6533b7d4fe1ef96bd126337e
RESEARCH PRODUCT
AFS: identification and quantification of species composition by metagenomic sequencing
Hanno SchmidtChristopher Felix KrombholzBertil SchmidtMathias WeberFabian RippRene KoeppelThomas HankelnSören Lukas HellmannYongchao LiuYongchao Liusubject
0301 basic medicineStatistics and ProbabilitySequence analysisLibrary preparationComputational biologyBiologyBioinformaticsBiochemistrylaw.invention03 medical and health sciences0404 agricultural biotechnologylawMolecular BiologyPolymerase chain reactionShotgun sequencingHigh-Throughput Nucleotide SequencingSequence Analysis DNA04 agricultural and veterinary sciencesAccession number (bioinformatics)040401 food scienceBiological materialsComputer Science ApplicationsComputational Mathematics030104 developmental biologyComputational Theory and MathematicsMetagenomicsFood MicrobiologyIdentification (biology)MetagenomicsSoftwaredescription
Abstract Summary DNA-based methods to detect and quantify taxon composition in biological materials are often based on species-specific polymerase chain reaction, limited to detecting species targeted by the assay. Next-generation sequencing overcomes this drawback by untargeted shotgun sequencing of whole metagenomes at affordable cost. Here we present AFS, a software pipeline for quantification of species composition in food. AFS uses metagenomic shotgun sequencing and sequence read counting to infer species proportions. Using Illumina data from a reference sausage comprising four species, we reveal that AFS is independent of the sequencing assay and library preparation protocol. Cost-saving short (50-bp) single-end reads and Nextera® library preparation yield reliable results. Availability and Implementation Datasets, binaries and usage instructions are available under http://all-food-seq.sourceforge.net. Raw data is available at NCBI’s SRA with accession number PRJNA271645. Supplementary information Supplementary data are available at Bioinformatics online.
year | journal | country | edition | language |
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2017-01-05 | Bioinformatics |