This project will generate physical and data resources that will dramatically advance understanding of the functions of thousands of genes in photosynthetic organisms. Photosynthetic organisms provide food and energy for nearly all life on Earth, yet most of their genes remain uncharacterized. This project will expand the availability of mutants needed to study the functions of genes in the single-celled model photosynthetic alga Chlamydomonas reinhardtii. The new project will use the newly generated mutants to identify relationships between genes and observable characteristics and will allow genes to be assigned to genetic pathways on an unprecedented scale. The resulting mutants will be available to the research community via the Chlamydomonas Resource Center, and the resulting data will be searchable on a website. The basic knowledge and resources generated by this project will lay the groundwork for advances in biotechnology, agriculture, and health. The placement of thousands of genes into pathways will identify new opportunities for pathway engineering in photosynthetic organisms. Mutants with enhanced or deficient growth in specific environments will reveal genetic targets for enhancing resistance of crops to a broad range of stresses. Mutants with defects in cilia will advance our structural and molecular understanding of these organelles, which play key roles in development and disease. The project will enhance infrastructure for research and education by providing urgently needed high-quality disruption mutants for many genes. The project will directly contribute to the training of many undergraduates, college graduates, and a postdoctoral fellow, and will advance the training of countless young researchers as they use the resources produced.
The project builds on the team's success in developing the existing Chlamydomonas mutant resource and extensive preliminary studies demonstrating that mutant phenotypes can be assessed in pools, where each mutant's growth rate is tracked by measuring the abundance of its unique DNA barcode. High confidence in a genotype-phenotype relationship requires three independent high-confidence alleles disrupting the gene of interest. The first aim of this project is to increase from 9% to 84% the percentage of genes covered with three high-confidence disruptions by improving the mapping accuracy of existing mutants and by generating additional mutants. The second aim is to systematically assign genes to pathways by identifying high-confidence genotype-phenotype relationships across the genome. The phenotypes of 70,000 mutants will be determined under hundreds of conditions, half of which will be selected by the community. Genes will be clustered into pathways based on the principle that mutants affected in in the same pathway show a similar pattern of phenotypes across a broad range of conditions. The third aim is to make the resulting mutants and data broadly available to the research community. Mutants generated by the project will complement the Chlamydomonas Resource Center's existing collection by providing coverage for genes not currently represented. Insertion sites, mutant and gene phenotypes, and gene pathway assignments will be searchable online. This project will transform our understanding of photosynthetic organisms by producing a comprehensive genotype-phenotype map. The availability of mutants and phenotypes will allow the community to make rapid progress on determining the molecular functions of uncharacterized genes and the proteins they encode.
This award was jointly funded by the Systems and Synthetic Biology Program and the Genetic Mechanisms Program in the Division of Molecular and Cellular Biosciences and by the Infrastructure Capacity for Biology Program / Collections in Support of Biological Research in the Division of Biological Infrastructure. All three programs are in the Biological Sciences Directorate.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
