High throughput phenomics for diatoms: Challenges and solutions

Abstract

Underpinning primary food chains, atmospheric carbon cycling, and vital ecosystem functions are diatoms, a class of microalgae found ubiquitously in aquatic environments around the globe (Armbrust, 2009; Nelson et al., 1995). As with most organisms on earth climate change threatens their survival and distribution, therefore their ability to adapt to environmental drivers through phenotypic plasticity has become a topic of investigation in recent years (Cox, 2014; Sackett et al., 2013; Vartanian et al., 2009). Furthermore, diatoms are being seen in a new light thanks to recent endeavours to unravel the genomes of a broad range of species across the phylogenetic tree, including the currently underway ‘100 Diatom Genome Project’ and the “Earth BioGenome Project” project which aims to sequence over 3000 protozoa (Bowler et al., 2008; Armbrust, 2009, Joint Genome Institute, 2021; Earth BioGenome Project, 2022; Mock et al., 2022). Knowing the genome is however insufficient in understanding the complex responsivity of an organism exposed to variable environmental conditions, and thus a large-scale diatom phenotyping project is needed. Embarking on such a project that involves a multitude of diverse and intricate organisms will undoubtedly pose challenges. These hurdles stem not only from their extensive genetic diversity, but also from the complex endeavour of consolidating their phenomes. In adapting modern phenomics methods to bridge the genome-phenome gap in diatoms, multi-driver and multi-trait relationships must be considered across a range of species, in which many phenotypes may be expressed under different conditions (Chitwood and Topp, 2015). Armed with comprehensive genomic and phenomic datasets for a range of diatoms, we may be able to predict with more precision the effects of climate change on ecological and biogeochemical processes that are driven by diatom primary productivity.