Ya Cui, Frederick J. Arnold, Jason Sheng Li, Jie Wu, Dan Wang, Julien Philippe, Michael R. Colwin, Sebastian Michels, Chaorong Chen, Tamer Sallam, Leslie M. Thompson, Albert R. La Spada, Wei Li
{"title":"多组学定量性状位点将串联重复大小变异与人脑基因调控联系起来","authors":"Ya Cui, Frederick J. Arnold, Jason Sheng Li, Jie Wu, Dan Wang, Julien Philippe, Michael R. Colwin, Sebastian Michels, Chaorong Chen, Tamer Sallam, Leslie M. Thompson, Albert R. La Spada, Wei Li","doi":"10.1038/s41588-024-02057-2","DOIUrl":null,"url":null,"abstract":"<p>Tandem repeat (TR) size variation is implicated in ~50 neurological disorders, yet its impact on gene regulation in the human brain remains largely unknown. In the present study, we quantified the impact of TR size variation on brain gene regulation across distinct molecular phenotypes, based on 4,412 multi-omics samples from 1,597 donors, including 1,586 newly sequenced ones. We identified ~2.2 million TR molecular quantitative trait loci (TR-xQTLs), linking ~139,000 unique TRs to nearby molecular phenotypes, including many known disease-risk TRs, such as the G<sub>2</sub>C<sub>4</sub> expansion in <i>C9orf72</i> associated with amyotrophic lateral sclerosis. Fine-mapping revealed ~18,700 TRs as potential causal variants. Our in vitro experiments further confirmed the causal and independent regulatory effects of three TRs. Additional colocalization analysis indicated the potential causal role of TR variation in brain-related phenotypes, highlighted by a 3ʹ-UTR TR in <i>NUDT14</i> linked to cortical surface area and a TG repeat in <i>PLEKHA1</i>, associated with Alzheimer’s disease.</p>","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"27 1","pages":""},"PeriodicalIF":31.7000,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi-omic quantitative trait loci link tandem repeat size variation to gene regulation in human brain\",\"authors\":\"Ya Cui, Frederick J. Arnold, Jason Sheng Li, Jie Wu, Dan Wang, Julien Philippe, Michael R. Colwin, Sebastian Michels, Chaorong Chen, Tamer Sallam, Leslie M. Thompson, Albert R. La Spada, Wei Li\",\"doi\":\"10.1038/s41588-024-02057-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Tandem repeat (TR) size variation is implicated in ~50 neurological disorders, yet its impact on gene regulation in the human brain remains largely unknown. In the present study, we quantified the impact of TR size variation on brain gene regulation across distinct molecular phenotypes, based on 4,412 multi-omics samples from 1,597 donors, including 1,586 newly sequenced ones. We identified ~2.2 million TR molecular quantitative trait loci (TR-xQTLs), linking ~139,000 unique TRs to nearby molecular phenotypes, including many known disease-risk TRs, such as the G<sub>2</sub>C<sub>4</sub> expansion in <i>C9orf72</i> associated with amyotrophic lateral sclerosis. Fine-mapping revealed ~18,700 TRs as potential causal variants. Our in vitro experiments further confirmed the causal and independent regulatory effects of three TRs. Additional colocalization analysis indicated the potential causal role of TR variation in brain-related phenotypes, highlighted by a 3ʹ-UTR TR in <i>NUDT14</i> linked to cortical surface area and a TG repeat in <i>PLEKHA1</i>, associated with Alzheimer’s disease.</p>\",\"PeriodicalId\":18985,\"journal\":{\"name\":\"Nature genetics\",\"volume\":\"27 1\",\"pages\":\"\"},\"PeriodicalIF\":31.7000,\"publicationDate\":\"2025-01-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nature genetics\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1038/s41588-024-02057-2\",\"RegionNum\":1,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GENETICS & HEREDITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature genetics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1038/s41588-024-02057-2","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
Multi-omic quantitative trait loci link tandem repeat size variation to gene regulation in human brain
Tandem repeat (TR) size variation is implicated in ~50 neurological disorders, yet its impact on gene regulation in the human brain remains largely unknown. In the present study, we quantified the impact of TR size variation on brain gene regulation across distinct molecular phenotypes, based on 4,412 multi-omics samples from 1,597 donors, including 1,586 newly sequenced ones. We identified ~2.2 million TR molecular quantitative trait loci (TR-xQTLs), linking ~139,000 unique TRs to nearby molecular phenotypes, including many known disease-risk TRs, such as the G2C4 expansion in C9orf72 associated with amyotrophic lateral sclerosis. Fine-mapping revealed ~18,700 TRs as potential causal variants. Our in vitro experiments further confirmed the causal and independent regulatory effects of three TRs. Additional colocalization analysis indicated the potential causal role of TR variation in brain-related phenotypes, highlighted by a 3ʹ-UTR TR in NUDT14 linked to cortical surface area and a TG repeat in PLEKHA1, associated with Alzheimer’s disease.
期刊介绍:
Nature Genetics publishes the very highest quality research in genetics. It encompasses genetic and functional genomic studies on human and plant traits and on other model organisms. Current emphasis is on the genetic basis for common and complex diseases and on the functional mechanism, architecture and evolution of gene networks, studied by experimental perturbation.
Integrative genetic topics comprise, but are not limited to:
-Genes in the pathology of human disease
-Molecular analysis of simple and complex genetic traits
-Cancer genetics
-Agricultural genomics
-Developmental genetics
-Regulatory variation in gene expression
-Strategies and technologies for extracting function from genomic data
-Pharmacological genomics
-Genome evolution