February 18, 2016
Matthias Steinrücken, Assistant Professor of Biostatistics, is part of a large international team of researchers using genomic analysis to trace the origins of the first Native Americans. Steinrücken and colleagues published their findings in an article titled “Genomic evidence for the Pleistocene and recent population history of Native Americans” that appeared in the journal Science.
The team compared the genomes of 31 living Native Americans, Siberians and people from Oceania with 23 ancient Native American genomes to establish a timeline for the arrival and spread of Amerindian populations. Using ancient and modern genome-wide data, the researchers concluded that the ancestors of all present-day Native Americans entered the Americas no earlier than 23,000 years ago as a single migration wave traveling from Siberia to Alaska during the height of the last Ice Age. Eventually, according to their genomic analysis, the early Americans diverged into two distinct populations: one branch distributed throughout North America, and the other peopled Central and South America, as well as part of northern North America.
Contrary to competing theories, the researchers found no evidence for multiple migration waves crossing from Asia into the Americas, nor evidence that Polynesians or Europeans contributed to the genetic heritage of Native Americans. The Inuit and Eskimo people arrived much later, spreading throughout the Arctic beginning about 5500 years ago.
The analysis, using the most comprehensive genetic data set from Native Americans to date, was conducted using three different statistical models. Steinrücken, together with colleagues from the University of California Berkeley, led the development of one of those models, applying it to the genomic sequence data and adapting and refining the method as needed.
In addition to helping to improve our understanding of how ancient populations settled the Americas, Steinrücken says that the statistical models he helped to develop can be applied to discovering how disease associated genetic variation works at the population level. Says Steinrücken, “Unravelling our demographic history is a necessary foundational step to enable researchers to detect disease associated genetic variation in genome wide association studies. Furthermore, the model underlying the statistical method can be used to detect local ancestry in genomic data, that is, trace the origin of different regions in the genome of given individuals. This is a key step in performing admixture disease mapping to identify candidate regions that harbor disease related genetic variation.”