DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Choi, Jung Kyoon | - |
dc.contributor.advisor | 최정균 | - |
dc.contributor.advisor | Lee, Jeong Ho | - |
dc.contributor.advisor | 이정호 | - |
dc.contributor.author | Lee, Taeyeop | - |
dc.date.accessioned | 2021-05-11T19:41:55Z | - |
dc.date.available | 2021-05-11T19:41:55Z | - |
dc.date.issued | 2020 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=901565&flag=dissertation | en_US |
dc.identifier.uri | http://hdl.handle.net/10203/283479 | - |
dc.description | 학위논문(박사) - 한국과학기술원 : 의과학대학원, 2020.2,[v, 161 p. :] | - |
dc.description.abstract | Autism spectrum disorder (ASD) is a neurodevelopmental disorder with high heritability estimate. To unravel the genetic causes of ASD, genetic variations that affect protein coding genes were extensively studied. Yet, the role of noncoding variants remains poorly understood. Here, by utilizing the three-dimensional structure of the genome, we attempted to assess the effect of noncoding de novo mutations (DNM) which were identified in simplex autism families. The noncoding DNMs showed evidence for transcriptional dysregulation and the target genes of noncoding DNMs were involved in biological pathways such as histone modification, prenatal brain development, and pregnancy. In addition to the DNMs, the effect of rare inherited variations was examined in multiplex autism families. Rare recessive variants shared by affected siblings were located in regulatory regions active in brain tissues, and filtered genes targeted by the variants were highly expressed in the brain. Specifically, prioritization by evolutionary features indicated a novel gene, FRRS1L, which is an outer-core component of the AMPA receptor complex. In the behavioral experiments, Frrs1l knockout mice demonstrated impaired recognition of social novelty, whereas human gene knockin mice showed improved social memory. Finally, to better interpret the noncoding common variants found from genome-wide association studies (GWASs), we developed a fine-mapping tool. The developed tool employs a convolutional neural network, which detects complex epigenetic patterns shared by risk variants scattered among multiple GWAS loci. When applied for major psychiatric disorders, the predicted causal variants were concentrated in active regulatory regions of relevant cell types and were in physical contact with transcription factors. When evaluating the ASD model, disease relevant features exhibited high level of importance, reflecting the pathophysiology of the disorder. Our findings highlight the role of diverse spectrum of noncoding variants in ASD. | - |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | autism▼anoncoding variant▼aepigenome▼ade novo mutation▼amachine learning | - |
dc.subject | 자폐 스펙트럼 장애▼a비암호화 변이▼a후성유전체▼a드노보 변이▼a기계학습 | - |
dc.title | Genetic architecture of autism spectrum disorder | - |
dc.title.alternative | 자폐 스펙트럼 장애의 유전학적 원인에 기여하는 비암호화 변이의 역할 | - |
dc.type | Thesis(Ph.D) | - |
dc.identifier.CNRN | 325007 | - |
dc.description.department | 한국과학기술원 :의과학대학원, | - |
dc.contributor.alternativeauthor | 이태엽 | - |
dc.title.subtitle | contribution of de novo, rare inherited, and common noncoding variants | - |
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