College of Science

89 Assemblmore: An Assembler-Agnostic, Reference-Aware, Genome-Assembly Refinement Tool

Manitejus Kotikalapudi; Ofer Rog; and Ryan Pellow

Faculty Mentor: Ofer Rog (Biological Sciences, University of Utah)

During my time at the University of Utah’s Summer Program for Undergraduate Research (SPUR), I engaged in the bioinformatic challenge of genome assembly, specifically relating to assembly based on newly emerging ultra-long sequencing technologies. The main research question that underpinned my research was “Can assembly of a genome’s long, repetitive regions be completed with contextual information and be automated?” A positive answer to this research question will enable significant advances in the study of telomeres, ribosomal RNA, Copy Number Variation, etc. A recent preprint[1] – which improved upon the current Caenorhabditis Elegans genome – demonstrates techniques that show that the research question is answerable in a manual context. My contribution further explored the question’s feasibility in an automated context.

To this end, I built the foundations of an automated genome assembly refinement tool: Assemblmore. In its current state, Assemblmore takes as input a reference genome, raw reads from an ultra-long sequencing platform, and a draft assembly created by de novo genome assemblers such as Flye[2], Hifiasm,[3] or Canu.[4] It then scaffolds the draft assembly to the reference via minimap2[5] and uses the alignment data to output a more contiguous assembly that fixes many of the ‘small’ contiguity issues, which can often be rectified with one or two ultra-long reads that span the gaps in the assembly.[6] Further details of the core algorithm are in Supplementary Figure 1. The intended full pipeline is outlined in Figure 1. Upon the future completion of Assemblmore, most complex repetitive regions will be identified and rectified.

Assemblmore Activity Diagram with grey, green, orange, and red boxes.
Figure 1. Assemblmore Activity Diagram. Grey, green, orange, and red boxes indicate supplied input information, completed modules, in-progress modules, and incomplete modules, respectively. The grey boxes at the bottom include further details on the completed modules.

Notably, Assemblmore facilitated rapid assembly of the first telomere-to-telomere reference genome for the nematode Caenorhabditis Nigoni, an emergent model organism. The previous best assembly[7] had around 12Mb of unclassified data, representing around 148 contigs. With Hifiasm, Assemblmore, and minimal manual refinement, I created a new assembly and classified the 12Mb. This draft genome could now be a new tool for researchers in Caenorhabditis comparative genomics. Future work with Assemblmore involves finalizing the complex region rectification functionality and performing further validations and benchmarks.

Code Availability

Assemblmore is maintained at https://github.com/TejusK123/assemblmore.

Supplementary Info

High Level Pseudocode for the core algorithm in Assemblmore's second module
Supplementary Figure 1. Pseudocode for the second Assemblmore module.
  1. Ichikawa, K. et al. CGC1, a new reference genome for Caenorhabditis elegans. Preprint at https://doi.org/10.1101/2024.12.04.626850 (2024). ↵
  2. Kolmogorov, M., Yuan, J., Lin, Y. & Pevzner, P. A. Assembly of long, error-prone reads using repeat graphs. Nat Biotechnol 37, 540–546 (2019). ↵
  3. Cheng, H., Concepcion, G. T., Feng, X., Zhang, H. & Li, H. Haplotype-resolved de novo assembly using phased assembly graphs with hifiasm. Nat Methods 18, 170–175 (2021). ↵
  4. Koren, S. et al. Canu: scalable and accurate long-read assembly via adaptive k -mer weighting and repeat separation. Genome Res. 27, 722–736 (2017). ↵
  5. Li, H. Minimap2: pairwise alignment for nucleotide sequences. Bioinformatics 34, 3094–3100 (2018). ↵
  6. Kolmogorov, M., Yuan, J., Lin, Y. & Pevzner, P. A. Assembly of long, error-prone reads using repeat graphs. Nat Biotechnol 37, 540–546 (2019). ↵
  7. Yin, D. et al. Rapid genome shrinkage in a self-fertile nematode reveals sperm competition proteins. Science 359, 55–61 (2018). ↵

About the authors

name: Manitejus Kotikalapudi

name: Ofer Rog

institution: University of Utah

name: Ryan Pellow

License

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RANGE: Undergraduate Research Journal (2025) Copyright © 2025 by University of Utah is licensed under a Creative Commons Attribution 4.0 International License, except where otherwise noted.

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