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A computational platform for the high-throughput identification of short RNAs and their targets in plants

用于高通量鉴定植物中短 RNA 及其靶标的计算平台

基本信息

批准号：
BB/E004091/1
负责人：
Vincent Moulton
金额：
$ 31.93万
依托单位：
University of East Anglia
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2007
资助国家：
英国
起止时间：
2007 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=BB%2FE004091%2F1
关键词：
computational platform throughput identification short

项目摘要

Most of the RNA molecules in cells are involved in protein production (ribosomal, transfer or messenger RNAs). However there are RNA molecules with other functions. Two classes of such non-coding RNAs which have been recently discovered are microRNAs (miRNAs) and small interfering RNAs (siRNAs). These regulatory RNA molecules are very short (19-24 nucleotides) and are thus commonly known as short RNAs (sRNAs). Some sRNAs can interact with specific mRNAs because they have partially complementary sequences. As a result of these interactions the expression of the targeted mRNAs is significantly reduced. Other sRNAs can target the chromosomes and trigger DNA modification. More than a hundred miRNAs have been identified in plant species (Arabidopsis, rice and poplar). However, the total number of sRNAs in plants is much higher: A recent experimental study identified about 75,000 sRNAs in Arabidopsis. In addition, several miRNAs found in one species were absent from the other suggesting that there are miRNAs which are specific to certain groups of plants. To systematically identify sRNAs in plants, the co-PIs laboratories have started to use a novel high-throughput sequencing technology (454 pyrosequencing). Initially, they are studying Arabidopsis and later, as the genome sequences will become available, tomato and alfalfa sRNAs will be analysed. This novel technology produces about 200,000 sRNA sequences for each sample. Preliminary results from the 454 technology are currently processed manually using standard bioinformatics tools. However, such an analysis is unfeasible for the millions of sRNA sequences that will be derived from future 454 experiments. The main goal of this project is to develop a computational platform dedicated to the analysis of data generated by the high-throughput 454 sRNA sequencing projects. This platform will classify new sRNAs, some of which will be subjected to further experimental work, and search for possible RNA targets. It will be initially tested on 454 data from Arabidopis, and subsequently on tomato and alfalfa. Later in the project, a comparative analysis tools will be incorporated for mutant analysis. New bioinformatics tools and novel sRNAs discovered through this project will be made publically available. Identifying the full complement of sRNAs in different plant species will allow us to characterise an important and little understood layer of regulation in specific plant traits such as fleshy fruit development and ripening in tomato, and nitrogen fixation in alfalfa.

细胞中的大多数RNA分子参与蛋白质的产生（核糖体、转移或信使RNA）。然而，还有一些RNA分子具有其他功能。最近发现的两类这样的非编码RNA是微小RNA（miRNA）和小干扰RNA（siRNA）。这些调节RNA分子非常短（19-24个核苷酸），因此通常称为短RNA（sRNA）。一些sRNA可以与特定的mRNA相互作用，因为它们具有部分互补序列。作为这些相互作用的结果，靶向mRNA的表达显著降低。其他sRNA可以靶向染色体并触发DNA修饰。在植物物种（拟南芥、水稻和白杨）中已经鉴定出超过100种miRNA。然而，植物中sRNA的总数要高得多：最近的一项实验研究在拟南芥中发现了大约75，000个sRNA。此外，在一个物种中发现的几种miRNAs在另一个物种中不存在，这表明存在特定于某些植物群体的miRNAs。为了系统地鉴定植物中的sRNA，co-PI实验室已经开始使用一种新的高通量测序技术（454焦磷酸测序）。最初，他们正在研究拟南芥，后来，随着基因组序列的可用，番茄和苜蓿sRNAs将被分析。这项新技术为每个样品产生约20万个sRNA序列。454技术的初步结果目前使用标准生物信息学工具进行人工处理。然而，这样的分析是不可行的，将从未来的454个实验中获得数百万的sRNA序列。该项目的主要目标是开发一个计算平台，专门用于分析高通量454 sRNA测序项目产生的数据。该平台将对新的sRNA进行分类，其中一些将进行进一步的实验工作，并寻找可能的RNA靶点。它将首先在454个来自拟南芥的数据上进行测试，然后在番茄和苜蓿上进行测试。在项目后期，将采用比较分析工具进行突变分析。新的生物信息学工具和通过该项目发现的新型sRNAs将在实验室中提供。在不同的植物物种中鉴定sRNA的完整互补将使我们能够在特定的植物性状中发现一个重要的和鲜为人知的调控层，例如番茄的肉质果实发育和成熟，以及苜蓿的固氮。