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CAS Array: design and assessment of a genotyping array for Chinese biobanking

BACKGROUND: Chronic diseases are becoming a critical challenge to the aging Chinese population. Biobanks with extensive genomic and environmental data offer opportunities to elucidate the complex gene–environment interactions underlying their aetiology. Genome-wide genotyping array remains an effici...

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Autores principales: Tian, Zijian, Chen, Fei, Wang, Jing, Wu, Benrui, Shao, Jian, Liu, Ziqing, Zheng, Li, Wang, You, Xu, Tao, Zhou, Kaixin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10031742/
https://www.ncbi.nlm.nih.gov/pubmed/36968613
http://dx.doi.org/10.1093/pcmedi/pbad002
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author Tian, Zijian
Chen, Fei
Wang, Jing
Wu, Benrui
Shao, Jian
Liu, Ziqing
Zheng, Li
Wang, You
Xu, Tao
Zhou, Kaixin
author_facet Tian, Zijian
Chen, Fei
Wang, Jing
Wu, Benrui
Shao, Jian
Liu, Ziqing
Zheng, Li
Wang, You
Xu, Tao
Zhou, Kaixin
author_sort Tian, Zijian
collection PubMed
description BACKGROUND: Chronic diseases are becoming a critical challenge to the aging Chinese population. Biobanks with extensive genomic and environmental data offer opportunities to elucidate the complex gene–environment interactions underlying their aetiology. Genome-wide genotyping array remains an efficient approach for large-scale genomic data collection. However, most commercial arrays have reduced performance for biobanking in the Chinese population. MATERIALS AND METHODS: Deep whole-genome sequencing data from 2 641 Chinese individuals were used as a reference to develop the CAS array, a custom-designed genotyping array for precision medicine. Evaluation of the array was performed by comparing data from 384 individuals assayed both by the array and whole-genome sequencing. Validation of its mitochondrial copy number estimating capacity was conducted by examining its association with established covariates among 10 162 Chinese elderly. RESULTS: The CAS Array adopts the proven Axiom technology and is restricted to 652 429 single-nucleotide polymorphism (SNP) markers. Its call rate of 99.79% and concordance rate of 99.89% are both higher than for commercial arrays. Its imputation-based genome coverage reached 98.3% for common SNPs and 63.0% for low-frequency SNPs, both comparable to commercial arrays with larger SNP capacity. After validating its mitochondrial copy number estimates, we developed a publicly available software tool to facilitate the array utility. CONCLUSION: Based on recent advances in genomic science, we designed and implemented a high-throughput and low-cost genotyping array. It is more cost-effective than commercial arrays for large-scale Chinese biobanking.
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spelling pubmed-100317422023-03-23 CAS Array: design and assessment of a genotyping array for Chinese biobanking Tian, Zijian Chen, Fei Wang, Jing Wu, Benrui Shao, Jian Liu, Ziqing Zheng, Li Wang, You Xu, Tao Zhou, Kaixin Precis Clin Med Research Article BACKGROUND: Chronic diseases are becoming a critical challenge to the aging Chinese population. Biobanks with extensive genomic and environmental data offer opportunities to elucidate the complex gene–environment interactions underlying their aetiology. Genome-wide genotyping array remains an efficient approach for large-scale genomic data collection. However, most commercial arrays have reduced performance for biobanking in the Chinese population. MATERIALS AND METHODS: Deep whole-genome sequencing data from 2 641 Chinese individuals were used as a reference to develop the CAS array, a custom-designed genotyping array for precision medicine. Evaluation of the array was performed by comparing data from 384 individuals assayed both by the array and whole-genome sequencing. Validation of its mitochondrial copy number estimating capacity was conducted by examining its association with established covariates among 10 162 Chinese elderly. RESULTS: The CAS Array adopts the proven Axiom technology and is restricted to 652 429 single-nucleotide polymorphism (SNP) markers. Its call rate of 99.79% and concordance rate of 99.89% are both higher than for commercial arrays. Its imputation-based genome coverage reached 98.3% for common SNPs and 63.0% for low-frequency SNPs, both comparable to commercial arrays with larger SNP capacity. After validating its mitochondrial copy number estimates, we developed a publicly available software tool to facilitate the array utility. CONCLUSION: Based on recent advances in genomic science, we designed and implemented a high-throughput and low-cost genotyping array. It is more cost-effective than commercial arrays for large-scale Chinese biobanking. Oxford University Press 2023-02-23 /pmc/articles/PMC10031742/ /pubmed/36968613 http://dx.doi.org/10.1093/pcmedi/pbad002 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of the West China School of Medicine & West China Hospital of Sichuan University. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Tian, Zijian
Chen, Fei
Wang, Jing
Wu, Benrui
Shao, Jian
Liu, Ziqing
Zheng, Li
Wang, You
Xu, Tao
Zhou, Kaixin
CAS Array: design and assessment of a genotyping array for Chinese biobanking
title CAS Array: design and assessment of a genotyping array for Chinese biobanking
title_full CAS Array: design and assessment of a genotyping array for Chinese biobanking
title_fullStr CAS Array: design and assessment of a genotyping array for Chinese biobanking
title_full_unstemmed CAS Array: design and assessment of a genotyping array for Chinese biobanking
title_short CAS Array: design and assessment of a genotyping array for Chinese biobanking
title_sort cas array: design and assessment of a genotyping array for chinese biobanking
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10031742/
https://www.ncbi.nlm.nih.gov/pubmed/36968613
http://dx.doi.org/10.1093/pcmedi/pbad002
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