I’ve been mobbed with e-mails from readers asking about my reaction to the new paper by Anders Eriksson and Andrea Manica in PNAS, titled “Effect of ancient population structure on the degree of polymorphism shared between modern human populations and ancient hominins”
I have not been posting as frequently the last month or two because I have been out of the country doing science.
The new paper’s press release has given rise to quite a lot of media attention, much of which unfortunately misrepresents our current knowledge of human and Neandertal genomes. Razib Khan summarized the situation on Monday, in a post titled, “Why you shouldn’t publish in PNAS”. I agree with his criticism, although I have a perspective coming out soon in PNAS. In fact, I suppose this episode shows why everyone should publish in PNAS, because so many journalists will just parrot press releases instead of asking relevant experts. Ewen Callaway did a great job on this story by putting it into the broader context (“Neandertal sex debate highlights benefits of pre-publication”). You will notice how no other science writers with any Neandertal knowledge picked up this press release…
Paleoanthropology is a field where data are rare and precious, and we do a lot of arguing about the validity of models. I love arguing about the validity of models (Cliff Notes version: All models are wrong).
Genomics is not such a field. We have abundant data today to compare with Neandertal genomes. Yet puzzlingly, the idea of Neandertal ancestry has been challenged by several papers that haven’t performed any new empirical comparisons at all. I’m struggling to figure this out. We have an unparalleled ability to explore the genomes of humans and Neandertals, and we should believe a computer model with no empirical data?
I’ve been assessing the Neandertal similarity of 1000 Genomes Project samples here on my blog (e.g., “Which population in the 1000 Genomes Project samples has the most Neandertal similarity?”). This is ongoing research here in my group, but we’ve been making it open because it tells us immediately that some hypotheses about Neandertal similarity must be wrong. Modeling is a lot of work. We’re trying to avoid putting a lot of investment into modeling that will be easily refuted by the next piece of genomic data. Data are flowing now so rapidly that we can afford to be naive empiricists.
For example, our comparisons quickly refute the hypothesis that Neandertal similarity comes only from ancient population structure in Africa. That hypothesis predicts much more heterogeneity within Africans in Neandertal similarity than exists today. We’ve shown that the heterogeneity in Africans is basically the same as within Europeans or Asians, and that the variance among African populations so far is quite small. Those are very simple observations, which are consistent with what Yang and colleagues
Another example is the proportion of Neandertal ancestry. Initially, the proportion of ancestry from Neandertals in living people was argued to be between 1 and 4 percent
Here’s a third example. I haven’t written about here yet, but I have been lecturing about it quite widely over the past few months. Earlier this year, the genome of Ötzi the Tyrolean Iceman was reported by Andreas Keller and colleagues
I’d like to see the model of African population structure that could explain this result…
If you’ll remember my earlier posts on the 1000 Genomes Project samples, this chart is a histogram of the number of shared Neandertal derived SNP alleles in different samples. The European and Asian samples are substantially greater than either African sample (here, Luhya and Yoruba colored differently). If we took as a baseline that Europeans have an average of 3.5 percent Neandertal, Ötzi would have around 5.5 percent (again, the actual percentage would be highly model-dependent). He has substantially greater sharing with Neandertals than any other recent person we have ever examined.
You can imagine, we have carried out just about every comparison we can think that could explain this result as anything other than greater Neandertal ancestry. Aaron and I will be putting our manuscript on the arXiv as soon as we’ve both signed off on all the text and figures, hopefully this week. This is simple stuff, and I see no reason not to be open about it – anybody with the Ötzi data can immediately do the same thing.
We think that showing and sharing these comparisons will save people a lot of useless effort. Personally, I can’t believe that these people spending effort on population models for Neandertals aren’t talking to those of us who have already carried out these comparisons and have already presented them in public. I guess we’ll find out if secrecy or openness leads to better science.
Meanwhile, I can share the abstract of the conference paper I’ll be presenting in September at the meeting of the European Society of Human Evolution in Bordeaux:
Evaluating recent evolution, migration and Neandertal ancestry in the Tyrolean Iceman
Paleogenetic evidence from Neandertals, the Neolithic and other eras has the potential to transform our knowledge of human population dynamics. Previous work has established the level of contribution of Neandertals to living human populations. Here, I consider data from the Tyrolean Iceman. The genome of this Neolithic-era individual shows a substantially higher degree of Ne- andertal ancestry than living Europeans. This comparison suggests that early Upper Paleolithic Europeans may have mixed with Neandertals to a greater degree than other modern human populations. I also use this genome to evaluate the pattern of selection in post-Neolithic Europeans. In large part, the evidence of selection from living peoples genetic data is confirmed by this specimen, but in some cases selection may be disproved by the Icemans genotypes. Neolithic-living human comparisons provide information about migration and diffusion of genes into Europe. I compare these data to the situation within Neandertals, and the transition of Neandertals to Upper Paleolithic populations three demographic transitions in Europe that generated strong genetic disequi- libria in successive populations.