[논문]Investigating Mitonuclear Genetic Interactions Through Machine Learning: A Case Study on Cold Adaptation Genes in Human Populations From Different European Climate Regions

Kalyakulina, Alena; Iannuzzi, Vincenzo; Sazzini, Marco; Garagnani, Paolo; Jalan, Sarika; Franceschi, Claudio; Ivanchenko, Mikhail; Giuliani, Cristina

doi:10.3389/fphys.2020.575968

[해외논문] Investigating Mitonuclear Genetic Interactions Through Machine Learning: A Case Study on Cold Adaptation Genes in Human Populations From Different European Climate Regions 원문보기

Frontiers in physiology, v.11, 2020년, pp.575968 -

Kalyakulina, Alena (Department of Applied Mathematics, Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky State University of Nizhny Novgorod , Nizhny Novgorod , Russia) , Iannuzzi, Vincenzo (Alma Mater Research Institute on Global Challenges and Climate Change (Alma Climate), University of Bologna , Bologna , Italy) , Sazzini, Marco (Laboratory of Molecular Anthropology and Centre for Genome Biology, Department of Biological, Geological and Environmental Sciences, University of Bologna , Bologna , Italy) , Garagnani, Paolo (Department of Experimental, Diagnostic and Specialty Medicine (DIMES), University of Bologna , Bologna , Italy) , Jalan, Sarika (Complex Systems Laboratory, Discipline of Physics, Indian Institute of Technology Indore , Indore , India) , Franceschi, Claudio (Laboratory of Systems Medicine of Healthy Aging, Lobachevsky State University of Nizhny Novgorod , Nizhny Novgorod , Russia) , Ivanchenko, Mikhail (Department of) , Giuliani, Cristina

Abstract ▼ AI-Helper

Cold climates represent one of the major environmental challenges that anatomically modern humans faced during their dispersal out of Africa. The related adaptive traits have been achieved by modulation of thermogenesis and thermoregulation processes where nuclear (nuc) and mitochondrial (mt) genes play a major role. In human populations, mitonuclear genetic interactions are the result of both the peculiar genetic history of each human group and the different environments they have long occupied. This study aims to investigate mitonuclear genetic interactions by considering all the mitochondrial genes and 28 nuclear genes involved in brown adipose tissue metabolism, which have been previously hypothesized to be crucial for cold adaptation. For this purpose, we focused on three human populations (i.e., Finnish, British, and Central Italian people) of European ancestry from different biogeographical and climatic areas, and we used a machine learning approach to identify relevant nucDNA–mtDNA interactions that characterized each population. The obtained results are twofold: (i) at the methodological level, we demonstrated that a machine learning approach is able to detect patterns of genetic structure among human groups from different latitudes both at single genes and by considering combinations of mtDNA and nucDNA loci; (ii) at the biological level, the analysis identified population-specific nuclear genes and variants that likely play a relevant biological role in association with a mitochondrial gene (such as the “obesity gene” FTO in Finnish people). Further studies are needed to fully elucidate the evolutionary dynamics (e.g., migration, admixture, and/or local adaptation) that shaped these nucDNA–mtDNA interactions and their functional role.

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