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The Thousand Polish Genomes-A Database of Polish Variant Allele Frequencies.

Elżbieta KajaAdrian LejmanDawid SielskiMateusz SypniewskiTomasz GambinMateusz DawidziukTomasz SuchockiPawel GolikMarzena WojtaszewskaMagdalena MroczekMaria StępieńJoanna SzydaKarolina Lisiak-TeodorczykFilip WolbachDaria KołodziejskaKatarzyna FerdynMaciej DąbrowskiAlicja WoźnaMarcin ŻytkiewiczAnna Bodora-TroińskaWaldemar ElikowskiZbigniew J KrólArtur ZaczyńskiAgnieszka PawlakRobert GilWaldemar WierzbaPaula DoboszKatarzyna ZawadzkaPawel ZawadzkiPaweł Sztromwasser
Published in: International journal of molecular sciences (2022)
Although Slavic populations account for over 4.5% of world inhabitants, no centralised, open-source reference database of genetic variation of any Slavic population exists to date. Such data are crucial for clinical genetics, biomedical research, as well as archeological and historical studies. The Polish population, which is homogenous and sedentary in its nature but influenced by many migrations of the past, is unique and could serve as a genetic reference for the Slavic nations. In this study, we analysed whole genomes of 1222 Poles to identify and genotype a wide spectrum of genomic variation, such as small and structural variants, runs of homozygosity, mitochondrial haplogroups, and de novo variants. Common variant analyses showed that the Polish cohort is highly homogenous and shares ancestry with other European populations. In rare variant analyses, we identified 32 autosomal-recessive genes with significantly different frequencies of pathogenic alleles in the Polish population as compared to the non-Finish Europeans, including C2 , TGM5 , NUP93 , C19orf12 , and PROP1 . The allele frequencies for small and structural variants, calculated for 1076 unrelated individuals, are released publicly as The Thousand Polish Genomes database, and will contribute to the worldwide genomic resources available to researchers and clinicians.
Keyphrases
  • copy number
  • genome wide
  • oxidative stress
  • adverse drug
  • emergency department
  • palliative care
  • dna methylation
  • machine learning
  • genetic diversity
  • artificial intelligence