples where the later inhabitants of a region come from later migrations with little input from earlier populations in the same region. If lions did they same, they would be a parallel to the population history of hominins.

On the whole,though, I’d like to see a fuller consideration of these different sets of data. The present sample of lion genome diversity is not yet enough to evaluate whether today’s lions may retain small contributions from divergent populations that may once have existed. I’m interested in whether the modern lions have to some extent absorbed ancient lion populations across Africa and possibly Asia, in the way that modern humans have absorbed many archaic hominin populations.

The genetic ancestry of modern lions was originally published by John Hawks at john hawks weblog on May 04, 2020.

Link: Bioarchaeology and the resilience of past societies

2020-04-28T00:00:00-00:00

Gwen Robbins Schug has a piece in Anthropology News looking at the lack of any simplistic relationship between climate change, crisis, and cultural change in the past: “The Long View of Climate Change and Human Health”.

The subhead summarizes the theme of the essay pretty well:

The deterministic view that climate change invariably causes migration, competition, violence, and collapse is overly simplistic. Bioarchaeology shows us that human responses are far more complex and diverse.

I like the way that the essay closes, reflecting upon the failure of the big history view of the fate of societies. Instead, it’s a “little history” that we should be thinking about – the way that individuals matter, and the way that chance turns of events at the microscale make a difference.

These tiny decisions may appear mere turbulence to the historical picture. Yet if we take the long view seriously, every society is on the edge of survivability in geological time. At the threshold of the lifting edge, turbulence matters.

Broadly speaking, bioarchaeology demonstrates that there are no grand narratives in human history. Small-scale societies are often resilient in the face of environmental change; mobility, flexibility, and adaptive diversity are a largely successful strategy for avoiding negative consequences (see for example, Berger and Wang 2017; Temple and Stojanowski 2019). Complex societies, in contrast, are often much more rigid and they are built on social inequality. When these large-scale societies overshoot—undergo rapid population growth and practice unsustainable agricultural overproduction in the context of rapid climate and environmental changes—those who are resilient and who survive the short-term crisis may experience other forms of suffering (see for example, Robbins Schug, Parnell, and Harrod 2019; Tung et al. 2016).

People survive and sometimes thrive in the face of huge challenges. Other times, people fail despite their best efforts. Failure may result from a cultural system that sets people up for failure. But often it’s bad luck.

Link: Bioarchaeology and the resilience of past societies was originally published by John Hawks at john hawks weblog on April 28, 2020.

Neandertal ancestors of African populations

2020-04-25T00:00:00-00:00

Earlier this year, Lu Chen and coworkers from Joshua Akey’s research group published an assessment of the amount of Neandertal ancestry in the genomes of present-day African people: “Identifying and Interpreting Apparent Neandertal Ancestry in African Individuals”.

In the wake of the initial Neandertal genome sequencing in 2010, journalists and many scientists spread the misconception that African people have no Neandertal genetic ancestry. That was wrong at the time and many people pointed out how wrong it was.

The research itself, from Svante Pääbo’s team, did not propagate this misconception. All of the authors were pretty consistent in noting that their tests could only measure the difference between sub-Saharan and other populations in Neandertal ancestry, and could not rule out Neandertal contributions to sub-Saharan African peoples.

Still, in the first year or two of genome-powered scientific conversation about Neandertal introgression, other scientists focused upon an alternative explanation: incomplete lineage sorting from a structured African population. As this idea was debated, again and again geneticists defended the introgression hypothesis by arguing that introgressed DNA was not found in Africa. As this genuine debate about incomplete lineage sorting was reported by journalists, they also reinforced the misconception that Neandertal introgression only exists in peoples outside Africa.

Through this period, I was one of the people working to debunk the myth that African populations have no Neandertal ancestry. A look at my 2010 post, “NEANDERTALS LIVE!”, shows me giving the correct answer for this question, “Do living Africans have Neandertal ancestry, too?”

The fact that living Africans are less genetically similar to the Neandertals is extremely important evidence of the Neandertals’ genetic contribution to populations outside Africa. But it doesn’t bear on how much back-migration into Africa may have happened.

We know that the answer is nonzero, because Africa has received immigrants from other parts of the world during historic times. The same genetic patterns that reflect population contacts up and down the East African coast, and across the Sahara into West Africa, show the possible conduits for the flow of Neandertal-derived genes into African populations.

I had actually grappled with this problem in my earlier paper (with Greg Cochran) in 2006, looking at what we should expect Neandertal introgression to look like: “Dynamics of Adaptive Introgression from Archaic to Modern Humans” (PDF). A number of scientists over the years suggested that any gene flow from Neandertals should be absent from Africans. That simply wasn’t true, and we pointed out why introgressed genes from Neandertals or other archaic humans might be found broadly across Africa.

Research over the last ten years has looked into the amount of Eurasian gene flow into Africa over the last 30,000 years, adding a good bit to our understanding of human population structure. That Eurasian gene flow was part of the big story of 2017, as early Holocene ancient DNA data from South Africa reinforced the finding that today’s southern African peoples have a good fraction of ancestry from Eurasian sources over the last 5000 years.

Now Chen and coworkers have given us a new set of estimates for how much Neandertal ancestry occurs in African populations. Their results are sketched out in the following figure:

Figure 2a from Chen et al. 2020. This shows "violin plots" depicting the amount of Neandertal sequence identified in various populations per individual. East Asian (EAS), South Asian (SAS), European (EUR) and Native American (AMR) groups average between 50 and 60 megabases per individual, which is just under 2 percent. African populations have between 15 and 20 megabases.

These comparisons are limited to 1000 Genomes Project samples, and those are mostly in the northern parts of sub-Saharan Africa, from Gambia, Sierra Leone, Nigeria, and Kenya. Chen and colleagues identify between 15 and 20 megabases of Neandertal DNA per genome in these samples. That’s around a third the amount that the authors find in Eurasian and Native American population samples.

Europeans and Asians have around 2% Neandertal ancestry, and sub-Saharan Africans have around 0.6%.

The Neandertal DNA in African populations comes from two sources. Most of it comes from so-called “back-migration” of Eurasian modern humans into Africa. That gene flow can mostly be traced to the last 50,000 years. It’s not yet clear how much that gene flow into Africa may have accelerated over time. The population growth of the Holocene, with cattle pastoralism spreading southward across Africa, has helped fuel the spread of Eurasian genes in historic times. Yet a green Sahara during later parts of the Pleistocene also enabled contacts and dispersals that became more difficult in the recent, more arid North African landscape.

The other source of Neanderthal DNA in Africa is a kind of incomplete lineage sorting. This ILS, however, marks Neanderthal-African shared haplotypes that are absent in the rest of the world. Chen and coworkers look at the mutational differences among these and find that they have a peculiar age distribution. They do not date to the founding of the Neanderthal lineage more than 600,000 years ago. Instead, they are haplotypes that were transferred from African populations into Neanderthals by gene flow prior to 100,000 years ago.

Our own data are most consistent with models of human-to-Neanderthal gene flow between 100 and 150 ka, as IBDmix does not detect any signal in simulations with earlier gene flow. However, our results do not preclude earlier instances of gene flow, only that IBDmix is not powered to detect them. Thus, it is tempting to speculate that perhaps there were multiple waves of pre-OOA dispersals and admixture between modern humans and Neanderthals, although additional data are needed to make more definitive inferences.

Multiple waves of gene flow from Africa into Neandertals seem likely, and are corroborated by fossil discoveries like those from Misliya and Apidima.

This paper has many additional interesting things to say about Neandertal introgression. The one that I want to mark before ending is that Chen and colleagues look back at the “extra” amount of Neandertal similarity in Asian genomes compared to European genomes. This “extra Neandertal” has been estimated as much as 20% in previous work, but that assumed that Africans had no Neandertal ancestry. The Neandertal ancestry that does occur in Africa today comes in large part from gene flow out of western Eurasia, which means it is shared more with Europeans, Arabs, and other western Eurasian people than with East Asian populations. Looking at this effect, Chen and coworkers estimate that East Asian populations still have a bit more Neandertal than western Eurasian people, but only about half the previous bonus, around 8%.

It’s a cool paper that answers a number of worthwhile questions. It will be great to see larger samples applied to this and other similar problems. As I reflected in the Iceland Denisovan genetics post, we will learn much more when large samples can better characterize the haplotypes that have come from Neandertals and other populations.

I suspect when we have equivalently large samples in Africa, it will reveal a small amount of direct Neandertal introgression during the period of modern human emergence.

Neandertal ancestors of African populations was originally published by John Hawks at john hawks weblog on April 27, 2020.

Quote: Robert Broom has no apologies

2020-04-27T00:00:00-00:00

Robert Broom, in the first paragraph of his paper, “Further Evidence on the Structure of the South African Pleistocene Anthropoids”, says it better than I could.

NO apology need be given for publishing to the world at the earliest possible moment all new evidence that is discovered which seems to throw additional light on the structure of the apes that apparently are related to the ancestors of man. Every month reveals some new facts of importance, and it seems to me better that these should be announced at once, than that they should be held back for perhaps years in the hope of publishing a detailed account.

Next time you hear someone say that “real paleontologists take time to do quality science”, you can pull this one out of your pocket.

Quote: Robert Broom has no apologies was originally published by John Hawks at john hawks weblog on April 27, 2020.

Denisovan ancestors of the Iceland population

2020-04-25T00:00:00-00:00

Last week in Nature, Laurits Skov and collaborators from Aarhus University and from Kari Stefansson’s research group in Iceland gave a high-resolution look at Neanderthal and Denisovan introgression in the Iceland population. The title of their paper is: “The nature of Neanderthal introgression revealed by 27,566 Icelandic genomes”.

I see this paper as a first step in a new phase of research. Up to now, samples of human genomes used in phylogenomic analysis have been limited in number. The 1000 Genomes Project samples include a hundred or so individuals from just a few populations. Most other studies have had much smaller sample sizes. Ancient genomes by their nature are limited in number.

Small samples do enable geneticists to answer some questions with high confidence. These are the questions where ancient people were very different from each other, and from people living today. “Did they mix at all?”, or “Assuming total isolation between them, when did their populations start to diverge?” But when you start to specify just how strict the assumptions must be to do the math, you start to see how unsatisfying the answers to such simplistic questions really are.

Truly large samples allow us to answer questions that involve small levels of difference between ancient and modern people. Ancient humans were like us in most ways. Nearly all their phenotypes overlapped with those of living populations. They were emphatically not subject to “total isolation”, they mixed repeatedly. How often did they mix? How important was that mixture to their evolution? Those questions take big samples to start to answer.

I’m going to spend some time evaluating this research and pulling out some of the new directions in separate posts. Skov and coworkers are able to identify the fine-scale similarities between haplotypes in the genomes of living people and in three high-coverage ancient genomes. In this case that includes the so-called Vindija and Altai Neanderthal genomes and the Denisova genome.

In this post, I want to focus on the Denisovan component of ancestry.

The advantages of a large-sample approach are abundantly evident when considering the very small amount of genomic DNA that Iceland people have from Denisovans. Skov and coworkers quantified the very small amount (0.1%) of DNA shared within the Iceland population from Denisovan ancestry and they discuss several scenarios for how it may have gotten there.

Finding Denisovan ancestry in western Eurasian samples is not a first-ever result, and similar small fractions of this ancestry have been found in other recent studies. Earlier this year, Anders Bergström and coworkers reviewed the variation found from whole-genome sequencing of many Human Genome Diversity Project samples, and quantified Denisovan-like haplotypes in many populations, including New Guinea populations. Their figure from the supplementary information shows the amount of each population’s genome that they infer to be Denisovan:

Figure S17B from Bergström et al. 2020, showing the amount of genomic sequence inferred to represent Denisovan ancestry in lots of populations.

Bergström and coworkers estimated that 2.8% of the ancestry of the highland New Guinea sample in their study came from Denisovans. As visible in the figure, the amount of genome identified with high confidence as Denisovan is less than the overall estimate, and amounts to around 25 million base pairs per genome in the highland New Guinea sample.

[As an aside, it is not obvious how this result reported in the Bergström et al. supplement connects to the estimated fraction of ancestry. Twenty-five million base pairs is less than one percent of a genome (and less than half a percent of a diploid genome). For my discussion here, I’m just looking at the fraction of this amount as estimated for other populations.]

If we look at western Eurasian populations here, like French or Orcadian, around 0.1 on the x-axis scale, or 1 million base pairs, are estimated to be Denisovan. Assuming the same 3:1 ratio that seems to apply to the New Guinea sample in that paper, this would suggest around 0.1 percent of the genomes of these samples are Denisovan in origin.

[As another aside, did anybody else notice that the Bergström et al. supplementary figure has more Denisovan ancestry inferred in the San sample than in French? Something with incomplete lineage sorting is surely going on that hasn’t been well quantified here. One problem is that Bergström et al. seem to have assumed near-zero introgression in African populations, and Joshua Akey’s group showed that this assumption is incorrect. ]

Bergström and coworkers (2020) is the most recent analysis of Denisovan introgression into Eurasian populations, but some earlier work from Joshua Akey’s group provide somewhat more resolution of these issues. In 2018, Sharon Browning and coworkers examined Denisovan ancestry in Eurasian populations and inferred two Denisovan source populations for introgressed haplotypes in most Asian populations. I’ll return to this paper below. Earlier this year, Lu Chen and coworkers looked at Neanderthal ancestry in sub-Saharan African samples. In the course of this analysis, they also quantified Denisovan-like genome segments in 1000 Genomes Project samples. They found a similar amount of Denisovan-like haplotypes in African and Eurasian population samples, around 1 megabase on average. Chen and coworkers interpreted this result as a baseline for incomplete lineage sorting for their purposes, which was to identify Neanderthal ancestry in sub-Saharan Africa. But it is interesting in the context of identifying true Denisovan introgression in all these populations.

So the Iceland result found by Skov and coworkers, using a vastly bigger sample of living people, seems to be pretty close to what other populations in western Eurasia have. If anybody was wondering if Denisovan ancestry in Iceland is a sign of a transoceanic migration from Melanesia to Iceland, that hypothesis isn’t necessary.

OK, let’s look more closely at what Skov and collaborators find from their enormous Iceland sample. This is a figure showing the distribution of introgressed haplotypes across all the chromosomes:

Figure 1d shows the genomic distribution of archaic fragments and the DAV [Denisovan, Altai, or Vindija] genome that they share the most variants with: Vindija Neanderthal (50.8%), Altai Neanderthal (13.1%), Denisovan (3.3%), two or more DAV genomes (20.4%) or not shared with a DAV genome (unknown, 12.2%).

This figure is one of those nutty diagrams that shows a logogram of every chromosome split into 4 panels that each are marked up with colored blocks representing the location of introgressed haplotypes. Together these add up to around 40 percent of the genome with some evidence of introgression within the modern sampled individuals.

According to the results, the Iceland population has something like 0.1 percent Denisovan-like ancestry across their genome. Skov and coworkers went to some effort to try to understand where this Denisovan component came from.

Denisovan ancestry may come from direct mixture of early modern people with a Denisovan group; or alternatively, Denisovan ancestry in Icelanders may have come indirectly from Denisovan mixture with Neanderthals that happened before early modern humans mixed with Neanderthals. Skov and coworkers provide a figure that shows the difference between the direct and indirect models:

Notice that in the direct model, non-African peoples get around 0.12-0.16% of their ancestry directly from a divergent Denisovan group. In the indirect model, the “introgressing Neanderthal” group gets 6-8% of its ancestry from Denisovans, and then gives 2% to the ancestors of today’s non-African peoples.

Because the Denisovan component of ancestry is so small, it is difficult to test the difference between these scenarios. The two scenarios (direct versus indirect) do predict slightly different things about the Denisova-like haplotypes. If these all came indirectly into modern humans from a Neanderthal population after Denisovan-Neanderthal introgression, then recombination should have connected many of them directly to haplotypes that otherwise resemble Neanderthals, creating a recognizable pattern. This puts a constraint on how early the Denisovan-Neanderthal mixture could have been. But if such Denisovan-Neanderthal introgression happened within the period just before modern-Neanderthal introgression, it would be very hard to tell the scenarios apart. And the sizes of these populations matter – the survival of distinct Denisovan lineages after introgression within a Neanderthal population is more likely in a larger population than a smaller one. All this means that there are a lot of ways that a different sequence of events might lead to a similar outcome.

One thing that the study concludes for certain is that this Denisovan component of Iceland genomes does not come from incomplete lineage sorting alone. These are not ancient African genetic haplotypes that merely resemble Denisovans. They really did come from Denisovans at some stage of prehistory.

A second thing that is clear is that the Denisovan-like haplotypes in Icelanders do not come directly from the Denisovan population sampled at Denisova cave in the Denisova 3 high-coverage genome. Skov and coworkers were able to examine the extent of allele sharing between the Denisova-like haplotypes in Icelanders and the Denisova 3 genome itself:

We find that the amount of derived variant sharing is compatible with a scenario where the introgressing Denisova splits from the sequenced Denisova around 300-350 kya.

That’s a fascinating conclusion. The extent of diversification within Denisovans that this would represent is as great as the greatest divergences among surviving modern human populations that survive today. Their simulations suggest greater uncertainty than reflected in the sentence I’ve quoted here. This range of uncertainty appears to extend from 270,000 years up to 400,000 years ago.

Again, this is an observation that confirms something already known from other work. The paper from Guy Jacobs and coworkers last year on Indonesian population diversity provided good evidence of deep Denisovan diversity. Many people in New Guinea today have a heritage including introgression from two different groups of Denisovans. Both of these Denisovan-like groups continued to exist until the last 40,000 years, it seems from the lengths of the introgressed haplotypes. Jacobs and coworkers denoted these Denisovan-like groups as D2 and D1. They estimated that the D2 group diverged from the population ancestral to both Denisova 3 and D1 around 360,000 years ago, and D1 diverged from the Denisova 3 population around 280,000 years ago. These findings pointed to very deep population diversity within “Denisovans”, more in fact that is present among the most diverse modern human groups.

These estimates of divergence dates are based on simplistic models of divergence with no subsequent gene flow. They are likely to be wrong. If these “Denisovan” populations behaved like modern human and Neanderthal groups, they probably shared some amount of gene flow at times after their divergence. That would make the “divergence date” estimates appear more recent than the real initial diversification of these populations.

It is not clear whether other Asian or island Southeast Asian populations may also have mixture from the “D2” population. The 2018 work from Browning and coworkers established that today’s Asian populations have Denisovan ancestry from at least two “waves” of introgression. One of those, accounting for around a third of the Denisovan-like ancestry in East Asian people today, looks to have been genetically similar to the Denisova 3 genome. The other wave was genetically quite divergent from this Denisova-3-like population. In the analysis by Browning and coworkers, they were able to find evidence for both waves in samples of living people originating from China, Japan, and Vietnam, including several ethnic groups in China. They even found a trace of the Denisova-3-like wave in Finland. But they found only the divergent wave in South Asian populations, and they did not identify either Denisovan wave in European populations other than Finland, or in samples with Native American ancestry. Browning and collaborators did not estimate a divergence date for this population, and Jacobs and coworkers did not establish whether this mainland Asian divergent wave was the same as either the D1 or D2 introgression source that they identified. So the identity of this divergent Denisova-like introgression wave at the moment is up in the air.

It is reasonable to ask whether the divergent Denisova-like wave that Browning and colleagues found in Asians might be the same as the Denisova-like ancestry that Skov and colleagues identify in Icelanders. It’s also reasonable to ask whether both of these represent the same source as the D2 population identified by Jacobs and coworkers.

I’m not convinced that they are the same, for reasons I’ll go into below. But it’s not a bad idea to start with the hypothesis that they might be the same, and think about how to test that. So I’ll propose that these signals all equate to the same divergent population, and that they originate from a Denisova-like population in South Asia.

In this hypothesis, most of the D2 component of ancestry in Sahulian populations actually reflects introgression from this divergent Denisovan group. The ancestors of today’s Sahulians would have encounted the D2 population as they transited South Asia. Later, they picked up ancestry from the different D1 population, which might come from a Wallacean or island Southeast Asian source.

Meanwhile, southwest Asian Neanderthals also had a small component of D2 ancestry. They got this from introgression or gene flow with the South Asian D2 population. That gene flow was not small, it had to be something like 6 to 8 percent of the genome of the southwest Asian Neanderthal population. The out-of-Africa wave of modern humans then picked up a small fraction of this D2 ancestry when they mixed with the southwest Asian Neanderthals. That component provides the measurable Denisovan ancestry in most of today’s people, including Icelanders. It also is present in New Guinea, but accounts for a much smaller amount of the D2 signature in this population.

This hypothesis leaves the timing of these events somewhat flexible. Today’s Sahulian groups are more divergent from other non-African populations than any of those populations are from each other, and they may have picked up their extra D2 ancestry anywhere along the road to Sahul. Jacobs and coworkers (2019) inferred the time of D2 mixture into New Guinea populations at 46,000 years ago, with an error interval going up to the time they estimate that these populations first differentiated from the stem out-of-Africa groups, around 51,000 years ago. These dates are contingent on a variety of assumptions in the article, and we cannot take them as “real” dates that we can test hypotheses with. They just give an indication of where this introgression is relative to the divergence of the New Guinea ancestral population from other populations today. Likewise, the models examined by Skov and coworkers looked at introgression among Neanderthal, Denisovan, and modern populations at or around 45,000 years ago. Their analyses provided some demonstration of how Denisovan introgression may have originated, but they could not differentiate the direct and indirect hypotheses from each other, much less provide real confidence intervals for the date of Denisovan introgression.

How could we test this hypothesis? What is needed is some further large samples of other populations to test whether the small component of Denisovan ancestry can really come from a single source. 27,000 people might be overkill for testing that, but more than a few thousand will be needed.

The observation by Browning and coworkers that South Asian peoples today have more detectable ancestry from the “divergent wave” of Denisovans than European or other groups is very interesting. Bergström and coworkers this year also found more evidence of Denisovan-like ancestry within their South Asian samples than in European samples. Meanwhile, those same samples showed more Neanderthal ancestry in European groups than in South Asian groups. This set of observations was not designed to examine the question of Denisovan ancestry via introgression from Neanderthals, so I don’t want to take the results too far out of context. But on the surface this doesn’t look like a simple Denisovan-via-Neanderthal-introgression hypothesis can work for all the “divergent wave” component. The ancestors of South Asian people seem likely to have mixed directly with divergent Denisovans in addition to any divergent Denisovan ancestry they may trace to Neanderthal introgression.

OK, this is all quite complicated, because none of these studies were really designed to answer this question, and most of them are underpowered to examine the difference between direct and indirect mixture scenarios. But someone will have to get into these details with larger sample soon, because the alternative is that there were possibly many mixtures with many different divergent Denisovan groups.

For me, disproving the hypothesis that a single D2 population can account for all this Denisovan ancestry would be a welcome conclusion. After all, what reason do we have to assume that nature was parsimonious with its Denisovans? Much of what we know makes me expect to find more diversity among past peoples, not less. The divergence of the Denisovans from Neanderthals was definitely before 430,000 years ago, constrained by the fact that the Sima de los Huesos genomic samples are already on the Neanderthal population branch. According to estimates by Alan Rogers and coworkers, the Denisovan origin was likely soon after the stem Neanderthal-Denisovan common ancestors parted ways from sub-Saharan Africans, possibly close to 700,000 years ago (see my 2017 post, “How long ago did Neandertals and Denisovans part ways?”).

Four populations that only began diverging after 400,000 years ago would seem to be a paltry sampling of the Denisovan diaspora. If there weren’t other Denisovans, we’ll need to explain why.

Denisovan ancestors of the Iceland population was originally published by John Hawks at john hawks weblog on April 25, 2020.

Babies get their intestinal viruses in stages

2020-04-23T00:00:00-00:00

A fascinating new paper by Guanxiang Liang and coworkers in Nature looks at how infants end up with a community of viruses in their guts: “The stepwise assembly of the neonatal virome is modulated by breastfeeding”.

Results indicate that, early after birth, pioneer bacteria colonize the infant gut and by one month prophages induced from these bacteria provide the predominant population of virus-like particles. By four months of life, identifiable viruses that replicate in human cells become more prominent. Multiple human viruses were more abundant in stool samples from babies who were exclusively fed on formula milk compared with those fed partially or fully on breast milk, paralleling reports that breast milk can be protective against viral infections. Bacteriophage populations also differed depending on whether or not the infant was breastfed. We show that the colonization of the infant gut is stepwise, first mainly by temperate bacteriophages induced from pioneer bacteria, and later by viruses that replicate in human cells; this second phase is modulated by breastfeeding.

Initially most of the viruses are bacteriophages, but as the abstract indicates, as time passes more and more of the viral community is made up of viruses that inhabit the human gut cells.

The discussion focuses upon the finding that breastfeeding reduces the level of pathogenic viruses in the infants. That finding replicates other work based on different approaches. One of the infant cohorts included in this study was from Botswana, and the findings there are more pronounced than in their U.S. (Philadelphia)-based cohorts.

In the African cohort, we not only found viruses that grow in human cells more commonly in exclusively formula-fed babies, but we also found more colonization in both feeding groups compared to US babies, emphasizing potential opportunities to intervene to reduce viral transmission to infants.

The variation of microbiomes in different human populations is a really important component of human biological variability. Studies like this one are helping to show how that variation comes about through the development process and environmental exposures.

Babies get their intestinal viruses in stages was originally published by John Hawks at john hawks weblog on April 23, 2020.

Stone Age minds in internet time

2020-04-22T00:00:00-00:00

The journalist Kenneth Miller has an article in the current Discover magazine on “How Our Ancient Brains Are Coping in the Age of Digital Distraction”. I make a brief appearance to help explain the genetic complexity of brain evolution on the human lineage.

It’s a good article and I’m going to assign it for my undergraduate class next week. My last week theme always covers what biological anthropology can tell us about the future of humanity. Usually people go overboard on the idea of “Stone Age minds”, but a look at optimality theory is rarely unrewarded.

Humans, of course, forage for data more voraciously than any other animal. And, like most foragers, we follow instinctive strategies for optimizing our search. Behavioral ecologists who study animals seeking nourishment have developed various models to predict their likely course of action. One of these, the marginal value theorem (MVT), applies to foragers in areas where food is found in patches, with resource-poor areas in between. The MVT can predict, for example, when a squirrel will quit gathering acorns in one tree and move on to the next, based on a formula assessing the costs and benefits of staying put — the number of nuts acquired per minute versus the time required for travel, and so on. Gazzaley sees the digital landscape as a similar environment, in which the patches are sources of information — a website, a smartphone, an email program. He believes an MVT-like formula may govern our online foraging: Each data patch provides diminishing returns over time as we use up information available there, or as we start to worry that better data might be available elsewhere.

Yeah, my problem is that whatever I am writing tends to look like diminishing marginal value too quickly!

Stone Age minds in internet time was originally published by John Hawks at john hawks weblog on April 22, 2020.

Killing it: From handaxes to hafted spears, no difference in hunting or meat-eating

2020-04-22T00:00:00-00:00

The change in technology from Acheulean to Middle Stone Age in Africa was a major event in human prehistory. Or was it?

If there is one generalization that we can make from the African record, with all its imperfections, it is that large cutting tools were more common in assemblages from the earlier Middle Pleistocene than later. A second generalization is that Levallois-flaked points and evidence of hafting are more common in the later Middle Pleistocene than earlier. These may seem like a trade-off, and they may have been – although I’m not aware of anyone testing with numbers whether the two are causally connected instead of merely coincidental trends.

I think most anthropologists have assumed that technological change from Acheulean handaxes to Middle Stone Age hafted spears would make some difference in how ancient hominins hunted, scavenged, and ate animals.

The biggest-ever review of this question was published last year, with data drawn from sites across Africa from 800,000 to 130,000 years ago. The paper from Geoff Smith and coworkers, published in the Journal of Human Evolution, provides a useful and detailed review of faunal exploitation across African sites from the later Acheulean and earlier Middle Stone Age: “Subsistence strategies throughout the African Middle Pleistocene: Faunal evidence for behavioral change and continuity across the Earlier to Middle Stone Age transition”.

The review is a meta-analysis of published faunal data from site reports and articles. Looking at sites from Morocco across to Ethiopia and down through Kenya and Tanzania to South Africa, Smith and coworkers compiled faunal lists and other information from a varied array of more than 40 sites, some of which had faunal evidence from multiple time periods. They conclude that what seems like a big change in technology made no difference at all to which prey animals hominins hunted.

The currently available faunal data do not support a broadening of the hominin dietary niche during the Middle Pleistocene. While smaller-sized bovids, such as gazelles, grysbok, southern reedbuck, and springbok, are preserved throughout the Middle Pleistocene sample, these species never illustrate significant increases. Similarly, dangerous game (e.g., Cape buffalo and long-horned buffalo; see SOM Table S2) are recorded in small numbers throughout the faunal dataset. Increased proportions of dangerous game within MSA assemblages have been argued to reflect improvements in projectile technology, which provides the ability to hunt game at greater distances (Klein et al., 2007). While the proportion of these species increases from the early (0.03%) to late Middle Pleistocene (4%), they never predominate. Results from this metastudy suggest that such a change neither occurred on a broad scale during the Middle Pleistocene nor in parallel with the appearance of MSA technologies.

The data are pretty clear about two things. First, there is an enormous difference between open air and cave sites in faunal evidence.

Figure 6 from Smith et al. 2019. The left panel shows Acheulean-era sites, with prey species in different size classes (size class 1 is smallest, 6 is elephants). It's striking the difference between cave sites and open air sites, especially in the lack of large mammal remains.

Hominins did not move the bones of elephants and hippos to caves, and they rarely moved large bovid remains. This is a known bias in zooarchaeology, but when you see a figure like this, it really reinforces just how much the hominin behavioral record is biased by the places that archaeologists prefer to dig. Some of the bias is that there are many cave sites in the MSA time period. Another bias is that archaeologists have been more likely to investigate open air sites that have obvious preservation of large mammal remains. A large fraction of hominin foraging behavior may be entirely missing from the record.

The other obvious feature of the results is that there really is no difference between Acheulean and MSA faunal size distributions other than the greater number of MSA sites that are caves.

A third important generalization from the data is that later Middle Pleistocene sites have more evidence for hominin processing of carcasses than earlier sites. The earlier sites have greater evidence for carnivore involvement, while later sites have more cutmarks and evidence for transport of selected body parts. However, that greater intensity of hominin involvement may reflect the bias toward cave sites in the later Middle Pleistocene.

There is too little data on mortality profiles across these sites for Smith and coworkers to do a comparison of selectivity of prime age adults in prey species. Still, there are many Oldowan-era sites that have a clear bias toward selection of prime age adults by hominins, at least for some prey size classes. It is not probably going to be very informative to look at more detailed aspects of prey selection without first knowing that the hominin contribution is much higher than carnivore contribution to faunal assemblages.

The meta-analysis approach obviously has limits. The quality of data is constrained by the data that has been reported. This varies greatly in depth and detail because some sites were excavated more than 50 years ago.

Also, the chronological information about sites is of varied quality. A good example is Kabwe, included here as a Sangoan/early MSA site. The recent paper by Rainer Grün and coworkers that provides some dates for the hominin material makes it clear that the contextual relationship of artifacts, faunal remains, and hominin fossils in the Broken Hill mine is basically unknown. It may be that the faunal material is of later Middle Pleistocene age, but it’s not obvious what (if any) hominin involvement may have been involved in accumulating animal bones. Kabwe is one of the rare sites that have both hominin fossil material, archaeological material, and fossil material. The unfortunate reality is that being from the same site does not provide evidence of association.

Other sites have similar difficulties. It may not seem objectionable acknowledge the uncertainty about geological age and simply lump sites as early or late. Still, the earlier open-air sites may be quite short duration accumulations that have very large uncertainty of geological age, while later cave sites may sample thousands of years with a more precise knowledge of age. Much rides on whether they are classified as “Acheulean” or “MSA”, yet that classification also depends in some cases on a small artifact assemblage. This kind of classification may serve the purpose of testing whether these coarse groupings have any correlation to faunal exploitation. But we cannot assume that such groupings are meaningful.

An enormous hole in this kind of project is the lack of knowledge of which (if any) hominins are responsible for the faunal remains. To their credit, Smith and coworkers are agnostic about which species of hominins are represented by the behavioral patterns across these many sites:

Currently, associated hominin fossils are limited and do not allow for direct correlations between various African Middle Pleistocene hominin species (e.g., Homo heidelbergensis, Homo rhodesiensis, Homo naledi and Homo sapiens) and a specific lithic technology or subsistence strategy. In general, this period is recognized by a mosaic of lithic entities and hominin species and the broad scale trends discussed here are complementary with more local and regional scale variation in terms of exact timings and causal mechanisms of behavioral change and continuity.

That’s an appropriately cautious statement. We do not know which hominin species made the artifact assemblages sampled at these sites. There were likely other species or divergent populations in addition to the ones listed. All of them were tool users and ate hunted animals.

With that caution in place, it remains interesting that there is no pattern over time across faunal assemblages in prey size selection. I think that’s striking evidence that earlier Middle Pleistocene hominins had achieved the ability to efficiently hunt prey species in the proportions that made ecological sense for them. The fact that later hominins selected the same prey sizes suggests that this aspect of hominin hunting was near equilibrium regardless of the precise toolkits they used.

If you ask me who was doing the hunting, I’d say it was every hominin that existed in Africa across this time period. I think it is likely that they all had similar niches with respect to carnivory.

Killing it: From handaxes to hafted spears, no difference in hunting or meat-eating was originally published by John Hawks at john hawks weblog on April 22, 2020.

What ancient DNA is telling us about the prehistory and history of the horse

2020-04-21T00:00:00-00:00

Ludovic Orlando has a great review of recent research into the origins and evolution of domesticated horses: “Ancient Genomes Reveal Unexpected Horse Domestication and Management Dynamics”. The review is open access in BioEssays.

Here’s a cool fact:

With nearly 300 ancient genomes sequenced at above onefold coverage, horses have provided the largest genomic time series characterized to date after humans.

I’m a bit surprised that dogs aren’t higher than horses, but horse bones are quite a bit more common in some archaeological settings.

Botai horses indeed did not show close genetic affinities to modern domestic breeds. They clustered instead together with the Przewalski's horse, a horse discovered in the late 1870s roaming wild in Mongolia, and considered since as the only truly wild horse living on the planet. In short, the earliest domestic horses known in the archaeological record appeared to be the direct ancestors of the only modern horse that was supposed to have never been domesticated. It then became obvious that current models of horse evolution required serious rethinking.

Instead, the ancestors of today’s domesticated horses appear in the archaeological record around 4100 years ago in Hungary. The date and subsequent widespread occurrence of this single lineage of horses is striking as a parallel to the spread of steppe ancestry in humans inhabiting the same regions. It would seem that the spread of Bronze Age steppe peoples brought a lineage of horses everywhere the people went.

The expansion of this population of domesticated horses is matched by the equally striking extinction of many diverse lineages of horses throughout Eurasia. The review suggests that additional lineages remain to be found, with hints of their existence given by the rare occurrence of very divergent mitochondrial DNA haplotypes in a few ancient specimens.

The review goes on to discuss several other issues related to horse genetics. One important topic is the introduction of progressively stronger inbreeding in the last 2000 years. Some societies selected for particular male patrilines, while others were more ecumenical.

Ancient DNA can cast an invaluable light into ancient phenotypes that are invisible from skeletal evidence. The most widely reported of these phenotypes so far relate to pigmentation. That’s not only because pigmentation phenotypes are highly visible, it’s also because they are genetically simple enough to enable reliable phenotype prediction from sparse SNP data.

With horses, there is a lot to go on for pigmentation analysis. Many well-known color variations exist today, and they differ within and between horse breeds. The genetic variants that correlate with many of them are known. The element related to pigmentation that Orlando includes in his review relates to a cultural pattern:

It is noteworthy that this information cannot only reveal the traits that past breeders most likely selected, but can also help document past funerary traditions. For instance, the analysis of coat coloration loci in the 13 complete horse skeletons found in the funerary monument of Berel (Kazakhstan) revealed that ≈2500 years ago already, Scythian Pazyryk Iron Age nomads herded the full diversity of horse coat colors present in the region today. Since those horses were specifically killed for the funerals of Pazyryk elite members, the genetic data also showed that sacrifices were not targeted toward particular family groups or coat colors.

Orlando here cites his own 2017 work in a paper led by Pablo Librado.

Overall it is a useful and interesting review. We are relatively advanced in knowledge of horse domestication now compared to many other domesticates, at least with respect to the major ancestors of today’s breeds. We have to keep in mind how much we don’t know about ancient variation that has not been sampled, and the discovery of presently-unknown populations should not surprise us.

What ancient DNA is telling us about the prehistory and history of the horse was originally published by John Hawks at john hawks weblog on April 21, 2020.