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Reference-guided de novo assembly approach improves genome reconstruction for related species


Lischer, Heidi E L; Shimizu, Kentaro K (2017). Reference-guided de novo assembly approach improves genome reconstruction for related species. BMC Bioinformatics, 18(1):474.

Abstract

Background: The development of next-generation sequencing has made it possible to sequence whole genomes
at a relatively low cost. However, de novo genome assemblies remain challenging due to short read length,
missing data, repetitive regions, polymorphisms and sequencing errors. As more and more genomes are
sequenced, reference-guided assembly approaches can be used to assist the assembly process. However, previous
methods mostly focused on the assembly of other genotypes within the same species. We adapted and extended
a reference-guided de novo assembly approach, which enables the usage of a related reference sequence to guide
the genome assembly. In order to compare and evaluate de novo and our reference-guided de novo assembly
approaches, we used a simulated data set of a repetitive and heterozygotic plant genome.
Results: The extended reference-guided de novo assembly approach almost always outperforms the corresponding
de novo assembly program even when a reference of a different species is used. Similar improvements can be
observed in high and low coverage situations. In addition, we show that a single evaluation metric, like the widely
used N50 length, is not enough to properly rate assemblies as it not always points to the best assembly evaluated
with other criteria. Therefore, we used the summed z-scores of 36 different statistics to evaluate the assemblies.
Conclusions: The combination of reference mapping and de novo assembly provides a powerful tool to improve
genome reconstruction by integrating information of a related genome. Our extension of the reference-guided de
novo assembly approach enables the application of this strategy not only within but also between related species.
Finally, the evaluation of genome assemblies is often not straight forward, as the truth is not known. Thus one
should always use a combination of evaluation metrics, which not only try to assess the continuity but also the
accuracy of an assembly.

Abstract

Background: The development of next-generation sequencing has made it possible to sequence whole genomes
at a relatively low cost. However, de novo genome assemblies remain challenging due to short read length,
missing data, repetitive regions, polymorphisms and sequencing errors. As more and more genomes are
sequenced, reference-guided assembly approaches can be used to assist the assembly process. However, previous
methods mostly focused on the assembly of other genotypes within the same species. We adapted and extended
a reference-guided de novo assembly approach, which enables the usage of a related reference sequence to guide
the genome assembly. In order to compare and evaluate de novo and our reference-guided de novo assembly
approaches, we used a simulated data set of a repetitive and heterozygotic plant genome.
Results: The extended reference-guided de novo assembly approach almost always outperforms the corresponding
de novo assembly program even when a reference of a different species is used. Similar improvements can be
observed in high and low coverage situations. In addition, we show that a single evaluation metric, like the widely
used N50 length, is not enough to properly rate assemblies as it not always points to the best assembly evaluated
with other criteria. Therefore, we used the summed z-scores of 36 different statistics to evaluate the assemblies.
Conclusions: The combination of reference mapping and de novo assembly provides a powerful tool to improve
genome reconstruction by integrating information of a related genome. Our extension of the reference-guided de
novo assembly approach enables the application of this strategy not only within but also between related species.
Finally, the evaluation of genome assemblies is often not straight forward, as the truth is not known. Thus one
should always use a combination of evaluation metrics, which not only try to assess the continuity but also the
accuracy of an assembly.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Evolutionary Biology and Environmental Studies
08 University Research Priority Programs > Evolution in Action: From Genomes to Ecosystems
Dewey Decimal Classification:570 Life sciences; biology
590 Animals (Zoology)
Uncontrolled Keywords:Genome assembly, Reference-guided, De novo, Related species, Assembly evaluation
Language:English
Date:2017
Deposited On:14 Nov 2017 15:07
Last Modified:19 Feb 2018 09:16
Publisher:BioMed Central
ISSN:1471-2105
OA Status:Gold
Free access at:PubMed ID. An embargo period may apply.
Publisher DOI:https://doi.org/10.1186/s12859-017-1911-6
PubMed ID:29126390

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