A recent study used machine learning technology to analyze eight leading models of human origins and evolution, and the program identified evidence in the human genome of a “ghost population” of human ancestors. The analysis suggests that a previously unknown and long-extinct group of hominins interbred with Homo sapiens in Asia and Oceania somewhere along the long, winding road of human evolutionary history, leaving behind only fragmented traces in modern human DNA.
The study, published in Nature Communications, is one of the first examples of how machine learning can help reveal clues to our own origins. By poring through vast amounts of genomic data left behind in fossilized bones and comparing it with DNA in modern humans, scientists can begin to fill in some of the gaps of our species’ evolutionary history.
In this case, the results seem to match paleoanthropology theories that were developed from studying human ancestor fossils found in the ground. The new data suggest that the mysterious hominin was likely descended from an admixture of Neanderthals and Denisovans (who were only identified as a unique species on the human family tree in 2010). Such a species in our evolutionary past would look a lot like the fossil of a 90,000-year-old teenage girl from Siberia’s Denisova cave. Her remains were described last summer as the only known example of a first-generation hybrid between the two species, with a Neanderthal mother and a Denisovan father.
Read more: https://www.smithsonianmag.com/science-nature/artificial-intelligence-study-human-genome-finds-unknown-human-ancestor-species-180971436/#Vi1mIGO14YYuz3Ej.99
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