PhosSNP for Systematic Analysis of Genetic Polymorphisms That Influence Protein Phosphorylation
PhosSNP for Systematic Analysis of Genetic Polymorphisms That Influence Protein Phosphorylation
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PhosSNP 用于系统分析影响蛋白质磷酸化的遗传多态性
DOI：
10.1074/mcp.m900273-mcp200
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发表时间：
2010-04-01
影响因子：
7
通讯作者：
Yao, Xuebiao
中科院分区：
文献类型：
--
作者：
Ren, Jian;Jiang, Chunhui;Yao, Xuebiao
我们正在进入个性化基因组学时代，因为测序技术的突破使以高效和准确的方式对个人进行测序或基因分型成为可能。HapMap和其他类似项目的初步结果表明，世界人口和个人之间存在巨大的遗传差异。重要的是要描述这些变异的功能含义，即它们是否影响蛋白质的稳定性和生化性质。人们还普遍认为，基因变异是导致某些疾病的易感性不同或对治疗方法反应不同的主要原因。因此，在人类疾病的背景下理解基因变异就有可能成为“个性化医学”。在这项工作中，我们对可能影响人类蛋白质磷酸化特征的单核苷酸多态(SNPs)进行了全基因组分析。这里，我们将磷酸化相关的SNP(PhosSNP)定义为影响蛋白质磷酸化状态的非同义SNP(NsSNP)。使用内部开发的激酶特异性磷酸化位点预测器(GPS 2.0)，我们通过计算检测到大约70%的已报道的nsSNPs是潜在的phosSNPs。更有趣的是，与这些潜在的phosSNP中的74.6%类似，SNPs也可能导致邻近磷酸化位点的蛋白激酶类型的变化，而不是直接创建或移除磷酸化位点。综上所述，我们认为很大比例的nsSNPs可能会影响蛋白质的磷酸化特性，并在重新连接生物通路中发挥重要作用。最后，所有的phosSNP被整合到PhosSNP 1.0数据库中，该数据库是用Java 1.5(J2SE 5.0)实现的。学术研究人员可以免费获得PhosSNP 1.0数据库。分子与细胞蛋白质组学9：623-634,2010。
We are entering the era of personalized genomics as breakthroughs in sequencing technology have made it possible to sequence or genotype an individual person in an efficient and accurate manner. Preliminary results from HapMap and other similar projects have revealed the existence of tremendous genetic variations among world populations and among individuals. It is important to delineate the functional implication of such variations, i.e. whether they affect the stability and biochemical properties of proteins. It is also generally believed that the genetic variation is the main cause for different susceptibility to certain diseases or different response to therapeutic treatments. Understanding genetic variation in the context of human diseases thus holds the promise for "personalized medicine." In this work, we carried out a genome-wide analysis of single nucleotide polymorphisms (SNPs) that could potentially influence protein phosphorylation characteristics in human. Here, we defined a phosphorylation-related SNP (phosSNP) as a non-synonymous SNP (nsSNP) that affects the protein phosphorylation status. Using an in-house developed kinase-specific phosphorylation site predictor (GPS 2.0), we computationally detected that similar to 70% of the reported nsSNPs are potential phosSNPs. More interestingly, similar to 74.6% of these potential phosSNPs might also induce changes in protein kinase types in adjacent phosphorylation sites rather than creating or removing phosphorylation sites directly. Taken together, we proposed that a large proportion of the nsSNPs might affect protein phosphorylation characteristics and play important roles in rewiring biological pathways. Finally, all phosSNPs were integrated into the PhosSNP 1.0 database, which was implemented in JAVA 1.5 (J2SE 5.0). The PhosSNP 1.0 database is freely available for academic researchers. Molecular & Cellular Proteomics 9: 623-634, 2010.