Human Genetic Ancestry Uncovered by Computer Algorithm

The Rensselaer Polytechnic Institute announced a new computer algorithm developed by an international team of computer scientists, mathematicians and biologists that can correctly identify individuals' genetic ancestry in minutes without any prior knowledge of individuals' background.

Although the human genome is 99 percent the same for all humans, it is that 1 percent that makes us all different and that links us to different genetic backgrounds. Uncovering the genetic ancestry of individuals can have significant importance for two major contemporary interests. It can help to speed the work of anthropologists and historians who are investigating the origins of different populations and how the vast and diverse human population came to be. It can also help facilitate biomedical research so that treatments can be better customized for individuals.

The 1 percent difference between human genes can determine the major impacts of our responses to diseases, viruses, medications, and toxins. This program will help individuals understand their unique backgrounds and their unique responses to disease and environmental factors.

Petros Drineas, who is the senior author of the study and assistant professor of computer science at Rensselaer Polytechnic Institute, has said that this new computer algorithm, which uncovers genetic background, will be valuable for targeting drugs and other medical treatments as drugs and treatments can affect people from different genetic ancestries in very different ways. Further, according to Drineas, understanding genetic makeup is crucial to unraveling the genetic basis of complex diseases and opening the way for new research and treatments that are customized to the individual.

The program operated at more than 99 percent accuracy and correctly identified the ancestry of hundreds of individuals, including those from either similar or complex backgrounds, whose ancestries were unspecified. Drineas states that results were compared to existing databases and only one individual whose ancestry was equally Chinese and Japanese was incorrectly identified.

Identifications of genetic background are made by looking for specific DNA markers known a single nucleotide polymorphisms (SNPs pronounced "snips"). All that is needed from the individual is a DNA sample obtained from a simple cheek swab.

In addition to Drineas, the algorithm was developed by scientists from California, Puerto Rico, and Greece. The researchers involved include lead author Peristera Paschou from the Democritus University of Thrace in Greece; Elad Ziv, Esteban G. Burchard, and Shweta Choudhry from the University of California, San Francisco; William Rodriguez-Cintron from the University of Puerto Rico School of Medicine in San Juan; and Michael W. Mahoney from Yahoo! Research in California.

Gabrielle Demarco, "Computer program traces ancestry using anonymous DNA samples," Rensselaer Polytechnic Institute.