Decoding tissue-specific enhancers in plants using massively parallel assays and deep learning.

Yaxin Deng,Weihua Zhao,Yixue Xiong,Muhammad Naeem,Shan Lu,Xuanwei Zhou,Lingxia Zhao,Lida Zhang
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Abstract

Enhancers control gene expression, orchestrating plant development and responses to stimuli. However, the regulatory codes of enhancers that confer tissue-specific expression in plants remain largely unexplored. Using massively parallel reporter assays (MPRAs) in tomato tissues, we tested the enhancer activity of 11,180 promoter fragments derived from fruit-specific genes. We discovered 2,436 active fruit enhancer sequences, a subset of which showed differential activity between fruit and leaves, suggesting that they can drive fruit-specific gene expression in tomato. We dissected the sequence determinants of fruit enhancers using deep learning. Guided by the regulatory rules learned from our MPRA dataset, we designed synthetic enhancers and experimentally validated their ability to specifically target tomato fruit. Our study provides a comprehensive landscape of functional enhancers in tomato fruit, facilitating the de novo design of synthetic enhancers for tissue-specific gene expression in plants.
使用大规模并行分析和深度学习解码植物组织特异性增强子。
增强子控制基因表达,协调植物的发育和对刺激的反应。然而,在植物中赋予组织特异性表达的增强子的调控代码在很大程度上仍未被探索。利用大规模平行报告子分析(MPRAs)技术,研究人员在番茄组织中检测了来自果实特异性基因的11180个启动子片段的增强子活性。我们发现了2436个活跃的果实增强子序列,其中一个子集在果实和叶片之间表现出不同的活性,这表明它们可以驱动番茄果实特异性基因的表达。我们使用深度学习剖析了水果增强剂的序列决定因素。根据从MPRA数据集中了解到的监管规则,我们设计了合成增强剂,并通过实验验证了它们特异性靶向番茄果实的能力。我们的研究提供了番茄果实中功能增强子的全面景观,促进了植物组织特异性基因表达合成增强子的从头设计。
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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