A bizarre but popular bit of Science Denialist conventional wisdom that emerged out of a 2000 ceremony that Bill Clinton hosted in the Rose Garden for the Human Genome Project was the myth that modern genetic analysis had some proven that traditional racial designations were mass psychoses that didn’t reflect underlying genetic differences.

In reality, the opposite was true. By 2008 the above graph/map had been published for Europe. Here’s an interview with a geneticist who worked on this. From Quanta:

A Map of Human History, Hidden in DNA

The computational biologist John Novembre uses our genetic code to rewrite the history of humanity. By Ariel Bleicher

April 20, 2017 QUANTA MAGAZINE: What got you thinking about genetic diversity as a computational problem? JOHN NOVEMBRE: For me, the path starts pretty far back. In high school, I was a bit of a computer programming nerd. But in my classes, I was learning about the genetic code, which was completely mesmerizing. Then in college, I got a chance to do a summer research internship at Stanford, where I heard a talk by a student who had interned in Luigi Luca Cavalli-Sforza’s lab. What they do — what they’ve become famous for — is to look at variations in human genes, how they’re distributed across the globe, and what they can tell us about human history. That was fascinating to me. … I was hoping to get access to genetic data from a region of the world where there’s dense sampling, so that I could see what variation looks like at a continuous scale, where populations kind of blend into one another. And it turned out I was very lucky in that I got invited to join a collaboration with Carlos Bustamante, [then] at Cornell, to analyze one of the largest collections of [genomic data] being applied to human populations. The full data set was 3,192 European individuals. A large fraction of the sample had answered an ancestry questionnaire to say where their grandparents came from, and based on that, we saw we had samples from roughly 37 different origins across Europe. Q. So what did you learn? When we applied PCA, right away we saw this major pattern: There was a striking resemblance between where individuals are located in genetic space and their geography — where their grandparents came from.

In other words, when you plot the first two principal components of Europeans, the scatterplot is basically a map of Europe, with the Irish in the upper left corner and Greeks in the lower right corner.

That’s really remarkable given how closely related human individuals are. Most geneticists wouldn’t have thought you could tease apart very fine-scale structure within continental scales. Q. How fine-scale are we talking about? Let’s say I took an individual and hid their geographic location and then tried to put them back on a map. How well could I do? When we did this, we could often get within a few hundred kilometers. Even when we looked at German-speaking Swiss versus French-speaking Swiss versus Italian-speaking Swiss, we could see shifts in the genetic distribution. Q. I’m surprised that my grandparents’ geographic coordinates could have such a notable effect on my genetics, given how often humans migrate. How do you explain this influence? This is something I want to stress: The effect on your genetics is actually incredibly small. It’s just that we’re looking at so many locations in the genome that we can pick up very small effects. This is the magic of big data: Very subtle patterns become detectable. So it’s not that where your grandparents live has a huge impact on your genetics. It’s actually a very, very minor effect. But when you have hundreds of thousands of measurements, you can start to pick out that an individual seems to come from one location versus another. … One of the tools we’ve developed is a method that tells us where in a landscape there is more or less gene flow — in other words, how individuals are moving between populations. … So we’re able to produce a geographic map that is colored in brown and blue to represent areas of low and high migration. … When we run it on the human data from Europe, for instance, we see it infers a brown area of reduced migration between the U.K. and France, representing essentially the English Channel. We see a lot of blue — high migration — in the North Sea because of historical connections there, such as Viking contacts between Scandinavia and the U.K. Then we see brown diffusely around Switzerland and Austria, which we think represents the Alps. Q. Did you get any puzzling results, such as areas of low or high migration that don’t seem to jibe with the landscape? A. I’m more surprised by how often the genetics do align with the geological features. You take a bunch of living individuals and extract a molecule from their bodies and start comparing them to one another, and you can see that the Alps are a feature of our planet. It’s kind of wild.

Most of the continental-scale racial differentiation in the world is due to geographic barriers even more stringent than the Alps: the Himalayas, the Sahara, and the great oceans. For example, the Alps have pretty fairly low altitude passes, such as Brenner between Austria and Italy at 1,370 meter or 4,500 feet.

In contrast, the lowest passes over the Himalayas and Karakorams are at least 14,000 feet. Kora La pass at 15,290 feet is described as the lowest pass over the Himalayas. Interestingly, high-altitude adapted Tibetans live on both sides of the range, but they don’t live much below 5,000 feet because they are less well-adapted to tropical warm-weather diseases.

The biggest barriers to gene flow typically were oceans, but for whatever reason it’s hard for 21st Century Americans to look at a map of the world and notice how oceans create the biggest racial divisions. Here’s a map I made in 2005 showing routes largely not taken before c. 1492:

For example, before Columbus, there had been virtually no gene flow back and forth between South America and sub-Saharan Africa, even though they are only 1,600 miles apart. Before 1492, the main connection between Africa and South America was the incredibly remote Siberia-Alaska route.

Not surprisingly, pre-1492 natives of South America and of Africa look different both to the naked eye and to genomic analysis.