美國加州大學(xué)圣迭戈分校任兵團(tuán)隊繪制出人腦中單細(xì)胞染色質(zhì)可及性的比較圖譜。該項研究成果發(fā)表在2023年10月13日出版的《科學(xué)》上。
利用通過測序的轉(zhuǎn)座酶可及染色質(zhì)（snATAC-seq）的單核分析，研究人員探索了來自3名成年人的42個大腦區(qū)域的110萬個細(xì)胞的開放染色質(zhì)景觀。整合這些數(shù)據(jù)揭示了107種不同的細(xì)胞類型及其對人類基因組中544735個候選順式調(diào)控DNA元件（cCRE）的特異性利用。近三分之一的cCRE在單核細(xì)胞中表現(xiàn)出保守性和染色質(zhì)可及性。研究人員揭示了特定腦細(xì)胞類型與神經(jīng)精神疾病（包括精神分裂癥、雙相情感障礙、阿爾茨海默病（AD）和重度抑郁癥）之間的密切聯(lián)系，并開發(fā)了深度學(xué)習(xí)模型來預(yù)測非編碼風(fēng)險變異在這些疾病中的調(diào)節(jié)作用。
據(jù)了解，單細(xì)胞轉(zhuǎn)錄組學(xué)的最新進(jìn)展揭示了人類大腦中不同的神經(jīng)元和膠質(zhì)細(xì)胞類型。然而，調(diào)控細(xì)胞身份和功能的調(diào)控程序仍不清楚。
附：英文原文
Title: A comparative atlas of single-cell chromatin accessibility in the human brain
Author: Yang Eric Li, Sebastian Preissl, Michael Miller, Nicholas D. Johnson, Zihan Wang, Henry Jiao, Chenxu Zhu, Zhaoning Wang, Yang Xie, Olivier Poirion, Colin Kern, Antonio Pinto-Duarte, Wei Tian, Kimberly Siletti, Nora Emerson, Julia Osteen, Jacinta Lucero, Lin Lin, Qian Yang, Quan Zhu, Nathan Zemke, Sarah Espinoza, Anna Marie Yanny, Julie Nyhus, Nick Dee, Tamara Casper, Nadiya Shapovalova, Daniel Hirschstein, Rebecca D. Hodge, Sten Linnarsson, Trygve Bakken, Boaz Levi, C. Dirk Keene, Jingbo Shang, Ed Lein, Allen Wang, M. Margarita Behrens, Joseph R. Ecker, Bing Ren
Issue&Volume: 2023-10-13
Abstract: Recent advances in single-cell transcriptomics have illuminated the diverse neuronal and glial cell types within the human brain. However, the regulatory programs governing cell identity and function remain unclear. Using a single-nucleus assay for transposase-accessible chromatin using sequencing (snATAC-seq), we explored open chromatin landscapes across 1.1 million cells in 42 brain regions from three adults. Integrating this data unveiled 107 distinct cell types and their specific utilization of 544,735 candidate cis-regulatory DNA elements (cCREs) in the human genome. Nearly a third of the cCREs demonstrated conservation and chromatin accessibility in the mouse brain cells. We reveal strong links between specific brain cell types and neuropsychiatric disorders including schizophrenia, bipolar disorder, Alzheimer’s disease (AD), and major depression, and have developed deep learning models to predict the regulatory roles of noncoding risk variants in these disorders.
DOI: adf7044
Source: https://www.science.org/doi/10.1126/science.adf7044
期刊信息
Science：《科學(xué)》，創(chuàng)刊于1880年。隸屬于美國科學(xué)促進(jìn)會，最新IF：63.714
官方網(wǎng)址：https://www.sciencemag.org/
投稿鏈接：https://cts.sciencemag.org/scc/
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