Overcoming uncollapsed haplotypes in long-read assemblies of non-model organisms

Résultats de recherche: Contribution à un journal/une revueArticleRevue par des pairs

Résumé

Background: Long-read sequencing is revolutionizing genome assembly: as PacBio and Nanopore technologies become more accessible in technicity and in cost, long-read assemblers flourish and are starting to deliver chromosome-level assemblies. However, these long reads are usually error-prone, making the generation of a haploid reference out of a diploid genome a difficult enterprise. Failure to properly collapse haplotypes results in fragmented and structurally incorrect assemblies and wreaks havoc on orthology inference pipelines, yet this serious issue is rarely acknowledged and dealt with in genomic projects, and an independent, comparative benchmark of the capacity of assemblers and post-processing tools to properly collapse or purge haplotypes is still lacking. Results: We tested different assembly strategies on the genome of the rotifer Adineta vaga, a non-model organism for which high coverages of both PacBio and Nanopore reads were available. The assemblers we tested (Canu, Flye, NextDenovo, Ra, Raven, Shasta and wtdbg2) exhibited strikingly different behaviors when dealing with highly heterozygous regions, resulting in variable amounts of uncollapsed haplotypes. Filtering reads generally improved haploid assemblies, and we also benchmarked three post-processing tools aimed at detecting and purging uncollapsed haplotypes in long-read assemblies: HaploMerger2, purge_haplotigs and purge_dups. Conclusions: We provide a thorough evaluation of popular assemblers on a non-model eukaryote genome with variable levels of heterozygosity. Our study highlights several strategies using pre and post-processing approaches to generate haploid assemblies with high continuity and completeness. This benchmark will help users to improve haploid assemblies of non-model organisms, and evaluate the quality of their own assemblies.

langue originaleAnglais
Numéro d'article303
journalBMC Bioinformatics
Volume22
Numéro de publication1
Date de mise en ligne précoce5 juin 2021
Les DOIs
Etat de la publicationPublié - déc. 2021

Financement

We thank Antoine Limasset and Paul Simion for their useful advice. We also thank Michael Eitel for prompting us to initiate this benchmark of long-read assemblers. Nanopore reads were generated at Genoscope as part of the France Génomique project ’ALPAGA’ coordinated by Etienne Danchin ( www.france-genomique.org/projet/alpaga/ ). Part of this analysis was performed on computing clusters of the Leibniz-Rechenzentrum (LRZ) and the Consortium des Équipements de Calcul Intensif (CÉCI) funded by the Fonds de la Recherche Scientifique de Belgique (F.R.S.-FNRS) under Grant No. 2.5020.11. This project was funded by the Horizon 2020 research and innovation program of the European Union under the Marie Skłodowska-Curie grant agreement No. 764840 (ITN IGNITE, www.itn-ignite.eu ) for NG and JFF, and under the European Research Council (ERC) grant agreement No. 725998 (RHEA) to KVD. AH and AD are Research Fellows of the Fonds de la Recherche Scientifique – FNRS. These funding sources had no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript We thank Antoine Limasset and Paul Simion for their useful advice. We also thank Michael Eitel for prompting us to initiate this benchmark of long-read assemblers. Nanopore reads were generated at Genoscope as part of the France G?nomique project ?ALPAGA? coordinated by Etienne Danchin (www.france-genomique.org/projet/alpaga/). Part of this analysis was performed on computing clusters of the Leibniz-Rechenzentrum (LRZ) and the Consortium des ?quipements de Calcul Intensif (C?CI) funded by the Fonds de la Recherche Scientifique de Belgique (F.R.S.-FNRS) under Grant No. 2.5020.11.

Bailleurs de fondsNuméro du bailleur de fonds
Consortium des Équipements de Calcul Intensif
Leibniz-Rechenzentrum
Marie Skłodowska-Curie
Michael Eitel
Horizon 2020 Framework Programme764840, 725998
European commission
European Research Council
Fonds De La Recherche Scientifique - FNRS2.5020.11
Horizon 2020

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