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基质 RNAi 分析揭示了髓系转录因子的调控相互依赖关系。

Regulatory interdependence of myeloid transcription factors revealed by Matrix RNAi analysis.

机构信息

RIKEN Omics Science Center, RIKEN Yokohama Institute 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan.

出版信息

Genome Biol. 2009;10(11):R121. doi: 10.1186/gb-2009-10-11-r121. Epub 2009 Nov 2.

Abstract

BACKGROUND

With the move towards systems biology, we need sensitive and reliable ways to determine the relationships between transcription factors and their target genes. In this paper we analyze the regulatory relationships between 78 myeloid transcription factors and their coding genes by using the matrix RNAi system in which a set of transcription factor genes are individually knocked down and the resultant expression perturbation is quantified.

RESULTS

Using small interfering RNAs we knocked down the 78 transcription factor genes in monocytic THP-1 cells and monitored the perturbation of the expression of the same 78 transcription factors and 13 other transcription factor genes as well as 5 non-transcription factor genes by quantitative real-time RT-PCR, thereby building a 78 x 96 matrix of perturbation and measurement. This approach identified 876 cases where knockdown of one transcription factor significantly affected the expression of another (from a potential 7,488 combinations). Our study also revealed cell-type-specific transcriptional regulatory networks in two different cell types.

CONCLUSIONS

By considering whether the targets of a given transcription factor are naturally up- or downregulated during phorbol 12-myristate 13-acetate-induced differentiation, we could classify these edges as pro-differentiative (229), anti-differentiative (76) or neither (571) using expression profiling data obtained in the FANTOM4 study. This classification analysis suggested that several factors could be involved in monocytic differentiation, while others such as MYB and the leukemogenic fusion MLL-MLLT3 could help to maintain the initial undifferentiated state by repressing the expression of pro-differentiative factors or maintaining expression of anti-differentiative factors.

摘要

背景

随着系统生物学的发展,我们需要敏感和可靠的方法来确定转录因子与其靶基因之间的关系。在本文中,我们通过使用矩阵 RNAi 系统分析了 78 种髓系转录因子与其编码基因之间的调控关系,在该系统中,一组转录因子基因被单独敲低,并对由此产生的表达扰动进行定量。

结果

我们使用小干扰 RNA 敲低单核细胞 THP-1 细胞中的 78 种转录因子基因,并通过定量实时 RT-PCR 监测相同的 78 种转录因子和 13 种其他转录因子基因以及 5 种非转录因子基因的表达扰动,从而构建了一个 78 x 96 的扰动和测量矩阵。这种方法确定了 876 种情况,其中一种转录因子的敲低显著影响了另一种转录因子的表达(来自潜在的 7488 种组合)。我们的研究还揭示了两种不同细胞类型中细胞类型特异性转录调控网络。

结论

通过考虑给定转录因子的靶基因在佛波醇 12-肉豆蔻酸 13-醋酸酯诱导分化过程中是否自然上调或下调,我们可以使用 FANTOM4 研究中获得的表达谱数据将这些边缘分类为促分化(229)、抗分化(76)或两者都不是(571)。这种分类分析表明,有几个因素可能参与单核细胞分化,而其他因素,如 MYB 和致白血病融合 MLL-MLLT3,则可以通过抑制促分化因子的表达或维持抗分化因子的表达来帮助维持初始未分化状态。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c1e/2810662/16cf17c779f3/gb-2009-10-11-r121-1.jpg

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