{"id":49996,"date":"2019-01-17T00:00:00","date_gmt":"2019-01-16T23:00:00","guid":{"rendered":"http:\/\/www.pcb.ub.edu\/artificial-intelligence-applied-to-the-genome-identifies-an-unknown-human-ancestor\/"},"modified":"2020-11-18T15:10:12","modified_gmt":"2020-11-18T14:10:12","slug":"artificial-intelligence-applied-to-the-genome-identifies-an-unknown-human-ancestor","status":"publish","type":"post","link":"https:\/\/www.pcb.ub.edu\/en\/artificial-intelligence-applied-to-the-genome-identifies-an-unknown-human-ancestor\/","title":{"rendered":"Artificial intelligence applied to the genome identifies an unknown human ancestor"},"content":{"rendered":"<p>One of the ways of distinguishing between two species is that while both of them may cross breed, they do not generally produce fertile descendants. However, this concept is much more complex when extinct species are involved. In fact, the story told by current human DNA blurs the lines of these limits, preserving fragments of hominids from other species, such as the Neanderthals and the Denisovans, who coexisted with modern humans more than 40,000 years ago in Eurasia.<\/p>\n<p>Now, researchers of\u00a0IBE, CNAG-CRG\u00a0and the University of Tartu have used deep learning algorithms to identify a new and hitherto-unknown ancestor of humans that would have interbred with modern humans tens of thousands of years ago. \u201cAbout 80,000 years ago, the so-called Out of Africa occurred, 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, explained <a href=\"https:\/\/www.ibe.upf-csic.es\/bertranpetit\" target=\"_blank\" rel=\"noopener noreferrer\">Jaume Bertranpetit<\/a>, principal investigator at the IBE and head of Department at the UPF. \u201cWe know that from that time onwards, modern humans cross bred with Neanderthals in all the continents, except Africa, and with the Denisovans in Oceania and probably in South-East Asia, although the evidence of cross-breeding with a third extinct species had not been confirmed with any certaint.<\/p>\n<p><span style=\"font-size:16px\"><strong>Deep learning: deciphering the keys to human evolution in ancient DNA<\/strong><\/span><\/p>\n<p>Hitherto, the existence of the third ancestor was only a theory that would explain the origin of some fragments of the current human genome (part of the team involved in this study had already posed the existence of the extinct hominid in a\u00a0<a href=\"https:\/\/www.ibe.upf-csic.es\/home\/-\/asset_publisher\/T2caeLMECPvW\/content\/id\/\" style=\"font-weight: 200\" target=\"_blank\" rel=\"noopener noreferrer\">previous study<\/a>). However, deep learning has made it possible to make the transition from DNA to the demographics of ancestral populations.<\/p>\n<p>The problem the researchers had to contend with is that the demographic models they have analysed are much more complex than anything else considered to date and there were no statistic tools available to analyse them. Deep learning \u201cis an algorithm that imitates the way in which the nervous system of mammals works, with different\u00a0artificial neurons\u00a0that specialise and learn to detect, in data, patterns that are important for performing a given task\u201d, say\u00a0<a href=\"https:\/\/www.cnag.crg.eu\/oscar-lao\" target=\"_blank\" rel=\"noopener noreferrer\">\u00d2scar Lao<\/a>,<strong style=\"margin: 0px;padding: 0px;border: 0px;font-size: 12px;line-height: inherit;font-family: Arial, sans-serif;vertical-align: baseline;text-align: justify\">\u00a0<\/strong>Population Genomics group leader at the CNAG-CRG. and an expert in this type of simulations. \u201cWe have used this property to get the algorithm to learn to predict human demographics using genomes obtained through hundreds of thousands of simulations. Whenever we run a simulation we are travelling along a possible path in the history of humankind. Of all simulations, deep learning allows us to observe what makes the ancestral puzzle fit together\u201d.<\/p>\n<p>It is the first time that deep learning has been used successfully to explain human history, paving the way for this technology to be applied in other questions in biology, genomics and evolution.<\/p>\n<p><span style=\"font-size:16px\"><strong>An extinct hominid could explain the history of humankind<\/strong><\/span><\/p>\n<p>The deep learning analysis has revealed that the extinct hominid is probably a descendant of the Neanderthal and Denisovan populations. The discovery of a fossil with these characteristics this summer would seem to endorse the study finding, consolidating the hypothesis of this third species or population that coexisted with modern human beings and mated with them. \u201cOur theory coincides with the hybrid specimen discovered recently in Denisova, although as yet we cannot rule out other possibilities\u201d, said Mayukh Mondal, an investigator of the University of Tartu and former investigator at the IBE.<\/p>\n<p>\n<strong>\u25baReference article:\u00a0<\/strong>Mayukh Mondal, Jaume Bertranpetit, Oscar Lao. &#8220;<a href=\"https:\/\/www.nature.com\/articles\/s41467-018-08089-7\" target=\"_blank\" rel=\"noopener noreferrer\">Approximate Bayesian computation with Deep Learning supports a third archaic introgression in Asia and Oceania<\/a>&#8220;.\u00a0Nature Communications (2018). DOI:\u00a010.1038\/s41467-018-08089-7<\/p>\n<p>\u00a0<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Researchers from the Centro Nacional de An\u00e1lisis Gen\u00f3mico (<a href=\"http:\/\/www.pcb.ub.edu\/portal\/en\/cerca?p_p_id=cercador_WAR_empleatsempresesportlet&amp;p_p_lifecycle=0&amp;p_p_state=maximized&amp;p_p_mode=view&amp;p_p_col_id=column-1&amp;p_p_col_count=1&amp;_cercador_WAR_empleatsempresesportlet_jspPage=%2Fhtml%2Fcommon%2Fdetall-empresa.jsp&amp;_cercador_WAR_empleatsempresesportlet_empresaId=ENT_006440&amp;_cercador_WAR_empleatsempresesportlet_redirect=%2Fportal%2Fen%2Fcerca%3Fp_p_id%3Dcercador_WAR_empleatsempresesportlet%26p_p_lifecycle%3D0%26p_p_mode%3Dview%26_cercador_WAR_empleatsempresesportlet_keywords%3Dcnag%26_cercador_WAR_empleatsempresesportlet_tab%3D1\" target=\"_blank\" rel=\"noopener noreferrer\">CNAG-CRG<\/a>)\u00a0\u2013based in the Barcelona Science Park and integrated into the Centre for Genomic Regulation (<a href=\"https:\/\/www.crg.eu\/en\" target=\"_blank\" rel=\"noopener noreferrer\">CRG<\/a>)\u2013 the\u00a0Institute of Evolutionary Biology\u00a0(<a href=\"https:\/\/www.ibe.upf-csic.es\/\" target=\"_blank\" rel=\"noopener noreferrer\">IBE)<\/a>, and the\u00a0<a href=\"https:\/\/www.geenivaramu.ee\/en\" target=\"_blank\" rel=\"noopener noreferrer\">Institute of Genomics<\/a>\u00a0at the University of Tartu have identified, in the genome of Asiatic individuals, the footprint of a new hominid who cross bred with its ancestors tens of thousands of years ago.\u00a0The study,\u00a0published in Nature Communications, uses deep learning for the first time ever to account for human evolution, paving the way for the application of this technology in other questions in biology, genomics and evolution.<\/p>\n<p>\u00a0<\/p>\n","protected":false},"author":1,"featured_media":54949,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[8],"tags":[],"class_list":["post-49996","post","type-post","status-publish","format-standard","has-post-thumbnail","category-uncategorized"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.6 - 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