Systematic characterization of gene function in the photosynthetic alga Chlamydomonas reinhardtii

Most genes in photosynthetic organisms remain functionally uncharacterized. Here, using a barcoded mutant library of the model eukaryotic alga Chlamydomonas reinhardtii, we determined the phenotypes of more than 58,000 mutants under more than 121 different environmental growth conditions and chemical treatments. 59% of genes are represented by at least one mutant that showed a phenotype, providing clues to the functions of thousands of genes. Mutant phenotypic profiles place uncharacterized genes into functional pathways such as DNA repair, photosynthesis, the CO2-concentrating mechanism, and ciliogenesis. We illustrate the value of this resource by validating novel phenotypes and gene functions, including three novel components of an actin cytoskeleton defense pathway. The data also inform phenotype discovery in land plants: mutants in Arabidopsis thaliana genes exhibit similar phenotypes to those we observed in their Chlamydomonas homologs. We anticipate that this resource will guide the functional characterization of genes across the tree of life.

Methods
To connect genotypes to phenotypes, we measured the growth of 58,101 Chlamydomonas mutants representing 14,695 genes (83% of all genes encoded in the Chlamydomonas genome, based on the current genome annotation, v5.6) under 121 environmental and chemical stress conditions (both control and experimental conditions are given in Supplementary Table 1 and Supplementary Table 2). We pooled the entire Chlamydomonas mutant collection from plates into a liquid culture and used molecular barcodes to quantify the relative abundance of each mutant after competitive growth (Fig. 1a-f). Growth conditions included heterotrophic, mixotrophic, and photoautotrophic growth under different photon flux densities and CO2 concentrations, as well as abiotic stress conditions such as various pH and temperatures. We also subjected the library to known chemical stressors, including DNA damaging agents, reactive oxygen species, antimicrobial drugs such as paromomycin and spectinomycin, as well as the actin-depolymerizing drug latrunculin B (LatB). To further expand the range of stressors in the dataset, we identified 1,222 small molecules from the Library of AcTive Compounds on Arabidopsis (LATCA) that negatively influence Chlamydomonas growth (Supplementary Table 3, Supplementary Data 1), and performed competitive growth experiments in the presence of 52 of the most potent compounds. We chose to screen the LATCA library for active compounds in Chlamydomonas because we believed that these compounds would be more likely to impact pathways both in Chlamydomonas and plants, thus providing more general insights into gene functions in the green lineage. Taken together, this effort represents, to the best of our knowledge, the largest mutant-by-phenotype dataset to date for any photosynthetic organism, with 16.8 million data points (Supplementary Table 4).