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Epistatic selection between coding and regulatory variation in human evolution and disease.

机译:在人类进化和疾病的编码和调节变异之间的上位选择。

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Interaction (nonadditive effects) between genetic variants has been highlighted as an important mechanism underlying phenotypic variation, but the discovery of genetic interactions in humans has proved difficult. In this study, we show that the spectrum of variation in the human genome has been shaped by modifier effects of cis-regulatory variation on the functional impact of putatively deleterious protein-coding variants. We analyzed 1000 Genomes population-scale resequencing data from Europe (CEU [Utah residents with Northern and Western European ancestry from the CEPH collection]) and Africa (YRI [Yoruba in Ibadan, Nigeria]) together with gene expression data from arrays and RNA sequencing for the same samples. We observed an underrepresentation of derived putatively functional coding variation on the more highly expressed regulatory haplotype, which suggests stronger purifying selection against deleterious coding variants that have increased penetrance because of their regulatory background. Furthermore, the frequency spectrum and impact size distribution of common regulatory polymorphisms (eQTLs) appear to be shaped in order to minimize the selective disadvantage of having deleterious coding mutations on the more highly expressed haplotype. Interestingly, eQTLs explaining common disease GWAS signals showed an enrichment of putative epistatic effects, suggesting that some disease associations might arise from interactions increasing the penetrance of rare coding variants. In conclusion, our results indicate that regulatory and coding variants often modify the functional impact of each other. This specific type of genetic interaction is detectable from sequencing data in a genome-wide manner, and characterizing these joint effects might help us understand functional mechanisms behind genetic associations to human phenotypes-including both Mendelian and common disease.
机译:遗传变异之间的相互作用(非累加效应)已被强调为表型变异的重要机制,但是事实证明,人类之间遗传相互作用的发现是困难的。在这项研究中,我们表明,人类基因组中的变异谱已由顺式调节变异对假定有害的蛋白质编码变异的功能影响的修饰子效应所塑造。我们分析了来自欧洲(CEU [来自CEPH集合的具有北欧和西欧血统的犹他州居民])和非洲(YRI [位于尼日利亚伊巴丹的约鲁巴])的1000个基因组人口规模重测序数据,以及来自阵列和RNA测序的基因表达数据对于相同的样品。我们观察到在更高表达的调节单倍型上推定推定功能编码变异的代表性不足,这表明针对由于其调节背景而增加了渗透性的有害编码变异,有更强的纯化选择。此外,常见的调节多态性(eQTL)的频谱和影响大小分布似乎已成形,以最大程度地减少在更高表达的单倍型上具有有害编码突变的选择性缺点。有趣的是,解释常见疾病GWAS信号的eQTL显示出丰富的假定的上位效应,表明某些疾病的关联可能是由于相互作用增加了稀有编码变体的渗透性而引起的。总而言之,我们的结果表明,调节和编码变体经常会改变彼此的功能影响。这种特定类型的遗传相互作用可以在全基因组范围内从测序数据中检测到,表征这些联合效应可能有助于我们了解与人类表型(包括孟德尔病和常见病)的遗传关联背后的功能机制。

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