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CSA: A high-throughput chromosome-scale assembly pipeline for vertebrate genomes

Abstract : Background: Easy-to-use and fast bioinformatics pipelines for long-read assembly that go beyond the contig level to generate highly continuous chromosome-scale genomes from raw data remain scarce. Results: Chromosome-Scale Assembler (CSA) is a novel computationally highly efficient bioinformatics pipeline that fills this gap. CSA integrates information from scaffolded assemblies (e.g., Hi-C or 10X Genomics) or even from diverged reference genomes into the assembly process. As CSA performs automated assembly of chromosome-sized scaffolds, we benchmark its performance against state-of-the-art reference genomes, i.e., conventionally built in a laborious fashion using multiple separate assembly tools and manual curation. CSA increases the contig lengths using scaffolding, local re-assembly, and gap closing. On certain datasets, initial contig N50 may be increased up to 4.5-fold. For smaller vertebrate genomes, chromosome-scale assemblies can be achieved within 12 h using low-cost, high-end desktop computers. Mammalian genomes can be processed within 16 h on compute-servers. Using diverged reference genomes for fish, birds, and mammals, we demonstrate that CSA calculates chromosome-scale assemblies from long-read data and genome comparisons alone. Even contig-level draft assemblies of diverged genomes are helpful for reconstructing chromosome-scale sequences. CSA is also capable of assembling ultra-long reads. Conclusions: CSA can speed up and simplify chromosome-level assembly and significantly lower costs of large-scale family-level vertebrate genome projects.
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https://hal.inrae.fr/hal-03182981
Contributor : Papa Abdoulaye Sow <>
Submitted on : Friday, March 26, 2021 - 6:37:05 PM
Last modification on : Wednesday, May 12, 2021 - 8:09:20 AM

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Heiner Kuhl, Ling Li, Sven Wuertz, Matthias Stöck, Xu-Fang Liang, et al.. CSA: A high-throughput chromosome-scale assembly pipeline for vertebrate genomes. GigaScience, BioMed Central, 2020, 9 (5), ⟨10.1093/gigascience/giaa034⟩. ⟨hal-03182981⟩

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