New method could reveal what genes we might have inherited from Neanderthals.
Tuesday, 22nd June 2021
Thousands of years ago, ancient humans such as Neanderthals and Denisovans became extinct. But before that, they interbred with the ancestors of today's humans, and to this day, they still carry genetic mutations from extinct species.
More than 40% of Neanderthal genomes are believed to have survived among different non-African descendants today, but due to dispersal, any single genome consists of only up to 2% Neanderthal material. Some populations also carry genetic material from Denisovans, a mysterious group of ancient humans that may have lived in eastern Eurasia and Oceania thousands of years ago.
The process of introducing beneficial genetic material into our gene pool is called adaptive gene infiltration, and it often happens because it is beneficial to humans after they spread to all parts of the world. To cite a few examples, scientists believe that some mutations will affect the development and metabolism of the skin. But many mutations have not yet been discovered.
Now, researchers at the GLOBE Institute at the University of Copenhagen have developed a new method that uses deep learning techniques to search for undiscovered mutations in the human genome.
"We have developed a deep learning method called ‘genomatnn’, which jointly simulates gene infiltration, that is, the transfer of genetic information between species and natural selection. The model was developed to identify areas in the human genome where this infiltration of genes can occur, "said associate professor Fernando Racimo of the GLOBE Institute, the corresponding author of the new study.
We applied it to various data sets of the human genome and We found several beneficial candidate gene variants have been introduced into the human gene pool, "he said. The new method is based on the so-called Convolutional Neural Network (CNN), a learning framework commonly used in deep image and video recognition.
Researchers from the University of Copenhagen have trained CNN through hundreds of thousands of simulations to recognize patterns in genomic images that will be produced through the adaptive genetic infiltration of ancient humans.
In addition to confirming the proposed genetic mutations of adaptive genetic introgression, the researchers also discovered possible mutations of unknown genetic introgression.
"We have restored previously identified candidates for modern human adaptive genetic introgression, as well as some candidates that have not been described before," said Graham Gower, first author of the new study, a postdoctoral fellow.
Some mutations not previously described involve the central pathways of human metabolism and immunity.
"In the European genome, we have found two powerful candidate genes for Neanderthal adaptive genetic introgression into genomic regions that affect blood-related phenotypes (including blood cell counts). In Melanesia in the genome, we found infiltrated candidate variants of Denisovan genes that can affect a wide range of traits, such as blood-related diseases, tumor suppression, skin development, metabolism, and various neurological diseases. It is not clear how these traits were affected in modern carriers of ancient variants, such as neutral, positive, or negative, although it was historically thought that the infiltrated genetic material had a positive effect on the person who carried them,” he explained the following. The research team's stage is to adapt the method to more complex demographic and selection scenarios to understand the general fate of Neanderthal genetic material. Graham Gower noted that the team aims to track their work on this study The Role of Candidate Variants in the Genome Discovered in.
Looking Ahead, Human Search remains a genome that defies genetic material unsampled populations (so-called ghost populations). However, the researchers hope to be able to further train neural networks to identify mutations from these unsampled populations.
"Future work may also involve the development of a CNN that can detect infiltration of adaptive genes from ghost populations for situations where genome-of-origin data is not available," said Graham Gower.
The News Talkie Bureau
Source:
Sciencedaily.com