Back in the field: Eneza @enezer.bsky.social, Maria, and this year’s students are on Spiekeroog again in 2026, continuing to phenotype wild Arabidopsis in 2026. The dataset grows, and the story continues: Watching climate shape plants - in real time, in real environments.
New #preprint 😍‼️ led by 2 incredible postdocs @ninizhani.bsky.social & Ranj Papareddy: transforming #UFMylation from a local ribosome rescue pathway to systems level regulator of mRNA splicing www.biorxiv.org/content/10.6... A short 🧵
Our new experimental evolution study across 30+ locations using the plant Arabidopsis thaliana —— we direct "see" adaptation and extinction to different climates at the genetic as it happens!
Read it in Science
dx.doi.org/10.1126/scie...
@ucberkeleyofficial.bsky.social
@hhmi-science.bsky.social
Together, these approaches help connect lab biology with how plants function in nature, and I’m looking forward to many more exciting findings emerging from these landscape transcriptomic approaches.
They also nicely illustrate how ecology and molecular biology can inform and enrich each other
In contrast, Montalvão et al. sampled plants across many sites. This broad geographic sampling averages over local variation in climate, soil, genotype, plant history, etc.
What emerges are transcriptional programs that operate consistently across environments, i.e. biotic stress-response networks
In Mjema et al.,we reduced spatial complexity:
few sites,many individuals,multiple years,the same populations -> less variation in genotype,soil, neighboring plants,etc. What becomes visible are drivers such as temperature and climate anomalies www.biorxiv.org/content/10.6...
As already pointed out by @plantevolution.bsky.social sky.social, sampling design matters.
Different ways of sampling wild plants can reveal different organizing principles of transcriptomes
It’s exciting to see two recent studies probing Arabidopsis transcriptomes in native environments: Mjema et al. and Montalvão et al.
Both ask how molecular regulation operates in the wild - and arrive at complementary insights into how transcriptomes are organized in nature
Really cool work from @plantevolution.bsky.social and colleagues! In Montalvão et al., they show that native Arabidopsis transcriptomes are strongly shaped by interactions with biotic stressors.
Thanks so much, Detlef! It’s so exciting to explore how insights from the lab translate to real plants in the wild.
This took 5 years, thousands of plants and an amazing collaborative team.
Grateful to everyone who made this landscape transcriptomics approach possible and especially to @enezer.bsky.social for his incredible work and dedication.
Bar chart showing the number of predicted candidate genes associated with different plant traits in winter and spring. Blue bars represent winter and orange bars represent spring. Traits include leaf surface temperature, petiole length ratio, leaf aspect ratio, plant length, number of flowers, stem width, and cauline leaves.
But field variation did more:
It revealed new climate-relevant regulators - including hormone receptors - and generated predictions for >3,000 genes.
Can ecological variability become a discovery engine for gene function?
Network diagram of candidate genes associated with leaf surface temperature responses in Arabidopsis. Two panels compare winter and spring gene interaction networks.
Using paired phenotypes and >1,600 transcriptomes, machine learning recovered canonical temperature-response regulators such as PIF4, demonstrating that master regulators identified in the lab also operate under natural field conditions.
Two-panel figure showing climate variation and plant trait responses. Panel (a) plots monthly air temperature anomalies for five years (2021–2025). The winter–spring months (approximately January to May) are highlighted. The year 2021 shows strong negative temperature anomalies (colder than average), while 2024 shows strong positive anomalies (warmer than average), especially in spring. Panel (b) shows boxplots of petiole length ratio in Arabidopsis plants across the same years. Plants from the warmer year (2024) show higher petiole length ratios compared to colder years such as 2021, indicating longer petioles under warmer conditions. Statistical comparisons between years are indicated above the boxplots.
Temperature anomalies reshaped plant architecture in the wild.
Climate explained up to 17% of trait variation - despite all the noise of real ecosystems.
Map of Germany showing two study locations for wild Arabidopsis thaliana populations: Spiekeroog Island on the North Sea coast and Brachwitz in central Germany. Photographs illustrate the habitats and fieldwork at both sites. Spiekeroog shows sandy coastal dunes and vegetation, while Brachwitz shows a grassy hillside landscape. Additional images show field phenotyping activities, including measuring leaf traits with a ruler, marking plants, and recording leaf surface temperature using an infrared thermometer.
Across 5 years and 2 natural environments, we phenotyped >3000 wild Arabidopsis plants directly in situ in native populations (not sown,transplanted or grown in common gardens). This allowed us to directly observe how climatic variation shapes plant traits in the field.
Excited to share our latest preprint. Arabidopsis thaliana has been the leading model for plant genetics - but most of what we know comes from growth chambers.
Can this model also help us understand how climate shapes plants in the wild and reveal gene functions under real environmental variability?
This took 5 years, thousands of plants, and an amazing collaborative team.
I'm deeply grateful to everyone who made this landscape transcriptomic approach possible - especially @enezer.bsky.social for his incredible work and dedication throughout this project.
Bar chart showing the number of predicted candidate genes associated with different plant traits in winter and spring. Blue bars represent winter and orange bars represent spring. Traits include leaf surface temperature, petiole length ratio, leaf aspect ratio, plant length, number of flowers, stem width, and cauline leaves.
But field variation did more:
It revealed new climate-relevant regulators including hormone receptors, and generated predictions for >3,000 genes.
Can ecological variability become a discovery engine for gene function?
Network diagram of candidate genes associated with leaf surface temperature responses in Arabidopsis. Two panels compare winter and spring gene interaction networks.
Using paired phenotypes + transcriptomes (>1,600), we recovered canonical regulators like PIF4 straight from the field.
Lab-defined circuitry operates in nature
Two-panel figure showing climate variation and plant trait responses. Panel (a) plots monthly air temperature anomalies for five years (2021–2025). The winter–spring months (approximately January to May) are highlighted. The year 2021 shows strong negative temperature anomalies (colder than average), while 2024 shows strong positive anomalies (warmer than average), especially in spring. Panel (b) shows boxplots of petiole length ratio in Arabidopsis plants across the same years. Plants from the warmer year (2024) show higher petiole length ratios compared to colder years such as 2021, indicating longer petioles under warmer conditions. Statistical comparisons between years are indicated above the boxplots.
Temperature anomalies reshaped plant architecture in the wild.
Climate explained up to 17% of trait variation - despite all the noise of real ecosystems.
Map of Germany showing two study locations for wild Arabidopsis thaliana populations: Spiekeroog Island on the North Sea coast and Brachwitz in central Germany. Photographs illustrate the habitats and fieldwork at both sites. Spiekeroog shows sandy coastal dunes and vegetation, while Brachwitz shows a grassy hillside landscape. Additional images show field phenotyping activities, including measuring leaf traits with a ruler, marking plants, and recording leaf surface temperature using an infrared thermometer.
Across 5 years and 2 natural environments, we phenotyped >3000 wild Arabidopsis plants directly in situ - linking climate, phenotype, and transcriptome at the level of individual plants.
Please share! We are looking for a postdoctoral scientist (2 years, extension possible) starting from 01/05/2026 at
@ipbhalle.bsky.social! The project focuses on plant immune receptor biochemistry and structural biology.
Deadline 09/03/2026.
Apply at: ipb-halle.mhm.jobs/11-postdocto...
Wow, we received 10 times more applications than places for the ECR Network Meeting!
The applications are fantastic and we’re already very much looking forward to the event.
We’ll screen applications as quickly as possible. Thanks to everyone who applied!
ECR’s hurry up, only 2 days left, if you want to take part in
3rd Early Career Plant Researchers Network Meeting
Halle (Saale), 20–21 April 2026
⏱️Application deadline is 23rd Jan 2026
#PlantSci
➡️ www.plant-ecr-networking.eu
ECR's: if you want to take part in the
3rd Early Career Plant Researchers Network Meeting
remind the deadline, which is on 23rd January
www.plant-ecr-networking.eu
Poster announcing the 3rd Early Career Plant Researchers Network Meeting, held 20–21 April 2026 in Halle (Saale), Germany. The event targets experienced PhD students and postdoctoral researchers in plant science and features scientific talks, career development and grant-writing workshops, and networking. Travel and accommodation are covered, and participants are registered for the 11th Leibniz Plant Biochemistry Symposium (22–24 April 2026). Application deadline: 23 January 2026. Website: plant-ecr-networking.eu.
Are you an experienced PhD student or postdoc in plant science looking to connect, present your work, and discuss career paths?
Join us at the 3rd Early Career Plant Researchers Network Meeting, Halle (Saale), 20–21 April 2026
Deadline: 23 January 2026
plant-ecr-networking.eu
Finally! The European Union allows the use of genome editing! 🌱🌾🫛🇪🇺🧬
www.tagesschau.de/wirtschaft/v...
We (Nordborg & Weigel labs) need input on the next generation of genome browsers & data download modes for the #Arabidopsis #1001GenomesPlus project. We have now a curated collection of over 500 long read genomes.
Please help us by filling out this questionnaire: docs.google.com/forms/d/e/1F...
And now we have Arabidopsis plants with 8 chromosomes instead of 10 and no obvious phenotypic differences, this week in @science.org
#PlantScience
Paper here: www.science.org/doi/10.1126/...
Perspective here:
www.science.org/doi/10.1126/...
