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hal.structure.identifierUnité de recherches Espèces Fruitières et Vigne [UREFV]
hal.structure.identifierCentre de Bioinformatique de Bordeaux [CBIB]
dc.contributor.authorLE DANTEC, Loick
hal.structure.identifierBiodiversité, Gènes et Ecosystèmes [BioGeCo]
dc.contributor.authorCHAGNÉ, David
hal.structure.identifierBiodiversité, Gènes et Ecosystèmes [BioGeCo]
dc.contributor.authorPOT, David
hal.structure.identifierUnité de recherches Espèces Fruitières et Vigne [UREFV]
hal.structure.identifierCentre de Bioinformatique de Bordeaux [CBIB]
dc.contributor.authorCANTIN, Olivier
hal.structure.identifierBiodiversité, Gènes et Ecosystèmes [BioGeCo]
dc.contributor.authorGARNIER‐GÉRÉ, Pauline
hal.structure.identifierBiodiversité, Gènes et Ecosystèmes [BioGeCo]
dc.contributor.authorBEDON, Franck
hal.structure.identifierBiodiversité, Gènes et Ecosystèmes [BioGeCo]
dc.contributor.authorFRIGERIO, Jean-Marc
hal.structure.identifierBiodiversité, Gènes et Ecosystèmes [BioGeCo]
dc.contributor.authorCHAUMEIL, Philippe
hal.structure.identifierBiodiversité, Gènes et Ecosystèmes [BioGeCo]
dc.contributor.authorLÉGER, Patrick
hal.structure.identifierStation de physiologie végétale
dc.contributor.authorGARCIA, Virginie
hal.structure.identifierUnité de recherches Espèces Fruitières et Vigne [UREFV]
dc.contributor.authorLAIGRET, Frédéric
hal.structure.identifierCentre de Bioinformatique de Bordeaux [CBIB]
dc.contributor.authorDE DARUVAR, Antoine
hal.structure.identifierBiodiversité, Gènes et Ecosystèmes [BioGeCo]
dc.contributor.authorPLOMION, Christophe
dc.date.issued2004
dc.identifier.issn0167-4412
dc.description.abstractEnWe developed an automated pipeline for the detection of single nucleotide polymorphisms (SNPs) in expressed sequence tag (EST) data sets, by combining three DNA sequence analysis programs:Phred, Phrap and PolyBayes. This application requires access to the individual electrophoregram traces. First, a reference set of 65 SNPs was obtained from the sequencing of 30 gametes in 13 maritime pine (Pinus pinaster Ait.) gene fragments (6671 bp), resulting in a frequency of 1 SNP every 102.6 bp. Second, parameters of the three programs were optimized in order to retrieve as many true SNPs, while keeping the rate of false positive as low as possible. Overall, the efficiency of detection of true SNPs was 83.1%. However, this rate varied largely as a function of the rare SNP allele frequency: down to 41% for rare SNP alleles (frequency ` 10%), up to 98% for allele frequencies above 10%. Third, the detection method was applied to the 18498 assembled maritime pine (Pinus pinaster Ait.) ESTs, allowing to identify a total of 1400 candidate SNPs, in contigs containing between 4 and 20 sequence reads. These genetic resources, described for the first time in a forest tree species, were made available at http://www.pierroton.inra/genetics/Pinesnps. We also derived an analytical expression for the SNP detection probability as a function of the SNP allele frequency, the number of haploid genomes used to generate the EST sequence database, and the sample size of the contigs considered for SNP detection. The frequency of the SNP allele was shown to be the main factor influencing the probability of SNP detection
dc.language.isoen
dc.publisherSpringer Verlag (Germany)
dc.subjectEST
dc.subjectGENETIQUE
dc.subject.enSNP
dc.subject.enIN SILICO DETECTION
dc.subject.enPIN MARITIME
dc.subject.enANALYSE
dc.title.enAutomated SNP detection in expressed sequence tags : statistical considerations and application to maritime pine sequences
dc.typeArticle de revue
dc.identifier.doi10.1023/B:PLAN.0000036376.11710.6f
dc.subject.halSciences du Vivant [q-bio]/Biochimie, Biologie Moléculaire
bordeaux.journalPlant Molecular Biology
bordeaux.page461-470
bordeaux.volume54
bordeaux.issue3
bordeaux.peerReviewedoui
hal.identifierhal-02679200
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-02679200v1
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