David Reich – Bronze Age shock, the Neanderthal puzzle, & the sudden spread of farming

1. 0:00 – 16:24

   Ancient DNA suggests strong selection over last 10,000 years

   1. DRDavid Reich0:00

      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. 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, which is surprising 'cause 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 these events that happened five thousand years ago.

   2. DPDwarkesh Patel0:38

      I am back with David Reich, who is a professor of ancient DNA at Harvard. How do you describe what it is that you, um, you study?

   3. DRDavid Reich0:47

      I'm a geneticist.

   4. DPDwarkesh Patel0:48

      All right.

   5. DRDavid Reich0:48

      And I work on human history and how people, uh, relate, uh, ancient people relate to each other and people living today.

   6. DPDwarkesh Patel0:56

      Great. Um, and so we did an interview, uh, was it two years ago at this point? Which, um, ended up being one of the most popular interviews I've ever done. I think people just found really compelling that there's so much about human history we don't know and are just learning about now as a result of the kinds of techniques that your lab is using. And, um, you have a new preprint, 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?

   7. DRDavid Reich1:24

      Well, well, the dream was that when this field started, this ancient DNA field started, uh, more than sixteen or seventeen years ago, that we were gonna learn a lot about biology, learn about how people's biology changed over time by getting DNA out of ancient human remains and tracking changes over time. 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 archeology. 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-great-grandparents, and so on. And going back in time, thousands, tens of thousands, even hundreds of thousands of ancestors going back in time contributing 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 wanna 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.

   8. DPDwarkesh Patel3:51

      And c- can, can I ask a question? Um, I'll be asking a lot of naive questions through the next few hours. But why are frequency changes especially interesting?

   9. DRDavid Reich3:59

      So what we're interested in is using the experiment of nature that's occurred, uh, in, in our history over the last tens of thousands of years to understand what's, uh, biologically, uh, significant, uh, in our, in our DNA. And if there has been a change in environment that a, a population has experienced, for example, people have shifted to agriculture or begun living close to domesticated animals or moved to a new environment from a cold place to a warm place or a, a low place to a high place, 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, and that will tell us that there have been pushes in the, against the biology as a result of the changes in environment that people have experienced.

   10. DPDwarkesh Patel5:18

       Interesting. Okay. So what did you guys find?

   11. DRDavid Reich5:20

       So seven years ago, uh, Ali Akbari, uh, who is a, uh, at the time, was a postdoctoral scientist in my laboratory, and a few years later became a permanent staff scientist in my laboratory, set out to use the data that we were producing to learn about biological change over time. And I think the reason he was interested in our 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, uh, 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 thousands 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 s- in frequency between Europeans and East Asians. So Europeans and East Asians descend from a common ancestral population 40,000 or 50,000 years ago that came out of Africa and 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 40,000 or 50,000 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 would be some mutation that would've rocketed up to very high frequency. And 40,000 or 50,000 years is a lot of time. It's maybe 1,500 or 2,000 generations. And so that might be enough time easily to see 100% different in frequency, and yet you don't see any more compared to what you would 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 r- help the population get to a, um, 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 in frequencies of, of, of all the mutations that we're seeing in the DNA, we're looking at about 10 m- 10 million positions that vary, is due to directional selection adaptation versus other factors, especially genetic drift. Uh, and 98% of it is other factors, especially genetic drift. So it's overwhelmingly migrations and population structure causing fluctuations in 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.

   12. DPDwarkesh Patel9:15

       Can I, can I ask a clarifying question here? So why are we discounting population admixture or replacement as selection? Because if you think about it at a group level, if one population replaces another population, isn't that selection? I f- I, I remember from the last episode you were explaining how there's been huge changes in what kinds of people are in a specific area. 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 10,000 years?

   13. DRDavid Reich9:51

       It, it could count, uh, and may count, and probably should count in some respects. But it, it could also be that this population replacement is due to some cultural phenomenon, uh, technology held by one of these groups-

   14. DPDwarkesh Patel10:05

       Yeah

   15. DRDavid Reich10:05

       ... not others, and maybe there's some genetic mutations that are contributing to this. Who knows? It's possible. Uh, but what you're seeing is a whole genome shift. And so what we're looking to see is whether there's one place in the DNA that is driving the change-

   16. DPDwarkesh Patel10:19

       Mm

   17. DRDavid Reich10:19

       ... 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 in 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 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.

   18. DPDwarkesh Patel10:46

       Yeah.

   19. DRDavid Reich10:47

       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.

   20. DPDwarkesh Patel11:19

       [laughs]

   21. DRDavid Reich11:19

       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 steppe migration from the steppe north of the Black and Caspian Sea. 40%, 50%, 80% of the DNA becomes Yamnaya from steppe pastoralists, 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.

   22. DPDwarkesh Patel11:52

       Yeah.

   23. DRDavid Reich11:52

       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?

   24. DPDwarkesh Patel11:59

       Okay, in this next section, David explains the nitty-gritty of the methodology of this paper. It's honestly a bit technical, and I wanted you to get a sense of the results first, so I've moved that section to the end. If you wanna understand the methodology, just stick around for the full episode. Okay, you found these locations that seem to be under selection. Oh, a- a- another clarifying question. So you haveYou say thirty-eight hundred locations which you're fifty percent confident are-- have been under selection in the last ten thousand years.

   25. DRDavid Reich12:29

       Seventy-two hundred, which we're, we're, we're fifty percent confident.

   26. DPDwarkesh Patel12:31

       Oh, sorry.

   27. DRDavid Reich12:32

       So I think we're getting about seventy-two hundred positions in the DNA that have fifty percent confidence of being real.

   28. DPDwarkesh Patel12:38

       Yeah.

   29. DRDavid Reich12:39

       So only half of those are real.

   30. DPDwarkesh Patel12:41

       Uh, I see. Okay.
2. 16:24 – 35:40

   Natural selection intensified during the Bronze Age

   1. DRDavid Reich16:24

      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, w- 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 Asians.

   2. DPDwarkesh Patel16:49

      Yeah.

   3. DRDavid Reich16:49

      So now we're seeing hundreds of positions that are rocketing up in frequency with s-selection rates one percent or more in a lot of cases. So one percent or more selection rates will mean that there'll be a rapid doubling over periods of dozens of generations, and so over fifteen hundred, two thousand generations like you see separating Europeans and East Asians, shouldn't you see many f- genetic variants that are a hundred percent 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, with 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 and the culture. So this is aPopulation 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 11,000 or 12,000 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 pop-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, uh, needs of this population. So it's not surprising, perhaps, that in the context of these dramatic changes, the biology of the population might be not in the i-ideally adapted, uh, position. That is that there might be what some people call an evolutionary mismatch, where you take a, 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 of 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.

   4. DPDwarkesh Patel19:40

      Interesting. Okay, so it might be helpful to... You, you, uh, in the paper, you have, you, you have many examples of, um, this intensification of selection around the Bronze Age, and so, um, feel free to navigate it yourself. But it might be helpful to go through some of these-

   5. DRDavid Reich19:54

      Sure

   6. DPDwarkesh Patel19:55

      ... specific examples.

   7. DRDavid Reich19:56

      So we look-- One of the things we do in this work is we look carefully at many, many of these positions in the, in, in the DNA. We've-- actually have an internet browser that you could look at called the Ages Browser that Ali and a colleague of his, who's a co-author of our paper, built, uh, that allows you to query these, each of these ten million positions and see the trajectories at each, at each position and the evidence for selection. 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-

   8. DPDwarkesh Patel20:31

      Mm

   9. DRDavid Reich20:31

      ... or a radical change in natural selection. And very often that occurs in the period between 5,000 to 2,000 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 TIC2, 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 three thousand 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 op-opposite direction. That's speculative.

   10. DPDwarkesh Patel21:52

       Oh, interesting. And, uh, the thing it was protecting against was probably another disease?

   11. DRDavid Reich21:56

       Maybe.

   12. DPDwarkesh Patel21:58

       Prepping for this episode required a full lit review. I needed to understand why other methods had failed to find evidence of natural selection over the last ten thousand years. What exactly did Reich and Akbari do differently? Honestly, this was quite subtle because the most important points were distributed across a bunch of different papers. And it was frustrating to talk to LLMs about it because they kept getting confused. One of them would fail to understand an important crux, and so I'd switch 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/dwarkesh 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 trait after trait, 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-lactose would matter, lactase 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 w-was it, uh, FADS1?

   13. DRDavid Reich23:50

       Yeah.

   14. DPDwarkesh Patel23:50

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

   15. DRDavid Reich24:19

       Right. So FADS, FADS1:2, this variant is sort of a vegetarian/meateating ad- ad- adaptation.

   16. DPDwarkesh Patel24:27

       Yeah.

   17. DRDavid Reich24:27

       And already in work prior to this, actually Ian Mathieson, who, uh, w- was a former, uh, colleague, uh, w- worked with me in 2015, identified this as a very strongly selected variant, and it's actually been ancient. You see, uh, copies in archaic humans too.

   18. DPDwarkesh Patel24:42

       Mm-hmm.

   19. DRDavid Reich24:42

       Um, one of the findings of our paper is the ABO blood system. You know, you get your blood typed as A, B, and O. The B variant has increased up to 10% 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.

   20. DPDwarkesh Patel24:57

       Mm-hmm.

   21. DRDavid Reich24:58

       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 TIC2 variant for, uh, tuberculosis risk, uh, multiple sclerosis risk variant inflected and increased in frequency before the Bronze Age, and then 2,000 or 3,000 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. Um, 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-

   22. DPDwarkesh Patel25:54

       Mm

   23. DRDavid Reich25:54

       ... 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- 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 gonna be starting to grow plants-

   24. DPDwarkesh Patel26:24

       Yeah

   25. DRDavid Reich26:24

       ... and maybe farm animals. That happens in the Neolithic, you know, beginning 10 or 11 or 12,000 years ago. It spreads into Europe after 8,500 years ago. But actually the intensification happens like 5,000 years ago, 4,000 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 may be 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, 'cause 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 5,000 years ago.

   26. DPDwarkesh Patel27:24

       So you did some work with, uh, Batya and many other colleagues in 2014. You were looking at 20,000 or 30,000 African American genomes today, and you were saying, look, there's some percentage, 80% West African DNA and then 20% European DNA, and can we look at their, uh, genomes today, and do we see that their, uh, allele frequencies are much different than what you'd, you'd 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 200, 300 years of extremely intense environment change, you know, going from, uh, you know, y- 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, or the change in environment is even stronger than what we see from Africans in Africa then being trans- migrated to the, uh, uh, to the New World and then living under slavery.

   27. DRDavid Reich28:30

       That, that may be the case. It also may be the case that that period is just too s- short to see much effect.

   28. DPDwarkesh Patel28:35

       Mm-hmm.

   29. DRDavid Reich28:36

       So what you're looking in for in the Batya et al paper, uh, where we looked at about 30,000 African Americans and looked to see whether there is, instead of the average percentage of maybe around 80% West African ancestry, in some places in the DNA more than 80%, in some places in the DNA less than 80%, significantly, as you would expect if there was natural selection from some r- genetic variant for Eur- 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.

   30. DPDwarkesh Patel29:05

       Hmm.
3. 35:40 – 58:00

   Why didn't evolution max out intelligence?

   1. DPDwarkesh Patel35:40

      Yeah. So there's this, uh, a person who has this theory of collective intelligence hypothesis, which is this idea that, um, the selection forIntelligence has actually been in the opposite direction, that as society has developed, there's been more specialization. If there's more specialization, each person only needs to understand a smaller and smaller 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 elect- a selection in the last 2,000 years as so- 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 Henrich's book, the amount of information that they needed to ha- ha- hold onto 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.

   2. DRDavid Reich36:48

      [laughs]

   3. DPDwarkesh Patel36:48

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

   4. DRDavid Reich37:02

      Right. So, you know, this is the power of data, right? Like, you know, the... I think Joe, if you asked him, uh, prior to this work, uh, what the hunter-gatherer selection would be and where their set point for, uh, you know, this particular trait would've been, you know, I think he probably wouldn't have made a very strong prediction. But he would've said, "Well, maybe you would've expected it to have a high predicted value of this trait because these people were really having to do a lot of things and figure st- a lot of stuff out maybe. Uh, and that maybe once you have more complex societies, there'd be more of a collective brain, and maybe there'll be selection against this trait." And in st- 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.

   5. DPDwarkesh Patel37:56

      Yeah.

   6. DRDavid Reich37:56

      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 pre- genetic predictor of years of schooling, there's another amazing study from 2017 from a group in Iceland, uh, that looked at this measure over the last 100 years in Iceland, and it looked at older people, and it looked at younger people, people born more recently in Iceland. And there's a estimated 0.1 standard deviation decrease in genetic predictor of intelligence in Iceland just within one century. Uh, it's an absolutely huge effect-

   7. DPDwarkesh Patel38:27

      Yeah

   8. DRDavid Reich38:27

      ... over a short period. Uh, and this is selection against years of schooling. If, if I said intelligence, I didn't mean to. It's 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 c- 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.

   9. DPDwarkesh Patel39:12

      Mm.

   10. DRDavid Reich39:12

       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 delaying 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?

   11. DPDwarkesh Patel39:39

       Yeah. Um, okay, so obviously a trait like years of schooling was not itself a meaningful thing in the past. Um, and the underlying things for it seem to have been under strong selection. So whatever in the genome predicts years of schooling seems to have been under strong selection. Um, and how, how should we think about this? What, like, what is the actual thing that's changing in the genome?

   12. DRDavid Reich40:00

       Yeah. Well, I think that there's two things going on that you need to think about. So one of them is that, uh, is that years of schooling is connected to so many other things genetically. So if you look at the genetic predictor of years of schooling, th- this trait has been measured in millions of people now. It's actually correlated to really, really surprising things. It's correlated to the age at which women have their first kid.

   13. DPDwarkesh Patel40:23

       Mm.

   14. DRDavid Reich40:23

       It's correlated to people's 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 sc- 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 may 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 to, 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 at, for a study where this measurement of the numbers of years of school was done not in Europeans.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 ten thousand 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 of five or six standard deviation correlation between the effect size of variance, a number of years of school in China today, and the trajectory in Europe just as strong actually-

   15. DPDwarkesh Patel42:28

       Mm

   16. DRDavid Reich42:28

       ... 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-- at predicting more years of schooling.

   17. DPDwarkesh Patel42:52

       Okay, just to make sure I understood, you're saying you're, um, you know, you're, you're looking at this ancient DNA in Europe, and you're saying, well, it seems to predict years of schooling for modern people in Europe, um, or at least a selection on those, uh, ancient DNA... That ancient DNA seems to predict more years of schooling in modern Europe. And then you also find, well, it also predicts how the same, um, variants predict more years of schooling for Chinese people in China.

   18. DRDavid Reich43:22

       Yeah.

   19. DPDwarkesh Patel43:23

       And so this is not just some weird artifact from the way these GWAS 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.

   20. DRDavid Reich43:37

       Correct.

   21. DPDwarkesh Patel43:38

       Jane Street is pretty secretive, but I did learn about one internal mechanism which illustrates how high trust and weird their culture is. Researchers aren't given compute allocations. Instead, Jane Streeters use an internal currency called hive bucks to bid for compute in real-time auctions. Everybody can spend as many hive bucks as they want, but your hive buck bid is meant to represent the real dollar value of the experiment that you wanna run. Now, notably during the auction, anybody can change anybody else's bid, and after the auction, people can even kill each other's jobs. People just trust each other to do this in a way that benefits the whole firm. As a result, Jane Street's allocations reflect a near real-time consensus on the highest priority uses of compute. As Axel, one of their ML engineers put it.

   22. SPSpeaker44:19

       I think Jane Street is, like, pretty bottom-up in terms of we have lots of different researchers who are all training their own models, sequence models, uh, all sorts of other weird and wonderful things.

   23. DPDwarkesh Patel44:28

       By the way, with their new compute deal, they've just added a six billion dollar hive buck stimulus to their internal economy. Jane Street is hiring researchers, engineers, and interns. Go to janestreet.com/dwarkesh to learn more. Okay, so stepping back, I wanna understand-- I think there's this question about, uh, what, what does this tell us about what actually changed in our environments, um, over the last eighteen thousand years? And I-- 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 things like intelligence or lack of schizophrenia or so forth, things just seem kinda robustly good, were 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 less predicted, uh, value for, uh, you know, what they would score on an intelligence test if, a 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, the, this was not a tr-- You just look at the human body or any animal and just like, there's-- Evolution has been acting on it so strongly to make it functional, 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, s-s-- Doesn't seem to have been under that strong selection, uh, in the Mesolithic or Paleolithic or those eras.

   24. DRDavid Reich46:09

       I think that that's a great question, and like, as we talked about before, uh, th-th-th-the human adap- selection is very effective. You-- It can move the mean value of traits within hundreds or thousands-

   25. DPDwarkesh Patel46:22

       Yeah

   26. DRDavid Reich46:22

       ... of years in one direction or the other, if that's adaptive in a particular environment. And so you might wonder, isn't intelligence good-

   27. DPDwarkesh Patel46:30

       Yeah. [laughs]

   28. DRDavid Reich46:30

       ... you know, in all contexts and places in 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.

   29. DPDwarkesh Patel47:00

       Well, but that-- When, when the Bible is being written, esp-especially the Old Testament, is exactly when selection for intelligence is the highest point-

   30. DRDavid Reich47:07

       Yeah
4. 58:00 – 1:09:40

   Evolution is limited by time, not population size

   1. DPDwarkesh Patel58:00

      Hmm. So a- all of this, um, evolution since out of Africa is acting on alleles that already exist in the pool of human variance from that first group, which we were talking about last time, on the order of 10,000 people that, um, you know, exploded out of, uh, out of Africa. And it's a, it... Is it surprising that across all these different traits, from cognitive profiles to, uh, resistance to different kinds of diseases, to, um, height, to whatever, that that one pool of people contained so much latent v- uh, variation that they could supply the, you know, enough s- you know, stretchiness to accommodate all these different traits that you're s- studying now?

   2. DRDavid Reich58:49

      Um, that's a rich question, and I think that the human population has within it, for complex traits, a tremendous amount of variation.

   3. DPDwarkesh Patel58:58

      Hmm.

   4. DRDavid Reich58:58

      So, uh, within the human population, there's a huge amount of variation that affects height. Uh, there's a huge amount of variation that affects body mass index. 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.

   5. DPDwarkesh Patel59:14

      Yeah.

   6. DRDavid Reich59:14

      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, one's 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 inv- 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.

   7. DPDwarkesh Patel1:00:14

      Hmm.

   8. DRDavid Reich1:00:14

      Every mutation that can occur does occur. There's eight billion people in the world.There are maybe 30 new mutations every generation, so that's like, what is it? It's like 240 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 100 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-

   9. DPDwarkesh Patel1:00:48

      Mm-hmm

   10. DRDavid Reich1:00:48

       ... for the new mutation to occur.

   11. DPDwarkesh Patel1:00:49

       And so how, how likely is it that the thing that changes the Bronze Age is just that the human population was big enough? So you, you, 3000 BC, you go to, I think, a population of 50 million-ish people. Um, the population is big enough that, and the gene flow between different areas is high enough such that things whi- which don't have an overwhelming selection coefficient, which aren't overwhelmingly favored by evolution, are finally visible, uh, visible to selection.

   12. DRDavid Reich1:01:13

       I think that's not likely to be true, but it's extremely interesting thing to think about. So I think already when population sizes are on the order of a million so or so, every mutation that can occur does occur within a few generations. And so that's well before the Bronze Age, if you take the population even of a place like Europe, but also, also of, of, of, of other places, or maybe it's at the, uh, dawn of the Bronze Age or the farming period. So the, the question you ask is maybe when the population is small, natural selection doesn't work effectively.

   13. DPDwarkesh Patel1:01:43

       Yeah.

   14. DRDavid Reich1:01:43

       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-

   15. DPDwarkesh Patel1:01:56

       Yeah

   16. DRDavid Reich1:01:56

       ... a lot in a small population just randomly. So if you have a population of size of 1,000, populations var- mutations will bop around o- by a frequency of one over 1,000 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 1,000. 0.1% 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 1,000 or 10,000.

   17. DPDwarkesh Patel1:02:27

       Mm.

   18. DRDavid Reich1:02:28

       If you are talking about mutations of the type that will start rising in some, only in large populations, but not small populations, those are 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.

   19. DPDwarkesh Patel1:02:50

       Mm.

   20. DRDavid Reich1:02:50

       There's just a timescale issue.

   21. DPDwarkesh Patel1:02:52

       Understand.

   22. DRDavid Reich1:02:52

       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 gonna work in small populations or large populations. It's not gonna be affected by the population size.

   23. DPDwarkesh Patel1:03:05

       Interesting. But you're saying more generally, once you hit a given threshold of population, the dominant factor is time span-

   24. DRDavid Reich1:03:10

       Correct

   25. DPDwarkesh Patel1:03:10

       ... not population size.

   26. DRDavid Reich1:03:11

       Correct.

   27. DPDwarkesh Patel1:03:12

       Okay. Interesting.

   28. DRDavid Reich1:03:13

       It's very interesting, and it's actually not widely understood. Yeah.

   29. DPDwarkesh Patel1:03:16

       Mm-hmm. Okay. So speaking of data contradicting what you might have otherwise assumed, uh, one of the papers you sent me beforehand, Malik 2016, found that there are not fixed differences between modern and archaic humans 50,000 years ago. Um, and of course, we know this is the period in which the so-called cognitive revolution happened and modernity started and people are making art or whatever. Um, 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?

   30. DRDavid Reich1:03:58

       Right. 50,000 years ago or so, or maybe 100,000 to 50,000 years ago, there's a quickening of the pace of change in culture. So people, you see the first extensive rep- uh, uh, representational art and, like, bead necklaces and drawings on the wall and so on and so forth, and also a rapid increasing pace of innovation, the types of tools that people use. And so the thought might be that there was gonna be, have been 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 that everybody suddenly had, soon had, and that made it possible for do these thi- to do these things, maybe s- some genes that, uh, allowed people to have repre- uh, li- complex language, representational language, for example. And so one thing that we did in 2016 in this paper by Shaat 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 100,000 or 200,000 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 sweeps 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, uh, um, uh, 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-
5. 1:09:40 – 1:17:52

   Why no farming before the Ice Age?

   1. DPDwarkesh Patel1:09:41

      We were talking earlier how there's no fixed differences between, um, humans fifty thousand years ago and humans today.

   2. DRDavid Reich1:09:47

      Mm-hmm.

   3. DPDwarkesh Patel1:09:47

      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.

   4. DRDavid Reich1:10:05

      That is such an interesting question. Right. Genetically, we're there.

   5. DPDwarkesh Patel1:10:08

      Yeah.

   6. DRDavid Reich1:10:08

      The common ancestral population has all of the ingredients for-

   7. DPDwarkesh Patel1:10:11

      Right

   8. DRDavid Reich1:10:11

      ... farming fifty thousand years ago. Uh, and you know, these people are distributed into different parts of the world, the Americas, you know, fifteen thousand years ago or whatever it is. Uh, you know, New Guinea forty thousand years ago, East Asia, you know, Europe, you know, West Africa. No farming develops, uh, before, you know, twelve or eleven thousand years ago. It only f- develops in the last, you know, twelve thousand years, the period known as the Holocene, which is sort of the end of the Ice Age. And if you talk to climate scientists, uh, 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, uh, and that actually this is true, and 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 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 sea- and ten years to ten years and a hundred years to a hundred years, and it's just a period of relative stability that we are miraculously living in, and that when this period of relative l- stability happens, you 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, a hundred thousand, two hundred thousand, three hundred thousand years ago. It's kind of a crazy observation that people just accept, uh, but it's, like, unbelievable.

   9. DPDwarkesh Patel1:11:53

      Oh, so y- you, you, you increased the range there. So you said a hundred thousand, two hundred thousand, three hundred thousand years ago, and we, based on the genetic differences between modern, uh, modern people and people from even three hundred thousand years ago, you think basically there's, they're modern three hundred thousand years ago?

   10. DRDavid Reich1:12:10

       I don't know. Like, I'm thinking about this all the time right now.

   11. DPDwarkesh Patel1:12:13

       Yeah. [laughs]

   12. DRDavid Reich1:12:13

       Uh, this is actually, like, actively what I'm thinking about-

   13. DPDwarkesh Patel1:12:15

       Yeah

   14. DRDavid Reich1:12:15

       ... right now. And, like, you know, there's a big transformation in terms of the culture of humans three hundred, four hundred thousand years ago, this invention of Levallois technology, the ability to make stone tools out of cores.

   15. DPDwarkesh Patel1:12:28

       Yeah.

   16. DRDavid Reich1:12:28

       The Middle Stone Age revolution or the Middle Paleolithic revolution, depending on whether y- what you call it in Africa or Eurasia. And this is aRevolution, 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.

   17. DPDwarkesh Patel1:12:44

       Hmm.

   18. DRDavid Reich1:12:44

       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, 100 to 50,000 years ago, uh, when there's this second transition with 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 300,000 or 200,000 years. Uh, and all of these people are capable of, you know, going to college-

   19. DPDwarkesh Patel1:13:23

       Right

   20. DRDavid Reich1:13:23

       ... 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 200 or 300,000 years ago, and that even Neanderthals had them, right? So it's not obvious that this was not the case.

   21. DPDwarkesh Patel1:13:39

       Yeah.

   22. DRDavid Reich1:13:39

       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 12,000 years ago you start having agriculture popping up in different places. It's kind of an outstanding mystery-

   23. DPDwarkesh Patel1:13:58

       Right

   24. DRDavid Reich1:13:58

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

   25. DPDwarkesh Patel1:14:10

       The climate thing seems surprising given there were so many different environments in which agriculture was independently developed. N- I, now I understand that across environments the variance could have gone down. But it just like, if, if it only had happened in one place at one time, I, I could have bought that explanation. But the fact that they're making maize in the New World, and they've got, um, uh, you know, cereals in the Old World and so forth, and just in, in very different environments makes it surprising that it would-

   26. DRDavid Reich1:14:39

       It's very, very surprising.

   27. DPDwarkesh Patel1:14:41

       Yeah.

   28. DRDavid Reich1:14:41

       And I think we accept it, but it's just like a crazy observation-

   29. DPDwarkesh Patel1:14:44

       Right

   30. DRDavid Reich1:14:44

       ... that most normal people don't realize.
6. 1:17:52 – 1:54:40

   The Neanderthal puzzle David can’t stop thinking about

   1. DRDavid Reich1:17:52

      it.

   2. DPDwarkesh Patel1:17:52

      What are other questions you have that, um, pe- uh, yeah, you're, you're either ha- are investigating right now or want to investigate these kinds of big picture questions of human history?

   3. DRDavid Reich1:18:04

      I think that I'm ... I mean, I'm, I'm perplexed. I don't know if we talked about it before, but, like, I remain very, very confused about the relationships between archaic and modern humans.

   4. DPDwarkesh Patel1:18:15

      Hmm.

   5. DRDavid Reich1:18:15

      We have genome sequences now from archaic humans who lived in Europe and the West Eurasia and Central Eurasia and the Neanderthals. We have archaic sequences from these ena- enigmatic Denisovans, who we now have, uh, a skeleton for, um, since we last talked. There's now a s- a f- a skull from a Denisovan-

   6. DPDwarkesh Patel1:18:32

      Hmm

   7. DRDavid Reich1:18:32

      ... 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 5 or 600,000 years ago, and that group descends a couple hundred thousand years before, uh, 7 or 800,000 years ago from the common ancestors of modern humans. And so genetically, the whole genome data says that Neanderthals and Denisovans 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 tone, stone tools, level of technology, this 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-

   8. DPDwarkesh Patel1:19:37

      Hmm

   9. DRDavid Reich1:19:37

      ... two or 300,000 years ago and then shot up to 100% frequency. And then Neanderthals and modern humans are both the product of mixture events that happened between archaic and modern humans 300 or 200,000 years ago, uh, 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 Denisovans, even though genome-wide Denisovans and Neanderthals cluster. So I'm thinking about that all the time now.

   10. DPDwarkesh Patel1:20:17

       And then connecting them would be interbreeding events or being in the same place at the same time that we missed?

   11. DRDavid Reich1:20:24

       There's a known interbreeding event-

   12. DPDwarkesh Patel1:20:25

       Yeah

   13. DRDavid Reich1:20:25

       ... from the lineage leading to, uh, modern humans into Neanderthals, but it's supposed to be only 5%.

   14. DPDwarkesh Patel1:20:31

       Yeah.

   15. DRDavid Reich1:20:32

       So I'm interested in that, that, that 5% is actually a sign of something much more impactful, that is that somehow Neanderthals are in some sense deeply modern in some ways. And even though they get swamped by archaic genes, that somehow-

   16. DPDwarkesh Patel1:20:45

       Hmm

   17. DRDavid Reich1:20:45

       ... they 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.

   18. DPDwarkesh Patel1:20:59

       Interesting. I- sorry, w- wh- uh, when was this interbreeding event?

   19. DRDavid Reich1:21:02

       300,000 to 200,000 years ago.

   20. DPDwarkesh Patel1:21:04

       And so the common ancestor between Neanderthals and most humans alive today is potentially more recent than the common ancestor between all humans alive today.

   21. DRDavid Reich1:21:14

       Oh, for sure.

   22. DPDwarkesh Patel1:21:15

       Yeah.

   23. DRDavid Reich1:21:15

       Yeah.

   24. DPDwarkesh Patel1:21:16

       Which is crazy.

   25. DRDavid Reich1:21:16

       Yeah. Well, you- not, not... The divergence to all the archaic humans, including Denisovans, is within human variation.

   26. DPDwarkesh Patel1:21:23

       Okay.

   27. DRDavid Reich1:21:23

       So, but, uh-

   28. DPDwarkesh Patel1:21:24

       Wait, what?

   29. DRDavid Reich1:21:25

       Yes. So the average time to the common ancestor of any two human genes is one or two million years ago. So, like if you look at any, the, a bit of your DNA that you get from your mother, and a bit of your D, that same bit of your DNA on the same chromosome. The copy of chromosome three you get from your mother, and the copy of chromosome three you get from your father, 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.

   30. DPDwarkesh Patel1:21:56

       And, um, I'm sure that there's a simple explanation, but how?
7. 1:54:40 – 2:13:49

   The methodology behind this breakthrough

   1. DRDavid Reich1:54:41

      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 anal- 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-African 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, uh, 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 m- 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 two thousand and fifteen 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 two thousand and fifteen, we analyzed data from about two hundred 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 twelve 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 two thousand and twenty-four by a group in Copenhagen analyzed the data, much better data than we had in two thousand and fifteen, and found only twenty-one 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 two thousand and fifteen. In a lot of ways it was disappointing 'cause 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- 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.

   2. SPSpeaker1:58:42

      Mm.

   3. DRDavid Reich1:58:43

      So, so what we did is we, uh, deployed a few, uh, innovations or changed, 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 fourteenfold. Uh, and the main thing that we do in this study is we report data in this study from about ten thousand individuals, uh, with new data. So this is like a very big increase in the amount of data in the literature, uh, and, uh, the total dataset size of ancient individuals distributed over the last eighteen thousand years is about sixteen thousand people. So this is a large dataset. 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, uh, which is Europe and the Middle East. Uh, it's not a more important part of the world than other places, but it's the place where maybe seventy or eighty percent 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 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 dataset of about sixteen thousand ancient people and twenty-two thousand people if we include the ancient and modern people, and then we look at how closely related each of these twenty-two thousand people are to each other, and we predict the genetic type at each position in the DNA at ten million positions based on the pattern of relatedness to all of the other twenty-two thousand people.And then we ask if, if natural selection blowing the frequency of the mutation in the same direction in all the 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 gonna 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.

   4. DPDwarkesh Patel2:01:25

      And ju- just to summarize to make sure I've understood, you're trying to make a model that predicts allele frequency changes over time.

   5. DRDavid Reich2:01:30

      Right.

   6. DPDwarkesh Patel2:01:31

      And you have two different parts.

   7. DRDavid Reich2:01:32

      Right.

   8. DPDwarkesh Patel2:01:32

      One part is this, uh, genetic related ne- relatedness matrix, which captures, um, how similar different genomes are to each other, and that should capture, um, the impact of different bottlenecks and of drift and of population admixtures and all those things which affect the entire genome.

   9. DRDavid Reich2:01:50

      Correct.

   10. DPDwarkesh Patel2:01:50

       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 doesn't become easier to predict the allele frequency changes than you would've 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, uh, are, have they gone through the same bottlenecks? Have they gone through the same drift, et cetera?

   11. DRDavid Reich2:02:21

       That's precisely right.

   12. DPDwarkesh Patel2:02:22

       Okay. Um, okay, so what have you learned?

   13. DRDavid Reich2:02:26

       So, uh, when we analyzed the data this way, we looked at 10 million positions in the DNA, uh, that, uh, in, in these 22,000 people, 16,000 of them were ancient. And we looked to see if there was more change in this consistent direction over time than you would expect by chance. And when we analyzed the data, we s- found many, many hundreds of places in the DNA that were changing too much, uh, over time in too consistent a way to be explained by chance. 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 blo- 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 work, there were at most a couple of dozen-

   14. DPDwarkesh Patel2:03:33

       Mm

   15. DRDavid Reich2:03:33

       ... 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 e- 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 pres- blood pressure or something like this. So we took the UK Biobank, which is about 500,000 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 10 million positions are connected to this trait in some way, in a convincing way. So in 10 million positions, about 15%, about 1.5 million pos- 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 or statistic, is it related to whether a ve- 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.

   16. DPDwarkesh Patel2:05:29

       Oh, sorry, what is a selection statistic?

   17. DRDavid Reich2:05:31

       This is the statistic we use to measure whether a mutation is changing over time s- uh, significantly, uh, uh, in a non-zero way.

   18. DPDwarkesh Patel2:05:41

       Got it.

   19. DRDavid Reich2:05:41

       So it's, it, it can be approximately thought of as a normally distributed statistic, a Gaussian statistic, uh, which is the number of standard deviations the statistical value is away from zero, where zero is the pos- is no natural selection.

   20. DPDwarkesh Patel2:05:57

       Got it.

   21. DRDavid Reich2:05:57

       Uh, it's not exactly that, but it's close to that. And so if the statistic is above five, we see about a fivefold enrichment in mutations that affect a trait.

   22. DPDwarkesh Patel2:06:07

       Interesting.

   23. DRDavid Reich2:06:07

       And so instead of 15% of the, uh, mutations that are, uh, th- at random affecting the trait, it's like 60 or 70 that are, are, are, are affecting the trait when we slide our statistic upward. And this is providing completely independent evidence that these sites are real, and as you slide above five, there's no more enrichment. So our interpretation of these results, uh, and that we were able to 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.

   24. DPDwarkesh Patel2:06:45

       Um, okay. And so just to make sure I understood, you're saying, look, in order to figure out what alleles are, been under selection, your model, uh-assign some statistics saying, "Oh, in order to explain why this allele has a specific frequency, we're gonna give it a selection statistic." 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 allele 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.

   25. DRDavid Reich2:07:30

       That's exactly right.

   26. DPDwarkesh Patel2:07:32

       Okay.

   27. DRDavid Reich2:07:32

       And this is, like, a brilliant idea that Ali had, and it's, it's... it really abandons the traditional approach of assigning statistical significance to mutations that cause, uh, a trait, because we're just using an external piece of information, the p- the correlation to 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 50% 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 99% of the way to the plateau, there's a 99% probability that's real.

   28. DPDwarkesh Patel2:08:20

       Mm.

   29. DRDavid Reich2:08:20

       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-

   30. DPDwarkesh Patel2:09:13

       Yeah

Episode duration: 2:13:49