Biology subjects

Korte, P.

Publications and source records attributed to Korte, P..

4 recordsLinked to original sources

bioRxiv2025

Under salt stress quinoa stomatal guard cells control transpiration in an ABA-primed manner

O_LIStomatal guard cells, located at the interface between the leaf and the atmosphere, play a key role in transpiration control and photosynthetic CO2 uptake. Halophytes like Chenopodium quinoa tolerate high soil salinity, but the mechanisms governing guard cell responses to salinity stress in relation to the associated epidermal bladder cells (EBCs) remain unknown. C_LIO_LIIn this study, responses of C. quinoa guard cells under salinity stress and external ABA application were analyzed using RNA profiling and voltage-clamp-based electrophysiology. C_LIO_LIUnder salt stress, guard cell RNA profiles reported the activation of ABA synthesis and signaling pathways. However, unlike EBCs, guard cells became transcriptionally insensitive to ABA. Voltage-clamp recordings revealed that under high Na+ concentrations, guard cells activity of K+ uptake channels remained unaffected, while they were impaired in ABA-induced activation of anion channels. As a consequence of a unique guard cell ABA response in salt-adapted plants, stomatal transpiration was reduced and CO2 sensitivity enhanced. C_LIO_LIWe propose that under salt stress, C. quinoa guard cells rewire their hormone signaling to switch from an ABA-sensitive to an ABA-insensitive mode. This adaptation may reflect the halophytes ability to perceive salinity as a non-stressful condition, allowing efficient water usage and sustained growth in saline environments. C_LI

plant biology↗

bioRxiv2025

Rapid adaptation and extinction across climates in synchronized outdoor evolution experiments of Arabidopsis thaliana

Climate change is threatening species with extinction, and rapid evolutionary adaptation may be their only option for population rescue over short ecological timescales. However, direct observations of rapid genetic adaptation and population dynamics across climates are rare across species. To fill this gap, we conducted a replicated, globally synchronized evolution experiment with the plant Arabidopsis thaliana for 5 years in over 30 outdoor experimental gardens with distinct climates across Europe, the Levant, and North America. We performed whole-genome sequencing on [~]70,000 surviving reproductive individuals and directly observed rapid and repeatable adaptation across climates. Allele frequency changes over time were parallel in experimental evolution replicates within the same climates, while they diverged across contrasting climates--with some allele frequency shifts best explained by strong selection between -46% to +60%. Screening the genome for signals of rapid climate adaptation identified a polygenic architecture with both known and novel adaptive genetic variants connected to important ecological phenotypes including environmental stress responses, CAM5 and HEAT SHOCK FACTORs, and germination and spring flowering timing, CYTOCHROME P450s and TSF. We found evolutionary adaptation trends were often predictable, but variable across environments. In warm climates, high evolutionary predictability was associated with population survival up to 5 years, while erratic trends were an early warning for population extinction. Together, these results show rapid climate adaptation may be possible, but understanding its limits across species will be key for biodiversity forecasting.

evolutionary biology↗

bioRxiv2020

Full species-wide leaf and seed ionomic diversity of Arabidopsis thaliana

O_LISoil is a heterogenous reservoir of essential elements needed for plant growth and development. Plants have evolved mechanisms to balance their nutritional needs based on availability of nutrients. This has led to genetically-based variation in the elemental composition ionome, of plants, both within and between species. C_LIO_LIWe explore this natural variation using a panel of wild-collected, geographically widespread Arabidopsis thaliana accessions from the 1001 Genomes Project including over 1,135 accessions, and the 19 parental accessions of the Multi-parent Advanced Generation Inter-Cross (MAGIC) panel, all with full-genome sequences available. C_LIO_LIWe present an experimental design pipeline for high-throughput ionomic screenings and analyses with improved normalisation procedures to account for errors and variability in conditions often encountered in large-scale, high-throughput data collection. We report quantification of the complete leaf and seed ionome of the entire collection using this pipeline and a digital tool-IonExplorer to interact with the dataset. C_LIO_LIWe describe the pattern of natural ionomic variation across the A. thaliana species and identify several accessions with extreme ionomic profiles. It forms a valuable resource for exploratory QTL, GWA studies to identify genes underlying natural variation in leaf and seed ionome and genetic adaptation of plants to soil conditions. C_LI

plant biology↗

bioRxiv2017

Verification of Arabidopsis stock collections using SNPmatch - an algorithm for genotyping high-plexed samples

Large-scale studies such as the Arabidopsis thaliana 1001 Genomes Project aim to understand genetic variation in populations and link it to phenotypic variation. Such studies require routine genotyping of stocks to avoid sample contamination and mix-ups. To genotype samples efficiently and economically, sequencing must be inexpensive and data processing simple. Here we present SNPmatch, a tool which identifies the most likely strain (inbred line, or \"accession\") from a SNP database. We tested the tool by performing low-coverage sequencing of over 2000 strains. SNPmatch could readily genotype samples correctly from 1-fold coverage sequencing data, and could also identify the parents of F1 or F2 individuals. SNPmatch can be run either on the command line or through AraGeno (https://arageno.gmi.oeaw.ac.at), a web interface that permits sample genotyping from a user-uploaded VCF or BED file.\n\nAvailability and implementation: https://github.com/Gregor-Mendel-Institute/SNPmatch.git

genomics↗