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Shengying Qin

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Articles

Contribution of copy number variants to schizophrenia in East Asian populations

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By Yu Chen, Qidi Feng, Max Lam, Mingrui Yu, YaoYao Sun, Yaoyao Sun, Cong Huai, Bimal Jana, Jack M. Fu, Calwing Liao, Robert Ye, Soyeon Kim, Justin Tubbs, Omar Shanta, Bhooma Thiruvahindrapuram, Yawen Jen, Guorui Zhao, Jess Wang, Stephen Scherer, Feng Zhu, Chih-Min Liu, Zhenglin Guo, Daniel P. Howrigan, Mark Daly, Benjamin M. Neale, Akira Sawa, Jonathan Sebat, Michael E. Talkowski, Jinsong Tang, Xiancang Ma, Shengying Qin, Weihua Yue, Tian Ge, Hailiang Huang, Wenzhao Shi
| Nature Verified
Abstract Studies on schizophrenia-associated rare copy number variants (CNVs) have predominantly focused on people of European (EUR) ancestry. Here we present a rare CNV study of schizophrenia in East Asian (EAS) populations, comprising 20,903 cases and 23,258 controls. We observed a significantly elevated genome-wide rare CNV burden in EAS cases compared with controls. Cross-population comparisons showed largely consistent rare CNV effects on schizophrenia risk.
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A blended genome and exome sequencing method captures genetic variation in an unbiased and cost-effective manner

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By Toni Boltz, Benjamin Chu, Matthew DeFelice, Calwing Liao, Julia M. Sealock, Robert Ye, Lerato Majara, Jack M. Fu, Lingyu Zhan, Sarah E. Medland, Sinéad B. Chapman, Simone Rubinacci, Jonna Grimsby, Tamrat Abebe, Melkam Alemayehu, Elizabeth Atkinson Verified, Tim B. Bigdeli, Harrison A. Brand, Lori B. Chibnik, Samuel Deluca, Ana M Diaz-Zuluaga, Abebaw Fekadu, Michael Gatzen, Bizu Gelaye, Toni Hill, Hailiang Huang, Roxanne James, Moses Joloba, Christopher Kachulis, Rogers Kamulegeya, Gabriel Kigen, Soyeon Kim, Nastassja Koen, Edith Kwobah, Seungmo Lee, Niall J Lennon, Penelope A. Lind, Esteban Lopera-Maya, Johnstone Makale, Serghei Mangul, Justin McMahon, Noeline Nakasujja, Carter Newman, Lethukuthula L. Nkambule, Ana Olivares, Catherine M Olsen, Linnet Ongeri, Sophie Parsa, Shengying Qin, Raj Ramesar, Chiara Sabatti, Jacquelyn Schneider, Christine Stevens, Anne Stevenson, Erik Stricker, Jessie Tang, Megan Townsend Verified, David Whiteman, Mary T. Yohannes, Mingrui Yu, Kai Yuan, NeuroGap-Psychosis Study, Dickens Akena, Lukoye Atwoli, Symon M Kariuki, Karestan C. Koenen, Charles Newton, Dan Stein, Solomon Teferra, Zukiswa Zingela, Carlos N. Pato, Michele Pato, Carlos Lopez-Jaramillo, Nelson B. Freimer, Roel A. Ophoff, Loes M. Olde Loohuis, Michael E. Talkowski, Benjamin M. Neale, Daniel P. Howrigan, Alicia Martin, Jacqueline I. Goldstein, Fred K. Ashaba, Amanda B. Bradway, Stella Gichuru, Marissa L. Gildea, Kalyn M. Hubbard, Wilfred E. Injera, Phillip R. Kalmbach, Joseph Kyebuzibwa, Pierre Mowlem, Henry Musinguzi, Rehema M. Mwema, Conor R. O’Neil, Adele Pretorius, Faye L. Reagan, Welelta Shiferaw, Rocky E. Stroud II
| Nature Verified
Abstract Here we developed and deployed the blended genome exome (BGE) method, a DNA library approach that generates low-pass whole-genome (1–4× mean depth) and deep whole-exome (30–40× mean depth) data in a single sequencing run. BGE is cost-effective, empowers most genomic discoveries possible with deep whole-genome sequencing and captures global common single-nucleotide polymorphism diversity.
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Author Correction: Improving polygenic prediction in ancestrally diverse populations - Nature Genetics

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By Yen-Feng Lin, Yen-Chen Anne Feng, Chia-Yen Chen, Max Lam, Akira Sawa, Alicia Martin, Shengying Qin, Tian Ge
| Nature Verified
Correction to: Nature Genetics https://doi.org/10.1038/s41588-022-01054-7, published online 5 May 2022. In the version of this article initially published, affiliation 24—Digital China Health Technologies Corp. Ltd., Beijing, China—was presented incorrectly and has been amended in the HTML and PDF versions of the article.
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