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利用综合图谱和预测模型揭示大脑活性调节元件的复杂性和进化。

Using a comprehensive atlas and predictive models to reveal the complexity and evolution of brain-active regulatory elements.

机构信息

Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA.

Khoury College of Computer Science, Northeastern University, Boston, MA 02115, USA.

出版信息

Sci Adv. 2024 May 24;10(21):eadj4452. doi: 10.1126/sciadv.adj4452. Epub 2024 May 23.


DOI:10.1126/sciadv.adj4452
PMID:38781344
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11114231/
Abstract

Most genetic variants associated with psychiatric disorders are located in noncoding regions of the genome. To investigate their functional implications, we integrate epigenetic data from the PsychENCODE Consortium and other published sources to construct a comprehensive atlas of candidate brain cis-regulatory elements. Using deep learning, we model these elements' sequence syntax and predict how binding sites for lineage-specific transcription factors contribute to cell type-specific gene regulation in various types of glia and neurons. The elements' evolutionary history suggests that new regulatory information in the brain emerges primarily via smaller sequence mutations within conserved mammalian elements rather than entirely new human- or primate-specific sequences. However, primate-specific candidate elements, particularly those active during fetal brain development and in excitatory neurons and astrocytes, are implicated in the heritability of brain-related human traits. Additionally, we introduce PsychSCREEN, a web-based platform offering interactive visualization of PsychENCODE-generated genetic and epigenetic data from diverse brain cell types in individuals with psychiatric disorders and healthy controls.

摘要

大多数与精神疾病相关的遗传变异位于基因组的非编码区域。为了研究它们的功能意义,我们整合了 PsychENCODE 联盟和其他已发表来源的表观遗传数据,构建了一个候选脑顺式调控元件的综合图谱。我们使用深度学习来模拟这些元件的序列语法,并预测谱系特异性转录因子的结合位点如何有助于各种类型的神经胶质细胞和神经元中的细胞类型特异性基因调控。这些元件的进化历史表明,大脑中出现的新调控信息主要是通过保守的哺乳动物元件内的较小序列突变产生的,而不是全新的人类或灵长类特异性序列。然而,灵长类特异性候选元件,特别是那些在胎儿大脑发育以及兴奋性神经元和星形胶质细胞中活跃的元件,与与大脑相关的人类特征的遗传性有关。此外,我们引入了 PsychSCREEN,这是一个基于网络的平台,提供了来自个体精神疾病和健康对照组的不同脑细胞类型的 PsychENCODE 生成的遗传和表观遗传数据的交互式可视化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b64e/11114231/b707e4fbbdd9/sciadv.adj4452-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b64e/11114231/c87a4c5e45ac/sciadv.adj4452-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b64e/11114231/2cc7d752e07c/sciadv.adj4452-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b64e/11114231/122a5843afef/sciadv.adj4452-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b64e/11114231/185d7bf5c08b/sciadv.adj4452-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b64e/11114231/9afd8d1361cb/sciadv.adj4452-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b64e/11114231/b707e4fbbdd9/sciadv.adj4452-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b64e/11114231/c87a4c5e45ac/sciadv.adj4452-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b64e/11114231/2cc7d752e07c/sciadv.adj4452-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b64e/11114231/122a5843afef/sciadv.adj4452-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b64e/11114231/185d7bf5c08b/sciadv.adj4452-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b64e/11114231/9afd8d1361cb/sciadv.adj4452-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b64e/11114231/b707e4fbbdd9/sciadv.adj4452-f6.jpg

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本文引用的文献

[1]
Leveraging base-pair mammalian constraint to understand genetic variation and human disease.

Science. 2023-4-28

[2]
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Science. 2023-4-28

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Science. 2023-4-28

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Science. 2023-4-28

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Sci Adv. 2023-2-15

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Nature. 2022-11

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Genome-wide meta-analysis of insomnia prioritizes genes associated with metabolic and psychiatric pathways.

Nat Genet. 2022-8

[10]
A single-cell atlas of chromatin accessibility in the human genome.

Cell. 2021-11-24

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