What is the effect of a mutation that "knocks out" a single gene in an organism's genome? Unsatisfyingly, today's plant geneticists can only say: "It depends." Only a small minority of mutations are lethal or have a significant impact. For the vast majority, at most only subtle effects have been detected. Plant genetics is poised to progress rapidly in remedying this situation, using a collection of "knockout" mutant strains of the model species Arabidopsis thaliana. Knockouts, carrying a tiny tagged segment of disruptive DNA in one targeted gene, are already available for ~67% of the 27,000+ unique genes in this plant's genome. Inspired by progress in yeast genetics, the project will grow large subsets of these knockouts in benign and challenging environments, quantifying ecological performance attributes (e.g., population growth rate, fruit yield). We predict that, as in yeast, such an approach will reveal important phenotypic differences between mutant and control lines and possibly reveal undiscovered genome-wide patterns. The project is a collaboration of primarily undergraduate institutions and will train young scientists in how major genomic questions are addressed by networks of researchers.
The project will involve screening 7000 available T-DNA lines to identify those that have mutations at only one gene, providing these results to the biological community. Traits relevant to plant performance will be measured in over 3000 single-mutant lines, across multiple environments. Cyberinfrastructure will be developed to disseminate common protocols and to archive and index data. Over 50 undergraduate researchers will be involved in collecting and analyzing data and communicating results. The project also includes a study of how participating in a distributed research network influences undergraduates' access to social capital within the scientific community. Results from this aspect of the work will lay the foundation for a larger scale, empirical study of the outcomes undergraduates realize by participating in research networks.
