Niklas Reichelt (Doctoral Researcher)
Ningjun Ni (university student)
Plants, as is the case for any living organism, exhibit species-specific thermal tolerance ranges beyond which life comes to an end. Even at optimal growing sites, however, plants may experience short-term temperature extremes that threaten their reproductive success.
Under natural conditions temperatures rise gradually during the course of a bright day. This gradual rise in temperature enables plants to anticipate and adapt to the deadly temperature extremes that may be reached during the late afternoon (when daytime temperatures typically hit their maximum) by triggering an acclimation process resulting in short-term acquired thermotolerance. Despite the fact that the molecular events triggered by a moderate increase in temperature have been well characterised, to date it is not known how plants sense this temperature increase and how the resulting signal is integrated at the cellular level to ultimately result in the acquisition of short-term thermotolerance.
Recent studies suggest that within A. thaliana considerable natural variation exists concerning the extent of the thermal response. This intraspecific variation will be exploited to identify the key molecular components involved in temperature sensing during short-term acquired thermotolerance using an unbiased genome mapping approach that takes advantage of the available Arabidopsis genetic resources. Recently, the genomes of more than 1000 A. thaliana accessions have been sequenced and made publically available by the 1001 Genomes Consortium. This large collection of accessions entirely spanning A. thaliana’s natural geographic range provides an excellent resource for studying the genetic basis of acquired thermotolerance using genome-wide association mapping (GWAS). Currently, we are investigating a suite of temperature-responsive plant traits using a broad array of different methods comprising molecular, analytical as well as more classical plant physiological techniques in order to identify those that are best-suited for the large-scale phenotyping required by GWAS. This will be followed by the actual screening. This project is performed in close collaboration with Prof. Arthur Korte [link] from the Centre for Computational and Theoretical Biology (CCTB).