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The three-dimensional landscape of the genome in human brain tissue unveils regulatory mechanisms leading to schizophrenia risk

机译:人脑组织基因组的三维景观推出了导致精神分裂症风险的监管机制

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摘要

Recent advances in our understanding of the genetic architecture of schizophrenia have shed light on the schizophrenia etiology. While common variation is one of the major genetic contributors, the majority of common variation reside in non-coding genome, posing a significant challenge in understanding the functional impact of this class of genetic variation. Functional genomicdatasets that range from expression quantitative trait loci (eQTL) to chromatin interactions are critical to identify the potential target genes and functional consequences of noncoding variation. In this review, we discuss how three-dimensional chromatin landscape, identified by a technique called Hi-C, has facilitated the identification of potential target genes impacting schizophrenia risk. We outline key steps for Hi-C driven gene mapping, and compare Hi-C defined schizophrenia risk genes defined across developmental epochs and cell types, which offer rich insights into the temporal window and cellular etiology of schizophrenia. In contrast with a neurodevelopmental hypothesis in schizophrenia, Hi-C defined schizophrenia risk genes are postnatally enriched, suggesting that postnatal development is also important for schizophrenia pathogenesis. Moreover, Hi-C defined schizophrenia risk genes are highly expressed in excitatory neurons, highlighting excitatory neurons as a central cell type for schizophrenia. Further characterization of Hi-C defined schizophrenia risk genes demonstrated enrichment for genes that harbor loss-of-function variation in neurodevelopmental disorders, suggesting a shared genetic etiology between schizophrenia and neurodevelopmental disorders. Collectively, moving the search space from risk variants to the target genes lays a foundation to understand the neurobiological basis of schizophrenia. (C) 2019 Elsevier B.V. All rights reserved.
机译:我们对精神分裂症遗传建筑的理解的最新进展对精神分裂症病因进行了揭示。虽然常见变异是主要的遗传贡献者之一,但大多数常见变异都存在于非编码基因组中,在理解这类遗传变异的功能影响方面会产生重大挑战。从表达定量性状基因座(EQT1)到染色质相互作用的功能性基因组特征对于鉴定潜在的靶基因和非编码变异的功能后果至关重要。在本文中,我们讨论了通过称为Hi-C的技术鉴定的三维染色质横向,并促进了影响精神分裂症风险的潜在靶基因的鉴定。我们概述了Hi-C驱动基因测绘的关键步骤,并比较了在发育中期和细胞类型中定义的Hi-C定义的精神分裂症风险基因,这提供了丰富的精神分裂症的颞窗和细胞病因。与精神分裂症中的神经发育假设相比,在出现后,Hi-C定义的精神分裂症风险基因在出现后富集,表明产后发育对精神分裂症发病机制也很重要。此外,Hi-C定义的精神分裂症风险基因在兴奋性神经元中高度表达,突出显示兴奋性神经元作为精神分裂症的中央细胞类型。进一步表征Hi-C定义的精神分裂症风险基因显示出侵扰神经发育障碍缺失变异的基因的富集,表明精神分裂症和神经发育障碍之间的共同遗传病程。统称,将搜索空间从风险变体移动到目标基因,为理解精神分裂症的神经生物学基础奠定了基础。 (c)2019年Elsevier B.V.保留所有权利。

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