OXFORD researchers believe they have created the largest ever family tree, taking a major step towards mapping the entirety of genetic relationships among humans.
The study was published today in the journal, Science, and builds on the past two decades of rapid advancements in human genetic research.
These advancements have generated genomic data for hundreds of thousands of individuals, including from thousands of prehistoric people.
Working out a way to handle data of this size had proved troublesome, until a new method published today by researchers at the University of Oxford’s Big Data Institute.
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Dr Yan Wong, evolutionary geneticist at the Big Data Institute and one of the principal authors of the study, said: “We have basically built a huge family tree, a genealogy for all of humanity that models as exactly as we can the history that generated all the genetic variation we find in humans today.
“This genealogy allows us to see how every person’s genetic sequence relates to every other, along all the points of the genome.
“This study is laying the groundwork for the next generation of DNA sequencing.
“As the quality of genome sequences from modern and ancient DNA samples improves, the trees will become even more accurate and we will eventually be able to generate a single, unified map that explains the descent of all the human genetic variation we see today.”
The study integrated data from eight different databases, and included a total of 3,609 genome sequences from 215 populations.
Algorithms predicted where common ancestors must be present, and the resulting network contained almost 27 million ancestors.
After adding location data, researchers were able to estimate where our predicted common ancestors lived.
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Lead author Dr Anthony Wilder Wohns, who undertook the research as part of his PhD at the Big Data Institute, said: “Essentially, we are reconstructing the genomes of our ancestors and using them to form a vast network of relationships.
“We can then estimate when and where these ancestors lived.
“The power of our approach is that it makes very few assumptions about the underlying data and can also include both modern and ancient DNA samples.
“While humans are the focus of this study, the method is valid for most living things, from orangutans to bacteria.
“It could be particularly beneficial in medical genetics, in separating out true associations between genetic regions and diseases from spurious connections arising from our shared ancestral history.”
The study was a collaboration between the Big Data Institute, the Broad Institute at Harvard University, and the University of Vienna.
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