Benchmarking of next and third generation sequencing technologies and their associated algorithms for de novo genome assembly
- Marios Gavrielatos
- Konstantinos Kyriakidis
- Demetrios A. Spandidos
- Ioannis Michalopoulos
Affiliations: Centre of Systems Biology, Biomedical Research Foundation, Academy of Athens, 11527 Athens, Greece, School of Pharmacy, Aristotle University of Thessaloniki (AUTh), 54124 Thessaloniki, Greece, Laboratory of Clinical Virology, Medical School, University of Crete, 71003 Heraklion, Greece
- Published online on: February 2, 2021 https://doi.org/10.3892/mmr.2021.11890
Copyright: © Gavrielatos
et al. This is an open access article distributed under the
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Genome assemblers are computational tools for de novo genome assembly, based on a plenitude of primary sequencing data. The quality of genome assemblies is estimated by their contiguity and the occurrences of misassemblies (duplications, deletions, translocations or inversions). The rapid development of sequencing technologies has enabled the rise of novel de novo genome assembly strategies. The ultimate goal of such strategies is to utilise the features of each sequencing platform in order to address the existing weaknesses of each sequencing type and compose a complete and correct genome map. In the present study, the hybrid strategy, which is based on Illumina short paired‑end reads and Nanopore long reads, was benchmarked using MaSuRCA and Wengan assemblers. Moreover, the long‑read assembly strategy, which is based on Nanopore reads, was benchmarked using Canu or PacBio HiFi reads were benchmarked using Hifiasm and HiCanu. The assemblies were performed on a computational cluster with limited computational resources. Their outputs were evaluated in terms of accuracy and computational performance. PacBio HiFi assembly strategy outperforms the other ones, while Hi‑C scaffolding, which is based on chromatin 3D structure, is required in order to increase continuity, accuracy and completeness when large and complex genomes, such as the human one, are assembled. The use of Hi‑C data is also necessary while using the hybrid assembly strategy. The results revealed that HiFi sequencing enabled the rise of novel algorithms which require less genome coverage than that of the other strategies making the assembly a less computationally demanding task. Taken together, these developments may lead to the democratisation of genome assembly projects which are now approachable by smaller labs with limited technical and financial resources.