Like many people I didn’t know much about Avicii when he was alive, though I know much more now that he has died. His stuff played while I was on the computer in the lab, or when I was working out. Avicii for me was the anti-Kardashian, as I had no idea who “he” (I wasn’t sure of gender though I assumed he was male)was, where he was from. He was just a DJ who made music, and I enjoyed the music. He wasn’t famous to me, but his music was famous.
The figure above is kind of hard to parse, but it’s from Body size downgrading of mammals over the late Quaternary, and it illustrates that in some periods larger animals tended to go extinct, while others there was no bias due to size (in fact, large animals tended to do quite well because of their wide ranges). I was pointed to this paper by an Ed Yong piece in The Atlantic, In a Few Centuries, Cows Could Be the Largest Land Animals Left.
One of my peeves with the overall field of natural history is that sometimes researchers just want to argue about the obvious because they can. Natural history is obviously historical, and so you can’t just run an experiment and settle things. It seems pretty clear to me looking at the pattern across the past two million years across six continents that humans are not the sufficient cause of megafaunal mass extinction but they are a necessary cause.
If it wasn’t for humans, mammoths would still be around. How do I know this? They were around for hundreds of thousands of years a minimum and made it through the Emian interglacial from 130,000 to 115,000 years ago when the world was actually warmer than it is today.
The major work of the paper above was assembling a large data set across a wide time period and geographic expanses. You can see that the emergence of Homo, and not just modern humans, is really what matters. The labels above are: LQ, average of all late Quaternary (LP to H) extinctions; LP, late Pleistocene; EP, end Pleistocene; TP, terminal Pleistocene; H, Holocene; and F, future extinctions. The end of the Pleistocene was probably bad because the shock of the climate change probably knocked out a lot of species which were already under pressure from humans.
I’ll leave you a quote from Yong’s piece:
When hominins like Neanderthals, Denisovans, and modern humans spread through Europe and Asia, the average mass of mammals there halved. When Homo sapiens later entered Australia, the mammals there became 10 times smaller on average. And when they finally entered the Americas, with effective long-range weapons in hand, they downsized the mammals there to an even steeper degree. By around 15,000 years ago, the average mass of North America’s mammals had fallen from 216 pounds to just 17.
Addendum: The reason that Holocene extinctions have a smaller size average is that there weren’t as many big mammals to kill. We’re pretty much moving down the trophic layers now….
When Rasmus Nielsen presented preliminary work on diving adaptations a few years ago at ASHG I really didn’t know what to think. To be honest it seemed kind of crazy. Everyone was freaking out over it…and I guess I should have. But it just seemed so strange I couldn’t process it. High altitude adaptations, I understood. But underwater adaptations?
The paper is out now, and open access, Physiological and Genetic Adaptations to Diving in Sea Nomads. There are a lot of moving parts in it, so I really recommend Carl Zimmer’s piece, Bodies Remodeled for a Life at Sea:
On Thursday in the journal Cell, a team of researchers reported a new kind of adaptation — not to air or to food, but to the ocean. A group of sea-dwelling people in Southeast Asia have evolved into better divers.
When Dr. Ilardo compared scans from the two villages, she found a stark difference. The Bajau had spleens about 50 percent bigger on average than those of the Saluan.
Only some Bajau are full-time divers. Others, such as teachers and shopkeepers, have never dived. But they, too, had large spleens, Dr. Ilardo found. It was likely the Bajau are born that way, thanks to their genes.
A number of genetic variants have become unusually common in the Bajau, she found. The only plausible way for this to happen is natural selection: the Bajau with those variants had more descendants than those who lacked them.
As some of you might know “sea nomads” are common across much of Southeast Asia. The Bajau are just one major group. The anthropology here is not surprising…but the biology most definitely is. For various technical reasons, the authors didn’t have extremely fine-grained genome data (high coverage sequence data, or very high-density chips). So they didn’t do some haplotype-based tests (e.g., iHS), though that might not matter anyhow (see below why). But, looking at the genome-wide relatedness and comparing that to makers which deviated from that expectation, both of which they could do robustly, the authors narrowed in on candidates for targets of selection. From the paper: “Remarkably, the top hit of our selection scan (Table 1) is SNP rs7158863, located just upstream of BDKRB2, the only gene thus far suggested to be associated with the diving response in humans.”
There are many cases where researchers find selection signals in an ORF of unknown function. In this case, the top hit happens to be exactly in light with the biological characteristic you’re already curious about. The alignment is so good it’s hard to believe.
But wait, there’s more! Spleen size variation is not due to variation on just one locus. It’s polygenic, albeit probably dominated by larger effect quantitative trait loci (QTLs) than something like height (so more like skin color). They compared the Bajau to a nearby population, the Saluan, as well as Han Chinese as an outgroup. On the whole the distribution of allele frequency differences should reflect the phylogeny (Han(Bajau, Saluan)). The key is to look for cases where the Bajau are the outgroup. From the paper:
While some of the selection signals uniquely present in the Bajau may be related to other environmental factors, such as the pathogens, several of the other top hits also fall in candidate genes associated with traits of possible importance for diving. Examples include FAM178B, which encodes a protein that forms a stable complex with carbonic anhydrase, the primary enzyme responsible for maintaining carbon dioxide/bicarbonate balance, thereby helping maintain the pH of the blood….
FAM1788 shows up again later:
We identified one region overlapping chr2:97627143, which falls in the gene FAM178B, that falls in the 99% quantile of the genome-wide distribution for the fD statistic (Martin et al., 2015). Of the populations considered, this region exclusively stands out in the Bajau, and the signal appears strongest when using Denisova as source. Notably, this region was also proposed as a candidate for Denisovan introgression in Oceanic populations by….
What they’re saying here is that the allele at this locus adapted to diving may have come originally from the Denisovans! Remember, we already know that one of the Tibetan high altitude adaptations come from the Denisovans. So this isn’t surprising, but it is pretty cool. But most of the other hits don’t seem to be introgressed. That is, they come from modern humans (or have been segregating in our species for a long, long, time).
Many of the alleles found at high frequencies in the Bajau are found in other populations, just as very low frequencies. This implies that selection is operating on standing variation. Another suggestion that this is so is that the widths of the regions of the genome impacted by selection seem rather narrow. In contrast, the Eurasian adaptation to lactose digestion is from a de novo mutation, something that wasn’t at high frequency at all in the ancestral human populations. The sweep is strong and powerful around that single mutation, and huge swaps of the genome around it “hitchhiked” along so that on a population-wide level the area around the mutational target was homogenized (basically, a lot of one single original mutant human is found around that causal variant for lactase persistence).
Anyone who has learned basic quantitative genetics knows that one way to change a mean trait value is just to change the allele frequencies at a lot of different loci…over time you’ll have a lot of low-frequency alleles present in an individual which would otherwise never have occurred. Eventually, you can have a median value which is outside of the range of the original distribution. The mechanism here in a dynamic sense seems totally comprehensible, though as Carl Zimmer notes, and the rather short-shrift given in the Cell paper suggest, they’re not sure in a proximate sense how the selection is working (i.e., obviously there is a fitness implication but how does it manifest? Do people die? Are they unable to support a family?).
One key issue is to consider the demographic history of these people. The authors tried to model it genetically:
We found a model compatible with the data that has a divergence time of ∼16 kya, with subsequent high migration from Bajau to Saluan and low migration from Saluan to Bajau (for details see STAR Methods). We note that the estimate of 16 kya may reflect the divergence of old admixture components shared in different proportions by the Saluan and the Bajau, similarly to, for example, European populations being closely related to each other but differing in the proportion of ancient admixture components….
The authors cite papers which outline the real story about what happened, so they know that the model is somewhat unrealistic. For example, Ancient genomes document multiple waves of migration in Southeast Asian prehistory:
Southeast Asia is home to rich human genetic and linguistic diversity, but the details of past population movements in the region are not well known. Here, we report genome-wide ancient DNA data from thirteen Southeast Asian individuals spanning from the Neolithic period through the Iron Age (4100-1700 years ago). Early agriculturalists from Man Bac in Vietnam possessed a mixture of East Asian (southern Chinese farmer) and deeply diverged eastern Eurasian (hunter-gatherer) ancestry characteristic of Austroasiatic speakers, with similar ancestry as far south as Indonesia providing evidence for an expansive initial spread of Austroasiatic languages. In a striking parallel with Europe, later sites from across the region show closer connections to present-day majority groups, reflecting a second major influx of migrants by the time of the Bronze Age.
The upshot is that the predominant genetic character of Southeast Asia dates to the Neolithic, and to a great extent even more recently. The deep divergence between two Austronesian groups may be an artifact of drift in one group (probably the Bajau), or different proportions of admixture from the primary ancestral components in maritime Southeast Asia: Austronesian, Austro-Asiatic, and indigenous hunter-gatherer. As per Lipson 2014 the Bajau are probably mostly Austronesian but may have Negrito ancestry from the Phillippines, as well as indigenous hunter-gatherer more closely related to Malaysian Negritos. There probably isn’t so much Austro-Asiatic in Sulawesi, but I’d bet the farmers have more of that.
Ultimately the question here is are the adaptations to diving old or new? Anthropologists and historians have all sorts of theories, as reported in the Carl Zimmer article and hinted at in the paper. My own bet is that they are both old and new. By this, I mean that some sort of maritime lifestyle was surely practiced by indigenous people between the end of the last Ice Age and the arrival of farmers. But if the variation was present in humans more generally, the Austronesians would probably also have the capacity for the diving adaptations. Mixing with hunter-gatherers and another bout of selection could have done the trick in concert. So the adaptations and lifestyle are old, but the Bajau people may date to the last 2,000 years, and selection within this population may be that recent.
A lot of the answer might be found in looking at the other sea nomad groups….
On this week’s episode of The Insight (Stitcher and Google Play) we talk to Lee Berger, author of Almost Human and a paleoanthropological revolutionary. Or, less sensationally Lee tells us his view on the practice and results of science in his field (which is literally in the field).
Like most scientists, Lee is passionate about his work, but unlike many, he’s really good at talking about it. That’s an important skill going forward because science is usually funded by the public or private foundations.
Here is the original paper on Homo naledi, Homo naledi, a new species of the genus Homo from the Dinaledi Chamber, South Africa. This small hominin had a brain 30% the size of our own, and lived until at least (and likely later than) 200,000 years ago in southern Africa. At some point they’ll get DNA out of naledi. Lee’s current opinion based on morphology seems to be that this is a highly basal lineage. That is, it separated from the one group that led to anatomically modern humans 2 million years ago!
Also, if you haven’t, please give us 5 stars on iTunes/Stitcher! I know how many readers I have, and 59 ratings aren’t the limit of reach of my audience.
When David Reich’s op-ed came out some discussion ensued about his focus on prostate cancer risk in African Americans. This is the research which put Reich on my personal radar (if you care, start with this 2006 paper, Admixture mapping identifies 8q24 as a prostate cancer risk locus in African-American men). I had a back-and-forth with Debbie Kennett about whether this was a robust result. To be honest I hadn’t followed the research closely because 1) my own risk of dying of prostate cancer is probably pretty low knowing what people in my extended pedigree tend to die from 2) I’m not terribly interested in disease genetics unless they have a strong evolutionary genomic implication.
Doing some cursory literature searches suggested that Reich was right to include that example in the book and the op-ed because there had been follow-up work that verified the initial result. I had told myself that perhaps I’d follow up on this at a later point. After reading Laura Hercher’s rather patronizing take on David’s op-ed I decided that now is as good a time as any.
Looking around I found a very recent paper which hits the spot. Genetic hitchhiking and population bottlenecks contribute to prostate cancer disparities in men of African descent (it’s in Cancer Research). It came out in February 2018, so it will be up on the literature, and, there is an evolutionary angle here (I am friendly with the first author and respect his work overall).
The paper is open access so I recommend you read it. But here’s the high level:
- They had access to Sarah Tishkoff’s huge data set of African populations, as well as 1000 Genomes, to produce a combined panel with 1 million markers and 64 populations (38 African).
- Then, they focused on the hits in the literature for prostate cancer SNPs, which they called CaP susceptibility loci. 68 SNPs with high confidence (they looked for p-values of 10-5 or less).
So they have the data set with populations and allele frequencies, and a subset of markers that they want to interrogate (no imputation here, they had all the SNPs). They developed a statistic, Genetic Disparity Contribution (GDC), to evaluate the impact of SNP differences across populations in terms of CaP risk (that is, prostate cancer risk).
First, they need to look at a SNP in a particular population:
i = SNP, j = individual, and k = population. The SNP here is the “risk allele” (remember, they come in two forms). 2, is reflecting the frequency of the risk allele. ORi is basically the odds ratio of a given SNP of developing prostate cancer.
Now, the GDC:
A = African and N = non-African. You are just using the frequencies within the populations of interest for the given SNP. You can compare different populations presumably.
Finally, the individual Genetic Risk Score (GRS):
The score for an individual j in population k is the sum of ̅ across all 68 markers. If the individual has no “risk alleles” (those that increase odds of developing prostate cancer), then their GRS = 0.
As I stated above I don’t know much about prostate cancer. Honestly, I should take more of an interest, since it seems to run on my sons’ maternal side, so they are at risk (I know I am at risk, but people in my family tend to die of heart issues rather than cancer). The heritability for this cancer is 0.42-0.58. This is not trivial. The authors state that “CaP has the highest familial risks of any major cancer.” I certainly did not know that.
Combining their population-wide data set and the knowledge of risks from GWAS on CaP risk SNPs, they generated the plot to the left which shows you each population’s mean GRS. They confirm earlier work which suggests that African populations are at more risk than non-African populations and that West African populations are at more risk than East African populations. The authors observe that some African populations do have low risks even on the global scale. But on the whole the rank here is:
West African > East African > South Asian > European > East Asian.
They used ADMIXTURE to confirm the obvious correlations; the more West African ancestry in an individual the higher the GRS. The highest non-African population are Puerto Ricans, who have substantial West African admixture.
But one thing to remember here is that some of these African populations are quite distinct. For example, though West African populations have the highest risks, the Hadza and the Baka have high risks as well, and these hunter-gatherers are very diverged from other Africans. In fact, we know from ancient DNA that modern African populations are fusions of extremely distinct groups whose divergence may go well north of 200,000 years ago.
The pattern of risk seemed a bit strange to me outside of Africa. On the genome-wide scale, South Asians are between Europeans and East Asians, with a slight bias if any toward Europeans. This is because half the ancestry of South Asians is closely related to that that contributed to Europeans, and half is distantly related to the ancestry of East Asians. This can easily explain why their archaic admixture fractions are between these two groups. And yet the average GRS makes it clear dthat they seem higher than these two populations.
Lachance et al. do the standard genetic calculations of risk, and perform some exploratory analysis of the population structure in their data (since they curated this from well-known sources this wasn’t necessary for outlier removal as much as the regression that they ran of GRS on ancestry fractions). But they didn’t delve deeply into demographic history that I allude to above. Rather, what they did focus on were signals of selection in regions of the genome that these the risk markers were embedded in.
They seem to come to two general conclusions:
- Selection through the side-effect of hitch-hiking does seem to drive some of the African vs. non-African divergences.
- Much of the difference can probably be due to specifics of drift in non-African populations in the “out of Africa” event, and there isn’t evidence of polygenic selection across the 68 loci in the aggregate.
The latter seems unsurprising because prostate cancer hits late in life. As a trait, it is not what you are going to be selecting against in a pre-modern world (anyway, grandmothers, not grandfathers, seem to increase descendant fitness the most in ethnographic work). Additionally, the authors say that “risk allele frequencies tend to be higher in Africa when risk alleles are ancestral, and risk allele frequencies tend to be higher in non-African populations when risk alleles are derived.” Ancestral/derived here relates to new mutations (the latter). We know that the “out of Africa” bottleneck resulted in the extinction of some ancestral variation, presumably including ancestral risk alleles.
The former, in regards to linked selection, is also not surprising. As non-Africans spread across the world they developed new local adaptations, and some allele frequencies shifted from the African ancestors. But not all. And that I think explains why South Asians have a higher risk than Europeans and East Asians. The authors observe several protective (lower risk) alleles rose in frequency due to being in a region where there was selection for lighter pigmentation. Pigmentation is one trait which is highly heritable where some non-Africans (South Asians, Oceanians) are often more like African populations than other Eurasian groups. If high-risk CaP alleles were somehow associated with ancestral pigmentation alleles, then it makes sense that South Asians have a higher risk, since they are more ancestral on these loci than other Eurasians.
Finally, there is the question of how applicable these GWAS are to diverse populations. These markers were discovered in mostly European panels, so there is the standard ascertainment bias. Though the authors do say that “The International Agency for Research on Cancer GLOBOCAN program estimates that CaP has the highest incidence of any tumor site in African-American, Caribbean, and African men.” That is, African men, just like men of the Diaspora, are at higher risk. And remember, the association with African ancestry emerged in African American men, with those with elevated African ancestry in a particular region of the genome being at higher risk. It wasn’t a naive observation of higher rates of CaP in African Americans.
Because the OR can vary between populations, the authors ran their analysis by equalizing the OR and also by using the literature value of OR at a marker population by population. They found the broad disparity held. Subsampling the markers also maintained the rank order in broad geographic terms. Finally, the authors observe that because of the bias in the discovery of European risk variants, there are probably African risk variants that are not in their marker set which result in an underestimate of the GRS.
What is the upshot of all of this? The less important one is that David Reich used the example of prostate cancer to open his discussion about population structure because it’s probably a robust result (and also, in the book he makes clear a lot of sociologists and anthropologists did not appreciate the correlation between disease and ancestry that seemed due to biology). The balance of the evidence points to the likelihood that men with African ancestry, in particular, but not exclusively, of West African ancestry, have somewhat higher risks all things equal of developing prostate cancer. As the authors note the risks overlap quite a between populations. A substantial number of men of European ancestry have a higher GRS for CaP than those of African ancestry. There are two classes of alleles driving this risk. One class has high-frequency differences between populations, and another class has a large impact on odds ratios (so small differences still matter).
The figure to the right shows that there is a strong correlation between predicted genetic risk score and the real death rate from prostate cancer. I’m a little confused though here about the relationship between the training set and the population one is predicting on. Presumably, the GWAS come from these populations based on medical research, which is the same body of literature collecting the death rates. But the interesting thing here is that East Asians, Europeans & Latin Americans, and Diaspora Africans, are all distinct clusters in both mortality and GRS.
Since the heritability is not high, but only moderate, and even this correlation is imperfect, one can still argue that the disparity is attributed to environment. But to be honest the South Asian prediction along with the relationship to pigmentation regions indicates to me that the GRS is capturing something real in population differences due to a combination of demographic history and natural selection.
Moving on from CaP, these academic debates about whether disparities are driven by genes, environment or both (or an interaction), miss the bigger picture that due to the contingencies of history different populations probably have different risks in late-in-life diseases. The South Asian risk for cardiac and metabolic illnesses is so extreme that I think most people won’t deny that that is a real thing (in particular since there is variation within South Asia for this judging by British medical data).
Almost done with She Has Her Mother’s Laugh: The Powers, Perversions, and Potential of Heredity. To be honest I’m a little relieved that there wasn’t that much focus on the “perversions” of heredity. Lots of interesting stuff. This is definitely a book that scientists and lay people could benefit from.
Carl is a great writer so he makes rather abstruse concepts clear and engaging to nonspecialists. As for those of us who have our noses close to the ground, we sometimes lose the bigger perspective. There is a lot of interesting research that he surfaces in She Has Her Mother’s Laugh that I wasn’t very familiar with, though I had probably read about it or seen it in one of his columns (or Ed Yong’s).
Met a lot of cool people, and touched base with others who I knew ahead of time, at the AAPA 2018. Compared to ASHG or even SMBE the conference was very white. I guess that’s why there were all the diversity sessions?
I had a lot of discussions with Lee Berger about science on a broad philosophical level. Unfortunately, specialization is such that it can be hard to communicate across disciplines such as human genomics and paleoanthropology. But as Lee brings enough samples into the open to do some real statistics I think that will change how constrained to the elect paleoanthropological knowledge is.
Lee’s son introduced me to the concept of South African barbecue. I haven’t had any yet, but I’m curious about it.
Lee will be on this week’s episode of The Insight. Again, please subscribe on iTunes, Stitcher, Google Play. The last episode with Stuart Ritchie was our most successful yet in terms of traffic. We’re suspecting that Lee’s episode will do quite well as well. People keep finding the podcast by chance. We really need reviews to get featured by iTunes!
Spencer and I will probably shift back to a two-person conversation next week. We should probably do an AMA again soon.
Was There a Civilization On Earth Before Humans? Very interesting piece, especially for those of us who have read science fiction. But my issue is straightforward: humans have scrambled biogeography so much in such a short amount of time. I think any other industrial species would have done the same. Even after they went extinct, the phylogeographic chaos they wrought would remain.
It seems very likely that all Australian marsupials descend from one South American ancestor species. The explosive emergence of very different placentals all across Australia simultaneously in the fossil record would be quite suspicious (or red deer descendants in New Zealand).
I spent some time with the people who were associated in some way with the Reich lab a fair amount during the AAPA meeting. I also talked to a few friends about what they thought about David’s op-ed and book. It’s no surprise that there are legitimate human population geneticists considering writing a response of some sort. It’s also no surprise that even critics of David within the population genetics community think that the Buzzfeed op-ed was so bad that it makes it harder for them say something, as the water has been nuddied.
In some ways the reaction has made one of David’s major points: population geneticists need to offer their unvarnished opinions, rather than cosigning people in other fields who mangle their findings.
Some people feel that David “threw me under the bus” in his now infamous chapter. I don’t see it that way.
As many of you know (if you subscribe to my total content feed you know) I have a few other blogs, one of them Brown Pundits. It actually receives substantial traffic from India now. It will be “interesting” to say the least.
A population genetic interpretation of GWAS findings for human quantitative traits. Stuck in the weeds of ancient DNA these past few years I haven’t been paying attention to the storm of GWAS and PRS approaching.
Recently I was having an email exchange with a friend (a prominent public intellectual who is not a scientist), and we were thinking about what “ancestral Africans” looked like. More precisely, the populations which were resident around ~100,000 to ~200,000 years before the present. These are the people who are depicted in paleoanthropology documentaries. Here were some of my major contentions:
1) We don’t know what they looked like
2) They probably were more likely to look like modern Africans than non-Africans
3) But modern Africans are diverse in their looks and we could expect that ancient Africans were too
The neighbor-joining tree above is generated with a naive model of successive bifurcation.
1) Khoisan split off 200,000 years ago
2) Mbuti split off 150,000 years ago
3) Mende split off 100,000 years ago
4) Japanese about 50,000 years ago
5) While Pathan and Basque only 15,000 years ago
The model is wrong in the details. Pathan and Basque have some ancestry is which recently diverged, and much that is deeply diverged. The 15,000 year value is just an average. Similarly, the Khoisan have some Eurasian ancestry. But in the broad sketch it illustrates that some African populations diverged a very long time ago from other groups.
Ancient Africans date to ~200,000 years before the present for all the modern populations. Khoisan to Japanese. You could probably use phylogenetic character reconstruction methods to attempt to infer what ancient Africans looked like…but I’m not sure that it would be useful since modern humans have spread over so many ecologies over such a short span of time.
Outside of Sub-Saharan Africa perhaps on the order of 95% of the ancestry derives from an expansion from a small founder group between 60 and 80 thousand years ago. Removing the “Basal Eurasian” component, groups as diverse as Native Americans, Oceanians and East Asians probably derive their ancestry from a common group which flourished between 50 and 60 thousand years ago (this pulse is the majority of the ancestry of Europeans and South and West Asians as well).
The point here is to illustrate that 50,000 years is definitely sufficient for a great deal of diversity to have emerged in human physical variation. And yet the Khoisan are ~200,000 years diverged from their ancestors within Africa. We actually know that indigenous southern Africans have been selected for lighter pigmentation. We also know that loci associated with pigmentation in modern humans exhibits a lot of variation in Africans, and this variation is likely an ancestral feature of our species.
In sum, the number of generations between ancestral Africans and all modern descendent populations is great enough that I’m not uncertain that we can predict what they look like in anything except their skeletal features. Additionally, most of the history of anatomically modern humans was likely highly structured within Africa. That’s another way of saying that ancient Africans themselves were probably physically diverse.
With all that being said, all things equal ancient Africans probably are more likely to look like modern Africans than modern non-Africans. The main reason is simply that modern Africans occupy the same broad ecological landscape as ancient Africans, and many of our features, from our build to our complexion seem dependent upon environmental pressures. There’s lot of evidence that very light skin is probably a derived characteristic of our species (there are consistent signatures of sweeps around pigmentation loci). And, there is also evidence that some of the archaic introgression into non-Africans may have consequences in our morphology and external physical characteristics. For example, Eurasians seem to have very high frequencies of Neanderthal variants of the keratin gene. This is implicated in hair, skin and nail development.
Addendum: Note that even if we have ancient genomes, polygenic characteristics are still hard to predict. Even today common SNPs only explain a minority of the variation in hair color in Europeans.
Reflecting back to it I think I started “exploring personal genomics” in the late 2000s. That’s when direct-to-consumer testing started to become popular, albeit very niche. The book Exploring Personal Genomics is now 5 years old, and a lot has changed since then. In the same year, 2013, David Mittelman and I cowrote Rumors of the death of consumer genomics are greatly exaggerated in Genome Biology.
Now Science has a commentary out, Crowdsourced genealogies and genomes, which reviews how large amounts of public data, genetic and classical genealogical, are being used to change the field before our very eyes. I would recommend though that you read the less edited (longer, more detailed) version on the website of the authors, Crowdsourcing big data research on human history and health: from genealogies to genomes and back again.
This fact from that piece is really illustrative of what’s happening today:
As the number of customers of whole-genome DTC genetic testing just crossed 16 million, it is worth noting that almost two-thirds of them joined since the beginning of 2017 . Based on current rates, this number of customers is predicted to be close to 100 million by end of 2020.
Recently I had a discussion with a friend that I suspect the “tropical pygmy” phenotype you see Central Africa and Southeast Asia is a pretty recent development. So this sort of assertion, “The Sentinelese tribe have remained on their North Sentinel Island, almost completely uncontacted for nearly 60,000 years…” is probably wrong. First, the Sentinelese probably arrived with other Andaman peoples during the Pleistocene from mainland Southeast Asia when the archipelago may have been connected to the mainland due to low sea levels.
Second, the small size of many tropical hunter-gatherer populations may simply be due to the difficulty of surviving in this environment. Though rainforests are lush, humans can’t access a lot of it, and small animals tend to require more energy to catch than is justified by how much meat they provide.
Different human populations facing similar environmental challenges have sometimes evolved convergent biological adaptations, for example hypoxia resistance at high altitudes and depigmented skin in northern latitudes on separate continents. The pygmy phenotype (small adult body size), a characteristic of hunter-gatherer populations inhabiting both African and Asian tropical rainforests, is often highlighted as another case of convergent adaptation in humans. However, the degree to which phenotypic convergence in this polygenic trait is due to convergent vs. population-specific genetic changes is unknown. To address this question, we analyzed high-coverage sequence data from the protein-coding portion of the genomes (exomes) of two pairs of populations, Batwa rainforest hunter-gatherers and neighboring Bakiga agriculturalists from Uganda, and Andamanese rainforest hunter-gatherers (Jarawa and Onge) and Brahmin agriculturalists from India. We observed signatures of convergent positive selection between the Batwa and Andamanese rainforest hunter-gatherers across the set of genes with annotated ‘growth factor binding’ functions (p<0.001). Unexpectedly, for the rainforest groups we also observed convergent and population-specific signatures of positive selection in pathways related to cardiac development (e.g. 'cardiac muscle tissue development'; p=0.003). We hypothesize that the growth hormone sub-responsiveness likely underlying the pygmy phenotype may have led to compensatory changes in cardiac pathways, in which this hormone also plays an essential role. Importantly, we did not observe similar patterns of positive selection on sets of genes associated with either growth or cardiac development in the agriculturalist populations, indicating that our results most likely reflect a history of convergent adaptation to the similar ecology of rainforest hunter-gatherers rather than a more common or general evolutionary pattern for human populations.
A minor note: there is some ethnographic data that the isolated Sentinelese are not as small as the other Andaman Islanders. Some of their small size may simply be due to exposure to diseases and the stress of settlers from the mainland.
On this week’s episode of The Insight (Stitcher and Google Play) we talk to Stuart Ritchie, a postdoc in Ian Deary’s lab, about recent developments in cognition and genomics. There’s a reason that Deary gets some time in She Has Her Mother’s Laugh; his group is publishing some really interesting work.
Before we get to the good stuff, Stuart gives us a quick review of general intelligence and why it matters. If you want a book-length treatment then his own book should suffice, Intelligence: All That Matters. Richard Haier’s The Neuroscience of Intelligence goes a little more into the “wet biology” aspect of the brain if that is more your style.
There are two reasons I wanted us to have Stuart on the podcast.
First, psychometrics is not a field which was hit by the replication crisis. It’s a pretty robust and reliable discipline. Companies such as the Educational Testing Service (ETS) rely on the predictive power of the constructs in the field to sell their products. And yet most well-educated people don’t really know much about intelligence testing except that it has been “debunked” by the Mismeasure of Man.
Because people don’t understand the history of intelligence testing (i.e., it enabled the meritocracy by removing the importance of “polish” and “good breeding”) it’s easy for American graduate schools to do things like removing the GRE as a criterion on admissions. Privately some academics have told me that this will mostly result in increasing the importance of undergraduate education and pedigree (because anti-GRE sentiment has become connected to “social justice” I think it’s removal is a fait accompli).
Second, the field of cognitive genomics is moving through a major turning point. A publication like this in January, A combined analysis of genetically correlated traits identifies 187 loci and a role for neurogenesis and myelination in intelligence, is going to be superseded in months. I’m not speculating. I know this as a fact, and so do many others. Where will we be in two years?
Ray Kurzweil has many ideas, some of them interesting, some kooky, and some of them wrong. But one idea he’s promoted which I think is correct is humans are not good at modeling exponential rates of growth. The field of psychometric genomics is now moving into the steep phase of ascent, as sample sizes go well above 1 million, and some researchers shift from proxy characteristics such as education and delve into raw intelligence test scores. Most people “outside of the know” are about to smash into the concrete before they even know it’s coming up at them….