Identification of Quantitative Trait Loci Underlying Proteome Variation in Human Lymphoblastoid Cells
Identification of Quantitative Trait Loci Underlying Proteome Variation in Human Lymphoblastoid Cells
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DOI：
10.1074/mcp.m900378-mcp200
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发表时间：
2010-07-01
影响因子：
7
通讯作者：
Bunger, Maureen K.
中科院分区：
文献类型：
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作者：
Garge, Nikhil;Pan, Huaqin;Bunger, Maureen K.
基于人群的蛋白质表达模式的变异性，特别是在人类中，经常观察到，但了解甚少。此外，人们对个体间遗传变异如何影响蛋白质表达模式知之甚少。为了开始解决这个问题，我们描述了技术和生物学变异的元素，有助于表达的544蛋白在人口的24个人淋巴母细胞样细胞系，已广泛的基因分型的国际HapMap计划的一部分。我们确定10%的蛋白质的表达水平与细胞倍增率密切相关。使用这些淋巴母细胞系的公开可用的基因型，我们应用遗传关联的方法来确定与蛋白质表达变异相关的数量性状基因座。结果鉴定了24种蛋白质形式，对应于15种蛋白质，其中遗传元件负责>50%的表达变异。与蛋白质表达水平相关的遗传变异与编码这些蛋白质形式中的19种的蛋白质转录物的基因顺式定位。四个遗传元件被确定为编码非同义单核苷酸多态性，导致迁移模式的变化，在二维凝胶。这是首次描述大规模蛋白质组学分析，证明人类细胞中基因组和蛋白质组变异之间的直接关系。Molecular & Cellular Proteomics 9：1383-1399，2010.
Population-based variability in protein expression patterns, especially in humans, is often observed but poorly understood. Moreover, very little is known about how interindividual genetic variation contributes to protein expression patterns. To begin to address this, we describe elements of technical and biological variations contributing to expression of 544 proteins in a population of 24 individual human lymphoblastoid cell lines that have been extensively genotyped as part of the International HapMap Project. We determined that expression levels of 10% of the proteins were tightly correlated to cell doubling rates. Using the publicly available genotypes for these lymphoblastoid cell lines, we applied a genetic association approach to identify quantitative trait loci associated with protein expression variation. Results identified 24 protein forms corresponding to 15 proteins for which genetic elements were responsible for >50% of the expression variation. The genetic variation associated with protein expression levels were located in cis with the gene coding for the transcript of the protein for 19 of these protein forms. Four of the genetic elements identified were coding non-synonymous single nucleotide polymorphisms that resulted in migration pattern changes in the two-dimensional gel. This is the first description of large scale proteomics analysis demonstrating the direct relationship between genome and proteome variations in human cells. Molecular & Cellular Proteomics 9: 1383-1399, 2010.