染色质
生物
计算生物学
仿形(计算机编程)
基因
遗传学
基因表达谱
基因表达
细胞生物学
分子生物学
计算机科学
操作系统
作者
Amy F. Chen,Benjamin Parks,Arwa S. Kathiria,Benjamin Ober-Reynolds,Jörg J. Goronzy,William J. Greenleaf
出处
期刊:Nature Methods
[Springer Nature]
日期:2022-05-01
卷期号:19 (5): 547-553
被引量:60
标识
DOI:10.1038/s41592-022-01461-y
摘要
In this work, we describe NEAT-seq (sequencing of nuclear protein epitope abundance, chromatin accessibility and the transcriptome in single cells), enabling interrogation of regulatory mechanisms spanning the central dogma. We apply this technique to profile CD4 memory T cells using a panel of master transcription factors (TFs) that drive T cell subsets and identify examples of TFs with regulatory activity gated by transcription, translation and regulation of chromatin binding. We also link a noncoding genome-wide association study single-nucleotide polymorphism (SNP) within a GATA motif to a putative target gene, using NEAT-seq data to internally validate SNP impact on GATA3 regulation.
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