Biology subjects

Krasileva, K.

Publications and source records attributed to Krasileva, K..

12 recordsLinked to original sources

bioRxiv2026

Tracking Transgenes with Color: RUBY as a Visual Marker in CRISPR-Edited Mutant Plants in Two Triticum Species

CRISPR-Cas9 is a powerful tool for precise genome editing in plants, but the presence of foreign DNA, such as T-DNA, raises regulatory concerns and complicates mutant screening and field studies of edited material. Detecting plants with good transgene expression and later removing the T-DNA from edited plants is both time-consuming and costly. To address this, we developed a system that uses the non-destructive RUBY reporter, linked to the CRISPR-Cas9 cassette, and expressed under the ZmUbi1 promoter. To assess the applicability of the system, it was tested on two Triticum species, targeting three genes in either tetraploid or hexaploid wheat. Strong correlations were observed in both T0 and T1 plants between betalain content and Cas9 expression, allowing for the quick identification of plants likely to be edited. Furthermore, the RUBY reporter could be used to select against the transgenic CRISPR-Cas9 cassette in subsequent generations at both the seed and seedling stages, thereby reducing the number of plants that need to be screened to identify edited lines without a T-DNA. This approach, using a nondestructive reporter, enabled rapid distinction between transgene expression in primary transgenics and served as a negative selection in the T1 generation, streamlining selection towards edited and T-DNA-free progeny.

plant biology↗

bioRxiv2025

Natural variation in regulatory code revealed through Bayesian analysis of plant pan-genomes and pan-transcriptomes

Understanding the genetic code of cis-regulatory elements (CREs) is essential for engineering gene expression and modulating agronomic traits in crops. In plants, CREs underlying rapid evolution of gene expression often overlap with structural variation in promoters, making them undetectable using single-reference genomes. Here, we develop K-PROB (K-mer-based in silico PROmoter Bashing), a computational tool that learns from intraspecies promoter sequence and gene expression variation in pan-genomes and pan-transcriptomes to identify CREs controlling gene expression. K-PROB deploys a k-mer-based Bayesian variable selection framework to prioritize causal variable identification. We demonstrate the effectiveness of our approach in maize and soybean, two staple crops species. Applying K-PROB to genes with the most highly variable promoter sequences and the most diverse patterns of expression, such as nucleotide-binding leucine-rich repeat receptors, we identified k-mers enriched for bona fide transcription factor binding sequences, and overlapping with open chromatin regions and DAP-seq binding sites. Notably, multiple significant k-mers are located within presence/absence structural variants, highlighting structural variation in promoters as key drivers of transcriptional diversity of highly variable genes. We further validated the regulatory effects of identified k-mers on gene expression using luciferase reporter assays. Our results showcase a high-throughput and pangenomic approach for probing natural intraspecies cis-regulatory diversity, discovering new causative cis-elements, and facilitating future expression engineering across plant species. Significance StatementUnderstanding which DNA sequences control gene expression is essential for crop improvement. Current methods for identifying regulatory elements rely on expensive, specialized biochemical datasets typically limited to a single genotype. We developed a computational tool that links natural sequence variation and gene expression variation to identify functional regulatory sequences. Our tool employs a statistical framework that prioritizes causality over correlation, in contrast to most genome-wide association studies. Applying it to maize and soybean, two staple crops, we uncovered known and novel regulatory elements and validated them with molecular assays. Our approach is scalable, cost-effective, and efficiently utilizes natural variation from existing pangenomic datasets, opening new avenues for future crop engineering and studying gene regulation in diverse plant species.

bioinformatics↗

bioRxiv2025

The Annotated Blueprint: Integrated Functional Genomic Resources for a Model Tetraploid Wheat Triticum turgidum cv. Kronos

Triticum turgidum cv. Kronos is a tetraploid wheat cultivar that underpins one of the richest community platforms for functional genomics. Over the past decade, about 3,000 exome- and promoter-capture datasets, linked to mutagenized seed stocks, and transcriptomic and phenotypic resources have accumulated, yet the absence of a reference genome has constrained their impact. Here, we present a chromosome-scale reference genome of Kronos with high-confidence annotations, including manual curation of over 1,000 disease resistance (NLR) genes. This reference revealed previously hidden NLR diversity and clarified their genomic organization at chromosomal ends. Re-analysis of exome- and promoter-capture datasets enabled high-resolution mutation discovery in genes and regulatory regions that were previously inaccessible, uncovering the full standing variation present in Kronos mutant lines. We further re-curated transcriptomic and small RNA datasets, generating improved, genome-wide maps of microRNAs and phasiRNAs important for wheat development. Collectively, these resources elevate Kronos to reference quality and establish it as a versatile platform for functional and translational wheat research.

plant biology↗

bioRxiv2025

mamp-ml: A deep learning approach to epitope immunogenicity in plants

Eukaryotes detect biomolecules through surface-localized receptors, key signaling components. A subset of receptors survey for pathogens, induce immunity, and restrict pathogen growth. Comparative genomics of both hosts and pathogens has unveiled vast sequence variation in receptors and potential ligands, creating an experimental bottleneck. We have developed mamp-ml, a machine learning framework for predicting plant receptor-ligand interactions. We leveraged existing functional data from over two decades of foundational research, together with the large protein language model ESM-2, to build a pipeline and model that predicts immunogenic outcomes using a combination of receptor-ligand features. Our model achieves 73% prediction accuracy on a held-out test set, even when an experimental structure is lacking. Our approach enables high-throughput screening of LRR receptor-ligand combinations and provides a computational framework for engineering plant immune systems.

immunology↗

bioRxiv2025

Molecular Insights into Fungal Innate Immunity Using the Neurospora crassa - Pseudomonas syringae Model

Recent comparative genomics and mechanistic analyses support the existence of a fungal immune system. Fungi encode genes with features similar to non-self recognition systems in plants, animals, and bacteria. However, limited functional or mechanistic evidence exists for the surveillance-system recognition of heterologous microbes in fungi. We found that Neurospora species coexist with Pseudomonas in their natural environment. We leveraged two model organisms, Neurospora crassa and Pseudomonas syringae DC3000 (PSTDC3000) to observe immediate fungal responses to bacteria. PSTDC3000 preferentially surrounds N. crassa cells on a solid surface, causing environmental dependent growth responses, bacterial proliferation and varying fungal fitness. Specifically, the Type III secretion system (T3SS) {Delta}hrcC mutant of PSTDC3000 colonized N. crassa hyphae less well. To dissect initial cellular signaling events within the population of germinated asexual spores (germlings), we performed transcriptomics on N. crassa after PSTDC3000 inoculation. Upon contact with live bacteria, a subpopulation of fungal germlings initiate a response as early as ten minutes post-contact revealing transcriptional differentiation of Reactive Oxygen Species (ROS) mechanisms, trace metal warfare, cell wall remodeling dynamics, multidrug-efflux transporters, secondary metabolite synthesis, and excretion. We dissected mutants of plausible receptors, signaling pathways, and responses that N. crassa uses to detect and mount a defense against PSTDC3000 and found seven genes that influence resistant and susceptibility phenotypes of N. crassa to bacterial colonization. Mutants in genes encoding a ctr copper transporter (tcu-1), ferric reductase (fer-1), superoxide reductase (sod-2), multidrug resistance transporter (mdr-6), a secreted lysozyme-Glycoside hydrolase (lyz) and the Woronin body tether leashin (NCU02793, lah-1 and lah-2) showed a significant reduction of growth in the presence of bacteria, allowing the bacteria to fully take over the fungal mycelium faster than wildtype. In this study we provide a bacterial-fungal model system within Dikarya that allows us to begin to dissect signaling pathways of the putative fungal immune system.

immunology↗

bioRxiv2024

Engineering pathogen-inducible promoters for conferring disease resistance in tomato

Many disease resistance genes utilized in crop breeding encode nucleotide-binding leucine-rich repeat receptors (NLRs), which are frequently race-specific and fail to provide durable protection in the field. Consequently, engineering broad-spectrum resistance has become a primary goal. While autoactive NLRs can provide broad-spectrum immunity by bypassing specific pathogen recognition, they often impose severe fitness costs. Here, we hypothesized that precise transcriptional control could mitigate these penalties and developed a synthetic strategy coupling pathogen-inducible (PI) promoters with autoactive NLRs. Through a transcriptomic meta-analysis, we identified and validated native tomato PI promoters that respond to diverse pathogens while remaining insensitive to abiotic stress. We established a tunable system by pairing these promoters varying in basal and inducible expression with NLRs exhibiting different degrees of autoactivity. Systematic characterization revealed that balancing these components is critical to prevent leaky immune activation in the absence of pathogens. Transgenic tomatoes expressing a weakly autoactive NLR under a PI phenylalanine ammonia-lyase promoter exhibited enhanced resistance to two taxonomically distinct pathogens without growth impairment. Disruption of the PI sequence largely abolished this resistance, confirming the necessity of pathogen-mediated transcriptional induction. Finally, we added an additional layer of tunability by engineering the copy number of inducible elements and the core promoter to fine-tune promoter strength while preserving inducibility. Together, our results showcase a versatile framework for engineering multi-pathogen resistance and provide new insights into using transcriptional control in overcoming the fitness costs associated with autoactive NLRs.

synthetic biology↗

bioRxiv2024

Engineering the plant intracellular immune receptor Sr50 to restore recognition of the AvrSr50 escape mutant

Pathogen-driven plant diseases cause significant crop losses worldwide. The introgression of intracellular nucleotide-binding leucine-rich repeat receptor (NLR) genes into elite crop cultivars is a common strategy for disease control, yet pathogens rapidly evolve to evade NLR-mediated immunity. The NLR gene Sr50 protects wheat against stem rust, a devastating disease caused by the fungal pathogen Puccinia graminis f. sp. tritici (Pgt). However, mutations in AvrSr50 allowed Pgt to evade Sr50 recognition, leading to resistance breakdown. Advances in protein structure modeling can enable targeted NLR engineering to restore recognition of escaped effectors. Here, we combined iterative computational structural analyses and site-directed mutagenesis to engineer Sr50 recognition of AvrSr50QCMJC, a Pgt effector variant that evades wild-type Sr50 detection. Derived by molecular docking, our initial structural model identified the K711D substitution in Sr50, which partially restored AvrSr50QCMJC recognition. Enhancing Sr50K711D expression via strong promoters compensated for weak recognition and restored robust immune responses. Further structural refinements led to the generation of five double and two triple receptor mutants. These engineered mutants, absent in nature, showed robust dual recognition for AvrSr50 and AvrSr50QCMJC in both Nicotiana benthamiana and wheat protoplasts. Notably, the K711D substitution was essential and synergistic with the additional substitutions for AvrSr50QCMJC recognition, demonstrating protein epistasis. Furthermore, this single substitution altered AlphaFold 2 predictions, enabling accurate modeling of the Sr50K711D-AvrSr50 complex structure, consistent with our final structural hypothesis. Collectively, this study outlines a framework for NLR engineering to counteract pathogen adaptation and provides novel Sr50 variants with potential for stem rust resistance.

plant biology↗

bioRxiv2023

Structure-Aware Annotation of Leucine-rich Repeat Domains

Protein domain annotation is typically done by predictive models such as HMMs trained on sequence motifs. However, sequence-based annotation methods are prone to error, particularly in calling domain boundaries and motifs within them. These methods are limited by a lack of structural information accessible to the model. With the advent of deep learning-based protein structure prediction, existing sequenced-based domain annotation methods can be improved by taking into account the geometry of protein structures. We develop dimensionality reduction methods to annotate repeat units of the Leucine Rich Repeat solenoid domain. The methods are able to correct mistakes made by existing machine learning-based annotation tools and enable the automated detection of hairpin loops and structural anomalies in the solenoid. The methods are applied to 127 predicted structures of LRR-containing intracellular innate immune proteins in the model plant Arabidopsis thaliana and validated against a benchmark dataset of 172 manually-annotated LRR domains. Author summaryIn immune receptors across various organisms, repeating protein structures play a crucial role in recognizing and responding to pathogen threats. These structures resemble the coils of a slinky toy, allowing these receptors to adapt and change over time. One particularly vital but challenging structure to study is the Leucine Rich Repeat (LRR). Traditional methods that rely just on analyzing the sequence of these proteins can miss subtle changes due to rapid evolution. With the introduction of protein structure prediction tools like AlphaFold 2, annotation methods can study the coarser geometric properties of the structure. In this study, we visualize LRR proteins in three dimensions and use a mathematical approach to flatten them into two dimensions, so that the coils form circles. We then used a mathematical concept called winding number to determine the number of repeats and where they are in a protein sequence. This process helps reveal their repeating patterns with enhanced clarity. When we applied this method to immune receptors from a model plant organism, we found that our approach could accurately identify coiling patterns. Furthermore, we detected errors made by previous methods and highlighted unique structural variations. Our research offers a fresh perspective on understanding immune receptors, potentially influencing studies on their evolution and function.

bioinformatics↗

bioRxiv2022

Pseudomonas isolates from ponds populated with duckweed prevent disease caused by pathogenic Pseudomonas species

Duckweeds are notoriously invasive plants. They are successful in inhabiting diverse environments, despite their lack of conventional immune pathways that are essential for disease resistance in other plant species. It is unclear how duckweeds thrive in the absence of these immune pathways. In this study, we investigated the effect of bacteria from duckweeds natural habitat on disease progression utilizing the duckweed-Pseudomonas pathosystem. Through nanopore sequencing of 16S and ITS rDNA amplicons we identified duckweed-associated bacterial and fungal genera present at three environmental sites. The pond filtrate from one of the three environmental locations primed duckweeds pathogen defenses leading to a reduction in disease symptoms. Furthermore, we were able to identify bacterial isolates from the filtrate that protect duckweed from disease symptoms upon Pseudomonas pathogen inoculation. The isolated protective bacteria belong to the Pseudomonas genus, and we demonstrated antagonistic interactions between the pathogen and beneficial strains in vitro and in vivo. The ability of our environmental isolates to protect against Pseudomonas pathogens appears to be plant/species specific as environmental strains showed no protective effect against Pseudomonas pathogens in Arabidopsis assays. Genome sequencing of the beneficial Pseudomonas strains showed the presence of several genes involved in bacterial competition. We have thus demonstrated that Pseudomonas species from duckweeds natural habitat can successfully antagonize other plant pathogens.

plant biology↗

bioRxiv2022

Comparative computational structural genomics highlights divergent evolution of fungal effectors

Elucidating the evolution of pathogen effector molecules is critical to understand infection mechanisms of fungal phytopathogens and ensure crop security. However, rapid diversification that diminishes sequence similarities between homologous effectors has largely concealed the roots of effector evolution. We predicted the folds of 26,653 secreted proteins from 21 species with AlphaFold and performed structure-guided comparative analyses on two aspects of effector evolution: uniquely expanded effector families and common folds present across the fungal species. Extreme expansion of nearly lineage-specific effector families was found only in several obligate biotrophs, Blumeria graminis and Puccinia graminis. The highly expanded effector families were the source of conserved sequence motifs, such as the Y/F/WxC motif. We identified additional lineage-specific effector families that include known (a)virulence factors, such as AvrSr35, AvrSr50 and Tin2. These families represented new classes of sequence-unrelated structurally similar effectors. Structural comparisons revealed that the expanded structural folds further diversify through domain duplications and fusion with disordered stretches. Sub-and neo-functionalized structurally similar effectors reconverge on regulation, expanding the functional pools of effectors in the pathogen infection cycle. We also found evidence that many effector families could have originated from ancestral folds that have been conserved across fungi. Collectively, our study highlights diverse mechanisms of effector evolution and supports divergent evolution of effectors that leads to emergence of pathogen virulence from ancestral proteins.

microbiology↗

bioRxiv2022

Engineering of Sr33 and Sr50 plant immune receptors to alter recognition specificity and autoactivity

Plants possess cytoplasmic immune receptors called nucleotide-binding leucine-rich repeat receptors (NLRs) that recognize the presence of a pathogen through a range of mechanisms: direct binding of effectors or indirect recognition of effector actions. The direct binding of effectors has been shown to be mediated through the NLRs leucine-rich repeat (LRR) domain. Accurate prediction of amino acids involved in these direct interactions can greatly enhance understanding of effector recognition and inform efforts to engineer new resistance. In this study, we utilized two homologous NLR resistance genes from wheat, Sr33 and Sr50, that recognize distinct effectors by directly binding to them through their LRR domain. While the effector recognized by Sr50 is known and described as AvrSr50, the effector recognized by Sr33 remains unknown. Through a combination of phylogenetics, allele diversity analysis in the LRR and structural modeling, we identified the amino acids in Sr50 likely to physically interact with its effector. Mutation of these sites helped identify 12 amino acids we hypothesized to be sufficient to mediate effector binding in Sr50. Changing these 12 corresponding amino acids in Sr33, we showed AvrSr50-dependent initiation of cell death in wheat protoplasts and Nicotiana benthamiana. Furthermore, we were able to pinpoint and change amino acid residues that govern autoactivity of Sr50 in the wheat protoplast cell death assay. These findings are a major advance towards the successful engineering of new effector recognition specificities in direct binder NLRs.

plant biology↗

bioRxiv2022

A draft genome assembly for the heterozygous wild tomato Solanum habrochaites highlights haplotypic structural variations of intracellular immune receptors

Solanum habrochaites LA1353 is a self-incompatible, highly heterozygous wild tomato that is a useful germplasm resource for the study of metabolism, reproduction and disease resistance. We generated a draft genome assembly with PacBio HiFi reads and genome annotations, which underscored the expansion of gene families associated with metabolite-production, self-incompatibility, DNA regulation and immunity. After manually curating intracellular nucleotide-binding leucine-rich repeat immune receptors (NLRs), we found that S. habrochaites LA1353 has a larger NLR inventory than other wild tomato species. A great number of heterozygous local copy number variations (CNVs) driven by haplotypic structural variations further expands the inventory, both enhancing NLR diversity and providing more opportunities for sequence evolution. The NLRs associated with local CNVs predominantly appear in the helper NLR (NRC)-related phylogenetic clades and are concentrated in a few physical NLR gene clusters. Synteny analysis points out that these genomic regions correspond to the known NLR clusters from which experimentally validated, functional NLRs, such as Hero, Mi-1.2 and Rpi-amr1, have been identified. Producing and incorporating Resistance Gene Enrichment Sequencing (RenSeq) data across wild tomato species, we reveal that the regions with local CNVs might have been shaped nearly equally by recent NLR gains and losses, along with enhanced sequence diversification that diminishes one-to-one orthology between heterozygous alleles. Our analysis suggests that these genomic regions may have accelerated evolutionary dynamics for NLR diversity generation in S. habrochaites LA1353.

plant biology↗