Quantitative Modeling of MicroRNA:Target Interactions in Cell Fate Transition

MicroRNA 的定量建模：细胞命运转变中的靶标相互作用

• 批准号: 9282625
• 负责人: YE DING
• 金额: $ 54.42万
• 依托单位: WADSWORTH CENTER
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-06-01 至 2020-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9282625
• 关键词: Address; Adult; Algorithms; Amaze; Binding; Binding Sites; Bioinformatics; Biological; Biology; Cell Differentiation process; Cell Fate Control; Cell Lineage; Cells; Cellular biology; Code; Collaborations; Communities; Computer Simulation; Computer software; Data; Databases; Development; Developmental Biology; Disease model; Enzymes; Gene Expression Regulation; Gene Targeting; Genes; Genetic Transcription; Goals; Health; Human; Human Development; Interdisciplinary Study; Internet; Lead; Maps; Measures; Mediating; Messenger RNA; MicroRNAs; Modeling; Molecular; Organism; Outcome; Output; Pattern; Physiology; Pilot Projects; Porifera; Positioning Attribute; Process; Proteins; RNA; RNA Degradation; Regenerative Medicine; Regulation; Research; Role; Seeds; Site; Software Tools; Stem cells; Testing; Therapeutic; Translational Repression; Untranslated RNA; Untranslated Regions; base; cell type; experimental study; high throughput screening; human disease; induced pluripotent stem cell; insight; interdisciplinary approach; next generation sequencing; novel; pluripotency; prediction algorithm; predictive modeling; statistics; tool; transcriptome

Quantitative Modeling of MicroRNA:Target Interactions in Cell Fate Transition Project Summary Cell fate transition is one of the most fundamental processes in biology. Such a transition is often thought to involve the coordinated action of multiple genes. MicroRNAs (miRNAs), an abundant class of small non-coding RNAs, have been postulated as key regulators of cell fate transition. However, complete elucidation of miRNA-mediated gene regulation has been a major challenge, and thus the current understanding of the roles and mechanisms of miRNAs during cell fate transition processes is limited. MiRNAs recognize their messenger RNA (mRNA) targets predominantly through binding sites in the 3ʹ′ untranslated regions (3ʹ′ UTRs). Successful target binding leads to mRNA degradation and/or translational repression. The regulatory outcome on a miRNA target is greatly influenced by the miRNA abundance and sponges, which are RNAs that compete with the target for interaction with the miRNA. These two important factors, and quantitative modeling of seedless site contributions and miRNA:target interactions have been completely ignored by existing miRNA target prediction algorithms. To address these algorithmic limitations for complete elucidation of miRNA regulatory functions, the interdisciplinary research team will 1) quantitatively map miRNA-mediated regulation of key regulators of cell fate transition, and measure miRNA and mRNA expression by next-generation sequencing; 2) develop a novel modeling framework that can address combined effects of seed and seedless sites and incorporate miRNA abundance and sponge effects for quantitative modeling of miRNA:target interactions; 3) predict  miRNA-mediated targeting during induced pluripotent stem cell fate transition; 4) validate miRNA- regulated targeting in cell fate transition and test predicted effects of seedless sites and miRNA and sponge abundance; and 5) disseminate results through database and software tools. This project will result in novel models for quantitative modeling of miRNA:target interactions that can address the effects of both seed and seedless sites, miRNA abundance and sponges. The model can be broadly applicable beyond the context of cell fate transition. The project will also lead to the identification of previously unknown miRNA-targeted genes, and provide key mechanistic insights into the miRNA- regulated control of cell fate transition. This research will significantly advance understanding of miRNA- mediated gene regulation in human development, facilitate development of miRNA-oriented therapeutics, and benefit human health.

microRNA的定量建模：细胞命运过渡中的目标相互作用 项目摘要 细胞脂肪转变是生物学中最基本的过程之一。这种过渡经常被认为 涉及多个基因的协调作用。 microRNA（mirnas），绝对的小类 非编码RNA已被认为是细胞脂肪转变的关键调节剂。但是，完成 阐明miRNA介导的基因调节一直是一个主要挑战，因此 了解miRNA在细胞脂肪过渡过程中的作用和机制是有限的。 miRNA认识到他们的使者RNA（mRNA）主要通过3ʹ'中的结合位点靶向。 未翻译的区域（3ʹ'UTRS）。成功的目标结合导致mRNA降解和/或 翻译表示。 miRNA目标的调节结果受miRNA的影响很大 丰度和海绵是与MiRNA相互作用的靶标的RNA。 这两个重要因素以及无种子位点贡献和miRNA的定量建模：目标 现有的miRNA目标预测算法完全忽略了相互作用。解决 这些算法的限制，用于完全阐明miRNA调节函数，跨学科 研究小组将1）定量绘制miRNA介导的细胞命运关键调节剂调节 过渡，并通过下一代测序测量miRNA和mRNA表达； 2）发展 新型建模框架可以解决种子和无种子地点的综合效果并结合 miRNA的miRNA丰度和赞助商效应miRNA的定量建模：目标相互作用； 3）预测 在诱导多能干细胞脂肪转变过程中，miRNA介导的靶向； 4）验证miRNA- 调节细胞脂肪过渡中的靶向和测试无种子位点和miRNA的预测影响 赞助商丰度； 5）通过数据库和软件工具传播结果。 该项目将导致新型模型用于miRNA的定量建模：可以 解决种子和无种子地位，mirna丰度和海绵的影响。该模型可以是 广泛适用于细胞命运过渡的背景。该项目还将导致身份证明 以前未知的miRNA靶向基因，并为miRNA-提供关键的机械见解 调节细胞命运转变的控制。这项研究将大大提高对miRNA-的理解 人类发育中介导的基因调节，促进以miRNA为导向的治疗的发展， 并受益于人类健康。