Tools for motif recognition in fungi

真菌基序识别工具

• 批准号: BB/G000573/1
• 负责人: Prudence Wong
• 金额: $ 13.13万
• 依托单位: University of Liverpool
• 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%2FG000573%2F1
• 关键词: Tools; motif; recognition; fungi

Recent technical advances in molecular genetics have made it possible to efficiently sequence the full complement of an organism's DNA (the genome), giving us the code that defines the makeup of that species. This will have many benefits in medicine, agriculture and biotechnology, as we are in a much better position to understand the fundamental processes and components that underlie the biology all around us. However, the mass of data is somewhat overwhelming, with each organism's genome extending to a code of many millions of bases. Therefore it is important that we develop new and efficient approaches to uncover the coded information it contains. For a long time we have understood the basics of how a gene is arranged and in particular how the three letter nucleic acid code can be interpreted as an amino acid code that makes up the proteins of the cell. But this is only part of the story, and even finding genes can be difficult at times. This project will aim to uncover the essential information that determines when genes are switched on and at what level. These regulatory sequences are also encoded, often near the genes themselves, but are much harder to identify. We hope to apply and develop computational analyses to allow us to rapidly compare relevant parts of a number of genome sequences simultaneously and thereby advance our understanding of the complex higher order code that defines gene expression. Our chosen organisms are the Aspergilli, which are responsible for various human and animal diseases, crop damage and the production of toxins as well as playing an important role in both the biotechnology and food industries. Because of their importance, many have been sequenced providing us with an ideal system for developing and testing new computational approaches. Tools for experimental testing of computer-generated hypotheses are also readily available.

分子遗传学的最新技术进步使得有效地对生物体DNA（基因组）的完整序列进行测序成为可能，为我们提供了定义该物种组成的代码。这将对医学、农业和生物技术产生许多好处，因为我们能够更好地了解我们周围生物学的基本过程和组成部分。然而，大量的数据有点压倒性，每个生物体的基因组扩展到数百万个碱基的代码。因此，重要的是我们开发新的和有效的方法来揭示它包含的编码信息。很长一段时间以来，我们已经了解了基因是如何排列的基础知识，特别是三个字母的核酸密码如何被解释为构成细胞蛋白质的氨基酸密码。但这只是故事的一部分，有时甚至找到基因也很困难。该项目旨在揭示决定基因何时开启以及开启水平的基本信息。这些调控序列也被编码，通常靠近基因本身，但更难识别。我们希望应用和开发计算分析，使我们能够快速比较一些基因组序列的相关部分，同时，从而推进我们的复杂的高阶代码，定义基因表达的理解。我们选择的生物体是黑曲霉，它是造成各种人类和动物疾病、农作物损害和毒素产生的原因，在生物技术和食品工业中发挥着重要作用。由于它们的重要性，许多已经被排序，为我们提供了开发和测试新计算方法的理想系统。对计算机生成的假设进行实验测试的工具也很容易获得。

项目成果

Transcriptome analysis of the filamentous fungus Aspergillus nidulans directed to the global identification of promoters.

• DOI: 10.1186/1471-2164-14-847
• 发表时间: 2013-12-03
• 期刊: BMC genomics
• 影响因子: 4.4
• 作者: Sibthorp C;Wu H;Cowley G;Wong PW;Palaima P;Morozov IY;Weedall GD;Caddick MX
• 通讯作者: Caddick MX