“High-throughput phenotyping of IncCOBRA1 and DXO1 mutants in Arabidopsis”

Project Summary:

Improvements in phenotyping using computational methods can allow for more accurately collected and analyzed phenotypic data that plant scientist can use to study biological processes. Using two different types of mutants, one with possible subtle effects and another with possible great defects on growth rate, phenotypic tools were used to both confirm these effects and test the tools themselves. lncCOBRA1 is a part of the CONSERVED IN BRASSICA RAPA(COBRA) lncRNAs that are associated with plant growth. DXO1 is a protein that marks NAD+ mRNAs for degradation and null mutants of DXO1 have severely stunted plant growth. The mutant genotypes include lnccobra1-1 (reduced expression of lncCOBRA1 created using T-DNA), lnccobra1-2 (complete deletion of lncCOBRA1 created using CRISPR), and dxo1-2 (null mutant created using T-DNA). Arabidopsis control and mutant genotypes were grown for about three weeks. Phenotyping rigs developed by the Julkowska/Nelson labs with a Raspberry Pi camera module were used to collect images in 30-minute intervals. The images were analyzed using PlantCV, an open-source image software that can quantify plant phenotypes using jpg images, and further data analysis pipelines. lncCOBRA1 and DXO1 mutants’ growth rate were compared to their respective wildtypes. lncCOBRA1 mutants had subtle significant differences in growth rate while DXO1 mutants had great significant differences in growth rate. Further improvements on phenotyping will allow for a variety of different plant phenotypes that can be better analyzed and a more user-friendly interface to allow scientists to use the analytical pipeline.

My Experience:

This summer, I learned a lot about computational science, which was an invaluable skill to learn for a future scientist. I improved my computer skills while also learning how to connect those skills to plant science research. I found out how important it is to learn even the basics of bioinformatics to be able to choose the best option for gathering data for your specific project. I was able to spend the summer watching what plant scientist work on daily and how even the smallest detail in your work can matter tremendously…especially when it comes to coding. It was a great experience to contribute even a little to the longer ongoing work of several scientists. The collaboration between the labs at BTI was also amazing to be a part of since I was able to meet and connect with many people.

 Credit: BTI Education and Outreach and UC Berkeley Resource for Undergraduates.