转自Olink Proteomics
感兴趣的读者可以接下来继续来看结果分析:
1)局部蛋白定量性状位点(local protein quantitative trait loci ,cis-pQTL)分析:
搜寻编码92蛋白基因250kb内的SNPs。(Manhattan plot of 129 cis-pQTLs for 66 proteins.)
2)全基因组跨QTL映射分析(genome-wide trans-pQTL mapping):
如下图:相关的反式片段和蛋白的染色体位置被突出显示。snps被标记为红色条,映射的蛋白质被标记。每个弯曲的箭头都表示从snp到蛋白质的反式pQTL效应。
3)本次分析数据中排除了已被发现的关联后,还揭示了新的pQTL关联,包括25个蛋白的36个cis-pQTLs和27个蛋白的48个反式pQTLs。
并且和转录组数据比较显示了基于转录组的eQTL分析并不能很好的反应现象,例如,相比之下,85个反pQTLs在表达水平上都没有被检测到。
Proportion of inter-individual variation explained by genetic and microbial factors. Each bar represents a protein. Y axis is the explained variation. Proportion of variation is separated into cis-pQTLs (blue), trans-pQTLs (green), and microbiome (red).
参考文献:
1.Zhernakova, D.V., Le, T.H., Kurilshikov, A. et al. Individual variations in cardiovascular-disease-related protein levels are driven by genetics and gut microbiome. Nat Genet 50, 1524–1532 (2018). https://doi.org/10.1038/s41588-018-0224-72.Zheng, J., Haberland, V., Baird, D. et al. Phenome-wide Mendelian randomization mapping the influence of the plasma proteome on complex diseases. Nat Genet 52, 1122–1131 (2020). https://doi.org/10.1038/s41588-020-0682-6