Sun Xiaohan, Zhang Junying
School of Computer Science and Technology, Xidian University, Xi'an 710071, P, R, China.
BMC Bioinformatics. 2014 Jun 17;15:194. doi: 10.1186/1471-2105-15-194.
Schizophrenia is a severe brain disorder, and SNPs (Single nucleotide polymorphism) in schizophrenia-associated miRNAs are believed to be one of the important reasons for dysregulation which might contribute to the altered expression of genes and ultimately result in the disease. Identification of causal SNPs in associated miRNAs may have certain significance in understanding the mechanism of schizophrenia.
For the above purposes, a method based on detection of free energy change is proposed for identification of causal SNPs in schizophrenia-associated miRNAs. A miRNA is firstly segmented, and free energy change is computed after adding an SNP into a segment. The method discovers successfully 6 out of 32 known SNPs and some artificial SNPs could cause significant change in free energy, and among which, 6 known SNPs are supposed to be responsible for most cases of schizophrenia in population.
The proposed method is not only a convenient way to discover causal SNPs in schizophrenia-associated miRNAs without any biochemical assay or sample comparison between cases and controls, but it also has high resolution for causal SNPs even if the SNPs are not reported for their very rare cases in the population. Moreover, the method can be applied to discover the causal SNPs in miRNAs associated with other diseases.
精神分裂症是一种严重的脑部疾病，与精神分裂症相关的微小RNA（miRNA）中的单核苷酸多态性（SNP）被认为是导致失调的重要原因之一，这种失调可能会导致基因表达改变并最终引发该疾病。识别相关miRNA中的因果SNP对于理解精神分裂症的发病机制可能具有一定意义。
为实现上述目的，提出了一种基于检测自由能变化的方法来识别与精神分裂症相关的miRNA中的因果SNP。首先对miRNA进行分段，然后在某一段中添加一个SNP后计算自由能变化。该方法成功发现了32个已知SNP中的6个，并且一些人工SNP可导致自由能发生显著变化，其中6个已知SNP被认为是导致人群中大多数精神分裂症病例的原因。
所提出的方法不仅是一种无需任何生化检测或病例与对照之间的样本比较就能发现与精神分裂症相关的miRNA中因果SNP的便捷方法，而且即使SNP在人群中因极为罕见而未被报道时，该方法对因果SNP仍具有高分辨率。此外，该方法可应用于发现与其他疾病相关的miRNA中的因果SNP。
