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Genome Assembly Techniques: Comparison
Please note this is a comparison between Version 2 by Yu Peng and Version 1 by Yu Peng.

Genome assembly techniques comprise the algorithmic and computational protocols by which a genome sequence is reconstructed de novo from a set of sequencing reads, without reliance on a pre-existing reference sequence [1]. The defining operational feature is the inference of the original linear or haplotype-resolved chromosome sequence from short, overlapping or non-overlapping fragments, a problem whose solution requires resolving repeats, distinguishing allelic variants from paralogous sequences, and ordering and orienting contigs into chromosome-scale scaffolds [2]. The methodological space is conventionally organized by the graph paradigm employed for reconstruction: short-read assembly predominantly uses the de Bruijn graph, in which reads are decomposed into fixed-length k-mers and the genome is traversed as a path through a compact graph whose edges represent (k−1)-overlaps, whereas long-read assembly employs overlap–layout–consensus (OLC) approaches that exploit the greater span of individual reads to bridge repetitive regions that are unresolvable with short fragments [2][3]. Contemporary chromosome-scale assembly integrates multiple data types: long accurate reads (for example, PacBio HiFi) provide high per-base accuracy across multi-kilobase spans, ultralong reads (for example, Oxford Nanopore Technologies) traverse large repetitive blocks, and proximity-ligation or Hi-C data supply long-range linkage information for phasing haplotypes and scaffolding contigs into telomere-to-telomere (T2T) chromosome arms [4]. The term further encompasses assembly paradigms for non-clonal or mixed samples, including single-cell amplified genome assembly, in which the genome of an individual uncultivated cell is reconstructed from whole-genome amplification products, and metagenome assembly, in which reads from a microbial community are partitioned and assembled into metagenome-assembled genomes (MAGs) [5]. Across these settings, the output of a genome assembly technique is a set of contigs or scaffolds accompanied by quantitative metrics of continuity and completeness that describe the extent to which the reconstructed sequence recovers the underlying chromosome architecture [1].

  • genome assembly
  • sequencing reads
  • sequence overlap
  • consensus sequence

Genome Rearrangement Algorithms·Genetics·Biochemistry, Genetics and Molecular Biology·Life Sciences

References

  1. Heng Li; Richard Durbin; Genome assembly in the telomere-to-telomere era. Nat. Rev. Genet. 2024, 25, 658-670. [CrossRef]
  2. Medhat Mahmoud; Daniel P. Agustinho; Fritz J. Sedlazeck; A Hitchhiker's Guide to long-read genomic analysis. Genome Res. 2025, 35, 545-558. [CrossRef]
  3. Phillip E C Compeau; Pavel A Pevzner; Glenn Tesler; How to apply de Bruijn graphs to genome assembly. Nat. Biotechnol. 2011, 29, 987-991. [CrossRef]
  4. Dmitry Antipov; Mikko Rautiainen; Sergey Nurk; Brian P. Walenz; Steven J. Solar; Adam M. Phillippy; Sergey Koren; Verkko2 integrates proximity-ligation data with long-read De Bruijn graphs for efficient telomere-to-telomere genome assembly, phasing, and scaffolding. Genome Res. 2025, 35, 1583-1594. [CrossRef]
  5. Daniel P. Agustinho; Yilei Fu; Vipin K. Menon; Ginger A. Metcalf; Todd J. Treangen; Fritz J. Sedlazeck; Unveiling microbial diversity: harnessing long-read sequencing technology. Nat. Methods 2024, 21, 954-966. [CrossRef]
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