 and then I'd like to start our introduction for our speaker with a land acknowledgement as we do each Wednesday. Here, the Archaeological Research Facility is located in Fuichin, which is the ancestral and unseated territory of Chachenyo-speaking Ohlone people, successors of the historic and sovereign Verona ban of Alameda County. We acknowledge that this land remains of great importance to the Ohlone people and that the ARF community inherits a history of archeological scholarship that has disturbed Ohlone ancestors and made attempts to erase living Ohlone people from the present and future of this land. It is therefore our collective responsibility to critically transform archeological inheritance and practice in support of Ohlone sovereignty and to hold the University of California accountable to the needs of all native and indigenous peoples, well, not just our words, but our actions. So today, we'll be having a talk on Neanderthals with Dr. Loritz Goff, who's a postdoctoral research in the Morjani Lab and Lab in the Department of Molecular and Cell Biology here at UC Berkeley. He did his PhD in bioinformatics at our house and he developed a method for detecting Neanderthal and denose of an ancestry in modern humans without using the archaic reference genomes and used it to find archaic segments in 27,000 Icelanders in 89 Papuans. His postdoc in Ben Porter's group, Ben Peter's group site at the Max Planck Institute for Evolutionary Anthropology and Leipzig, where he further studied archaic introgression in ancient genomes and studied Neanderthal communities. In the Morjani Lab, he's focused on studying archaic introgression in South Asian populations and the evolution of human germline mutation rate. So please join me in welcoming him to our brown bag talk today. Thank you very much. Well, hello everyone and thank you for attending this talk. So, my name is Lauerz and thank you for the introduction. And today I'm gonna talk to you about what I did my postdoc, my postdoc works, which is from the Max Planck Institute in Leipzig. And this work is all about the Neanderthal community and what we can learn from doing a genetic analysis of 13 Neanderthals from two sites in the Altai Mountains. And so I'm gonna do it a bit in reverse because there's no way I could have done all this by myself. And I had a lot of help from a lot of very talented people. So I wanna acknowledge all of them upfront. So the way I'm gonna structure my talk is as follows. First, I hope you can, can you read everything all right? Okay, good. So first we're gonna talk about, we need some context first. So first of all, what do we know about Neanderthal communities up until this point? Then I'm gonna introduce these two caves, the Gisgar Cave and Oklatnikov Cave and how they fit into all of this. And then as this is a genetic study, we're gonna have to do a little genetics reminder just so everyone is on the same page. And then we're gonna jump into the results. So without further ado, let's get into it. The first question is, what do we know about Neanderthal communities? So in the past 12 years, researchers from the Max-Bang Institute in Leipzig had managed to sequence 18 Neanderthals from 14 different sites. This is the work that awarded the Sponsored Power of the Snowball Prize a couple of weeks ago. So you can see these are all the places where we sequence Neanderthals. You can see the sort of spread out over the Neanderthal range. So you believe they lived mainly in Europe, but also as far east as the Altar Mountains to Siberia, which is all the way over here. It's where the two caves I'll be talking about today are located. So even though we have a lot of Neanderthal genomes now, the issue is that it's typically only a single individual per site. And these sites were occupied from 120,000 years ago to 50,000 years ago. So it's really quite spread out in time and space. So at this point, we don't really have a good idea of what a Neanderthal community was like. There has been some previous studies looking into this. So for instance, there was a study from Spain where they sequenced 12 individuals, but as a sequence, they looked at four positions in the entire genome. And from this, they can conclude that there was at least 12 individuals in a little community. And they might also have some hints about the social structure. And then there was another study. This is not a genetic study, but this study looked at Kosselal footprints that they found on a beach in France. And from that, you can sort of also get an idea of how many individuals were in a community. So they also estimate something like 10 to 13 individuals in a community. We've seen our image is not, our resolution is not very high yet, which brings us to this paper with the Tagiskaya and Oklatnikov cave. And by the way, I forgot to say in the beginning, this talk is gonna be around 30 minutes. So I have time for questions. And I prefer that you ask questions while I'm going through the talk. I feel like that flow is better. I don't know if that's how you usually do it. Yeah, so if you have any question, feel free to interrupt and ask your question. Yes, so now we're zooming in on Tagiskaya and Oklatnikov cave. And you can see that it's all the way here in southern Siberia on the border with Kazakhstan in Russia. And these are the two caves marked here. And you might notice that they're very close to the famous Denizoba cave, which is where we first found a bone from a Denizoba, which is another type of human like the Neanderthals that lives here. So first I'm gonna go through each cave. And now we're sort of in the, in not in my area of expertise. This is the archaeology, but I'll bear with me. I'll do my best to summarize the important things. So Tagiskaya cave has been excavated since 2007. The excavation is still going on. And at this point, around 30% of the cave has been excavated, which has already yielded around 80 Neanderthal bones and teeth. And you can see some of them here. Some of them in red are from this study. And so the important thing about this cave is that we think the occupation was short. So if you do optical dating of sediments, if you do the carbon dating, it all points to the occupation being, between 50 and 60,000 years ago. And so there's only one layer, this layer six. You can see that. Well, this is where we find all the Neanderthal remains. It's also where we find all the bison bones that they were hunting and eating. And it's also where we find all the lithics. So we think it's a relatively short occupation. And by that, I mean, over a couple of thousand of years max. And it happened somewhere between 50 and 60,000 years ago. Now for Oclathnikov cave, the story is quite different, unfortunately. So that was excavated in the 80s. And as you can see before, with Tagiskaya cave, we know exactly where each remain come from, what layer it come from. But here we don't. Oh, yeah. And I just asked a question about the previous state. You can. So everything is in layer six. Yeah. Are they articulated burials or disarticulated bones out there? It's not burials. And can you specify what it means? I like, the bones are spread all over. We're not talking about skeletons in articulation, we're talking about random bones. Yes, yes, yes, exactly. So most of these things are actually quite small. So we have teeth and we have small pieces of bones. We don't have a big femur, for instance, or a skull or anything like that. Yeah, so that was the Giskaya cave. It looks nice, but Oclathnikov, we don't know so much about, unfortunately. So it's excavated, but as far as I understand, everything was taken out of the cave. And then you were going through all the settlements. So we don't know exactly where the bones are from. And the dating here is also more tricky. So we only have a minimum age here. So older than 45,000 years ago. Yes, in the back. I think quite quickly in most of the caves, they knew it was the Anatole's house because they found some teeth that has some characteristic the Anatole, I mean. But I think the bones, I think that assumes like where you can scan through a lot of bones and look for human proteins. Yeah, yeah. So the takeaway here, Giskaya has more accurate dating than Oclathnikov and also more information. And also, coincidentally, the DNA preservation is also much better in the Giskaya cave than Oclathnikov cave. So you will see me in this talk mainly focusing on Giskaya cave. It's just because that's where we have the most data from. Another thing that you need to know is that the tool industry, in the stone tool industry in Giskaya cave and Oclathnikov cave are very similar. They are called the Sibiyachika variant. This particular type of variant is different from other sites in the Altai mountains. So only these two caves and another site has this one. And it's actually very similar to a stone tool industry that's seen in Europe. So that let researchers let our Russian collaborators to suggest that it actually looks like there's been multiple Neanderthal migrations from Europe and into Siberia. The first one being something like 100,000 years ago. And that's the one, that's the population where the first high-coverage Neanderthal genome comes from. That comes from this first one. And then a second one, somewhere around 60,000 years ago because they have the similar tool industry. So this is a, was that a hand? Oh, sorry. So this is a case where the hypothesis of multiple migrations actually comes from archaeology first. And then the same year it was actually confirmed also using genetics. So there is one high-coverage Neanderthal already from secret from Czechia sky cave. And this individual also shows that these Neanderthals are more like the European Neanderthals than the other Neanderthals that live in Siberia. So that's sort of the background of the case. Is there any questions at this point? I see no questions. So now we're gonna do a quick genetic experimenter. So I know all of you probably know this but it's always good to have a little bit of pressure. So this is what our genomes look like. You can see we have 23 chromosome pairs. All the other zones are labeled one until 22. And then you also have the sex chromosomes. And the most common constellations is X, X then you are a female and XY then you are male. And then in addition to this we also have this mitochondria which is sort of a little piece of circular DNA in our bodies that generates all the energy in our bodies. So if you hold your breath you won't be using your mitochondria because it runs on oxygen. So it is quite important. One thing that's gonna come back later I'm just saying it down but I will say it again later is so each you inherit a chromosome from each of your parent but there's something special about some of them. So for the Y chromosome that's a chromosome that's only inherited from the father to the son. And this little mitochondria this little powerhouse of the cell is only inherited from mother to children. And then only the daughter will then pass it on. And then so each chromosome is just a long sequence of base pairs. And there's four different type of bases. So we have an AC and a G and a T and the data we look at as geneticists looks something like this. Imagine a giant sex file with 3.2 billion letters in it. And that will be our data. So again one chromosome you get from your mom and one you get from your dad. So that's quite a lot of data but we're assuming in on specific things. So each time you get your parents pass DNA onto you they copy the DNA and pass it on. But this DNA copying machinery is not perfect. And sometimes there will be mistakes. And that's actually quite good for us because that's what we use to differentiate different individuals and find out who's related to who. So on average each of you here in this room will probably have something like 75 mutations that no one else in this room have. That is being passed on from your parents. So these are the signals that we're using. So you can imagine the more related you are to someone the less differences you will have. So I try to illustrate that here with... So this is our data. We have this long sequence of letters and sometimes there's differences. You can see there's a C here and there's a G here on this other individual. And then... So if you define a brother in the room with, you know, there are 75 differences between us? Yes. Okay. Well, some of them might be shared but a majority are actually not. And mutations you can mainly thank your file upon, by the way. 75% of them come from the paternal line, sorry. Yes. So now we have the setup. So we have a few differences means you're closely related and more differences means you're more instantly related to each other. So the data we look at here is we take the entire genome and we look at positions that we know already varying in population. So we don't look at the entire thing but we look at something like 700,000 positions. Then we look at 70 million positions on a Y chromosome and we look at the entire mitochondria. But the mitochondria is small. So it's only 15,000 letters that we have to look at. And so that's our data. So now that's... So we take all our bones and we extract DNA from them. And so this is all the individuals that we could get DNA from. And I listed them here with, this is the ID of the domain. And most of them are from Jekyll Sky Cave and then only a few are from that cave. Another thing is that here you can see which element it is. So that this is a little tooth symbol. That means that it comes from a tooth. And if not, it comes from a bone. And then we can also determine the genetic sex of the individual. And so because sometimes these teeth are deciduous, like the first one, for instance, is an example of a deciduous tooth. We sort of estimate how old were this individual, not at the time of death, but at the time where you lose this teeth. So you can see this age estimate here sometimes as a D. And that means that it's a deciduous tooth. So it's not time of death. It's time of losing this tooth. And some of them I wanna highlight already. So we very quickly discovered that one individual, this Jekyll Sky 12 year, is actually the same individual as the previous high coverage Jekyll Sky I told you about earlier. So it's the same individual represented by two remains, one tooth and one bone. Then we have another interesting example here. This is another case where I can just go pretty confident that this was probably coming from the same individual, these two bones, because one is a mandible and the other is an incisor that fits perfectly into that mandible. So they already had a pretty good suggestion that this was the same individual. And we'll see if we can confirm that with genetics. Yes, so let's jump into how are all these fragments of bones, like the individuals that they come from, how are they related to each other? So just to get you ready for the type of plot I'm gonna show you in a bit. Let's say imagine that we have a father and a mother and we have a son and a daughter actually. And then we have some individual that's not immediately related to any of them. But we only have data from the red ones, the son, the daughter, and the unrelated. So if we compare them to each other, we're gonna see that. So if we compare the, like the unrelated individual to itself, it's gonna be identical. It's gonna be the same sequence. And the same if you compare the daughter to yourself and the son to himself. But the more interesting thing is what when we compare them to each other, so you can see that the daughter and the son, they're gonna have a first degree relationship. Whereas this unrelated individual is gonna not be related, have an unrelated relationship to both of them. Does this make sense? Yes. So now let's do it on our data. And this is what it looks like. So you can actually see that, you see a lot of gray, first of all. So you see that most of these individuals that we find are not related to each other. But they are little clusters here and there. So we take the first one. This is the piece got six and piece got 14. And that was the truth and mandible that I told you about earlier that fit together and was suspected to be the same individual. And that is blue. So that is identical. These two remains come from the same individual. We have another case here where we have three teeth all from the same individual. What's a bit interesting is that so one of the teeth are deciduous and the other two are permanent. So we were already very excited that, can you say something about Neanderthals coming back to the cave, returning to the cave and keep on being there? But as it turns out, if you estimate how old with this individual have been, it's very possible this is just one event. So the individual loses a tooth and then dies shortly after. So we cannot make any claims about Neanderthals having a favorite cave or something like that. Which is scary. Eh? Which is scary. Yeah. Because teeth like, so you know, if you have a kid, they're deciduous to just sitting and not for like two weeks before actually like on the out. Yeah. Yeah. They just, yeah. Yeah. Exactly. So now let's turn to, we actually find a first degree relationship too, which is very interesting. It's the first one ever reported between a pair of Neanderthals. Of course they existed, but the first time we have the DNA from it. So it's a male and a female. And there's like three different ways a first degree relationship could be. Like these two individuals could be siblings. They could be brother and a sister. They could be mother and son. Or they could be father and a daughter. But you remember earlier, I told you about the mitochondria and how this was inherited only from mother to children. So let's think about what that would look like. We have mitochondria data for these individuals too. So if the mitochondria, if it's a brother and a sister, then the mitochondria will be the same because they're both inherited from the mother. And if it's a mother and son, then the mitochondria will also be the same. Because again, in the mother, if the son is inherited from the mother, but with their father and daughter, they could be different or they could also be the same. But luckily for us, they are different. So we can actually, we're confident and say like, these two individuals are first degree related and it's a father and it's daughter. The daughter is a teenage daughter and the father is an adult male. I think that's very exciting because that sort of means we go from something like this, these are the remains to be able to say something like this, to paint relationships of the other side. And I want to congratulate to Trump Joplin, who's an amazing artist who's drawing all these things for us. So this is a summary of how all the individuals in our cave are related. So these big squares will be males and the circles will be females. And the letters indicate individual names and all the specimens that come from the same individual will be these little circles in here. So you can already see that we have a father-daughter. We also have a second degree relationship that I didn't tell you about because we cannot say that much about that. That can be a cousin pair. That could be a grandmother and grandson or it could be uncle and niece or nephew. It could be many things. So we cannot say that which one it is. But you already see that some of these videos are related to each other. So this was probably the same Neanderthal community. This is like a snapshot of a community consistent with the occupation of this cave being very short. So now that we have a community, what can we actually say about it? And as two main points we can make and one of them is how big, how large is this community and how large is the population that this community comes from. And another thing we can say something about a social organization but let's start with just the size of this community. So I'm again like prepping you for this blood that I'm about to show you. So we have each individual on the X-axis and the Y-axis is something called homo-psychology. It means how many times is the DNA from your parents the same? And if that happens all the time, then you have very low diversity and a small population size. But if homo-psychology is low, that means there's a lot of diversity and a larger population size. So that looks like this. Don't worry so much about what the different colors mean yet. What doesn't change, sorry. The colors are blue is for Neanderthals and denusubans and orange is for early modern humans. Modern humans are together, something like 40,000 years ago. And what you can already see here is that there's more homo-psychocity in the Neanderthals. And this means that Neanderthals lived in smaller communities than modern humans. There's less genetic diversity in them. So another question could be, so this is comparing to ancient modern humans, but what if we compare to modern humans today? And what if we zoom even further out and compare to our closest relatives who are alive today? So the great age, you can see gorillas and orangutans and stuff like that. So then we'll get something like this. So I collapsed all the tachyscaia into one bar and just put some error bars on so you can see what the average is. And you can obviously see that the homo-psychocity is way higher than the other individuals. And by the way, some people call this in breeding too, but I don't think that's a nice term. That's something mainly for like animal breeding and like these are human, so we shouldn't use that term. So you can see that modern-day human populations all these here, they have much more diversity. They have much less homo-psychocity compared to Neanderthals. And actually the population that the Neanderthals look most like are these green ones, which are mountain gorillas. And so this is not to say that Neanderthals live like mountain gorillas or anything like that. This is only how big is the community. And so the mountain gorillas, as you might know, is an endangered species and there's less than 1,000 individuals alive of this species today. So think of like, so we are analyzing the Neanderthals, something like 10,000 years before they go extinct, like all the way to the eastern most range of their habitat and it's a small population. So there's not a lot of individuals around. It's what this shows us. And then the last thing, now we talked about how big the community is, but let's talk about how these communities are related to each other. So, and the way we're gonna do that is, so I should say that, first of all, we know that you cannot just have a community of 10 individuals constant through time, because sometimes just by chance, you will only have sons and then you will go extinct. You cannot get more children. So you need these communities to interact with each other. And then the question we want to ask is, well, so how are these communities interacting with each other? Is it mainly women who are moving between communities or is it more the men or both who are moving between these communities? And I'm gonna illustrate this with little cartoons here. So imagine we look at the mitochondria. That was the thing I said before that that's inherited from mother to children, but only passed through the daughters. This is gonna be a history of the maternal line of women in these communities. And I've drawn little communities here. I have four communities. Each of them have some individual sense. And these are the DNA sequences this graph represent. And if you're gray, then you're all the same. But you can imagine that in each community, mutations will happen because the machinery is not perfect. And then you get differences. So I color them in different colors here. But we only have DNA from one community. We only have DNA from the Tagiskaya community. So what I'm setting up here is that I'm doing a lot of computer simulations. Like all these little communities live inside my computer and then they interact and attract them through time. Then we can see what scenario fits best with the data we are having. So there was the mitochondria. So we can compare that, the mitochondria diversity through the white chromosome diversity. So you can imagine if there's no movement between communities, then all the diversity in the Tagiskaya community that we're looking at should be more or less the same compared to the white chromosome diversity if there's no movement or if they're moving at the same rate. But you can maybe also imagine different scenarios. So you can imagine that the female are moving between groups. And here what I want you to notice is that so for instance, in this community here, there's now some orange mutations from this community here. And there's a green one from over here and some blue ones in here. But they're still just the purple ones in the white chromosome. So if women are moving, you will get more different types of mitochondria if you just look at one population because they come from other places. And vice versa, if you have the men moving between the different communities, then there's gonna be low diversity on the mitochondria but higher diversity on the white chromosome. Does this make sense? Thanks. So now let's see in the data, what does it actually look like? So this is the data. I have my satisfies all the way here on the left. And then I have one human populations here on the right. So the first thing you can see is that this is the amount of diversity on the Y axis. The first thing you can see is that the bars are not very tall. So that means low diversity in the Neanderthals. But that's good. That was the same thing we found from before. So now if we zoom in, the first bar here is the height of the mitochondria diversity. This is how much mitochondria diversity is there. And this one is how much white chromosome diversity is there. Then I'm also compared to some other populations. But the important thing is there's much more mitochondria diversity than there's white chromosome diversity. It's actually a factor of 10 times higher. So this suggests that it's mainly the women who are moving between these communities. And to get an idea of, well, how much are they moving and how big are the communities? We set up all our computer simulations and we simulate a whole bunch of scenarios and we find the best fitting one. Oh, I forgot I had this slide. This is just taking the difference in white chromosome diversity minus mitochondria diversity and looking at that if any of you are very negative, that means you have very high mitochondria diversity. And if you're very positive, then you have very high white chromosome diversity. Let's just to show again that these guys are again more similar to the plaintiffs, but they're more extreme than all present-day human populations. So now that we, so now we try all our different simulations and what we find is that the best fitting scenario, keep in mind this is a simple computer simulation where we have these communities and the videos are moving between them. It can never capture all the complexity of real life, but it's a good approximation. And using this approximation, we find that these community sizes were small. So something like 10 to 20 individuals, which is consistent with all the ecological literature on this. And it actually looks like that females are moving quite a lot between these communities. So we have something like between 50 and 100% of all the women in a community actually come from other communities. And even if you have male migration or if not it doesn't make the model fit any better. So this is consistent with very low male mobility between these groups. Yeah, and that was it. So just to sum up everything. So this is the first time we have DNA from an entire community of Neonazales. And we look at the outer zones, we look at the micro-front there and we look at the white-front zone. And what we can learn from doing this is that this Neonazale population was small. So a small community size and a small, and that has been small for a while. And we also find that some individuals are related to each other. For instance, we have the father-daughter that I showed you about earlier. And so even though these communities are small, they're not isolated. So they do exchange migrants with each other and they're primarily linked by female migration. This is what our data suggests. And with that, I would like to thank you all for inviting me and thank you for listening. There are questions. Yes. Fascinating to talk with those who are historians. I've never really watched the field change dramatically with all this ancient DNA work. And maybe people don't know, but because of the problem, this is post-doc research here at Berkeley. Yes. Really, but I'm starting on this one. It's where ancient DNA started. Yes. So maybe you'll follow in line for that. I have a couple of questions, mostly about terminology. For example, the assumptions that go behind calling something a community. Yeah. And why that was chosen rather than a group or a selection or collection. Yeah, yeah. At a particular site. And the other term that I would like a little clarification is calling what is happening with mobile female migration because that is another whole set of communication. So if you can say something about why a community is justified by migration or migrant. Yeah. Which of course has a negative overcome. Yes, yes, yes, yes. So let's do the community first. So this is actually like, I come from genetics and we mainly call things groups or populations. Right. But we settled on the term of community sort of to show that so these are individuals who are living together. It's the reason why we use it, but like overlapping in time and in space. And then we have a broader term population which is more like this collection of communities. Are you happy with that answer? The other one is the library. Yeah, I'm getting that. It was just the first part of it. So migrant, yes, that sort of implies going from somewhere to somewhere else. So there's also, we also had a debate of what to call that because like for some species, not humans, not radius for some other one, you also have migration. What is their intent between this migration? And we sort of wanted to, we don't know, but that probably was like the NSL probably knew what they were doing. So we want the one with intent, the migration. The other one would be maybe more like diffusional or something like that. I just want mobility, gain more agency to those women that thinking that they were migrants and they were having to escape. That's the way in which... Yeah, that's true. Yeah, that's true. I didn't think of it like that. That's a good point. Yeah, and I think the other aspect of mobility again suggests that what you don't have necessarily is a finite rule that sticks together. That's one of the assumptions that I was talking about in my modeling approach there. Yeah, yeah. Anyway, trust them. No, it's very good point then. This is for sure not a matter that settled yet. It's just what our data indicates. So, yeah, I think there was more questions. Yeah. Thank you very much. It was a really, really interesting talk. I mean, it is fun. We have a few technical questions that I think through the implications of this. So, if we go back to the relatedness issues and how they did the aspect of like brother, sister, mother, father, mother, son, and father, daughter. So, what happens, I'm sorry, I haven't thought through this, I'm sorry. What happens when you have situations siblings who have different parents who might share a mother but not a father or a father but not a mother? Yeah. Then they will second degree. I have to think of second degree. Yeah. Okay. And in the case in the last time, I'm clear that we did not have any similar. Yes, there was no familiar basis between them. But there's an interesting little extra piece of information here. So, I did tell you that Takiskaya Cape, we're most sure about the dating. It's between 15, 16,000 years ago. But we're not. But what we actually find is that there is a mitochondria version in Takiskaya Cape that's identical to what one of the videos on Platnikov Cape has. They have like the exact same DNA sequence. And that sort of means that like, so how long can you have that without a mutation coming and changing it? And that means that you can have that for a couple of thousand years. So, that means that you can actually sort of constrain the timing of Platnikov Cape. It must have been inhabited within a couple of thousand years of Takiskaya Cape. So, this greater than 45, probably closer to 50 to 60 thousand years. And then, how do these two things relate to this? No, so, then it's over. There's been a whole study on that. That has been occupied for more, and I actually have the first author here in the room. Is it like 200,000 years? Over 200,000 years. From 55,000 years ago? No. So, that's a long, complicated matter. You see, it's about being there and then the end of the thousand, and both of them, and then modern humans in the end. But here we only see the end of the thousand. So, there's a no overlap? Yes, there is a no overlap. So, how do we know if there's a no overlap in any relationship? So, now we're more into... So, there are in the Anatols and the newsmen around in the New South Cape at this time. But we don't find any familiar relationship to any of the bones. And one more. All right, thank you. So, it's a really long relationship. It's a really long relationship. People who are related to each other. But for us, that's not always what it is. Yeah, yeah, yeah. So, it's more people who are living together. So, if we go back to the representation that you've had of the difference between the bones and the bones. This one? Yeah. As an individual in the Middle East, all right, for the long, individual in the Middle East. So, then what do you anticipate would be needed and of course, how do you know to talk about the movement between these different communities? Yeah, yeah. Because of the changes, the changes, the sample sizes. Yeah. To really know for sure, yeah. So, I can tell you about something that we wanted to do, but never ended up happening. So, of course we wanted to sequence all the individuals. You know, you can sort of imagine that maybe you can build a complete family tree. And in addition to that, we wanted to do strontium analysis, like isotope analysis of the teeth. Because, and I have a good photo of that, I think. Can I go all the way back to... Yeah. So, you can see that we are just at the mountain's end. So, there's actually a lot of different types of rock. So, there's a lot of different... Yeah, strontium isotopes are there. They have a lot of different values. So, and we have a lot of teeth. So, could you, like, look at each tooth and figure out where this individual come from? Where did it move? If you see someone who has moved from another community, can you even look at the strontium, the isotope analysis, and see do they actually do... Is there any childhood from this other cave or something like that? That's something we wanted to do, but then COVID happened, we couldn't go, and now there's a wall. So, yeah. It would have been nice to do, though. Yes. So, Mr. Moore, a lot of these questions, but you guys don't know anything about it. You know, in terms of looking at all of the work that you've done in the end... So, how does this Siberian community... How does it compare to these others you have been looked at by the Institute in terms of just the genetic... Is there a... Yes. So, I can give you a two-part answer to that question. The first one is about the sizes of the communities. And it seems that there are more Neanderthals in Europe at this time than there are here in Southern Siberia. So, the community size, but also the broader population size, they have more genetic diversity. As comes from sort of the social organization, like, do they also show female mobility? There is... There was one of the studies I highlighted here in the beginning. There is this cave from Spain where they have these four positions, like three on the mitochondria, one on the vital zone that they live in. And so, what they find is that all the females have different mitochondria, but all the males have the same. It's a very small size, and there's a lot of issues with this study, but that actually suggests the same organization as what I'm suggesting, the female mobility. But I would say that it could be nice for some more data from this cave to really know what's going on. Yeah, so in those sense... Yeah, and these are the two data that we have. We don't have DNA from all communities. And is it the same over the hundreds of thousands of years that are occupied Europe and across different places? We don't know. That would be interesting to see in the future. And a little spoiler is that there will be studies on that in the future. We already have a spot for you here in the talk. Great talk. Thank you. Are there any other questions? Yes? I think that's a great point because when you're comparing the diversity in the enterprise that you have, there's a whole array of other populations by observing different models. Yeah. What role does the apple sign play in meeting those contrasts? Yeah, so the amount of... Let's go to the homosexuality. That's your question. The amount of inbreeding. Lack of diversity, let's call it that instead. In the Anathars. You never see these amounts in modern humans. In present-day living humans. It's always much more. Of course, if you have... Let's say you only have one individual from each. You're actually still lucky because the genome is not a unit. Because there's something... I'm not going to talk about this, but the DNA you get from your parents is actually a mix of that, too. You have DNA from your parents, but you actually have both your grandparents and a quarter of your great-grandparents. So there's actually a lot of... There's a lot of independent places in the genome. So even if you only have one genome, you can with pretty high accuracy say the homosexuality in these two individuals is statistically difficult. It was a little bit of a roundabout way of saying, yes, if you want, that the community is much more. Yes? So, just thinking about the... I'm referring to this game, I guess that father and the daughter being there suggests that I get the same time or that they came back. Over time it was... So we don't know, but I will say that if I had the... the table... Yeah. I will say the most likely thing is probably that this is one event. And you can... Some of them die quite young. Some of them die quite young. So you can maybe imagine something like... Life was hard back then. And you can sort of imagine that it's just... because it couldn't get enough things or something. And then the individuals die in this case. I don't know what the answer is, but to me that's the more likely one. Did the animal bones or lithics figure any information about this one? Actually, like... It doesn't tell you how they died, but it tells us what happened after that. So we have one of the teeth. This... I don't know if you can see my arm. Let's take this guy right here. That was very hard to work with because that tooth had been eaten by a hyena. So when we look at the DNA, it's hyena DNA. Which makes... That's very different from more of the other videos. Like, oh, this must be someone coming from far away or something like that. It just makes a human DNA and hyena DNA. But that doesn't say that they were killed by hyenas, but maybe post-mortem hyenas could come out of the cave and dig around and eat them. Yes? We can't answer that. From what I understand, we can figure out now what we need to know. Yeah. Well, not marrying. We don't know if they had that kind of... Yeah. So... Yeah. Yeah. Okay. Yeah. Yeah. Ah, yeah. Yeah. No, but you have a... It's a very good point. So maybe let me find one with arrows on like this one. So when does the community sort of end and where does another one begin? So... You can imagine how these arrows go to 100%. That all means that these communities are very connected. And it's actually where does one begin and where does one end. And I'm going to say that the best-fitting one suggests like this community size and with this level of connectionness, but you can tweak the parameters, you know. Other ones can also explain the data. But that's where it would be really nice to have, you know, more DNA. Yeah. Yeah. Yeah. It's going to be really nice to have, you know, more DNA and many of these isotope analysis too. But that also is why you have so much unrelatedness within one site. And it won't be even going to start looking at the entire team. Yeah. Yes, that is a good point. Yeah. Maybe talking about it as a reading community, we like to think because I didn't get married, but you know, they're really in that position of in a reading and your community is yes, perhaps social, but also perhaps more of a reading community than a happy little social. Yeah. Yes. Yes. You know that in any case it's boring because you kind of come together and go apart, come together and go apart. In kind of a kind of bicycle and you're foraging on a the moments of the pain class or whatever that got these folks there that that was just being, you know, a thought for a time and you know, in mind have come together and a larger, you know, come up and move actually quite fluidly among the various different camps or something like that. That's exactly right. And so most of the bone, most of the bone that we eat in the stand-up house is bison bones. So they were hunting bison. And the bison are migratory. So they come to this area in a while. So we think this has only been occupied in the time of year where bison is around. And some people also suggested that in some sites, there's just so many bison bones that in order to kill and butcher all these bones without all the meat going bad, you would need a lot of individuals. So perhaps, that isn't what people, some people argue, yeah, exactly that all these communities come together to do something, maybe hunting, maybe something else. Yes, all of the above. And then they go to the farm. We often share it in English. It's a great opportunity. Thank you for having me. I will stop sharing.