Resolving the complexity of the human genome using single-molecule sequencing View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2015-01

AUTHORS

Mark J. P. Chaisson, John Huddleston, Megan Y. Dennis, Peter H. Sudmant, Maika Malig, Fereydoun Hormozdiari, Francesca Antonacci, Urvashi Surti, Richard Sandstrom, Matthew Boitano, Jane M. Landolin, John A. Stamatoyannopoulos, Michael W. Hunkapiller, Jonas Korlach, Evan E. Eichler

ABSTRACT

The human genome is arguably the most complete mammalian reference assembly, yet more than 160 euchromatic gaps remain and aspects of its structural variation remain poorly understood ten years after its completion. To identify missing sequence and genetic variation, here we sequence and analyse a haploid human genome (CHM1) using single-molecule, real-time DNA sequencing. We close or extend 55% of the remaining interstitial gaps in the human GRCh37 reference genome--78% of which carried long runs of degenerate short tandem repeats, often several kilobases in length, embedded within (G+C)-rich genomic regions. We resolve the complete sequence of 26,079 euchromatic structural variants at the base-pair level, including inversions, complex insertions and long tracts of tandem repeats. Most have not been previously reported, with the greatest increases in sensitivity occurring for events less than 5 kilobases in size. Compared to the human reference, we find a significant insertional bias (3:1) in regions corresponding to complex insertions and long short tandem repeats. Our results suggest a greater complexity of the human genome in the form of variation of longer and more complex repetitive DNA that can now be largely resolved with the application of this longer-read sequencing technology. More... »

PAGES

608

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/nature13907

DOI

http://dx.doi.org/10.1038/nature13907

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1014139802

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/25383537


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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1038/nature13907'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/nature13907'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/nature13907'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/nature13907'


 

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