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Meta Gene Regulatory Networks in Maize Highlight Functionally Relevant Regulatory Interactions
The Plant Cell ( IF 11.6 ) Pub Date : 2020-03-17
Zhou, P., Li, Z., Magnusson, E., Cano, F. A. G., Crisp, P. A., Noshay, J., Grotewold, E., Hirsch, C., Briggs, S. P., Springer, N. M.

Regulation of gene expression is central to many biological processes. Gene regulatory networks (GRNs) link transcription factors (TFs) to their target genes and represent a map of potential transcriptional regulation. A consistent analysis of a large number of public maize transcriptome datasets including >6000 RNA-Seq samples was used to generate 45 co-expression based GRNs that represent potential regulatory relationships between TFs and other genes in different populations of samples (cross-tissue, cross-genotype, tissue-and-genotype, etc). While these networks are all enriched for biologically relevant interactions, different networks capture distinct TF-target associations and biological processes. By examining the power of our co-expression based GRNs to accurately predict co-varying TF-target relationships in natural variation datasets we found that presence/absence expression changes - rather than quantitative changes - of a TF, are more likely to associate with target gene changes. Integrating information from our TF-target predictions and previous eQTL mapping results provided support for 68 TFs underlying 74 previously identified trans-eQTL hotspots spanning span a variety of metabolic pathways. This study highlights the utility of developing multiple GRNs within a species for detecting putative regulators of important plant pathways and providing potential targets for breeding or biotechnology applications.



中文翻译:

玉米中的元基因调控网络突出了功能相关的调控相互作用

基因表达的调节是许多生物学过程的核心。基因调控网络(GRN)将转录因子(TFs)链接到其靶基因,并代表潜在的转录调控图谱。对大量公共玉米转录组数据集(包括> 6000 RNA-Seq样本)进行的一致分析,用于生成45种基于共表达的GRN,这些GRN表示不同样本群体中TF与其他基因之间的潜在调控关系(跨组织,交叉基因型,组织基因型等)。虽然这些网络都丰富了生物学相关的相互作用,但不同的网络却捕获了不同的TF-靶标关联和生物学过程。通过检查我们基于共表达的GRN在自然变异数据集中准确预测共变TF-靶标关系的能力,我们发现TF的存在/不存在表达变化(而非定量变化)更可能与靶标相关基因改变。整合来自我们TF目标预测和先前eQTL定位结果的信息,为支持68个TF提供了支持,这些TF是74个先前确定的跨eQTL热点的基础,跨越了多种代谢途径。这项研究强调了在一个物种内开发多种GRN的实用性,以检测重要植物途径的假定调控因子,并为育种或生物技术应用提供潜在的靶标。更可能与靶基因改变有关。整合来自我们TF目标预测和先前eQTL定位结果的信息,为支持68个TF提供了支持,这些TF是74个先前确定的跨eQTL热点的基础,跨越了多种代谢途径。这项研究强调了在一个物种内开发多种GRN的实用性,以检测重要植物途径的假定调控因子,并为育种或生物技术应用提供潜在的靶标。更可能与靶基因改变有关。整合来自我们TF目标预测和先前eQTL定位结果的信息,为支持68个TF提供了支持,这些TF是74个先前确定的跨eQTL热点的基础,跨越了多种代谢途径。这项研究强调了在一个物种内开发多种GRN的实用性,以检测重要植物途径的假定调控因子,并为育种或生物技术应用提供潜在的靶标。

更新日期:2020-04-21
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