LAUSR

The ability to directly measure and monitor poor nutrition in individual animals and ecological communities is hampered by methodological limitations. In this study, we use nutrigenomics to identify nutritional biomarkers in a freshwater zooplankter, Daphnia pulex, a ubiquitous primary consumer in lakes and a sentinel of environmental change. We grew animals in six ecologically relevant nutritional treatments: nutrient replete, low carbon (food), low phosphorus, low nitrogen, low calcium and high Cyanobacteria. We extracted RNA for transcriptome sequencing to identify genes that were nutrient responsive and capable of predicting nutritional status with a high degree of accuracy. We selected a list of 125 candidate genes, which were subsequently pruned to 13 predictive potential biomarkers. Using a nearest‐neighbour classification algorithm, we demonstrate that these potential biomarkers are capable of classifying our samples into the correct nutritional group with 100% accuracy. The functional annotation of the selected biomarkers revealed some specific nutritional pathways and supported our hypothesis that animal responses to poor nutrition are nutrient specific and not simply different presentations of slow growth or energy limitation. This is a key step in uncovering the causes and consequences of nutritional limitation in animal consumers and their responses to small‐ and large‐scale changes in biogeochemical cycles.