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<p>The discovery of non-canonical bases (NCBs) and development of synthetic xeno-nucleic acids (XNAs) has spawned interest in many applications in viral genomics, synthetic biology and DNA storage. However, inability to do high-throughput sequencing of NCBs has been a significant limitation. We demonstrate that XNAs with NCBs can be robustly sequenced on a MinION system ( &gt; 2.3×10<sup>6</sup> reads/flowcell) to obtain significantly distinct signals from controls (median fold-change &gt;6×). To enable AI-model training, we synthesized and sequenced a complex pool of 1,024 NCB-containing oligonucleotides with varied 6-mer contexts and high purity ( &gt; 90%). Bootstrapped models assisted in data preparation, and data augmentation with spliced reads provided high context diversity, enabling learning of generalizable models to decipher NCB-containing sequences with high accuracy ( &gt; 80%) and specificity (99%). These results highlight the versatility of nanopore sequencing for interrogating unusual nucleic acids, and the potential to transform the study of genetic material beyond those that use canonical bases.</p>

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Direct high-throughput deconvolution of non-canonical bases via nanopore sequencing and bootstrapped learning

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月30日

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  • Mauricio Perez,
  • Michiko Kimoto,
  • Priscilla Rajakumar,
  • Chayaporn Suphavilai,
  • Rafael Peres da Silva,
  • Hui Pen Tan,
  • Nicholas Ting Xun Ong,
  • Hannah Nicholas,
  • Ichiro Hirao,
  • Wei Leong Chew,
  • Niranjan Nagarajan

摘要

The discovery of non-canonical bases (NCBs) and development of synthetic xeno-nucleic acids (XNAs) has spawned interest in many applications in viral genomics, synthetic biology and DNA storage. However, inability to do high-throughput sequencing of NCBs has been a significant limitation. We demonstrate that XNAs with NCBs can be robustly sequenced on a MinION system ( > 2.3×106 reads/flowcell) to obtain significantly distinct signals from controls (median fold-change >6×). To enable AI-model training, we synthesized and sequenced a complex pool of 1,024 NCB-containing oligonucleotides with varied 6-mer contexts and high purity ( > 90%). Bootstrapped models assisted in data preparation, and data augmentation with spliced reads provided high context diversity, enabling learning of generalizable models to decipher NCB-containing sequences with high accuracy ( > 80%) and specificity (99%). These results highlight the versatility of nanopore sequencing for interrogating unusual nucleic acids, and the potential to transform the study of genetic material beyond those that use canonical bases.