Progress and promise of omics for predicting the impacts of climate change on harmful algal blooms

Abstract

Climate change is predicted to increase the severity and prevalence of harmful algal blooms (HABs). In the past twenty years, omics techniques such as genomics, transcriptomics, proteomics and metabolomics have transformed that data landscape of many fields including the study of HABs. Advances in technology have facilitated the creation of many publicly available omics datasets that are complementary and shed new light on the mechanisms of HAB formation and toxin production. Genomics have been used to reveal differences in toxicity and nutritional requirements, while transcriptomics and proteomics have been used to explore HAB species responses to environmental stressors, and metabolomics can reveal mechanisms of allelopathy and toxicity. In this review, we explore how omics data may be leveraged to improve predictions of how climate change will impact HAB dynamics. We also highlight important gaps in our knowledge of HAB prediction, which include swimming behaviors, microbial interactions and evolution that can be addressed by future studies with omics tools. Lastly, we discuss approaches to incorporate current omics datasets into predictive numerical models that may enhance HAB prediction in a changing world. With the ever-increasing omics databases, leveraging these data for understanding climate-driven HAB dynamics will be increasingly powerful.