The importance of fine-scale studies for integrating palaeogenomics and archaeology

eurasian-genomes-published

Short review (behind paywall) The importance of fine-scale studies for integrating paleogenomics and archaeology, by Krishna R. Veeramah, Current Opinion in Genetics & Development (2018) 53:83-89.

Abstract (emphasis mine):

There has been an undercurrent of intellectual tension between geneticists studying human population history and archaeologists for almost 40 years. The rapid development of paleogenomics, with geneticists working on the very material discovered by archaeologists, appears to have recently heightened this tension. The relationship between these two fields thus far has largely been of a multidisciplinary nature, with archaeologists providing the raw materials for sequencing, as well as a scaffold of hypotheses based on interpretation of archaeological cultures from which the geneticists can ground their inferences from the genomic data. Much of this work has taken place in the context of western Eurasia, which is acting as testing ground for the interaction between the disciplines. Perhaps the major finding has not been any particular historical episode, but rather the apparent pervasiveness of migration events, some apparently of substantial scale, over the past ∼5000 years, challenging the prevailing view of archaeology that largely dismissed migration as a driving force of cultural change in the 1960s. However, while the genetic evidence for ‘migration’ is generally statistically sound, the description of these events as structured behaviours is lacking, which, coupled with often over simplistic archaeological definitions, prevents the use of this information by archaeologists for studying the social processes they are interested in. In order to integrate paleogenomics and archaeology in a truly interdisciplinary manner, it will be necessary to focus less on grand narratives over space and time, and instead integrate genomic data with other form of archaeological information at the level of individual communities to understand the internal social dynamics, which can then be connected amongst communities to model migration at a regional level. A smattering of recent studies have begun to follow this approach, resulting in inferences that are not only helping ask questions that are currently relevant to archaeologists, but also potentially opening up new avenues of research.

Interesting excerpts (emphasis mine, reference numbers removed for clarity):

There are two major, somewhat intertwined, problems that currently exist.

First, archaeologists are not critiquing whether the migrations identified by paleogenomics using sophisticated population genetic machinery are actually occurring. Instead, the technical criticism arrives in terms of how these migrations are being ascribed to specific cultures. In many paleogenomic papers, there is a tendency (and often an analytical and technical need) to associate samples with particular archaeological cultures, for which all samples are then treated as possessing some kind homogenous and pervasive social identity that is bound in space and time. The major critiques of this thus far have been directed to those studies examining Corded-Ware and Bell-Beaker-related individuals and their potential relationship to the Yamnaya [Vander Linden (2016), Heyd (2017), Furholt (2017)], but are applicable to many other ‘migration’ scenarios described in the recent literature. This is compounded by the use of sometimes small numbers of samples to represent certain cultures from a particular geographic area as representatives of the entire culture at a supra-regional level. Yet often these archaeological cultures such as Corded-Ware and Bell-Beaker themselves show considerable variability in space and time, and even within cemeteries, which is not factored into the genetic analysis.

From a population geneticists point of view, this kind of simplification is somewhat understandable and will often likely have very little impact on the final analysis, given that the primary goal is usually to use ancient samples to better understand modern genetic variation. Though there may be a specific historical interest in some of these past events, I would argue that the aim for most population geneticists at a higher level is to try and fit modern patterns of genetic variation using the simplest models possible that take into account past demographic events (for example fitting f-statistics using the ADMIXTUREGRAPH approach), as this is how we are trained. Although sharing an archaeological culture may not mean that a set of individuals are part of the same homogeneous social group in reality, this approach may be a good enough heuristic to find broad genetic connections compared to another group represented by a different culture, which can then ultimately help understand and model modern human population structure. However, for an archaeologists interested in the ancient individuals themselves and their social identity, this lumping is unsatisfactory, where sophisticated narratives of the individual migrants and their ancient communities are the intended goal.

eurasian-genomes
From the paper. Barplot showing cumulative number of ancient Eurasian genomes published on a yearly basis up to 8th July 2018. Includes samples undergoing both whole genome shotgun and SNP capture sequencing.

The second related problem is that ‘migration’ in the sense used currently in the paleogenomics literature lacks sufficient detail to be of much use for an archaeologists attempting to disentangle the complex social dynamics within and between communities. To truly understand the role of migration as a social process and its contribution towards cultural changes, it is necessary to describe it as a structured behaviour, rather than treating it as an explanatory ‘black box’. Are the migrations occurring as a result of short range waves-of-advance movements, or as long-distance movements via leapfrogging models or stream migrations along established routes dependent on key kinship networks. Are there return migrants, and are some subset of individuals more predisposed to migration driving the signals? Although such models were implemented in past studies (even with classical markers [1]) and are part of the population genetics literature, they are lacking in the current paleogenomics literature when discussing migration. The finding that there is an increase of 12.3% of ancestry type X in population A compared to the preceding population B that is suggestive of a migration, is not particularly useful for examining these kind of models. It is also unclear to what degree standard population genetic parameters estimated from genomic data such as effective population size, Ne, and gene flow are relevant to models studied in archaeology, given they reflect (somewhat undefined) long-term population sizes and average rates of movements over time, rather than reflecting any kind of reality of census size and mobility in the ancient communities the archaeologists are actually attempting to study.

The text goes on to talk about ways of studying fine-grained social dynamics of local cultures, such as:

define levels of genetic relatedness, but also in terms of material culture, age, sex, stress and activity indicators, stable isotopes for diet reconstruction (nitrogen, d13C and d15N, carbon, 13C/12C) and strontium and oxygen isotopes for mobility (87Sr/86Sr, d18O). Where possible, sites should be examined over multiple generations. In addition it will be incredibly useful to characterize the impact of disease in these communities, which is also proving to be a highly fruitful realm for paleogenomics.

I would say that the main problem is not the obvious limitations of palaeogenomics in terms of identifying prehistoric ethnolinguistic communities and their evolution, which is why it is just another tool to complement archaeology and linguistics. The main problem is the narrow understanding that some people have of the inherent limitations of palaeogenomics – especially when it interests them – , when publicizing simplistic conclusions based on these tools and their results. And I am not referring only to amateurs.

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Inca and Spanish Empires had a profound impact on Peruvian demography

peru-population-history

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.

peru-admixture
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).

peru-population-pca
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). (…)

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