Spread of Y. pestis, earlier than previously thought, may have caused Neolithic decline


Open access Emergence and Spread of Basal Lineages of Yersinia pestis during the Neolithic Decline, by Rascovan et al. Cell (2018)

Abstract (emphasis mine):

Between 5,000 and 6,000 years ago, many Neolithic societies declined throughout western Eurasia due to a combination of factors that are still largely debated. Here, we report the discovery and genome reconstruction of Yersinia pestis, the etiological agent of plague, in Neolithic farmers in Sweden, pre-dating and basal to all modern and ancient known strains of this pathogen. We investigated the history of this strain by combining phylogenetic and molecular clock analyses of the bacterial genome, detailed archaeological information, and genomic analyses from infected individuals and hundreds of ancient human samples across Eurasia. These analyses revealed that multiple and independent lineages of Y. pestis branched and expanded across Eurasia during the Neolithic decline, spreading most likely through early trade networks rather than massive human migrations. Our results are consistent with the existence of a prehistoric plague pandemic that likely contributed to the decay of Neolithic populations in Europe.

(A) Schematic representation of the trajectories and time periods (thousand years before present, kyr) of major known human migrations in Eurasia during the Neolithic and Bronze Age. The observed geographic distribution and divergence times of Y. pestis strains from the Gok2 and Bronze Age clades cannot be explained by the timings and routes of these human movements.
(B) Geographic distribution of the use of animal traction and wheeled transport across Neolithic and Bronze Age populations in Eurasia, which broadly expanded during the period of 5,500 and 5,000 BP. The expansion of these technological innovations overlaps the predicted period for the expansion of the basal Y. pestis strains.
(C) Timeline indicating the proposed key historical events that contributed to the emergence and spread of plague during the Neolithic.

We have evolved in the interpretation of the plague from 1) a Corded Ware-driven disease, to 2) a steppe disease that was spread by Yamna and Corded Ware, and now 3) a (potentially) Trypillia-driven disease that spread to the west earlier than Yamna and Corded Ware, but probably also later east and west with both.

At least it still seems that the plague and its demographic consequences were a good reason for the expansion of Indo-Europeans and Uralians into Europe, as we thought…

Featured image, from the paper: “The predicted model of early dispersion of Y. pestis during Neolithic and Bronze Age was built by integrating phylogenetic information of Y. pestis strains from this period (Figure 1E), their divergence times (Figure 3), the geographic locations, carbon dating and genotypes of the individuals, and the archaeological record. The model suggests that early Y. pestis strains likely emerged and spread from mega-settlements in Eastern Europe (built by the Trypillia Culture) into Europe and the Eurasian steppe, most likely through human interaction networks. This was facilitated by wheeled and animal-powered transports, which are schematized in the map with red lines with arrows pointing in both senses. Our model builds upon a previous model (Andrades Valtuena et al., 2017) that proposed the spread of plague to be associated with large-scale human migrations (blue line).


Inca and Spanish Empires had a profound impact on Peruvian demography


Open access Evolutionary genomic dynamics of Peruvians before, during, and after the Inca Empire by Harris et al., PNAS (2018) 201720798 (published ahead of print).

Abstract (emphasis mine):

Native Americans from the Amazon, Andes, and coastal geographic regions of South America have a rich cultural heritage but are genetically understudied, therefore leading to gaps in our knowledge of their genomic architecture and demographic history. In this study, we sequence 150 genomes to high coverage combined with an additional 130 genotype array samples from Native American and mestizo populations in Peru. The majority of our samples possess greater than 90% Native American ancestry, which makes this the most extensive Native American sequencing project to date. Demographic modeling reveals that the peopling of Peru began ∼12,000 y ago, consistent with the hypothesis of the rapid peopling of the Americas and Peruvian archeological data. We find that the Native American populations possess distinct ancestral divisions, whereas the mestizo groups were admixtures of multiple Native American communities that occurred before and during the Inca Empire and Spanish rule. In addition, the mestizo communities also show Spanish introgression largely following Peruvian Independence, nearly 300 y after Spain conquered Peru. Further, we estimate migration events between Peruvian populations from all three geographic regions with the majority of between-region migration moving from the high Andes to the low-altitude Amazon and coast. As such, we present a detailed model of the evolutionary dynamics which impacted the genomes of modern-day Peruvians and a Native American ancestry dataset that will serve as a beneficial resource to addressing the underrepresentation of Native American ancestry in sequencing studies.

Admixture among Peruvian populations. (A) Colors represent contributions from donor populations into the genomes of Peruvian mestizo groups, as estimated by CHROMOPAINTER and GLOBETROTTER. The label within parentheses for each Peruvian Native American source population corresponds to their geographic region where Ama, And, and Coa represent Amazon, Andes, and coast, respectively. (B) Admixture time and proportion for the best fit three-way ancestry (AP, Trujillo and Lima) and two-way ancestry (Iquitos, Cusco, and Puno) TRACT models [European, African, and Native American (NatAm) ancestries] for six mestizo populations. (C) Network of individuals from Peruvian Native American and mestizo groups according to their shared IBD length. Each node is an individual and the length of an edge equals to (1/total shared IBD). IBD segments with different lengths are summed according to different thresholds representing different times in the past (52), with 7.8 cM, 9.3 cM, and 21.8 cM roughly representing the start of the Inca Empire, the Spanish conquest and occupation, and Peruvian independence. IBD networks are generated by Cytoscape (98) and only the major clusters in the network are shown for different cutoffs of segment length. AP, Central Am, and Matsig are short for Afroperuvians, Central American, and Matsiguenka, respectively. The header of each IBD network specifies the length of IBD segments used in each network.

Interesting excerpts

The high frequency of Native American mitochondrial haplotypes suggests that European males were the primary source of European admixture with Native Americans, as previously found (23, 24, 41, 42). The only Peruvian populations that have a proportion of the Central American component are in the Amazon (Fig. 2A). This is supported by Homburger et al. (4), who also found Central American admixture in other Amazonian populations and could represent ancient shared ancestry or a recent migration between Central America and the Amazon.

Following the peopling of Peru, we find a complex history of admixture between Native American populations from multiple geographic regions (Figs. 2B and 3 A and C). This likely began before the Inca Empire due to Native American and mestizo groups sharing IBD segments that correspond to the time before the Inca Empire. However, the Inca Empire likely influenced this pattern due to their policy of forced migrations, known as “mitma” (mitmay in Quechua) (28, 31, 37), which moved large numbers of individuals to incorporate them into the Inca Empire. We can clearly see the influence of the Inca through IBD sharing where the center of dominance in Peru is in the Andes during the Inca Empire (Fig. 3C).

ASPCA of combined Peruvian Genome Project with the HGDP genotyped on the Human Origins Array. A.) European ancestry. B.) African ancestry. Samples are filtered by their corresponding ancestral proportion: European ≥ 30% (panel A) and African ≥ 10% (panel B). The two plots in each panel are identical except for the color scheme: reference populations are colored on the left and Peruvian populations are colored on the right. Each point is one haplotype. In the African ASPCA we note three outliers among our samples, two from Trujillo and one from Iquitos, that cluster closer to the Luhya and Luo populations, though not directly. It is likely that these individuals share ancestry with other regions of Africa in addition to western Africa, but we cannot test this hypothesis explicitly as we have too few samples.

A similar policy of large-scale consolidation of multiple Native American populations was continued during Spanish rule through their program of reducciones, or reductions (31, 32), which is consistent with the hypothesis that the Inca and Spanish had a profound impact on Peruvian demography (25). The result of these movements of people created early New World cosmopolitan communities with genetic diversity from the Andes, Amazon, and coast regions as is evidenced by mestizo populations’ ancestry proportions (Fig. 3A). Following Peruvian independence, these cosmopolitan populations were those same ones that predominantly admixed with the Spanish (Fig. 3B). Therefore, this supports our model that the Inca Empire and Spanish colonial rule created these diverse populations as a result of admixture between multiple Native American ancestries, which would then go on to become the modern mestizo populations by admixing with the Spanish after Peruvian independence.

Further, it is interesting that this admixture began before the urbanization of Peru (26) because others suspected the urbanization process would greatly impact the ancestry patterns in these urban centers (25). (…)


The demographic history and mutational load of African hunter-gatherers and farmers


Interesting new article (behind paywall), The demographic history and mutational load of African hunter-gatherers and farmers, Nat Ecol Evol (2018)

Abstract (emphasis mine):

Understanding how deleterious genetic variation is distributed across human populations is of key importance in evolutionary biology and medical genetics. However, the impact of population size changes and gene flow on the corresponding mutational load remains a controversial topic. Here, we report high-coverage exomes from 300 rainforest hunter-gatherers and farmers of central Africa, whose distinct subsistence strategies are expected to have impacted their demographic pasts. Detailed demographic inference indicates that hunter-gatherers and farmers recently experienced population collapses and expansions, respectively, accompanied by increased gene flow. We show that the distribution of deleterious alleles across these populations is compatible with a similar efficacy of selection to remove deleterious variants with additive effects, and predict with simulations that their present-day additive mutation load is almost identical. For recessive mutations, although an increased load is predicted for hunter-gatherers, this increase has probably been partially counteracted by strong gene flow from expanding farmers. Collectively, our predicted and empirical observations suggest that the impact of the recent population decline of African hunter-gatherers on their mutation load has been modest and more restrained than would be expected under a fully recessive model of dominance.

“Inferred demographic models of the studied populations. a, EUR-first branching model, in which ancestors of EUR (aEUR) diverged from African populations before the divergence of the ancestors of RHG (aRHG) and AGR (aAGR). b, RHG-first branching model, in which aRHG were the first to diverge from the other groups. c, AGR-first branching model, in which aAGR were the first to diverge from the other groups. We assumed an ancient change in the size of the ancestral population of all humans (ANC). We assumed that each subsequent divergence of populations was followed by an instantaneous change in the effective population size (Ne). We also assumed that there were two epochs of migration between the following population pairs: wAGR/aAGR and wRHG/aRHG, eAGR/aAGR and eRHG/aRHG, and EUR and eAGR/aAGR. The figure labels correspond to the parameters of the model estimated by maximum likelihood and the 95% confidence intervals assessed by bootstrapping by site 100 times (Supplementary Table 4). Vertical arrow corresponds to the direction of time, from past to present, with divergence times given on the left and expressed in thousand years ago(ka). Effective population sizes (N) are given within the diagram and expressed in thousands of individuals. Bold horizontal arrows indicate an estimated parameter for the effective strength of migration 2Nm > 1, while thin horizontal arrows indicate 2Nm ≤ 1.”

See also:

Demographic research of Neolithic, Chalcolithic, and Bronze Age Europe


I mentioned in the Indo-European demic diffusion model the need to assess absolute and relative population growth – as well as other demographic changes – to interpret genomic data from the different European regions studied.

One article I referred to was Demographic traces of technological innovation, social change and mobility: from 1 to 8 million Europeans (6000–2000 BCE), by Johannes Müller.

Excerpts (emphasis mine):

  • The neolithization of Northern and Northwestern Europe (probably with new forms of slash-and-burn agriculture; Feeser et al. 2012; Schier 2009) was also one of the causes for the population increase observed.
  • The introduction of the plough and developing technologies (e.g. the introduction of the wheel) (cf. Mischka 2011) might also be causes of rising population figures from ca. 3500–3000 BC.
  • The establishment of subcontinental value systems, such as the Corded Ware and Bell-Beaker phenomena (Czebreszuk/Szmyt 2003; Furholt 2004), in contrast to regional identities, might have triggered different reactions in different areas, leading to fluctuating population levels.
  • The introduction of Bronze Age ideologies, including bronze as a technology, triggered the spread of Neolithic and Bronze Age societies to vast areas of Europe (e.g. Earle/Kristiansen 2010).A major population increase is observed in both the areas already settled as well as in new areas of interest.
Absolute population values in Europe and the Near East from 6500–1500 BCE (interpolation line: spline).

In our population estimations for Central Europe and Scandinavia, population increases are associated with the periods from 5500–5000 BCE (LBK) and 3500–3000 BCE (middle and late Funnelbeaker Culture), but not for the period from 2500–2000 BCE (Bell Beaker). Consequently, this would possibly indicate forms of immigration for the first two periods and a form of interregional networking (e.g. through marriage) for the latter. But as also for the first cases on the supra-regional level (which our enquiries investigated), no other area with a significant population decrease could be observed, therefore “proof” for larger population displacement is not given. For such inquiries, studies on a more regional level are probably necessary. Nevertheless, for the Bell Beaker period I would like to exclude the possibility of large population influxes at least to Central Europe and South Scandinavia as the population values show no indication of such an event (cf. Fig. 10). In consequence, supra-regional networks or population-exchanges between smaller regions might be responsible for the isotope values.

One could interpret from the graphics, including known anthropological and genomic data, that:

  • The population growth corresponding to the Corded Ware expansion from ca. 3300 into Central Europe was seen initially with the introduction of new technology, but then stalled – probably with population replacement during the A-horizon of the Corded Ware culture.
  • The Yamna expansion into South-East Europe must have included some population replacement, i.e. influx into progressively deserted areas (such as that of the Cucuteni-Trypillia culture), since it did not leave traces of population growth.
  • The impact of the expansion of East Bell Beakers from ca. 2500 BC is clear in South-East Europe, and especially in Western Europe – taking into account the whole population growth in Europe. In Central Europe and Scandinavia the overall impact of BB migration was more limited, which suggests some degree of population replacement.

Also important to interpret genomic data are the actual economic and social differences in the different periods and cultures – usually growing after the introduction of farming. A good example is the scarce data from Khvalynsk, where the sample of haplogroup R1b (most likely of subclade M269) shows – apart from a closer position in PCA to Yamna – a a high-status burial, similar to high-status individuals buried under kurgans in later Yamna graves. This man was therefore probably a founder of an elite group of patrilineally-related families, which dominated in the following Yamna culture, which explains the clear expansion of this haplogroup’s subclades from this region.

Figures from Rebellion and Inequality in Archaeology (2017), by Johannes Müller

Other interesting papers on European demographics by Johannes Müller include:

Check out also works by Marko Porčić (such as Radiocarbon test for demographic events in written and oral history) or Stephen Shennan.

EDIT (17 Feb 2018): For how variation in the effective population size governs genetic diversity, see:

Featured image, from the main article: “The distribution of agrarian regions in Europe and the Near East in relation to the supra-regions as defined in this study: Near East (NE) about 2.400.000 km2; South East Europe (SEE) about 1.087500 km2; Central Europe and South Scandinavia (CE/SSc) about 1.613.000 km2. Europe includes 10.050.000 km2 (without Iceland)”.

See also: