Suppr超能文献

使用基于网络的方法注释骨髓增生异常综合征中差异表达的 LincRNAs 的功能。

Annotating function to differentially expressed LincRNAs in myelodysplastic syndrome using a network-based method.

机构信息

Department of Radiology, Center for Bioinformatics and Systems Biology, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA.

Lowy Cancer Research Centre, Prince of Wales Clinical School, University of New South Wales, Sydney, 2052, Australia.

出版信息

Bioinformatics. 2017 Sep 1;33(17):2622-2630. doi: 10.1093/bioinformatics/btx280.

Abstract

MOTIVATION

Long non-coding RNAs (lncRNAs) have been implicated in the regulation of diverse biological functions. The number of newly identified lncRNAs has increased dramatically in recent years but their expression and function have not yet been described from most diseases. To elucidate lncRNA function in human disease, we have developed a novel network based method (NLCFA) integrating correlations between lncRNA, protein coding genes and noncoding miRNAs. We have also integrated target gene associations and protein-protein interactions and designed our model to provide information on the combined influence of mRNAs, lncRNAs and miRNAs on cellular signal transduction networks.

RESULTS

We have generated lncRNA expression profiles from the CD34+ haematopoietic stem and progenitor cells (HSPCs) from patients with Myelodysplastic syndromes (MDS) and healthy donors. We report, for the first time, aberrantly expressed lncRNAs in MDS and further prioritize biologically relevant lncRNAs using the NLCFA. Taken together, our data suggests that aberrant levels of specific lncRNAs are intimately involved in network modules that control multiple cancer-associated signalling pathways and cellular processes. Importantly, our method can be applied to prioritize aberrantly expressed lncRNAs for functional validation in other diseases and biological contexts.

AVAILABILITY AND IMPLEMENTATION

The method is implemented in R language and Matlab.

CONTACT

xizhou@wakehealth.edu.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

摘要

动机

长非编码 RNA(lncRNAs)已被牵涉到多种生物功能的调控中。近年来,新鉴定的 lncRNAs 的数量急剧增加,但它们的表达和功能尚未从大多数疾病中描述。为了阐明 lncRNA 在人类疾病中的功能,我们开发了一种新的基于网络的方法(NLCFA),该方法整合了 lncRNA、蛋白质编码基因和非编码 miRNAs 之间的相关性。我们还整合了靶基因关联和蛋白质-蛋白质相互作用,并设计了我们的模型,以提供关于 mRNAs、lncRNAs 和 miRNAs 对细胞信号转导网络的综合影响的信息。

结果

我们从骨髓增生异常综合征(MDS)患者和健康供体的 CD34+造血干细胞和祖细胞(HSPCs)中生成了 lncRNA 表达谱。我们首次报道了 MDS 中异常表达的 lncRNAs,并使用 NLCFA 进一步优先考虑了具有生物学相关性的 lncRNAs。总之,我们的数据表明,特定 lncRNAs 的异常水平密切参与了控制多种癌症相关信号通路和细胞过程的网络模块。重要的是,我们的方法可用于在其他疾病和生物学背景下优先考虑异常表达的 lncRNAs 进行功能验证。

可用性和实现

该方法在 R 语言和 Matlab 中实现。

联系人

xizhou@wakehealth.edu

补充信息

补充数据可在生物信息学在线获得。

相似文献

引用本文的文献

本文引用的文献

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验