桑格测序
遗传学
基因
次等位基因频率
单核苷酸多态性
生物
编码区
发起人
等位基因
非翻译区
遗传关联
内含子
全基因组关联研究
等位基因频率
基因型
分子生物学
DNA测序
基因表达
核糖核酸
作者
Maria Margarida Nunes Gaspar de Matos,Joana M. Xavier,Patrícia Abrantes,Inês Sousa,Nádia Rei,Fereydoun Davatchi,Farhad Shahram,Gorete Jesus,Filipe Barcelos,Joana Vedes,Manuel Salgado,Bahar Sadeghi Abdollahi,Abdolhadi Nadji,Maria Francisca Moraes‐Fontes,Niloofar Mojarad Shafiee,Fahmida Ghaderibarmi,José Vaz Patto,Jorge Crespo,Sofia Oliveira
标识
DOI:10.1111/1756-185x.12369
摘要
Abstract Aim To explain the missing heritability after the genome‐wide association studies era, sequencing studies allow the identification of low‐frequency variants with a stronger effect on disease risk. Common variants in the interleukin 10 gene ( IL 10 ) have been consistently associated with Behçet's disease ( BD ) and the goal of this study is to investigate the role of low‐frequency IL 10 variants in BD susceptibility. Methods To identify IL 10 low‐frequency variants, a discovery group of 50 Portuguese BD patients were Sanger‐sequenced in a 7.7 kb genomic region encompassing the complete IL 10 gene, 0.9 kb upstream and 2 kb downstream, and two conserved regions in the putative promoter. To assess if the novel variants are BD ‐ and/or Portuguese‐specific, they were assayed in an additional group of BD patients (26 Portuguese and 964 Iranian) and controls (104 Portuguese and 823 Iranian). Results Rare IL 10 coding variants were not detected in BD patients, but we identified 28 known single nucleotide polymorphisms with minor allele frequencies ranging from 0.010 to 0.390, and five novel non‐coding variants in five heterozygous cases. ss836185595, located in the IL 10 3′ untranslated region, was also detected in one Iranian control individual and therefore is not specific to BD . The remaining novel IL 10 variants (ss836185596 and ss836185602 in intron 3, ss836185598 and ss836185604 in the putative promoter region) were not found in the replication dataset. Conclusion This study highlights the importance of screening the whole gene and regulatory regions when searching for novel variants associated with complex diseases, and the need to develop bioinformatics tools to predict the functional impact of non‐coding variants and statistical tests which incorporate these predictions.
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