Team

I started out as a developmental biologist, but over the past two decades years, my lab has come to focus more and more on questions of evolution. We investigate these both from a genomic perspective and starting from phenotypes, primarily, but not exclusively in Arabidopsis thaliana. The most recent addition is a strong investment in plant-microbe interactions, including natural microbiomes; see our PATHOCOM project! I am an elected member of the US National Academy of Sciences, the Royal Society, the German National Academy of Sciences and EMBO. I have served or am serving on many advisory and editorial boards and have co-founded three biotech start-ups.

My work focuses on challenges associated with Next Generation Sequencing. Apart from operating the instruments, I am involved in various research projects.

My work as a technician in the group focuses on molecular and plant projects aimed at identifying hybrid incompatibilities and characterizing the underlying causal genes. Starting mid of 2021, I am also involved in a PacBio sequencing project. Aside from research, I am lab safety person and have several organizational tasks that help the department run smoothly.

One area of interest for my research is understanding what shapes genome diversity and investigating how we can artificially increase genomic diversity and accelerate domestication processes. Figuring out these questions may not only be important for improving plant breeding, but it also holds promise for halting the wave of extinctions the world is experiencing and for determining strategies to mitigate it. I am convinced that transposable elements (TEs) will be a key element in addressing these challenges.

I am interested in deciphering the genetic basis of adaptation and phenotypic plasticity of flowering time of plants, especially in response to changing environmental conditions. I use natural variation as a resource of genetic diversity to identify new alleles of known genes to better understand gene function, regulation, and interaction. Employing CRISPR/Cas9 technology, I investigate GxG interaction by testing a deleterious genetic deletion in a large set of natural Arabidopsis genetic backgrounds. I also work on herbicide resistance of Alopecurus myosuroides (black-grass), a plant species classified as a weed. Several next generation sequencing technologies and methods are applied to study the dynamics of resistance dispersion and the population structure of local and nationwide samples.

The plant epigenome is at the base of intraspecific variation and environmental adaptation. DNA methylation and histone modification patterns lead to chromatin alteration and transposable element (TE) silencing. To assess TE insertion polymorphisms, I am using PacBio HiFi reads for generating chromosome-level genome assemblies of different Arabidopsis thaliana accessions. I am integrating these genomes with epigenetic variation data from wildtypes and mutants defective for epigenetic pathways. This intersection will shed light onto chromatin and TE dynamics.

Ribosomes are responsible for protein synthesis and they are essential for cellular growth. Perhaps due to their essential role in the central dogma of molecular biology, ribosomes have generally been regarded as immutable homogeneous machines. Nevertheless, in eukaryotic genomes, multiple functional paralogous genes exist for each of the ~80 ribosomal proteins, indicating that diversification might be more widespread than thought. By analyzing long-read based A. thaliana genome assemblies, I investigate the extent of intraspecies ribosome heterogeneity and its functional implications.

Hybrid vigor, a key example of system-level emergence, already intrigued Darwin. Whether it constitutes a single phenomenon or rather a collection of syndromes, and whether hybrids are equipped to bypass classical life-history trade-offs, remain unclear. Taking a systematic approach, I study the genetic, transcriptomic, and phenotypic covariance in a large number of Arabidopsis thaliana F1 hybrids, and strive to understand how genetic variants combine in the F1s, the mode of gene expression, the associated pathways, as well as the potential cost to the apparent growth vigor.

Mutations are raw materials for evolution. Detecting mutations precisely and comprehensively is a challenge due to the repeat nature of plant genomes. Haplotype-resolved T2T assembly is the perfect foundation for variant calling. I am working on variant calling with population-scale assemblies by pangenome graphs. Adaptive complex genome rearrangements cannot be simply represented by pairwise comparisons within two individuals. How to accurately represent the multi-allele and complex nature of these variants remains an open problem. The consequence of complex rearrangements brings the birth and death of coding genes. Annotating genes with high accuracy and then combining them into a pangenome graph is the new challenge in the pangenome era.

I work on pipelines for high throughput processing of short and long read sequencing data and automated image-based phenotyping. I support department members in their research projects and am the data protection coordinator of the institute.

Genomes across the tree of life comprise variable amounts of repetitive sequences. Transposable elements (TEs) are predominant among eukaryotic repeated sequences and largely contribute to genome size variation. TEs are important in the generation of genetic diversity among populations. However, little is known about the evolution of TE sequences over long periods of time. I study the variation in TE sequences using high-quality genome assemblies to understand the mutational processes affecting TE insertions over time.

With the availability of state-of-the-art sequencing resources, I'm interested in spontaneous mutation and sequence variants in A. thaliana.

Due to local adaptation and population structure, genomes of different individuals can vary to a great extent. To represent this variation, we utilize the concept of variation graphs, which provide a powerful toolkit. I am working to combine these genome graphs with genome-wide-association (GWA) approaches to connect complex genomic variation with organism traits. Beginning with multiple whole-genome assemblies, I will first tackle the problem of graph construction, providing an accurate representation of genomic variation and the basis of the analysis.

Single reference genome can't represent all information within a species. With the decline in sequencing prices and the development of long-read sequencing technologies, we can assemble more genomes within a species to construct pangenomes. Relative to the linear reference genome, a genome graph is a more efficient way for information storage. In addition to short variants (SNPs/Indels), long variants (SVs) also play an important role in biological process. Using long reads, SVs can be accurately detected.

Exposure to bacterial pathogens and symbionts plays a major role in shaping plant genomes through the course of evolution. My research focuses on identifying genomic signatures of plant-bacterial interactions in order to discover and understand plant adaptations to biotic stress. As a bioinformatician, I address these questions by developing computational methods, which take advantage of rich sequence data, such as population-level genomics. Specifically, I employ a comparative-genomics approach, which frames the analysis of sequence information in the context of the underlying evolutionary process.

I am part of the PATHOCOM project team and involved in samples collection and sequencing efforts. Additionally I support the lab members in various projects and take care of the day-to-day lab operations.

I am fascinated by the interaction of plants with their natural environment. Plants constantly process favourable or less favourable environmental stimuli and can withstand even the harshest conditions. I want to know how plants do that together with their microbiome. In my research I use a wide array of methods to understand plant-microbe interactions ranging from field work to molecular biology, genomics, bioinformatics and plant-microbe interaction assays. In the Weigel lab I work as part of the PATHOCOM project. My role in the PATHOCOM project is to study the effect of microbe-microbe interactions in the plant Arabidopsis thaliana with ultra-high-throughput experimental testing. This experimental data will be used to model interaction patterns to understand how microbe-microbe, plant-microbe interactions and microbial community composition are shaped in nature.

Pseudomonas is one of the most common plant pathogens, and can infect a wide range of species. However, infection potential varies greatly between individual Pseudomonas isolates, in part due to their specific repertoire of effectors. I am interested in how genetic variation of both host and pathogen impacts the outcome of infection. To address this question, I use a natural Arabidopsis – Pseudomonas pathosystem, as Arabidopsis thaliana is a host to different strains of Pseudomonas species in the wild.

My primary goal is to make sure the lab is running smoothly. Additionally, I am part of the PATHOCOM project team. PATHOCOM seeks to understand how microbial communities develop and how microbe-host and microbe-microbe interactions shape community composition and structure. Specifically, we examine the community relationships within Arabidopsis thaliana and its major bacterial leaf microbes, using a variety of field, molecular, and experimental techniques.

After the sampling action of Hyaloperonospora arabidopsidis in the wild as part of the project Pathodopsis, this oomycete caught my interest not only as a chance to do field work also on the molecular level. I am highly interested in the coevolutionary pattern between the obligate biotroph and its host. One signature of tracking this process is to concentrate on virulence factors. I am focusing on the role of pathogenic effector variants on a European-wide scale.

I am interested in various fundamental and applied aspects of plant health. Therefore, I joined the PATHOCOM Project to investigate both in the field and laboratory pathogenic (bacterial) communities and their patterns of development and interactions at the ecological and genetic levels. In this project we aim to understand how microbial communities evolve and how interactions (e.g., competition, mutualism) shape their composition and structure. This will be addressed using Arabidopsis thaliana and its main bacterial leaf microbes.

I research the genetic interaction of plants and their pathogens across the landscape. I have experience in genomics, bioinformatics, software engineering, and plant phenomics. I use these skills to build models that inform how genetic material has moved across the landscape historically, and how the coevolutionary balance between plants and their pathogens might change as our climate changes. In the past, I have researched the population and landscape genomics of various plants (Arabidopsis, Brachypodium, Eucalyptus, and others), and developed several novel computational methods to analyse population genomics data.

All living organisms need to defend themselves against parasites and pathogens. The rapid and ancient arms race between hosts and pathogens leads to amazing innovation of immune systems. My work is aimed to discover new immune mechanisms in plant genomes. To do so, I combine my expertise in the ancient antiviral immune systems of bacteria with the genomic resources of Weigelworld to ask how we can find new immunity in plants. I like to mix stuff and cross fields - prokaryotes and eukaryotes, wet and dry work, evolutionary conservation and evolutionary innovation.

Eukaryotic organisms harbor large communities of microorganisms forming an holobiont, considered to be a single ecological and evolutionary unit. In recent years, bacterial community dynamics and their effect on the plant holobiont have been the subject of many studies. However, little is known regarding the role that bacteriophages play in shaping those bacterial communities. In my work I intend to set the basis for understanding the role of the microvirome in plant colonization and development, by studying Arabidopsis thaliana associated bacteria and phages, in laboratory and natural settings.

My work is focused on the effector repertoire in the Pseudomonas syringae species complex, a major plant pathogen infecting a wide range of plant species, including those of high agricultural relevance. Type III Secretion System effectors (T3SEs) are injected into plant cells by the bacteria in order to manipulate host immunity and metabolism to the pathogen's benefit. The precise repertoire of T3SEs varies dramatically across the species complex and has a complicated relationship with pathogenicity. Using in silico tools, I investigate the distribution, phylogeny and protein structure of T3SEs identified in our Tübingen isolate collection of 1524 genomes.

Nucleotide-binding leucine-rich repeat (NLR) proteins are a major factor of disease resistance in plants. My work focuses on describing the NLR diversity in Arabidopsis thaliana and tackling the challenging problem of annotating NLRs in Arabidopsis genomes.

My project in Weigel lab is to employ single-cell RNA sequencing to dissect the transcriptome during plant immunity at single cell level using the well-established Arabidopsis thaliana - Pseudomonas. syringae system.

My research focuses on effector-triggered immunity (ETI) in Arabidopsis thaliana. We use single-cell sequencing to elucidate the molecular mechanisms behind the ETI response under various conditions. I am co-supervised by Marja Timmermanns, Center for Plant Molecular Biology.

To understand the intra pathogen-pathogen interactions within plant hosts in nature, the first step to reveal the diversity of the microbiota associated with the hosts in field samples. Arabidopsis thaliana has emerged as a perfect model for this endeavor, thanks to the intensive work and accumulated knowledge in the past decades. The phyllosphere, also known as the microbiota within the leaves of A. thaliana, will be characterized in a large, hierarchically structured sample. As part of the PATHOCOM team, I am particularly interested in experimental characterization of the spectrum of interactions among pathogenic bacteria and the commensal species by using ultra-high-throughput methods in planta. Moreover, we are also going to identify genes, from both host and microbe, underlying these interactions. The experimental data will be combined with the genetic data to generate a model that can predict patterns in pathogen communities.

My work focuses on improving regenerability of important vegetatively-propagated subsistence crops of southern Africa. I explore the genetic basis for regenerability variance in different genotypes using a reverse genetics approach on targeted genes associated with de novo shoot regeneration. Using genome editing techniques, I evaluate the effect of targeted gene expression levels on the shoot formation capabilities of plant protoplasts. I also study the effect of media composition on regenerability. Preliminary work focuses on the model plant, Arabidopsis thaliana, and lessons from this are applied to cassava (Manihot esculenta), sweet potato (Ipomoea batatas), and horned melon (Cucumis metuliferus).

I’m interested in investigating mechanisms of plant adaptation and develop ways to improve plants, in particular staple crops, by using new genomic technologies, in order to address current issues like food safety and climate change. A topic that I find particularly interesting is applying gene editing systems to improve plant responses to stresses, yield and nutritional value. My project explores the regenerative potential of cassava (Manihot esculenta), a staple crop for about 800 million people globally, by using DNA-free genome editing techniques in leaf mesophyll protoplasts. Through protoplast transformation and transcriptional activation, I also study how genes involved in developmental processes, such as shoot and root formation, can be used to improve cassava’s regeneration ability.

The recent transition of molecular biology into a data-driven discipline made the application of statistical (machine) learning practical for informing experimental designs and for unveiling the causal gene regulatory mechanisms that shape organismal complexity from genotype to phenotype. We employ statistical approaches in form of intelligent software, which we implement for efficient deployment in high-performance cloud architectures to scale our exploration of natural variation to the entire tree of life and our mechanistic understanding of gene expression regulation to all genes of a eukaryotic organism.

My research is focused on protein sequence alignment. Sequence searches in protein space allow to elucidate distant evolutionary relationships and present a challenging computational problem. While traditional search methods like BLAST are increasingly overburdened by the exponential growth of genomic data, I work on novel algorithms and highly optimized C++ implementations to solve this fundamental problem more efficiently. I am known as the author of the widely used DIAMOND alignment tool.

I am a PhD student in the Computational Biology Lab. My work focuses on casual inference of gene regulatory networks from transcriptomic data.

Trained as a molecular geneticist, I have always been curious about molecular mechanisms, and spent many years investigating small RNAs and their impact on Arabidopsis development. A game-changer was our Pathodopsis adventure, where the bind-blowing experience of finding and studying plants ‘in the wild’ taught me that molecular biology is often like watching an elephant in a zoo – a small part of reality. Extending the ‘safari’ feeling, I am now combining ecology and genetics. Drawing from the naturally occurring variation in Arabidopsis populations, we study disease resistance to a wide-spread oomycete pathogen. Our goal is to understand the spatio-temporal dynamics of resistance and virulence, as well as the molecular (and functional) evolution of resistance loci at various spatial scales.