On Feb. 24, 2022, researchers from the University of Oxford have used data from UK Biobank participants to look at changes to the brain on average 4.5 months after mild SARS-CoV-2 infection. The study was published in Science.

• New genealogical network of human genetic diversity reveals how individuals across the world are related to each other, in unprecedented detail
• The research predicts common ancestors, including approximately when and where they lived
• The analysis recovers key events in human evolutionary history, including the migration out of Africa
• The underlying method could have widespread applications in medical research, for instance identifying genetic predictors of disease risk

The past two decades have seen extraordinary advancements in human genetic research, generating genomic data for hundreds of thousands of individuals, including from thousands of prehistoric people. This raises the exciting possibility of tracing the origins of human genetic diversity to produce a complete map of how individuals across the world are related to each other.

Until now, the main challenges to this vision were working out a way to combine genome sequences from many different databases and developing algorithms to handle data of this size. However, a new method published today by researchers from the University of Oxford’s Big Data Institute can easily combine data from multiple sources and scale to accommodate millions of genome sequences.

Since individual genomic regions are only inherited from one parent, either the mother or the father, the ancestry of each point on the genome can be thought of as a tree. The set of trees, known as a “tree sequence” or “ancestral recombination graph”, links genetic regions back through time to ancestors where the genetic variation first appeared.

The study integrated data on modern and ancient human genomes from eight different databases and included a total of 3,609 individual genome sequences from 215 populations. The ancient genomes included samples found across the world with ages ranging from 1,000s to over 100,000 years. The algorithms predicted where common ancestors must be present in the evolutionary trees to explain the patterns of genetic variation. The resulting network contained almost 27 million ancestors.

After adding location data on these sample genomes, the authors used the network to estimate where the predicted common ancestors had lived. The results successfully recaptured key events in human evolutionary history, including the migration out of Africa.