Dataset Information

Genetic profiling of Vietnamese population from large-scale genomic analysis of non-invasive prenatal testing data.

ABSTRACT: 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.

SUBMITTER: Tran NH

PROVIDER: S-EPMC7644705 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Genetic profiling of Vietnamese population from large-scale genomic analysis of non-invasive prenatal testing data.

Tran Ngoc Hieu NH Vo Thanh Binh TB Nguyen Van Thong VT Tran Nhat-Thang NT Trinh Thu-Huong Nhat TN Pham Hong-Anh Thi HT Dao Thi Hong Thuy THT Nguyen Ngoc Mai NM Van Yen-Linh Thi YT Tran Vu Uyen VU Vu Hoang Giang HG Bui Quynh-Tram Nguyen QN Vo Phuong-Anh Ngoc PN Nguyen Huu Nguyen HN Nguyen Quynh-Tho Thi QT Do Thanh-Thuy Thi TT Lam Nien Vinh NV Ngoc Phuong Cao Thi PCT Truong Dinh Kiet DK Nguyen Hoai-Nghia HN Giang Hoa H Phan Minh-Duy MD

Scientific reports 20201105 1

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 g ...[more]

PMID: 33154511

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Project description:BackgroundThe Approximate Bayesian Computation (ABC) approach has been used to infer demographic parameters for numerous species, including humans. However, most applications of ABC still use limited amounts of data, from a small number of loci, compared to the large amount of genome-wide population-genetic data which have become available in the last few years.ResultsWe evaluated the performance of the ABC approach for three 'population divergence' models - similar to the 'isolation with migration' model - when the data consists of several hundred thousand SNPs typed for multiple individuals by simulating data from known demographic models. The ABC approach was used to infer demographic parameters of interest and we compared the inferred values to the true parameter values that was used to generate hypothetical "observed" data. For all three case models, the ABC approach inferred most demographic parameters quite well with narrow credible intervals, for example, population divergence times and past population sizes, but some parameters were more difficult to infer, such as population sizes at present and migration rates. We compared the ability of different summary statistics to infer demographic parameters, including haplotype and LD based statistics, and found that the accuracy of the parameter estimates can be improved by combining summary statistics that capture different parts of information in the data. Furthermore, our results suggest that poor choices of prior distributions can in some circumstances be detected using ABC. Finally, increasing the amount of data beyond some hundred loci will substantially improve the accuracy of many parameter estimates using ABC.ConclusionsWe conclude that the ABC approach can accommodate realistic genome-wide population genetic data, which may be difficult to analyze with full likelihood approaches, and that the ABC can provide accurate and precise inference of demographic parameters from these data, suggesting that the ABC approach will be a useful tool for analyzing large genome-wide datasets.

Dataset Information

Genetic profiling of Vietnamese population from large-scale genomic analysis of non-invasive prenatal testing data.

Publications

Genetic profiling of Vietnamese population from large-scale genomic analysis of non-invasive prenatal testing data.

Similar Datasets

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