Cis regulatory module discovery in immune cell development

Q2 Medicine
S. R. Ganakammal, M. Kaplan, N. Perumal
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引用次数: 0

Abstract

Transcriptional regulatory mechanisms are mediated by a set of transcription factors (TFs), which bind to a specific region (motifs or transcription factor binding sites, TFBS), on the target gene(s) leading to gene expression. Eukaryotic regulatory motifs, referred to as cis regulatory modules (CRMs), tend to co-occur near the regulated gene's transcription start site and provide the building blocks to transcriptional regulatory networks that model the relevant TF-TFBS interactions. Here, we study IL-12 stimulated transcriptional regulators in STAT4 mediated T helper 1 (Th1) cell development by focusing on the identification of TFBS and CRMs using a set of Stat4 ChIP-on-chip target genes. A region containing 2000 bases of Mus musculus sequences with the Stat4 binding site, derived from the ChIP-on-chip data, has been characterized for enrichment of other motifs and, thus CRMs. We find two such motifs, (NF-κB and PPARγ/RXR) being enriched in the Stat4 binding sequences compared to neighboring background sequences and sets of random sequences of equal size. Furthermore, these predicted CRMs were observed to be associated with biologically relevant target genes in the ChIP-on-chip data set by meaningful gene ontology annotations. These analyses will lead to a better understanding of transcriptional regulatory networks in IL-12 stimulated Stat4 mediated Th1 cell differentiation.
免疫细胞发育中Cis调控模块的发现
转录调控机制是由一组转录因子(TFs)介导的,这些转录因子结合到靶基因上的特定区域(基序或转录因子结合位点,TFBS),导致基因表达。真核生物调控基序,被称为顺式调控模块(CRMs),倾向于在被调控基因的转录起始位点附近共同发生,并为模拟相关TF-TFBS相互作用的转录调控网络提供构建块。在这里,我们通过使用一组STAT4 ChIP-on-chip靶基因鉴定TFBS和CRMs,研究IL-12刺激的转录调控因子在STAT4介导的T辅助1 (Th1)细胞发育中的作用。一个包含2000个碱基的小家鼠Stat4结合位点的区域,从ChIP-on-chip数据中得到,已经被表征为其他基序的富集,因此是CRMs。我们发现两个这样的基序(NF-κB和PPARγ/RXR)在Stat4结合序列中比邻近的背景序列和相同大小的随机序列更丰富。此外,通过有意义的基因本体注释,观察到这些预测的crm与ChIP-on-chip数据集中的生物学相关靶基因相关。这些分析将有助于更好地理解IL-12刺激的Stat4介导的Th1细胞分化的转录调控网络。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
In Silico Biology
In Silico Biology Computer Science-Computational Theory and Mathematics
CiteScore
2.20
自引率
0.00%
发文量
1
期刊介绍: The considerable "algorithmic complexity" of biological systems requires a huge amount of detailed information for their complete description. Although far from being complete, the overwhelming quantity of small pieces of information gathered for all kind of biological systems at the molecular and cellular level requires computational tools to be adequately stored and interpreted. Interpretation of data means to abstract them as much as allowed to provide a systematic, an integrative view of biology. Most of the presently available scientific journals focus either on accumulating more data from elaborate experimental approaches, or on presenting new algorithms for the interpretation of these data. Both approaches are meritorious.
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