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Comparative analysis of miRNA networks regulating flowering

Comparative analysis of miRNA networks regulating flowering
调控开花的miRNA网络的比较分析
批准号:
196931075
负责人:
Professor Dr. Detlef Weigel
金额:
$0.0万
依托单位:
依托单位国家:
德国
项目类别:
Priority Programmes
财政年份:
2011
资助国家:
德国
项目状态:
已结题
起止时间:
2010-12-31 至 2013-12-31

项目摘要

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中文摘要
翻译
在过去的15年中,我们对开花时间控制的遗传和分子基础有了大量的了解,特别是对拟南芥和单子叶水稻这两个物种。然而,将这些知识转移到其他作物和树木并不总是直截了当的,主要有两个原因:首先,我们对物种内部和物种之间的开花时间网络的保护和差异了解不足。其次,人们对开花时间调节剂的多效性知之甚少。本文以模式植物拟南芥(a . thaliana)和芸苔科(Brassicaceae)作物为研究对象,比较分析了控制开花及植物发育和生理其他方面的两个microRNA (miRNA)模块:miR156及其SPL转录因子靶点,miR172及其ap2相关靶点。我们的综合项目包括:(1)序列驱动的方法,利用油菜科快速增加的基因组序列的可用性,加上小RNA群体的超高通量测序;(ii)几个物种的比较表型分析;(三)基因筛选,由于新一代测序技术的最新进展,新突变可以很容易地绘制和分子鉴定。
英文摘要
In the past 15 years we have learned a great deal about the genetic and molecular basis of flowering time control, particularly in two species, the dicot Arabidopsis thaliana and the monocot rice. Transferring this knowledge to other crops and trees has, however, not always been straight-forward, because of two main reasons: First, we have an insufficient understanding of conservation and divergence of flowering time networks within and between species. Second, the pleiotropic effects of flowering time regulators are only poorly understood. Here, we propose a comparative analysis in the Brassicaceae, which include both the model plant A. thaliana and Brassica crops, to investigate two microRNA (miRNA) modules controlling flowering as well as other aspects of plant development and physiology: miR156 and its SPL transcription factor targets, and miR172 and its AP2-related targets. Our integrated program incorporates (i) sequence-driven approaches that exploit the availability of a rapidly increasing number of genome sequences in the Brassicaceae, coupled with ultra-high throughput sequencing of small RNA populations; (ii) comparative phenotypic analyses in several species; and (iii) genetic screens that make use of the incredible ease with which novel mutations can be mapped and molecularly identified due to recent advances in next-generation sequencing technologies.
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