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

这笔资金部分支持了利用基因组学技术组合确定局部适应的生理和基因组基础的工作。我们能够通过分析基因表达数据来完成之前的工作，从而首次通过多物种分析增强了对淡水昆虫物种适应的理解。结合R程序文库，对应用下一代测序技术获得的RNA-seq数据进行统计分析，并沿纬度梯度检测物种间基因表达。该项目的结果是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以用来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工作的框架，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，在淡水生态系统中收集更多的昆虫，以解决这些石蝇物种基因表达谱的长期时间动态，以提高我们对环境变化背景下基因表达变化的贡献的理解。

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.