高度精确的序列和位置无关的DNA合成和测序错误分析。

IF 3.9 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Huiran Yeom*, Namphil Kim, Amos Chungwon Lee, Jinhyun Kim, Hamin Kim, Hansol Choi, Seo Woo Song, Sunghoon Kwon and Yeongjae Choi*, 
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引用次数: 0

摘要

在DNA合成和测序等过程中,对DNA存储数据进行全面的误差分析对于可靠的DNA数据存储至关重要。合成和测序错误都取决于核苷酸的序列和碱基的转移;忽略任何一个错误源都会导致最小化错误率的技术挑战。在这里,我们提出了一种方法和工具包,利用由10个碱基移位序列阵列生成的寡核苷酸文库,该文库被单独标记为独特的分子标识符,同时描述和描述DNA合成和测序错误。这种方法使DNA合成和测序的位置和序列无关的错误分析成为可能。使用该工具包,我们报告了一般DNA数据存储以及退化碱基增强DNA数据存储中合成和测序中的碱基过渡错误。所提出的方法和数据将有助于以最小的错误开发DNA序列设计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Highly Accurate Sequence- and Position-Independent Error Profiling of DNA Synthesis and Sequencing

Highly Accurate Sequence- and Position-Independent Error Profiling of DNA Synthesis and Sequencing

Highly Accurate Sequence- and Position-Independent Error Profiling of DNA Synthesis and Sequencing

A comprehensive error analysis of DNA-stored data during processing, such as DNA synthesis and sequencing, is crucial for reliable DNA data storage. Both synthesis and sequencing errors depend on the sequence and the transition of bases of nucleotides; ignoring either one of the error sources leads to technical challenges in minimizing the error rate. Here, we present a methodology and toolkit that utilizes an oligonucleotide library generated from a 10-base-shifted sequence array, which is individually labeled with unique molecular identifiers, to delineate and profile DNA synthesis and sequencing errors simultaneously. This methodology enables position- and sequence-independent error profiling of both DNA synthesis and sequencing. Using this toolkit, we report base transitional errors in both synthesis and sequencing in general DNA data storage as well as degenerate-base-augmented DNA data storage. The methodology and data presented will contribute to the development of DNA sequence designs with minimal error.

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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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