子痫前期易感基因HLA-G SNPs的生物信息学分析和筛选

Bioinformatics analysis and screening of SNPs of preeclampsia susceptible gene HLA-G

目的:应用生物信息学的方法分析疾病相关基因单核苷酸多态性(single nucleotide polymorphisms,SNPs)位点,筛选可导致子痫前期易感基因HLA-G功能变化的SNPs位点。方法:使用SNPper软件从公共数据库dbSNP获得HLA-G编码区的SNPs数据,并下载SNPs位点侧翼序列,使用PARSESNP软件进行分析。结果:在HLA-G基因的编码区发现5个SNPs位点(C343T、C348T、A396T、A466G、C1903T),PSSM Difference分别为19.5、17.4、15.6、6.8和16,其单核苷酸的变化会引发错义突变,且PSSM D ifference>10的突变很可能为有害突变。结论:本文应用生物信息学策略对子痫前期易感基因HLA-G编码区的SNPs进行分析,搜寻对HLA-G基因表达和蛋白质结构及功能产生影响的SNPs,为疾病与基因的关联性研究提供很有价值的信息。

Objective： To analyze the single nucleotide polymorphisms （SNPs） sites of disease - related gene by bioinformatics method, screen the SNPs sites inducing functional changes of HLA - G associated with preeclampsia. Methods ： SNPper software was used to obtain SNPs data in coding region of HLA - G gene from public database （dbSNP） , flanking sequences of SNPs sites were downloaded, PARSESNP software was used for analysis . Results： Five SNPs sites （C343T, C348T, A396T, A466G and C1903T） in coding region of HLA - G gene were found, the PSSM Differences were 19. 5, 17.4, 15.6, 6. 8 and 16, respectively. The changes of single nucleotides induced missense mutation, and the mutation with PSSM Difference 〉 10 was probably detrimental mutation. Conclusion ： Bioinformatics strategies are applied for SNPs analysis in coding region of HLA - G gene, search for the SNPs affecting the expression of HLA - G gene, structure and function of protein, and provide valuable information for studying the correlation between disease and gone.