基于深度学习的细胞特异性基因调控网络,从单细胞多组数据中推断出来
Junlin Xu1, Changcheng Lu2, Shuting Jin1
1School of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, Hubei 430065, China.
Nucleic acids research
|March 4, 2025
概括
新的深度学习框架scMultiomeGRN有效地使用集成的单细胞多组数据重建基因调节网络 (GRNs). 这种方法增强了对基因调节和疾病机制的理解,优于现有的模型.
科学领域:
- 基因组学和生物信息学
- 系统生物学 系统生物学
- 计算生物学 计算生物学
背景情况:
- 基因调节网络 (GRNs) 对于理解基因组调节和遗传信息传输至关重要.
- 单细胞多组数据为GRNs提供了高分辨率的洞察力,但由于单细胞测序中的数据丢失而受到限制.
- 准确的GRN推断对于阐明健康和疾病中的细胞机制至关重要.
研究的目的:
- 开发一个深度学习框架,scMultiomeGRN,用于推断转录因子 (TF) 监管网络.
- 整合单细胞RNA测序 (scRNA-seq) 和单细胞ATAC测序 (scATAC-seq) 数据,以进行强大的GRN重建.
- 从具有挑战性的单细胞多组数据中提高GRN推断的准确性和分辨率.
主要方法:
- 开发了scMultiomeGRN,这是一个深度学习框架,利用scRNA-seq和scATAC-seq数据的独特集成.
- 实现了模式特定的邻近聚合器和跨模式注意模块,以学习TF表示.
- 概念化了TF网络图形结构,以增强网络阐释.
主要成果:
- 在基准数据集上,scMultiomeGRN与最先进的模型相比表现优越.
- 该框架成功确定了与疾病相关的调节网络,包括阿尔茨海默病微质中的SPI1和RUNX1.
- 从单细胞多组数据中获得了精确的细胞类型特定的GRN推断.
结论:
- scMultiomeGRN提供了一种强大的深度学习方法,用于重建基因调节网络.
- 该框架有效地克服了单细胞数据丢失的局限性,以改进GRN推断.
- 能够发现与人类疾病相关的细胞类型特定的调节机制.
相关概念视频
01:58Cell Specific Gene Expression
13.4K
Multicellular organisms contain a variety of structurally and functionally distinct cell types, but the DNA in all the cells originated from the same parent cells. The differences in the cells can be attributed to the differential gene expression. Liver cells, whose functions include detoxification of blood, production of bile to metabolize fats, and synthesis of proteins essential for metabolism, must express a specific set of genes to perform their functions. Gene expression also varies with...
13.4K
02:33Combinatorial Gene Control
8.3K
Combinatorial gene control is the synergistic action of several transcriptional factors to regulate the expression of a single gene. The absence of one or more of these factors may lead to a significant difference in the level of gene expression or repression.
The expression of more than 30,000 genes is controlled by approximately 2000-3000 transcription factors. This is possible because a single transcription factor can recognize more than one regulatory sequence. The specificity in gene...
The expression of more than 30,000 genes is controlled by approximately 2000-3000 transcription factors. This is possible because a single transcription factor can recognize more than one regulatory sequence. The specificity in gene...
8.3K
01:23Regulation of Expression at Multiple Steps
863
The gene expression in cells is regulated at different stages: (i) transcription, (ii) RNA processing, (iii) RNA localization, and (iv) translation. Transcriptional regulation is mediated by regulatory proteins such as transcription factors, activators, or repressors—these control gene expression by initiating or inhibiting the transcription of genes. Once a precursor or pre-mRNA is produced, it undergoes post-transcriptional modification, including 5' capping, splicing, and the...
863
02:24Regulation of Expression Occurs at Multiple Steps
2.9K
2.9K
02:23Master Transcription Regulators
6.8K
Master transcription regulators are regulatory proteins that are predominantly responsible for regulating the expression of multiple genes. Often these genes work in concert to drive a complex process. Activation of a master transcription regulator can lead to a cascade of transcriptional activation necessary for that outcome. These regulators can directly bind to the regulatory sequences of the various genes involved, or they can indirectly regulate transcription by binding to regulatory...
6.8K