作者团队

Yang Eric Li, Sebastian Preissl, Michael Miller, ..., M Margarita Behrens, Joseph R Ecker, Bing Ren

研究方向

人类大脑单细胞染色质可及性图谱

论文题目 

A comparative atlas of single-cell chromatin accessibility in the human brain

论文摘要

INTRODUCTION: Neuropsychiatric disorders and mental illnesses are the leading cause of disease burden in the United States.  Tens of thousands of sequence variants in the human genome have been linked to the etiology of these conditions.  However, elucidating the role of the identified risk variants remains a challenge because most of them are outside of protein-coding regions and currently lack functional annotation.  These disease risk variants likely exert their influence by perturbing transcriptional regulatory elements, thereby modulating gene expression in cell types pertinent to neuropsychiatric disorders.  Recent advancements in single-cell technologies have unveiled a high degree of cellular heterogeneity across the human brain.  However, the transcriptional regulatory sequences governing the identity and function of each individual brain cell type remain to be delineated, hindering our ability to interpret the noncoding disease risk variants.

RATIONALE: Conventionally, transcriptional regulatory sequences may be determined by evidence of chromatin accessibility that generally accompanies transcription factor binding and chromatin remodeling.  However, prior catalogs of transcriptional regulatory elements lack the information about cell-type–specific activities of each element because of the use of bulk tissue samples.  Recent technological strides have empowered us to analyze chromatin accessibility at the single-cell level, enabling the creation of cell-type–specific maps of transcriptional regulatory elements for complex organs such as the human brain.

RESULTS: In this study, we present a comprehensive analysis of chromatin accessibility in the human brain at the single-cell level, encompassing a collection of 1.1 million cells from 42 distinct brain regions in three neurotypical adult subjects.  We used this chromatin atlas to define 107 distinct brain cell types and uncovered the state of chromatin accessibility at 544,735 putative transcriptional regulatory elements in these cell types.  A substantial number of these regulatory elements also exhibited both sequence conservation and chromatin accessibility in mouse brain cells, underlining their functional importance.  Through integrative analysis, we have linked many putative transcriptional regulatory elements to potential target genes.  We further leveraged this atlas to predict disease relevant cell types for 19 neuropsychiatric traits and disorders.  Finally, we developed machine learning models to predict the regulatory function of disease risk variants.  We have made this atlas freely available to the public through an interactive web portal CATLAS (www.catlas.org).

CONCLUSION: The single-cell chromatin atlas of the human brain represents a valuable resource for the neuroscience community.  It offers insights into the gene-regulatory programs shaping the diversity of brain cell types and aids in interpreting the functional roles of disease risk variants located outside of protein-coding regions.  This atlas, in combination with other molecular and anatomical data, promises to advance our understanding of brain function and neuropathology, ultimately offering avenues for more effective approaches to addressing neuropsychiatric disorders.

    介绍：神经精神疾病和精神疾病是美国疾病负担的主要原因。人类基因组中数以万计的序列变异与这些疾病的病因有关。然而，阐明已确定的风险变异的作用仍然是一项挑战，因为它们大多数位于蛋白质编码区之外，目前缺乏功能注释。这些疾病风险变异可能通过干扰转录调节元件来发挥其影响，从而调节与神经精神疾病相关的细胞类型中的基因表达。单细胞技术的最新进展揭示了人类大脑中高度的细胞异质性。然而，控制每种脑细胞类型的特性和功能的转录调控序列仍有待确定，这阻碍了我们解释非编码疾病风险变异的能力。

    基本原理：转录调控序列通常可以通过染色质可及性来确定，而染色质可及性通常伴随转录因子结合和染色质重塑。然而，由于使用的是大块组织样本，之前的转录调节元件目录缺乏每个元件的细胞类型特异性活性信息。最近的技术进步使我们能够在单细胞水平分析染色质的可及性，从而能够创建复杂器官（如人脑）转录调节元件的细胞类型特异性图谱。

    结果：在这项研究中，研究人员在单细胞水平上对人脑的染色质可及性进行了全面分析，包括来自3名神经典型成人受试者42个不同脑区的110万个细胞。研究人员使用该染色质图谱定义了107种不同的脑细胞类型，并揭示了这些细胞类型中544,735个推测的转录调节元件的染色质可及性状态。在小鼠脑细胞中，大量的这些调控元件也表现出序列保守性和染色质可及性，强调了它们的功能重要性。通过整合分析，研究人员将许多推测的转录调控元件与潜在的靶基因联系起来。进一步利用该图谱预测了19种神经精神特征和疾病相关细胞类型。最后，研究人员开发了机器学习模型来预测疾病风险变异的调节功能。通过交互式门户网站CATLAS （www.catlas.org）向公众免费提供了该图谱。

    结论：人脑单细胞染色质图谱是神经科学界的宝贵资源。它提供了对塑造脑细胞类型多样性的基因调控程序的见解，并有助于解释位于蛋白质编码区之外的疾病风险变异的功能作用。该图谱结合其他分子和解剖学数据，有望增进我们对脑功能和神经病理学的理解，最终为解决神经精神疾病提供更有效的方法。