Biology subjects

Bezrukov, I.

Publications and source records attributed to Bezrukov, I..

17 recordsLinked to original sources

bioRxiv2026

A Modular, AI-assisted Digitization Toolkit for Resource-Constrained Herbaria: A Case Study from Zimbabwe

Herbaria serve as invaluable spatio-temporal repositories of plant diversity information. Digitization of herbarium collections enhances the accessibility, discoverability, and long-term preservation of this important plant information, yet financial and infrastructural constraints often prevent herbaria in resource-constrained regions from digitizing their collections. Consequently, critical plant diversity data gaps remain due to underrepresentation of these collections in global biodiversity databases. Here, we describe an AI-assisted modular digitization toolkit specifically designed for herbaria operating under limited funding, developed and refined through our experience digitizing the crop wild relative (CWR) collection of the National Herbarium of Zimbabwe. The toolkit comprises three core components: (1) a portable, cost-effective photostation assembled from commodity parts, (2) a streamlined cascade workflow for systematic digital imaging, and (3) an AI-assisted data management pipeline for image quality control, label transcription, data analysis, and presentation. Compared to manual transcription and legacy optical character recognition approaches, AI-based transcription achieves lower time cost while maintaining high accuracy, and AI-driven data management delivers accessibility and reduced expenditure relative to conventional database infrastructure. The toolkit is designed to allow herbarium staff full autonomy over the digitization procedure, ensuring institutional ownership and the capacity for independent continuation beyond initial project support. By prioritizing affordability, modularity, and simplicity, this toolkit provides a replicable framework that may enable resource-constrained herbaria to locally generate high-quality scientific data for conservation and the sustainable utilization of plant genetic resources.

plant biology↗

bioRxiv2026

Biotic-response networks are an important organizer of the transcriptome in wild Arabidopsis thaliana populations

Extensive laboratory experimentation has revealed conserved molecular pathways controlling growth and stress responses in plants, yet how these programs operate in natural settings remains poorly understood. We investigated transcriptome organization in wild populations of Arabidopsis thaliana by sampling plants from 60 natural sites in Europe and North America across two seasons. Transcriptomes varied extensively among individuals and showed largely continuous rather than discrete structure across geography and season. Although disease and microbial colonization were common in the wild, wild transcriptomes did not simply recapitulate canonical laboratory stress signatures. Measured microbial infection, environmental, and phenotypic variables explained only a modest fraction of total expression variation, but infection-associated signals accounted for the largest share of the explainable component. Consistent with this, biotic-response networks defined in controlled laboratory experiments were well conserved in wild transcriptomes, whereas control and abiotic-response networks were substantially reorganized. Together, these results suggest that while core transcriptional modules remain recognizable across environments, regulatory relationships among modules differ markedly between laboratory and natural contexts. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=129 SRC="FIGDIR/small/711176v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@1c89152org.highwire.dtl.DTLVardef@bcd1acorg.highwire.dtl.DTLVardef@6975a2org.highwire.dtl.DTLVardef@1a9e2fe_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2025

Persistent trade-offs balance competition and colonization across centuries

Microbial competition drives rapid adaptation, often forcing organisms to specialize in new ecological niches. Adaptations that improve competitive ability can reduce performance in other environments creating trade-offs. Whether such trade-offs persist in nature--or are eroded as lineages adapt through compensatory changes--remains largely unknown. Here we show that a trade-off between competitive ability and host colonization has been stably maintained in natural Pseudomonas populations for centuries. Wild plant-pathogenic Pseudomonas compete using tailocins--phage-derived molecular weapons that bind to specific cell-surface receptors. Genomic surveys and functional assays reveal that the most broadly lethal tailocins remain rare--while the tailocins production increases competitive killing, it also compromises plant colonization. We determine that the polymorphisms behind this trade-off are not transient -- historical genomes spanning two centuries show that the trade-off has been maintained for at least 10-10 generations. Our results demonstrate that, in natural populations, a trade-off between competition and pathogenicity is fundamental and not easily overcome. SignificanceWhen a microbe colonizes a host, it must both establish infection and outcompete other organisms. Short-term experiments show that gains in competitive ability can reduce colonization, creating trade-offs, but whether microbes resolve these conflicts over long evolutionary timescales is unknown. We show that a trade-off between competitive killing and host colonization has been stably maintained for centuries in natural Pseudomonas populations infecting Arabidopsis thaliana. Tailocins--phage-derived weapons--provide strong competitive advantages, yet their production reduces colonization success, explaining why the most broadly lethal variants remain rare. Genomic surveys and historical genomes spanning two centuries reveal that the polymorphisms underlying this trade-off have persisted across 10-10 generations. Understanding such long-lived constraints can inform antimicrobial strategies that exploit evolutionary trade-offs.

evolutionary biology↗

bioRxiv2025

Cell-type specific gating of gene regulatory modules as a hallmark of early immune responses in Arabidopsis leaves

In plants, many cell types contribute to immunity, but what division of labor exists among cell types when immunity is activated? We compared, at single-cell resolution, the response of Arabidopsis thaliana leaf cells during pattern-triggered and effector-triggered immunity (PTI/ETI), sampled at 3 and 5 hours after infection with Pseudomonas syringae DC3000. Core defense modules were broadly shared across cell clusters, but their activation varied in timing and intensity, with key immune receptors also showing cell type-specific expression dynamics. We identified distinct mesophyll cell populations based on their resilience patterns: after the initial response, some cells continue to express defense genes at high levels during both PTI and ETI, while others quickly reinitiate growth-related gene expression programs, but only during PTI. Gene regulatory network inference revealed WRKY-regulated modules enriched in cells sensing effectors, while SA biosynthesis regulators were activated in complementary clusters. Finally, we used the cue1-6 mutant to demonstrate that core immune responses are robust despite altered leaf architecture. In addition, we uncovered cryptic defense pathways, including sucrose-responsive modules, in this mutant. By capturing early immune responses at high resolution, our study reveals cell type-specific coordination of plant immunity and provides a framework for decoding immune signaling networks.

plant biology↗

bioRxiv2025

Minimizing detection bias of somatic mutations in a highly heterozygous oak genome

Somatic mutations are particularly relevant for long-lived organisms. Sources of somatic mutations include imperfect DNA repair, replication errors, and exogenous damage such as ultraviolet radiation. A previous study estimated a surprisingly low number of somatic mutations in a 234-year-old individual of the pedunculate oak (Quercus robur), known as the Napoleon Oak. It has been suggested that the true number of somatic mutations was underestimated due to gaps in the reference genome and too conservative filtering of potential mutations. We therefore generated new high-fidelity long-read data for the Napoleon Oak (n = 12) to produce both a pseudo-haploid genome assembly and a partially phased diploid assembly. The high heterozygosity allowed for complete reconstruction of phased and gapless centromeres for 22 of the 24 chromosomes. On the other hand, the high heterozygosity posed challenges for short-read alignments. Use of only the pseudo-haploid assembly as a reference led to potential misalignments, while use of only the diploid assembly reduced variant detection sensitivity. Since most somatic mutations are layer-specific, the observed frequency is expected relatively low, even where all cells in a single layer contain a specific mutation. To address this challenge, we employed a read assignment strategy, selecting the appropriate reference sequence (pseudo-haploid or diploid) based on alignment score and mapping quality. Ultimately, we identified 198 high-confidence somatic mutations, compared with 17 somatic mutations identified before with the same set of short reads. Our approach thus increased the total estimated annual mutation rate by a factor of five.

genomics↗

bioRxiv2025

The structure of mitochondrial genomes is associated with geography in Arabidopsis thaliana

Chloroplasts and mitochondria are the primary sites for photosynthesis and respiration, each harboring its own unique genome. Although the organellar genomes are considerably smaller compared to the nuclear genome, they are nonetheless essential for survival of the organism. A common feature of many chloroplast and mitochondrial genomes is the presence of large repeated sequences longer than 1 kb. These can be either in inverted or direct orientation, and recombination between them leads to structural heteroplasmy. To understand the intraspecific evolution of organellar genomes, we assembled chloroplast and mitochondrial genomes of 143 A. thaliana accessions from PacBio HiFi sequencing data. We find large repeats to be associated with heteroplasmy and structural variation. Our extensive genome annotation identifies novel open reading frames (ORFs) in those accessions that lost large repeats, potentially introduced via horizontal gene transfer, illuminating additional paths for diversification of plant organelles. The loss of large repeats correlates with geography and phenotypes, pointing to their adaptive importance. The assembled and annotated organellar genomes constitute a rich source for future functional studies of the interaction between the three genomes of a plant.

evolutionary biology↗

bioRxiv2024

Gfa2bin enables graph-based GWAS by converting genome graphs to pan-genomic genotypes

Variation graphs offer superior representation of genomic diversity compared to traditional linear reference genomes, capturing complex features that are otherwise inaccessible to analysis. It seems self-evident that integrating these graphs with genome-wide association studies (GWAS) should enable more comprehensive understanding of genetic landscapes, potentially uncovering novel associations between genetic variations and traits. This approach takes full advantage of rich genomic information, thereby providing deeper insights into the genetic base of complex traits. Our tool, gfa2bin, offers multiple methods to (i) genotype variation graphs and (ii) convert the genotypes to well-established data formats for genome-wide association studies (GWAS). We demonstrate that variation graphs are feasible alternatives to traditional linear references for GWAS. Our case study using Arabidopsis thaliana and 1,695 traits shows that our approach complements SNP-based approaches, often identifying additional associations, with all associations having on average higher significance compared to SNP-based approaches. gfa2bin is implemented in Rust. Commented source code is available under MIT license at https://github.com/MoinSebi/gfa2bin. Examples of how to run gfa2bin are provided in the documentation. We added several Python scripts and a Snakemake pipeline for easy processing of our tool using larger data sets. In addition, we recommend using packing (https://github.com/MoinSebi/packing) for reduced storage and preprocessing (normalization) of sequence-to-graph alignments coverage.

bioinformatics↗

bioRxiv2024

Field conditions greatly modify a major growth-defense tradeoff in Arabidopsis thaliana

When plants defend themselves from pathogens, this often comes with a trade-off: the same genes that protect a plant from disease can also reduce its growth and fecundity in the absence of pathogens. One protein implicated in a major growth-defense trade-off in the plant Arabidopsis thaliana is ACCELERATED CELL DEATH 6 (ACD6), an ion channel that modulates salicylic acid (SA) synthesis to potentiate a wide range of defenses. Wild plant populations maintain significant functional variation in the ACD6 gene, with some alleles making the protein hyperactive. In the greenhouse, plants with hyperactive ACD6 alleles are resistant to diverse pathogens, yet are of smaller stature, their leaves senesce earlier, and they set fewer seeds. We hypothesized that such hyperactive alleles would not only affect the growth of microbial pathogens, but also more generally leaf microbiome assembly in the wild. To test this, we grew plants with hyperactive, standard, and defective ACD6 alleles in the same field-collected soil, both in climate-controlled conditions and outdoors. We surveyed visual phenotypes, gene expression, hormone levels, seed production, and the microbiome in each environment. To our surprise, we discovered that mature field plants, in stark contrast to greenhouse plants, were unaffected by their ACD6 genotype, suggesting that additional abiotic and/or microbial signals present outdoors - but not in the greenhouse - greatly modulate ACD6 activity.

plant biology↗

bioRxiv2024

Cryptic Variation in Adaptive Phenotypes Revealed by Panspecific flc Mutants

The study of mutants is one of the best tools for understanding the genetic basis of phenotypes that contribute to adaptation. Oddly, mutant analyses are almost always restricted to single genetic backgrounds and findings therefore can not be easily generalized. A case in point is the key regulator of flowering, FLOWERING LOCUS C (FLC), which has been inferred to explain much of the flowering time variation in Arabidopsis thaliana, yet mutants have been examined in very few backgrounds. We have previously established a set of panspecific flc mutants in 62 accessions of A. thaliana (Ruffley et al. 2024). Here, we investigate how genetic background modulates mutant effects on flowering and vegetative traits, as well as on physiology and transcriptomes. Time to onset of flowering in the genome-edited flc lines was reduced by up to 83%, but considerable variation remained. Genetic mapping showed that extremely early flowering in the absence of FLC was mostly explained by natural variation at the known FLC target FT, with additional contribution from loci colocalizing with FLC. Prognostic sequence analyses of accessions did not suggest that extremely-early combinations of engineered flc and natural FT alleles would be deleterious, yet extremely early flowering accessions are not represented in the commonly used collections of A. thaliana accessions. To test whether this discrepancy could be due to sampling bias, we undertook a focused collection effort of wild populations in Southern Italy, which confirmed that extremely early flowering accessions exist in natural populations. Apart from its specific role in flowering time regulation, FLC has pleiotropic effects on other ecophysiological traits such as growth, and these were also dependent on the genetic background, which was further supported by transcriptomic comparisons. Together we conclude that the various roles of FLC have greatly diversified in different genetic backgrounds. Our study provides a proof-of-concept on how analysis of panspecific mutants can reveal the true extent of genetic networks in which a focal gene participates in.

plant biology↗

bioRxiv2024

Gretl - Variation GRaph Evaluation TooLkit

Motivation: As genome graphs are powerful data structures for representing the genetic diversity within populations, they can help identify genomic variations that traditional linear references miss, but their complexity and size makes the analysis of genome graphs challenging. We sought to develop a genome graph analysis tool that helps these analyses to become more accessible by addressing the limitations of existing tools. Specifically, we improve scalability and user-friendliness, and we provide many new statistics for graph evaluation. Results: We developed an efficient, comprehensive, and integrated tool, gretl, to analyse genome graphs and gain insights into their structure and composition by providing a wide range of statistics. gretl can be utilised to evaluate different graphs, compare the output of graph construction pipelines with different parameters, as well as perform an in-depth analysis of individual graphs, including sample-specific analysis. With the assistance of gretl, novel patterns of genetic variation and potential regions of interest can be identified, for later, more detailed inspection. We demonstrate that gretl outperforms other tools in terms of speed, particularly for larger genome graphs. Availability and implementation: gretl is implemented in Rust. Commented source code is available under MIT licence at https://github.com/MoinSebi/gretl. Examples of how to run gretl are provided in the documentation. Several Jupyter notebooks are part of the repository and can help visualise gretl results.

bioinformatics↗

bioRxiv2023

The genetic and physiological basis of Arabidopsis thaliana tolerance to Pseudomonas viridiflava

O_LIThe opportunistic pathogen Pseudomonas viridiflava colonizes more than fifty agricultural crop species and is the most common Pseudomonas in the phyllosphere of European Arabidopsis thaliana populations. Belonging to the P. syringae complex, it is genetically and phenotypically distinct from well-characterized P. syringae sensu stricto. Despite its prevalence, we lack knowledge of how A. thaliana responds to its native isolates at the molecular level. Here, we characterize the host response in an A. thaliana - P. viridiflava pathosystem. C_LIO_LIWe measured host and pathogen growth in axenic infections, and used immune mutants, transcriptomics, and metabolomics to determine defense pathways influencing susceptibility to P. viridiflava infection. C_LIO_LIInfection with P. viridiflava increased jasmonic acid (JA) levels and the expression of ethylene defense pathway marker genes. The immune response in a susceptible host accession was delayed compared to a tolerant one. Mechanical injury rescued susceptibility, consistent with an involvement of JA. C_LIO_LIThe JA/ethylene pathway is important for suppression of P. viridiflava, yet suppression capacity varies between accessions. Our results shed light on how A. thaliana can suppress the ever-present P. viridiflava, but further studies are needed to understand how P. viridiflava evades this suppression to spread broadly across A. thaliana populations. C_LI

plant biology↗

bioRxiv2022

Pervasive Under-Dominance in Gene Expression as Unifying Principle of Biomass Heterosis in Arabidopsis

Complex traits, such as growth and fitness, are typically controlled by a very large number of variants, which can interact in both additive and non-additive fashion. In an attempt to gauge the relative importance of both types of genetic interactions, we have turned to hybrids, which provide a facile means for creating many novel allele combinations. We focused on the interaction between alleles of the same locus and performed a transcriptomic study involving 141 random crosses between different accessions of the plant model species Arabidopsis thaliana. Additivity is rare, consistently observed for only about 300 genes enriched for roles in stress response and cell death. Regulatory rare-allele burden affects the expression level of these genes but does not correlate with F1 rosette size. Non-additive gene expression in F1 hybrids is much more common, with the vast majority of genes (over 90%) being expressed below parental average. Unlike in the additive genes, regulatory rare-allele burden in the non-additive gene set is strongly correlated with F1 rosette size, even though it only mildly covary with the expression level of these genes. Our study underscores under-dominance as the predominant gene action associated with emergence of rosette growth trajectories in the A. thaliana hybrid model. Our work lays the foundation for understanding molecular mechanisms and evolutionary forces that lead to dominance complementation of rare regulatory alleles.

genomics↗

bioRxiv2021

Contrasting patterns of microbial dominance in the Arabidopsis thaliana phyllosphere

Sphingomonas is one of the most abundant bacterial genera in the phyllosphere of wild Arabidopsis thaliana, but relative to Pseudomonas, the ecology of Sphingomonas and its interaction with plants remains elusive. We analyzed the genomic features of over 400 Sphingomonas isolates collected from local A. thaliana populations, which revealed high intergenomic diversity, in contrast to genetically much more uniform Pseudomonas isolates found in the same host populations. Variation in Sphingomonas plasmid complements and additional genomic features suggest high adaptability of this genus, and the widespread presence of protein secretion systems hints at frequent biotic interactions. While some of the isolates showed plant-protective properties in lab tests, this was a rare trait. To begin to understand the extent of strain sharing across alternate hosts, we employed amplicon sequencing and a novel bulk-culturing metagenomics approach on both A. thaliana and neighboring plants. Our data reveal that Sphingomonas and Pseudomonas both thrive on other diverse plant hosts, but that Sphingomonas is a poor competitor in dying or dead leaves.

ecology↗

bioRxiv2021

Homozygosity at its Limit: Inbreeding Depression in Wild Arabidopsis arenosa Populations

New combinations of genetic material brought together through hybridization can lead to unfit offspring as a result of outbreeding or inbreeding depression. In selfing plants such as Arabidopsis thaliana, outbreeding depression is typically the result of pairwise deleterious epistatic interactions between two alleles that can geographically co-occur. What remains elusive is how often alleles resulting in genetic incompatibilities co-occur in natural populations of outcrossing plant species. To address this question, we screened over two thousand five hundred wild Arabidopsis arenosa hybrid plants in search for potential genetic mismatches. We show that although abnormal deleterious phenotypes are common, the transcriptional profiles of these abnormal A. arenosa plants differ substantially from those seen in incompatible A. thaliana hybrids. The abnormal hybrid phenotypes in A. arenosa had different underlying genetic architectures, yet a repeated theme was increased homozygosity, indicating that inbreeding rather than outbreeding depression gives rise to some of the deleterious phenotypes segregating in wild A. arenosa populations.

plant biology↗

bioRxiv2020

araDEEPopsis: From images to phenotypic traits using deep transfer learning

Linking plant phenotype to genotype, i.e., identifying genetic determinants of phenotypic traits, is a common goal of both plant breeders and geneticists. While the ever-growing genomic resources and rapid decrease of sequencing costs have led to enormous amounts of genomic data, collecting phenotypic data for large numbers of plants remains a bottleneck. Many phenotyping strategies rely on imaging plants, which makes it necessary to extract phenotypic measurements from these images rapidly and robustly. Common image segmentation tools for plant phenotyping mostly rely on color information, which is error-prone when either background or plant color deviate from the underlying expectations. We have developed a versatile, fully open-source pipeline to extract phenotypic measurements from plant images in an unsupervised manner. O_SCPLOWARAC_SCPLOWO_SCPLOWDEEPC_SCPLOWO_SCPLOWOPSISC_SCPLOW was built around the deep-learning model DeepLabV3+ that was re-trained for segmentation of Arabidopsis thaliana rosettes. It uses semantic segmentation to classify leaf tissue into up to three categories: healthy, anthocyanin-rich, and senescent. This makes O_SCPLOWARAC_SCPLOWO_SCPLOWDEEPC_SCPLOWO_SCPLOWOPSISC_SCPLOW particularly powerful at quantitative phenotyping from early to late developmental stages, of mutants with aberrant leaf color and/or phenotype, and of plants growing in stressful conditions where leaf color may deviate from green. Using our tool on a panel of 210 natural Arabidopsis accessions, we were able to not only accurately segment images of phenotypically diverse genotypes but also to map known loci related to anthocyanin production and early necrosis using the O_SCPLOWARAC_SCPLOWO_SCPLOWDEEPC_SCPLOWO_SCPLOWOPSISC_SCPLOW output in genome-wide association analyses. Our pipeline is able to handle images of diverse origins, image quality, and background composition, and could even accurately segment images of a distantly related Brassicaceae. Because it can be deployed on virtually any common operating system and is compatible with several high-performance computing environments, O_SCPLOWARAC_SCPLOWO_SCPLOWDEEPC_SCPLOWO_SCPLOWOPSISC_SCPLOW can be used independently of bioinformatics expertise and computing resources. O_SCPLOWARAC_SCPLOWO_SCPLOWDEEPC_SCPLOWO_SCPLOWOPSISC_SCPLOW is available at https://github.com/Gregor-Mendel-Institute/aradeepopsis.

plant biology↗

bioRxiv2019

The relationship between microbial biomass and disease in the Arabidopsis thaliana phyllosphere

A central goal in microbiome research is to learn what distinguishes a healthy from a dysbiotic microbial community. Shifts in diversity and taxonomic composition are important indicators of dysbiosis, but a full understanding also requires knowledge of absolute microbial population sizes. In addition to the number of microbial cells, information on taxonomic composition can provide important insight into microbiome function and disease state. Here we use shotgun metagenomics to simultaneously assess microbiome composition and microbial load in the phyllosphere of wild populations of the plant Arabidopsis thaliana. We find that wild plants vary substantially in the load of colonizing microbes, and that high loads are typically associated with the proliferation of single taxa, with only a few putatively pathogenic taxa achieving high abundances in the field. Our results suggest (i) that the inside of a plant leaf is on average sparsely colonized with an estimated two bacterial genomes per plant genome and an order of magnitude fewer eukaryotic microbial genomes, and (ii) that higher levels of microbial cells often indicate successful colonization by pathogens. Lastly, our results show that load is a significant explanatory variable for loss of estimated Shannon diversity in phyllosphere microbiomes, implying that reduced diversity may be a significant predictor of microbial dysbiosis in a plant leaf.

plant biology↗

bioRxiv2019

RPW8/HR Repeats Predict NLR-dependent Hybrid Performance

Hybrid offspring can look very different from their parents, including having greatly increased or decreased fitness. In many plant species, conflicts between divergent elements of the immune system can cause hybrids to express autoimmunity, a generally deleterious syndrome known as hybrid necrosis. We are investigating multiple hybrid necrosis cases in Arabidopsis thaliana that are caused by allele-specific interactions between different variants at two unlinked resistance (R) gene clusters. One is the RESISTANCE TO PERONOSPORA PARASITICA 7 (RPP7) cluster, which encodes an intracellular nucleotide binding site-leucine rich repeat (NLR) immune receptors that confer strain-specific resistance to oomycetes. The other is the RESISTANCE TO POWDERY MILDEW 8 (RPW8)/HOMOLOG OF RPW8 (HR) locus, which encodes atypical resistance proteins that can confer broad-spectrum resistance to filamentous pathogens. There is extensive structural variation in the RPW8/HR cluster, both at the level of gene copy number and at the level of C-terminal protein repeats of unknown function. We demonstrate that the number of RPW8/HR repeats correlate, albeit in a complex manner, with the severity of hybrid necrosis when these alleles are combined with specific RPP7 variants. This observation suggests that gross structural differences, rather than individual amino acid polymorphisms, guide the genetic interaction between RPW8/HR and RPP7 alleles. We discuss these findings in light of the similarity of RPW8/HR proteins with pore-forming toxins, MLKL and HET-S, from mammals and fungi.

genetics↗