Identifying susceptible genes for Parkinson disease employing next-generation sequencer

为了确定帕金森病的易感基因，使用下一代测序仪对候选基因(溶酶体储存疾病的负责基因)进行了全面的重新测序分析。我们将帕金森病患者的DNA样本排列成矩形阵列，并按每行和每列(8行8列)形成混合DNA样本集。对每组混合的DNA样本进行候选基因(约24kb)的聚合酶链式反应(PCR)扩增，每组扩增产物混合。根据厂家的说明书，对每组混合扩增片段进行Illumina GAIIx的单通道、单端、100bp的分析，并用BWA与候选基因的参考序列(Hg19)进行比对，每个等位基因的覆盖率约为1,000-2,000。只有超过20个QV的50个碱基对的读数被用于筛选变异体。我们特别关注了未在数据库SNP中注册的罕见变体，并使用整数编程算法搜索此类变体。结果发现，获得了3个未在数据库SNP中注册的变异体；每个变异体都在3个不同的杂合态样本中被鉴定。它们都是非同义的单核苷酸替换。据报道，一个是溶酶体储藏病的病原体，两个是未知的变异体。所有的变异都通过一个额外的直接核苷酸序列分析(Sanger方法)来确认。基于这些结果，我们认为矩阵合并方法是一种检测罕见变异的准确且经济有效的检测方法。

To identify susceptible genes for Parkinson disease, comprehensive resequencing analysis of candidate genes (responsible genes for lysosomal storage disease) employing a next-generation sequencer was conducted. We arranged 64 DNA samples of patients with Parkinson disease in an 8x8 rectangular array, and formed the pooled DNA sample sets by each row and column (8 rows and 8 columns). Each pooled DNA sample set was subjected to PCR amplifications of candidate genes (approximately 24 kb in total) and every amplicons for each set were mixed. The mixed amplicons for each set was subjected to an analysis of single lane of Illumina GAIIx, single-end, 100bp, according to manufactures' instructions.Reads were aligned to the reference sequences (hg19) of candidate genes by BWA with default parameters, and approximately 1,000-2,000 coverage per allele was obtained. Only 50 bp of reads with more than 20 of QV were used to screen variants. We specifically focused on rare variants not registered in dbSNP, and searching for such variants employing an integer programming algorithm. The results were that 3 variants not registered in dbSNP were obtained; each variant was identified in three different samples in the heterozygous state. All of them were nonsynonymous single nucleotide substitutions. One was reported to be pathogenic for a lysosomal storage disease, and two were unknown variants. All variants were confirmed by an additional direct nucleotide sequence analysis (Sanger method).Based on these results, it was suggested that the matrix pooling approach is an accurate and cost effective testing algorithm for detection of rare variants.