Rapid phylogenetic and functional classification of short genomic fragments with signature peptides.
Identifieur interne : 001D54 ( PubMed/Corpus ); précédent : 001D53; suivant : 001D55Rapid phylogenetic and functional classification of short genomic fragments with signature peptides.
Auteurs : Joel Berendzen ; William J. Bruno ; Judith D. Cohn ; Nicolas W. Hengartner ; Cheryl R. Kuske ; Benjamin H. Mcmahon ; Murray A. Wolinsky ; Gary XieSource :
- BMC research notes [ 1756-0500 ] ; 2012.
English descriptors
- KwdEn :
- Bacterial Proteins (classification), Bacterial Proteins (genetics), Base Sequence, DNA-Directed RNA Polymerases (classification), DNA-Directed RNA Polymerases (genetics), Databases, Genetic, Gene Expression Profiling, Genome, Bacterial, Metagenomics (methods), Oligopeptides (classification), Oligopeptides (genetics), Phylogeny, Sequence Alignment, Sequence Analysis, DNA, Sequence Homology, Nucleic Acid, Soil Microbiology, Species Specificity, Transcriptome.
- MESH :
- chemical , classification : Bacterial Proteins, DNA-Directed RNA Polymerases, Oligopeptides.
- chemical , genetics : Bacterial Proteins, DNA-Directed RNA Polymerases, Oligopeptides.
- methods : Metagenomics.
- Base Sequence, Databases, Genetic, Gene Expression Profiling, Genome, Bacterial, Phylogeny, Sequence Alignment, Sequence Analysis, DNA, Sequence Homology, Nucleic Acid, Soil Microbiology, Species Specificity, Transcriptome.
Abstract
Classification is difficult for shotgun metagenomics data from environments such as soils, where the diversity of sequences is high and where reference sequences from close relatives may not exist. Approaches based on sequence-similarity scores must deal with the confounding effects that inheritance and functional pressures exert on the relation between scores and phylogenetic distance, while approaches based on sequence alignment and tree-building are typically limited to a small fraction of gene families. We describe an approach based on finding one or more exact matches between a read and a precomputed set of peptide 10-mers.
DOI: 10.1186/1756-0500-5-460
PubMed: 22925230
Links to Exploration step
pubmed:22925230Le document en format XML
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<term>DNA-Directed RNA Polymerases (genetics)</term>
<term>Databases, Genetic</term>
<term>Gene Expression Profiling</term>
<term>Genome, Bacterial</term>
<term>Metagenomics (methods)</term>
<term>Oligopeptides (classification)</term>
<term>Oligopeptides (genetics)</term>
<term>Phylogeny</term>
<term>Sequence Alignment</term>
<term>Sequence Analysis, DNA</term>
<term>Sequence Homology, Nucleic Acid</term>
<term>Soil Microbiology</term>
<term>Species Specificity</term>
<term>Transcriptome</term>
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<term>DNA-Directed RNA Polymerases</term>
<term>Oligopeptides</term>
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<term>DNA-Directed RNA Polymerases</term>
<term>Oligopeptides</term>
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<term>Sequence Alignment</term>
<term>Sequence Analysis, DNA</term>
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<front><div type="abstract" xml:lang="en">Classification is difficult for shotgun metagenomics data from environments such as soils, where the diversity of sequences is high and where reference sequences from close relatives may not exist. Approaches based on sequence-similarity scores must deal with the confounding effects that inheritance and functional pressures exert on the relation between scores and phylogenetic distance, while approaches based on sequence alignment and tree-building are typically limited to a small fraction of gene families. We describe an approach based on finding one or more exact matches between a read and a precomputed set of peptide 10-mers.</div>
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<Month>Aug</Month>
<Day>28</Day>
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<Title>BMC research notes</Title>
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<ArticleTitle>Rapid phylogenetic and functional classification of short genomic fragments with signature peptides.</ArticleTitle>
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<Abstract><AbstractText Label="BACKGROUND" NlmCategory="BACKGROUND">Classification is difficult for shotgun metagenomics data from environments such as soils, where the diversity of sequences is high and where reference sequences from close relatives may not exist. Approaches based on sequence-similarity scores must deal with the confounding effects that inheritance and functional pressures exert on the relation between scores and phylogenetic distance, while approaches based on sequence alignment and tree-building are typically limited to a small fraction of gene families. We describe an approach based on finding one or more exact matches between a read and a precomputed set of peptide 10-mers.</AbstractText>
<AbstractText Label="RESULTS" NlmCategory="RESULTS">At even the largest phylogenetic distances, thousands of 10-mer peptide exact matches can be found between pairs of bacterial genomes. Genes that share one or more peptide 10-mers typically have high reciprocal BLAST scores. Among a set of 403 representative bacterial genomes, some 20 million 10-mer peptides were found to be shared. We assign each of these peptides as a signature of a particular node in a phylogenetic reference tree based on the RNA polymerase genes. We classify the phylogeny of a genomic fragment (e.g., read) at the most specific node on the reference tree that is consistent with the phylogeny of observed signature peptides it contains. Using both synthetic data from four newly-sequenced soil-bacterium genomes and ten real soil metagenomics data sets, we demonstrate a sensitivity and specificity comparable to that of the MEGAN metagenomics analysis package using BLASTX against the NR database. Phylogenetic and functional similarity metrics applied to real metagenomics data indicates a signal-to-noise ratio of approximately 400 for distinguishing among environments. Our method assigns ~6.6 Gbp/hr on a single CPU, compared with 25 kbp/hr for methods based on BLASTX against the NR database.</AbstractText>
<AbstractText Label="CONCLUSIONS" NlmCategory="CONCLUSIONS">Classification by exact matching against a precomputed list of signature peptides provides comparable results to existing techniques for reads longer than about 300 bp and does not degrade severely with shorter reads. Orders of magnitude faster than existing methods, the approach is suitable now for inclusion in analysis pipelines and appears to be extensible in several different directions.</AbstractText>
</Abstract>
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<Initials>J</Initials>
<AffiliationInfo><Affiliation>Physics Division, MS D454, Los Alamos National Laboratory, Los Alamos NM87545, USA.</Affiliation>
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<Author ValidYN="Y"><LastName>Bruno</LastName>
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<Author ValidYN="Y"><LastName>Cohn</LastName>
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