使用Seer Proteograph平台对质谱蛋白质组学的全基因组关联研究
Karsten Suhre1,2, Qingwen Chen3, Anna Halama1,2
1Bioinformatics Core, Weill Cornell Medicine-Qatar, Education City, 24144 Doha, Qatar.
bioRxiv : the preprint server for biology
|June 10, 2024
概括
质谱学 (MS) 蛋白质组学与全基因组关联研究 (GWAS) 结合,确定了新型蛋白质定量特征位点 (pQTLs). 这种方法克服了亲和性蛋白质组学的局限性,揭示了更多的药物发现目标.
科学领域:
- 基因组学就是基因组学.
- 蛋白质组学是指蛋白质组学.
- 药物基因组学 药物基因组学
背景情况:
- 全基因组关联研究 (GWAS) 与蛋白质组学相结合,对于药物发现至关重要.
- 现有的亲属性蛋白质组平台受限于可用的结合剂和潜在的表位效应,影响蛋白质定量特征位置 (pQTL) 检测.
研究的目的:
- 调查基于质谱 (MS) 的蛋白质组学对GWAS的实用性,以识别新的pQTLs.
- 在pQTL发现中,将基于MS的蛋白质组与基于亲和力的平台进行比较,并评估表位效应的影响.
主要方法:
- 利用基于MS的Seer Proteograph平台对来自美国和亚洲队伍的血液样本进行GWAS (N=1,585).
- 在样本中量化了1980种蛋白质,并分析了252种cis-pQTL,复制了90.
- 将MS识别的pQTL与SOMAscan和Olink平台的pQTL进行了比较.
主要成果:
- 确定了252个pQTLs,其中90个复制,其中包括30个新的关联.
- 发现高达三分之一的亲和蛋白质组 pQTLs 可能会受到表位效应的影响.
- 使用MS蛋白质组学证实了基因变异在pQTLs的另外三分之一的蛋白质表达中的作用.
结论:
- 基于MS的蛋白质组学为pQTL发现提供了基于亲和力的方法的补充方法.
- 这项研究突出了pQTLs,以前无法接近亲和蛋白质组学,强调了MS平台在更广泛的遗传关联研究中的潜力.
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