Tissue-Specific Enrichment of Lymphoma Risk Loci in Regulatory Elements.
Tissue-Specific Enrichment of Lymphoma Risk Loci in Regulatory Elements.
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DOI：
10.1371/journal.pone.0139360
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发表时间：
2015
期刊：
影响因子：
3.7
通讯作者：
Klein RJ
中科院分区：
文献类型：
--
作者：
Hayes JE;Trynka G;Vijai J;Offit K;Raychaudhuri S;Klein RJ
尽管许多多态性与发生淋巴瘤的风险相关，但这些变异如何促进肿瘤发生尚不清楚。在这里，我们报告了淋巴瘤风险snp，特别是在非霍奇金淋巴瘤亚型慢性淋巴细胞白血病中，与活性基因调控的表观遗传标记显著富集共定位。在许多ENCODE数据集中，这些富集以淋巴细胞特异性的方式被观察到，包括dna超敏以及多个片段定义的增强子区域。此外，我们还确定了淋巴细胞中调控元件和血液中基因表达变化相关的假定功能性snp。我们开发了一种算法UES，该算法使用蒙特卡罗模拟方法来计算先前确定的各种功能元件中风险snp的富集程度。这种整合多个数据集的多尺度方法有助于解开淋巴瘤的潜在生物学，更广泛地说，通常也适用于其他疾病的GWAS结果。
Though numerous polymorphisms have been associated with risk of developing lymphoma, how these variants function to promote tumorigenesis is poorly understood. Here, we report that lymphoma risk SNPs, especially in the non-Hodgkin’s lymphoma subtype chronic lymphocytic leukemia, are significantly enriched for co-localization with epigenetic marks of active gene regulation. These enrichments were seen in a lymphoid-specific manner for numerous ENCODE datasets, including DNase-hypersensitivity as well as multiple segmentation-defined enhancer regions. Furthermore, we identify putatively functional SNPs that are both in regulatory elements in lymphocytes and are associated with gene expression changes in blood. We developed an algorithm, UES, that uses a Monte Carlo simulation approach to calculate the enrichment of previously identified risk SNPs in various functional elements. This multiscale approach integrating multiple datasets helps disentangle the underlying biology of lymphoma, and more broadly, is generally applicable to GWAS results from other diseases as well.