MUMmer4: A fast and versatile genome alignment system

The MUMmer system and the genome sequence aligner nucmer included within it are among the most widely used alignment packages in genomics. Since the last major release of MUMmer version 3 in 2004, it has been applied to many types of problems including aligning whole genome sequences, aligning reads...

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Vydané v:	PLoS computational biology Ročník 14; číslo 1; s. e1005944
Hlavní autori:	Marçais, Guillaume, Delcher, Arthur L., Phillippy, Adam M., Coston, Rachel, Salzberg, Steven L., Zimin, Aleksey
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States Public Library of Science 01.01.2018 Public Library of Science (PLoS)
Predmet:	Algorithms Alignment Animals Arabidopsis - genetics Bioinformatics Biological effects Biology Biology and Life Sciences Computational biology Computational Biology - methods Computer and Information Sciences Computer science Data structures Funding Gene sequencing Genome, Human Genome, Plant Genomes Genomics Humans Medicine Methods Models, Theoretical Nucleotide sequence Packages Pan troglodytes Parallel processing Perl Polymorphism, Single Nucleotide Programming Languages Query processing Research and Analysis Methods Sequence Alignment - methods Sequence Analysis, DNA Sequence Analysis, Protein Software United States > US Maryland Baltimore Maryland Pennsylvania
ISSN:	1553-7358, 1553-734X, 1553-7358
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Abstract	The MUMmer system and the genome sequence aligner nucmer included within it are among the most widely used alignment packages in genomics. Since the last major release of MUMmer version 3 in 2004, it has been applied to many types of problems including aligning whole genome sequences, aligning reads to a reference genome, and comparing different assemblies of the same genome. Despite its broad utility, MUMmer3 has limitations that can make it difficult to use for large genomes and for the very large sequence data sets that are common today. In this paper we describe MUMmer4, a substantially improved version of MUMmer that addresses genome size constraints by changing the 32-bit suffix tree data structure at the core of MUMmer to a 48-bit suffix array, and that offers improved speed through parallel processing of input query sequences. With a theoretical limit on the input size of 141Tbp, MUMmer4 can now work with input sequences of any biologically realistic length. We show that as a result of these enhancements, the nucmer program in MUMmer4 is easily able to handle alignments of large genomes; we illustrate this with an alignment of the human and chimpanzee genomes, which allows us to compute that the two species are 98% identical across 96% of their length. With the enhancements described here, MUMmer4 can also be used to efficiently align reads to reference genomes, although it is less sensitive and accurate than the dedicated read aligners. The nucmer aligner in MUMmer4 can now be called from scripting languages such as Perl, Python and Ruby. These improvements make MUMer4 one the most versatile genome alignment packages available.
AbstractList	The MUMmer system and the genome sequence aligner nucmer included within it are among the most widely used alignment packages in genomics. Since the last major release of MUMmer version 3 in 2004, it has been applied to many types of problems including aligning whole genome sequences, aligning reads to a reference genome, and comparing different assemblies of the same genome. Despite its broad utility, MUMmer3 has limitations that can make it difficult to use for large genomes and for the very large sequence data sets that are common today. In this paper we describe MUMmer4, a substantially improved version of MUMmer that addresses genome size constraints by changing the 32-bit suffix tree data structure at the core of MUMmer to a 48-bit suffix array, and that offers improved speed through parallel processing of input query sequences. With a theoretical limit on the input size of 141Tbp, MUMmer4 can now work with input sequences of any biologically realistic length. We show that as a result of these enhancements, the nucmer program in MUMmer4 is easily able to handle alignments of large genomes; we illustrate this with an alignment of the human and chimpanzee genomes, which allows us to compute that the two species are 98% identical across 96% of their length. With the enhancements described here, MUMmer4 can also be used to efficiently align reads to reference genomes, although it is less sensitive and accurate than the dedicated read aligners. The nucmer aligner in MUMmer4 can now be called from scripting languages such as Perl, Python and Ruby. These improvements make MUMer4 one the most versatile genome alignment packages available. The MUMmer system and the genome sequence aligner nucmer included within it are among the most widely used alignment packages in genomics. Since the last major release of MUMmer version 3 in 2004, it has been applied to many types of problems including aligning whole genome sequences, aligning reads to a reference genome, and comparing different assemblies of the same genome. Despite its broad utility, MUMmer3 has limitations that can make it difficult to use for large genomes and for the very large sequence data sets that are common today. In this paper we describe MUMmer4, a substantially improved version of MUMmer that addresses genome size constraints by changing the 32-bit suffix tree data structure at the core of MUMmer to a 48-bit suffix array, and that offers improved speed through parallel processing of input query sequences. With a theoretical limit on the input size of 141Tbp, MUMmer4 can now work with input sequences of any biologically realistic length. We show that as a result of these enhancements, the nucmer program in MUMmer4 is easily able to handle alignments of large genomes; we illustrate this with an alignment of the human and chimpanzee genomes, which allows us to compute that the two species are 98% identical across 96% of their length. With the enhancements described here, MUMmer4 can also be used to efficiently align reads to reference genomes, although it is less sensitive and accurate than the dedicated read aligners. The nucmer aligner in MUMmer4 can now be called from scripting languages such as Perl, Python and Ruby. These improvements make MUMer4 one the most versatile genome alignment packages available.The MUMmer system and the genome sequence aligner nucmer included within it are among the most widely used alignment packages in genomics. Since the last major release of MUMmer version 3 in 2004, it has been applied to many types of problems including aligning whole genome sequences, aligning reads to a reference genome, and comparing different assemblies of the same genome. Despite its broad utility, MUMmer3 has limitations that can make it difficult to use for large genomes and for the very large sequence data sets that are common today. In this paper we describe MUMmer4, a substantially improved version of MUMmer that addresses genome size constraints by changing the 32-bit suffix tree data structure at the core of MUMmer to a 48-bit suffix array, and that offers improved speed through parallel processing of input query sequences. With a theoretical limit on the input size of 141Tbp, MUMmer4 can now work with input sequences of any biologically realistic length. We show that as a result of these enhancements, the nucmer program in MUMmer4 is easily able to handle alignments of large genomes; we illustrate this with an alignment of the human and chimpanzee genomes, which allows us to compute that the two species are 98% identical across 96% of their length. With the enhancements described here, MUMmer4 can also be used to efficiently align reads to reference genomes, although it is less sensitive and accurate than the dedicated read aligners. The nucmer aligner in MUMmer4 can now be called from scripting languages such as Perl, Python and Ruby. These improvements make MUMer4 one the most versatile genome alignment packages available.
Audience	Academic
Author	Phillippy, Adam M. Salzberg, Steven L. Coston, Rachel Delcher, Arthur L. Marçais, Guillaume Zimin, Aleksey
AuthorAffiliation	University of Technology Sydney, AUSTRALIA 4 National Human Genome Research Institute, Bethesda, Maryland, United States of America 3 Center for Computational Biology, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America 5 Departments of Biomedical Engineering, Computer Science, and Biostatistics, Johns Hopkins University, Baltimore, Maryland, United States of America 1 Institute for Physical Science and Technology, University of Maryland, College Park, Maryland, United States of America 2 Computational Biology Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America
AuthorAffiliation_xml	– name: 2 Computational Biology Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America – name: University of Technology Sydney, AUSTRALIA – name: 3 Center for Computational Biology, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America – name: 4 National Human Genome Research Institute, Bethesda, Maryland, United States of America – name: 5 Departments of Biomedical Engineering, Computer Science, and Biostatistics, Johns Hopkins University, Baltimore, Maryland, United States of America – name: 1 Institute for Physical Science and Technology, University of Maryland, College Park, Maryland, United States of America
Author_xml	– sequence: 1 givenname: Guillaume orcidid: 0000-0002-5083-5925 surname: Marçais fullname: Marçais, Guillaume – sequence: 2 givenname: Arthur L. surname: Delcher fullname: Delcher, Arthur L. – sequence: 3 givenname: Adam M. surname: Phillippy fullname: Phillippy, Adam M. – sequence: 4 givenname: Rachel surname: Coston fullname: Coston, Rachel – sequence: 5 givenname: Steven L. surname: Salzberg fullname: Salzberg, Steven L. – sequence: 6 givenname: Aleksey orcidid: 0000-0001-5091-3092 surname: Zimin fullname: Zimin, Aleksey
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/29373581$$D View this record in MEDLINE/PubMed
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Copyright	COPYRIGHT 2018 Public Library of Science 2018 Public Library of Science. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: Marçais G, Delcher AL, Phillippy AM, Coston R, Salzberg SL, Zimin A (2018) MUMmer4: A fast and versatile genome alignment system. PLoS Comput Biol 14(1): e1005944. https://doi.org/10.1371/journal.pcbi.1005944 2018 Public Library of Science. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: Marçais G, Delcher AL, Phillippy AM, Coston R, Salzberg SL, Zimin A (2018) MUMmer4: A fast and versatile genome alignment system. PLoS Comput Biol 14(1): e1005944. https://doi.org/10.1371/journal.pcbi.1005944
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SubjectTerms	Algorithms Alignment Animals Arabidopsis - genetics Bioinformatics Biological effects Biology Biology and Life Sciences Computational biology Computational Biology - methods Computer and Information Sciences Computer science Data structures Funding Gene sequencing Genome, Human Genome, Plant Genomes Genomics Humans Medicine Methods Models, Theoretical Nucleotide sequence Packages Pan troglodytes Parallel processing Perl Polymorphism, Single Nucleotide Programming Languages Query processing Research and Analysis Methods Sequence Alignment - methods Sequence Analysis, DNA Sequence Analysis, Protein Software
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