Bioinformatic methods for the investigation of cross-kingdom RNA communication

研究跨界RNA通讯的生物信息学方法

• 批准号: 447603908
• 负责人: Professor Dr. Alexander Goesmann
• 金额: --
• 依托单位: Institut für Bioinformatik und Systembiologie
• 依托单位国家: 德国
• 项目类别: Research Units
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/447603908?language=en
• 关键词: Bioinformatic; methods; investigation; cross; kingdom

Technological advances in terms of high-throughput RNA sequencing and bioinformatics data processing enable cost effective experiments for the investigation of cross-kingdom RNA communication (ckRNAi) in host-microbe interactions. In addition, the effects on the transcriptome of plants and their interacting microbes (viz. pathogens and beneficials) can be studied at an unprecedented level of detail by dual RNA sequencing approaches. With the establishment of many of these data sets, it becomes feasible to implement a comparative perspective to evaluate the effects of different RNA species (e.g. small (s)RNA and mRNA) in different plant-microbe interactions. Within this project, we will automate and standardize the existing analysis protocols and incorporate comparative analyses. We will apply the FAIR (Findable, Accessible, Interoperable, Reusable) principles on data and results. Participation in the consortium facilitates access to the required large-scale data sets and the comparative investigation of ckRNAi effects, whereas the RU5116 and each member of the consortium will benefit from our analysis capabilities for their own projects and for a more comprehensive view on RNA communication in plant-microbe interactions.More specifically, we will support our collaborating partners within this research group by implementing automated analysis workflows that are easy to use, that process, visualize, and compare the results, and that can be scaled-out efficiently in cloud computing environments. Finally, we will also evaluate open-source tools for comparative co-expression network analyses for the extension of our pipelines.

高通量 RNA 测序和生物信息学数据处理方面的技术进步使得能够进行具有成本效益的实验来研究宿主-微生物相互作用中的跨界 RNA 通讯 (ckRNAi)。此外，可以通过双 RNA 测序方法以前所未有的详细程度研究对植物转录组及其相互作用的微生物（即病原体和有益微生物）的影响。随着许多此类数据集的建立，实现比较视角来评估不同 RNA 物种（例如小 (s)RNA 和 mRNA）在不同植物-微生物相互作用中的影响变得可行。在这个项目中，我们将自动化和标准化现有的分析协议并纳入比较分析。我们将在数据和结果上应用公平（Findable、Accessible、Interoperable、Reusable）原则。参与该联盟有助于获取所需的大规模数据集和 ckRNAi 效应的比较研究，而 RU5116 和联盟的每个成员都将受益于我们对自己项目的分析能力，以及对植物-微生物相互作用中 RNA 通讯的更全面的了解。更具体地说，我们将通过实施易于使用的自动化分析工作流程来支持我们在该研究小组内的合作伙伴， 处理、可视化和比较结果，并且可以在云计算环境中有效地横向扩展。最后，我们还将评估用于比较共表达网络分析的开源工具，以扩展我们的管道。