ancient DNA

Science today has released the new paper on the Denisova high-coverage genome by Mattias Meyer and colleagues from Svante Pääbo's group [1]. There is a lot of material in the supplements of the new paper, and it will take some time to work through implications.

The basics are quite simple: The paper confirms the initial interpretation of the genome by David Reich and colleagues [2] in most respects. The mixture with a whole-genome sample from Papua New Guinea is estimated at 6% Denisovan ancestry. Confirming the later paper by Reich and colleagues [3], the new analysis finds no significant evidence of Denisovan ancestry in a mainland south Chinese (Han Dai) individual, and can exclude it down to a very small fraction:

However, in contrast to a recent study proposing more allele sharing between Denisova and populations from southern China, such as the Dai, than with populations from northern China, such as the Han (17), we find less Denisovan allele sharing with the Dai than with the Han (although non-significantly so, Z = –0.9) (Fig. 4B) (table S25). Further analysis shows that if Denisovans contributed any DNA to the Dai, it represents less than 0.1% of their genomes today (table S26).

That is a mystery to be explained. How did Asians end up lacking any evidence of Denisovan ancestry, when the peoples of Sahul (Australia and New Guinea) have six percent? It's nutty! The early modern humans who were the ancestors of present Sahulian peoples surely came from Asia, and they surely mixed with Denisovans there somewhere, right? But today there's no sign that present Asian peoples descended from those early Asian peoples.

We must, I think, conclude that there was at least one, and possibly several episodes of massive population movement across South and Southeast Asia.

I have recently completed a review of the analogous problem for Neandertals in Europe -- late and early Neandertals themselves appear to have been a dynamic population. I'm now working on a review of the situation in Southeast Asia. We may fundamentally have to look at the archaeological record in a new, and much more dynamic, way than has been the case.

Neandertal gene flow

To me at the moment, this is the most interesting paragraph of the new paper:

Interestingly, we find that Denisovans share more alleles with the three populations from eastern Asia and South America (Dai, Han, and Karitiana) than with the two European populations (French and Sardinian) (Z = 5.3). However, this does not appear to be due to Denisovan gene flow into the ancestors of present-day Asians, since the excess archaic material is more closely related to Neandertals than to Denisovans (table S27). We estimate that the proportion of Neandertal ancestry in Europe is 24% lower than in eastern Asia and South America (95% C.I. 12–36%). One possible explanation is that there were at least two independent Neandertal gene flow events into modern humans (18). An alternative explanation is a single Neandertal gene flow event followed by dilution of the Neandertal proportion in the ancestors of Europeans due to later migration out of Africa. However, this would require about 24% of the present-day European gene pool to be derived from African migrations subsequent to the Neandertal admixture.

This is a very interesting result, partially because it is the opposite of what we are finding. As I explained earlier this year, we are finding Europeans to share more Neandertal alleles than Asians do. The difference in our results has been much smaller than 24%; really only an increase of less than 0.5% on the whole genome, or maybe 10% relative to the overall amount in Europe (which is on the order of 3%).

My initial reaction to this difference is that it reflects the sharing of Neandertal genes in Africa. Meyer and colleagues filtered out alleles found in Africa, as a way of decreasing the effect of incomplete lineage sorting compared to introgression in their comparison. But if Africans have some gene flow from Neandertals, eliminating alleles found in Africans will create a bias in the comparison. If (as we think) some African populations have Neandertal gene flow, that probably came from West Asia or southern Europe. So as long as the present European and Asian (and Native American) samples have undergone a history of genetic drift, or if (as mentioned in the quote) they mixed with slightly different Neandertal populations, this bias will tend to make Asians look more Neandertal and Europeans less so.

Anyway, this demands further investigation. The Denisova genome makes a more compelling outgroup for these kinds of comparisons, because it is much closer to us than chimpanzees are. But it isn't really an outgroup because it shares alleles by descent with Neandertals. So it takes some clever genetics to compare the distributions of derived alleles in these genomes in terms of introgression versus incomplete lineage sorting.

Denisovan demography

It has become possible to make some good estimates of demographic history using only a single diploid genome, using a technique developed by Li and Durbin [4]. Meyer and colleagues applied this technique to the Denisova genome, finding that its genetic history contrasts with that of living human populations:

To estimate how Denisovan and modern human population sizes have changed over time we applied a Markovian coalescent model (22) to all genomes analyzed. This shows that present-day human genomes share similar population size changes, in particular a more than two-fold increase in size before 125,000–250,000 years ago (depending on the mutation rates assumed (23), Fig. 5B). Denisovans, in contrast, show a drastic decline in size at the time when the modern human population began to expand.

There is not yet enough data from Neandertal genomes to apply the same method, but to the extent that we understand their diversity, they show a similar picture. These archaic humans in Eurasia had much, much smaller effective population sizes than the ancient population of Africa. That's not surprising, given what we understand about ancient hunter-gatherer population dynamics.

What may be a bit more surprising is the geography. We know that Neandertals of Europe and Central Asia lived in an environment that was relatively marginal for their technology and subsistence pattern. The Denisovan population could well have lived in parts of South or Southeast Asia -- subtropical and tropical areas comparable to Africa in their ecological diversity and resource richness.

We might have imagined that the Denisovan population would be more diverse than Neandertals -- that it might have been comparable in diversity to part of Africa, if not the entirety of Africa. The genome is inconsistent with that picture.

How can we explain the apparent contrast?

1. Maybe Denisovans didn't live in South or Southeast Asia at all. If not, that demands that we explain how Australians got their genes.

2. Maybe the population was geographically extensive and diverse, but the genome from Denisova Cave doesn't represent it well. If so, we might discover that Sahulians actually have even more ancestry from this group. Alternatively, we might find that the early history of the population was widely shared, but the recent history diverged between Siberian and other branches of the Denisovan-inhabited region.

3. Maybe African diversity emerged from a much more complex series of interactions than we now appreciate. The demographic model of Li and Durban doesn't encompass admixture, just the probability of gene coalescence across time. We have recently begun to appreciate the reality of ancient African population structure. If those initial African populations were more divergent from each other than Neandertals and Denisovans, their later mixture would give rise to a picture of early population expansion, even if each of them had relatively low (Denisovan-like) diversity.

This picture is already complicated. It will get more so. We have a long way to go before the archaeology of MSA and Middle Paleolithic peoples will be reconciled with these genetic models.

The "modern human" catalog

I think it's tremendously interesting that the authors have compiled a list of gene variants shared by living humans that are absent from this high-coverage archaic human genome. It's a first step to identifying networks of genes that have been subject to recent evolutionary change in human ancestors.

That being said, the list of genes itself doesn't lend itself to concrete conclusions:

One way to identify changes that may have functional consequences is to focus on sites that are highly conserved among primates and that have changed on the modern human lineage after separation from Denisovan ancestors. We note that among the 23 most conserved positions affected by amino acid changes (primate conservation score ≥ 0.95), eight affect genes that are associated with brain function or nervous system development (NOVA1, SLITRK1, KATNA1, LUZP1, ARHGAP32, ADSL, HTR2B, CBTNAP2). Four of these are involved in axonal and dendritic growth (SLITRK1, KATNA1) and synaptic transmission (ARHGAP32, HTR2B) and two have been implicated in autism (ADSL, CNTNAP2). CNTNAP2 is also associated with susceptibility to language disorders (27) and is particularly noteworthy as it is one of the few genes known to be regulated by FOXP2, a transcription factor involved in language and speech development as well as synaptic plasticity (28). It is thus tempting to speculate that crucial aspects of synaptic transmission may have changed in modern humans.

Interesting. I can imagine a Ph.D. dissertation looking into the function of each of those genes. It is surely true that in the last 300,000 years, human brains have been evolving. But why these genes as opposed to others? And how many regulatory changes (as opposed to amino acid changes) may have been further involved?

Maybe even more interesting: How many times will the human alleles be found in some other Denisovan (or Neandertal) genomes, and how often will the "archaic" allele be found in anyone living now?

A limited series of comparisons is too small to exclude that the range of variation will overlap, as fossil analysts have known for a long time. So we will need to work on extending our knowledge of the range of variation within living people, by increasing the sample of genomes representing populations around the world, particularly in Africa.

The technology

Of course, the most exciting thing about the new paper is the proof of concept for future high-coverage archaic genomes. The lab was able to generate the high-coverage sequence using its existing samples, by sequencing single-strand DNA instead of requiring double-strand DNA. This is a massive advantage when working with ancient DNA, because damage to the sequence often prevents double-stranded DNA from being amplified.

The paper makes explicit that the Denisova phalanx simply has better endogenous DNA preservation than any other specimen known. That being said, the new sequencing method has greatly increased the sequence yield from the sample:

We applied this method to aliquots of the two DNA extracts (as well as side fractions) that were previously generated from the 40 mg of bone that comprised the entire inner part of the phalanx (2, 8). Comparisons of these newly generated libraries to the two libraries generated in the previous study (2) show at least a 6-fold and 22-fold increase in the recovery of library molecules (8), which is particularly pronounced for longer molecules (fig. S4).

It would be too soon to say that a similar increase in yield will happen for other specimens, but obviously, this may bring higher coverage into reach for several specimens that are currently only sequenced at very low coverage, including the Vindija, Mezmaiskaya, and El Sidron Neandertals. We will have to wait and see how the new technique affects ancient DNA recovery going forward.

I keep telling people that I think it's exciting that research into human evolution is now pushing technology forward. It has often been that paleoanthropology uses technological advances in other fields. But with ancient DNA, we really see an organic growth of technology along with research questions about our evolution. In our work on the ancient genomes, we're making some progress pushing forward knowledge about human biology by understanding human evolution. Evolution really is the fundamental principle of biology, but using evolution to learn about biology sometimes requires traveling through time. Ancient DNA gives us a time machine bringing new insights into reach.

References

Last month, David Reich and colleagues [1] reported on estimates of Denisovan ancestry for island and mainland Asian populations. Their most memorable conclusion was that they could find no substantial sign of Denisovan ancestry anywhere on the Asian mainland, or indeed on any island that had ever been connected by land to Asia.

The distribution was stark, as illustrated by the map from the paper:

I wrote about the paper when it was released ("Denisovan DNA in the islands, and an Australian genome"), noting:

Notice the apparent lack of Denisovan ancestry in anyone who lives anywhere that was once connected by land with mainland Asia. I say "apparent" deliberately: Abi-Rached and colleagues reported last month on the widespread distribution of Denisovan HLA types among today's Asian populations, and those may well be products of Denisovan genes that were later selected. I've already identified a handful of other loci that seem to reflect Denisovan ancestry in mainland Asian people. According to the comparisons by Reich and colleagues, such loci must be exceptions.

Abi-Rached and colleagues [2] had argued that HLA alleles found in the Denisovan genome are presently common in some parts of Asia, and likely reflect local adaptive introgression. Substantial introgression of a small number of genes would not be enough to create a strong genome-wide appearance of Denisovan ancestry. Still, it was a little odd that the first genes anybody looked closely at would provide strong evidence of introgression.

Now, Pontus Skoglund and Mattias Jakobsson [3] say that Denisovan ancestry is widespread across China and Southeast Asia.

That conclusion contradicts Reich and colleagues, so why do the studies come to such different results?

Skoglund and Jakobsson suggest that they have succeeded in finding introgression where others failed because their model accounts for ascertainment bias in the available datasets. SNP data come from genotyping chips, which have been designed using known polymorphisms. Five years ago, we knew much more about polymorphisms in Europe than other parts of the world, and so the HGDP, and HapMap to a lesser extent, do a good job of sampling rare alleles in Europe but miss many rare alleles in Africa and other populations. This is the ascertainment bias.

Some of the most obvious signs of introgression today are cases where rare alleles are shared with an archaic genome. If ascertainment bias causes you to miss the rare alleles, you'll miss the introgression.

But that explanation isn't really sufficient to explain the differences between these papers. For one thing, Reich and colleagues [1] also worked hard to account for ascertainment biases in their SNP samples. For another, whole genome comparisons between East Asian samples and the Denisova genome have not yielded evidence of Denisovan ancestry, even though whole genomes have no ascertainment bias. The number of whole genomes so far compared is very small, and so the statistical ability to detect introgression is lower, but Skoglund and Jakobsson actually replicate that null result in their current paper.

Probably most important, it's not clear that Skoglund and Jakobsson's result can actually be explained by rare alleles. Here is Figure 1e from their paper:

Figure 1e from Skoglund and Jakobsson (2011). Original caption: Interpolated spatial distribution of the frequency of Denisova alleles at SNPs where Denisova is different from chimpanzee and Neandertal. Sample localities are indicated with rectangles.

This map represents a clever comparison. It is a heat map of the mean local frequency of the subset of alleles that are present in Denisova but absent from chimpanzees and Neandertals. These are presumptively derived alleles relative to the chimpanzee. The SNPs here are all known to vary in human populations, because they are all included in the HGDP sample. So the map does not represent all the Denisova derived mutations in humans today, only a particular subset that is especially likely to be informative.

Given that the sites have been picked in a special way, we need to examine carefully how strong the pattern really is. Notice the scale of the heat map. The difference between the orange area in south China, from the green area in north China, is around 0.001, or a tenth of a percent in mean frequency. The actual values are reported in the online supplement, in Table S3. An exception of Yizu in south China who have around 0.006 more than their neighbors. The Yizu sample includes only 10 individuals (9 males, 1 female). The paper does not report the number of SNPs included in this comparison, but it must be a very small set relative to the total, because only a small fraction of human SNPs are known to be derived in Denisova and ancestral in Neandertals.

With this very small difference in frequencies, I would not rule out the hypothesis that the zone of high Denisova derived frequencies in south China is caused entirely by frequency enrichment of a small number of loci. A handful of genes like the HLA loci observed by Abi-Rached and colleagues might be enough to create this very slight elevation in the average. Hence, the best case is that the data here simply provide greater sensitivity to small amounts of introgression. The worst case is that the pattern may be dominated by the Yizu sample, which is really too small to carry this kind of load.

The strongest evidence presented in the paper is a comparison of north and south East Asian regions directly. Although the comparison of south China against other regions of the world (Africa, Europe) does not yield significant evidence of Denisovan similarity in this paper, south China differs from north China in essentially the same way that the Oceanian people do from other regions. And the Oceanian populations (here, Papua New Guinea and Bougainville) differ from other regions because of their Denisovan ancestry. So Skoglund and Jakobsson infer that the north/south comparison reflects Denisovan ancestry as well.

I think this comparison is sound, and the question is, how much introgression would this pattern require? The paper answers that question in this way:

Quantitative estimation of the precise fraction of Denisova-related ancestry in Southeast Asian populations based on genotype data are unfortunately sensitive to ascertainment bias and genetic drift, and such estimates will require genome sequence data that are currently unavailable. However, both the PCA results (Fig. 1B) and the approximately six times lower absolute values of the D statistic in tests between Northeast Asians and Southeast Asians compared with tests between Northeast Asians and Oceanians (Table S4) indicate a relatively low fraction of Denisova-related ancestry. Thus, the fraction is likely to be smaller than both the ~5% fraction of Denisova-related ancestry present in Oceanians and the ~2.5% fraction of Neandertal ancestry present in non-Africans (23, 24), perhaps around 1%.

One percent is an amount that whole genome comparisons at present do not rule out, and I think it's a reasonable guess. I would not have thought we could rule out a one percent contribution from other, non-Denisovan archaic people, for example.

We aren't very far from a more definitive answer of this question, as the data continue to accumulate every day. What I find interesting is the way that models can generate these 1% differences in ancestry proportions, depending on sampling and the pattern of migration assumed to have happened in the past. Two estimates that differ by less than a percent are not really different. This paper provides the suggestion of a more widespread Denisovan legacy, and I accept that as a possibility.

I should mention: less than one percent of a half billion people is still a very large number, added to five percent of the indigenous population of New Guinea and Australia, and smaller fractions of other island populations. The total amount of Denisovan legacy present in living people probably exceeds the population of Earth at the time the Denisovans lived.

References

We don't really know the extent of territory that might have been occupied by the population represented by the Denisova genome. The signs of mixture into the Melanesian/New Guinea population suggests that the Denisova individual shared many genes with people who lived somewhere along the South or Southeast Asian coast. Denisova itself, however, is in the Altai Mountains.

Last week I wrote some thoughts about the possible introgression of HLA alleles from Denisovans into more recent populations. HLA genes pose many problems for testing this hypothesis -- including the difficulty of identifying the alleles in a low-coverage genome and the high chance of incomplete lineage sorting of ancient alleles in recent populations. Other parts of the genome in principle may be much easier to find evidence of introgression.

If an allele that originated in Denisovans had some advantage in later populations, it might today be found very widely spread across Asian populations, even if the amount of Denisovan ancestry in most of these populations is very small. This was the theme of my paper with Gregory Cochran several years ago [1] ("The inevitability of introgression"). The probability that a single copy of an advantageous allele will survive and increase in the population is roughly 2s, where s is the fitness advantage in a heterozygote carrying the allele. A relatively small number of copies of an allele might have entered a recent human population by introgression from some ancient population, but these few copies would have a high likelihood of surviving and increasing in frequency, possibly toward fixation. HLA alleles could easily be in this category, but the challenges identifying them and high chance of ILS make the hypothesis hard to test.

Another strategy is to identify genes that have been selected in recent populations and see if the linked haplotype shows up in the Denisova genome. Recently, several studies have attempted to identify genes related to high altitude adaptation in Tibetans. At least some Denisovans lived in the mountainous areas of central Asia, and so I'm curious whether they might have some alleles adapted to this environment. The Altai are not nearly as high as the Tibetan plateau (in fact Denisova itself is not much higher than western Kansas), and we don't know how long Denisovan people might have been resident in Central Asia, but if we're looking for selected alleles there are some strong candidates in this category of genes.

So let's look at some of them. All positions here are mapped to the hg18 human genome assembly.

Yi and colleagues [2] find a strong frequency difference between China and Tibet for a SNP in EPAS1, at chr2:46441523. The derived allele, G, has a frequency of 87% in their Tibetan sample but only 9% in their Chinese sample (and zero in Denmark). The Denisova genome is represented by two reads at this site, both C, the ancestral allele. We don't necessarily have to accept that this is a functional site, but as the marker most strongly differentiating the high altitude population it would likely be closely linked to any functional variant. So the Denisova allele suggests that this ancient individual lacked whatever functional variant might currently be common in Tibetans for this gene.

Simonson and colleagues [3] took a different approach, focusing on candidate genes that they argued a priori were likely to be involved in adaptation to hypoxia because of their physiological role. They evaluated these genes for evidence of positive selection in Tibetans, finding several candidate haplotypes for recent adaptive evolution to high altitude.

For each of five genes, they identified a three-locus "core selection haplotype" that shows signs of selection within Tibet. The purpose of these three-SNP haplotypes was to examine the correlation of haplotypes and phenotypes in a sample of people where physiological data were taken. So they are intended as tags, not as comprehensive and unique identifiers of the candidates at the genetic level. But the three-locus haplotypes are the only ones reported in the supplement to the paper, so that's what I have to compare.

EGLN1: The three-allele candidate selected haplotype consists of A at chr1:229793717, T at chr1:229667980 and T at chr1:229665156. Denisova apparently has the selected haplotype with A at chr1:229793717 (2/2 reads), T at chr1:229667980 (3/3 reads) and T at chr1:229665156 (1/1 reads). However, it is not obvious whether this is significant. All three alleles on the candidate selected haplotype are the ancestral (present in chimpanzees and gorillas) alleles, which are much more likely to show up in the archaic genomes than derived alleles. These ancestral alleles are also present in several of the whole genomes provided along with the Denisova sequence reads. So it's not clear to me how good a candidate for selection the haplotype really is.

CYP17A1: Here the three-allele candidate selected haplotype includes G at chr10:104568521, G at chr10:104594906, and C at chr10:104517420. Denisova has C (5/5 reads, ancestral), T (4/4 reads, ancestral), and C (3/3 reads, ancestral). Again, Denisova has the all-ancestral haplotype here, but in this case it is not the selection candidate.

PTEN: The selected candidate haplotype is G at chr10:89770364, C at chr10:89790851 and C at chr10:89778618. Denisova has G (5/5 reads, ancestral), T (2/2 reads, derived), and C (4/4 reads, ancestral). Not selected.

I always find it interesting when the Denisova genome has a derived allele at an interesting site -- it is the shared derived alleles between these archaic genomes and living people that constitute evidence of genetic persistence of the archaic people. No single site carries that information (any one allele may be shared by incomplete lineage sorting), but I still like to note them. The Papuan and half the Native American, Sardinian and Mongolian reads share the derived T at chr10:89790851 with Denisova.

HMOX2: The candidate selected haplotype has C at chr16:4456093, T at chr16:4465266, T at chr16:4442515. Denisova has this candidate selected haplotype: C (3/3 reads, ancestral), T (4/4 reads, ancestral), T (5/5 reads, ancestral). That haplotype may also be in the Cambodian whole genome accompanying the Denisova data, and can't be ruled out for the Mongolian. Again, the all-ancestral haplotype and wider distribution argue against the hypothesis that this haplotype was specifically selected in Tibet.

PPARA: The core candidate selected haplotype has A at chr22:44827140, C at chr22:44832376 and T at chr22:44842095. Denisova has A (8/8 reads, ancestral), A (5/5 reads, ancestral), and C (2/2 reads, ancestral). Notice again, Denisova has the all-ancestral haplotype. As an ancient sequence, we are finding this is the usual case, human-derived alleles are just rarer in this genome.

OK, where are we? Out of six genes that are candidates for selection on altitude adaptation in Tibetans, the Denisova genome has two -- at ELGN1 and HMOX2. In both cases, the core selected haplotype consists entirely of ancestral alleles, and so I think they are actually poor evidence of introgression on the surface. I would test them by looking at more SNPs linked to the presumed selected haplotype, hoping to find some derived SNPs shared by the Denisovan genome and the presumed selected haplotypes. Unfortunately, publications do not yet routinely report long haplotypes, so it will take some more digging to test these cases.

References