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However, technology is increasingly becoming more competent in doing the analysis that we humans couldn\u2019t hope to achieve in a reasonable amount of time. This case appears to be all the more evident with findings published in the journal Nature Communications<\/em> back in 2019, where scientists were able to determine that we may have a \u201cghost\u201d lineage, from an as-of-yet unknown species of human ancestor, present within our genome\u2014and they found it with the help of artificial intelligence.<\/p>\n\n\n\n Said author and Universitat Pompeu Fabra evolutionary biologist Jaume Bertranpetit, ancient humans interbred with other extinct hominids as our species made an exodus out of Africa “about 80,000 years ago, […] when part of the human population, which already consisted of modern humans, abandoned the African continent and migrated to other continents, giving rise to all the current populations.\u201d<\/p>\n\n\n\n It was thought that our species only made contact\u2014and interbred\u2014with Neanderthals and Denisovans, whose genomic heritage is still visible in modern humans today<\/a>. However, the study by Bertranpetit and co-authors found a third \u201cintrogression<\/em>\u201d in our lineage from Eurasian DNA samples.<\/p>\n\n\n\n They found this \u201cghost\u201d lineage by employing the help of deep learning algorithms and a statistical inference technique called Bayesian inference<\/em>. The authors believe the \u201cghost\u201d lineage to be either \u201crelated to the Neanderthal-Denisova clade\u201d or a lineage which \u201cdiverged early from the Denisova lineage.\u201d<\/p>\n\n\n\n Temple University evolutionary genomics expert Joshua Schraiber described the deep learning method used in the study as \u201cfitting a more complicated shaped thing to a set of points in a bigger space.\u201d \u201c[You\u2019re] fitting some squiggly thing to a set of points in [a] much bigger, thousand-dimensional space. Deep learning says, \u2018I don’t know what squiggly shape should fit to these points, but let’s see what happens.\u2019\u201d<\/p>\n\n\n\n The team trained the algorithm using eight (8) known models of early Eurasian human evolution. From there, it projected how evolution would progress in such a way that it maintains the Out-of-Africa aspect of the theory, as well as reach the current population diversity that Eurasia has today. In doing so, the team found evidence pointing towards the new \u201cghost\u201d lineage.<\/p>\n\n\n\n “Our theory coincides with the hybrid specimen discovered recently in Denisova, although as yet we cannot rule out other possibilities”, said by co-author and University of Tartu genomicist Mayukh Mondal in a press statement.<\/p>\n\n\n\n Bertranpetit and team know that their research methodology is basically at its infancy, and results from using these technical methods are pretty few and far between. However, the team believes they are on to something pretty remarkable in their findings.<\/p>\n\n\n\n In Bertranpetit\u2019s statement to the Smithsonian Magazine: “We thought we’d try to find these places of high divergence in the genome, see which are Neanderthal and which are Denisovan, and then see whether these explain the whole picture. As it happens, if you subtract the Neanderthal and Denisovan parts, there is still something in the genome that is highly divergent.”<\/p>\n\n\n\nReferences<\/h2>\n\n\n\n
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