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Building Synthetic Chromosomes from Natural DNA
Corresponding Author(s) : D. Sindhu
International Journal of Allied Medical Sciences and Clinical Research,
Vol. 14 No. 1 (2026): 2026 Volume -14 - Issue 1
Abstract
De novo chromosome synthesis is costly and time-consuming, limiting its use in research and biotechnology. Building synthetic chromosomes from natural components is an unexplored alternative with many potential applications. In this paper, we report CReATiNG (Cloning, Reprogramming, and Assembling Tiled Natural Genomic DNA), a method for constructing synthetic chromosomes from natural components in yeast. CReATiNG entails cloning segments of natural chromosomes and then programmably assembling them into synthetic chromosomes that can replace the native chromosomes in cells. We used CReATiNG to synthetically recombine chromosomes between strains and species, to modify chromosome structure, and to delete many linked, non-adjacent regions totaling 39% of a chromosome. The multiplex deletion experiment revealed that CReATiNG also enables recovery from flaws in synthetic chromosome design via recombination between a synthetic chromosome and its native counterpart. CReATiNG facilitates the application of chromosome synthesis to diverse biological problems.
Aim: To investigate the opinions on building synthetic chromosomes from natural dna.
Objective: To investigate the opinions for understanding genetic function, basic research, biotechnological applications and potential therapeutic applications among the undergraduate dental students based on the gender
To investigate the opinions for understanding genetic function, basic research, biotechnological applications and potential therapeutic applications among the undergraduate dental students based on the year of study
Method: A cross-sectional survey was conducted among 200 dental students, comprising 97 males (48.5%) and 103 females (51.5%). The survey included 15 questions about building synthetic chromosomes from natural dna among undergraduate dental students were analyzed based on gender, age and year of study using chi-square tests to identify statistically significant differences.
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