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%的基因组编码蛋白质。由此产生的无数转录本主要由长链非编码rna （lncrna）组成，这些转录本在发育和细胞分化过程中表现出高度特异性的表达模式。这些最多样化的转录产物比蛋白质编码转录物表现出更高水平的选择性剪接，被认为是基因表达和表观遗传状态的重要调节因子。尽管在使用深度RNA测序的研究中发现了大量的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，而且范围往往有限。对于lncrna的系统功能标注和分类，目前还没有解决方案。我们之前已经表明，至少13%（可能更多）的人类基因组含有进化上保守的RNA二级结构，这是所有功能性非编码RNA的一个统一特征，其中大多数位于序列约束区域之外，表明纯化选择在高阶结构上。我们还开发了将RNA结构聚类成家族的方法，这些方法可用于识别与特定生物功能（例如蛋白质结合）相关的结构基序，并用于全基因组同源筛选。这些实验表明，RNA结构家族的同源物在整个基因组中反复出现，并优先富集于外显子序列（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地组装成lncrna，并最终决定宿主转录物的分子功能。本提案旨在通过基因组范围的注释和RNA结构基序的生化验证来系统地表征lncRNAs的功能。我们将在神经元分化过程中的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结构域的基因组图谱；（ii）在单分子分辨率下解决细胞分化的转录组学和表观基因组学景观；（iii）证实lncRNAs作为基因表达调控因子的功能；（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。总之，我们希望在单分子分辨率上揭示动物基因表达、表观遗传重编程和发育性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.