Human migration tracked in Stanford computer simulation

Early humans migrating from Africa carried small genetic differences like so much flotsam in an ocean current. Today’s studies give only a snapshot of where that genetic baggage came to rest without revealing the tides that brought it there. Now researchers at the Stanford University School of Medicine have devised a model for pinpointing where mutations first appeared, providing a new way to trace the migratory path of our earliest ancestors.

The study was led by Luca Cavalli-Sforza, PhD, emeritus professor of genetics, who has spent most of his career tracking the evolution of modern humans. Much of his current 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 during the past 50,000 years.

These mutations, most of which cause no physical change, tend to appear at a constant rate, providing a genetic timer. For example, if a population has 10 mutations after 50,000 years of evolution from the common ancestor in Africa, then the fifth mutation probably arose 25,000 years ago. 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.

With the help of senior application software developer Christopher Edmonds and statistician Anita Lillie, both researchers at Stanford, Cavalli-Sforza built a computer model to simulate how mutations spread in a migrating population. The results of this work are published in this week’s online issue of Proceedings of the National Academies of Science.

The group reduced the world’s continents to a simple rectangular grid. They populated the first few squares with computerized human populations and gave those electronic villages realistic rates for population growth, migration and mutations. The inhabitants had more than one child, on average, and those offspring could migrate to any neighboring square as long as it wasn’t filled to capacity. This population growth filled the initial squares to capacity and pushed the computerized people to migrate at a constant rate across their rectangular territory until the next space was filled.

When a mutation appeared within a population, descendants reproduced and migrated at the same rate as other individuals. Most of the mutations, however, simply disappeared due to chance.

Those mutations that stayed in the population until the simulation ended showed one of two patterns. If the mutation appeared in a heavily populated area, it had a lower chance of surviving for many generations or reaching high numbers. In these cases, the mutation remained extremely rare in the local population.

If a mutation appeared in a person at the edge of the migration front where the population was scarce, the mutation was more likely to spread through the population. The mutation-carrying person multiplied and the offspring migrated, taking the mutation to neighboring squares. If these neighboring squares were previously unoccupied, the mutated person had a high probability of reproducing and passing along the mutation. The mutation itself remained most common in the migratory wave front, a situation Cavalli-Sforza refers to as “surfing” the migratory wave.

Over the course of 64,000 simulations, the group came up with a model for finding 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 area 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.

In at least some simulations, the mutation no longer existed in the population where it first arose. Without the group’s way of estimating distance, there might be no trace of the mutation’s place of origin. Now they can generate a dated “we were here” sign to place on the route of human migration.

Stanford University Medical Center integrates research, medical education and patient care at its three institutions – Stanford University School of Medicine, Stanford Hospital & Clinics and Lucile Packard Children’s Hospital at Stanford. For more information, please visit the Web site of the medical center’s Office of Communication & Public Affairs at http://mednews.stanford.edu.

Media Contact

Amy Adams EurekAlert!

More Information:

http://mednews.stanford.edu

All latest news from the category: Studies and Analyses

innovations-report maintains a wealth of in-depth studies and analyses from a variety of subject areas including business and finance, medicine and pharmacology, ecology and the environment, energy, communications and media, transportation, work, family and leisure.

Back to home

Comments (0)

Write a comment

Newest articles

Combining robotics and ChatGPT

TUM professor uses ChatGPT for choreographies with flying robots. Prof. Angela Schoellig has proved that large language models can be used safely in robotics. ChatGPT develops choreographies for up to…

How the Immune System Learns from Harmless Particles

Our lungs are bombarded by all manner of different particles every single day. Whilst some are perfectly safe for us, others—known as pathogens—have the potential to make us ill. The…

Biomarkers identified for successful treatment of bone marrow tumours

CAR T cell therapy has proven effective in treating various haematological cancers. However, not all patients respond equally well to treatment. In a recent clinical study, researchers from the University…

Partners & Sponsors