title: Exploiting the great potential of Sequence Capture data by a new tool, SUPER-CAP.
abstract: The recent development of Sequence Capture methodology represents a powerful strategy for enhancing data generation to assess genetic variation of targeted genomic regions. Here, we present SUPER-CAP, a bioinformatics web tool aimed at handling Sequence Capture data, fine calculating the allele frequency of variations and building genotype-specific sequence of captured genes. The dataset used to develop this in silico strategy consists of 378 loci and related regulative regions in a collection of 44 tomato landraces. About 14,000 high-quality variants were identified. The high depth (>40×) of coverage and adopting the correct filtering criteria allowed identification of about 4,000 rare variants and 10 genes with a different copy number variation. We also show that the tool is capable to reconstruct genotype-specific sequences for each genotype by using the detected variants. This allows evaluating the combined effect of multiple variants in the same protein. The architecture and functionality of SUPER-CAP makes the software appropriate for a broad set of analyses including SNP discovery and mining. Its functionality, together with the capability to process large data sets and efficient detection of sequence variation, makes SUPER-CAP a valuable bioinformatics tool for genomics and breeding purposes.
authors.affiliation: Department of Agricultural Sciences, University of Naples Federico II, Via Università 100, 80055 Portici (NA), Italy.|Sequentia Biotech SL, Calle Compte d'Urgell, 240, 08035 Barcelona, Spain.
authors.forename: Valentino
authors.initials: V
authors.lastname: Ruggieri
authors.affiliation: Sequentia Biotech SL, Calle Compte d'Urgell, 240, 08035 Barcelona, Spain.
authors.forename: Irantzu
authors.initials: I
authors.lastname: Anzar
authors.affiliation: Sequentia Biotech SL, Calle Compte d'Urgell, 240, 08035 Barcelona, Spain.
authors.forename: Andreu
authors.initials: A
authors.lastname: Paytuvi
authors.affiliation: Department of Agricultural Sciences, University of Naples Federico II, Via Università 100, 80055 Portici (NA), Italy.
authors.forename: Roberta
authors.initials: R
authors.lastname: Calafiore
authors.affiliation: Sequentia Biotech SL, Calle Compte d'Urgell, 240, 08035 Barcelona, Spain.
authors.forename: Riccardo Aiese
authors.initials: RA
authors.lastname: Cigliano
authors.affiliation: Sequentia Biotech SL, Calle Compte d'Urgell, 240, 08035 Barcelona, Spain.
authors.forename: Walter
authors.initials: W
authors.lastname: Sanseverino
authors.affiliation: Department of Agricultural Sciences, University of Naples Federico II, Via Università 100, 80055 Portici (NA), Italy.
authors.forename: Amalia
authors.initials: A
authors.lastname: Barone
mesh_terms: D057225:Data Mining; D005787:Gene Frequency; D017343:Genes, Plant; D018551:Solanum lycopersicum / Q000235:genetics; D020641:Polymorphism, Single Nucleotide; D017421:Sequence Analysis / Q000379:methods*
keywords: heterozygous variants; sequence reconstruction; target enrichment; web tool analysis