Dataset Information

Analysis of Arabidopsis thaliana root growth kinetics with high temporal and spatial resolution.

ABSTRACT:

Background

Methods exist to quantify the distribution of growth rate over the root axis. However, non-destructive, high-throughput evaluations of total root elongation in controlled environments and the field are lacking in growth studies. A new imaging approach to analyse total root elongation is described.

Scope

High pixel resolution of the images enables the study of growth in short time intervals and provides high temporal resolution. Using the method described, total root elongation rates are calculated from the displacement of the root tip. Although the absolute root elongation rate changes in response to growth conditions, this set-up enables root growth of Arabidopsis wild-type seedlings to be followed for more than 1 month after germination. The method provides an easy approach to decipher root extension rate and much simpler calculations compared with other methods that use segmental growth to address this question.

Conclusions

The high temporal resolution allows small modifications of total root elongation growth to be revealed. Furthermore, with the options to investigate growth of various mutants in diverse growth conditions the present tool allows modulations in root growth kinetics due to different biotic and abiotic stimuli to be unravelled. Measurements performed on Arabidopsis thaliana wild-type (Col0) plants revealed rhythms superimposed on root elongation. Results obtained from the starchless mutant pgm, however, present a clearly modified pattern. As expected, deviation is strongest during the dark period.

SUBMITTER: Yazdanbakhsh N

PROVIDER: S-EPMC2859919 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Most studies on the biological effects of future climatic changes rely on seasonally aggregated, coarse-resolution data. Such data mask spatial and temporal variability in microclimate driven by terrain, wind and vegetation, and ultimately bear little resemblance to the conditions that organisms experience in the wild. Here, I present the methods for providing fine-grained, hourly and daily estimates of current and future temperature and soil moisture over decadal timescales. Observed climate data and spatially coherent probabilistic projections of daily future weather were disaggregated to hourly and used to drive empirically calibrated physical models of thermal and hydrological microclimates. Mesoclimatic effects (cold-air drainage, coastal exposure and elevation) were determined from the coarse-resolution climate surfaces using thin-plate spline models with coastal exposure and elevation as predictors. Differences between micro and mesoclimate temperatures were determined from terrain, vegetation and ground properties using energy balance equations. Soil moisture was computed in a thin upper layer and an underlying deeper layer, and the exchange of water between these layers was calculated using the van Genuchten equation. Code for processing the data and running the models is provided as a series of R packages. The methods were applied to the Lizard Peninsula, United Kingdom, to provide hourly estimates of temperature (100 m grid resolution over entire area, 1 m for a selected area) for the periods 1983-2017 and 2041-2049. Results indicated that there is a fine-resolution variability in climatic changes, driven primarily by interactions between landscape features and decadal trends in weather conditions. High-temporal resolution extremes in conditions under future climate change were predicted to be considerably less novel than the extremes estimated using seasonally aggregated variables. The study highlights the need to more accurately estimate the future climatic conditions experienced by organisms and equips biologists with the means to do so.