拟南芥和旱生植物组织特异性调控子的推断和优先排序

IF 4.6 4区 农林科学 Q1 BIOTECHNOLOGY & APPLIED MICROBIOLOGY aBIOTECH Pub Date : 2024-07-16 DOI:10.1007/s42994-024-00176-2
Honggang Dai, Yaxin Fan, Yichao Mei, Ling-Ling Chen, Junxiang Gao
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引用次数: 0

摘要

调控子是指通过转录因子与调控基序结合来实现特定生物功能的一组基因。为了推断拟南芥组织特异性基因调控子,我们开发了一个名为 InferReg 的新管道。 InferReg 利用包含 3400 个拟南芥转录组的基因表达矩阵,通过共表达模式初步预测转录因子(TF)和靶基因(TG)之间的调控关系。通过整合 TF 结合位点富集分析,它进一步改进了这些预期的相互作用,以消除仅由表达数据支持的假阳性。InferReg 还以 ChIP-seq 支持的 133 个转录因子为阳性样本,进一步训练图卷积网络,以学习 TF 与 TG 之间的调控逻辑,从而提高调控网络的准确性。为了评估 InferReg 的功能,我们利用它发现了拟南芥 5 个组织(花、叶、根、种子和幼苗)中的组织特异性调控子。我们使用博尔达排序法根据可靠性对每个组织的调控子的活性进行了排序,并与现有数据库进行了比较。结果表明,InferReg 不仅能识别已知的组织特异性调控子,还能发现新的组织特异性调控子。通过将 InferReg 应用于水稻表达数据,我们能够识别水稻组织特异性调控子,这表明我们的方法可以更广泛地应用。我们利用 InferReg 成功鉴定了拟南芥和芸苔属植物不同组织中的重要调控子,从而加深了我们对组织特异性调控以及调控子在组织分化和发育中的作用的理解。
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Inference and prioritization of tissue-specific regulons in Arabidopsis and Oryza

A regulon refers to a group of genes regulated by a transcription factor binding to regulatory motifs to achieve specific biological functions. To infer tissue-specific gene regulons in Arabidopsis, we developed a novel pipeline named InferReg. InferReg utilizes a gene expression matrix that includes 3400 Arabidopsis transcriptomes to make initial predictions about the regulatory relationships between transcription factors (TFs) and target genes (TGs) using co-expression patterns. It further improves these anticipated interactions by integrating TF binding site enrichment analysis to eliminate false positives that are only supported by expression data. InferReg further trained a graph convolutional network with 133 transcription factors, supported by ChIP-seq, as positive samples, to learn the regulatory logic between TFs and TGs to improve the accuracy of the regulatory network. To evaluate the functionality of InferReg, we utilized it to discover tissue-specific regulons in 5 Arabidopsis tissues: flower, leaf, root, seed, and seedling. We ranked the activities of regulons for each tissue based on reliability using Borda ranking and compared them with existing databases. The results demonstrated that InferReg not only identified known tissue-specific regulons but also discovered new ones. By applying InferReg to rice expression data, we were able to identify rice tissue-specific regulons, showing that our approach can be applied more broadly. We used InferReg to successfully identify important regulons in various tissues of Arabidopsis and Oryza, which has improved our understanding of tissue-specific regulations and the roles of regulons in tissue differentiation and development.

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来源期刊
CiteScore
7.70
自引率
2.80%
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