I’ve mentioned The genomic origins of the world’s first farmers a few times. It’s an intense model-based paper that revises some expectations and models of the origins of diverse human groups on the cusp of the Holocene:

The precise genetic origins of the first Neolithic farming populations in Europe and Southwest Asia, as well as the processes and the timing of their differentiation, remain largely unknown. Demogenomic modeling of high-quality ancient genomes reveals that the early farmers of Anatolia and Europe emerged from a multiphase mixing of a Southwest Asian population with a strongly bottlenecked western hunter-gatherer population after the last glacial maximum. Moreover, the ancestors of the first farmers of Europe and Anatolia went through a period of extreme genetic drift during their westward range expansion, contributing highly to their genetic distinctiveness. This modeling elucidates the demographic processes at the root of the Neolithic transition and leads to a spatial interpretation of the population history of Southwest Asia and Europe during the late Pleistocene and early Holocene.

A few things to note about this paper. First, no mention of Basal Eurasians. This research group doesn’t believe they’re necessary. As you may know, Basal Eurasians were hypothesized because Mesolithic Europeans seem genetically closer to eastern non-Africans than to incoming Early European Farmers (EEF) from Anatolia. One model that can explain this is that there was a population somewhere in N. Africa and W. Asia that split off first from other non-Africans, perhaps more than 60,000 years ago and that eventually merged back with West Eurasians at some point. Lazaridis et al. also believe this might explain why some W. Asia groups have less Neanderthal ancestry; the Basal Eurasians did not admix with them.

The problem, so far, is that nearly a decade after they were hypothesized we haven’t found a mostly Basal Eurasian sample. And, Basal ancestry is found in West Eurasia pretty early. Perhaps they’ll always remain a statistical construct?

Why doesn’t everyone think Basal Eurasians are necessary? If you read the above paper, the key issue is the distortionary impact that bottlenecks can have on the inferred branch lengths of a given phylogeny. They argue that a very strong bottleneck during the LGM 20,000 years ago inflated the divergence of European foragers from other populations and that subsequently, the populations bounced back very well so that their census sizes were likely large. And, they also argue that some of the distinctiveness of EEF from Anatolia is a function of their own bottleneck far more recently, around the beginning of the Holocene. Combined with these bottlenecks there are also various migrations between the branches in the typology, branches differentially impacted by these bottlenecks.

I don’t know how this aligns with earlier models, but I think it’s a serious contender. The key question I wonder is how this fits in with earlier ancient DNA and archaeology.

Eurogenes points me to a new talk by David Reich, that has a nice new long abstract online. I’ll just insert my comments within the blockquote…

We present an integrative genetic history of the Southern Arc, an area divided geographically between West Asia and Europe, but which we define as spanning the culturally entangled regions of Anatolia and its neighbors, in both Europe (Aegean and the Balkans), and in West Asia (Cyprus, Armenia, the Levant, Iraq and Iran). We employ a new analytical framework to analyze genome-wide data at the individual level from a total of 1,320 ancient individuals, 731 of which are newly reported and address major gaps in the archaeogenetic record. We report the first ancient DNA from the world’s earliest farming cultures of southeastern Anatolia and northern Mesopotamia, as well as the first Neolithic period data from Cyprus and Armenia, and discover that it was admixture of Natufian-related ancestry from the Levant—mediated by Mesopotamian and Levantine farmers, and marked by at least two expansions associated with dispersal of pre-pottery and pottery cultures—that generated a pan-West Asian Neolithic continuum [“it was” refers to Cyprus and Armenia? How Mesopatamian farmers related to the Zagros-Levant-Anatolian trichotomy?]. Our comprehensive sampling shows that Anatolia received hardly any genetic input from Europe or the Eurasian steppe from the Chalcolithic to the Iron Age; this contrasts with Southeastern Europe and Armenia that were impacted by major gene flow from Yamnaya steppe pastoralists [I believe Southeastern Europe had both patchy early Yamnaya and later Indo-Europeans? Armenia on the other hand seems unique].

In the Balkans, we reveal a patchwork of Bronze Age populations with diverse proportions of steppe ancestry in the aftermath of the ~3000 BCE Yamnaya migrations, paralleling the linguistic diversity of Paleo-Balkan speakers. We provide insights into the Mycenaean period of the Aegean by documenting variation in the proportion of steppe ancestry (including some individuals who lack it altogether), and finding no evidence for systematic differences in steppe ancestry among social strata, such as those of the elite buried at the Palace of Nestor in Pylos [Mycenanean Greece starts at 1750 BC, so probably at least 500 years at least from the major penetration of Indo-Europeans, so that’s 20 generations or so. That seems enough time for status-gene correlations to breakdown if there’s no endogamous caste-like structure].

A striking signal of steppe migration into the Southern Arc is evident in Armenia and northwest Iran where admixture with Yamnaya patrilineal descendants occurred, coinciding with their 3rd millennium BCE displacement from the steppe itself. This ancestry, pervasive across numerous sites of Armenia of ~2000-600 BCE, was diluted during the ensuing centuries to only a third of its peak value [Looking online, there’s a 2012 paper that indicates that modern Armenians have of the specifically Yamnaya R1b lineage. If this, true might explain why Armenian is so hard to place within a Indo-European tree, as Celtic, Germanic, Balto-Slavic and Indo-Iranian seem to come out of a broader Corded Ware cultural complex], making no further western inroads from there into any part of Anatolia, including the geographically adjacent Lake Van center of the Iron Age Kingdom of Urartu. The impermeability of Anatolia to exogenous migration contrasts with our finding that the Yamnaya had two distinct gene flows [David of Eurogenes does not like this, but this could mean Anatolian and CHG/Iranian pulses?], both from West Asia, suggesting that the Indo-Anatolian language family originated in the eastern wing of the Southern Arc and that the steppe served only as a secondary staging area of Indo-European language dispersal. The demographic significance of Anatolia on a Mediterranean-wide scale is further documented by our finding that following the Roman conquest, the Anatolian population remained stable and became the geographic source for much of the ancestry of Imperial Rome itself.

In the last week, I put up a big two-part series of posts on Substack, The wolf at history’s door and Casting out the wolf in our midst, about the spread of Indo-European (men) 5,000 years ago. By coincidence, a massive preprint on ancient DNA just came out of the Willerslev coalition of researchers, Population Genomics of Stone Age Eurasia. It really is massive, and is hard to summarize, but here’s the abstract:

The transitions from foraging to farming and later to pastoralism in Stone Age Eurasia (c. 11-3 thousand years before present, BP) represent some of the most dramatic lifestyle changes in human evolution. We sequenced 317 genomes of primarily Mesolithic and Neolithic individuals from across Eurasia combined with radiocarbon dates, stable isotope data, and pollen records. Genome imputation and co-analysis with previously published shotgun sequencing data resulted in >1600 complete ancient genome sequences offering fine-grained resolution into the Stone Age populations. We observe that: 1) Hunter-gatherer groups were more genetically diverse than previously known, and deeply divergent between western and eastern Eurasia. 2) We identify hitherto genetically undescribed hunter-gatherers from the Middle Don region that contributed ancestry to the later Yamnaya steppe pastoralists; 3) The genetic impact of the Neolithic transition was highly distinct, east and west of a boundary zone extending from the Black Sea to the Baltic. Large-scale shifts in genetic ancestry occurred to the west of this “Great Divide”, including an almost complete replacement of hunter-gatherers in Denmark, while no substantial ancestry shifts took place during the same period to the east. This difference is also reflected in genetic relatedness within the populations, decreasing substantially in the west but not in the east where it remained high until c. 4,000 BP; 4) The second major genetic transformation around 5,000 BP happened at a much faster pace with Steppe-related ancestry reaching most parts of Europe within 1,000-years. Local Neolithic farmers admixed with incoming pastoralists in eastern, western, and southern Europe whereas Scandinavia experienced another near-complete population replacement. Similar dramatic turnover-patterns are evident in western Siberia; 5) Extensive regional differences in the ancestry components involved in these early events remain visible to this day, even within countries. Neolithic farmer ancestry is highest in southern and eastern England while Steppe-related ancestry is highest in the Celtic populations of Scotland, Wales, and Cornwall (this research has been conducted using the UK Biobank resource); 6) Shifts in diet, lifestyle and environment introduced new selection pressures involving at least 21 genomic regions. Most such variants were not universally selected across populations but were only advantageous in particular ancestral backgrounds. Contrary to previous claims, we find that selection on the FADS regions, associated with fatty acid metabolism, began before the Neolithisation of Europe. Similarly, the lactase persistence allele started increasing in frequency before the expansion of Steppe-related groups into Europe and has continued to increase up to the present. Along the genetic cline separating Mesolithic hunter-gatherers from Neolithic farmers, we find significant correlations with trait associations related to skin disorders, diet and lifestyle and mental health status, suggesting marked phenotypic differences between these groups with very different lifestyles. This work provides new insights into major transformations in recent human evolution, elucidating the complex interplay between selection and admixture that shaped patterns of genetic variation in modern populations.

There’s so much, I can’t really reduce. Here are some highlights

1 – New hunter-gatherer cluster with a focus in the eastern Ukraine/Russian border region. Between the Dnieper and Don. Because I can barely read the admixture grap in extended figure 4, I’m not totally clear where this group is positioned in the graph, though it has some Causus hunter-gatherer

2 – Neolithicization was pretty slow (demic) in most of Europe, except Scandinavia. We knew this. Steppe arrival was faster everywhere, but mixed with local Neolithic substrate…except in Scandinavia, where there was straight up replacement. But Scandinavians do have Neolithic ancestry…so where’s that from?

3 – The paper claims that the Corded Ware people mixed with Globular Amphora culture. I’m pretty sure if they looked closely all the South Asians will steppe ancestry will show this too, and not any other type of European Neolithic.

4 – Scandinavia seems to have had several replacements even after the arrival of the early Battle Axe people. This is clear in Y chromosome turnover, from R1a to R1b and finally to mostly I1, the dominant lineage now. They claim that later Viking and Norse ancestry is mostly from the last pulse during the Nordic Bronze Age.

5 – They claim to detect it’s clear that Neolithic ancestry in North/Central/Eastern Europe was from Southeast Europe, while that in Western Europe was from Southwest Europe. This is expected.

6 – They confirm that in terms of polygenic prediction Yamnaya people were taller. They claim that it looks like N vs. S European differences in height aren’t selection, but stratification (Yamnaya predicts tallness).

7 – They find that dark hair and skin in Europeans seems correlated with WHG ancestry. This seems to confirm that the WHG were indeed dark of hair and eye. They find that lighter skin/hair really seems to come with Anatolian farmers and Yamnaya. Not the hunter-gatherers. Though selection does start earlier. They assert this has something to do with UV/Vitamin D, but if that, why were the HG groups dark? (if blue-eyed in the case of WHG) I think the explanation is some interaction with the agro-pastoralist lifestyle.

They also confirm that pigmentation selection went on until 3,000 years ago. This is obvious, and to me, it explains easily the heterogeneity in some CWC and post-CWC populations. Some of the early Bell Beakers in Britain look totally modern in pigmentation, but other populations are darker than they should be.

8 – Lots of selection in diet and immune system. What you’d expect. Basically a lot of illnesses might be mixture of the various populations. For example, diabetes comes from WHG.

9 – Neolithic Anatolians seem associated with some psychiatric issues. Could this be due to early dense-living? No idea. Also, they find EDU was selected for (one locus). Might be pleiotropy though.

10 – They find the African R1b around Lake Chad in some Ukrainian samples. Seems to confirm that somehow it’s from Eastern Europe? Weird.

Anyway, read it and tell me what you think.

People routinely ask me about a place to find pairwise Fst values. I have a dataset with 250,000 SNPs and 200 populations, and a script using plink that generates pairwise differences crosses populations. Here are two files with the results:

A file with the Fst values between populations in rows

A file with the Fst values between populations as a matrix

On the Apportionment of Archaic Human Diversity:

The apportionment of human genetic diversity within and between populations has been measured to understand human relatedness and demographic history. Likewise, the distribution of archaic ancestry in modern populations can be leveraged to better understand the interaction between our species and its archaic relatives, and the impact of natural selection on archaic segments of the human genome. Resolving these interactions can be difficult, as archaic variants in modern populations have also been shaped by genetic drift, bottlenecks, and gene flow. Here, we investigate the apportionment of archaic variation in Eurasian populations. We find that archaic genome coverage at the individual- and population-level present unique patterns in modern human population: South Asians have an elevated count of population-unique archaic SNPs, and Europeans and East Asians have a higher degree of archaic SNP sharing, indicating that population demography and archaic admixture events had distinct effects in these populations. We confirm previous observations that East Asians have more Neanderthal ancestry than Europeans at an individual level, but surprisingly Europeans have more Neandertal ancestry at a population level. In comparing these results to our simulated models, we conclude that these patterns likely reflect a complex series of interactions between modern humans and archaic populations.

The method is pretty neat. Read this closely. Here are some takeaways:

– European Neanderthal ancestry is lower than East Asian, but more diverse

– South Asians clearly have different Denisovan ancestry than East Asians

– Population structure matters…South Asian rare allele frequency is due to admixture between divergence groups

Basically, Neanderthal and Denisovan admixture is more complex than our simple stylized models.

Analysis of genomic DNA from medieval plague victims suggests long-term effect of Yersinia pestis on human immunity genes:

Pathogens and associated outbreaks of infectious disease exert selective pressure on human populations, and any changes in allele frequencies that result may be especially evident for genes involved in immunity. In this regard, the 1346-1353 Yersinia pestis-caused Black Death pandemic, with continued plague outbreaks spanning several hundred years, is one of the most devastating recorded in human history. To investigate the potential impact of Y. pestis on human immunity genes we extracted DNA from 36 plague victims buried in a mass grave in Ellwangen, Germany in the 16th century. We targeted 488 immune-related genes, including HLA, using a novel in-solution hybridization capture approach. In comparison with 50 modern native inhabitants of Ellwangen, we find differences in allele frequencies for variants of the innate immunity proteins Ficolin-2 and NLRP14 at sites involved in determining specificity. We also observed that HLA-DRB1*13 is more than twice as frequent in the modern population, whereas HLA-B alleles encoding an isoleucine at position 80 (I-80+), HLA C*06:02 and HLA-DPB1 alleles encoding histidine at position 9 are half as frequent in the modern population. Simulations show that natural selection has likely driven these allele frequency changes. Thus, our data suggests that allele frequencies of HLA genes involved in innate and adaptive immunity responsible for extracellular and intracellular responses to pathogenic bacteria, such as Y. pestis, could have been affected by the historical epidemics that occurred in Europe.

This isn’t surprising. But now that old DNA studies are getting cheap and mass-produced, I think people will be looking at changes in allele frequencies in the last 2,000 years a lot. More sophisticated methods for detecting natural selection either conclude or imply that sweeps are happening now, but this sort of study will confirm it (there’s evidence of natural selection in American Indians for obvious and unfortunate reasons).

Why do species get a thin slice of π? Revisiting Lewontin’s Paradox of Variation:

Under neutral theory, the level of polymorphism in an equilibrium population is expected to increase with population size. However, observed levels of diversity across metazoans vary only two orders of magnitude, while census population sizes (Nc) are expected to vary over several. This unexpectedly narrow range of diversity is a longstanding enigma in evolutionary genetics known as Lewontin’s Paradox of Variation (1974). Since Lewontin’s observation, it has been argued that selection constrains diversity across species, yet tests of this hypothesis seem to fall short of explaining the orders-of-magnitude reduction in diversity observed in nature. In this work, I revisit Lewontin’s Paradox and assess whether current models of linked selection are likely to constrain diversity to this extent. To quantify the discrepancy between pairwise diversity and census population sizes across species, I combine genetic data from 172 metazoan taxa with estimates of census sizes from geographic occurrence data and population densities estimated from body mass. Next, I fit the relationship between previously-published estimates of genomic diversity and these approximate census sizes to quantify Lewontin’s Paradox. While previous across-taxa population genetic studies have avoided accounting for phylogenetic non-independence, I use phylogenetic comparative methods to investigate the diversity census size relationship, estimate phylogenetic signal, and explore how diversity changes along the phylogeny. I consider whether the reduction in diversity predicted by models of recurrent hitchhiking and background selection could explain the observed pattern of diversity across species. Since the impact of linked selection is mediated by recombination map length, I also investigate how map lengths vary with census sizes. I find species with large census sizes have shorter map lengths, leading these species to experience greater reductions in diversity due to linked selection. Even after using high estimates of the strength of sweeps and background selection, I find linked selection likely cannot explain the shortfall between predicted and observed diversity levels across metazoan species. Furthermore, the predicted diversity under linked selection does not fit the observed diversity–census-size relationship, implying that processes other than background selection and recurrent hitchhiking must be limiting diversity.