MultiCRISPR-EGA: Optimizing Guide RNA Array Design for Multiplexed CRISPR Using the Elitist Genetic Algorithm.

IF 3.7 2区生物学 Q1 BIOCHEMICAL RESEARCH METHODS

ACS Synthetic Biology Pub Date : 2025-03-21 Epub Date: 2025-02-20 DOI:10.1021/acssynbio.4c00860

Yangyu Zhang, Guanlin Chen, Ce Liang, Bin Yang, Xin Lei, Tao Chen, Huaiguang Jiang, Wei Xiong

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引用次数: 0

Abstract

Multiplexed CRISPR design, which allows for the concurrent and efficient editing of multiple genomic sites, is a powerful tool for complex genetic modifications. However, designing effective multiplexed guide RNA (gRNA) arrays remains challenging due to the exponential increase in potential gRNA array candidates and the significant impact of different target site selections on efficiency and specificity. Recognizing that more stable gRNAs, characterized by lower minimum free energy (MFE), have prolonged activity and thus higher efficacy, we developed MultiCRISPR-EGA, a graphical user interface (GUI)-based tool that employs the Elitist Genetic Algorithm (EGA) to design optimized single-promoter-driven multiplexed gRNA arrays. Computational experiments on Escherichia coli gene targets demonstrate that the EGA can rapidly optimize multiplexed gRNA arrays, outperforming other intelligent optimization algorithms in CRISPR interference (CRISPRi) applications, while the GUI provides real-time design progress control and compatibility with various CRISPR-Cas systems. This tool aims to advance the multiplexed gRNA array design process, enabling more efficient and cost-effective genome editing for synthetic biology.

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多路CRISPR- ega：使用精英遗传算法优化多路CRISPR引导RNA阵列设计。

多路CRISPR设计允许同时有效地编辑多个基因组位点，是复杂遗传修饰的强大工具。然而，设计有效的多路向导RNA （gRNA）阵列仍然具有挑战性，因为潜在的gRNA阵列候选物呈指数级增长，不同的靶点选择对效率和特异性有显著影响。认识到更稳定的gRNA，以更低的最小自由能（MFE）为特征，具有更长的活性，从而具有更高的功效，我们开发了MultiCRISPR-EGA，这是一个基于图形用户界面（GUI）的工具，采用精英遗传算法（EGA）来设计优化的单启动子驱动的多路gRNA阵列。大肠杆菌基因靶点的计算实验表明，EGA可以快速优化多路gRNA阵列，在CRISPR干扰（CRISPRi）应用中优于其他智能优化算法，而GUI提供实时设计进度控制并与各种CRISPR- cas系统兼容。该工具旨在推进多路gRNA阵列设计过程，使合成生物学的基因组编辑更有效和更具成本效益。

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

ACS Synthetic Biology 生物-

CiteScore

8.00

自引率

10.60%

发文量

380

审稿时长

6-12 weeks

期刊介绍： The journal is particularly interested in studies on the design and synthesis of new genetic circuits and gene products; computational methods in the design of systems; and integrative applied approaches to understanding disease and metabolism. Topics may include, but are not limited to: Design and optimization of genetic systems Genetic circuit design and their principles for their organization into programs Computational methods to aid the design of genetic systems Experimental methods to quantify genetic parts, circuits, and metabolic fluxes Genetic parts libraries: their creation, analysis, and ontological representation Protein engineering including computational design Metabolic engineering and cellular manufacturing, including biomass conversion Natural product access, engineering, and production Creative and innovative applications of cellular programming Medical applications, tissue engineering, and the programming of therapeutic cells Minimal cell design and construction Genomics and genome replacement strategies Viral engineering Automated and robotic assembly platforms for synthetic biology DNA synthesis methodologies Metagenomics and synthetic metagenomic analysis Bioinformatics applied to gene discovery, chemoinformatics, and pathway construction Gene optimization Methods for genome-scale measurements of transcription and metabolomics Systems biology and methods to integrate multiple data sources in vitro and cell-free synthetic biology and molecular programming Nucleic acid engineering.