Identifying transcriptomic indicators of growth rate and environmental stress in marine phytoplankton

海洋浮游植物是一种极其多样化的生物，它们完成了地球上大约一半的光合作用，在碳循环中起着关键作用。气候变暖预计会对影响海洋浮游植物群落生产力和分类组成的环境条件产生巨大影响。浮游植物的多样性和复杂的进化史给建模者提出了挑战，他们试图预测浮游植物生产力和生物地理的变化，以及气候变暖对生物地球化学的后续影响。成千上万的浮游生物通常被分为几种功能类型，这些功能类型是由少数生态和生理特征区分的，这些特征很少受到数据的约束。转录组学可以用于监测浮游植物群落的基因表达，并为我们提供更多的机制理解不同浮游植物物种和/或功能群如何以及为什么响应不断变化的环境条件。在此，我们提出在受控实验室培养中，在几个生态重要的海洋浮游植物分类群中，鉴定不同时间尺度下与生长速度和对几种环境条件的驯化相关的差异表达基因，从短暂的新环境条件应用到多代驯化。这项工作将使我们能够识别与浮游植物生长速度和对环境条件的适应相关的通用转录组信号，并将提供一个数据库的开端，该数据库可用于解释从野外获取的越来越多的海洋浮游植物亚转录组，并有助于确定下一代生物地球化学模型中浮游植物功能群的关键性状的遗传基础。

Marine phytoplankton are an extremely diverse group of organisms that perform about half the photosynthesis on Earth and play a key role in the carbon cycle. Climate warming is expected have dramatic effects on environmental conditions that influence both the productivity and taxonomic composition of marine phytoplankton communities. The diversity and complex evolutionary history of the phytoplankton presents challenges for modelers who seek to project changes to phytoplankton productivity and biogeography and subsequent impacts on biogeochemistry in response to climate warming. Thousands of plankton species are routinely grouped into a few functional types, that are distinguished by a small number of ecological and physiological traits that that are poorly constrained by data. Transcriptomics can be used to monitor gene expression of phytoplankton communities in situ and provide us with a much more mechanistic understanding of how and why different phytoplankton species and/or functional groups respond to changing environmental conditions. Here we propose to identify differentially expressed genes associated with growth rate and with acclimation to several environmental conditions under different time-scales from transient application of a new environmental condition to multi-generation acclimation, across several ecologically important marine phytoplankton taxa in controlled lab cultures. This work will allow us to identify universal transcriptomic signals associated with phytoplankton growth rate and acclimation to environmental conditions, and will provide the beginnings of a database that can be used to interpret the increasing number of marine phytoplankton metatranscriptomes taken from the field, and facilitate the identification of the genetic bases of key traits that define phytoplankton functional groups for next-generation biogeochemical models.