HSE Researchers Teach Neural Network to Distinguish Origins from Genetically Similar Populations
Researchers from the AI and Digital Science Institute, HSE Faculty of Computer Science, have proposed a new approach based on advanced machine learning techniques to determine a person’s genetic origin with high accuracy. This method uses graph neural networks, which make it possible to distinguish even very closely related populations.
Over the past 10–15 years, genetic analysis has become increasingly popular not only as a tool for medical diagnostics, but also as a means of ancestry research. DNA testing allows people to learn more about their ethnic background, identify the places where their ancestors lived, and determine the number of Neanderthal mutations in a person’s genome.
This has become possible thanks to the development of modern technologies—such as genotyping, data storage and processing systems, and machine learning—and the significant reduction in their cost. However, current testing methods are unable to differentiate between genetically similar populations that have lived in adjacent regions for extended periods.
Researchers from the AI and Digital Science Institute have developed a method for distinguishing between individuals from closely related populations. At the heart of this technology are graph neural networks, which do not rely on DNA sequences but instead use graphs to represent genetic links between individuals with shared genome segments. These shared segments indicate the degree of kinship between people, revealing how many generations back their common ancestors lived. The more overlaps there are, the closer their ancestral connection is. In the model, each person is represented by a vertex in the graph, and the strength of the connection between them is indicated by the edges in the graph.
The method was tested on data from various regions. The results were particularly insightful for the population of the East European Plain, as a large dataset had already been compiled there. The graph neural network was able to accurately determine the population affiliation of individuals from genetically similar ethnic groups.
Aleksei Shmelev
‘Existing methods of genetic analysis address a different task: they identify affiliation with large, isolated groups, such as determining whether someone has French, German, or English ancestry. Our method enables the analysis of closely related populations, which is particularly relevant for Russia, a country with a diverse ethnic background,’ said Aleksei Shmelev, one of the study's authors and Research Assistant at the HSE International Laboratory of Statistical and Computational Genomics, AI and Digital Science Institute.
In their future work, the researchers aim to train the neural network to predict the proportion of different populations within a genome.
They have named their development AncestryGNN, which stands for 'Neural Network-Based Prediction of Population Affiliation via Shared Genome Segments.’
Vladimir Shchur
As noted by Vladimir Shchur, Head of the International Laboratory of Statistical and Computational Genomics at the AI and Digital Science Institute, HSE University, the proposed method holds great potential for more accurate understanding of human history and can be applied in genealogy and anthropology research.
This research was supported by a grant from the Government of the Russian Federation as part of the federal program ‘Artificial Intelligence.’
See also:
HSE Researchers Discover Who Eats Out in Russia—And Why
Around one-third of Russians (31.3%) rarely eat out or buy ready-made meals. The core group of active consumers—those who eat out or purchase prepared food almost every day or several times a week—accounts for only about 9% of the population. These are the findings of a study conducted by the HSE Institute for Social Policy. According to the researchers eating out is no longer a marker of high social status in Russia.
Ancient Craniiform Brachiopod: A Newly Discovered Species with a Unique Shell Shape and Lifestyle
Scientists from HSE University, MSU, and Tallinn University of Technology have studied a fossil species of ancient brachiopods that lived in a warm sea in what is now northern Estonia more than 445 million years ago. These ancient brachiopods developed a cup-shaped shell with a protective 'cap' that shielded them from overgrowth by other marine organisms. The study has been published in Palaeogeography, Palaeoclimatology, Palaeoecology.
Scientists Develop Bacterium-Sized Microlaser
An international team of researchers, including scientists from HSE University–St Petersburg, has developed microlasers that emit deep-ultraviolet light at a wavelength of 255 nanometres. The devices operate at room temperature, and the smallest of them measures just two micrometres in diameter—roughly the size of a bacterium. These microlasers could be used in sensors, spectroscopic systems, photonic chips, and communication devices. The paper has been published in Optics & Laser Technology.
HSE Develops App for Assessing Phonological Processing in Children
Researchers at the HSE Centre for Language and Brain have developed a new digital tool for assessing children's phonological processing skills—the ZARYA (Sound Analysis of the Russian Language) test battery. It is the first standardised application in Russia designed to provide a fast and reliable assessment of children's ability to distinguish speech sounds, retain them in working memory, and perform phonemic analysis. The app runs on Android tablets and smartphones and is available for download from RuStore. Details of the test validation have been published in the Journal of Speech, Language, and Hearing Research.
Researchers Discover How Spelling Errors Slow Down Reading in Russian
Psycholinguists from the Centre for Language and Brain at HSE University–St Petersburg have shown that words that are frequently misspelled are processed more slowly by readers, even when presented with the correct spelling. The researchers confirmed this effect for the first time using Russian-language materials and found that response speed is most strongly linked to how confidently individuals can distinguish the correct spelling of a word from an incorrect one. The study has been published in The Mental Lexicon.
Scientists Discover Why Europium 'Misbehaves'
Europium is a rare-earth metal responsible for the pure red glow in displays and other luminescent materials. For a long time, however, it refused to emit light when surrounded by certain organic molecules known as acylpyrazolone ligands. Chemists have now uncovered the reason: in europium complexes with these ligands, a 'black window' appears—a charge-transfer state in which the energy absorbed by the ligand is dissipated as heat rather than emitted as light. Understanding this mechanism opens the way to designing more efficient red-emitting materials for displays, fluorescent thermometers, and chemical sensors. The results have been published in Dalton Transactions.
HSE Economists Reveal How the Wage Gap Emerges Among Vocational School Graduates
HSE researchers examined the careers of 600,000 graduates of Russian secondary vocational education programmes and found that at the start of their careers, the gender wage gap reaches 23%, doubling after three years. This disparity is largely due to male and female students choosing different occupations when enrolling in vocational schools. These were the findings made by Sergey Roshchin, Natalya Yemelina, and Ksenia Rozhkova from of the HSE Faculty of Economic Sciences. The article has been published in Educational Studies.
HSE Researchers Make Aldehydes Perform Dual Function
Chemists from HSE University have discovered a way to carry out a reductive addition reaction without using an external reducing agent. Instead, the required 'resource' is supplied by the aldehyde itself, one of the reaction participants. This approach helps prevent unwanted side reactions, reduces toxicity, and simplifies the production and synthesis of organic molecules, including those used in the manufacture of medicines. The study has been published in Journal of Catalysis.
HSE Scientists Explain Why Findings in Autism Research Differ
Researchers from the Cognitive Health and Intelligence Centre at HSE University conducted the first-ever systematic review of studies on the specifics of emotion-from-motion perception in autism. The review showed that differences found between autistic and non-autistic individuals are largely associated with the experimental design and the types of tasks given to study participants. The review findings have been published in Research in Autism.
Tremors: Scientists Develop Method for Real-Time Tracking of Hazardous Underground Vibrations
Researchers from HSE MIEM and IPKON RAS have developed a new mathematical monitoring model that can identify the source of hazardous underground vibrations in real time. The technology could help reduce the risk of damage to buildings, roads, and other infrastructure located near quarries and mining sites. The paper has been published in Russian Mining Industry.