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An artificial chromosome for data storage

National Science Review 2021年第5期8卷 67-75页

作者： Weigang Chen Mingzhe Han Jianting Zhou Qi Ge Panpan Wang Xinchen Zhang Siyu Zhu Lifu Song Yingjin Yuan School of Microelectronics Tianjin University Frontier Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering(Ministry of Education) Tianjin University Syn Bio Research Platform Collaborative Innovation Center of Chemical Science and Engineering (Tianjin)School of Chemical Engineering and TechnologyTianjin University

DNA digital storage provides an alternative for information storage with high density and long-term ***, we report the de novo design and synthesis of an artificial chromosome that encodes two pictures and a video clip. The encoding paradigm utilizing the superposition of sparsified error correction codewords and pseudo-random sequences tolerates base insertions/deletions and is well suited to error-prone nanopore sequencing for data retrieval. The entire 254 kb sequence was 95.27% occupied by encoded *** Transformation-Associated Recombination method was used in the construction of this chromosome from DNA fragments and necessary autonomous replication sequences. The stability was demonstrated by transmitting the data-carrying chromosome to the 100 th generation. This study demonstrates a data storage method using encoded artificial chromosomes via in vivo assembly for write-once and stable replication for multiple retrievals, similar to a compact disc, with potential in economically massive data distribution.

关键词： DNA storage synthetic biology indel correction encoded DNA artificial chromosome

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Nannochloropsis artificial chromosomes(Nanno ACs)loom on the horizon

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Journal of Oceanology and Limnology 2023年第6期41卷 2336-2347页

作者： Li GUO Guanpin YANG College of Marine Life Sciences Ocean University of ChinaQingdao 266003China Institute of Evolution and Marine Biodiversity Ocean University of ChinaQingdao 266003China Key Laboratory of Marine Genetics and Breeding of Ministry of Education Ocean University of ChinaQingdao 266003China

Species in genus Nannochloropsis,especially *** and ***,have been evolving as the model microalgae for both application and theory *** position effect of genome integration,the carrying capability limitation of integrative vectors and the instability of non-integrative vectors have hindered Nannochloropsis genetic modification with concatenate genes and extremely long DNA *** molecular tools including genetic transformation,homologous recombination,gene edition,gene stacking and episome vectors for transient gene expression and diverse reporters and selection markers have been rapidly developing in Nannochloropsis *** construction of animal and plant artificial chromosomes with“top down”strategy has set fine examples for the construction of Nannochloropsis artificial chromosomes(NannoACs).It seems that the methods and materials to set the foundation for constructing NannoACs are at *** this review,we outlined the current status of transgenes in Nannochloropsis species,summarized the limitations of both integrative and non-integrative vectors,and proposed a tentative approach to construct NannoACs by doubling and stabilizing the genome first,and then truncating the natural *** once constructed will facilitate transferring the desired traits and concatenate genes into Nannochloropsis genetic backgrounds,thus contributing towards its genetic improvement and synthetic biological studies.

关键词： Nannochloropsis artificial chromosome microalgal genetic improvement gene stacking concatenate gene trait transfer

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A Puzzle-Based Genetic Algorithm with Block Mining and Recombination Heuristic for the Traveling Salesman Problem

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Journal of Computer Science & Technology 2012年第5期27卷 937-949页

作者：张百栈黄伟修张真真 Department of Information Management Yuan Ze UniversityTaoyuan 32026TaiwanChina Department of Computer Science Xiamen UniversityXiamen 361005China

In this research, we introduce a new heuristic approach using the concept of ant colony optimization （ACO） to extract patterns from the chromosomes generated by previous generations for solving the generalized traveling salesman problem. The proposed heuristic is composed of two phases. In the first phase the ACO technique is adopted to establish an archive consisting of a set of non-overlapping blocks and of a set of remaining cities （nodes） to be visited. The second phase is a block recombination phase where the set of blocks and the rest of cities are combined to form an artificial chromosome. The generated artificial chromosomes （ACs） will then be injected into a standard genetic algorithm （SGA） to speed up the convergence. The proposed method is called ＂Puzzle-Based Genetic Algorithm＂ or ＂p-ACGA＂. We demonstrate that p-ACGA performs very well on all TSPLIB problems, which have been solved to optimality by other researchers. The proposed approach can prevent the early convergence of the genetic algorithm （GA） and lead the algorithm to explore and exploit the search space by taking advantage of the artificial chromosomes.

关键词： artificial chromosome blocks mining block recombination traveling salesman problem

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Machine learning-aided scoring of synthesis difficulties for designer chromosomes

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Science China(Life Sciences) 2023年第7期66卷 1615-1625页

作者： Yan Zheng Kai Song Ze-Xiong Xie Ming-Zhe Han Fei Guo Ying-Jin Yuan Frontiers Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering Ministry of EducationTianjin UniversityTianjin300072China School of Chemical Engineering and Technology Tianjin UniversityTianjin300072China School of Computer Science and Engineering Central South UniversityChangsha410083China

Designer chromosomes are artificially synthesized ***,these chromosomes have numerous applications ranging from medical research to the development of ***,some chromosome fragments can interfere with the chemical synthesis of designer chromosomes and eventually limit the widespread use of this *** address this issue,this study aimed to develop an interpretable machine learning framework to predict and quantify the synthesis difficulties of designer chromosomes in *** the use of this framework,six key sequence features leading to synthesis difficulties were identified,and an e Xtreme Gradient Boosting model was established to integrate these *** predictive model achieved high-quality performance with an AUC of 0.895 in cross-validation and an AUC of 0.885 on an independent test *** on these results,the synthesis difficulty index(S-index)was proposed as a means of scoring and interpreting synthesis difficulties of chromosomes from prokaryotes to *** findings of this study emphasize the significant variability in synthesis difficulties between chromosomes and demonstrate the potential of the proposed model to predict and mitigate these difficulties through the optimization of the synthesis process and genome rewriting.

关键词： synthetic biology machine learning artificial chromosome chemical synthesis

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