Integrating Hi-C links with assembly graphs for chromosome-scale assembly

Long-read sequencing and novel long-range assays have revolutionized de novo genome assembly by automating the reconstruction of reference-quality genomes. In particular, Hi-C sequencing is becoming an economical method for generating chromosome-scale scaffolds. Despite its increasing popularity, th...

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Veröffentlicht in:	PLoS computational biology Jg. 15; H. 8; S. e1007273
Hauptverfasser:	Ghurye, Jay, Rhie, Arang, Walenz, Brian P., Schmitt, Anthony, Selvaraj, Siddarth, Pop, Mihai, Phillippy, Adam M., Koren, Sergey
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States Public Library of Science 01.08.2019 Public Library of Science (PLoS)
Schlagworte:	Algorithms Animals Assembly Bioinformatics Biology and Life Sciences Biosynthesis Chromosome number Chromosome replication Chromosomes Chromosomes, Human - genetics Computational Biology Computer and Information Sciences Computer science Computer Simulation Databases, Nucleic Acid - statistics & numerical data DNA sequencing Gene sequencing Genome, Human Genomes Genomic Library Genomics Genomics - methods Genomics - statistics & numerical data High-Throughput Nucleotide Sequencing - methods High-Throughput Nucleotide Sequencing - statistics & numerical data Humans Informatics Inversions Methods Open source software Research and Analysis Methods Scaffolding Sequence Analysis, DNA - methods Sequence Analysis, DNA - statistics & numerical data Software Source code Technology application Whole genome sequencing United States United States > US Maryland California
ISSN:	1553-7358, 1553-734X, 1553-7358
Online-Zugang:	Volltext
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Abstract	Long-read sequencing and novel long-range assays have revolutionized de novo genome assembly by automating the reconstruction of reference-quality genomes. In particular, Hi-C sequencing is becoming an economical method for generating chromosome-scale scaffolds. Despite its increasing popularity, there are limited open-source tools available. Errors, particularly inversions and fusions across chromosomes, remain higher than alternate scaffolding technologies. We present a novel open-source Hi-C scaffolder that does not require an a priori estimate of chromosome number and minimizes errors by scaffolding with the assistance of an assembly graph. We demonstrate higher accuracy than the state-of-the-art methods across a variety of Hi-C library preparations and input assembly sizes. The Python and C++ code for our method is openly available at https://github.com/machinegun/SALSA.
AbstractList	Long-read sequencing and novel long-range assays have revolutionized de novo genome assembly by automating the reconstruction of reference-quality genomes. In particular, Hi-C sequencing is becoming an economical method for generating chromosome-scale scaffolds. Despite its increasing popularity, there are limited open-source tools available. Errors, particularly inversions and fusions across chromosomes, remain higher than alternate scaffolding technologies. We present a novel open-source Hi-C scaffolder that does not require an a priori estimate of chromosome number and minimizes errors by scaffolding with the assistance of an assembly graph. We demonstrate higher accuracy than the state-of-the-art methods across a variety of Hi-C library preparations and input assembly sizes. The Python and C++ code for our method is openly available at https://github.com/machinegun/SALSA. Hi-C technology was originally proposed to study the 3D organization of a genome. Recently, it has also been applied to assemble large eukaryotic genomes into chromosome-scale scaffolds. Despite this, there are few open source methods to generate these assemblies. Existing methods are also prone to small inversion errors due to noise in the Hi-C data. In this work, we address these challenges and develop a method, named SALSA2. SALSA2 uses sequence overlap information from an assembly graph to correct inversion errors and provide accurate chromosome-scale assemblies. Long-read sequencing and novel long-range assays have revolutionized de novo genome assembly by automating the reconstruction of reference-quality genomes. In particular, Hi-C sequencing is becoming an economical method for generating chromosome-scale scaffolds. Despite its increasing popularity, there are limited open-source tools available. Errors, particularly inversions and fusions across chromosomes, remain higher than alternate scaffolding technologies. We present a novel open-source Hi-C scaffolder that does not require an a priori estimate of chromosome number and minimizes errors by scaffolding with the assistance of an assembly graph. We demonstrate higher accuracy than the state-of-the-art methods across a variety of Hi-C library preparations and input assembly sizes. The Python and C++ code for our method is openly available at https://github.com/machinegun/SALSA. Long-read sequencing and novel long-range assays have revolutionized de novo genome assembly by automating the reconstruction of reference-quality genomes. In particular, Hi-C sequencing is becoming an economical method for generating chromosome-scale scaffolds. Despite its increasing popularity, there are limited open-source tools available. Errors, particularly inversions and fusions across chromosomes, remain higher than alternate scaffolding technologies. We present a novel open-source Hi-C scaffolder that does not require an a priori estimate of chromosome number and minimizes errors by scaffolding with the assistance of an assembly graph. We demonstrate higher accuracy than the state-of-the-art methods across a variety of Hi-C library preparations and input assembly sizes. The Python and C++ code for our method is openly available at Long-read sequencing and novel long-range assays have revolutionized de novo genome assembly by automating the reconstruction of reference-quality genomes. In particular, Hi-C sequencing is becoming an economical method for generating chromosome-scale scaffolds. Despite its increasing popularity, there are limited open-source tools available. Errors, particularly inversions and fusions across chromosomes, remain higher than alternate scaffolding technologies. We present a novel open-source Hi-C scaffolder that does not require an a priori estimate of chromosome number and minimizes errors by scaffolding with the assistance of an assembly graph. We demonstrate higher accuracy than the state-of-the-art methods across a variety of Hi-C library preparations and input assembly sizes. The Python and C++ code for our method is openly available at https://github.com/machinegun/SALSA.Long-read sequencing and novel long-range assays have revolutionized de novo genome assembly by automating the reconstruction of reference-quality genomes. In particular, Hi-C sequencing is becoming an economical method for generating chromosome-scale scaffolds. Despite its increasing popularity, there are limited open-source tools available. Errors, particularly inversions and fusions across chromosomes, remain higher than alternate scaffolding technologies. We present a novel open-source Hi-C scaffolder that does not require an a priori estimate of chromosome number and minimizes errors by scaffolding with the assistance of an assembly graph. We demonstrate higher accuracy than the state-of-the-art methods across a variety of Hi-C library preparations and input assembly sizes. The Python and C++ code for our method is openly available at https://github.com/machinegun/SALSA.
Audience	Academic
Author	Pop, Mihai Koren, Sergey Ghurye, Jay Schmitt, Anthony Rhie, Arang Selvaraj, Siddarth Walenz, Brian P. Phillippy, Adam M.
AuthorAffiliation	1 Department of Computer Science, University of Maryland, College Park, Maryland, United States of America 3 Arima Genomics, San Diego, California, United States of America 2 Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institute of Health, Bethesda, Maryland, United States of America Ottawa University, CANADA
AuthorAffiliation_xml	– name: 2 Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institute of Health, Bethesda, Maryland, United States of America – name: 1 Department of Computer Science, University of Maryland, College Park, Maryland, United States of America – name: 3 Arima Genomics, San Diego, California, United States of America – name: Ottawa University, CANADA
Author_xml	– sequence: 1 givenname: Jay orcidid: 0000-0003-1381-4081 surname: Ghurye fullname: Ghurye, Jay – sequence: 2 givenname: Arang orcidid: 0000-0002-9809-8127 surname: Rhie fullname: Rhie, Arang – sequence: 3 givenname: Brian P. orcidid: 0000-0001-8431-1428 surname: Walenz fullname: Walenz, Brian P. – sequence: 4 givenname: Anthony surname: Schmitt fullname: Schmitt, Anthony – sequence: 5 givenname: Siddarth surname: Selvaraj fullname: Selvaraj, Siddarth – sequence: 6 givenname: Mihai orcidid: 0000-0001-9617-5304 surname: Pop fullname: Pop, Mihai – sequence: 7 givenname: Adam M. orcidid: 0000-0003-2983-8934 surname: Phillippy fullname: Phillippy, Adam M. – sequence: 8 givenname: Sergey orcidid: 0000-0002-1472-8962 surname: Koren fullname: Koren, Sergey
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/31433799$$D View this record in MEDLINE/PubMed
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Notes	new_version ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Sergey Koren has received travel and accommodation expenses to speak at Oxford Nanopore Technologies conferences. Anthony Schmitt and Siddarth Selvaraj are employees of Arima Genomics, a company commercializing Hi-C DNA sequencing technologies.
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Snippet	Long-read sequencing and novel long-range assays have revolutionized de novo genome assembly by automating the reconstruction of reference-quality genomes. In...
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SubjectTerms	Algorithms Animals Assembly Bioinformatics Biology and Life Sciences Biosynthesis Chromosome number Chromosome replication Chromosomes Chromosomes, Human - genetics Computational Biology Computer and Information Sciences Computer science Computer Simulation Databases, Nucleic Acid - statistics & numerical data DNA sequencing Gene sequencing Genome, Human Genomes Genomic Library Genomics Genomics - methods Genomics - statistics & numerical data High-Throughput Nucleotide Sequencing - methods High-Throughput Nucleotide Sequencing - statistics & numerical data Humans Informatics Inversions Methods Open source software Research and Analysis Methods Scaffolding Sequence Analysis, DNA - methods Sequence Analysis, DNA - statistics & numerical data Software Source code Technology application Whole genome sequencing
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Title	Integrating Hi-C links with assembly graphs for chromosome-scale assembly
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