Shommo Ghada, Apolloni Bruno
Sudan University of Science and Technology, Department of Information Technology and Computer Science, Sudan.
Department of Computer Science, Via Comelico 39/41, 20135, Milano, Italy.
Noncoding RNA Res. 2021 Oct 1;6(4):159-166. doi: 10.1016/j.ncrna.2021.09.001. eCollection 2021 Dec.
The regulatory role of the Micro-RNAs (miRNAs) in the messenger RNAs (mRNAs) gene expression is well understood by the biologists since some decades, even though the delving into specific aspects is in progress. In this paper we will focus on miRNA-mRNA modules, where regulation jointly occurs in miRNA-mRNA pairs. Namely, we propose a holistic procedure to identify miRNA-mRNA modules within a population of candidate pairs. Since current methods still leave open issues, we adopt the strategy of postponing any decision on the value of the module ingredients exactly at the end, i.e. at the moment of biologically exploiting the results. This diverts chains of statistical tests into sequences of specially-devised-evolving metrics on the possible solutions. This strategy is rather expensive under a computational perspective, so needing implementations on HPC. The reward stands in the discovery of new modules, possibly hosting non differentially expressed miRNAs and mRNAs and pairs containing genes that currently are considered not targeted. In the paper we implement the procedure on a Multiple Myeloma dataset publicly available on GEO platform, as a template of a cancer instance analysis, and hazard some biological issues. These results, jointly with the normal manageability of the computations, suggest that the discovery procedure may be profitably extended to a wide spectrum of diseases where miRNA-mRNA interactions play a relevant role.
几十年来,生物学家已经很好地理解了微小RNA(miRNA)在信使RNA(mRNA)基因表达中的调控作用,尽管对具体方面的深入研究仍在进行中。在本文中,我们将聚焦于miRNA-mRNA模块,其中调控在miRNA-mRNA对中共同发生。具体而言,我们提出了一种整体方法来在候选对群体中识别miRNA-mRNA模块。由于当前方法仍存在未解决的问题,我们采用在最后才对模块成分的值做出任何决定的策略,即在生物学上利用结果的时刻。这将统计检验链转变为针对可能解决方案的特殊设计的演化度量序列。从计算角度来看,这种策略成本相当高,因此需要在高性能计算(HPC)上实现。其回报在于发现新的模块,这些模块可能包含未差异表达的miRNA和mRNA以及包含目前被认为无靶向作用的基因的对。在本文中,我们在GEO平台上公开可用的多发性骨髓瘤数据集上实施该方法,作为癌症实例分析的模板,并探讨了一些生物学问题。这些结果,连同计算的正常可管理性,表明该发现程序可能有益地扩展到miRNA-mRNA相互作用起相关作用的广泛疾病谱。