PhosSNP for systematic analysis of genetic polymorphisms that influence protein phosphorylation.
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 approximately 70% of the reported nsSNPs are potential phosSNPs. More interestingly, approximately 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.
Ren
Jian
J
Department of Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China.
Jiang
Chunhui
C
Gao
Xinjiao
X
Liu
Zexian
Z
Yuan
Zineng
Z
Jin
Changjiang
C
Wen
Longping
L
Zhang
Zhaolei
Z
Xue
Yu
Y
Yao
Xuebiao
X
D000465:Algorithms; D000595:Amino Acid Sequence; D001665:Binding Sites / Q000235:genetics; D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D055106:Genome-Wide Association Study / Q000379:methods; D006801:Humans; D008954:Models, Biological; D010766:Phosphorylation / Q000235:genetics*; D020641:Polymorphism, Single Nucleotide / Q000502:physiology; D011494:Protein Kinases / Q000378:metabolism; D011499:Protein Processing, Post-Translational / Q000235:genetics*; D011506:Proteins / Q000235:genetics / Q000378:metabolism; D017422:Sequence Analysis, DNA; D020539:Sequence Analysis, Protein
D011506:Proteins; D011494:Protein Kinases