David Reich – Why the Bronze Age was an inflection point in human evolution

Uh that um uh that's very exciting and I wanted to talk to you about it. Um so let's begin. What can you can you t give me a little bit of context on what we're talking about today?

And that dream has really not been realized uh since the beginning of this field. So while the field's been a big success with regard to learning about human history, it's resulted in um surprising findings about human migrations, people not being descended from the people who lived in the same place hundreds or thousands or tens of thousands of years before and mixture being common in human history.

sex bias processes being common in human history and things that were not expected from archaeology. And so the field's been a big success from that perspective. But what's not been successful is learning about uh biology and biological change.

And one big reason for that has been that the sample sizes have been too small. So when you have a single person's DNA, it provides a a tremendous amount of information about history. And that's because when you look at one person's DNA, it's not a single person. It's many people. It's your two parents. It's your four grandparents. It's your eight great grandparents and sixteen great great grandparents and so on.

And going back in time, thousands, tens of thousands, even hundreds of thousands of ancestors going back in time contributed to people today. So when you look at the DNA of a single person's genome or a Neanderthal genome, you have effectively tens of thousands of ancestors all represented in your data.

And you can ex you can position that individual exquisitely with respect to other people from whom you have data. But when you are interested in how a particular genetic variant that affects something like your skin pigmentation or affects your ability to digest

cow's milk into adulthood or affects a behavioral trait. When you want to see how that changes over a time, a single person gives you only one sample or maybe two samples, the one that is in their mother and the one that's in their father. And so to get a high resolution picture of how the frequency changes over time, you need to have very big sample sizes of truly very large numbers of people. And we just didn't have that until the last few years.

So what motivates this study that we're, I think, talking about today and the work that hopefully another number of groups will be doing in the coming years is the fact that we now finally have those numbers and we can do something with the data to see how frequency changes over time.

then there's pressure on the population to adapt to these new stresses, these new these new needs.

And the way you're gonna detect that is you're gonna see that the frequency of a genetic variant that, for example, might allow you to live at higher altitude, for example, or that might sort of nudge you to have a different behavioral pattern that might be advantageous in the new situation, that genetic variant might push systematically in some direction in a way that is enough that you can detect it.

Now it's very hard to detect slight shifts in frequency by a few percent or a ten percent unless you have a very, very big sample size. And so what we're looking for are those changes in frequency that are too extreme to be due to chance, then that will tell us. that there have been pushes in the against the biology as a result of the changes and environment that people have experienced.

laboratory rather than other places was that a focus of our laboratory has been generating truly large amounts of data from ancient humans. We've been really trying to industrialize the process, make it very inexpensive, make it high quality.

and generate large numbers of samples with lots of good data for this purpose. So there's been this large amount of data that we've generated, and it made it possible to conceive again of asking the question about whether there's been frequency changes over time. So the mainstream view in human evolution in the last several decades

has been that natural selection has been pretty quiescent over the last several hundred thousand of years of human history. And there's several lines of evidence that have been deployed to document this. One is that if you compare diverse populations from different continents around the world, for example, Europeans and East Asians. And you look at mutations that differ in frequency between these groups, all mutations differ a little bit in frequency, sometimes a lot.

You can say, what are the most different mutations in terms of frequency between Europeans and East Asians? And there's almost no genetic changes that are 100% different in frequency between Europeans and East Asians. So Europeans and East Asians descend from a common ancestral population forty or fifty thousand years ago that came out of Africa in the Middle East.

This population had a set of gene frequencies, genetic frequencies, and these variants bopped around uh randomly, a process known as genetic drift, or perhaps under selection in one direction or another. And the time that's passed since forty or fifty thousand years ago is sufficiently small on an evolutionary timescale that there's just not much genetic differentiation on average between these two groups, Europeans and East Asians.

But however, if there's been natural selection, for example, to help people in one place digest. digest alcohol better, or for example, digest milk better, or do something else better, what you might expect is that there was be some mutation that would have rocketed up to very high frequency. And forty or fifty thousand years is a lot of time. It's maybe fifteen hundred or two thousand generations.

And so that might be enough time, easily, to see a hundred percent different in frequency, and yet you don't see any more compared to what you'd expect by chance. So this made it seem that just selection has been quiescent. Maybe a few hundred thousand years ago, the ancestral human population got to some kind of optimum. And

After that, there hasn't been much genetic change in one way or the other. And there's been small amounts of natural selection or there's been selection to remove bad mutations that are constantly raining down on the genome, but not what we call directional selection, which is newly arising mutations or mutations being pushed in a systematic direction to help the population get to a different adaptive set point that's that's that's more favorable for the conditions that population is living in.

So we were able to partition how much of the changes and frequencies of of of all the mutations that we're seeing in the DNA. We're looking at about 10 mil 10 million positions that vary, is due to directional selection, adaptation. versus other factors, especially genetic drift. Uh, and ninety-eight percent of it is other factors, especially genetic drift. So it's overwhelmingly migrations and population structure causing fluctuations and frequency.

And as a result, it's super hard to actually detect the signals of natural selection in adaptive natural selection because they're a tiny fraction of the total frequency change. the vast majority of it are these migrations and mixtures. Nevertheless, there's so much natural selection, as our study thinks, has shown, that in fact, it's been rampant in the genome.

one population came in and kind of replaced the previous one, and then a new population came in and replaced the previous one. And to the extent that the genetics are relevant to why that population replaced the other one. Um why why why should that not count towards uh you know what we understand to be selection over the last ten thousand years?

And so what we're looking to see is whether there's one place in the DNA that is driving the change in a way that's different from the rest of the genome. And really from a statistical point of view, what happens at these times of migration is there's just

huge fluctuations and frequencies. And these are extremely uninformative times for looking and detecting natural selection. The best moments to detect natural selection is when migrations and population and admixtures are not happening for a few hundred years. And during these times you can actually see the mutations slowly blowing in one direction as a result. Yeah.

Really the way we think about the history of Europe and the Middle East and the way we think about it for the purpose of this study is as an archipelago of little populations in space and time, each of which are pretty isolated from each other. So a little population in Britain isolated for a few hundred years, a little population in Hungary isolated for a few hundred years between big events of migration and mixture.

And in each of those little experiments of nature we can ask, does this mutation slightly increase in frequency? Does that same mutation slightly increase in frequency? And if all the arrows point in the same direction, we win.

And they're telling us that natural selection is occurring. So for example, 4,500 years ago in Europe, almost all mutations go through huge frequency changes. And that's not because of natural selection, it's because of the step migration from the step north of the Black and Caspian Sea, 40%, 50%, 80% of the DNA becomes Yamnia from step pastoralis.

And their frequencies of mutations were different, not because of selection necessarily, but just because they had evolved in different places for thousands and tens of thousands of years. And then if you look at the descendant populations, there's huge changes in frequency. And it's very what you need to do is see, oh, is natural selection explaining a shift more than you would expect by chance?

Okay. You found these locations that seem to be under selection. Oh, an another clarifying question. So you have you say thirty eight hundred locations which you're fifty percent confident are have been under selection the last ten thousand years.

uh and that uh in fact almost every position in the DNA is uh correlated to a position that in being dragged in one way or the other uh by natural selection. Instead of being quiescent, Natural selection is everywhere. Even though it's only two percent of the frequency change, it's tugging the positions in one direction or the other everywhere.

So we analyzed these positions that we had identified, these hundreds of positions, the ones we were super confident about, and we looked to see whether they were randomly distributed in the DNA or whether they had patterns. And what we did is we looked at maybe a hundred or so traits where there had been genome-wide association studies for all sorts of different traits, like ones associated with immunity or autoimmunity or behavior or metabolism and uh basically other uh other things.

And for each of these, we could ask, are the genetic variations that are known to affect these traits from genome-wide association studies? Do they have an unusual number of genetic selection signals? And what we found is there was a vast enrichment by about a four or five fold for immune traits. That is, there was a super concentration of selected uh signals in immune traits.

Whereas also we saw a strong enrichment for metabolic traits, things that might have impacted your obesity or fat traits or type two diabetes. And really almost no detectable enrichment, as far as we could tell, for behavioral traits or for uh for for psychiatric traits.

And the uh reason we think we see and we have evidence that this is so, uh, much weaker signals for behavioral traits is that behavioral traits we know from other studies, medical studies, are underpinned by much larger numbers of genes than immune traits, which are underpinned by relatively small numbers of genes of strong effect. Behavioral traits traits are

shaped genetically by very large number of genes of weak effect, and we just don't have the statistical power to detect these very weak signals there. So when we do an analysis where we look at our very strong signals of selection. That collection of very strong results is very effectively querying the immune traits, but is not very effectively querying the behavioral traits.

It may still be the case, and I guess it is, that immune traits are the most selected category, but it is not at all the case. And in fact, we can prove it's not the case that behavioral traits are not selected. So we think there's two reasons.

why natural selection has uh we've been able to prove really that there's two reasons why uh how to reconcile the previous observations with our new observations. Remember the previous observation is that Is that natural selection seems to have been quiescent over a timescale of hundreds of thousands or many tens of thousands of years. Reason that you don't see a hundred percent different in frequency variance across Europeans and East Asia.

So now we're seeing hundreds of positions that are rocketing up in frequency with selection rates 1% or more in a lot of cases. So 1% or more selection rates will mean that there'll be a rapid doubling over periods of dozens of generations. And so over 1,500, 2000 generations, like you see separating Europeans and East Asians, shouldn't you see many?

genetic variants that are 100% differently different in frequency across populations. So we were able to show that this is explained by at least two factors. So one of them is that we actually in this part of the world, Europe and the Middle East, are in a period of accelerated natural selection.

And one way to see this is to look at this enrichment pattern that we're observing, where immune traits are unusually associated with these selection signals. And we could compare the last five thousand years of our of our time period. what's called the Bronze Age and further onward, uh to the previous five thousand years. And what we see is that this intensification of selection around immune traits, similarly the intensification around metabolic traits,

has accelerated over this time period. So it's not like natural selection has been at the same rate over all s places and times. In fact, it's increasing over the time period we're analyzing. And so plausibly the whole time period has increased compared to previous periods. So we're in a period of intensified selection. That's not implausible because this is a t a population that went through a huge shock in terms of the way people live in the culture. So this is a

population that almost everybody we're analyzing are farmers or food producers in one way or another. Farming was invented for the first time anywhere in the world in the Middle East, eleven or twelve thousand years ago. The people who invented farming uh exploded into Europe after 8,500 years ago and spread across Europe and expanded rapidly. In the Bronze Age, there was an intensification of how people lived with much higher population densities.

people living more and more next to their animals and getting their diseases and exchanging their diseases with them and with each other. And so this is a period of rapid, rapid change in terms of how people are living. Resulting in different biological needs of this population. So it's not surprising.

That in the context of these dramatic changes, the biology of the population might be not in the i uh ideally adapted uh position. That is, that there might be what some people call an evolutionary mismatch where you take uh a genetic uh variation that's evolved in hunter-gatherers and put it into farmers or pastoralists, and it's not exactly right.

And so what you're seeing is the DNA of this population, which is descended from hunter-gatherers only 10,000 years ago, reacting to the shock have having been moved into an agricultural and bronze age and high population density and urban environment. And a hypothesis is that what we're seeing is the adaptation that occurs as a result of that.

And one of the things that we see is that while for the most part, uh, the the signals of natural selection we detect are consistent with being constant natural selection over time.

in a handful of them we're able to see that there's been a reversal or a radical change in natural selection. And very often that occurs in the period between five thousand to two thousand years ago, which is the Bronze Age and the uh iron age, a period of rapid population growth and rapid movement to uh intensive use of of of um of many technologies that were not used that way before.

So an example of this is the tick two uh genetic variant that is a major risk factor for severe tuberculosis, which is the major infectious disease, the most important infectious disease killer in the world today. And if you look at the this major risk factor for tuberculosis, this variant rockets up in frequency from eight or six thousand years ago to maybe nine or ten percent in this part of the world. And then it rockets down in frequency in the last 3,000 years.

In both cases there's very clear evidence of natural selection, in the first case to increase in frequency, and then in the next case to decrease in frequency. And a possible reason for this is maybe the spread of tuberculosis uh maybe becomes endemic in the population two or three thousand years ago that's potentially consistent with uh pathogen uh sequence data and other lines of evidence.

And maybe this variant was protecting against something before then, but then tuberculosis became uh significant after that point. And it was so bad that it pushed in the up opposite direction. That's speculative. Oh.

one of them would fail to understand an important crux. And so I switched over to a different model, and that one would get tripped up on the very next point. I ended up using Cursor to kick off a handful of models at the same time and compare their results after. I could have one model critique the response of another. This was super useful because while I'm not a geneticist, I do have enough taste to be able to say, hey, this answer makes sense. These ones don't.

I also had Cursor turn this work into a flashcard so I could retain what I learned. Cursor started as a programming tool, but I found it really great for this kind of research. There's no other interface where I can get answers from a bunch of independent LLMs All while reading the relevant paper on the same screen. Go to cursor.com slash Thorcash to try it out.

One of the big takeaways for me, uh, from the paper was just that something weird happened in the Bronze Age. Um, and that as you said, we're not like across trade after trade. Uh, the selection intensifies during the Bronze Age. And this makes sense for some things. For example, why do we see lactase persistence?

uh where adults can process milk. Why is that intensified during this period? Oh well it makes sense this is the time when we don't we start using cattle not just for the meat, but then also for milk and wool and other secondary products. Um so it makes sense this is why l uh la lactose would matter lactose persistence would matter more. But then there's other things which seem like they should have been relevant since the dawn of agriculture. I forget the exact name of the allele, but was it

Uh fad S1, um, which uh helps convert plant fatty acids into long chain fatty acids that your body needs. Uh and that's also relevant when you move from a diet of meat as a hunter-gatherer to a diet of cereals. But why why you that is also one I think you found was under a special selection or especially high selection during the bron uh you know 5,000, 3,000 years ago. Um yeah, so w w what's going on? Why why is the bronze so special across all these different traits? that you're observing.

One of the findings of our paper is the A B O blood system. You know, you get your blood typed, it's A, B, and O. The B variant has increased up to ten percent at the expense of A, but previous work has shown that A and B were both already present. in the ancestor of humans and gibbons, you know, other other other apes. Uh and so these mutations, some of them have been going back and forth and fluctuating over time uh in different time periods. But we're talking about changes in the Bronze Age.

So this tick two variant for uh tuberculosis risk, uh multiple sclerosis risk variant inflected and increased in frequency before the Bronze Age and then two or three thousand years ago reversed.

At that period, and there's differences in Northern Europe where this process is super strong, very strong positive selection, very strong negative selection. And then in southern Europe, only a little bit and not even very strong negative selection for hemochromatosis, which is iron pathogenic iron buildup that causes problems uh in Europe. That too has reversed around this period in some of the complex traits that maybe we'll talk about later.

These traits too have periods of intensification of natural selection. For example, depigmentation, which is the uh Europeans have depigmented, gotten lighter skin over the last 10,000 years. You can see it in our data. The period of strongest depigmentation is between about 4,000 to 2,000 years ago. And then after that, it's much less.

And so this seems to be a very impactful, eventful, important period where a lot of the processes that we are s d seeing become very powerful. And it's surprising on first principles. You might think. before you walked into this genetic data that the big change is going to be starting to grow plants and maybe farm animals. And that happens in the Neolithic, you know, beginning ten or eleven or twelve thousand years ago and spreads into Europe after eighty five hundred years ago.

But actually the intensification happens like five thousand years ago, four thousand years ago. And so it's really interesting. This this observation of that being a key point, that being an inflection point tells us something about when humans, at least in this part of the world, were wrenched into a way of living that was so different from how the hunter-gatherer ancestors lived.

that the organism had to adapt very strongly and that maybe the degree of that wrenching process moving into the Bronze Age was qualitatively greater. Than the degree of the wrenching process that happened from the initial transition to growing plants. So, which is surprising because our

cartoon picture is that the big transition is farming, but the genetic data, the biological readout, is saying our genome is reacting much more strongly to this these events that happened five thousand years ago. So

uh allele frequencies are much different than what you just expect from this admixture. Um and you find uh correct me if I'm wrong, but you found that they weren't. That is to say that over two hundred, three hundred years of extremely intense environment change, you know, going from uh, you know, yeah, chattel slavery and uh c yeah, completely new environment. Uh there's no effect of natural selection.

And so we see episodes like this where we don't see natural selection and then but then the Bronze Age apparently must have had an even stronger effect, where the change in environment is even stronger than what we see from Africans in Africa, then being transp migrated to the uh uh to the New World and then living under slavery.

significantly as you would expect if there was natural selection from some ri genetic variant for your from Europeans or from Africans. We didn't see any place in the DNA that was significantly different from what you would expect by chance. And so uh

One possible explanation for that is just that there's only a handful of generations, maybe five, over which the natural selection would operate. And so maybe if the selection was two percent a generation, you would still only see maybe a 10% compounded effect. And there's just not enough time to detect it. But the Bronze Age is not 300 years, it's 3,000 years. It's the power of compound interest. And you have enough time to begin to see a strong effect.

But this really, really, really does seem to be a very impactful time in terms of human history. And you can see it in our complex traits. So for example, if you look at pigmentation, for example, uh, which is the uh strongest signal of selection for a complex trait in uh our data set. So you look at genetic mutations that are known to affect pigmentations.

you add up their effect across all of the DNA. So there's dozens or hundreds of them. And you look to see in what time are is the natural selection strongest. And the time period is really uh 2000 to 4000 years ago.

Uh and for some of these other traits as well, you see again the time period over which the selection is strongest uh is 2,000, 4,000 years ago. So for example, if you look at Uh, genetic variants that affect uh measures of cognitive performance, for example, uh, such as performance on intelligence tests.

uh in uh people in white British people today. Uh so this is of course a very strange trait to measure in the past because there were no intelligence tests and there was no school, but it is a predictor today and you could look at how it's changed in the past. And we see very strong natural selection for this combination of genetic variants that predicts people's performance on IQ tests and also.

is highly correlated to the predictor that predicts the number of years of school or the household wealth of people, all crazy traits in the past, because there was no wealth in the past. There was no school in the past. But if you look at the predictors today, there is a strong uh there is a strong movement in a systematic direction, uh a large effect about a standard deviation on the scale of modern variation. And then we can do this trick

of looking to see whether there's periods of time when this natural selection has occurred more intensely or less intensely. What we do is we drag a 2000 year window through our data and we repeat our whole analysis, not on 18,000 years, but just on a short 2000 year window. And we can measure the strength of selection in each of these 2,000-year windows. And what you see when you look at intelligence is you see that this maxes out.

In the Bronze Age, between five thousand, four thousand, three thousand, two thousand years ago, and the impact in the last two thousand years is almost nothing. There's no evidence of natural selection at all. You might think your bias coming into this, my bias perhaps,

if there's any signal of natural selection on this trade at all, might be that it would be unusually strong in the last two thousand years. Maybe this is a time of industrialization, maybe this is a time of greater need for this particular trait.

But in fact there's no evidence of natural selection at all in the last two thousand years, but there's very strong evidence in between two thousand and four thousand years ago, where instead of a one standard deviation strength of selection, it's a two standard deviation strength uh sort of averaged over this time period.

at a kind of heterogeneous group of people. There's, you know, Southern Europeans and Northern Europeans and hunter-gatherers and farmers and at different times in the past, those groups are more or less represented. Yeah. So the whole strength of the methodology Aliyakbari developed is it corrects for that uh changing ancestry over time. And as I mentioned before, really what's being asked here is we've divided up our whole data set into an archipelago of little populations.

in different places in space and time. And we're asking in each place in space and time a little pocket of people in Britain from four thousand years ago to thirty five hundred years ago, a little pocket of people in Hungary, a little pocket of people in in Italy from two thousand years ago to fifteen hundred years ago. In each of these places uh where the ancestry is relatively similar without being too disrupted in that short period by

uh migrations, we watch to see if the genetic changes blow in the same direction. And what we're doing here is we're measuring the strength of selection at each point in time after correcting for the big population changes that have occurred.

or um this the the thing that uh predicts household income or whatever. Um so these seem like do

Especially given that the this is only two percent of the change in yellow frequencies and then like the ninety eight percent is coming from migration. So that then it's sort of stupendous to think about like, well, what is the impact of migration then? If this alone can explain um or is driving a standard deviation change in these kinds of qualities, at least among the kind of variation we see in the world.

who are like uh at the mean, at zero. And that's migration. Yeah. Uh so what you're seeing is those two groups had different set points for those traits. And then the step pass storylists have a lower set value of this. And so you see huge fluctuations in the predictor of this trait over time. That doesn't prove selection. What that is just telling you is migration.

But what our test is telling you is in addition to those fluctuations due to select uh due to migration, is there a consistent effect of natural selection blowing the trait in the same direction over all over all places and times? And that's what we're detecting. Yeah.

part of the world and um therefore actually the ancients were much smarter than us and we've sort of evolved out in intelligence. And your results seem to point in the opposite direction. That Although there's not been election selection in the last two thousand years as s you know, society's gotten more complicated, at least when society began.

there was more need for the kind of thing that predicts intelligence today. And the reason that's surprising is if you think about hunter-gatherers, um, yeah, reading your colleague Joseph Hendrick's book, the amount of information that they needed to ha hold on to and assess everything from um how to process food to how to build shelters, fire, et cetera, compared to my world where I gotta like know how to set up mics and ask questions.

It's just like it seems like the gr demands on intelligence should have been like way higher in the ancestral environment. And so it's very surprising that the beginnings of civilization increase Um the selection on intelligence. Right.

these people were really having to do a lot of things and figure stu a lot of stuff out, maybe. Uh, and that maybe once you have more complex societies, there'll be more of a collective brain and maybe there'll be selection against this trait. And in fact, it's sort of the opposite in some ways. So it's the power of data. It's not what you expect. And, you know, after looking at this data, it's actually the value of data to try to make sense of all these things.

You know, it's very interesting, like uh the genetic predictor of intelligence. There's lots of kind of things that are confusing about it. So it's actually worth talking about it. Uh or the genetic predictor of years of schooling, which is highly correlated to it and is measured even better.

So if you look at the brid genetic predictor of years of schooling, there's another amazing study from 2017 from a group in Iceland that looked at this measure over the last hundred years in Iceland and it looked at older people. And it looked at younger people, but people born more recently in Iceland. And there's a estimated point one standard deviation decrease.

in genetic predictor of intelligence in Iceland just within one century is an absolutely huge effect over a short period. And this is selection against years of schooling. I if I said intelligence, I didn't mean to. selection against uh the num uh genetic predictors of numbers of years of school. And so one possible interpretation of this, uh sort of hand wavy, uh, is that actually what's being measured here is not

selection for years of schooling or for actually real intelligence, but for another trait altogether that's correlated to both of them. So for example, the predictor of numbers of years of schooling is very, very strongly correlated to the age at which women have their first kid. Uh and if you control for that for number of years of schooling, all of the signal of uh years of schooling goes away. So maybe what you're measuring is.

Women's decision about when to have children. And, you know, if you have children earlier, you don't go to school as much. If you have children later, you go to school more. Maybe it's some kind of measurement of delight and gratification or putting things off or planning. The same trait is correlated to body mass index, to obesity, or to uh walking pace. So is this really like uh intelligence as we think about it, or is it something else?

that manifests itself differently in different times uh in the past. Yeah.

Obesity, it's correlated to people's walking pace. It's correlated to people's household wealth, uh, it's correlated to uh a variety of other traits that seem quite different from it. So if you think you're actually measuring years of s uh genetic prediction of uh intelligence or years of or or actual, you know, studiousness or something like that, you should think again because there's many things that it's correlated to. There seems to be some kind of general trait.

that maybe you could think of as executive function or maybe propensity to defer gratification or something or I make just waving my hands. that is under selection and it pushes all these traits in the same direction, uh, one way or the other. And in different times in the past, it's it's it's advantageous or disadvantageous.

But when we found this signal of uh years of schooling uh being increased, the the g genetic propensity to go to school for more years, uh as it manifests itself t in people in white British people today. Uh when we found the signal, we were sort of incredulous, like how could this be? Maybe this is a problem.

So we did a few tests to try to figure out whether this was real. And one of the tests we did is we looked for a study where this measurement of the numbers of years of school was done not in European. but was done in Chinese people in China. And we looked at variants that had the effect size of many variants as they affected the number of years of school in China.

And we saw whether they had a relationship, a correlation to the trajectory of those same genetic variants in Europeans over the last 10,000 years. So these are two parts of the world where the populations have been essentially completely disconnected. And there's no way by chance that the trajectory in Europeans over the last ten thousand years will have anything to do with the number of years, uh the effect on the years of schooling in China today.

But there's actually a huge statistical correlation, a five or six standard deviation correlation between the effect size of variance and number of years of school in China today. and the trajectory in Europe, just as strong actually, as the effect size of variance in Europeans to years of school to to the trajectory in Europeans. So we just could not see a way this could happen by chance. And once we saw that, we really felt quite convinced.

that this was a real signal and that really somehow there has been natural selection to increase the genetic changes that today manifest themselves as more years of school uh predicting more years of schooling.

predict more years of schooling for Chinese people in China. Yeah. And so this is not just some weird artifact from the way these GWAPs were done in Europe. This seems to have rebu these parts of the genome seem to robustly predict. the kind of thing that actually leads to more years of schooling, at least in people today. Correct.

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um over the last 18,000 years. And I w we talked a little about what happened after the Bronze Age. I wanna understand it's surprising to me, we're talking about this during the collective intelligence part of the conversation, but it's surprising to me that

intelligence or lack of schizophrenia or so forth. Things just seem kind of robustly good. We're not maxed out um before the Bronze Age. And in fact, there was so much the diversity among different populations was so big that you have uh the European hunter gatherers um having three standard deviations is less predicted uh value for uh you know what they would score on the intelligence test if test if it existed.

Uh but you know, they were existing in the real world in a place where intelligence matters. And so how can it be that um they this was not a tr we just look at the human body or any animal, it's just like There's evolution has been acting on it so strongly to make it functional to the things it needs to do. And this one thing, which seems like so relevant, especially to what human hunter gatherers needed to do.

Is not under doesn't seem to have been under that strong selection uh in the Mesolithic or Paleolithic or those eras.

You know, in all contexts and places and time. And I think that there's a number of ways to think about that. First of all, I think we are speaking from the point of view of a society which intensely values this particular trait, you know, ability to score well on uh IQ tests or things like them, or to go to school for a long time or whatever it is.

And I think this is unprecedented in human history that we live in a time like this. Like if you look at the, you know, Hebrew and Christian Bible and you look at how much intelligence is valued, it's basically not at all.

Some communities are not, there might be valuation of things that are more proximate to, you know, years of schooling. But really broadly, it's not been a high value in the population.

here is a new uh world environment and go figure out how to process food there and make shelter and everything else. All the things which, you know, your colleagues like Joseph Henrik are talked about, like the how modern people underestimate the difficulty of

um doing this kind of thing with a small band of people. Anyways, this is a like m maybe that's not IQ test intelligence and that's why we don't see that strong a selection effect on this thing. But I just intuitively it seems like regardless of the value system, it just seems very valuable to uh ha have this trait maxed out.

Obesity, years of schooling, walking pace, you know, performance and IQ tests, household wealth, all these crazy traits all seem to be governed to a substantial extent by a shared combination of genetic variants. And let's just think about what this might mean. So in Iceland, in the last hundred years, there's been selection against this combination of variants. Uh and one possible interpretation is it's basically selection for

two ways of investing in your children. Having many kids and not investing a lot in them, or having few kids and investing more in them. Right. So if you invest in deferring, deferring having kids but

becoming, you know, having more wealth, having more resources and putting more into each kid, you're gonna have a lower fertility and you're gonna have fewer kids. And that's gonna result in ro lower fertility, but those kids might survive more and do better in society. Alternatively, you can just have as many kids as you

can and invest less in them. They might have individually less good outcomes, but in a time of plenty, which is potentially Iceland in this twentieth century, it might make sense to have more kids and invest less in them. And so there's a toggle between having more kids and investing less in them and having more kids and investing in less in one's life and having fewer kids and investing more in excelling in various ways or something like this.

And so you can imagine that actually at different times and in different places in in ecology, there's resource, there's different ways like mammals often invest a lot in with a pregnancy and a small number of children, whereas fish. will spawn huge numbers of offspring into the, you know, the the the river, the great majority of whom will be eaten, uh, but that is an effective way to produce offspring in certain conditions.

So there'll be a toggle, depending on the environmental conditions, back and forth between investing in large numbers of offspring with fewer and less investment or smaller numbers of offspring with more investment. And maybe we're just seeing that move back and forth over different places and times.

Similarly for schizophrenia and bipolar disease, how could this ever be advantageous? But maybe what we're seeing with these diseases is a kind of readout of some kind of spectrum of traits that actually in other in some contexts might be advantageous, maybe being anxious or being imaginative or being neurotic might be helpful in a shamanistic tradition, you know, in a religious tradition, which values people who can have visions, uh, or values people who can be creative. And maybe these are

subclinical versions of schizophrenia or bipolar disease that in certain times may be advantageous and in other times may be disadvantageous. Maybe you're just seeing selection.

from different types of creativity or other thinking that can be valuable in different contexts. I'm waving my hands here, but my sense is that these complex traits have not pushed in one direction because there's advantages there's spectrums where there's advantages to both ends of the spectrum and there's multidimensional uh uh uh you know impacts of these different traits.

there is no longer a need uh to the same extent to be able to build up body fat to sort of survive in times of stress because there's more constant stores of food. And so as a result, there will be no there will be natural selection against body fat, which can be uh once you move into an agricultural environment and to periods of food plenty. And so maybe what you're seeing is that this

group of people in Europe and the Middle East over the last 10,000 years has moved into a a period of relatively more stable food where building up stores of fat are not as advantageous and there's been selection against this combination of traits. Europeans actually are relatively better protected.

genetically against type two diabetes than some other populations around the world, like African Americans and Native Americans that have perhaps not been as exposed to ag agriculture for as much time. So you may be seeing the effect of more exposure to more stable Food accessibility.

uh access to high value nutrition. Uh that is not true to the same extent in farming communities. On the flip side of this, uh, these long, these famines are, I think, something that occurs more commonly in agricultural societies. But the time scale and the tempo of them is very different from the hunting tempo. So maybe there's a famine every three years.

And indeed, if you look at the bones of farmers, uh, at least in some communities, there's more stress in them, maybe due to a famine every three years or a famine every five years. But selection might not be apt acting on that three year time period. Your fat store uh it from, you know, the latest hunt is not gonna carry you through to the famine three years later. And so survival of famines is a different thing than building up body fat uh for uh being able to uh survive two weeks later.

That makes you wonder whether there's much more room at the top for intelligence. As in, if humans had been selected especially for intelligence, they could have been much smarter. And the reason that's relevant is We're currently building AI systems, which we're trying to make as smart as possible. And in fact, the only goal of the training process is intelligence. We don't have to worry about also at the same time making their immune systems powerful and

Uh, and I think that there's trade offs probably. Uh, but uh I think it's highly likely that if natural selection was pushed pushed any of these trades uh in uh more in one direction than it is, the the mean would move.

If you take all these mutations and all set them to the high height variant, a person will be extremely tall, like as tall as a tall building. You know, if you of course, which will never happen, but if you take all these variants that affect schizophrenia risk. they will, and you point them all in the same direction, uh, there will be extreme risk or extreme protection uh for schizophrenia. So for complex traits, ones underpinned by many mutations, all the variation already exists.

to move the population to a different adaptive set point that's optimal in the environment which it's in. So if you push the in uh population into a new environment within hundreds or thousands of years, the population can rapidly move to a new adaptive set point. There are some

unusual traits like ability to digest cow's milk or protection against sickle cell anemia that require a single very important mutation that may not yet exist in the population. And then you have to wait for the mutation to occur in some some people. And when the populations are relatively small, only 10,000 people, you might have to wait dozens or hundreds of generations for that mutation to arise.

But when the populations are large, uh, there's not mutation limiting anymore. Every mutation that can occur does occur. There's eight billion people in the world. There are maybe thirty new mutations every generation. So that's like what is it? It's like two hundred and forty billion new point mutations every generation. There's only three billion DNA bases in the genome. So every mutation that can occur does occur about a hundred times every generation. And we're not mutation limited anymore.

And so it's not like you have to that the mutations can arise again. They do arise again, but when the population's only 10,000, you have to wait dozens or hundreds of generations sometimes for the new mutation to occur.

So the the question you ask is maybe when the population is small, natural selection doesn't work effectively. So a common thing that people think about with natural selection, and that is true, is that in small populations, selection doesn't work effectively. Um, and that's because mutations bop around in frequency from generation to generation a lot in a small population, just randomly. So if you have a population of size one thousand.

populations, ver mutations will bop around by a frequency of one over a thousand every generation. And if the selection coefficient is less than that, it will be drowned in the random bopping around of frequencies due to genetic drift. But that is already for a population of 1000.1% selection coefficient is very weak. We're talking about 1% effects, and that's much very strong. It will work very well even in a population of a size a thousand or ten thousand.

If you are talking about mutations of the type that will start rising and some only in large populations, but not small populations. selection coefficients that are on the scale of one over 10,000 or one over 100,000. And those ones will take 10,000 or 100,000 generations to rise in frequency, which is hundreds of thousands or millions of years.

So that's not gonna do anything over the timescale we're talking about. There's just a timescale issue. So we're talking about strong measurable selection coefficients on the order of half a percent or more. in this study. And all of those are going to work in small populations or large populations. It's not going to be affected by the population size.

Does this suggest that nothing biological changed to make modern humans modern and some the thing that happened was some cultural change? How how do we understand what this data tells us?

And so the thought might be that there was gonna be have been uh some kind of genetic switch, a kind of uh important genetic change that uh was occurred in the population and that swept to high frequency and that everybody suddenly had, soon had, and that made it possible for do these th to do these things, maybe sp some genes that uh allowed people to have repr uh like complex language, representational language, for example. And so one thing that we did in 2016.

in this paper by Shat Malik and colleagues, uh, is we looked across the DNA for places that might be expected to look like this, that where all people living today, or nearly all people living today share a common ancestor, uh, maybe a hundred thousand or two hundred thousand years ago. And we looked really hard and right across all the DNA we could look at, we couldn't find anything more than four or five hundred, more recent than four or five hundred thousand years ago.

This is like a crazy result because uh it looks like there's no key selective sweep. that have occurred in this period that is ancestral to everyone living today. We talked before about no selective sweeps between Europeans and East Asians, but there don't even seem to be any selective sweeps. between like shared between all humans in this really important period when a lot of um evidence in the material culture record appears.

And so it could be that there's biological adaptation in this period, but it's polygenic. There's lots of mutations that all shift. In the same direction to help the population to move to a new set point, but there's no key biological change that rises to high frequency in this time.

But all of these groups today are able to do go to college, do everything everybody else does. And so there is like no evidence that there is any key mutation lacking in some groups that are not present in the others.

everybody in the world or almost everybody in the world, um, or the variance we see between different humans today was latent in this group and which which sort of seems And I get your point that, well, um, if you just stack up different

uh uh uh different uh different things across the genome, then stacking them up really ha has a big effect. But that um it's interesting that like we have so many different groups in the world today and that all that diversity It comes from a very small population size.

selection there's been uh in different human populations over time. One of the things this new work that we're involved in is doing is showing that at least in the last eighteen thousand years, 10,000 years, 5,000 years, In this part of the world, there actually has been significant movement, at least for a handful of important traits. We looked at more than 500 traits, about a hundred of them.

uh complex traits showed significant movement in uh systematic direction uh over this time period. So it really does seem that there is a response. uh to the environments people are living in that is occurred over this period and is potentially stronger than in previous periods.

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We were talking earlier how there's no fixed differences between um humans fifty thousand years ago and humans today. So if there's no genetic basis for uh the kind of thing that allowed humans to have more symbolic representation, have farming, et cetera. I think I asked you this question last time we talked, but especially with this context, why no farming before the ice age? Genetically we were there.

No farming develops uh before, you know, 12 or 11,000 years ago. It only f develops in the last, you know, 12,000 years, the period known as the Holocene, which is sort of the end of the ice age. And if you talk to climate scientists and archaeologists, you know, I keep asking people this question every time I meet someone who's an expert in this. It's like,

How can this be that farming develops in all these places? Are we really living in such an unusual time? And people tell me, indeed, we're living in an un very unusual time on a scale of two million years. That is, twelve thousand years ago we switched into this period of not just warmth, but climate stability. And that

I and that actually this is true. And it's sort of hard to believe that we're living in special such a special time. But if you look at, for example, uh data from the s bottoms of ponds where you can measure the fluctuations of temperatures using Isotopic signatures. Apparently we're in a period where it's just

fluctuating a lot less year to year and sees and ten years to ten years and hundred years to hundred years. And it's just a period of relative stability that we are miraculously living in. And that when this period of relatively stability happens, somehow the it follows that multiple groups independently turn to agriculture, even though the genetic complement

uh, you know, w all of whom have the same genetic complement that arises fifty thousand, hundred thousand, two hundred thousand, three hundred thousand years ago. It's kind of a crazy observation that people just accept. Unbelievable.

four hundred thousand years ago, this invention of Levallois technology, the ability to make stone tools out of course, and the Middle Stone Age Revolution or the Middle Paleolithic Revolution, depending on whether you what you call it in Africa or Eurasia. And this is a

revolution, a new way of making stone tools that's shared by Neanderthals and by modern humans, but is not shared in East or South Asia. Um, and it's a big change and it it involves a cognitive change, presumably, in order to make this

sort of technology. And then there's a further change to the Upper Paleolithic, later Stone Age, uh, maybe uh a hundred to fifty thousand years ago, uh, when there's the second transition where it's a new type of tool making, but not as revolutionary as the earlier one.

So when the cognitive leap happens is unclear. The diversification of the lineages leading to people living today like Khoisan Southern Africas and Rainforest Hunter Gatherers and uh that all occurs more on the timescale of three hundred thousand or two hundred thousand years. uh and all of these people are capable of, you know, going to college and doing everything. And so, you know, it's not obvious that all the toolkit, the cognitive toolkit, the behavioral toolkit, the genetic

abilities were not all in place two or three hundred thousand years ago, and that even Neanderthals had them, right? So it's not obvious that this was not the case. Yeah. And so, like I just don't know. You sort of distribute these people descended from this diversification that happens 200, 300,000 years ago to different parts of the world. And then bing, you know, after twelve thousand years ago, you start having agriculture popping up in different places.

It's kind of an outstanding mystery of human history. And, you know, I I find it unbelievable that we live in a play in a time period that climatologically is so unique on a scale of two million years. But my colleagues tell me it's true.

is like around seventy thousand years ago. And everybody accepts that these people all have in place the cognitive, behavioral, intellectual ingredients that are necessary for the farming revolution and state building state societies. Because when these descendants of these people get distributed to West Africa, to East Africa,

to the Americas, to Europe, to South Asia, to East Asia, to New Guinea, and so on. Their descendants all do this, like independently or semi-independently, or completely independently, or demonstrably, completely independently in all these different parts of the world.

So the cognitive resources for doing this must have all been in place, but it's a very long fuse, like it the delays for 40,000 years, for 70, so you know, 60,000 years in all these different places after the common ancestral population splits up.

five thousand BC with the Bronze Age,'cause like population wise, it doesn't seem like, you know, ten thousand BC to five thousand BC in the early Neolithic much is happening. It's is it possible that they had farming, but they didn't have copper, they didn't have tin, uh, which you needed to go to I guess the Middle East for to develop a civilization that could make use of bronze at a large scale and so they just disappeared from the historical record.

shared toolkit from then, but there's just a a fuse, a t a long fuse delay until all this stuff happens. Interesting. It's kind of like an amazing thing and we don't question it.

uh a skeleton for um since we last talked. There's now a s a foot a skull from a Denisovan that's been shown to be a Denisovan. Uh and we have data from lots of modern humans. Uh and there's really big mysteries about the relationships amongst these groups. So genetically,

the Denisovans and the uh Neanderthals are sisters. They descend from a common ancestral population five or six hundred thousand years ago. And that group's descends a couple hundred thousand years before uh seven or eight hundred thousand years ago from the common ancestors of modern humans.

And so genetically, the whole genome data says that Neanderthals and Denisovins are archaic humans from a common ancestral archaic population. But there are so many things shared between Neanderthals and modern humans that don't seem to be shared between with East Asians. Uh they both share uh Middle Stone Age stone tools, level WA technology, this uh cognitively unique type of way of making stone tools that wasn't used in East Asia. They both

have the same mitochondrial DNA and Y chromosome sequence. So the Y chromosome sequence of Neanderthals, the mitochondrial DNA of Neanderthals is actually modern human that came through interbreeding two or three hundred thousand years ago and then shot up to a hundred percent frequency.

And then Neanderthals and modern humans are both the product of mixture events that happened between archaic and modern humans three hundred or two hundred thousand years ago, demonstrably through patterns of variation in ancient and modern DNA. And so it feels that there's something shared between Neanderthals and modern humans that's not shared with Denisovans, even though the vote of the whole genome says that Denisovans and Neanderthals are related.

So one wonders whether there's something connecting kind of uh Neanderthals and modern humans that's different from Denisovins, even though genome-wide Denisovins and Neanderthals cluster. So I'm thinking about that all the time now.

in some ways and even though they get swamped by archaic genes, that somehow they're actually have more of a modern impact than one would think and that the Middle Stone Age and you know, middle Paleolithic revolution that they share with modern humans is actually more fundamentally a part of who they are in some sense than we think.

typical time they share a common ancestor is one or two million years ago. That's before the split from Neanderthals and Denisovans. So there's many places in your DNA where you're more closely related to a Neanderthal on your mother's side than you are to your father.

And that these two separate earlier, maybe 700 to 800,000 years ago, from the ancestors of modern humans, people like us. So that's the big result of a lot of studies since 2010. But there's also evidence of an interbreeding event that happened maybe 200 to 300,000 years ago. And that actually tur resulted in uh modern humans.

uh contributing DNA to the ancestors of Neanderthals. So this is maybe 5% of the DNA of Neanderthals comes from this interbreeding event, and a lot of studies have shown this. And so uh I'm very interested in this because uh actually from the archaeological record, Neanderthals and modern humans sort of look actually quite similar to each other, much more similar to each other than in s a lot of them do to Denisovans, these archaic humans in East Asia.

Uh so a lot of the history people have thought that Neanderthals are our sister, but in two but in 2010, the sequencing of the Denisovin genome made it very clear that on average Denisovins are closer to Neanderthals than to modern humans. So this was like a very confusing result. Um, and most people now think that Neanderthals and Denisovans are like descend from a common ancestral population, separated earlier from the ancestors of modern humans.

I'm interested in the possibility that actually the right way to think about Neanderthals is actually as somehow culturally modern humans. uh and uh even though that genetically they're mostly Denisovans and the model I'm thinking about is motivated by this archa archaeological phenomenon known as the Middle Stone Age Revolution. So if this is Africa, And this is, I don't know, Europe. Uh

I'm interested in the idea that this is something that's shared between African uh between modern humans and Neanderthal, and it's somehow some shared cultural feature that's absent in East Asia. And that might have a relationship in the genetic data and is somehow related to this five percent DNA.

So the idea I'm interested in is the possibility that there is a population here that invents the Middle Stone Age and the Middle Paleolithic, sometimes called Levalois technology, and that people from this population expand into Europe. And they mix with the local archaic humans who are there. And that is what this 5% interbreeding event is. It happens two to 300,000 years ago. And it produces a group that as it expands across this landscape in Europe.

uh mostly picks up the local DNA and becomes mostly archaic genetically, but retains its modern human culture, the way of making stone tools and some of its traditions. And so one of the things that's super interesting about this is that if you actually look at the genetics, uh, the whole genome, the Neanderthals and Denisovin's cluster. But if you look at the mitochondrial DNA, which people get from their moms and they get from their moms,

Neanderthals in modern humans cluster. So if you look at the mitochondrial DNA, Denisovins and modern humans share an ancestor well more than 700 or 800,000 years, as you expect from the history. And if you look at the wise chromosome that you get from your dad,

Denisovins and modern humans share an ancestor more than seven or eight hundred thousand years ago, which is uh consistent with this history. But if you look at the Neanderthal mitochondrial DNA, it's only three to four hundred fifty thousand years. If you look at the Y prosome, it's only three to four hundred fifty thousand years.

So what the current genetic work is asking us to believe is that even though this is only 5% of the whole genome, it reintroduces mitochondrial DNA and Y chromosomes and they jump up to 100% frequency. It's kind of a crazy claim because the probability of this occurring by chance is low, maybe five percent times five percent, so a very small number. And so it's sort of what we actually all believe.

Uh but it's sort of a very sort of surprising event. And somehow it's accreted all the findings in the whole literature so that we make ourselves believe this, but it seems sort of Unlikely on first principles that somehow only 5% will introduce both the Y chromosome and mitochondrial DNA. And it really looks like this. So there's this amazing data.

from this site in Spain that's like two to four hundred thousand years old. It's three to four hundred thousand years old at site called Cima de los Suezos. And they have a nuclear genome that looks Neanderthal-like, most of the genome, but their mitochondrial DNA microsome is Denisobin like. So it really looks like there was a population related to modern humans that pushed into this Cima de las Suasis like population, displaced

its mitochondrial DNA and Y chromosome, but kept the rest of its genome. So it really looked like something like this happened. So the idea that I'm sort of playing with, and you know, probably it's wrong, who knows, but is that there's a landscape This is maybe Europe and You can break it up into a hundred or so.

deems, little areas, and modern humans get introduced at the bottom right corner in the Middle East or something, and they spread into Europe. And as this population spreads, there's a wavefront of expansion and they're interacting with the local archaic humans.

And even if there's a small amount of interbreeding, the theory from lots of studies, simulations, and lots of studies of all these different species, like mammals and birds and so on, shows that there is Uh when there's even a little amount of interbreeding as there's an invasion or a movement of expansion of one group into the territory occupied by the other, there's massive integration of local genes.

that these pioneers at the wavefront, they'll sometimes interbreed with the local population. And there's so many of them around that their DNA will get swamped by the local group. So by the time they make it to the other side, they're largely local. And So maybe what we're seeing is that this is what's happened. You have like a modern human population that's matrilineal, for example, where transmission of making stone tools this way is happening from your mother to the kid. And

That's why they're retaining their mitochondrial DNA. But by the time they get to the other end of Europe, they're mostly archaic. They're mostly local archaic. So you'll end up with a 95% population replacement. So this would explain why the mitochondrial DNA is shared between Neanderthals and modern humans.

And it would exp also explain why the mixture proportion is only 5%. But like the really interesting thing is that actually there's other evidence from studies of modern humans that actually modern humans are two also admixed. And that the right way to think about this. Is that modern humans are a mixture of two groups, maybe like 1.5 million years ago, and that they come together two to 300,000 years ago with like 20%. 200 to 300,000 years ago, with maybe 20% ancestry from this archaic.

African group and 80% ancestry from this early modern lineage, and that the same group then mixes with.

It expands into archaic humans in Europe. It mixes with the local population. It gets 95% replaced, but still retains its cultural. Features and maybe some genetic features. And it expands in Africa too. And here it's not 95% replaced, it's only 20% replaced. And probably the reason that happens is that this group is much, much more diverged. It's arc much more archaic. It's 1.5 million years diverged rather than 700 to 800,000 years diverged.

And as a result, there's many more incompatibilities genetically, and there's much more barriers to gene flow, but there's still a lot, maybe 20%. And we have evidence that this is a big mixture that happens. And so what you're actually seeing is a modern human expansion, both into Europe.

And into Africa. In one place it forms Neanderthals, in one place as it forms the ancestors of everybody living today. But all of these groups are descended from this key sort of revolutionary event that happens here. So we often talk about the revolutionary events. fifty to a hundred thousand years ago, the more symbolic behavior and so on and so forth that sort of first appear in Africa and the Middle East and spread beyond. But there's also this earlier event.

And this event is sort of contemporaneous with the breakup of all the different groups also in Africa today. Uh, you know, the Khoisan Southern Africans and the Central African rainforest hunter gatherers. So one wonders whether this is an equally important formative event. And it also, if that's true, makes you think of Neanderthals as actually somehow our our cousins, that they're actually share our Y chromosome, they're share our mitochondrial DNA.

their share formation of this two or three hundred thousand year old event, their shared toolkit. So even though the genome is telling us that they're cousins of Neanderthal uh uh Denisovins, the the the the actual correct way to think about them may be in an important sense somehow the uh you know, relations or the close cousins of modern humans.

And multiple studies, there's at least three, maybe four or five studies that I've I know about, have looked at the patterns of variation in people today and say the data in modern people today, including in Africans, is not consistent with the homogeneous populations. It looks like a population that split well more than a million years ago, into multiple well at least two, but maybe many groups.

and then came together with an important coming together a few hundred thousand years ago. The papers have different models that they fit, but they all have this feature of a f more than a million years ago, there's a split up. And then on the order of a few hundred thousand years ago, there's a coming together and a remixture event forming the ancestors of anatomically modern humans.

And they mix with like local groups and who knows where they are, Southern Africa, Western Africa, Central Africa, Eastern Africa. We don't have any ancient DNA. But like, you know, this is a very rich environment. People have been living there for like seven million years at least.

And like there would have been different groups of people everywhere. Probably it's not just two groups, it's probably more groups. I think the important theme here is there's evidence of substructure that's well more than a million years ago. And this place would have been a landscape full of archaic humans that would have been differently, you know, related to these expanding people and would and would have admixed with them when they came through.

the most Yamnaya ancestry you see in India is twenty percent or ten you know, most people have less than ten percent or five percent. I see. It's you know, there's just been a lot of mixture on the way, but it is the tracer die. Right. Like it tracks Indo-European languages and important aspects of Indo-European culture are coming through Yamnaya. So if you know where to look, that tracer die is only 10%, it's only 5%, it's only 2% in some groups.

but it's the languages people speak and it's important cultural shared elements that connect them to people on the other side of the Indo-European speaking world. So this five percent you s you shouldn't sneeze at it, right? Like that's tracing something important in this model.

So I'm very interested in patterns that would explain this. If you invoke and assume that there was like a matrilineal or a patrilineal expansion. Um, it could be either, uh, where it modern humans, when they were expanded in across the landscape of Europe. uh retain their identity along one of the lines. Like if you incorporate a local, if it's if it's matrilineal, when they incorporate a male from the local community, they're brought into the community and the kids are raised.

by based on the culture of the mothers or something, or or if it's a patrilineal expansion and they incorporate a female from the community, it's incorporated, sort of raised with the culture of the fathers. So if that happens, it guarantees one of these two parts of the genome to look like it does. Because It's a modern human expansion. If it's patrilineal, it will retain the Y chromosome. If it's matrilineal, it will retain the mitochondrial DNA. So it will solve one of your two problems.

Solve the other one, so you need to solve the other one. Uh, so the other one you can solve either by natural selection or you can solve it by social selection. So uh in So by the way, patrilineality and matrilineality are the rule, not the exception in human communities. Usually communities sort of follow cont have continuity along the male or the female line. Um and you usually it's patrilineality, sometimes it's matrilineality. Um so

You can also have phenomena like social selection. So uh so it could be that once you have kids of someone who is from uh the uh whose father, for example, is from the outside community, that those the male c usually in most communities, uh females all reproduce. Like that's typical today. Like usually women have kids if they can. But men in traditional societies are actually very variable in their reproductive success. A large fraction of men never have kids.

uh and then there's a relatively smaller number of there's a a subset of men have many kids yeah with many women. Um and so there's competition among men for kids. So in this context where males are competing for access to females.

then female mate choice begins to be an important process. And uh you have a phenomenon where uh It could be the case that like the if you are your dad is an archaic male, then you're not going to be as successful in the competition for local females if your dad is a non-archaic male.

So a some simple social phenomenon like that could explain the data. And we actually see this in human societies. So for example, If I remember right, like in Central African rainforest hunter-gatherers, there's different treatment of boys and girls depending on whether their dad or mom is one group or the other.

With me earlier. That's two populations 70,000 years separated. There's no biological incompatibilities between West Africans and Europeans. There's no natural selection against biological incompatibilities. So we know with when the Androthals and modern humans met in Mix. Uh there were there were biological incompatibilities. That was at 700,000 years ago.

Um, and so there's as populations become more apart, there begins to be biological incompatibilities rapidly developing, probably as the square of the distance separation, because you need pairs of interacting genes and therefore it's the square of the separation. Uh so here it would have been maybe only 400,000 years separated between this lineage and this line.

Here, it's like 1.2 million years. It's a lot. So these are at the edge of not being able to produce children. So this is quite different humans. These are actually three times closer than these. Yeah. You know, and like if you look at mixtures of humans today, there are mixtures in Southern Africa today or people who are half this distance. Yeah. Right? Like Ko you know, if you look at Khoisan and Bantu people mixing in Southern Africa, like Rakosa.

which is the answer you know, the population of, for example, Nelson Manavella. This is groups that are separated by almost two hundred thousand years, which is half of this. Totally incompatible compatible. And so Like what you're seeing is this is a group that's actually completely permeable genetically or nearly completely permeable. This this one is almost certainly has substantial biological incompatibilities because

Three hundred thousand years later, two or three hundred thousand years later, we see the interbreeding between Neanderthals and modern humans or between Denisophones and modern humans. There's clear evidence of incompatibility at that point. But this would be even bigger. So what you would expect to see is that as this group spread, they would be moving into a territory full of archaic humans and there would be some interbreeding, but the kids would be not very fit, they would die off.

There would be a lot of infert infertility. And so the barriers to gene flow or the of of and to interbreeding would be greater. So to me, it's not at all surprising that as this group moves into Eurasia, here's Eurasian archaics. you know, the ancestors of d Denisobans. You know, and these are only four hundred thousand years diverged from these people over here. And here's African archaic.

And these are like 1.2 million years diverge. So, you know, they just don't interbreed as much. And so you don't get as much uh much much much gene flow. But the key thing is at the same time. It's the same time. So like it really feels like the signature of an explosion of people from one place interacting with people here, interacting with people here. It's the same sort of sort of cultural revolution or technological revolution impacting this place, impacting this place.

And creating populations that are kind of both impacted by this cultural revolution, which we know is the case because this they share the same toolkit. Um and so, you know, some people argue that level law technology is independently invented, but this would be a

sort of but you know it's very similar and uh this would be a way that it would have the same origin. Interesting. And sort of so there's a cultural shared thread, this shared tool toolkit. There's a mitochondrial DNA Y chromosome th thread, which is and then there is a a timing sort of shared thread, which is they both form by mixture.

Other ones I didn't even talk about, like super divergent lineage filling into Denisovans and like all this other stuff. And we still say, oh, the whole genome says Neanderthals and Denisovans are sisters, so that's the truth.

uh and we've like patched it all together and gotten it all to work. And oh you look at the mitochondrial DNA in the Y chromosome and they have this odd pattern and it's improbable, but we can get that to work if we invoke natural selection, you know, things like this. So so You patch it all together, you make these it's a little reminds one of uh

sort of what happened in the ancient world where uh there was this idea that the uh sun revolves around the earth. But it doesn't quite explain the movements of the planets properly. And so in order to get the movements of the planets to work right, uh, you know, the Ptolemyan astronomers would have m made up these uh epicycles, these special like extra rotations and movements to make everything work about right. Uh and it was a such a convoluted model and then when Copernicus

uh and colleagues suggested instead that actually what's happening is everything's a revolving around the sun that is simplified things and made things ever so much simpler. So what w the situation that was happening is that that as as sort of as astronomical information accumulated, it kept being contradictory to the standard model, but it could be made to work by proposing another complication and another complication and another complication.

But you know, this is not like as like fantastic as, you know, proposing that everything revolves around the sun rather than the earth, but it is much simpler. Uh, and actually it explains many, many things.

The only possible explanation is that the stars are so far away that it is just incomprehensible and implausible. And so the heliocentric theory was dismissed. And the reason I what I'm gonna try and ask is what is the equivalent of like, oh, for this to work, the stars had to be so far away that it's inconceivable. Where like actually the stars are so far away. And maybe we should adopt the the the implausible implication that this theory gives us.

extensive, now extensive work on modern human substructure with the now extensive work based on ancient DNA of archaic human relationships to modern humans. And if you put them together, you realize they line up in terms of their time. uh of substructuring. So I think that I don't know if that's improbable. It seems actually parsimonious to me. But yeah.

So if if that's what happens and you have a mutation that occurs in the Caucasus or, you know, somewhere in the Middle East or Northeast Africa, and there's key genetic mutations that make people able to do this, and then this population expands. You know, when it moves into Europe, it's swamped by local genes, but there could be retention of those genes bec through selection as it expands.

So maybe what you're actually seeing is that actually there are genetic developments. Most of the discussion on this, I point, has been focused on the 50 to 100,000 year event. uh and this is like anatomically modern human behavior. But this is like a lot of my archaeologists think this is an equally, if not more profoundly significant event in many ways. And why is that not the event that we should be talking about?

Um, so that is where you start seeing uh evidence for possible fixed differences. What's basically happening if everybody shares a common ancestor four hundred thousand, five hundred thousand years ago is there's a single ancestor at that time. And if you compared it to another population, like

But anatomically modern humans appear at this time. And actually recognizable Neanderthals appear roughly around this time too.

a quickening of sort of, you know, behavioral sort of traits, you know, which could be not genetic at all or it could be genetic, like, you know, there was there's lots of arguments about this. Uh, but you know, people are obsessed with You know, like we were obsessed with intelligence in the earlier in our conversation, but people are obsessed with art and, you know, these things that seem important to us. But like who knows what's important? Yeah. Um and yeah.

The work that I've been involved in has consistently shown that I was wrong in my biases coming into the work. And I've really been almost traumatized by this. Like again and again I've come into a project with some kind of guess about what the data was showing. And then the data doesn't show that. So for example, when I got involved in the Neanderthal Genome Project, helping to analyze data, looking at how archaic Neanderthals were related to modern humans.

I was part of a group of scientists who had established that non-Africans were a simple subset of African variation and that there was no evidence at all. of Neanderthal interbreeding into the ancestors of modern humans or other archaic interbreeding. different analyses that I and and very much more other people had done made it look like non-Africans variation was just a subset, a small sample of that in Africa. And that could have fully explained the data.

And so that when I was involved in analyzing the Neanderthal DNA sequences, What happened was I found this very strong evidence of Neanderthals being more closely related to non-Africans than to Africans. And it was very surprising. And I thought it must be a mistake. I thought it was I was quite incredulous. I thought it was unlikely to be true. because other evidence that had been uh c that had been found before

seemed to point in the other direction. And so I spent several years trying to make these results go away, as did my colleagues. And we just couldn't make the results go away. They just kept getting stronger. And this experience working on natural selection was the same. So what we had felt here was that what we were convinced of was that natural selection had been pretty quiescent in our species over the last several hundred thousand years. Therefore, if we look at patterns of variation.

in non-African people today, uh or in any people today, we should see not a lot of selection going on. And indeed, the first ancient DNA studies, beginning in 2015 with this paper that we were involved in with Ian Matheson and colleagues, Indeed, these papers seem to show relatively small numbers of genetic positions associated with natural selection. So in 2015, we analyzed data from about 200 Europeans and Middle Easterners to try to understand frequency changes over time.

And we compared those ancient people who were the sources of modern Europeans. to people in Europe today. And we looked at frequency differences that were too extreme to be due to chance. And we were very excited to find 12 positions that we were convinced were highly different in frequency between Europeans today and what we would expect based on the history that that that we had we and others had identified was the history relating modern to ancient Europeans.

And so some of these were known and some of these were not known. And this was very exciting. And we hoped that as the numbers of samples would increase and we would get higher resolution to be able to appreciate differences in frequencies over time, we hoped

that this would make it possible to detect far more. And what was quite disappointing over the subsequent decade is that that didn't happen. So for example, the largest study of that type in 2024 by a group in Copenhagen, analyzed the data, much better data than we had in 2015, and found only 21 positions that were highly different in frequency across time.

And while that was exciting, it was almost twice as many as we had found in twenty fifteen. In a lot of ways it was disappointing because the sample size and data quality had gone up so much, and yet this is all that was found.

And so what that suggested is that we might be hitting an asymptote and we might not be able to get beyond where we currently were, and that this approach to learning about biology, sort of which would be v w was very promising in theory, might actually not produce a high yield. That maybe in fact Natural selection was quiescent. And in fact, what the reason we're seeing so few changes.

is that actually there's not been a lot of adaptive directional selection. So that was the situation we found ourselves in until just a a a few years ago when we carried out this study in our research group led by Ali Akbari. So so what we did is we uh deployed a few uh innovations or change uh to try to improve our power to detect.

uh natural selection. One of them is we just pumped a lot of data into the system. And so we increased the amount of data by about 14 fold. And the main thing that we do in this study is we report data study from about 10,000 individuals with new data. So this is like a very big increase in the amount of data in the literature and the total data set size of ancient individuals distributed over the last 18,000 years.

is about 16,000 people. So this is a large data set. It's much larger than was previously possible. And when you have more data, you can estimate frequency changes with much more subtlety. And the data comes from only one part of the world, which is Europe in the Middle East. Uh it's not a more important part of the world than other places, but it's the place where maybe 70 or 80% of the data in the ancient DNA literature so far comes from due to historical reasons.

And it provides us with a natural laboratory where we can see what happens over one place over time as environments change to the genome. It's really interesting to imagine doing this type of analysis in other parts of the world. And the comparative analyses are super important and interesting. But this study right now is about this one place in the world where we have particularly fantastic data. The other thing we did is we developed an entirely new methodology that hadn't been used in this.

area before. And the methodology is based on a technique that had been developed for finding risk factors for disease. um in uh uh in in in medical studies. Uh and uh a simple way to explain it is we ask how to predict the genetic type a person has. based on its pattern of relatedness to other people. So we'll have a data set of about 16,000 ancient people and 22,000 people if we include the ancient and modern people.

And then we look at how closely related each of these 22,000 people are to each other, and we predict the genetic type at each position in the DNA at 10 million positions based on the pattern of relatedness to all of the other 22,000 people. And then we ask if if natural selection blowing the frequency of the mutation in the same direction in all geographic places and at all times.

predicts the data a little bit better than just knowing the relatedness to all the other samples in the database. So we're simply asking the alternative hypothesis is that selection has been blowing in the same direction at all times. And we simply ask if that explains the data better.

And that's a s a dumb assumption, uh, because of course the truth is that natural selection is going to have changed in frequency over time, but we're just asking the simplest of questions, whether assuming a constant rate of selection explains the data more than not doing so.

And uh then you have the separate thing, which is like, okay, if we look at specific locations. Can we just say that, oh, this location has been selected at whatever coefficient over time? Um, and if we add some coefficient, it does it become easier to predict.

the allele frequency changes than you would have just seen from this other artifact, which is only predicted which is just looking at like, oh, if you look at the whole genome, are these guys in the same, you know, are they have they gone through the same bottlenecks? Have they gone through the same drift, et cetera.

Now there's a bit of a statistical problem in figuring out how many there are because they're so densely packed that they're close to each other and they're interfering with each other. But when you try to piece them out and say, let's look at let's count them only one in each place in the DNA and blank blank out the others, we find at least about 479 positions that are all independently pushing in the same way.

uh those positions are 99% confident that they're real. By another criteria of more than 50% confident that they're real, we think that about 3,800 positions are all pushing in the same direction. So this is like a crazy number of results.

given that in our work previously and other people's at work, there were at most a couple of dozen discoveries coming from a single scan. So when we got this result, we were very surprised. We were thought it must be wrong. And we spent the next couple of years trying to make the results go away, but they just got kept getting stronger. And so what we were trying to do is to look for some kind of independent type of evidence to tell us whether these positions were real.

And we stumbled on something really ic uh powerful for this purpose that had not been used in this way before. And it relied on the fact that we had very large numbers of discoveries, like many hundreds of discoveries or even thousands. Uh and so what we did is we took a completely independent data set, which was the

corpus of genome-wide association studies. So these are studies that people have carried out in hundreds of thousands of people looking for whether particular genetic mutations are more common in people with high blood pressure with than with low blood blood pressure or something like this. So we took the UK Biobank, which is about five hundred thousand people.

from Great Britain, who have been measured for hundreds and hundreds of traits. The whole genomes of all these peoples have been sequenced. And for each of these traits, we could look whether each of these ten million positions are connected to this trait in some way in a convincing way.

So in ten million positions, about fifteen percent, about one point five million p positions in the DNA are predictive of at least one of these several hundred traits. So then we could ask a question, f is our natural selection signal, our statistics, Is it related to whether a ver a mutation causes a high blood pressure or some other trait? So we slid our statistic for natural selection from upward, you know, to a value of one, a value of two, a value of three, a value of four, a value of five.

And as we did that, the enrichment for genetic mutations that affect traits got higher and higher. So whereas it was only 15% when we didn't use our selection statistic, when we uh required the selection statistic to be above about five. uh there was about a fivefold enrichment for mutations that cause traits.

validate and show that these interpretations made sense using computer simulations of our process. Our interpretation of this result is that once you slide the statistic above five, essentially all the signals of natural selection are real.

Um and independently, you know, we run these studies on modern populations where we say, if you look at height or eye color, intelligence, whatever trait, what are the parts of the genome that are correlated with that trait? And the higher statistic you give it uh in your study in order to explain the low frequency changes over time as a result of selection, the more probable it is that that region in the genome is associated with traits.

uh that have like some functional thing that we can measure.

traits, uh measured in a completely different way to read off the probability mutations are real. So we can ask how much enrichment for real signal is there given a particular selection statistic. And if it's halfway enriched to the plateau,

the correct interpretation of that we're able to show is that fifty percent of the mutations are are are really selected. If it's three quarters of the way toward the plateau, there's a three quarters probability that the mutation is real. If there's a ninety nine percent of the way to the plateau, There's a 99% probability that's real. So that gives us a calibrated estimate of the probability that a particular position is really under natural selection.

A a major concern here is that actually what we're seeing is not that these mutations are really under selection, but rather that both association to a disease. and uh our selection signal are due to some third thing that's causing both of them, which is a type of selection, which is not what we're after, not selection to adapt to new environments, but

what's called background selection, selection against newly arising bad mutations that are removed from the population that tend to be concentrated in genes. Genes are also the parts of the genome that tend to be associated to traits. And so this common process is causing both the enrichment for trait signals.

and is also causing the enrichment for selection signals that we're observing. That's the concern. We were super concerned about this. So what we did is we repeated this enrichment analysis. in slices of the DNA that all were affected to the same extent. by background selection, by this rain of slightly bad mutations, and we get exactly the same pattern. We also repeated this experiment in just using mutations of the same frequencies.

uh uh because there's different statistical power to detect these signals at different frequencies. And we see the same pattern where above a value of the selection statistic of around five, we get this plateau.

Uh another change has been in solution enrichment. So it's been this way of taking a sample that has very small percentages of human DNA, but then suddenly creating a a pro a process that will mean that the great majority of the sequences that one's analyzing will be

useful for analyses. And so the approach that we used was we took the DNA samples that we had, most of which were very low percentages of human DNA, less than ten percent, often less than one percent, which is such a low proportion that it's prohibitively expensive to sequence them into just brute force sequencing them given the technology that we had available at the time. And so we took these uh samples and washed them over a artificially synthesized set of

short DNA fragments that targeted positions of the DNA that we were interested in analyzing. So this is more than a million positions that are highly variable in people. And we picked many of these to be biologically interesting. We had a whole set of known

biological targets that affected traits in genome-wide association studies, which is the way that people look to see if there's particular genetic variants in modern people that cause uh that have particular impacts and p phenotypes and traits. And so what we did is we uh had this artificially synthesized set of uh uh DNA fragments that we washed our ancient sample over and it bound the parts of the DNA that we targeted.

And the resulting sequence that we generated was very enriched for the parts of the genome that were informative about history. And even though only ten percent or one percent of the DNA was human, it ended up that a very large fraction was from the parts of the genome that we were interested in, and it became economically efficient to do

Uh sometimes the microbial sequence is very interesting. So it might be pathogens that that that that a person died of. So there's for example, uh amazing amazing work uh about for ex different plagues of malaria and black death and hepatitis B and so on that have been obtained from the sequences of these pathogens in people's teeth and other parts of their body when they died.

Um, but we're focusing here on the human DNA. And uh so what we did is we uh this changed the amount of data that was possible to produce from tens per year to hundreds per year, and then we further and roboticized and industrialized the process.

so that there were many hundreds or even thousands per year. And so just in our laboratory, we've been generating genome scale data from uh more than five thousand individuals per year. I know this is true also of several other laboratories in the world now. And this huge jump in data, this sort of semi-exponential or even super exponential jump in some cases, has made it possible to ask and answer questions. So while the f we're there were only on the order of 10 genome sequences.

uh from humans uh in 2010. There this year it was passed more than 20,000 reported sequences. So there's several orders of magnitude increase. And the questions we were able to ask in twenty fourteen are just not the same as the ones we can ask today.