TF-High-Evolutionary: In Vivo Mutagenesis of Gene Regulatory Networks for the Study of the Genetics and Evolution of the Drosophila Regulatory Genome.

IF 11 1区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY
Xueying C Li, Vani Srinivasan, Ian Laiker, Natalia Misunou, Nicolás Frankel, Luisa F Pallares, Justin Crocker
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引用次数: 0

Abstract

Understanding the evolutionary potential of mutations in gene regulatory networks is essential to furthering the study of evolution and development. However, in multicellular systems, genetic manipulation of regulatory networks in a targeted and high-throughput way remains challenging. In this study, we designed TF-High-Evolutionary (HighEvo), a transcription factor (TF) fused with a base editor (activation-induced deaminase), to continuously induce germline mutations at TF-binding sites across regulatory networks in Drosophila. Populations of flies expressing TF-HighEvo in their germlines accumulated mutations at rates an order of magnitude higher than natural populations. Importantly, these mutations accumulated around the targeted TF-binding sites across the genome, leading to distinct morphological phenotypes consistent with the developmental roles of the tagged TFs. As such, this TF-HighEvo method allows the interrogation of the mutational space of gene regulatory networks at scale and can serve as a powerful reagent for experimental evolution and genetic screens focused on the regulatory genome.

TF-High-Evolutionary:基因调控网络的体内诱变,用于研究果蝇调控基因组的遗传和进化。
了解基因调控网络中突变的进化潜力对于进一步研究进化和发育至关重要。然而,在多细胞系统中,以定向和高通量的方式对调控网络进行遗传操作仍然具有挑战性。在这项研究中,我们设计了一种与碱基编辑器(活化诱导脱氨酶,AID)融合的转录因子(TF)--TF-High-Evolutionary(HighEvo),用于在果蝇的调控网络中持续诱导TF结合位点的种系突变。在种系中表达 TF-HighEvo 的果蝇种群积累突变的速度比自然种群高出一个数量级。重要的是,这些突变在整个基因组的目标 TF 结合位点周围累积,导致了与标记 TF 的发育作用相一致的不同形态表型。因此,这种TF-HighEvo方法可以大规模检测基因调控网络的突变空间,并可作为一种强大的试剂,用于以调控基因组为重点的实验进化和遗传筛选。
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
Molecular biology and evolution
Molecular biology and evolution 生物-进化生物学
CiteScore
19.70
自引率
3.70%
发文量
257
审稿时长
1 months
期刊介绍: Molecular Biology and Evolution Journal Overview: Publishes research at the interface of molecular (including genomics) and evolutionary biology Considers manuscripts containing patterns, processes, and predictions at all levels of organization: population, taxonomic, functional, and phenotypic Interested in fundamental discoveries, new and improved methods, resources, technologies, and theories advancing evolutionary research Publishes balanced reviews of recent developments in genome evolution and forward-looking perspectives suggesting future directions in molecular evolution applications.
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