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De novo assembly of the complex genome of Nippostrongylus brasiliensis using MinION long reads

Overview of attention for article published in BMC Biology, January 2018
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Title
De novo assembly of the complex genome of Nippostrongylus brasiliensis using MinION long reads
Published in
BMC Biology, January 2018
DOI 10.1186/s12915-017-0473-4
Pubmed ID
Authors

David Eccles, Jodie Chandler, Mali Camberis, Bernard Henrissat, Sergey Koren, Graham Le Gros, Jonathan J. Ewbank

Abstract

Eukaryotic genome assembly remains a challenge in part due to the prevalence of complex DNA repeats. This is a particularly acute problem for holocentric nematodes because of the large number of satellite DNA sequences found throughout their genomes. These have been recalcitrant to most genome sequencing methods. At the same time, many nematodes are parasites and some represent a serious threat to human health. There is a pressing need for better molecular characterization of animal and plant parasitic nematodes. The advent of long-read DNA sequencing methods offers the promise of resolving complex genomes. Using Nippostrongylus brasiliensis as a test case, applying improved base-calling algorithms and assembly methods, we demonstrate the feasibility of de novo genome assembly matching current community standards using only MinION long reads. In doing so, we uncovered an unexpected diversity of very long and complex DNA sequences repeated throughout the N. brasiliensis genome, including massive tandem repeats of tRNA genes. Base-calling and assembly methods have improved sufficiently that de novo genome assembly of large complex genomes is possible using only long reads. The method has the added advantage of preserving haplotypic variants and so has the potential to be used in population analyses.

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The data shown below were compiled from readership statistics for 111 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 111 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 26 23%
Student > Ph. D. Student 22 20%
Student > Master 16 14%
Student > Bachelor 11 10%
Student > Postgraduate 4 4%
Other 15 14%
Unknown 17 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 34 31%
Biochemistry, Genetics and Molecular Biology 29 26%
Computer Science 8 7%
Immunology and Microbiology 5 5%
Environmental Science 4 4%
Other 11 10%
Unknown 20 18%