Deciphering the structure-function relationships of long noncoding RNAs

哺乳动物基因组被广泛转录成RNA。在人类中，超过80%的基因组被转录，而不到2%的蛋白质编码。所得的无数转录物主要由长非编码RNA（lncRNA）组成，其是在发育和细胞分化期间表现出高度特异性表达模式的加工转录物。这些最多样化的转录产物显示出比蛋白质编码转录物更高水平的选择性剪接，并且被认为是基因表达和表观遗传状态的重要调控因子。尽管在采用深度RNA测序的研究中鉴定了大量lncRNA，但表征lncRNA的特定生物学功能仍然是一项艰巨的任务，涉及昂贵的实验室实验，这些实验通常范围有限。对于lncRNA的系统功能注释和分类，目前还没有解决方案。我们以前已经表明，至少有13%（可能更多）的人类基因组具有进化保守的RNA二级结构，所有功能性非编码RNA的统一特征，其中大部分位于序列限制区域之外，这表明对更高级结构的纯化选择。我们还开发了将RNA结构聚类到家族中的方法，该方法可用于鉴定与特定生物功能（例如蛋白质结合）相关的结构基序，以及用于全基因组同源性筛选。这些实验表明，RNA结构家族的同源物在整个基因组中重复出现，并优先富集在外显子序列内（相对于外显子-内含子边界）。因此，我们假设这些RNA结构基序作为模块化的功能元件（类似于蛋白质结构域），可以通过选择性剪接选择性组装成lncRNA，并最终决定宿主转录本的分子功能。该建议旨在通过RNA结构基序的全基因组注释和生物化学验证来系统地表征lncRNA的功能。我们将在神经元分化过程中表观遗传重编程的背景下测试我们的假设。利用我们在比较基因组学、机器学习、纳米孔测序和分子生物学方面的专业知识，（i）绘制重复出现的结构RNA结构域的全基因组图谱;（ii）以单分子分辨率解析细胞分化的转录组和表观基因组景观;（iii）证实lncRNA作为基因表达调节因子的功能;和（iv）评估lncRNA中RNA修饰的普遍性及其对RNA结构形成的潜在影响。 总体而言，我们期望在单分子分辨率上解开动物基因表达、表观遗传重编程和发育个体发生的基本机制。

Mammalian genomes are extensively transcribed into RNA. In humans, over 80% of the genome is transcribed while less than 2% codes for proteins. The resulting myriad of transcripts are largely composed of long non-coding RNAs (lncRNAs), processed transcripts that exhibit highly -specific expression patterns during development and cellular differentiation. These most diverse transcriptional products display higher levels of alternative splicing than protein coding transcripts and are recognized as important regulators of gene expression and epigenetic states. Despite multitudes of lncRNAs being identified in studies employing deep RNA sequencing, characterizing the specific biological functions of lncRNAs remains a daunting task involving costly laboratory experiments that are often limited in scope. There are no current solutions for the systematic functional annotation and classification of lncRNAs. We have previously shown that at least 13% (and likely much more) of the human genome harbours evolutionarily conserved RNA secondary structures, a unifying feature of all functional non-coding RNAs, the majority of which lie outside sequence--constrained regions, suggesting purifying selection on higher--order structures. We have also developed methods to cluster RNA structures into families, which can be used to identify structural motifs associated with specific biological functions (e.g. protein binding) and for genome--wide homology screens. These experiments have shown that homologs to RNA structure families recur throughout the genome and are preferentially enriched within exonic sequences (versus exon--intron boundaries). We therefore hypothesize that these RNA structural motifs serve as modular functional elements (akin to protein domains) that can be selectively assembled into lncRNAs through alternative splicing and ultimately dictate the molecular functions of the host transcript. This proposal seeks to systematically characterize the function of lncRNAs through the genome--wide annotation and biochemical validation of RNA structural motifs. We will test our hypotheses in the context of epigenetic reprogramming during neuronal differentiation. Using our expertise in comparative genomics, machine learning, nanopore sequencing and molecular biology, to (i) chart a genome--wide map of recurring structural RNA domains; (ii) resolve the transcriptomic and epigenomic landscape of cellular differentiation at single--molecule resolution; (iii) substantiate the function of lncRNAs as regulators of gene expression; and (iv) Evaluate the prevalence of RNA modifications in lncRNAs and their potential impact on RNA structure formation.  Overall, we expect to unravel the fundamental mechanisms governing gene expression, epigenetic reprogramming and developmental ontogenies of animals at single-molecule resolution.