European ancient DNA – the movie

by Edward Pegler on 1 October, 2017

We have learned loads from the autosomal DNA analyses of Europe’s ancient populations which have poured out of Harvard and other universities in the last two years. Europe was a restless place, changing people more than some of us would have guessed. Here’s the movie adaptation.

I put together the video above for my own benefit because I wanted to see what the latest genetic results showed. However, even though it’s a bit crude at the moment (Flash MX 2002 anyone?) it seems like potentially a good way of looking at the new info on ancient autosomal DNA that’s coming out.

What is it?

The background of the video is what’s known as a PCA plot (principal components analysis), which is designed to display data with many variables. This one I have taken from Mathieson et al. (in press). Each dot represents one person’s DNA profile. The grey dots show modern individuals from Europe and the Middle East who have had their full genomes (or DNA) sequenced. The coloured dots show various ancient people from Europe and the Middle East who have been dug up and had their DNA sequenced too (lucky them… and for free too).

In the case of someone’s DNA there are many variables, usually referred to as single nucleotide polymorphisms, or SNPs, within their personal sequence. The PCA plot is designed to show the variability  between different individuals’ DNA sequences. The maximum variability between sequences is plotted on the x-axis (called principal component 1, or PC1). Once this maximum variability has been accounted for, then the next lot of variability extremes are plotted on the y-axis as PC2 (if you want a proper explanation of this, then learn statistics and matrices).

Suffice to say, the graph is good at showing up variabilities of people’s DNA sequences. However, the axes themselves tell you nothing at all really.

All I’ve done is overlaid on this PCA plot the currently determined genetic positions of people located a number of European and Middle Eastern nations (indicated by their flags) for the last ten thousand years. This is based on the data of various academic groups (listed in the references below). It’s not perfect. There are plenty of holes and biases in the data. But it’s a start.

What are the national flags for?

Each of the circular flags represent the genetics through time (based on the available data) of people in the geographical area now represented by the country with that flag. For those of you who are thinking ‘why is my glorious nation not represented?’ it’s because only some nations so far have had enough ancient DNA studied to provide a sufficiently good picture of what’s happened in the last ten thousand years. Using nearby nations as proxies may help but, either way, it’s irrelevant as your DNA doesn’t belong to a nation anyway.

Anyway… so, for Ukraine, say (blue and yellow flag), the people who lived there in 8000 BC appear to have the genetic composition shown on the plot. The people who now live in Ukraine have a different genetic composition, in large part because of the influx of people from elsewhere during the last 10 thousand years. How that composition is thought to have changed over time is shown by the video (Ukraine is particularly wierd in this respect as its DNA isn’t even consistent, as shown by the flag splitting in the movie. In truth this probably happens for all nations).

It’s important to understand what the movie is showing. Firstly, the moving flags do not show moving countries. What they show is how people in the area of a particular modern country have changed genetically over this period.

So here are the rules of reading the movie:

The Rules

RULE 1: Movements of the little flags are generally due to the influx of people from somewhere else into that region. The more rapid the movement, the more likely that the existing population is displaced, killed or swamped by the incomers.

CAUTION! all this evidence is based on burials, so people retreating to the mountains, say, are less likely to show up in ancient DNA studies (mountain burials tend to be more difficult and less well preserved ). Also some cultures don’t bury people which makes it very difficult to analyse their bones (I’ve had to guess where Britain started). If the flags start to move back on themselves, this could well be an indicator that the genes of earlier populations of that area, under-represented on the movie, are becoming mixed in with the new immigrants.

RULE 2: The geographical origin of the immigrants is given by the direction toward which the flag moves. Any national flags lying on the path to which the flag is moving could be the geographical locations of the immigrants. To solve which of these flags is the right one is more complex and requires statistical analysis of SNPs.

RULE 3: The amount of population change is indicated by how far the flag moves toward the immigrant flag nation. Obviously this is easier to tell if there’s only one flag in the way.


You can see that for many European countries there have been two major movements of the little flags indicating population swamping or replacement. The first is at the time of initial colonisation of those lands by farmers between 7000 and 4000 BC. The second is what must have been a traumatic phase of migration from the Russian and Ukrainian Steppes at the beginning of the Bronze Age between 3400 and 2500 BC.

However, you might be able to spot other things in the data which have not been commented on so much. The one I’ve noticed is how everyone in northern Europe now appears to be moving toward a ‘ghost’ population at the right hand end of the plot. This is either due to a problem with interpolation of missing bits of ancient DNA (known as ‘imputing’), meaning that many ancient samples may be plotted too far to the right, or is due to the influx of Scandinavian and Siberian hunter-gatherers, and perhaps some other central Asian peoples, over the last few thousand years.

Either way, the data is still in its early stages. The excitement of the last two ‘Reich Lab’ years will calm down as further sampling of ancient DNA becomes more standard. Many errors and tweaks will be found in current interpretations. There’s also a real lack of Iron age and Medieval data in the studies. There is so much wrong with the video above which can only be improved with time (I hope by someone else with better software).

As a personal opinion I suspect that the little flags’ movements may turn out to be much more jerky over the last few millennia than they seem to be here, and that the Eastern European countries will be bouncing around and splitting quite a lot in this period.

Either way, as Svante Paabo has recently said, this is a revolution for archaeology as big as the radiocarbon one of the 1940s and 1950s. Time to rewrite all those books.


Mathieson, I. et al. (in press) The Genomic History of Southeastern Europe, (review copy posted on bioarxiv 9 May 2017, revised 19 September)

The major source for the info in this post is the PCA plot in the supplementary information. Other useful info comes from the following, including their supplementary information.

Günther, T. et al. (in review) Genomics of Mesolithic Scandinavia reveal colonization routes and high latitude adaptation, (review copy posted on bioarxiv 17 July 2017, revised 30 July)

Lazaridis I. et al. 2017 Genetic origins of the Minoans and Mycenaeans, Nature 548. 214-8.

Lipson, M. et al. (in press) Parallel ancient genomic transects reveal complex population history of early European farmers, (review copy posted on bioarxiv 6 Mar 2017)

Martiniano, R. et al. 2017 The population genomics of archaeological transition in west Iberia, PLoS Genetics 13, pp24.

Mittnik, A. et al. (in press) The Genetic History of Northern Europe, (review copy posted on bioarxiv 3 Mar 2017).

Olalde, I. et al. (in press) The Beaker Phenomenon and the Genomic Transformation of Northwest Europe, (review copy posted on bioarxiv 9 May 2017)

Reich D. et al. 2016 Ancient DNA analysis of St. Mary’s City Lead Coffins Burial, Technical report, Harvard.

Saag, L. et al. (in press) Extensive farming in Estonia started through a sex-biased migration from the Steppe, (review copy posted on bioarxiv 2 Mar 2017)

Unterländer M. et al. 2017 Ancestry and demography and descendants of Iron Age nomads of the Eurasian Steppe, Nature Communications 8, 14615.

Other source papers

Allentoft, M.E. et al. 2015 Population genomics of Bronze Age Eurasia, Nature 522, 167-174.

Broushaki, F. et al. 2016 Early Neolithic genomes from the eastern Fertile Crescent, Science 353, 499-503.

Cassidy, L.M. et al. 2016 Neolithic and Bronze Age migration to Ireland and establishment of the insular Atlantic genome, PNAS 113, 368–373.

Fu, Q. et al. 2016 The genetic history of Ice Age Europe, Nature 534, 200-205.

Gallego-Llorente, M. et al. 2016 The genetics of an early Neolithic pastoralist from the Zagros, Iran, Scientific Reports 6, pp7.

Günther, T. et al. 2015 Ancient genomes link early farmers from Atapuerca in Spain to modern-day Basques, PNAS 112, 11917–11922.

Haak W, et al. 2015 Massive migration from the steppe was a source for Indo-European languages in Europe, Nature 522, 207-11.

Hofmanová, Z. et al. 2016 Early farmers from across Europe directly descended from Neolithic Aegeans, PNAS 113, 6886–6891.

Jones, E.R. et al. 2015 Upper Palaeolithic genomes reveal deep roots of modern Eurasians, Nature Communications 6, 1-7.

Jones, E.R. et al. 2017 The Neolithic Transition in the Baltic Was Not Driven by Admixture with Early European Farmers, Current Biology 27, 1-7.

Kilinç, G.M. et al. 2016 The Demographic Development of the First Farmers in Anatolia,

Lazaridis, I. et al. 2016 Genomic insights into the origin of farming in the ancient Near East, Nature 536, 419-24.

Mathieson, I. et al. 2015 Genome-wide patterns of selection in 230 ancient Eurasians, Nature 528, 499-503.

Olalde, I. et al. 2015 A Common Genetic Origin for Early Farmers from Mediterranean Cardial and Central European LBK Cultures, Molecular Biology and Evolution 32, 3132-3142.

Omrak, A. et al. 2017 Genomic Evidence Establishes Anatolia as the Source of the European Neolithic Gene Pool, Current Biology 26, 1-6.

Skoglund, P. et al. 2014 Genomic Diversity and Admixture Differs for Stone-Age Scandinavian Foragers and Farmers, Science 344, 747-750.





What type of grass are you on, Jared?

by Edward Pegler on 5 July, 2017

Does agriculture start with lucky grass, as Jared Diamond says, or does lucky grass start with agriculture.

I’ve been sitting enjoying the weather in my garden in Swindon, England. It’s a mess, full of random weeds and overgrown grass. But who cares? The Sun’s out.

And there is a particularly fine, architectural grass growing just next to me here which I couldn’t help pulling a few spikelets off, rubbing them in my hands and seeing, after some careful winnowing, what was left. There, in my palm, were a few tiny brown seeds, about a millimetre long.

From what I can tell, the grass I’ve been handling is Phleum pratense, or ‘purple-stem cat’s tail’. It grows widely in light soils across the Eurasian steppe from here in Britain to there in China, but is of no great interest to anyone and I don’t think it’s ever been cultivated.

But those tiny seeds in my hand made me think of how far the grass-based grain crops of the world, maize, wheat, millet, etc. have come in ten thousand years and the shear hassle they must have been to collect enough sustenance off in their primitive forms.

Undoubtedly, primitive barley was an easier source of protein that primitive maize (teosinte). But was that just the luck of the draw in places where people chose to start agriculture anyway.

Jared Diamond’s argument in ‘Guns, Germs & Steel‘ was simple. That luck was crucial. Farming started where the grass was best, in the Middle East. But tell that to the Mesoamericans who persevered with the unbelievably unpromising teosinte.

So, let’s take a momentary fight of fancy and say that in some parallel universe farming started right here, in what was destined to become Swindon. What grass from the unpromising range of grasses on offer here would those ancient Swindonians have picked. Perhaps purple stem cat’s tail, with its tiny, but protein-rich seeds, would have been one of them. Perhaps millennia later we’d be amazed at the widespread use of Cat’s Tail as one of the major carbohydrate sources of the world’s burgeoning population.

And an alternative Jared would be extolling the good-fortune of the those who lived thousands of years ago in Swindon (not something often said about the place now), as they harvested local wild grasses.


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