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如何构建哺乳动物模式形成的转录网络模型。

How to build transcriptional network models of mammalian pattern formation.

作者信息

Kioussi Chrissa, Gross Michael K

机构信息

Department of Pharmaceutical Sciences, College of Pharmacy, Oregon State University, Corvallis, Oregon, United States of America.

出版信息

PLoS One. 2008 May 14;3(5):e2179. doi: 10.1371/journal.pone.0002179.

Abstract

BACKGROUND

Genetic regulatory networks of sequence specific transcription factors underlie pattern formation in multicellular organisms. Deciphering and representing the mammalian networks is a central problem in development, neurobiology, and regenerative medicine. Transcriptional networks specify intermingled embryonic cell populations during pattern formation in the vertebrate neural tube. Each embryonic population gives rise to a distinct type of adult neuron. The homeodomain transcription factor Lbx1 is expressed in five such populations and loss of Lbx1 leads to distinct respecifications in each of the five populations.

METHODOLOGY/PRINCIPAL FINDINGS: We have purified normal and respecified pools of these five populations from embryos bearing one or two copies of the null Lbx1(GFP) allele, respectively. Microarrays were used to show that expression levels of 8% of all transcription factor genes were altered in the respecified pool. These transcription factor genes constitute 20-30% of the active nodes of the transcriptional network that governs neural tube patterning. Half of the 141 regulated nodes were located in the top 150 clusters of ultraconserved non-coding regions. Generally, Lbx1 repressed genes that have expression patterns outside of the Lbx1-expressing domain and activated genes that have expression patterns inside the Lbx1-expressing domain.

CONCLUSIONS/SIGNIFICANCE: Constraining epistasis analysis of Lbx1 to only those cells that normally express Lbx1 allowed unprecedented sensitivity in identifying Lbx1 network interactions and allowed the interactions to be assigned to a specific set of cell populations. We call this method ANCEA, or active node constrained epistasis analysis, and think that it will be generally useful in discovering and assigning network interactions to specific populations. We discuss how ANCEA, coupled with population partitioning analysis, can greatly facilitate the systematic dissection of transcriptional networks that underlie mammalian patterning.

摘要

背景

序列特异性转录因子的遗传调控网络是多细胞生物模式形成的基础。解读和描绘哺乳动物的网络是发育、神经生物学和再生医学中的核心问题。转录网络在脊椎动物神经管的模式形成过程中指定相互交织的胚胎细胞群。每个胚胎细胞群都会产生一种独特类型的成体神经元。同源结构域转录因子Lbx1在五个这样的细胞群中表达,Lbx1的缺失会导致这五个细胞群中的每一个出现不同的重新指定。

方法/主要发现:我们分别从携带一个或两个无效Lbx1(GFP)等位基因拷贝的胚胎中纯化了这五个细胞群的正常和重新指定的细胞池。微阵列用于显示在重新指定的细胞池中,所有转录因子基因的8%的表达水平发生了改变。这些转录因子基因构成了控制神经管模式形成的转录网络活性节点的20 - 30%。141个受调控节点中的一半位于超保守非编码区的前150个簇中。一般来说,Lbx1抑制在Lbx1表达域外具有表达模式的基因,并激活在Lbx1表达域内具有表达模式的基因。

结论/意义:将Lbx1的上位性分析限制在通常表达Lbx1的那些细胞上,使得在识别Lbx1网络相互作用时具有前所未有的灵敏度,并允许将这些相互作用分配到特定的一组细胞群中。我们将这种方法称为ANCEA,即活性节点受限上位性分析,并认为它在发现网络相互作用并将其分配到特定群体中通常会很有用。我们讨论了ANCEA与群体划分分析相结合如何能够极大地促进对哺乳动物模式形成基础的转录网络的系统剖析。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/788a/2527684/fa22f22b80b9/pone.0002179.g001.jpg

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