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Anchorage Accurately Assembles Anchor-Flanked Synthetic Long Reads

Authors Xiaofei Carl Zang, Xiang Li, Kyle Metcalfe, Tuval Ben-Yehezkel, Ryan Kelley, Mingfu Shao

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Author Details

Xiaofei Carl Zang
  • Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA, USA
Xiang Li
  • Department of Computer Science and Engineering, The Pennsylvania State University, University Park, PA, USA
Kyle Metcalfe
  • Element Biosciences, San Diego, CA, USA
Tuval Ben-Yehezkel
  • Element Biosciences, San Diego, CA, USA
Ryan Kelley
  • Element Biosciences, San Diego, CA, USA
Mingfu Shao
  • Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA, USA
  • Department of Computer Science and Engineering, The Pennsylvania State University, University Park, PA, USA

Funding

This work is supported by the US National Science Foundation (2019797 and 2145171 to M.S.) and by the US National Institutes of Health (R01HG011065 to M.S.).

Acknowledgements

We thank Qimin Zhang and Qian Shi for constructive discussions and suggestions on this work.

Cite AsGet BibTex

Xiaofei Carl Zang, Xiang Li, Kyle Metcalfe, Tuval Ben-Yehezkel, Ryan Kelley, and Mingfu Shao. Anchorage Accurately Assembles Anchor-Flanked Synthetic Long Reads. In 24th International Workshop on Algorithms in Bioinformatics (WABI 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 312, pp. 22:1-22:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)
https://doi.org/10.4230/LIPIcs.WABI.2024.22

Abstract

Modern sequencing technologies allow for the addition of short-sequence tags, known as anchors, to both ends of a captured molecule. Anchors are useful in assembling the full-length sequence of a captured molecule as they can be used to accurately determine the endpoints. One representative of such anchor-enabled technology is LoopSeq Solo, a synthetic long read (SLR) sequencing protocol. LoopSeq Solo also achieves ultra-high sequencing depth and high purity of short reads covering the entire captured molecule. Despite the availability of many assembly methods, constructing full-length sequence from these anchor-enabled, ultra-high coverage sequencing data remains challenging due to the complexity of the underlying assembly graphs and the lack of specific algorithms leveraging anchors. We present Anchorage, a novel assembler that performs anchor-guided assembly for ultra-high-depth sequencing data. Anchorage starts with a kmer-based approach for precise estimation of molecule lengths. It then formulates the assembly problem as finding an optimal path that connects the two nodes determined by anchors in the underlying compact de Bruijn graph. The optimality is defined as maximizing the weight of the smallest node while matching the estimated sequence length. Anchorage uses a modified dynamic programming algorithm to efficiently find the optimal path. Through both simulations and real data, we show that Anchorage outperforms existing assembly methods, particularly in the presence of sequencing artifacts. Anchorage fills the gap in assembling anchor-enabled data. We anticipate its broad use as anchor-enabled sequencing technologies become prevalent. Anchorage is freely available at https://github.com/Shao-Group/anchorage; the scripts and documents that can reproduce all experiments in this manuscript are available at https://github.com/Shao-Group/anchorage-test.

Subject Classification

ACM Subject Classification
  • Applied computing → Molecular sequence analysis
Keywords
  • Genome assembly
  • de Bruijn graph
  • synthetic long reads
  • anchor-guided assembly
  • LoopSeq

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References

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