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Patterns of ancient human migrations tracked by computer simulation

Researchers can pinpoint ‘we were here’ signs from our human ancestors


Early humans migrating from Africa carried small genetic differences like so much flotsam in an ocean current. Today’s studies have given only a snapshot of where that genetic baggage came to rest without revealing where the changes arose. Until now.

Researchers at the School of Medicine have devised a model for pinpointing where mutations – most of which cause no physical change – first appeared. The work provides a new way to trace the migratory path of early humans.

The project was led by Luca Cavalli-Sforza, PhD, professor of genetics, emeritus, who spent most of his career tracking the evolution of modern humans. Much of this work involves following mutations in the Y chromosome – which is passed exclusively from father to son – as humans migrated from Africa and spread to the rest of the world over the past 50,000 years.

Based on his Y chromosome studies, Cavalli-Sforza traced the point in time any given mutations appeared in a population. But where was the population located at that time? Until now genetics hasn’t had an answer.

“If we know the time when a mutation arose, we know something. If we also knew the place, we’d know almost everything,” Cavalli-Sforza said. Knowing both the date and location of the mutation’s origin enables researchers to place a dated “we were here” sign on the route of human migration.

With the help of senior application software developer Christopher Edmonds and statistician Anita Lillie, both of Stanford, Cavalli-Sforza built a computer model to simulate how mutations spread in a migrating population.

The results of this work were published online in the Jan. 20 issue of Proceedings of the National Academies of Science.

Over the course of 64,000 simulations the group noticed two trends. If a mutation appeared within a settled computer “village,” it usually disappeared due to chance. If it did persist in the population, it remained rare.

If, on the other hand, the mutation appeared in a migrating population, it became common in that group. That’s because the population was smaller, so the mutated individual had a higher chance of passing along the genetic trait. The mutation remained most common at the leading edge of the migration, a situation Cavalli-Sforza refers to as “surfing” the migratory wave. Eventually, mutations become most common at boundaries, such as the edge of continents, where migration screeched to a halt.

From these simulations the group came up with a model for pinpointing a mutation’s origin. First they identified the mutation’s farthest edge – corresponding with a boundary such as the ocean or mountain range in human populations. Then they calculated the average location of where the mutation is distributed – called the mutation’s centroid. According to the models, the centroid is about half the distance between where the mutation arose and where it ended up.

By following the migratory route backward from the centroid researchers can flag the spot where the mutation arose. Combining the mutation’s birthplace with the evolutionary date of the mutation’s origin, geneticists can map the progress of early humans traveling across continents.

How the model works

For their human migration simulation, Professor Luca Cavalli-Sforza and his team reduced the world’s continents to a simple rectangular grid. They populated left-hand squares with computerized human populations. These electronic villages had realistic rates for population growth, migration and mutations.

The simulated inhabitants reproduced and those offspring could migrate to any neighboring square as long as it wasn’t filled to a pre-set capacity. This population growth filled the initial squares, then pushed the computerized people to migrate at a constant rate across their rectangular territory until all the spaces were filled.

When a mutation appeared, descendants reproduced and migrated at the same rate as other individuals.

The simulation showed the mutation’s actual origin (a star in the figure below) and shaded the squares to indicate a mutation’s prevalence. An “X” indicates the mutation’s centroid.

On the left, a mutation arose in a migrating population and surfed the migratory wave to its boundary, where the mutation became common. On the right, a mutation appeared in an inhabited area but did not travel, remaining rare in the population.