Utilizing non-invasive prenatal test sequencing data for human genetic investigation
Non-invasive prenatal testing (NIPT) employs ultra-low-pass sequencing of maternal plasma cell-free DNA to detect fetal trisomy. Its global adoption has established NIPT as a large human genetic resource for exploring genetic variations and their associations with phenotypes. Here, we present methods for analyzing large-scale, low-depth NIPT data, including customized algorithms and software for genetic variant detection, genotype imputation, family relatedness, population structure inference, and genome-wide association analysis of maternal genomes. Our results demonstrate accurate allele frequency estimation and high genotype imputation accuracy (R<sup>2</sup>>0.84) for NIPT sequencing depths from 0.1× to 0.3×. We also achieve effective classification of duplicates and first-degree relatives, along with robust principal-component analysis. Additionally, we obtain an R<sup>2</sup>>0.81 for estimating genetic effect sizes across genotyping and sequencing platforms with adequate sample sizes. These methods offer a robust theoretical and practical foundation for utilizing NIPT data in medical genetic research.
Authors
- Anders Albrechtsen (ORCID: https://orcid.org/0000-0001-7306-031X)
- Xingchen Lin
- Guo-Bo Chen
- Shiyao Cheng
- Hankui Liu (ORCID: https://orcid.org/0000-0001-7826-0388)
- Huanhuan Zhu (ORCID: https://orcid.org/0000-0002-2995-4911)
- Mingxi Huang (ORCID: https://orcid.org/0000-0002-6399-5880)
- Linxuan Li (ORCID: https://orcid.org/0000-0002-7920-4684)
- R. W. Davies (ORCID: https://orcid.org/0000-0002-2252-0862)
- Yanhong Liu (ORCID: https://orcid.org/0000-0002-0759-7597)
- Shujia Huang (ORCID: https://orcid.org/0000-0003-2100-2534)
- Xiu Qiu (ORCID: https://orcid.org/0000-0003-1248-229X)
- Xianmei Lan
- Xin Jin (ORCID: https://orcid.org/0000-0001-7554-4975)
- Rasmus Nielsen (ORCID: https://orcid.org/0000-0003-0513-6591)
- Hao Li (ORCID: https://orcid.org/0000-0001-5677-3377)
- Siyang Liu
- Zhe Xu (ORCID: https://orcid.org/0000-0001-5157-570X)
- Yuqin Gu (ORCID: https://orcid.org/0009-0005-9817-466X)
Institutions
- BGI Group (China) (CN)
- University of Copenhagen (DK)
- Sun Yat-sen University (CN)
- Shenzhen University (CN)
- Capital Medical University (CN)
- University of Oxford (GB)
- Beijing Tian Tan Hospital (CN)
- Guangzhou Women and Children Medical Center (CN)
- Chinese University of Hong Kong, Shenzhen (CN)
- Zhejiang Provincial People's Hospital (CN)
- University of Chinese Academy of Sciences (CN)
- Hangzhou Medical College (CN)
- BGI Genomics
- IT University of Copenhagen (DK)
- Guangzhou Medical University (CN)
- University of California, Berkeley (US)
Publication Details
- Journal
- Cell Genomics
- Published
- 2024-10-01
- DOI
- https://doi.org/10.1016/j.xgen.2024.100669
- Citations
- 19
- Primary Topic
- Genomics and Rare Diseases
- Type
- article
- Field-Weighted Citation Impact
- 10.46
Funders
- National Natural Science Foundation of China
- Basic and Applied Basic Research Foundation of Guangdong Province