한빛사논문
고려대학교
Seoyeon Kim 1,2,10, Jihae Lee 3,10, In Gyeong Koh 1,2, Jungeun Ji 1,2, Hyun Jung Kim 4,5, Eunha Kim 6,7, Jihwan Park 8, Jong-Eun Park 9 and Joon-Yong An 1,2,3,*
1Department of Integrated Biomedical and Life Science, Korea University, Seoul, Republic of Korea.
2L-HOPE Program for Community-Based Total Learning Health Systems, Korea University, Seoul, Republic of Korea.
3School of Biosystem and Biomedical Science, College of Health Science, Korea University, Seoul, Republic of Korea.
4Department of Biomedical Sciences, College of Medicine, Korea University, Seoul, Republic of Korea.
5Department of Anatomy, College of Medicine, Korea University, Seoul, Republic of Korea.
6Department of Neuroscience, College of Medicine, Korea University, Seoul, Republic of Korea.
7BK21 Graduate Program, Department of Biomedical Sciences, College of Medicine, Korea University, Seoul, Republic of Korea.
8School of Life Sciences, Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea.
9Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.
10These authors contributed equally: Seoyeon Kim, Jihae Lee.
*Corresponding author: correspondence to Joon-Yong An
Abstract
Single-cell technologies have enhanced comprehensive knowledge regarding the human brain by facilitating an extensive transcriptomic census across diverse brain regions. Nevertheless, understanding the cellular and temporal specificity of neurological disorders remains ambiguous due to developmental variations. To address this gap, we illustrated the dynamics of disorder risk gene expression under development by integrating multiple single-cell RNA sequencing datasets. We constructed a comprehensive single-cell atlas of the developing human brain, encompassing 393,060 single cells across diverse developmental stages. Temporal analysis revealed the distinct expression patterns of disorder risk genes, including those associated with autism, highlighting their temporal regulation in different neuronal and glial lineages. We identified distinct neuronal lineages that diverged across developmental stages, each exhibiting temporal-specific expression patterns of disorder-related genes. Lineages of nonneuronal cells determined by molecular profiles also showed temporal-specific expression, indicating a link between cellular maturation and the risk of disorder. Furthermore, we explored the regulatory mechanisms involved in early brain development, revealing enriched patterns of fetal cell types associated with neuronal disorders indicative of the prenatal stage’s influence on disease determination. Our findings facilitate unbiased comparisons of cell type‒disorder associations and provide insight into dynamic alterations in risk genes during development, paving the way for a deeper understanding of neurological disorders.
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