Elucidating mechansims and roles of alternative polyadenylation

阐明替代聚腺苷酸化的机制和作用

• 批准号: BB/H002286/1
• 负责人: Gordon Simpson
• 金额: $ 98.74万
• 依托单位: University of Dundee
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2009
• 资助国家: 英国
• 起止时间: 2009 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FH002286%2F1
• 关键词: Elucidating; mechansims; roles; alternative; polyadenylation

Our genes are made of DNA, but when they are switched on, copies are made in a related molecule called RNA and this RNA goes on to code for the protein products of our genes. As the gene is copied into RNA, the RNA is cut and a string of Adenine molecules (A for short) are added at the end. This so-called 'poly A tail' functions to protect the RNA from being degraded, and helps to transport the RNA around the cell and stimulates the formation of protein from the RNA. The site at which the poly A tail is added is not always the same, even for the same gene. For example, half of all human genes have RNAs with more than one site for adding a poly A tail. Controlling the site at which the poly A tail is added is very important because it ultimately affects how genes function. However, this is a process we know surprisingly little about. It's not just human RNAs that have different poly A tails, other animals and plants do too. We have been studying how plants control the time at which they flower, a process where genes are very precisely controlled. In the course of this work, we have discovered that three factors called FCA, FY and, most recently, FPA, function to control poly A site selection of some RNAs. Such basic aspects of gene expression are very similar in plants and animals and it turns out that there are human proteins highly related to FY and FPA. It is possible therefore, that these proteins control poly A site selection in humans too, but very little is known about them. As we have found that FCA and FPA don't need each other to control poly A site choice, we think they must be doing this in different ways. This gives us a chance to understand how poly A site choice can be controlled. In this proposal we plan to build on what we know about FCA and FPA in plants, but this knowledge should be of much more general interest. We want to know two things: (1) How do FCA and FPA control the site at which a poly A tail is added (2) What genes do FCA and FPA regulate by controlling alternative poly A site choice? We will work out how FCA and FPA control poly A sites by identifying the features of the RNA required. This should be quite straightforward. We will make test genes containing different parts of the target gene and see how they affect poly A site selection when placed back in plants. In order to find the other genes whose normal poly A tail depends on FCA and FPA, we will look at where RNAs are polyadenylated in normal plants and in mutant plants that lack FCA or FPA. It is now possible for us to look at nearly all the RNAs in a cell thanks to Next Generation Sequencing, a technology that is revolutionizing modern biology by giving us huge amounts of sequence data, very quickly and at a fraction of the cost to before. This technology has been developed to look at RNA by sequencing a short part of every RNA, sufficient to identify it, called a 'tag'. To find the tag, scientists use the poly A tail and sequence what is next to it. This is a happy coincidence for us, because it means that in addition to tagging a particular RNA, this method also tells us where a poly A tail has been added to RNA. To analyse the large amounts of data and make comparisons, we will need to develop specialized computational tools. Because we already know genes where FCA and FPA control poly A site selection, we should be able to find changes in these 'tags' if our tools are working well. Once we are sure they are, we can look for other shifts in 'tags' to identify other genes controlled by FCA and FPA. As lots of other scientists are also using this sequencing technology, but for completely different reasons, we can use our analysis tools to look at changes in polyadenylation in their data too. In this way we will be able to identify cell-types and situations where alternative polyadenylation is an important part of gene regulation.

我们的基因是由DNA组成的，但是当它们被打开时，在一种叫做RNA的相关分子中复制，这种RNA继续编码我们基因的蛋白质产物。当基因被复制成RNA时，RNA被切割，并在末端添加一串腺嘌呤分子（简称A）。这种所谓的“poly A tail”的功能是保护RNA不被降解，并有助于将RNA运输到细胞周围，刺激RNA形成蛋白质。多聚腺苷酸尾的添加位点并不总是相同的，即使对于相同的基因也是如此。例如，所有人类基因中有一半的RNA具有多于一个添加poly A尾的位点。控制多聚腺苷酸尾的添加位点非常重要，因为它最终会影响基因的功能。然而，这是一个我们所知甚少的过程。不仅仅是人类的RNA有不同的poly A尾，其他动物和植物也有。我们一直在研究植物是如何控制开花时间的，这是一个基因受到非常精确控制的过程。在这项工作的过程中，我们已经发现，三个因素称为FCA，FY和最近，FPA，功能控制多聚A位点选择的一些RNA。这些基因表达的基本方面在植物和动物中非常相似，并且事实证明存在与FY和FPA高度相关的人类蛋白质。因此，这些蛋白质也可能控制人类的多聚腺苷酸位点选择，但人们对它们知之甚少。由于我们发现FCA和FPA并不需要彼此来控制聚A位点的选择，我们认为他们一定是以不同的方式这样做的。这使我们有机会了解如何控制聚A位点的选择。在本提案中，我们计划以我们对工厂中FCA和FPA的了解为基础，但这些知识应该具有更广泛的意义。我们想知道两件事：（1）FCA和FPA如何控制多聚腺苷酸尾的添加位点（2）FCA和FPA通过控制选择性多聚腺苷酸位点来调节哪些基因？我们将研究FCA和FPA如何通过识别所需RNA的特征来控制poly A位点。这应该很简单。我们将使测试基因含有不同部分的目标基因，看看他们如何影响多聚腺苷酸位点选择时，放回植物。为了找到其他基因的正常poly A尾依赖于FCA和FPA，我们将研究在正常植物和缺乏FCA或FPA的突变植物中RNA的聚腺苷酸化位置。由于下一代测序技术，我们现在可以看到细胞中几乎所有的RNA，这项技术通过为我们提供大量的序列数据，非常快速，成本只有以前的一小部分，从而彻底改变了现代生物学。这项技术已经发展到通过对每个RNA的一小部分进行测序来观察RNA，足以识别它，称为“标签”。为了找到标签，科学家们使用聚腺苷酸尾并对其旁边的序列进行测序。这对我们来说是一个令人高兴的巧合，因为这意味着除了标记特定的RNA外，这种方法还告诉我们在RNA的何处添加了聚腺苷酸尾。为了分析大量数据并进行比较，我们需要开发专门的计算工具。因为我们已经知道FCA和FPA控制poly A位点选择的基因，如果我们的工具工作良好，我们应该能够找到这些“标签”的变化。一旦我们确定它们是，我们就可以寻找“标签”中的其他变化，以识别由FCA和FPA控制的其他基因。由于许多其他科学家也在使用这种测序技术，但出于完全不同的原因，我们也可以使用我们的分析工具来查看他们数据中多聚腺苷酸化的变化。通过这种方式，我们将能够识别细胞类型和情况下，替代聚腺苷酸化是基因调控的重要组成部分。

项目成果

The RNA-binding protein FPA regulates flg22-triggered defense responses and transcription factor activity by alternative polyadenylation.

• DOI: 10.1038/srep02866
• 发表时间: 2013-10-09
• 期刊: SCIENTIFIC REPORTS
• 影响因子: 4.6
• 作者: Lyons, Rebecca;Iwase, Akira;Gansewig, Thomas;Sherstnev, Alexander;Duc, Celine;Barton, Geoffrey J.;Hanada, Kousuke;Higuchi-Takeuchi, Mieko;Matsui, Minami;Sugimoto, Keiko;Kazan, Kemal;Simpson, Gordon G.;Shirasu, Ken
• 通讯作者: Shirasu, Ken

Detection and mitigation of spurious antisense expression with RoSA

使用 RoSA 检测和减轻虚假反义表达

• DOI: 10.12688/f1000research.18952.1
• 发表时间: 2019
• 期刊: F1000Research
• 作者: Mourão K

Statistical models for RNA-seq data derived from a two-condition 48-replicate experiment

来自两个条件 48 次重复实验的 RNA-seq 数据的统计模型

• DOI: 10.48550/arxiv.1505.00588
• 发表时间: 2015
• 作者: Gierlinski M

Detection and Mitigation of Spurious Antisense Reads with RoSA

使用 RoSA 检测和减少虚假反义读取

• DOI: 10.1101/425900
• 发表时间: 2018
• 作者: Mourão K

Statistical models for RNA-seq data derived from a two-condition 48-replicate experiment.

• DOI: 10.1093/bioinformatics/btv425
• 发表时间: 2015-11-15
• 期刊: Bioinformatics (Oxford, England)
• 作者: Gierliński M;Cole C;Schofield P;Schurch NJ;Sherstnev A;Singh V;Wrobel N;Gharbi K;Simpson G;Owen-Hughes T;Blaxter M;Barton GJ
• 通讯作者: Barton GJ