Characterization of the Common Genetic Variation in the Spanish Population of Navarre

Large-scale genomic studies have significantly increased our knowledge of genetic variability across populations. Regional genetic profiling is essential for distinguishing common benign variants from disease-causing ones. To this end, we conducted a comprehensive characterization of exonic variants...

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Published inGenes Vol. 15; no. 5; p. 585
Main Authors Maillo, Alberto, Huergo, Estefania, Apellániz-Ruiz, María, Urrutia-Lafuente, Edurne, Miranda, María, Salgado, Josefa, Pasalodos-Sanchez, Sara, Delgado-Mora, Luna, Teijido, Óscar, Goicoechea, Ibai, Carmona, Rosario, Perez-Florido, Javier, Aquino, Virginia, Lopez-Lopez, Daniel, Peña-Chilet, María, Beltran, Sergi, Dopazo, Joaquín, Lasa, Iñigo, Beloqui, Juan José, Alonso, Ángel, Gomez-Cabrero, David
Format Journal Article
LanguageEnglish
Published Switzerland MDPI AG 04.05.2024
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ISSN2073-4425
2073-4425
DOI10.3390/genes15050585

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Summary:Large-scale genomic studies have significantly increased our knowledge of genetic variability across populations. Regional genetic profiling is essential for distinguishing common benign variants from disease-causing ones. To this end, we conducted a comprehensive characterization of exonic variants in the population of Navarre (Spain), utilizing whole genome sequencing data from 358 unrelated individuals of Spanish origin. Our analysis revealed 61,410 biallelic single nucleotide variants (SNV) within the Navarrese cohort, with 35% classified as common (MAF > 1%). By comparing allele frequency data from 1000 Genome Project (excluding the Iberian cohort of Spain, IBS), Genome Aggregation Database, and a Spanish cohort (including IBS individuals and data from Medical Genome Project), we identified 1069 SNVs common in Navarre but rare (MAF ≤ 1%) in all other populations. We further corroborated this observation with a second regional cohort of 239 unrelated exomes, which confirmed 676 of the 1069 SNVs as common in Navarre. In conclusion, this study highlights the importance of population-specific characterization of genetic variation to improve allele frequency filtering in sequencing data analysis to identify disease-causing variants.
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ISSN:2073-4425
2073-4425
DOI:10.3390/genes15050585