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Logical Analysis of Multiple Single-Nucleotide-Polymorphisms with Programmable DNA Molecular Computation for Clinical Diagnostics.

Chao ZhangTingting ZhengQian MaLinlin YangMingzhi ZhangJunyan WangXiaoyan TengYanyan MiaoHsiao-Chu LinYang YangDa Han
Published in: Angewandte Chemie (International ed. in English) (2022)
Analyzing complex single-nucleotide-polymorphism (SNP) combinations in the genome is important for research and clinical applications, given that different SNP combinations can generate different phenotypic consequences. Recent works have shown that DNA-based molecular computing is powerful for simultaneously sensing and analyzing complex molecular information. Here, we designed a switching circuit-based DNA computational scheme that can integrate the sensing of multiple SNPs and simultaneously perform logical analysis of the detected SNP information to directly report clinical outcomes. As a demonstration, we successfully achieved automatic and accurate identification of 21 different blood group genotypes from 83 clinical blood samples with 100 % accuracy compared to sequencing data in a more rapid manner (3 hours). Our method enables a new mode of automatic and logical sensing and analyzing subtle molecular information for clinical diagnosis, as well as guiding personalized medication.
Keyphrases
  • single molecule
  • genome wide
  • circulating tumor
  • cell free
  • machine learning
  • healthcare
  • deep learning
  • health information
  • dna methylation
  • high resolution
  • social media
  • nucleic acid
  • circulating tumor cells
  • big data