Sequencing Strategy to Ensure Accurate Plasmid Assembly.

IF 3.7 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
ACS Synthetic Biology Pub Date : 2024-12-20 Epub Date: 2024-11-07 DOI:10.1021/acssynbio.4c00539
Sarah I Hernandez, Casey-Tyler Berezin, Katie M Miller, Samuel J Peccoud, Jean Peccoud
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引用次数: 0

Abstract

Despite the wide use of plasmids in research and clinical production, the need to verify plasmid sequences is a bottleneck that is too often underestimated in the manufacturing process. Although sequencing platforms continue to improve, the method and assembly pipeline chosen still influence the final plasmid assembly sequence. Furthermore, few dedicated tools exist for plasmid assembly, especially for de novo assembly. Here, we evaluated short-read, long-read, and hybrid (both short and long reads) de novo assembly pipelines across three replicates of a 24-plasmid library. Consistent with previous characterizations of each sequencing technology, short-read assemblies had issues resolving GC-rich regions, and long-read assemblies commonly had small insertions and deletions, especially in repetitive regions. The hybrid approach facilitated the most accurate, consistent assembly generation and identified mutations relative to the reference sequence. Although Sanger sequencing can be used to verify specific regions, some GC-rich and repetitive regions were difficult to resolve using any method, suggesting that easily sequenced genetic parts should be prioritized in the design of new genetic constructs.

确保质粒组装准确的测序策略
尽管质粒在研究和临床生产中得到了广泛应用,但在生产过程中,验证质粒序列的需求是一个瓶颈,而这个瓶颈往往被低估。尽管测序平台在不断改进,但所选择的方法和组装流水线仍会影响质粒的最终组装序列。此外,用于质粒组装的专用工具很少,尤其是用于从头组装的工具。在这里,我们评估了短读数、长读数和混合(既有短读数又有长读数)从头组装流水线在 24 个质粒文库的三个重复品中的应用。与之前对每种测序技术的特征描述一致,短读数组装在解决富含 GC 的区域方面存在问题,而长读数组装通常存在小的插入和缺失,尤其是在重复区域。混合方法有助于生成最准确、最一致的组装结果,并识别出相对于参考序列的突变。虽然桑格测序可用于验证特定区域,但一些富含 GC 的区域和重复区域难以用任何方法解决,这表明在设计新的基因构建体时,应优先考虑容易测序的基因部分。
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来源期刊
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.
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