A comparative approarch to genome annotation in Tribolium

该项目需要对用于赤霉菌RNAi筛选的基因和dsRNA模板进行电子计算机鉴定，并开发用于基因发现的生物信息学方法。卡氏锥虫的基因组注释将进一步改进，以获得高通量模板生成的高成功率，并为剩余的约6850个较难正确预测的未筛选基因获得高成功率，因为高表达和更容易预测的基因已经成为iBeetle第一阶段的靶标。在这个项目中，将识别出可能是正确的mRNAs片段，并将其提供给Efuleria公司，用于筛选高效siRNA含量高和脱靶效应最小的区域，用于引物设计和物理dsRNA模板生成。为了增加对已报道的信使核糖核酸片段的信心，从而提高其成功率，将开发一种新的比较基因寻找方法来补充表达证据，并将其应用于目前在布朗实验室(堪萨斯州立大学)进行测序和组装的四个Tribolium物种的基因组。方法开发的目标将超越Tribolium的特定应用，并针对其他基因组密集的真核生物分支，如脊椎动物。将在该项目中设计和实施的新基因预测工具将同时识别所有物种的所有基因。IBeetle Gr-Sta1第3页(共5页)将通过基于多基因组比对的图形结构和其中节点为候选外显子的系统发育树来介绍不同物种的基因结构之间的相互依赖

This project entails the in silico identification of the genes and the dsRNA templates for the RNAi screen of Tribolium castaneum as well as bioinformatics method development for gene-finding. The genome annotation of T. castaneum will be further improved in order to obtain a high success rate for high throughput template generation and of RNAi knockdowns for the remaining roughly 6850 not-yetscreened genes that are harder to correctly predict, because highly expressed and easier to predict genes have been targeted in the first phase of iBeetle already. Likely to be correct fragments of mRNAs will be identified in this project and delivered to the company Eupheria for filtering for regions with high content of efficient siRNAs and minimal off-target effects, for primer design and physical dsRNA template generation. To increase confidence in - and therefore the success rate of - the reported mRNA fragments, a new method for comparative gene finding to supplement expression evidence will be developed and applied to four Tribolium species' genomes that are currently sequenced and assembled in the Brown lab (Kansas State University). The goals of method development will go beyond Tribolium-specific applications and target other genome-dense eukaryotic clades, like vertebrates, too. The new gene prediction tool that will be designed and implemented in this project will identify all genes in all species simultaneously. The iBeetle Gr-Sta1 page 3 of 5 interdependency between the gene structures of different species will be introduced via a graph structure that is based on a multiple genome alignment and a phylogenetic tree in which the nodes are candidate exons