Genetic profiling of Vietnamese population from large-scale genomic analysis of non-invasive prenatal testing data.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
05 11 2020
05 11 2020
Historique:
received:
24
04
2020
accepted:
26
10
2020
entrez:
6
11
2020
pubmed:
7
11
2020
medline:
16
3
2021
Statut:
epublish
Résumé
The under-representation of several ethnic groups in existing genetic databases and studies have undermined our understanding of the genetic variations and associated traits or diseases in many populations. Cost and technology limitations remain the challenges in performing large-scale genome sequencing projects in many developing countries, including Vietnam. As one of the most rapidly adopted genetic tests, non-invasive prenatal testing (NIPT) data offers an alternative untapped resource for genetic studies. Here we performed a large-scale genomic analysis of 2683 pregnant Vietnamese women using their NIPT data and identified a comprehensive set of 8,054,515 single-nucleotide polymorphisms, among which 8.2% were new to the Vietnamese population. Our study also revealed 24,487 disease-associated genetic variants and their allele frequency distribution, especially 5 pathogenic variants for prevalent genetic disorders in Vietnam. We also observed major discrepancies in the allele frequency distribution of disease-associated genetic variants between the Vietnamese and other populations, thus highlighting a need for genome-wide association studies dedicated to the Vietnamese population. The resulted database of Vietnamese genetic variants, their allele frequency distribution, and their associated diseases presents a valuable resource for future genetic studies.
Identifiants
pubmed: 33154511
doi: 10.1038/s41598-020-76245-5
pii: 10.1038/s41598-020-76245-5
pmc: PMC7644705
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
19142Références
Nat Biotechnol. 2013 Mar;31(3):213-9
pubmed: 23396013
Gigascience. 2015 Feb 25;4:7
pubmed: 25722852
Cell. 2018 Oct 4;175(2):347-359.e14
pubmed: 30290141
Nature. 2016 Aug 17;536(7616):285-91
pubmed: 27535533
Nat Rev Genet. 2019 Sep;20(9):520-535
pubmed: 31235872
J Biotechnol. 2019 Jun 20;299:72-78
pubmed: 31054297
Bioinformatics. 2011 Nov 1;27(21):2987-93
pubmed: 21903627
Nature. 2015 Oct 1;526(7571):68-74
pubmed: 26432245
Cell. 2019 Oct 17;179(3):736-749.e15
pubmed: 31626772
Bioinformatics. 2009 Aug 15;25(16):2078-9
pubmed: 19505943
Nature. 2017 Aug 3;548(7665):87-91
pubmed: 28746312
Nucleic Acids Res. 2001 Jan 1;29(1):308-11
pubmed: 11125122
Nat Genet. 2014 Aug;46(8):818-25
pubmed: 24974849
Nature. 2015 Oct 1;526(7571):82-90
pubmed: 26367797
Genome Biol. 2016 Jun 06;17(1):122
pubmed: 27268795
Nat Genet. 2015 May;47(5):435-44
pubmed: 25807286
Bioinformatics. 2014 Aug 1;30(15):2114-20
pubmed: 24695404
Nature. 2020 May;581(7809):434-443
pubmed: 32461654
Bioinformatics. 2016 Jan 15;32(2):292-4
pubmed: 26428292
J Matern Fetal Neonatal Med. 2019 Dec;32(23):4009-4015
pubmed: 29865915
Nat Genet. 2011 May;43(5):491-8
pubmed: 21478889
Genome Res. 2011 Jun;21(6):940-51
pubmed: 21460063
Nat Biotechnol. 2011 Jan;29(1):24-6
pubmed: 21221095
Nucleic Acids Res. 2018 Nov 16;46(20):e120
pubmed: 30169659
Hum Mutat. 2019 Oct;40(10):1664-1675
pubmed: 31180159
Curr Protoc Bioinformatics. 2013;43:11.10.1-11.10.33
pubmed: 25431634
PLoS One. 2013 Nov 18;8(11):e79667
pubmed: 24260275
Am J Hum Genet. 2006 Jan;78(1):2-14
pubmed: 16385445
Nucleic Acids Res. 2014 Jan;42(Database issue):D980-5
pubmed: 24234437
Bioinformatics. 2010 Mar 15;26(6):841-2
pubmed: 20110278
Nat Rev Genet. 2019 Sep;20(9):495
pubmed: 31420601