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Last week, police arrested Joseph DeAngelo as a suspect in case of the Golden State Killer, an infamous serial murderer and rapist whose case has been open for over forty years. The arrest is huge news in and of itself, but for people interested in the social uses of genetic data, the way in which DeAngelo was identified—using genetic genealogy & genetic data from crime-scene samples—was noteworthy. In this blog post, we discuss some of the genetics and math underlying the way in which he was identified (see also Henn et al). Because there’s been lots of discussion of the ethics of these approaches, we will not focus on that here; see here for a collection of links & news articles.

 The use of genetic data to identify suspects is not new. In the US, law enforcement makes extensive use of their CODIS (Combined DNA Index System) database—genetic searches against the database have aided almost 400,000 investigations since the mid-1990s. The CODIS database contains the genotypes of over 13 million people, most of whom have been convicted of a crime. The genetic information included about each person in the CODIS database is relatively sparse. Most of the profiles record genotypes at just 13 sites in the genome (since 2017, 20 sites have been genotyped). Because the CODIS sites are highly variable 极光加速器安卓, CODIS genotypes identify people nearly uniquely—they are sometimes called “DNA fingerprints” . (The CODIS markers reveal more than fingerprints do, though–they can reveal considerable ancestry information, can reveal close relatives, and in some cases, it’s possible to identify genome-wide genetic profiles that “match” a particular CODIS dataset well.)

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 In the Golden State Killer case, genotyping the samples at the CODIS markers did not reveal a match—Joseph DeAngelo was apparently not included in the CODIS database. Nonetheless, the genetic search continued. Investigators apparently genotyped the crime scene sample at a genome-wide set of SNPs, or single-nucleotide polymorphisms. SNPs are the markers of choice for large consumer genetics services like Ancestry and 23andMe (as well as for genome-wide association studies [GWAS].)极光TV-V9.9手机盒子破解版_软件仓库_QQ风云网 - 用心 ...:2021-1-28 · 安卓最强照片编辑器v5.5破解版 安卓韩剧TV清爽版v4.9.0 聚合vip播放器V1.04去广告版 安卓看漫画v2.8.7破解会员版 IPTV环球电视v2.8.8 陆港澳台 VLLO视频编辑器v5.6.7会员版 极光TV-V9.9手机盒子破解版 为知笔记V7.9.8会员破解版 讯飞语记V4.4.1270会员破解

 These SNP databases are growing rapidly. The plot below shows the number of users in each of a set of repositories over the last few years (plot from here). The largest databases—AncestryDNA and 23andMe—are private. But the fourth-largest—GEDmatch, which now has about 950,000 profiles—is an online service that searches for genetic matches with any user who uploads an appropriately formatted genotype file.雷霆加速器破解免费版软件介绍 雷霆加速器永久免费版下载 ...:2021-6-3 · 雷霆加速器是热门的游戏加速神器，支持王者荣耀、阴阳师等各种不同类型的游戏加速，让玩家能够畅玩所有网络游戏，现在提供了雷霆加速器破解版下载地址，完成雷霆加速器破解版下载安装，就可伍使用雷霆加速器的功能，雷霆加速器永久免费破解版让用户能够免费

 Investigators searched for the suspect’s profile by making a personal user account and uploading a genotype file created from the SNP data obtained from crime-scene samples. To do this, the investigators must have created a data file mimicking the SNP set and file format provided by some genetic genealogy company . There was no exact match in the GEDmatch database—indeed, investigators did not expect that DeAngelo would have uploaded his own data—but the trail was not yet cold. The police could still run a  search scanning the database for relatives of the suspect. If it is possible to identify a close relative, then the search for the suspect will be narrowed considerably, even if the suspect is not in the database. This is similar to the familial searching done using the CODIS database, which is legal in some States. (But it is imperfect, see work here and here from Rori Rohlfs and colleagues). However, in the CODIS database, familial search efficacy is limited to close relatives (usually parents and siblings, and more tenuously uncles/aunts/nieces/nephews and first cousins). Thirteen microsatellite markers’ worth of information is simply not enough to distinguish a distant cousin from an unrelated person. With the hundreds of thousands of markers on a typical SNP chip, familial searching is much more powerful—third cousins can be found most of the time, and many (but not all) fourth cousins can be found too. A sample set of profile matches from GEDmatch is shown below:

 Looking at SNP-based relative matches in GEDmatch, police found what they needed in the form of 10 to 20 likely relatives. These likely relatives represented third-to-fourth cousins of DeAngelo, most of whom he had probably never met. Using this genetic data, in combination with genealogical information about these relatives, the Golden State Killer investigation narrowed to one extended family, eventually honing in on DeAngelo himself.

 Geneticists and genetic genealogists have been using these techniques for some time; the GEDmatch database exists because genealogists wanted to share genomic resources to help identify relatives, allowing families to be reunited (see here). Widespread reporting of the method used to identify DeAngelo as the suspected Golden State Killer has inspired a surge of interest in genetic privacy (see here for a general review of topic). Though DeAngelo’s capture is widely celebrated, people are also understandably surprised that the decisions of third or fourth cousins can potentially expose one to surveillance. In this post, we explore some simple models to ask questions about the extent of surveillance that is possible using the methods employed in the Golden State Killer case.

 Two opposed phenomena govern the effectiveness of familial searches on genetic databases, one genealogical and one genetic. The genealogical phenomenon, which we could call “genealogical blowup”, is that the number of relatives one has at a specified degree of relatedness increases as the relatedness becomes more distant. For example, whereas a typical person may have one, two, or three siblings, he or she will usually have a large number—dozens or even hundreds—of third cousins (or “third-degree” cousins). The picture below shows the genealogical blowup phenomenon. On the left, we see the probability that a random person has at least one cousin of degree p in a database (depending on the size of the database), and on the right, we see the average number of cousins contained in a database. The number of genealogical cousins one has—where genealogical极光下载下载_极光下载绿色版_极光下载2.0.3-华军软件园:2021-5-2 · 极光下载致力于提供一个最高速的下载工具。极光下载不仅支持多连接 。 智能的下载调度： 极光下载采用了智能分块、智能调度、智能镜像分析等。 简洁为美的人性化设计： 极光下载专注于简洁为美的设计。从界面到功能都保持最简洁的设计。 纯绿色：

(The calculation on the left is based on the work of to Shchur and Nielsen. To make our calculations, we adopt some simplifying assumptions that are certainly wrong—namely complete inbreeding avoidance, monogamy with random mating, non-overlapping generations, random participation in the database, and population sizes similar to US census sizes across the last few generations. However, these calculations are useful to get a rough sense of the problem. Some details and pointers to other sources are in the notes below. The primary caveat that our assumptions entail is that our computations apply most directly to ancestry groups that are well represented in the database. GEDmatch is mostly composed of profiles from Americans of European ancestry. Recent immigrants to the US and people from non-European backgrounds are likely to find fewer relatives in GEDmatch than are European-Americans whose families have been in the US for a few generations.)

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The genomic material you share with your first cousin is the overlapping fragments of genome that both of you have inherited from your shared grandparents. Below we show a simulation of you and your first cousin’s genomic material that you both inherited from your shared grandmother (details about how we made these simulations here). In the third panel we show the overlapping genomic regions in purple. These are regions where you and your cousin will have matching genomic material, due to having inherited it “identical by descent” from your shared grandmother. (If you are full first cousins, you will also have shared genomic regions from your shared grandfather, not shown here.)

Now consider the case of third cousins. You share one of eight sets of great-great grandparents with each of your (likely many) third cousins. On average, you and your third cousin each inherit one-sixteenth of your genome from each of those two great-great grandparents. This turns out to imply that on average, a little less than one percent of your and your third cousin’s genomes (2 * (1/16)^2 =0.78%) will be identical by virtue of descent from those shared ancestors. If you do share one percent of your genomes, then your relationship to your cousin will likely be detectable using SNPs—the shared portions will be concentrated in relatively long stretches of chromosome that are easy to see statistically. But the more interesting thing is the variation around that average. There is a non-trivial chance (~2%) that you will actually share no identical segments of your genome with your third cousin—in that case, we say you are genealogical cousins but not genetic cousins.

Here’s an example where third cousins share some blocks of their genome (on chromosome 16 and 2) due to their great, great grandmother:

Here’s an example where the same individual shares the same great, great grandmother with another 3rd cousin, but has no genetic sharing due to that connection:

As the degree of relatedness decreases—on to fourth cousins, fifth cousins, and so on—an ever-larger proportion of one’s genealogical cousins will not be genetic cousins. The figure below shows the proportion of degree-p cousins with which one expects to share either at least one, two, or three genetic blocks. Sharing 1 block is not very informative (see here). Individuals with whom one shares three or more large genetic fragments are likely strong leads. (Again, the assumptions used here are explained in the notes below.)

An appreciation of these two phenomena—genealogical blowup and the noisiness of genetic inheritance—is crucial for understanding how public SNP databases might be used by law enforcement in the future. There is a tradeoff. One typically has a large number of genealogical eighth cousins, but only a small proportion of them will be genetic cousins, and even these are often impossible to identify as such. On the other hand, it is easy to detect one’s first cousins, but because one typically has a small number of first cousins, the probability that a random person has one in a genetic database is low unless the database is very large. (Another factor relevant for law enforcement is that closer matches are more useful; they narrow the pool of possible suspects more.) The image below combines the considerations illustrated in the previous plots, showing the expected numbers of genetic cousins in the database. The tradeoff of genealogical blowup and the noisiness of genetic inheritance is optimized in the third to fifth cousin range—you have a lot of genealogical cousins at this degree of relatedness, and many of them will be detectable genetic cousins. Because closer relatives are more useful to law enforcement than more distant relatives, it’s likely that many of the cases that could be solved by these methods would involve some mix of 2nd, 3rd, and 4th cousins.

The Golden State Killer results are close to what we expect given the size of the GEDmatch database. Under the assumptions we make here, it’s likely that a large percentage of people have at least one high-confidence genetic cousin in GEDmatch, and the number of 3rd-4th cousins found for DeAngelo—10 to 20—is not too far from the expectations. It’s striking that uploading one’s information to a matching database potentially opens up a large number of other people to eventual identification, and that most of these people are distant enough relatives that one would likely never have met them. To illustrate, consider that 13 million individuals in CODIS likely wouldn’t reveal a familial match because only very close relatives are detectable in CODIS. But using the far smaller GEDmatch database (~1 million individuals), investigators tracked DeAngelo down. As Yaniv Erlich put it recently, “You are a beacon who illuminates 300 people around you.” It’s also striking that we’re already in an era in which familial searches against publicly accessible SNP databases are feasible for a lot of cases, probably the majority of cases where the suspect has substantial recent ancestry in the US—the public datasets are big enough (or will be soon). The limiting factor here may be the genealogical work to trace distant cousins through family trees, but big public datasets might make the genealogical task easier too. From here, it’s a question of deciding the circumstances under which we as a society want these familial searches to be used.

Doc Edge (@DocEdge85) & Graham Coop (@Graham_Coop) 

Thanks to the Coop lab and Debbie Kennett for helpful comments on an earlier draft.  

Notes

A pth cousin is a person with whom one shares an ancestor (in our model, an ancestral couple) p+1 generations ago (your great(p-1) grandparents). If there’s no inbreeding in one’s recent family tree, then one is descended from 2^p ancestral couples p+1 generations ago. A pair of individuals in the present are pth cousins (or closer) if their sets of 2^p ancestral couples overlap—they share ancestors p+1 generations ago. Let’s assume that there are Np potential ancestors in N/2 couples, p generations back. If each of these couples have the same probability of having children and there is not too much variation in family size, we can view the problem as if people in the present “choose” their ancestors p+1 generations ago at random. Your ancestors were no doubt very special people, but as far as this model is concerned they were just 2^p random draws from all the couples who’ve left descendants. To calculate the probability that you and I are pth cousins, we just need to calculate the probability that our two sets of 2^p ancestors overlap (note that this assumes monogamy, i.e. that we’ll be full not half cousins, but even if that wasn’t true, that just alters things by a factor of two). Now, we have something close to a classic probability problem: we draw a set of 2^p balls at random from an urn with Np balls, replace the balls in the urn, and repeat the draw of 2^p balls—what is the probability that at least one ball is a member of both sets of 2p balls?

The probability that you and I are pth cousins is roughly (4^p/(N_p/2)), when N_p<<2^p ie when your ancestors are a small fraction of the total people in the population. In a current-day database of K individuals, drawn from the same population as you, your expected number of pth cousins is K*4^p/(N_p/2). Two factors make this blow up quickly back over the generation. First, 4p grows quickly back over the generations; second, population sizes have increased rapidly in the recent past, which means that N_p  declines quickly with p (because p counts generations backward in time).  

One of biggest uncertainties in our calculations is the size of the pool of possible ancestors. Our calculations should therefore be viewed as crude approximation. Our calculations are based on assuming that the population size of possible ancestors is given by the census population size of the USA. To get the census population size we assume a generation time of 30 years, and take the population size in the decade 1950-30*(p+1). We assume that roughly ½ of the individuals in the population are potentially parents, and that 90% of potentially parents have children. We impose a floor on the population size that it cannot drop below 1 million potential parents, to reflect the fact that for people of European-ancestry, the pool of ancestors back then would also include Europe. Given the large variation in family sizes N should likely be lower still, as variation in family size decreases the effective N further.

Shchur and Nielsen recently worked through the probability that you have no pth cousins in a database of K individuals, in a model similar to that described above. The model Shchur and Nielsen use is more realistic than the one we consider here—it allows for some inbreeding and takes explicit account of the fact that some couples will not have children. They find (their equation 7) that the probability that an individual has no pth cousins in the database, given a fixed population size of N, is approximately exp(-2^(2*p-2)*K/N).

The math underlying the genetic calculation is described in more detail here. To summarize: if you share two ancestors p+1 generations with your pth cousin, then you share a particular autosomal chromosomal region with probability 2*(1/2^p+1 -1). You have 22 autosomal chromosomes, and each generation, recombination happens in ~34 places on these chromosomes. Looking back p+1 generations, your chromosomes are broken up into approximately (22+34(p+1)) chunks, which are spread across your ancestors. Likewise, your relative’s genome is broken into (22+34*(p+1)) chunks. Because recombination events rarely happen in the exactly same place, your two genomes combined are broken into (22+34*d*2) pieces. As each of these is inherited identical by descent to both you and your cousins from that ancestor with probability 1/2^{2(p+1 -1)}, you and your cousins should expect to share EB=1/2^{2(p+1)-1 2*(22+34(p+1)) blocks of your autosomal genome. The probability that you share 0 blocks is approximately exp(-EB), while the probability of sharing 2 or more blocks (Q_p腾讯云视听_腾讯云视听极光_腾讯云视听官网 - 云+社区 - 腾讯云:网络视听大会谢幕，腾讯云五大方案齐亮相！image.png 中国网络视听大会素有“年度风向标”之誉，为了此次视频产业盛会，腾讯云特意准备重磅新品 腾讯明眸-极速高清解决方案视频智能分析解决方案月光魔方-ai视频广告暨流量变现方案腾讯云数字版权保护方案ugsv短视频sdk及美颜动效五大解决方案 ...}

Putting all of this together, your expected number of genetic pth cousins is (Q_p*K*4^p/(N_p/2). That’s the solid line plotted in the final figure.

[Part of a continuing set of blog posts on 极光加速器官方网站]
In the last post I described how you are descended from a vast number of ancestors, from all over the world. But how much of your genome traces back to each of these ancestors?

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Let’s imagine that the individual is you. The maternal genome (the copy from your mum, note correct spelling on mum) is shown on top, and the paternal genome on the bottom. I paint each chromosome with a colour indicating where an individual’s genetic material has been copied from. So for example, you inherited the entirety your father’s paternal copy of chromosome 21; see how the entire lower, paternal copy of your father’s chromosome 21 is highlighted. So you have none of your paternal grandma’s copy of chromosome 21. Your paternal grandma had a full copy herself (she transmitted her chromosome to her son), but none of that is in your genome, as your father didn’t transmit it to you. Your copy of chromosome 21 from your mother is a mosaic (a recombinant) between her maternal and paternal copies of this chromosome, note how the painting of this chromosome changes from bottom to top as we move left to right along chromosome 21. Going another generation back see how this means that you have inherited the left part of chromosome 21 from your maternal grandma, and the right half of chromosome from your maternal grandfather.

Now let’s track your genome up your male lineage (technically your patrilineage), following your father, your father’s father, etc :

Each generation you go back, you inherit less of your genome from any given ancestor. Six generations back, you only inherited a small section at the tip of chromosome 13, and a section of chromosome 5. By chance, those fragments are both inherited from great-great-great-great-great-great grandfather’s maternal copy of the genome, the one he received from his mother. Thus, moving one more generation back, we find that none of your (autosomal) genome has been copied down over the generations from this male lineage. The entirety of the two copies of your genome is present back then, scattered across your sixth four ancestors, it just happens that none of it is derived from this individual. Despite being your genealogical ancestor, he is not your genetic ancestor, none of their story has been passed down to you. If you are female none of your genome descends from him, if you are male you will have his Y chromosome but your daughters will have nothing from him. Your ancestor had a full genome, and they transmitted their genome to their children, and their children in turn transmitted some of it to their grandchildren, but over the generations it was whittled down till by chance none of it is in you. His genomic story may live on in some of his other descendants, e.g. your sixth cousins, but not in you.

In the figure below I show a simulation of how much of your autosomal genome is present in each genealogical ancestor as we go back up the generations.

[discussed in more detail here]
Your genome is shown in the middle, in the next semi-circle out are your two parents (blue and red), then your four grandparents, and so one as we move out. At each level, the intensity of the colour indicate how much of your autosomal genome is in that ancestor, the total contribution to your genome sums to 100%.
For the first number of generations, all of your genealogical ancestors are your genetic ancestors, and contributed big chunks of your genome to you. But as we go further back we start to run into ancestors who contributed no genetic ancestry to your genome (these individuals are indicated by the white spaces). For example following the male lineage of fathers’ lineage back on far right, marked with an blue arrow; there, seven generations back, is that first ancestor who contributed nothing to your autosome. Moving back through the generations, more and more of your ancestors do not contribute to you genome”. Your family tree is soon full of genetic holes, ancestors who contribute no big regions of your genome to you, see how more and more of your ancestors are coloured white as we move out through the semicircles. Below I show the rapid increase of your number of genealogical ancestors (red line 2^k) contrasted with your number of genetic ancestors (black dots), which grows far more slowly:

Your genetic ancestors rapidly become a tiny fraction of your total number of ancestors. The probability that you inherit genetic material from an ancestor drops off rapidly as we move back over the generations. I discuss these ideas in more depth here and here.

In the last post, I described how your vast number of ancestors meant that you were descended from nearly everyone in the world more than a few thousand years back. But you are only a genetic descendant of a relatively few of those individuals, as most have left no trace in your genome. For example, you might be able to trace a particular route through your pedigree to Charlemagne, 极光超级信息发布破解全过程_jushiya的专栏-CSDN博客:2021-8-1 · 破解了伍后，一使用，拷，才发觉这软件作者在骗钱， 这种破东东也要几百人民币 使用“极光超级信息发布”发到对方的机器， 对方的机器必须是有伍下两个条件的， 第一，对方的机必须是开机的，｛这点最难了｝, but there’s less than a 1/100 million chance that you’re a genetic descendant of Charlemagne due to that particular connection through your pedigree. Forty generations back most of your genome traces back to a random subset of around twenty-six hundred individuals out of all your millions of ancestors. It’s unlikely that Charlemagne is one of them.

While your family tree is staggeringly vast and geographically widespread, your genetic ancestry is likely more restricted. To illustrate this, consider the simulation shown in the gif below. Similar to those pictures in the last post, I trace back your ancestry over the generations. But now I’ve coloured genealogical ancestors in red, genetic ancestors are overlain in blue.

The x axis gives the geographic location of the ancestor. I’m simulating a population of 500,000 individuals spread out over 50 geographic regions. The vertical lines give the boundaries between these regions. Each generation back an individual’s parent comes from a neighbouring region with a 25% probability, and from a randomly chosen region with a 1/50 probability. Each time the gif ticks over, the histogram shows you how many ancestors you have in each region that number of generations back.

Up to about 7 generations back all of your ancestors are genetic ancestors (the blue perfectly overlays the red, but soon after that many of your ancestors make no major genetic contribution to you. In the figure below I show a zoomed in histogram of the geographic locations of ancestors in a simulation 17 generations back

You soon have genealogical ancestors from all over the place, yet there are geographic regions in which you have no recent genetic ancestors. Some of your genetic ancestors are from distant locations, but most are much more geographically restricted. That’s because the majority of routes back through your family tree trace back ancestors who stayed closer to home.

A thousand years back I’m descended from nearly everyone everywhere in Europe. I’m related to these individuals via millions of lines of descent back through my vast family tree. Yet the majority of the lines back through my pedigree trace to people living in the UK and Western Europe. Many lines trace back to more distant locations, but these are relatively few in number compared to those tracing back to closer to home. Ancestors along each of these lines are (roughly) equally likely to contribute to my genome. Therefore, most of my roughly 2600 genetic ancestors from 1000 years ago, who contributed the majority of my genome to me, will be random people living in the UK and western Europe at that time (who happened to leave descendants).

Looking back a few thousand years more, I’m a descendant of nearly everyone who ever lived almost everywhere in the world (at least those who left descendants, and many did). Yet most of the just over ~6000 individuals from that time who contributed the majority of my genome to me will mostly be found all over Western Eurasia. There’s nothing much special about these individuals who happen to be my genetic ancestors a few thousand years back. They’re likely not royalty. My genetic ancestors are just a random subset of all of my genealogical ancestors, they just happen to be my genetic ancestors due to the vagaries of meiosis and recombination.

This fact also means that my set of genetic ancestors, say a thousand years ago, likely doesn’t overlap much with yours, even if you’re from the UK. However, my genetic ancestors will overlap with some (random subset) of the people currently in the UK (and Western Europe). This is why reputable genetic ancestry companies can tell you something infortmative about where your ancestors lived in the past. When 23&me tells me that most of my genetic ancestry traces back to the UK, they’re telling me where the bulk of my ancestors lived, a few hundred to a thousand years ago, even though I have ancestors all over Europe. Although honestly I think they should also phrase this as something like: “the majority of individuals who are Graham’s eighth through sixteenth-cousins currently live in the UK”. That phrasing is much closer to what they are really doing when they look at your genome. Should I be excited if a genomic ancestry company tells me that a few megabases of my genome traces back Scandinavia? Should I start to imagine that my ancestors were Vikings sailing the seven seas? Well, I already knew that my ancestors lived all over Europe, and so I already knew that my ancestors included many Vikings. These genomic connections can be fun, but if I have Scandinavian genomic ancestry and someone else in the UK does not, that does not mean that I can claim they do not have Viking ancestors, nor that I’m more Viking than they are. Such differences are more likely the result of the randomness of meiosis than an excess of berserker blood in your ancestors.

Does it matter that I’m not genetically related to all of my ancestors? In talking about these topics I’ve been told things like “I won’t bother tracing my family tree back more than eight generations, as I guess many of those people aren’t my ancestors”. But any individual to whom my family tree traces back is my ancestor. My great^8 grandmother had a profound influence on who her son (my great^7 grandfather) was, and she shaped who many of my ancestors were. Her genomic story was passed down to my grandfather and father. The fact that my father, due to the randomness of meiosis and recombination, did not pass on the small part of his genome that he had inherited from her, to me seems largely irrelevant. Even if I inherited a small fraction of my genome from her, it would mean little in terms of how I resemble her. She is just one of the hundreds of genomic book passages that may been passed down from my ancestors in her generation.

Looking further back still, some sixty thousand years ago modern humans interbred with Neanderthals (and Denisovans) as our ancestors spread out of Africa. Note that I did mean to say“our ancestors”, as in, absolutely everyone’s. Everyone in the world is descended from those modern humans who first met and mated with Neanderthals, just as we are all the descendants of the many groups of people who remained in Africa. If we look carefully, using computational tools that detect subtle genomic signals, I can see that around 2% of my genome traces back to Neanderthal ancestors (this 2% of Neanderthal ancestry is scattered all over my genome like Neanderthal confetti). If you have a lot of Sub-Saharan ancestry, we would likely detect many fewer Neanderthal blocks of ancestry in your genome. You’re still descended from Neanderthals, but fewer of the routes back through your family tree trace back to Neanderthal than through mine. The fact that any of us carry the genomic trace of Neanderthal interbreeding is a fascinating insight into all of our family trees, and one of the most surprising findings in human genomics in the past decade. That this Neanderthal ancestry isn’t evenly split over everyone in the world is a statement that we vary in our degree of relatedness to people who lived tens of thousands of years ago. But this variation in our pedigrees are quantitative rather than qualitative; we are bound together much more by our vast shared family tree than we are divided by it.

These ideas are sometimes deeply unintuitive. I’ve studied them for over a decade and still truly cannot really get my head around how I can be descended from so many people, and yet genetically to so few of them, just a few thousand years ago. However, grappling with these ideas is important. All of us will have to get much more used to thinking about these ideas of genomics, ancestry, and family trees. Millions of people have chosen to be genotyped for ancestry tests, many more are being genotyped as part of large panels for medical genetics research. What genomics can and cannot say about our family history will become much more central to how we perceive ourselves over the coming decade.

In the coming posts we’ll bring into focus more seemingly contradictory ideas. We’ll see that despite the fact that everyone is related just a few thousand years back, I have to go back over a hundred thousand years to find the common ancestor of all of our mitochondria. Even more surprisingly, we’ll see that the copies of a chromosome I have from mother and father last share a common ancestor more than half a million years ago.
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*What I’m describing here is the recombination process of crossing over. You will also inherit small stretches of DNA from either parent due to gene conversion. You can think of gene conversion as your mum switching from copying out her mother’s (your maternal grandmother’s) copy of chromosome 21 to copying from her father’s (you maternal grandfather’s) copy for a short stretch. There’s more of these gene conversions per meiosis than crossover (~300 hundred compared to ~30 on average). However, these gene conversion events are just short stretches of copying, just a few hundred letters (bases) long, while crossovers demark switches between long stretches of copying between the parental chromosomes (for 100s of millions of bases). Therefore, crossovers determine the bulk of your ancestry. That said these gene conversion events do mean that you have more genetic ancestors than the numbers above would indicate, here’s the graph from above with genetic ancestors due to both gene conversion and crossing over:

Your number of genetic ancestors including gene conversion keeps up with you genealogical common ancestors for long than the number of genetic ancestors tracking crossovers alone. However, these extra recent genetic ancestors due to gene conversion contribute very little to your genome. For example, 14 generations back you you have an extra ~7000 genetic ancestors due to gene conversion, compared to the ~950 due crossover alone. But each of these extra “gene conversion” genetic ancestors contribute only a few hundred bases to you, while the ones due to crossovers contribute several million bases. Less than 1/5000th of your genome traces back to all of these gene conversion genetic ancestors combined 14 generations back. Therefore, through the post I’ve ignored these extra gene conversion ancestors, and framed it as where most of your ancestry traces back to (note the use of weasel words like “most”, and “little to none”). I think that is a more accurate reflection of where your ancestry traces back to, but I did struggle a bit with how to simplify these complex ideas.

In the last post I discussed the idea that that we are all related in the recent past (building off the work of Chang, Derrida, and colleagues). This idea can be confusing; for many of us our ancestors all seem to come from one or a few geographic locations. How does this geographic restriction affect the relatedness between modern day humans?

I’m originally from the UK, but I’ve been in the States for a third of my life. However, in general my ancestors weren’t big travelers. My family is from Yorkshire and Staffordshire in England. My mum traced our family tree back a few years ago; my photocopy of it is stuffed in a drawer somewhere. A bit further back, apparently many generations of my granddad’s side of the family are buried in a churchyard in a village (I think) somewhere outside of Melton Mowbray. No seafaring life with a kid in every port for my ancestors. Unsurprisingly then my ancestry report from 23&me makes for dull reading, and says my recent ancestry is all from the UK. How then do I have ancestors all over the world just a few thousand years back? Is it really possible that I am related to nearly everyone who lived in the entire world?

The key to this is that I, and you, have vast number of ancestors just a short time into the past. Fourteen generations back –roughly four hundred years ago– you have over sixteen thousand ancestors. Twenty generations back you have (potentially) over million different people as ancestors. Even if only a few people in the past emigrated from a specific country to the country you’re from, you are likely descended from those immigrants.

To illustrate this, consider the following simulation. We track your ancestors back over the generations as we did before. But now instead of coming from a well-mixed population, I’ve divided up the population of a million individuals into ten regions. These regions are arrayed along a line for simplicity, and the boundaries are shown as vertical lines. Each generation back, there’s a 1/50 chance that an individual’s parent comes from a neighbouring region. We see our first local migration event 4 generations back; one of your 16 great-great-grandparents is from the neighbouring region. See how their pedigree in that region rapidly expands; you soon have many ancestors in this second region.

On top of the local migration, in these simulations there’s a 1/5000 chance that an individual’s parent comes from some more distant region (chosen at random). We only see these long distance migrants deep in your pedigree. These migration events are occurring in the population all the time. However, It’s unlikely that any of your recent ancestors is one of these immigrants, as there’s only a low rate of immigration. But you have vast numbers of ancestors further back, and so further back you start to be descended from them too. See how eleven generations back you have over two thousand ancestors, and a couple of them are from distant regions. Looking slightly further back, each of your immigrant ancestors has many ancestors from his or her distant homeland. You’ll soon be descended from nearly everyone in these distant regions.

This rapid spatial expansion of your ancestors means also that you share recent genealogical ancestors with present-day individuals in distant locations, as both your and their ancestors are found all over the place. To illustrate this, I’ve run our simulation for another individual who lives at the other end of the set of regions from you. Below I plot your two family trees together.

Maybe you think 1/5000 individuals being an immigrant from some distant location is too high, and it likely is for distant locations or other continents. However, even if it were as low as 1 in a million, we only have to go back roughly 600 years to find you descended from one of these rare long distant immigrants. A thousand years back I’m descended from nearly every traveler of the high seas who set foot in Europe. Well at least those that left descendants there; if they had an unfortunate accident with a short-sword before conceiving a child, then they’re out of luck. As a result of the ones who had kids, I have millions of ancestors on every habitable continent just a few thousands of years ago.

I’m not an anthropologist of distant oceanic islands, so I can’t tell you for sure that there’s nowhere in the world so remote (and so long isolated) that we can rule out that you recent shared ancestry with people from these remote regions. However, I can confidently tell you that you’re related to nearly everyone in the world via ancestors just a few thousand years back. Even for the remotest locations in the world, I suspect that they too are soon part of our family tree. as nowhere has been completely isolated for many thousands of years.

Some links to related topics:

Simulations by Brian Pears of the spread of ancestors across the UK.

Kaplanis et al (page 6) from Yaniv Erlich’s group explore patterns of dispersal using vast human genealogies. See a video of their graphic depiction of dispersal here.

Jerome Kelleher et al explore technical aspects of the spatial spread of your ancestors, and calculate the rate of spread of the rapidly expanding geographic region your ancestors are drawn from. We’ve used related ideas to calculate dispersal distances from genetic data (see 极光加速破解).

Thanks to Vince Buffalo, Doc Edge, Emily Josephs, and Jeff Ross-Ibarra for feedback on an earlier draft of this post.