A changing global environment, rising population and increasing demand for biofuels are challenging agriculture and creating a need for technologies to increase biomass production. Here we demonstrate that the inhibition of poly (ADP-ribose) polymerase activity is a promising technology to achieve this under non-stress conditions. Furthermore, we investigate the basis of this growth enhancement via leaf series and kinematic cell analysis as well as single leaf transcriptomics and plant metabolomics under non-stress conditions. These data indicate a regulatory function of PARP within cell growth and potentially development. PARP inhibition enhances growth of Arabidopsis thaliana by enhancing the cell number. Time course single leaf transcriptomics shows that PARP inhibition regulates a small subset of genes which are related to growth promotion, cell cycle and the control of metabolism. This is supported by metabolite analysis showing overall changes in primary and particularly secondary metabolism. Taken together the results indicate a versatile function of PARP beyond its previously reported roles in controlling plant stress tolerance and thus can be a useful target for enhancing biomass production.

BackgroundGrowth is an important parameter to consider when studying the impact of treatments or mutations on plant physiology. Leaf area and growth rates can be estimated efficiently from images of plants, but the experiment setup, image analysis, and statistical evaluation can be laborious, often requiring substantial manual effort and programming skills.ResultsHere we present rosettR, a non-destructive and high-throughput phenotyping protocol for the measurement of total rosette area of seedlings grown in plates in sterile conditions. We demonstrate that our protocol can be used to accurately detect growth differences among different genotypes and in response to light regimes and osmotic stress. rosettR is implemented as a package for the statistical computing software R and provides easy to use functions to design an experiment, analyze the images, and generate reports on quality control as well as a final comparison across genotypes and applied treatments. Experiment procedures are included as part of the package documentation.ConclusionsUsing rosettR it is straight-forward to perform accurate, reproducible measurements of rosette area and relative growth rate with high-throughput using inexpensive equipment. Suitable applications include screening mutant populations for growth phenotypes visible at early growth stages and profiling different genotypes in a wide variety of treatments.