Global transcriptome analysis for identification of interactions between coding and noncoding RNAs during human erythroid differentiation
Global transcriptome analysis for identification of interactions between coding and noncoding RNAs during human erythroid differentiation
复制标题
用于鉴定人红细胞分化过程中编码和非编码 RNA 之间相互作用的全局转录组分析
DOI：
10.1007/s11684-016-0452-0
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发表时间：
2016-09-01
影响因子：
8.1
通讯作者：
Fang, Xiangdong
中科院分区：
文献类型：
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作者：
Ding, Nan;Xi, Jiafei;Fang, Xiangdong
近年来，对红系发育过程中的编码基因、miRNAs和lncRNAs的研究不断深入。然而，尚未进行集中于三种RNA类型的整合的分析。在本研究中，我们比较了编码基因，miRNA和lncRNA表达谱的动态。为了探索红细胞生成的动态变化和控制转录组水平这些变化的潜在机制，我们利用高通量测序技术从脐带血造血干细胞和以下四个红系分化阶段以及成熟红细胞中获得转录组数据。结果表明，lncRNA是红系分化的有前途的细胞标记候选物。聚类分析将差异表达基因分为四个亚型，分别对应于干性维持、中期分化和成熟过程中的动态变化。综合分析表明，非编码RNA可能参与控制血细胞成熟，特别是与血红素代谢和对氧自由基和DNA损伤的反应。这些调控相互作用显示在一个全面的网络中，从而推断RNA及其相关功能之间的相关性。这些数据为正常红细胞生成的研究提供了大量的资源，这将允许进一步调查和了解红细胞发育和获得性红细胞疾病。
Studies on coding genes, miRNAs, and lncRNAs during erythroid development have been performed in recent years. However, analysis focusing on the integration of the three RNA types has yet to be done. In the present study, we compared the dynamics of coding genes, miRNA, and lncRNA expression profiles. To explore dynamic changes in erythropoiesis and potential mechanisms that control these changes in the transcriptome level, we took advantage of high throughput sequencing technologies to obtain transcriptome data from cord blood hematopoietic stem cells and the following four erythroid differentiation stages, as well as from mature red blood cells. Results indicated that lncRNAs were promising cell marker candidates for erythroid differentiation. Clustering analysis classified the differentially expressed genes into four subtypes that corresponded to dynamic changes during stemness maintenance, mid-differentiation, and maturation. Integrated analysis revealed that noncoding RNAs potentially participated in controlling blood cell maturation, and especially associated with heme metabolism and responses to oxygen species and DNA damage. These regulatory interactions were displayed in a comprehensive network, thereby inferring correlations between RNAs and their associated functions. These data provided a substantial resource for the study of normal erythropoiesis, which will permit further investigation and understanding of erythroid development and acquired erythroid disorders.