Chen Lei, Chu Chen, Kong Xiangyin, Huang Guohua, Huang Tao, Cai Yu-Dong
College of Information Engineering, Shanghai Maritime University, Shanghai, 201306, People's Republic of China.
State Key Laboratory of Molecular Biology, Shanghai Key Laboratory of Molecular Andrology, Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, 200031, People's Republic of China.
PLoS One. 2015 Mar 13;10(3):e0117090. doi: 10.1371/journal.pone.0117090. eCollection 2015.
Uncovering the molecular mechanisms underlying reproduction is of great importance to infertility treatment and to the generation of healthy offspring. In this study, we discovered novel reproduction-related genes with a hybrid computational method, integrating three different types of method, which offered new clues for further reproduction research. This method was first executed on a weighted graph, constructed based on known protein-protein interactions, to search the shortest paths connecting any two known reproduction-related genes. Genes occurring in these paths were deemed to have a special relationship with reproduction. These newly discovered genes were filtered with a randomization test. Then, the remaining genes were further selected according to their associations with known reproduction-related genes measured by protein-protein interaction score and alignment score obtained by BLAST. The in-depth analysis of the high confidence novel reproduction genes revealed hidden mechanisms of reproduction and provided guidelines for further experimental validations.
揭示生殖背后的分子机制对于不孕症治疗和健康后代的孕育至关重要。在本研究中，我们采用一种混合计算方法发现了与生殖相关的新基因，该方法整合了三种不同类型的方法，为进一步的生殖研究提供了新线索。此方法首先在基于已知蛋白质 - 蛋白质相互作用构建的加权图上执行，以搜索连接任何两个已知生殖相关基因的最短路径。出现在这些路径中的基因被认为与生殖有特殊关系。这些新发现的基因通过随机化检验进行筛选。然后，根据通过蛋白质 - 蛋白质相互作用得分以及通过BLAST获得的比对得分所衡量的与已知生殖相关基因的关联，进一步选择其余基因。对高可信度的新型生殖基因进行深入分析揭示了生殖的隐藏机制，并为进一步的实验验证提供了指导。
