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Título: | Copy number variation in the porcine genome inferred from a 60 k SNP BeadChip |
Autor: | Ramayo-Caldas, Yuliaxis; Castelló, Anna CSIC ORCID; Pena, Ramona N.; Alves, Estefania; Mercadé, Anna CSIC ORCID; Souza, Carla A.; Fernández, Ana Isabel; Pérez-Enciso, Miguel CSIC ORCID; Folch, Josep María CSIC ORCID | Fecha de publicación: | 2010 | Editor: | BioMed Central | Citación: | BMC Genomics 11: 593 (2010) | Resumen: | [Background]: Recent studies in pigs have detected copy number variants (CNVs) using the Comparative Genomic Hybridization technique in arrays designed to cover specific porcine chromosomes. The goal of this study was to identify CNV regions (CNVRs) in swine species based on whole genome SNP genotyping chips. [Results]: We used predictions from three different programs (cnvPartition, PennCNV and GADA) to analyze data from the Porcine SNP60 BeadChip. A total of 49 CNVRs were identified in 55 animals from an Iberian x Landrace cross (IBMAP) according to three criteria: detected in at least two animals, contained three or more consecutive SNPs and recalled by at least two programs. Mendelian inheritance of CNVRs was confirmed in animals belonging to several generations of the IBMAP cross. Subsequently, a segregation analysis of these CNVRs was performed in 372 additional animals from the IBMAP cross and its distribution was studied in 133 unrelated pig samples from different geographical origins. Five out of seven analyzed CNVRs were validated by real time quantitative PCR, some of which coincide with well known examples of CNVs conserved across mammalian species. [Conclusions]: Our results illustrate the usefulness of Porcine SNP60 BeadChip to detect CNVRs and show that structural variants can not be neglected when studying the genetic variability in this species. |
Versión del editor: | https://doi.org/10.1186/1471-2164-11-593 | URI: | http://hdl.handle.net/10261/248357 | DOI: | 10.1186/1471-2164-11-593 | E-ISSN: | 1471-2164 |
Aparece en las colecciones: | (CRAG) Artículos (INIA) Artículos |
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copychip.pdf | 1,09 MB | Adobe PDF | Visualizar/Abrir |
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