权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

A reconstruction of networks in freshwater ecosystems using genomics and proteomics to assess the strength of vulnerability to climatic change of aquatic insects

利用基因组学和蛋白质组学重建淡水生态系统网络，以评估水生昆虫对气候变化的脆弱性强度

基本信息

批准号：
20K04751
负责人：
ガンボア・メンデスマリベット・アリアナ
金额：
$ 2.75万
依托单位：
Ehime University
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
2020
资助国家：
日本
起止时间：
2020-04-01 至 2021-03-31
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-20K04751/
关键词：
Environmental Engineering Evolution Adaptation Freshwater biology adaptation freshwater climatic change genetics proteomics

项目摘要

The funding support partially the work for identifying the physiological and genomic basis of local adaptation using a combination of genomics techniques. We were able to complete previous work by analyzing gene expression data leading to a first-time enhanced understanding of adaptation in freshwater insect species using multi-species analysis. We conducted statistical analysis on RNA-seq data obtained applying Next-generation of sequencing technology, by a combination of R program libraries and detected gene expression among species along a latitudinal gradient. The result of the project led to detect stress responses of multiple aquatic species due to changes in environmental conditions. The physiological responses detected could be used to predict future environmental change. Notably, our study could serve as a framework for future work on integrating temporary data to further investigate gene-ecosystem models that could improve ecosystem and climate policies. We planned to continue gathering data and collecting more insects in the freshwater ecosystems to resolve the long-term temporal dynamics of gene expression profiles among these stonefly species to improve our understanding of the contributions of gene expression changes within the context of environmental changes.

资金部分支持使用基因组学技术的组合来确定当地适应的生理和基因基础的工作。我们能够通过分析基因表达数据来完成以前的工作，从而首次使用多物种分析增强了对淡水昆虫物种适应性的理解。我们对利用下一代测序技术获得的RNA-seq数据进行了统计分析，通过R程序库的组合，检测了沿着纬度梯度物种间的基因表达。该项目的结果导致检测多种水生物种因环境条件变化而产生的应激反应。检测到的生理反应可用于预测未来的环境变化。值得注意的是，我们的研究可以作为未来整合临时数据的工作框架，以进一步研究可以改善生态系统和气候政策的基因生态系统模型。我们计划继续收集数据，并收集更多的淡水生态系统中的昆虫，以解决这些石首鱼物种之间的基因表达谱的长期时间动态，以提高我们的理解，在环境变化的背景下，基因表达变化的贡献。