Prediction of miRNA-mRNA associations in Alzheimer’s disease mice using network topology

摘要: Little is known about the relationship between miRNA and mRNA expression in Alzheimer’s disease (AD) at early- or late-symptomatic stages. Sequence-based target prediction algorithms anti-correlation profiles have been applied to predict targets using omics data, but this approach often leads false positive predictions. Here, we joint profiling analysis of levels Tg6799 AD model mice 4 8 months age a network topology-based method. We constructed gene regulatory networks used PageRank algorithm significant interactions mRNA. In total, 8 cluster modules were predicted by transcriptome data for co-expression pathology. 54 miRNAs identified as being differentially expressed AD. Among these, 50 miRNA-mRNA integrating sequence prediction, analysis, algorithm. set that changed hippocampus mice. determined several candidate genes miRNA. For functional validation primary cultured neurons from (MT) littermate (LM) controls, overexpression ARRDC3 enhanced PPP1R3C expression. showed tendency decrease miR139-5p miR3470a both LM MT cells. Pathological environment created Aβ treatment increased Sfpq did not significantly alter miR3470a. promoter activity cells Our results demonstrate AD-specific changes system well their These help further our understanding function mechanism various molecular pathology