Group Leader

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Dr. Karin Köhl
Phone:+49 331 567-8111
Email:Koehl@...

Infrastructure Groups and Service Units

Plant Cultivation and Transformation

The infrastructure group of Dr. Karin Köhl develops and uses reproducible and efficient methods for plant cultivation in controlled environments and the field and performs routine transformations for Arabidopsis and Solanaceae as a service to the entire institute. The scientific work concentrates on abiotic stress tolerance especially under field conditions and the development of data management structures for phenotyping and metadata capture.

Improvement of drought tolerance in potato

Potato is the 3rd most important food crop with more than 50 % produced in developing countries. Potato is water efficient, but not drought tolerant. Thus, reduced water availability due to climate change will decrease yield by up to 30 % in the next decade. The efficient breeding of drought-tolerant cultivars depends on the identification of suitable markers for marker assisted selection (MAS).

<p>Fig 1: Potato cultivars grown at two water supplies (left sufficient water, right drought stress) in a field trial in Golm 2011.</p> Zoom Image

Fig 1: Potato cultivars grown at two water supplies (left sufficient water, right drought stress) in a field trial in Golm 2011.

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Karin Köhl coordinates the projects TROST and VALIDS TROST, in which research institutions and breeders cooperate to establish combined metabolite and transcript marker models for tolerance prediction in European starch cultivars. Tolerance assessed from tuber starch yield in multisite-multiyear drought stress trials (see Fig. 1) varied significantly but was linked to a yield penalty. Cross-validated models predicted drought tolerance from leaf metabolite and transcript concentrations independent of the agro-environment. Presently, the efficiency of the MAS approach is tested in a segregating population by comparing the drought tolerance of MAS selected genotypes to the tolerance of genotypes selected by established methods.

In collaboration with the International Centre for Potato (CIP), we develop morphological drought tolerance markers to overcome the bottleneck of large-scale phenotyping for GWAS studies. We measure growth parameter continuously by autonomous laser scanning to determine derived growth parameter and critical developmental intervals. After validation in African target environments, these markers will accelerate the development of early-maturing-Agile Potato and increase food security in arid environments.

<p><strong>Fig. 2</strong>: Autonomous laser imaging of a segregating potato population under control and drought conditions.</p> Zoom Image

Fig. 2: Autonomous laser imaging of a segregating potato population under control and drought conditions.

Phenotyping and data management

Plant breeding and genetics require fast and exact phenotyping that is reproducible independent of scientist and location. Efficient statistical evaluation of phenotyping data furthermore requires standardised data storage ensuring long-term data availability. We developed a simple and cost-efficient system, the Phenotyper, which employs mobile devices for on-site data entry and open-source software for data management (Köhl and Gremmels, 2015). The Phenotyper provides a well-structured, but flexible data acquisition and management structure for on-site measurements and thus enables efficient automatic data evaluation and data sharing. The Phenotyper system is available to the scientific community from the software project repository of the Bioinformatics organization (Bioinformatics: Phenotyper and source code).

Past data management projects yielded a plant resource and experiment management that is based on the LIMS software Nautius (Köhl et al., 2008) and a management system for plant transformation (Köhl and Gremmels, 2010) and plant cultivation; these systems are in continuous use since 2005 or 2009, respectively.

Arabidopsis field trials

<p><strong>Fig. 3</strong>. <strong>Arabidopsis under field conditions.</strong> Temperature (A) and light intensity fluctuations (B) in the field during seed production of <em>Arabidopsis thaliana</em>. Platform for microclimate measurement (C). Arabidopsis field trial (D). Phenotype of <em>Arabidopsis thaliana</em> under climate-controlled conditions (E) and field conditions (F). Different anthocyanin accumulation in Arabidopsis accessions grown on natural sandy soil in response to photo chilling (G, H).</p> Zoom Image

Fig. 3. Arabidopsis under field conditions. Temperature (A) and light intensity fluctuations (B) in the field during seed production of Arabidopsis thaliana. Platform for microclimate measurement (C). Arabidopsis field trial (D). Phenotype of Arabidopsis thaliana under climate-controlled conditions (E) and field conditions (F). Different anthocyanin accumulation in Arabidopsis accessions grown on natural sandy soil in response to photo chilling (G, H).

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Arabidopsis research is mostly done in controlled environments, in which the effects of up to two environmental factors on the plant are studied. In natural environments, plants face multiple and fluctuating stresses simultaneously, which can create a conflict situation. In this situation, the evolutionary adaptation or the physiological acclimation to one factor can be disadvantageous with the respect to another factor. The fluctuating conditions in the field can result in major differences between phenotypes observed in controlled conditions and in the field, to the extent that mutants that were indistinguishable from the wildtype under controlled conditions lost fitness in the field. We therefore developed a field trial system for Arabidopsis and run a platform for microclimate measurement.

LED

The model species Arabidopsis thaliana is mostly grown under controlled conditions in growth chambers under fluorescent lamps. Light emitting diodes (LED) were suggested as an alternative to improve energy efficiency and long-term stability of light quality. The effect of a change towards LEDs on the reproducibility of results has been tested by measuring plant growth and fitness, photosynthesis (AG Schöttler) and metabolism (AG Fernie).

Isotope Labelling

Plant material labelled with stable, heavy isotopes of C, N and S are produced for metabolite identification by high-resolution mass spectrometry and metabolomics (Giavalisco et al. 2009; 2011).

 
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