气候变化领域集成服务门户(CCPortal): Prediction of Alzheimer’s disease-specific phospholipase c gamma-1 SNV by deep learning-based approach for high-throughput screening

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DOI	10.1073/pnas.2011250118
	Prediction of Alzheimer’s disease-specific phospholipase c gamma-1 SNV by deep learning-based approach for high-throughput screening
	Kim S.-H.; Yang S.; Lim K.-H.; Ko E.; Jang H.-J.; Kang M.; Suh P.-G.; Joo J.-Y.
发表日期	2021
ISSN	00278424
卷号	118 期号:3
英文摘要	Exon splicing triggered by unpredicted genetic mutation can cause translational variations in neurodegenerative disorders. In this study, we discover Alzheimer’s disease (AD)-specific single-nucleotide variants (SNVs) and abnormal exon splicing of phospholipase c gamma-1 (PLCγ1) gene, using genome-wide association study (GWAS) and a deep learning-based exon splicing prediction tool. GWAS revealed that the identified single-nucleotide variations were mainly distributed in the H3K27ac-enriched region of PLCγ1 gene body during brain development in an AD mouse model. A deep learning analysis, trained with human genome sequences, predicted 14 splicing sites in human PLCγ1 gene, and one of these completely matched with an SNV in exon 27 of PLCγ1 gene in an AD mouse model. In particular, the SNV in exon 27 of PLCγ1 gene is associated with abnormal splicing during messenger RNA maturation. Taken together, our findings suggest that this approach, which combines in silico and deep learning-based analyses, has potential for identifying the clinical utility of critical SNVs in AD prediction. © 2021 National Academy of Sciences. All rights reserved.
英文关键词	Alzheimer’s disease \| deep learning \| PLCγ1 \| single-nucleotide variation
语种	英语
scopus关键词	histone H3; messenger RNA; phospholipase C gamma1; Alzheimer disease; animal experiment; animal model; animal tissue; Article; brain cortex; brain development; computer model; controlled study; deep learning; disease course; exon; forebrain; gene expression; gene identification; gene insertion; gene mutation; genome-wide association study; high throughput screening; histone modification; human; human genome; mouse; nonhuman; PLCgamma1 gene; priority journal; RNA splicing; single nucleotide polymorphism
来源期刊	Proceedings of the National Academy of Sciences of the United States of America
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/180976
作者单位	Neurodegenerative Disease Research Group, Daegu, 41062, South Korea; Korea Brain Research Institute, Daegu, 41062, South Korea; Department of Computer Science, University of Nevada, Las Vegas, NV 89154, United States; School of Life Sciences, Ulsan National Institute of Science and Technology, Ulsan, 44919, South Korea
推荐引用方式 GB/T 7714	Kim S.-H.,Yang S.,Lim K.-H.,等. Prediction of Alzheimer’s disease-specific phospholipase c gamma-1 SNV by deep learning-based approach for high-throughput screening[J],2021,118(3).
APA	Kim S.-H..,Yang S..,Lim K.-H..,Ko E..,Jang H.-J..,...&Joo J.-Y..(2021).Prediction of Alzheimer’s disease-specific phospholipase c gamma-1 SNV by deep learning-based approach for high-throughput screening.Proceedings of the National Academy of Sciences of the United States of America,118(3).
MLA	Kim S.-H.,et al."Prediction of Alzheimer’s disease-specific phospholipase c gamma-1 SNV by deep learning-based approach for high-throughput screening".Proceedings of the National Academy of Sciences of the United States of America 118.3(2021).