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paleoanthropology, genetics and evolution

Photo Credit: Contemporary human skull compared to the Kabwe cranium. John Hawks CC-BY-NC 2.0

Legacy of a candidate gene and replication in genomics

During the 1990s and early 2000s, many human geneticists and other scientists (especially psychologists) tried to study the genetics of human traits by following a candidate gene approach. In this approach, researchers studying a phenotype identified a genetic polymorphism and tested it within a sample of individuals to see whether it correlated with their phenotype.

The criteria for identifying a polymorphism as a “candidate gene” varied from study to study. The single most widespread criterion was that the polymorphism had to be easy to genotype using early 1990s-era genetic approaches. Length polymorphisms and microsatellite (STR) loci were especially common as polymorphic markers. Later, when microarray approaches became cheaper and more reliable, many researchers continued to rely upon the length polymorphisms and STR markers because they were comparable with older literature. To do this, researchers worked to find which SNP haplotypes were linked to the length polymorphism, enabling them to impute length polymorphism alleles from SNPs.

Ideally, researchers hoped to identify genes with protein products that had a plausible biochemical connection to a trait. The idea was that biochemistry and cell biology could identify networks of genes that had a structural or regulatory role in generating a phenotype, and that systematic investigation of the variation in those specific genes would enable researchers to discover the genetic causes of variation in the phenotype.

One of the most famous of the “candidate gene” length polymorphisms for psychological and behavioral phenotypes is the 5-HTTLPR polymorphism. This is a length polymorphism that lies in or near the 5’ promoter region of the gene SLC6A4. Serotonin, also known in the biochemical literature as 5-HT, is transported into neurons by SLC6A4. The serotonin transporter protein became known as the 5-HT transporter, or 5-HTT.

Armin Heils and coworkers during the mid-1990s found a tandem repeat polymorphism in the promoter region of 5-HTT, which they found to be connected to gene expression activity: “Allelic Variation of Human Serotonin Transporter Gene Expression”. They named this polymorphism 5-HTTLPR, and hypothesized that it may be related to variation in behavior:

We have recently characterized the human and murine 5‐HTT genes and performed functional analyses of their 5′‐flanking regulatory regions. A tandemly repeated sequence associated with the transcriptional apparatus of the human 5‐HTT gene displays a complex secondary structure, represses promoter activity in nonserotonergic neuronal cells, and contains positive regulatory components. We now report a novel polymorphism of this repetitive element and provide evidence for allele‐dependent differential 5‐HTT promoter activity. Allelic variation in 5‐HTT‐related functions may play a role in the expression and modulation of complex traits and behavior.

This kind of assertion was very exciting to psychologists who were looking for ways that genetics might influence behavior. The 5-HTTLPR polymorphism was easily genotyped with mid-1990s-era approaches. It wasn’t cheap, but it was cutting edge science. A possible large-effect variant affecting behavior would fit well with behavioral psychology approaches that relied on samples of dozens of individuals. One lab after another began to test whether 5-HTTLPR was related to behavior.

Later, a similar polymorphism was discovered in the 5-HTT gene of rhesus macaques. The monkey polymorphism enabled experimenters to test how the gene might influence responses to maternal deprivation, alcohol exposure, and many other conditions.

All of this has been a long-winded way of introducing a recent blog post by Scott Alexander, who looked into the legacy of this research on the 5-HTTLPR polymorphism and psychological and behavioral phenotypes: “5-HTTLPR: A pointed review”.

To make a long story short, twenty years of research into this candidate gene appear to have been largely a waste of time and effort. Today, well-powered studies involving thousands of research subjects have shown that SLC6A4 makes little to no difference in clinical conditions or normal behavior.

Alexander reviews this result and emphasizes the depth of the problem in a way that I’ve seen few state so clearly:

First, what bothers me isn’t just that people said 5-HTTLPR mattered and it didn’t. It’s that we built whole imaginary edifices, whole castles in the air on top of this idea of 5-HTTLPR mattering. We “figured out” how 5-HTTLPR exerted its effects, what parts of the brain it was active in, what sorts of things it interacted with, how its effects were enhanced or suppressed by the effects of other imaginary depression genes. This isn’t just an explorer coming back from the Orient and claiming there are unicorns there. It’s the explorer describing the life cycle of unicorns, what unicorns eat, all the different subspecies of unicorn, which cuts of unicorn meat are tastiest, and a blow-by-blow account of a wrestling match between unicorns and Bigfoot.
This is why I start worrying when people talk about how maybe the replication crisis is overblown because sometimes experiments will go differently in different contexts. The problem isn’t just that sometimes an effect exists in a cold room but not in a hot room. The problem is more like “you can get an entire field with hundreds of studies analyzing the behavior of something that doesn’t exist”. There is no amount of context-sensitivity that can help this.

Today, there are geneticists who criticize the GWAS approach. GWAS identifies statistical associations between SNP alleles in a sample and phenotypes, but most of these associations have not led to better knowledge of the biochemical or developmental pathways by which genes affect phenotypes.

Indeed, the genetic variations that actually cause phenotypic variations are invisible to GWAS. The method’s reliance on the phenomenon of genetic linkage between common SNPs and causal variants means that findings from any one population may have little application to other populations that share a different history that gave rise to different linkage patterns.

Still, many geneticists who began their careers within the last fifteen years may not know the history of the 1990s and early 2000s-era human genetics. At that time, some geneticists strongly pushed the idea that gene discovery must be supported by clear biochemical evidence demonstrating the mechanism by which gene variants affect phenotypes.

In those days, I had many conversations with human geneticists who were endlessly frustrated that they couldn’t get their work published because it was based upon genome-wide analyses. Some reviewers insisted on biochemical work to support statistical evidence of gene-phenotype associations.

5-HTTLPR was strongly pushed by those who wanted this kind of biochemically-informed approach to genomics. The variant was almost the perfect candidate gene.

Chimpanzees learn to crack nuts faster than humans

Early this year, Christophe Boesch and coworkers released a paper describing their observations on how fast chimpanzees and humans learn to crack nuts. They collected data on human foragers from the Mbendjele group, and chimpanzees of the Taï forest, watching how children and juvenile chimpanzees learn from other individuals, the extent that older individuals “teach” by intentionally directing their behavior toward the learners, and measuring the rate at which individuals can get panda nuts out of their shells.

The method that each group uses to crack nuts is very similar.

Most people’s intuition probably would suggest that humans would learn how to crack nuts faster than chimpanzees. Boesch and coworkers found the opposite: Chimpanzees learn much faster than humans, and chimpanzees attain adult proficiency at much younger ages than humans do.

Figure showing nutcracking speed versus age in chimpanzees and human hunter-gatherers
Figure 1 from Boesch et al. 2019. Original caption: "Learning curves for the ‘number of nuts cracked per minute’ in Taï chimpanzees and Mbendjele foragers; (a) when considering absolute age (above) and (b) when considering relative age whereby 1.0 corresponds to the population-specific age of first reproduction. Indicated are the fitted model and its confidence intervals. For the plot age was binned (bin width: 0.1 year), and the number nuts cracked per minute was averaged per age bin. Symbol area represents the total observation time per age bin (0.1 to 15.8 hours)."

This is just an incredible figure. Taï chimpanzee adults and Mbendjele adults both end up with a similar pace of nutcracking – the humans average a bit higher but the variation among human and chimpanzee adults overlaps completely.

The paper includes a nice paragraph describing the acquisition of technical knowledge in humans from many small-scale societies. The overarching generalization is that human foragers and small-scale agriculturalists take many years to attain maximum performance in tasks that require some technical learning:

Recent studies about the acquisition of technical intelligence skills in humans revealed that apprentices may need many years of practice before reaching adult expertise. Despite social exposure to expert tool users’ performances and advice, apprentices only acquire the skills after many years of practice and with slow progress in performance. For example, stone knappers in Langda, New Guinea begin to acquire the technique as adults but appear to encounter difficulties in following the guidance and advice from skilled individuals, as for at least five years, they continue to produce much shorter adze heads employing different strategies than the ones demonstrated to them. A similar pattern has been observed in Khambhat, India, with the acquisition of another type of stone knapping technique, where apprentices pay no attention to some aspects of the technique used by experts, such that their final products are quite different from those of the latter. As a result, high quality beads are produced only after seven to ten years of practice. Similarly, long learning processes have also been documented for the hourly return rate in hunting and honey, palm heart, or tuber gathering among the Ache or the Hiwi, for the reported age of acquisition in different tasks ranging from food and craft production to music and story-telling among the Tsimane of South America, and for the production of knapping stones as tools for hideworking in Ethiopia.

The cross-cultural buildup of such data over the last 20 years has given rise to the idea that learning technical processes is so difficult that humans must be specially adapted to be able to learn this stuff. In such studies, the apparently very long period of skill acquisition is characteristic even of tasks like honey collection and digging tubers.

But the fact that chimpanzees learn to crack nuts much faster than humans causes Boesch and coworkers to suggest an alternative hypothesis. Humans are slower at learning how to do things because humans have a larger number of specialized technical tasks to learn how to do. They term this a “life history” hypothesis, because their proposition is that humans develop slower and need to attain full competency at adulthood, not as juveniles, and so humans have the luxury of taking longer at each individual task, possibly enabling them to learn a larger number of specialized tasks.

Both of these hypotheses take what seems like a bug and try to make it a feature. Humans in foraging societies take 20 years to achieve peak hunting returns. Why should this be, when lions manage to achieve peak returns in only 3 or 4 years? According to the “hard to learn” hypothesis, it is because human hunting is a lot harder to do than lion hunting, because humans are using a very technical set of abilities. According to the “life history” hypothesis, it is because humans have lots of other things on their plate, and their learning has to balance all these things against the timeline of development.

Obviously, the nutcracking example busts the “hard to learn” logic, because chimpanzees are using the same method as humans, and achieve peak performance much faster.

But the “life history” hypothesis doesn’t seem to describe the pattern for learned skills that humans start to perform as adolescents and fail to become fully proficient until age 35 or higher. I come back to the question of why it takes humans 20 years to achieve peak hunting success. The problem is similar in timeline to the “apprenticeship” examples of specialized tool manufacture mentioned above.

One answer might be that the “life history” hypothesis works for easier tasks, and the “hard to learn” hypothesis works for harder ones. Chimpanzees do not become craft specialists or tenured professors. Maybe these really are uniquely difficult, and that’s why it takes humans so long to become proficient at them (and many never become proficient).

I would offer an alternative possibility: Humans may take a long time to gain apparent efficiency of performance in such tasks because human social relationships hold back performance.

Some tasks are communal, meaning that all individuals in a group may benefit from one person’s effort, while no person can monopolize the fruits of her labor. As a result, individuals are disincentivized from maximal performance, as long as that performance has costs. For example, hunters in a hunting and gathering society vary greatly in their average success rate and return rate of meat. Studies of hunters in such societies have shown that adolescents have low return rates, which increase gradually up to age 35 or 40. Those returns later decline at older and older ages. This pattern has previously been explained as the delay caused by the time needed to learn complicated hunting skills. But such a hypothesis neglects the costs of hunting. Such costs include energetic costs from hunting effort, risk of injury or death while hunting, the opportunity costs of socializing or pursuing other activities, and the social obligations that are imposed upon good hunters, among others. In a food sharing group, a young hunter would be entirely rational to pursue a strategy of increasing learning effort only as older hunters decline in their abilities.

Likewise, an apprentice often would be best served not to attain too great a skill while still under the thumb of his master. If the apprentice can actually monopolize the benefits of his own labor, the situation would be different, but an apprentice’s independence depends on an intricate network of social relationships, not purely the quality of his work.

It is at the same time quite true that some human technical tasks are made vastly more complicated by cultural rules. For example, something as simple as a bead has many culturally determined characteristics, including length, diameter, smoothness, type of drill hole, material, and many others that increase the difficulty of an craftsman attaining the necessary precision.

My point is that watching how fast individuals in real societies attain maximal performance is a very bad measure of how fast they might be able to learn. Human motivation is social, not merely economic.

Pointing to a need for better data presentation

Knowable magazine, which is an outlet of the Annual Reviews series of journals, has a great current article by Betsy Mason on the need to improve how scientists present their data: “Why scientists need to be better at data visualization”.

The problem of meaningful data visualization is approaching critical proportions in the study of human population genomics. Common means of portraying variation among genomes simply typically be interpreted by anyone without deep experience in examining them.

Mason’s article doesn’t touch upon these more difficult types of visualization, but it provides some solid context on the bigger picture of misleading graphs and color schemes across the sciences. I endorse this point about tools: Scientists won’t spend time learning good visualization methods themselves, but they have to use tools.

One way to combat the power of precedent is by incorporating better design principles into the tools scientists use to plot their data (such as the software tools that have already switched from the rainbow default to more perceptually even palettes). Most scientists aren’t going to learn better visualization practices, O’Donoghue says, “but they’re going to use tools. And if those tools have better principles in them, then just by default they will [apply those].”
Scientific publishers could also help, he says. “I think the journals can play a role by setting standards.” Early-career scientists take their cues from more experienced colleagues and from published papers. Some journals, including PLoS Biology, ELife and Nature Biomedical Engineering have already responded to Weissgerber’s 2015 work on bar graphs. “In the time since the paper was published, a number of journals have changed their policies to ban or discourage the use of bar graphs for continuous data, particularly for small data sets,” she says.

Even in paleoanthropology, where beautiful physical objects like fossils and stone tools are an important part of our work, we could do much better than most current practice in finding ways to make information comprehensible to readers.

Working toward more ethical anatomical collections at the University of Cape Town

Victoria Gibbon of the University of Cape Town has written a piece for The Conversation recounting how UCT is addressing some historical wrongs in the development of its human anatomy collection: “Skeletons and closets: How one university reburied the dead”.

I returned to the University of Cape Town (UCT) and examined the Human Skeletal Repository records. Unfortunately, I found 11 individuals with known names or dates of deaths or which were known to the donor in life. The research suggested these remains should not be at the university.
Fast forward to 2018 after a lengthy process of figuring out a way forward. With the university’s Office of Inclusivity and Change we have embarked on the initial phase of the restitution project. Of the 11 unethically procured sets of remains, nine are from the town of Sutherland in the Northern Cape. We decided to start there.

This case has been in the news in South Africa during the last few weeks, and this essay is a good opportunity to see the case from the perspective of a biological anthropologist.

Anopheles mosquitoes disperse over long distances by wind

This is decidedly unsettling: “Windborne long-distance migration of malaria mosquitoes in the Sahel”.

Studies seeking to understand the paradoxical persistence of malaria in areas in which surface water is absent for 3–8 months of the year have suggested that some species of Anopheles mosquito use long-distance migration. Here we confirm this hypothesis through aerial sampling of mosquitoes at 40–290 m above ground level and provide—to our knowledge—the first evidence of windborne migration of African malaria vectors, and consequently of the pathogens that they transmit.

The work is by Diana Huestis and coworkers in Nature. The long-distance dispersal helps to address why it is so hard to eliminate malaria. It looks like females (80% of those dispersing this way) take on blood meals and then hitch a ride on the wind.

Are three-rooted molars evidence of Denisovan introgression in Asia?

During the 1980s and 1990s, the idea of multiregional evolution of modern humans was based upon the observation that today’s people living in various regions of the world share traits with archaic humans who lived in the same regions. Such traits provided evidence of regional continuity of ancestry.

This summer a brief report by Shara Bailey, Jean-Jacques Hublin, and Susan Antón suggested that three-rooted mandibular premolars in today’s Asian populations have actually been inherited from Denisovans: “Rare dental trait provides morphological evidence of archaic introgression in Asian fossil record”.

According to this idea, three-rooted mandibular molars are a regional continuity trait in Asia. Molars in the mandibular dentition usually have two roots, but a three-rooted form occurs in East Asian people fairly commonly.

It has long been thought that the prevalence of 3-rooted lower molars in Asia is a relatively late acquisition occurring well after the origin and dispersal of H. sapiens. However, the presence of a 3-rooted lower second molar in this 160,000-y-old fossil hominin suggests greater antiquity for the trait. Importantly, it also provides morphological evidence of a strong link between archaic and recent Asian H. sapiens populations. This link provides compelling evidence that modern Asian lineages acquired the 3-rooted lower molar via introgression from Denisovans.

Here is the illustration including the virtual model of the Xiahe M2.

Figure 1 from Bailey et al. 2019, showing the three-rooted alveoli for M1 and CT scan of three-rooted M2 from the Xiahe mandible
Figure 1 from Bailey et al., 2019. Original caption: The 3-rooted lower molar anomaly. Three-rooted lower first molar alveolar sockets showing distolingual position of accessory root and the 3-rooted lower first molar (lingual view); (Inset) 3-rooted lower second molar of Xiahe Denisovan individual (lingual view). Left and Middle images courtesy of Christine Lee (California State University, Los Angeles, CA). M, mesial; L, lingual; D, distal; B, buccal. Credit Bailey et al. CC-BY-NC-ND 4.0

I think that Bailey and coworkers here present an interesting hypothesis. This idea brings back to my mind some of the 1990s-era discussion about how scientists should recognize evidence of genetic admixture or introgression from morphological traits.

During the 1990s, several scientists were highly critical of others’ identification of “continuity features”. They noted that it was difficult to prove that any feature was a unique markers of descent from local archaic humans, because the fossil record is incomplete and biased. Some features that had been identified as continuity traits in Neandertals and later Europeans, they argued, might also have been present in earlier African populations but not yet sampled in the tiny fossil record of the Middle Pleistocene in Africa. Much discussion about regional continuity during the 1990s (and to some extent even earlier) focused upon whether “Neandertal” traits in later Europeans really were uniquely found in Neandertals, or whether they might have been in other populations at non-negligible frequencies.

Many advocates of an “out of Africa” model of evolution also suggested that apparent continuity traits might instead have resulted from parallelism or convergence in the newly-arrived modern humans. In their view, early modern humans might rapidly evolve to become similar to archaic humans in the same parts of the world, because of natural selection in the same local environments.

My own concern at the time was that continuity traits suffer an analytical bias that is hard to deal with. A strange trait that we see in a Neandertal is easy to notice when we see it in later European skeletal remains. But we don’t really know how likely such similarity may be without considering the total number of traits we didn’t notice.

This brings us back to sampling. In the period just before the apparent dispersal of modern humans from Africa, anthropologists have found many Neandertals and relatively few of anything else. If we accept that the Xiahe mandible is really a Denisovan (which maybe we should be more cautious about), that still brings the net number of Denisovan specimens with lower first molars to the grand total of one.

I always thought it was quite reasonable to start from the assumption that the data probably reflect a simple mixture model, and a Neandertal trait that was present at a lower frequency in Upper Paleolithic Europeans probably reflected some ancestry into that population from Neandertals.

I still think that’s reasonable, but my perspective has changed a bit. The main difference in my thinking today is that we know that the fractions of ancestry from many archaic groups are small—on the order of a few percent. I don’t think we can predict much about how such small levels of ancestry may affect morphology.

Europeans do have Neandertal ancestors—we now know that beyond any question. But East Asians today also have Neandertal ancestors. In fact, Neandertals contributed more genetic ancestry to East Asians than they did to Europeans. And Neandertals contributed more than ten times as much ancestry to East Asians as Denisovans contributed to East Asians.

Which morphological traits of East Asians today are markers of their Neandertal ancestry? That’s a question that presently has no answer. The answer might even be “none”. But it would be strange for East Asian people today to have no skeletal signs of Neandertal ancestry if European people (with less Neandertal ancestry) have some skeletal features that point that direction.

And it would be even more remarkable for many East Asians to have a dental trait that uniquely reflects their 0.002 fraction of Denisovan ancestry and have none that reflect their 0.02 fraction of Neandertal ancestry.

Maybe it’s really true. If so, we should probably guess that natural selection has acted on three-rooted mandibular molars differently from other traits, favoring its persistence in later populations.

I think it’s good to be alert for morphological connections between living and archaic groups. I don’t assume that they will reflect the frequency of contribution of genes from archaic groups. If the frequency of a trait diverges a great deal from the small fraction of genetic ancestry, it may be a sign of interesting evolutionary dynamics.

Quote: Darwin on the tree of life

Charles Darwin, in On the Origin of Species, introduced the idea that the relationships between organisms form a tree.

Darwin was not the first to propose that species resulted from evolution, but earlier ideas like Lamarck’s envisaged evolution as a transformation along a chain of species.

Darwin, near the end of Chapter 4 of Origin, discussed his idea about the relationships of organisms as part of a tree. This passage is not as quoted as the famous “tangled bank” passage, but it has similar power:

The affinities of all the beings of the same class have sometimes been represented by a great tree. I believe this simile largely speaks the truth. The green and budding twigs may represent existing species; and those produced during each former year may represent the long succession of extinct species. At each period of growth all the growing twigs have tried to branch out on all sides, and to overtop and kill the surrounding twigs and branches, in the same manner as species and groups of species have tried to overmaster other species in the great battle for life. The limbs divided into great branches, and these into lesser and lesser branches, were themselves once, when the tree was small, budding twigs; and this connexion of the former and present buds by ramifying branches may well represent the classification of all extinct and living species in groups subordinate to groups. Of the many twigs which flourished when the tree was a mere bush, only two or three, now grown into great branches, yet survive and bear all the other branches; so with the species which lived during long-past geological periods, very few now have living and modified descendants. From the first growth of the tree, many a limb and branch has decayed and dropped off; and these lost branches of various sizes may represent those whole orders, families, and genera which have now no living representatives, and which are known to us only from having been found in a fossil state. As we here and there see a thin straggling branch springing from a fork low down in a tree, and which by some chance has been favoured and is still alive on its summit, so we occasionally see an animal like the Ornithorhynchus or Lepidosiren, which in some small degree connects by its affinities two large branches of life, and which has apparently been saved from fatal competition by having inhabited a protected station. As buds give rise by growth to fresh buds, and these, if vigorous, branch out and overtop on all sides many a feebler branch, so by generation I believe it has been with the great Tree of Life, which fills with its dead and broken branches the crust of the earth, and covers the surface with its ever branching and beautiful ramifications.

Milk proteins in Neolithic dental calculus

A new research paper by Sophy Charlton and coworkers looks at calculus on human teeth from several Neolithic-era sites in England, finding that many of the individuals have trace evidence of milk consumption: “New insights into Neolithic milk consumption through proteomic analysis of dental calculus”.

There has long been debate over the origins of dairy consumption within European populations. Whilst it was previously assumed that lactase persistence (LP) was under positive selection following the advent of agriculture, recent genetic studies of prehistoric human remains have revealed LP may have only emerged in Europe in the last 4000 years. These findings stand in contrast to organic residue analysis of Neolithic pottery indicating the utilisation of dairy products, and zooarchaeological mortality profiles consistent with dairying herds at Neolithic sites. The recent discovery of the milk protein β-lactoglobulin (BLG) within human dental calculus presents a new method via which to explore dairy product consumption in the archaeological past. Here, we apply shotgun proteomic analysis to dental calculus samples from three British Neolithic sites, revealing the earliest identification of BLG in human dental calculus to date. The presence of BLG peptides in individuals who are unlikely to possess LP provides new insight into dairying in the British Neolithic, suggesting the potential processing of milk by Neolithic populations to reduce the lactose content of dairy products.
Additionally, organic residue analysis of pottery from Hambledon Hill has indicated the presence of both porcine and ruminant fats, and ruminant adipose and dairy fats (Copley et al. 2003, 2005a, b, 2008). The presence of dairy fats in > 25% of potsherds analysed has been suggested to indicate that ‘dairying was a very important element of animal husbandry at Hambledon Hill’ (Copley et al. 2008, p. 535).

It’s nice to have confirmation that milk trace residues in pottery co-occur with milk trace residues in human dental calculus. More and more sites where these data show a pattern will help us to understand the big picture – both by helping us to interpret sites where preservation is not as good, and by looking at smaller-scale shifts in diet.

It is no surprise that people in Britain started relying upon animal milk before lactase persistence was common in northern European populations. That’s how natural selection works. The environment changes, creating different survival and fertility conditions. Only then can genes that are adaptive in the new environment proliferate due to selection in the population.

Can methylation of DNA in ancient bones really predict the morphology of Denisovans?

Last week, Cell published a new paper by David Gokhman and coworkers that tries to infer the skeletal form of Denisovans from signatures of methylation in the Denisovan genome data. The paper is here: “Reconstructing Denisovan Anatomy Using DNA Methylation Maps”.

I’m a skeptic about the paper. The authors follow an approach that has not been shown to predict the morphology of any living humans or any other species.

The study tries to justify its method by looking at Neanderthal methylation and saying that the methylation pattern can accurately predict Neanderthal bone shapes. This may look convincing on the surface. But it’s actually not. This is a case where “researcher degrees of freedom” are very high.

I am working on a comment to submit to Cell about the study, focusing on some technical issues. I hope that the editors will be interested in publishing a critical exchange on the approach.

In the meantime, I want to point readers to a related study by another group of researchers that has been mostly ignored in the press coverage on this new paper.

Genevieve Housman and coworkers released a preprint earlier this year on biorXiv that looked at methylation patterns in several primate species (chimpanzees, macaques, vervet monkeys, baboons, and marmosets) to see if methylation could predict skeletal morphology within species or between species.

The preprint is here: “Intra- and Inter-Specific Investigations of Skeletal DNA Methylation and Femur Morphology in Primates”.

Housman and coworkers carried out a careful study that includes several analyses that are not in the new Cell paper by Gokhman and colleagues. Housman and coworkers measured DNA methylation in bone cells taken from the femur of each primate individual, and they actually took caliper measurements on the femur of each individual. This means that in every case they compared like with like. That’s different from what Gokhman and colleagues could do with ancient DNA, where the samples are coming from different parts of the skeleton from a mixture of different cell types.

Housman and coworkers found some methylation differences that seemed to associate with morphology in their samples. But these were small effects that they could not separate from other possible influences (genetic and environmental differences). I would add that the small sample sizes in the study (only 4 chimpanzees, for example) make it possible that the observed effects might be spurious effects of small samples.

When they looked between species, Housman and colleagues found differences in methylation, similar to Gokhman and coworkers in this new study. Some of those differences in methylation are near genes that matter to skeletal form. Gokhman and coworkers found the same thing for Denisovans and Neanderthals. But in the living primates, the methylation differences actually did not correlate well to the phylogenetic relationships of the primate species. While Housman and coworkers suggest that the methylation differences between species might make some difference to the evolution of their traits, they did not try to predict what those differences were. That’s very reasonable considering the lack of clear signatures within species and the small proportion of the genome included in these regions with different methylation.

What I think: Studying methylation differences is a promising avenue of research, but we are a long way from understanding how differences in methylation may relate to differences in the skeleton. It is important to match like with like – in the Housman study, the methylation of femur bone cells was used to study femur form.

It’s not outlandish to think that the pattern of methylation across promoters in the genome might give a clue about morphology. But there are huge gaps in our knowledge. And there are things we know about methylation in bone that this study doesn’t seem to represent. Those make me skeptical that this study is doing much more than presenting an interesting hypothesis.

I’ve seen a number of geneticists quoted in news stories, saying that now paleoanthropologists will have to test what methylation has told us about Denisovan morphology. That’s only partly correct. A test with paleontology cannot be valid until comparative evidence supports the proposed mechanism connecting differential methylation to morphology—remember, based here upon indirect functional inference for only 2.2 genes per trait.

But if we’re looking for a paleontological test, the Xiahe mandible may already provide one. Gokhman and coworkers predict that the Denisovan dental arch should be longer than modern humans and also longer than Neandertals. The Xiahe mandible, with its complete M3 agenesis, does not have a long dental arch.

When peer review turns to trolling

In University Affairs, environmental scientist Ryan Bullock looks at his career-worth of experience subjecting his research to peer review: “The trolls have infested academic peer review”.

It’s a worthwhile perspective and many scientists will recognize their own experiences.

After much consideration, I believe that current peer-review processes often do the opposite of what they are supposed to achieve. That is, the double-blind system provides no assurance to me – and, by extension, the readers – that reviewers are qualified professionals. The blind review process can reduce accountability, leading to poor-quality service work, which reviewers can no doubt still count on in their annual evaluations without having properly served their journal, their discipline or their colleagues. The blinded format can encourage boorish and unethical behaviour. To top it off, troll reviews waste an incredible amount of professional time and energy of authors, editors and colleagues who reviewed earlier drafts.

I agree that the system of anonymity is harmful. I sign my reviews for journals that permit it. I think that an open system would be much fairer to authors and referees. I also think openness would do much to reduce the overhyping of research articles upon their release.

Big data approaches to scientific career success

Undark recently published an article by Viviane Callier, looking at recent research on scientific career trajectories: “What Matters Most on the Road to Scientific Success?”.

For many people, the most salient (and potentially troubling) findings coming out of this research are that publication in “prestige” journals is transmitted through training networks, from supervisors to trainees. That, and there’s a selection effect at work:

“The prestige of your doctorate does matter insofar as it helps you get a more prestigious job,” Larremore explained. “But what we’ve found is, once you’re in the door to a faculty job, the training then doesn’t matter.” In other words, once in the same department, the productivity of faculty members who trained at more prestigious universities was indistinguishable from that of their colleagues who trained at less prestigious universities.

Relevant to me:

<blockquote.They also found that scientists were more likely to succeed if they trained with graduate and postdoctoral mentors with disparate expertise that they could incorporate into their own work.</blockquote>

David said he suspects that building connections that had not previously existed might be key to success. “There’s an intellectual space that hasn’t really been occupied before,” he said. “And if you can draw on two different areas of expertise and take something that’s kind of unique to each of them and bring them together into a problem of your own, then you can stake out some territory that hasn’t been explored before.”

Most successful scientists today will work in teams. Moving between teams seamlessly is very important to anyone who wants to continue to do exciting, cutting-edge work.

Stopping 'wasteful recollection of data already held by other research groups'

Last week I commented on the American Association of Physical Anthropologists’ recent statement on access to data: “Biological Anthropology association speaks out on data access”.

This is a big issue to which many voices have contributed. I’d like to bring attention to a broader selection of those views—not just the loudest or most widely read.

Three years ago, Lynn Copes and coworkers published a Scientific Data descriptive paper for a dataset of CT scans of non-human primate skeletal material. The paper is open access: “A collection of non-human primate computed tomography scans housed in MorphoSource, a repository for 3D data.”

The sample consists of 489 scans taken from 431 specimens, representing 59 species of most Primate families. These data have transformative reuse potential as such datasets are necessary for conducting high power research into primate evolution, but require significant time and funding to collect. Similar datasets were previously only available to select research groups across the world.

This has been a groundbreaking data release, providing an irreplaceable source of data not only for comparative analyses with other primate collections but also for education. The Harvard Museum of Comparative Zoology, which houses the primate material in the study, is to be congratulated for its forward thinking.

In the Scientific Data paper, Copes and colleagues commented on the overall situation with data access in biological anthropology. One paragraph is especially worth sharing:

Despite this rush to digitize, comparative morphology is experiencing a crisis as a mode of addressing large-scale evolutionary questions due to the difficulty involved in accruing datasets large enough to have high explanatory power, and the small community of researchers that can participate effectively. This presents a paradox: If so many researchers are putting large efforts into scanning, where are the massive samples? Though a few research groups have managed to generate large samples of scans comprehensively representing diversity in one clade or another, this work has been time consuming, and expensive: as a result these scans are not made widely accessible to non-collaborating researchers. This inequality in access to what is now essential, basic data clearly falls short of scientific ideals for meritocracy. Furthermore, a significant component of the unmanageable demand for 3D scan data experienced by museums may represent wasteful recollection of data already held by other research groups.

We are in an age where scientists must recognize the risk of destruction, damage, and loss of physical specimens held by museums around the world. Creating high-fidelity digital models of the physical objects and distributing those models widely is increasingly essential as a strategy for protecting objects with scientific and heritage value.

Of course researchers cannot answer every possible question from a digital model. But even for questions that must be addressed from original specimens, providing high-resolution digital data is essential for future researchers to see the details of analyses and use them as comparative data for analysis of other objects.

Natural areas going to the dogs

Human presence has changed the natural environment in many ways. One of the most important is the spread of species that do well in the presence of humans, many of which we tolerate and tacitly (or explicitly) encourage. Like Canis familiaris.

Last week, the Washington Post ran a short article describing research into the destructiveness of feral dogs in Brazil’s national parks and other natural areas: “The dog is one of the world’s most destructive mammals. Brazil proves it.”

It was found that the closer humans lived to a nature preserve, the more likely dogs had penetrated it.
But perhaps most striking? The dogs were neither feral nor domestic — but somewhere in between.
“All the dogs we detected had an ‘owner’ or a person that the animal has a bond with,” Paschoal said. “The species population increases following human populations, exacerbating their potential impact on wildlife.”

This is why many farms have dogs, to deter or kill small carnivores and other animals that would otherwise damage crops or kill small domesticates (especially chickens and other fowl). In communities where neutering and spaying are not practiced, large semi-feral dog populations often exist at the edges of human societies. They can rely upon discarded human foods during times when wild foods are scarce, which gives them a buffer that wild predators lack.

This process must have been important in the prehistoric past also. It may have contributed to a certain brittleness of human societies in the face of environmental change, since dogs would have reduced small herbivore biodiversity in the areas of human settlement, with longer-term consequences for forest and grassland plant community composition.

Looking at the importance of art in astronomical sciences

I’d like to point to a recent article from Undark by writer Mara Johnson-Groh, looking at the way that artistic visualization methods have been important to astronomy in recent years: “Sketching the Stars: How Art Can Advance Astronomy”

The article profiles several real-world examples where scientists have applied art techniques to build a better means of visualizing and understanding large astronomical datasets. This one was trippy:

With the aid of a specialized loom, they have also created woven installations nearly the size of a van that visualize the interconnectivity of the cosmic web. “We believe that art, as much as science, seeks to say something true about the nature of existence,” they wrote in a 2017 paper on their collaboration, “and that end is best served by artistic representation that grapples with real data and not only with allegorical concepts.”

The bottom line of the article is encompassed in the last paragraph:

“Applying the techniques from art definitely influences the way astronomers see and interact with their data,” English said. “I don’t think [techniques from art] in astronomy visualization can be relegated to a sidebar any longer. It really does enhance discovery science.”

Human genetics is always a step or two behind astronomy in terms of data processing and visualization. I see a lot of promise over the next few years in developing new ways of visualizing and understanding genetic datasets from humans and other creatures.

A story of Australian repatriation

The September issue of Smithsonian magazine has a feature article by Tony Perrottet recounting the burial ceremony for the “Mungo Man” skeleton, which happened in late 2017. The article includes perspectives from Aboriginal people, scientists, and museum professionals, and gives an idea of the scope of the repatriation issue in Australia. I will be looking at assigning this for my courses: “A 42,000-Year-Old Man Finally Goes Home”.

The article tells many stories that are part of the broader issue of repatriation. One section recounts a visit to the Repatriation Program of the National Museum of Australia, with director Michael Pickering. In this passage, he recounts the problems of inadequate curation of Aboriginal (and other) skeletal material in the past:

“We had 3,000 individuals, all indigenous, in the ’80s,” Pickering marveled. “Rooms full of bones.” Locating the Aboriginal communities to return them to involved serious detective work. Many of the skeletons were mixed up, their labels faded or eaten by silverfish, and their origins were only traced through century-old correspondence and fading ledgers.
The unit’s centerpiece is a table where skeletons are laid out for tribal elders, who wrap the remains in kangaroo skin or wafer-thin paperbark to take back to Country. But not all of them want to handle the remains, Pickering said, often asking staff to do it instead. “It can be a harrowing experience for the elders,” says heritage officer Robert Kelly, who has worked in repatriation since 2003. “To see the skulls of their ancestors with serial numbers written on them, holes drilled for DNA tests, wires that were used for display mounts. They break down. They start crying when they see these things.”

Later in the article, there are two paragraphs juxtaposed back-to-back with each other that express a deep contrast in views of the past. I cannot share the article without commenting on them.

Just as revolutionary was what Mungo Man meant for the understanding of Aboriginal culture. “Up until Mungo, Aboriginals had been frequently denigrated,” Bowler said bluntly. “They were ignorant savages, treacherous. Suddenly here was a new indication of extraordinary sophistication.” The reverent treatment of the body—the oldest ritual burial site ever found—revealed a concern for the afterlife eons before the Egyptian pyramids. Two of Mungo Man’s canine teeth, in the lower jaw, were also missing, possibly the result of an adolescent initiation ceremony, and there were the remains of a circular fireplace found nearby. “It took me a long time to digest the implications,” Bowler said. Today, Aboriginal people still use smoke to cleanse the dead. “It’s the same ritual, and there it was 40,000 years ago.” All the evidence pointed to a spectacular conclusion: Aboriginal people belong to the oldest continuous culture on the planet.
News of Mungo Man’s discovery, presented as a triumph by scientists, provoked outrage in the Aboriginal communities; they were furious that they had not been consulted about their ancestor’s removal from his homeland. “I read about it in the newspaper like everybody else,” recalls Mary Pappin, a Mutthi Mutthi elder. “We were really upset.” The first quiet protests over archaeological work had begun years earlier over Mungo Lady, led by her mother, Alice Kelly, who would turn up with other women at new digs and demand an explanation, carrying a dictionary so she could understand the jargon. “My mum wrote letters,” recalls her daughter. “So many letters!” Removing Mungo Man seemed the height of scientific arrogance. Tensions reached such a point by the end of the 1970s that the 3TTs placed an embargo on excavation at Lake Mungo.

I work to build a better scientific understanding of the past. When we look at past people, we often come to understand their inventiveness and creativity, the depth of their cultures, and the way they overcame challenges. Building a richer picture of ancient people can be inspiring.

But the first paragraph here illustrates a self-serving narrative by archaeologists. “Suddenly here was a new indication of extraordinary sophistication.” The notion suggests that we should recognize the past achievements of ancient people as a reason for respecting their descendants today. That’s wrong. It’s backwards.

Treating living people with respect does not require understanding their ancestors. Treating living people with respect is basic humanity. It is wrong for archaeologists (and geneticists and other scientists) to work without effective consultation with communities of descendants and relatives.

In fact, there was nothing “sudden” about the shift in archaeological practice. The stories told before the 1970s were created by colonial Europeans—including archaeologists and anthropologists—to control and subjugate Aboriginal people.

The Mungo archaeological work began at a time when colonial assumptions were newly questioned within archaeology, by a generation of researchers coming of age during the 1960s and 1970s. The interpretation of the Mungo discoveries incorporated ethnographic insights in ways that were rare in earlier archaeological work, part of a shift in archaeological practice globally. The work was important scientifically, it led to new ways of looking at the past. That much is true.

But the work itself still reflected colonial practices and structures. Archaeology might have been shifting its interpretations of past peoples, but it hadn’t yet found its way to full respect of descendant communities in conceiving and carrying out the work.

Archaeological discoveries about ancient Aboriginal people are fascinating. I hope that such discoveries will continue, because they bring a perspective on the development and history of human societies not only within Australia but as a comparison for many other parts of the world.

But discoveries cannot continue without the participation and engagement of local and descendant communities. Science developed without such participation is bad science—ethically wrong, and almost certainly factually wrong.