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2018 Holiday Movie - Introducing Arabidopsis thaliana

Posted on December 18, 2017

Click to watch: read more

Life on the edge prepares plants for climate change

Posted on December 18, 2017

Paper in Nature Ecology & Evolution on adaptation to climate change read more

Life on the edge prepares plants for climate change

 

 

In the first study to predict whether different populations of the same plant species can adapt to climate change, we found that central European populations of A. thaliana are most at risk.

 

We investigated A. thaliana because it grows across a very wide geographic range. Surprisingly, Scandinavian plants can cope with extreme drought as well as those from Mediterranean countries, according to our study research just published in Nature Ecology and Evolution. This could be because water in the Scandinavian soil is frozen for many months, making it inaccessible to plants and effectively creating drought conditions.

 

We planted seeds collected from over two hundred locations as diverse as North Africa, Spain, central Europe and northern Sweden. After they had germinated under optimal conditions,  we challenged them with severe drought, and recorded their ability to survive this stress. Using large-scale genome sequencing information, specific genetic variants could be linked to the plants’ ability to survive longer. Combined with climate predictions from the Intergovernmental Panel on Climate Change, we could generate maps showing the location of genetic variants key to the species’ future survival.

 

Over the next 50 to 100 years, extreme drought events are predicted to become more and more widespread. This is one of the most challenging consequences of global warming for plants and animals. A steady increase in temperatures is already underway, but this and other studies show that reduced rainfall, which will affect plants and humans alike in a less linear way, is likely to have an even greater effect on survival. By 2070, Central Europe is likely to have much less rainfall than today. Our new research shows that plants in this region do not have the gene variants needed to adapt.  

 

Previous predictions for the distribution of plants or animals in response to climate change have largely ignored the fact that there is often a tremendous amount of genetic variation in a species. For the first time, knowledge about the geographic distribution of genetic variation has been used to map a species’ ability to adapt by natural selection.

 

Role for F-box protein HAWAIIAN SKIRT in miRNA function

Posted on November 22, 2017

New paper in Plant Physiology read more

A role for the F-box protein HAWAIIAN SKIRT in plant microRNA function

Lang PLM, Christie MD, Dogan ES, Schwab R, Hagmann J, Van de Weyer AL, Scacchi E, Weigel D.

Plant Physiol. 2017 Nov 7. doi.org/10.1104/pp.17.01313

As regulators of gene expression in multicellular organisms, microRNAs (miRNAs) are crucial for growth and development. While a plethora of factors involved in their biogenesis and action in Arabidopsis thaliana has been described, these processes and their fine-tuning are not fully understood. Here, we used plants expressing an artificial miRNA target mimic (MIM) to screen for negative regulators of miR156. We identified a new mutant allele of the F-box gene HAWAIIAN SKIRT (HWS; At3G61590), hws-5, as a suppressor of the MIM156-induced developmental and molecular phenotypes. In hws plants, levels of some endogenous miRNAs are increased and their mRNA targets decreased. Plants constitutively expressing full-length HWS - but not a truncated version lacking the F-box domain - display morphological and molecular phenotypes resembling those of mutants defective in miRNA biogenesis and activity. In combination with such mutants, hws loses its delayed floral organ abscission ('skirt') phenotype, suggesting epistasis. Also, the hws transcriptome profile partially resembles those of well-known miRNA mutants hyl1-2, se-3 and ago1-27, pointing to a role in a common pathway. We thus propose HWS as a novel, F-box dependent factor involved in miRNA function.

Congratulations, Dr. Giovanna Capovilla!

Posted on October 09, 2017

Giovanna successfully defended her PhD thesis entitled 'Exploring the role of temperature regulated alternative splicing in flowering time and morphogenesis' read more

Congratulations, Giovanna!

Maus Türöffner Tag

Posted on October 03, 2017

How we sequence DNA - teaching lab for kids read more

As big fans of Die Maus, we participated in this year's open house event and showed how DNA can be extracted, read and sequenced. 

Big thanks to all kids for a fun day!

6th bioRxiv of 2017: Massive field data from rain manipulation

Posted on September 11, 2017

Field experiment with 517 A. thaliana accessions in Madrid & Tübingen read more

A rainfall-manipulation experiment with 517 Arabidopsis thaliana accessions

Exposito-Alonso et al. https://doi.org/10.1101/186767

The gold standard for studying natural selection is to quantify lifetime fitness in individuals from natural populations that have been grown together under different field conditions. This has been widely done in ecology to measure phenotypic selection in nature for a wide range of organisms -- an evolutionary force that seems to be most determined by local precipitation patterns. Studies that include whole-genome data would enable the translation of coefficients of selection to the genetic level, but such studies are still scarce, even though this type of genetic knowledge will be critical to predict the effect of climate change in natural populations. Here we present such an experiment including rainfall-manipulation with the plant Arabidopsis thaliana. The experiment was carried out in a Mediterranean and a Central European field station with rainout shelters to simulate a high and low rainfall treatment within each location. For each treatment combination, we planted 7 pots with one individual and 5 pots with 30 counted seeds of 517 whole-genome sequenced natural accessions covering the global species distribution. Survival, germination, flowering time, and final seed output were measured for ca. 25,000 pots, which contained ca. 14,500 individual plants and over 310,00 plants growing in small populations. This high-throughput phenotyping was only possible thanks to image analysis techniques using custom-made scripts. To make the data and processing code available, we created an R package dryAR (http://github.com/MoisesExpositoAlonso/dryAR).

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