NyuWa Genome resource: A deep whole-genome sequencing-based variation profile and reference panel for the Chinese population
The lack of haplotype reference panels and whole-genome sequencing resources specific to the Chinese population has greatly hindered genetic studies in the world’s largest population. Here, we present the NyuWa genome resource, based on deep (26.2×) sequencing of 2,999 Chinese individuals, and const...
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Veröffentlicht in: | Cell reports (Cambridge) 2021-11, Vol.37 (7), p.110017-110017, Article 110017 |
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Sprache: | eng |
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Zusammenfassung: | The lack of haplotype reference panels and whole-genome sequencing resources specific to the Chinese population has greatly hindered genetic studies in the world’s largest population. Here, we present the NyuWa genome resource, based on deep (26.2×) sequencing of 2,999 Chinese individuals, and construct a NyuWa reference panel of 5,804 haplotypes and 19.3 million variants, which is a high-quality publicly available Chinese population-specific reference panel with thousands of samples. Compared with other panels, the NyuWa reference panel reduces the Han Chinese imputation error rate by a margin ranging from 30% to 51%. Population structure and imputation simulation tests support the applicability of one integrated reference panel for northern and southern Chinese. In addition, a total of 22,504 loss-of-function variants in coding and noncoding genes are identified, including 11,493 novel variants. These results highlight the value of the NyuWa genome resource in facilitating genetic research in Chinese and Asian populations.
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•Identification of 25.0 million variants by WGS of 2,999 Chinese individuals•NyuWa reference panel outperforms public ones for Chinese populations•A reference panel applicable for northern and southern Chinese populations•Clinical insights and loss-of-function analysis
Zhang et al. construct the NyuWa genome resource with 79.3 million variants and a reference panel of 5,804 haplotypes based on deep whole-genome sequencing of Chinese individuals, which will help the study of population genetics, medical genetics, and genotype-phenotype association in the world’s largest population. |
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ISSN: | 2211-1247 2211-1247 |
DOI: | 10.1016/j.celrep.2021.110017 |