Title Identifying genomic signatures of positive selection to predict protective genomic loci in the cohort of Lithuanian clean-up workers of the Chornobyl nuclear disaster /
Authors Žukauskaitė, Gabrielė ; Domarkienė, Ingrida ; Matulevičienė, Aušra ; Dauengauer-Kirlienė, Svetlana ; Kučinskas, Vaidutis ; Ambrozaitytė, Laima
DOI 10.3390/cimb45040195
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Is Part of Current issues in molecular biology.. Basel : MDPI. 2023, vol. 45, iss. 4, p. 2972-2983.. eISSN 1467-3045
Keywords [eng] adaptiveness ; positive selection ; protective genome variation ; whole-genome sequencing ; RAiSD ; Lithuanian clean-up workers of Chornobyl nuclear disaster ; selective sweep
Abstract [eng] Some people resist or recover from health challenges better than others. We studied Lithuanian clean-up workers of the Chornobyl nuclear disaster (LCWC) who worked in the harshest conditions and, despite high ionising radiation doses as well as other factors, continue ageing relatively healthily. Thus, we hypothesised that there might be individual features encoded by the genome which act protectively for better adaptiveness and health that depend on unique positive selection signatures. Whole-genome sequencing was performed for 40 LCWC and a control group composed of 25 men from the general Lithuanian population (LTU). Selective sweep analysis was performed to identify genomic regions which may be under recent positive selection and determine better adaptiveness. Twenty-two autosomal loci with the highest positive selection signature values were identified. Most important, unique loci under positive selection have been identified in the genomes of the LCWC, which may influence the survival and adaptive qualities to extreme conditions, and the disaster itself. Characterising these loci provide a better understanding of the interaction between ongoing microevolutionary processes, multifactorial traits, and diseases. Studying unique groups of disease-resistant individuals could help create new insights for better, more individualised, disease diagnostics and prevention strategies.
Published Basel : MDPI
Type Journal article
Language English
Publication date 2023
CC license CC license description