Exploiting Natural Genetic and Organismic Variation to Identify the DNA Motifs Regulating Transcription

了解非编码DNA如何调节基因表达对于解决生物学中的无数问题至关重要。 生物技术与人类健康。然而，这一奋进已被证明是一个重大挑战，部分原因是， 基因组似乎编码许多高度复杂的调控网络。特别是在脊椎动物中， 元件如启动子或增强子是高度多样的，并且含有数十个DNA基序， 插入序列。传统的序列分析策略侧重于保守性， 挑选出功能基序，因为调控DNA进化迅速，甚至经常重新定位。 转录起始位点（TSS）是基因调控的标志。精确的TSS能够定义DNA基序 功能上与转录有关。TSS进一步允许锚定和比较调节区域 或跨越进化的直向同源基因，独立于直接序列保守。虽然遥远 相关生物通常缺乏同源的调控DNA，这仍有待探索，在何种程度上特异性 序列基序被选择性地保守以驱动表达基因。因此我开发了加帽的小RNA- seq（csRNA-seq），其准确地映射稳定（蛋白质编码和非编码RNA）和 不稳定转录本（增强子RNA、趋异转录本）以揭示全基因组的活性调节元件。 csRNA-seq仅需要总RNA作为起始材料，因此能够在几乎任何真核生物中进行TSS谱分析。 可以提取RNA的生物体。真核生物，从单细胞原生生物到人类，在器官方面各不相同， 遗传和调控的复杂性。我假设这个频谱的多样性，结合TSS映射 （csRNA-seq），可以用来揭示关键的DNA基序和随后的TF网络，调节 真核生物的基因表达类似于考古学家在史前遗址的工作， TSS沿着生命之树“挖掘”祖先的、不那么复杂的基因调控状态。这些见解 也应该有助于更好地解释人类基因组。为了探索这个核心假设，我试图 1)实施用于分析和可视化csRNA-seq的工具，并促进比较分析 注释跨物种的调控特征，2）鉴定介导转录起始的TF结合位点 3）追踪TF结合位点的进化和使用及其在调控中的空间组织， 直向同源基因或基因组的元件。为了准备，我已经生成了42个真核生物的数据 跨越20亿年的转录组进化，并加入了一个特殊的生物信息学小组， 也提供了一个独特的培训机会，这对我成功过渡到独立至关重要。 如果这项提议成功，将揭示介导转录的主要DNA基序，并显着扩大我们的研究范围。 对真核生物基因调控机制的理解。此外，它将提供一种新的方法， 捕获新生的TSS（csRNA-seq），一个免费的软件套件，以促进分析，一个数据门户，以方便数据 访问和浏览，以及更大的科学界的独特数据集。

Understanding how non-coding DNA regulates gene expression is critical to addressing myriad problems in biotechnology and human health. This endeavor, however, has proven a major challenge, in part, as the genome appears to encode many highly convoluted regulatory networks. Particularly in vertebrates, regulatory elements such as promoters or enhancers are highly diverse and contain of dozens of DNA motifs spaced by intervening sequences. Traditional sequence analysis strategies that focus on conservation are ineffective to single out the functional motifs as regulatory DNA evolves rapidly and often even relocates. The transcription start site (TSS) is a landmark of gene regulation. Accurate TSS enables to define DNA motifs functionally associated with transcription. TSSs further allow anchoring and comparing the regulatory regions or orthologous genes across evolution, independent of direct sequence conservation. Although distantly related organisms typically lack homologous regulatory DNA, it remains to be explored to what extent specific sequence motifs are selectively conserved to drive expression gene. I therefore developed capped small RNA- seq (csRNA-seq), which accurately maps the TSS of both stable (protein coding and non-coding RNAs) and unstable transcripts (enhancer RNAs, divergent transcripts) to reveal active regulatory elements genome-wide. csRNA-seq only requires total RNA as starting material, thus enabling TSSs profiling in virtually any eukaryotic organism from which RNA can be extracted. Eukarya, from unicellular protists to humans, vary in organismic, genetic and regulatory complexity. I hypothesize that this spectrum in diversity, combined with TSS mapping (csRNA-seq), can be exploited to uncover the key DNA motifs and subsequently TF networks that regulate gene expression across the Eukarya. Analogous to the work of an archeologist at prehistoric sites, mapping TSSs along the tree of life ‘excavates’ ancestral, less convoluted states of gene regulation. These insights should also be instrumental to better interpret the human genome. To explore this central hypothesis, I seek to 1) implement tools for the analysis and visualization of csRNA-seq and facilitate the comparative analysis of annotated regulatory features across species, 2) identify the TF binding sites mediating transcription initiation across Eukarya, 3) trace the evolution and usage of TF binding sites and their spatial organization in regulatory elements of orthologous genes or sets of genes. In preparation, I have generated data for 42 Eukarya spanning over 2 billion years of transcriptome evolution and joined an exceptional bioinformatics group, which also provides a unique an opportunity for training critical for my successful transition to independence. This proposal, if successful, will reveal the major DNA motifs mediating transcription and markedly expand our mechanistic understanding of eukaryotic gene regulation. Furthermore, it will provide a novel method to capture nascent TSSs (csRNA-seq), a free software suite to facilitate analysis, a data portal for easy data access and browsing, and unique dataset to the greater scientific community.