Tianyi Li, Hui Xu, Shouzhen Teng, Mingrui Suo, Revocatus Bahitwa, Mingchi Xu, Yiheng Qian, Guillaume P Ramstein, Baoxing Song, Edward S Buckler, Hai Wang
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引用次数: 0
摘要
在没有专家干预或先验领域知识的情况下合理设计植物顺式调控 DNA 序列仍然是一项艰巨的任务。在这里,我们开发了一种深度学习框架 PhytoExpr,它能够使用近端调控序列作为唯一输入,预测 mRNA 丰度和植物物种。PhytoExpr 在植物界主要支系的 17 个代表性物种上进行了训练,以增强其通用性。通过输入扰动,以单核苷酸分辨率实现了输入序列的定量功能注释,揭示了保守非编码序列和转录因子结合位点中大量预测的高影响核苷酸。PhytoExpr 对玉米 HapMap3 单核苷酸多态性(SNPs)的评估表明,顺式-eQTL 中富含预测的高影响 SNPs。此外,我们还提供了两种算法,利用 PhytoExpr 的强大功能设计功能性顺式调控变体,并通过随机 DNA 序列的硅进化从头创建物种特异性顺式调控序列。我们的模型为群体遗传学中功能变体的发现以及基因组编辑和合成生物学中调控序列的合理设计提供了一种通用而稳健的方法。
Modeling 0.6 million genes for the rational design of functional cis-regulatory variants and de novo design of cis-regulatory sequences.
Rational design of plant cis-regulatory DNA sequences without expert intervention or prior domain knowledge is still a daunting task. Here, we developed PhytoExpr, a deep learning framework capable of predicting both mRNA abundance and plant species using the proximal regulatory sequence as the sole input. PhytoExpr was trained over 17 species representative of major clades of the plant kingdom to enhance its generalizability. Via input perturbation, quantitative functional annotation of the input sequence was achieved at single-nucleotide resolution, revealing an abundance of predicted high-impact nucleotides in conserved noncoding sequences and transcription factor binding sites. Evaluation of maize HapMap3 single-nucleotide polymorphisms (SNPs) by PhytoExpr demonstrates an enrichment of predicted high-impact SNPs in cis-eQTL. Additionally, we provided two algorithms that harnessed the power of PhytoExpr in designing functional cis-regulatory variants, and de novo creation of species-specific cis-regulatory sequences through in silico evolution of random DNA sequences. Our model represents a general and robust approach for functional variant discovery in population genetics and rational design of regulatory sequences for genome editing and synthetic biology.
期刊介绍:
The Proceedings of the National Academy of Sciences (PNAS), a peer-reviewed journal of the National Academy of Sciences (NAS), serves as an authoritative source for high-impact, original research across the biological, physical, and social sciences. With a global scope, the journal welcomes submissions from researchers worldwide, making it an inclusive platform for advancing scientific knowledge.