Computational analysis of causality between miRNAs and antisense transcription

miRNA 与反义转录之间因果关系的计算分析

• 批准号: 7213770
• 负责人: Christopher Dale Rock
• 金额: $ 20.8万
• 依托单位: TEXAS TECH UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-28 至 2009-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7213770
• 关键词: Address; Affect; Affinity; Algorithms; Animals; Antisense RNA; Apoptosis; Arabidopsis; Bacterial Infections; Base Sequence; Binding; Biogenesis; Biological; Biological Assay; Biological Process; Biology; Blur; Caenorhabditis elegans; Categories; Cell Lineage; Chlamydomonas; Church; Class; Code; Complementary DNA; Complex; Computational Technique; Computer Analysis; Computing Methodologies; Custom; DNA Sequence; DNA-Directed RNA Polymerase; Data; Data Set; Databases; Depth; Development; Disease; Double-Stranded RNA; Drosophila genus; Embryonic Development; Epigenetic Process; Etiology; Eukaryota; Eukaryotic Cell; Evolution; Exons; Functional RNA; Future; Gene Expression; Gene Expression Profile; Gene Expression Regulation; Gene Targeting; Genes; Genetic; Genetic Transcription; Genome; Genomics; Growth and Development function; Hand; Hematopoiesis; Human; Human Genome; Introns; Knock-out; Learning; Length; Life; Light; Link; Malignant Neoplasms; Measures; Mediating; Messenger RNA; Methods; MicroRNAs; Modeling; Molecular; Molecular Profiling; Morphologic artifacts; Mouse-ear Cress; Nature; Neuronal Differentiation; Northern Blotting; Nucleotides; Numbers; Ontology; Organ; Organism; Output; Pattern; Plants; Play; Prevalence; Principal Investigator; Production; Proteins; RNA; RNA Interference; RNA library; RNA-Directed RNA Polymerase; Regulation; Research; Research Personnel; Resources; Rice; Role; Science; Small Interfering RNA; Small RNA; Solutions; Source; Statistical Methods; Structure; System; Testing; Theft; Thermodynamics; Tissues; Transcript; Transcriptional Regulation; Transgenic Organisms; Translations; Untranslated Regions; Validation; Virus Diseases; Work; base; biological adaptation to stress; functional genomics; gene discovery; gene function; gene repression; genome sequencing; human disease; insight; interest; lipid metabolism; mutant; novel; programs; research study; statistics; theories; tool

DESCRIPTION (provided by applicant): Antisense transcription is a widespread and pervasive phenomenon affecting about 25% of eukaryotic genes, but its origins and functions are unknown. Small RNAs such as microRNAs (miRNAs) and trans- acting small-interfering RNAs (ta-siRNAs) are also pervasive in metazoans and plants and play important roles in gene regulation, development, and disease, but to date the predictive power of computational methods for plant and animal small RNA discovery is limited. Based on computational analysis of four independent Arabidopsis transcriptome databases, it is hypothesized that miRNAs and ta-siRNAs are triggers for antisense transcription in Arabidopsis. This hypothesis will be rigorously tested using computational and statistical methods on the entire Arabidopsis and rice genomes. Using known and hypothesized miRNA and ta-siRNA target gene antisense transcription as a learning set, a new algorithm will be developed based on antisense transcription combined with established miRNA prediction methods to discover new candidate miRNAs, ta-siRNAs and their hypothetical target genes. The identified putative small RNA target genes would be inherently "interesting" as potential key regulators of growth and development. The predicted novel small RNAs and their targets will be experimentally validated with a facile transient assay system, RNA blots and rapid amplification of cDNA ends (RACE) to prove novel small RNA- directed cleavage of targets. Transcriptome profiling on whole genome tiling arrays of known mutants that affect small RNAs and antisense transcription will determine the extent of causality of antisense and small RNAs. A novel algorithm for small RNA prediction based on a phenomenon shared between plants and animals may have general utility for small RNA discovery in any organism for which deep genomic resources exist, for genome annotation, and for better understanding of human disease etiologies. Such a predictive tool would also have utility in the fields of functional genomics and evolutionary biology. A better understanding of small RNAs and their roles in gene regulation may shed light on "the RNA World" and the origins of life.

描述（由申请人提供）：反义转录是一种广泛而普遍的现象，影响约25%的真核基因，但其起源和功能尚不清楚。小RNA如微小RNA（miRNA）和反式作用小干扰RNA（ta-siRNA）也普遍存在于后生动物和植物中，并且在基因调控、发育和疾病中发挥重要作用，但迄今为止，用于植物和动物小RNA发现的计算方法的预测能力是有限的。基于对四个独立的拟南芥转录组数据库的计算分析，假设miRNA和ta-siRNA是拟南芥中反义转录的触发因子。这一假设将严格测试使用整个拟南芥和水稻基因组的计算和统计方法。利用已知和假设的miRNA和ta-siRNA靶基因反义转录作为学习集，将开发基于反义转录的新算法，结合已建立的miRNA预测方法，以发现新的候选miRNA、ta-siRNA及其假设的靶基因。所鉴定的推定的小RNA靶基因作为生长和发育的潜在关键调节因子将是固有的“令人感兴趣的”。预测的新型小RNA及其靶标将用简易的瞬时测定系统、RNA印迹和cDNA末端的快速扩增（RACE）进行实验验证，以证明新型小RNA定向的靶标切割。影响小RNA和反义转录的已知突变体的全基因组平铺阵列上的转录组谱分析将确定反义和小RNA的因果关系的程度。基于植物和动物之间共享的现象的小RNA预测的新算法可能对存在深层基因组资源的任何生物体中的小RNA发现、基因组注释以及更好地理解人类疾病病因具有普遍效用。这种预测工具也将在功能基因组学和进化生物学领域中具有实用性。更好地了解小RNA及其在基因调控中的作用可能有助于了解“RNA世界”和生命的起源。