The Journey of Man: A Genetic Odyssey (4 page)

Genetic variation was critical for the study of human diversity because is it is genetic change that actually produces evolution. At its most basic level, evolution is simply a change in the genetic composition of a species over time. Thus in order to assess how closely related
individuals are – in particular whether they form a single species – it is important to know something about their genes. If the genes are the same, then they are the same species. What physical anthropology desperately needed was a collection of varying traits – known as polymorphisms, from the Greek for ‘many forms’ – with a simple pattern of inheritance. These could then be used to study human diversity in an effort to categorize it. Some traits like this were already known, particularly diseases like haemophilia. The problem with disease-causing polymorphisms was that they were simply too rare to be of any use in classification. Common, genetically simple polymorphisms were critical.

These arrived in 1901, when Karl Landsteiner noticed an interesting reaction upon mixing the blood from two unrelated people: some of the time it clumped together, forming large clots. This coagulation reaction was shown to be heritable, and it constituted the first demonstration of biochemical diversity among living humans. This experiment led to the definition of human blood groups, which would soon be applied to transfusions all over the world. If your doctor tells you that you have type A blood, this is actually the name given by Landsteiner to the first blood group polymorphism over a century ago.

Building on Landsteiner’s insight, a Swiss couple named Hirszfeld began to test the blood of soldiers in Salonika during the First World War. In a 1919 publication, they noted different frequencies of blood groups among the diverse nationalities thrown together by the hostilities – the first direct survey of human genetic diversity. The Hirszfelds even formulated a theory (accepted by some to this day) in which the A and B blood groups represent the traces of ‘pure’ populations of aboriginal humans, each composed entirely of either A or B individuals. These pure races later became mixed through migration, leading to the complicated patterns of A and B seen in their study. They failed to explain how the two races may have arisen, but given that group A was thought to have originated in northern Europe, while B was a southern marker at highest frequency in India, it seems that there must have been two independent origins of modern humans.

In the 1930s an American named Bryant and an Englishman named Mourant, building on the work of the Hirszfelds, began to test blood samples from around the world. Over the next thirty years these two
men and their colleagues would examine thousands of people, from hundreds of populations, both living and dead. Bryant and his wife (like the Hirszfelds, another of the marital duos in population genetics) even went so far as to test American and Egyptian mummies, establishing the ancient nature of the ABO polymorphisms. In 1954 Mourant drew together the rapidly expanding body of blood group data in the first comprehensive summary of human biochemical diversity,
The Distribution of the Human Blood Groups
– a seminal work that became the standard text of experimental human population genetics for the next twenty years. This was the beginning of the modern era of human genetics.

While the Hirszfelds clearly felt that their data on blood groups supported a racial classification that had become blurred by recent migration, and Carleton Coon later used them to support his theories of discrete subspecies, no one had actually tested the genetic data to see if there was any real indication of racial subdivision. This obvious analysis was finally carried out in 1972 by a geneticist whose primary research interest, oddly enough, was fruit flies – not humans.

Using the data collected by Mourant and others, Richard Lewontin, then a professor at the University of Chicago, performed a seemingly trivial study of how human genetic variation sorted into within- versus between-group components. The question he was tying to answer, objectively, was whether there was any indication in the genetic data of a distinct subdivision between human races. In other words, he was directly testing the hypotheses of Linnaeus and Coon about human subspecies. If human races showed significant differences in their patterns of genetic diversity, then Linnaeus and Coon must be right.

Lewontin describes the development of the analysis:

The paper was written in response to a request … to contribute an article to the new journal
Evolutionary Biology
. I had been thinking at that time about diversity measures … not in the context of population genetics, but in the context of ecology. I had to take a very long bus trip to Bloomington, Indiana, and I had long had the habit, when going on trains and buses, of writing papers. I needed to write this paper, so I went on the bus trip with a copy of Mourant and a table of p
ln
p [a mathematical table used for calculating the diversity measure].
On this bus trip, he began what would become one of the landmark studies in human genetics. In the analysis, Lewontin used as his model the new science of biogeography (the study of animal and plant geographic distributions) because he thought this was analogous to what he was doing with humans – looking for geographic subdivisions in order to define race. In fact, unsure of how to define a ‘race’ objectively, he divided humans largely along geographical lines – Caucasians (western Eurasia), Black Africans (sub-Saharan Africa), Mongoloids (east Asia), South Asian Aborigines (southern India), Amerinds (Americas), Oceanians and Australian Aborigines.

The surprising result he obtained was that the majority of the genetic differences in humans were found within populations – around 85 per cent of the total. A further 7 per cent served to differentiate populations within a ‘race’, such as the Greeks from the Swedes. Only 8 per cent were found to differentiate between human races. A startling conclusion – and clear evidence that the subspecies classification should be scrapped. Lewontin says of the result:

I had no expectation – I honestly didn’t. If I had any prejudice, it probably was that the between-race difference would have been a lot larger. This was reinforced by the fact that, when my wife and I were in Luxor [Egypt], years before it was overrun with tourists, she got in a discussion with a guy in the lobby. He was talking to her as if he knew her. She kept saying ‘I’m sorry, sir, you’ve mistaken me for someone else.’ Finally he said, ‘Oh, I’m sorry madam – you all look alike to me.’ That really had a big effect on my thinking – they really are different from us, and we’re all alike.

But the result was there in the statistical analysis, and it has been confirmed by many other studies over the past three decades. The small proportion of the genetic variation that distinguishes
between
human populations has been debated endlessly (is it higher within or between races?), but the fact remains that a small population of humans still retains around 85 per cent of the total genetic diversity found in our species. Lewontin likes to give the example that if a nuclear war were to happen, and only the Kikuyu of Kenya (or the Tamils, or the Balinese …) survived, then that group would still have
85 per cent of the genetic variation found in the species as a whole. A strong argument indeed against ‘scientific’ theories of racism – and clear support for Darwin’s assessment of human diversity in the 1830s. It really was a case of ‘out of many, one’, as the title of this chapter says in Latin. But does this mean that the study of human groups is meaningless – can genetics really tell us anything about human diversity?

For the next step on our journey, we need to cover some basic population genetics. The theory of how genes in a population behave over time is fairly complicated, and makes use of many related branches of quantitative science. Statistical mechanics, probability theory and biogeography have all contributed to our understanding of population genetics. But many of the theoretical frameworks are based on a few key concepts that can be understood by anyone, reflecting the relative simplicity of the forces involved.

The most basic force is mutation, and without it polymorphism would not exist. By mutation I mean a random change in a DNA sequence – these occur at a rate of around thirty per genome per generation. Looking at it another way, each person alive today is carrying around thirty completely novel mutations that distinguish them from their parents. Mutations are random because they arise as copying mistakes during the process of cell division, with no particular rhyme or reason as to where those mistakes might occur – our genomes do not appear to favour certain types of mutation based on what the effect might be. Rather, we are like Heath Robinson engineers, forced to make use of what we are given in the mutational lottery. The blood group variants discovered by Landsteiner originated as mutations, as do all other polymorphisms.

The second force is known as selection, in particular natural selection. This is the force that Darwin got so excited about, and it has certainly played a critical role in the evolution of
Homo sapiens
. Selection acts by favouring certain traits over others by conferring a reproductive advantage on their bearers. For example, in cold climates
animals with thick fur would have an advantage over hairless ones, and their offspring would be more likely to survive. Selection is certainly what has made us the sentient, cultured apes we are today. It is what produced the important traits of speech, bipedalism and opposable thumbs. Without natural selection we would still be very similar to the relatively unsophisticated ape-like ancestor we would encounter if we could go back in time 5 million years or so.

The third force is known as genetic drift. This is a rather specialized term for something we have an innate sense of – the tendency of small samples to reflect a biased view of the population from which they are drawn. If you flip a coin 1,000 times, you expect to get around 500 heads and 500 tails. If, on the other hand, you flip the coin only 10 times, it is quite likely that you will get something other than a 5–5 outcome – perhaps 4–6 or 7–3. This random fluctuation in a sampled group is due to the small number of individual events in the sample. If we think of people as genetically sampled ‘events’, and assume that the population from which we will draw the sample for the
next
generation is created anew in the
present
generation (as is the case for living organisms), then you can see that small population sizes can lead to drastic changes in gene frequency within only a few generations. In the case of our coin flippers, getting a result of 7–3 would be reflected in the likelihood of flipping that number in the next generation, with a 70 per cent chance of getting heads and 30 per cent of getting tails. It’s like a ratchet, because the probability change in the previous generation affects the probability in the subsequent generations. In the coin-flipping analogy, we’ve gone from a frequency of 50 per cent to 70 per cent in a single generation – a pretty rapid change. Clearly, drift can have a huge effect on gene frequencies in small populations.

The combination of these three forces has produced the dizzying array of genetic patterns we see today – and the vast diversity we see in human populations. Their action has also produced the small percentage of human variation that distinguishes between human groups. That much was known by the middle of the twentieth century. But simply recognizing the existence of human diversity at a biochemical level, and knowing something about the way genes behave in populations, didn’t really say much about the details of human evolution and migration. Enter an Italian physician with a historical bent
and a talent for mathematics, who came to the field influenced by a new way of thinking about bacteria and flies.

Luigi Luca Cavalli-Sforza had started his career in Pavia as a medical student. He soon left medicine to devote himself to genetics research, first on bacteria and later on humans. At university he had studied under the famous
Drosophila
geneticist Buzzati-Traverso, who was an adherent of the Dobzhansky school of genetics. Theodosius Dobzhansky had also been Richard Lewontin’s PhD supervisor, and the story therefore begins to show a common thread. The main theme of Dobzhansky’s research was the study of genetic variation, in particular large-scale chromosomal rearrangements in fruit flies. He pioneered techniques in genetic analysis, and his laboratory in New York was to be the epicentre of a revolution in biology during the mid-twentieth century. Dobzhansky and his students advocated a new view of genetic variation in which there was no division into an optimized ‘wild type’ (the normal form of the organism, created through a long period of natural selection) and a quirky ‘mutant’, invariably disadvantaged in some way. This was too simplistic, they thought – primarily because there was simply too much variation to account for if most of the mutants were carrying a suboptimal genetic package. If, instead, one thought of variation as the normal state of species, then evolution suddenly made much more sense. There was a previously unrecognized reservoir of different types on which evolution could act – favouring some in one case, losing them in another.

So, with a thorough background in the seemingly disparate fields of fruit-fly variation and medicine, Cavalli-Sforza began to conduct studies of blood polymorphisms – later termed ‘classical’ polymorphisms by geneticists – in an effort to assess the relationships among modern humans. This work was begun in the 1950s, a heady time for the field of genetics. The structure of DNA had just been deciphered by Crick and Watson, and the application of the methodology of the physical sciences promised a revolution in biology. Like most geneticists, Cavalli-Sforza made use of the rapidly developing techniques
of biochemistry to assay variation. But unlike many of them, he was also comfortable with the application of mathematics – particularly its most pragmatic branch, statistics. The dizzying variety of the data being generated by studies of polymorphisms needed a coherent theoretical framework to make it understandable. And statistics was about to ride to the rescue.