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Kirst, M.

Publications and source records attributed to Kirst, M..

At least 19 recordsLinked to original sources
bioRxiv2026

Single-Cell Omics to Uncover Cell-Type-Specific Gene Regulatory Networks Driving Mucilage Production in Specialized Roots

Aerial roots of certain maize (Zea mays) and sorghum (Sorghum bicolor) genotypes secrete a carbohydrate-rich mucilage that sustains nitrogen-fixing bacteria, and the underground roots of most plants secrete mucilage at their tips. In both settings, border cells released from the root cap produce this mucilage, yet the genes controlling their formation remain largely unknown. We sequenced the RNA of about 23,000 nuclei from mucilage-secreting roots of maize, sorghum, and Medicago truncatula, sampled before and after secretion. Each species yielded 10 to 15 clusters, which we annotated with published markers and with new markers that we validated by in situ hybridization in the two cereals and by promoter-reporter fusions in M. truncatula. We then inferred modular and cell type-specific gene regulatory networks. Transcriptional programs diverged across the three species except in the quiescent center and the meristem, and in the clusters containing border cells, where a shared set of regulators emerged. Silencing three of five candidate regulators reduced border cell number, while silencing a partially overlapping set of three regulators reduced root diameter in M. truncatula. Silencing the C2H2 zinc finger protein MtrunA17_Chr1g0148421 also reduced border cell viability. A maize insertion mutant of bzip89 released fewer border cells than the wild type. These networks offer entry points for tuning mucilage production in cereal and legume crops.

plant biology↗
bioRxiv2026

A chromosome-scale reference genome and single-nucleus root atlas reveal the cellular and molecular basis of coastal adaptation in sand bean (Strophostyles helvola)

Plants adapted to saline coastal habitats provide valuable systems for understanding how natural selection reshapes stress-response programs, yet the cellular and molecular basis of this adaptation remains poorly resolved. Here, we generated a chromosome-scale reference genome and a single-nucleus transcriptomic atlas of roots from sand bean (Strophostyles helvola), a wild legume represented by salt-tolerant Beach and salt-sensitive Inland ecotypes. The atlas comprised 87,901 nuclei assigned to 25 transcriptional clusters representing 16 major root cell types. Salt exposure elicited cell-type-specific transcriptional responses that differed between Beach and Inland roots. Beach roots preferentially maintained respiration-, energy metabolism-, and protein-homeostasis-associated functions, whereas Inland roots showed stronger induction of canonical abiotic-stress, ABA, water-deficit, hypoxia, and oxidative-stress programs. Integrating baseline ecotype differences with salt-responsive expression revealed that many genes induced by salt in Inland roots were already expressed at higher levels in untreated Beach roots. This baseline-enriched configuration comprised a broadly distributed regulatory backbone, including ERF-family transcription factors and RING-type E3 ubiquitin ligases, together with cell-type-associated modules involving ion and water transport at the root-soil interface, redox and dehydration protection in outer-root tissues, endodermal barrier-associated genes, and vascular regulatory candidates. These findings support a model in which Beach salt tolerance is associated not with entirely distinct stress-response pathways, but with the pre-existing and spatially organized deployment of conserved protective programs that remain responsive to salt exposure. Our study establishes genomic and cellular resources for sand beans and provides a framework for investigating how natural variation in the regulation and cellular organization of conserved pathways contributes to environmental stress tolerance.

plant biology↗
bioRxiv2025

A Circadian Light Regulator Controls a Core CAM Gene in the Ice Plant's C3-to-CAM Transition

Crassulacean acid metabolism (CAM) enhances drought tolerance by shifting carbon fixation to the night, improving water-use efficiency compared to C3 and C4 photosynthesis. However, the molecular regulators of CAM induction remain poorly understood. Here, we generate the first single-nucleus transcriptome atlas of a CAM species, Mesembryanthemum crystallinum, to resolve transcriptional dynamics at the cell-type level during the C3-to-CAM transition. Using snRNA-seq and a 24-hour time-course bulk RNA-seq dataset, we identify PPCK1, a key CAM enzyme regulator, as part of a co-expression network enriched in circadian clock genes and salt-induced pathways. We demonstrate that the ice plant HY5 (McHY5) directly activates PPCK1, a function absent in the C3 model species Arabidopsis thaliana. This discovery reveals a fundamental divergence in transcription factor activity between a CAM and a C3 species, suggesting that CAM evolution in M. crystallinum involved a rewiring of core regulatory elements underlying CAM. Identifying a transcription factor that directly controls a major CAM gene provides a key step toward decoding CAM regulatory architecture and opens new avenues for engineering drought-resilient crops.

plant biology↗
bioRxiv2025

InteracTor: Feature Engineering and Explainable AI for Profiling Protein Structure-Interaction-Function Relationships

Characterizing protein families structural and functional diversity is essential for understanding their biological roles. Traditional analyses often focus on primary and secondary structures, which may not fully capture complex protein interactions. Here we introduce InteracTor, a novel toolkit that extracts multimodal features from protein three-dimensional (3D) structures, including interatomic interactions like hydrogen bonds, van der Waals forces, and hydrophobic contacts. By integrating Explainable AI (XAI) techniques, we quantified the importance of the extracted features in the classification of protein structural and functional families. InteracTors interpretable features enable mechanistic insights into the determinants of protein structure, function, and dynamics, offering a transparent means to assess their predictive power within machine learning models. Interatomic interaction features extracted by InteracTor demonstrated superior predictive power for protein family classification compared to features based solely on primary or secondary structure, revealing the importance of considering specific tertiary contacts in computational protein analysis. This work provides a robust framework for future studies aiming to enhance the capabilities of models for protein function prediction and drug discovery. AUTHOR SUMMARYInteracTor is a computational toolkit designed to enhance our understanding of protein structure and function by focusing on three-dimensional (3D) structural interactions. Unlike traditional approaches that primarily rely on sequence or secondary structure data, InteracTor extracts biologically meaningful features such as hydrogen bonds, van der Waals forces, and hydrophobic contacts, which are critical for protein stability and dynamics. By integrating these features into machine learning models alongside explainable AI methods, InteracTor provides interpretable insights into how specific structural interactions influence protein behavior. Our results demonstrate that tertiary structure features significantly improve the accuracy of protein family classification compared to sequence-based methods alone, underscoring the importance of considering 3D interactions in computational protein analyses. The toolkits modular design makes it adaptable for diverse applications, including drug discovery and protein engineering. In a broader context, InteracTor bridges the gap between computational biology and practical applications in medicine and biotechnology by offering a transparent and robust framework for analyzing proteins at a molecular level. This work represents a step forward in leveraging structural data to advance predictive modeling and biological discovery.

bioinformatics↗
bioRxiv2025

Single-nuclei transcriptomics revealed auxin-driven mechanisms of wood plasticity and severe drought tolerance in poplar

Drought significantly affects forests and woody crops by limiting their growth, increasing their susceptibility to diseases, and reducing productivity. Wood anatomical plasticity is a crucial adaptive mechanism that enables trees to cope with fluctuations in water availability. During severe drought, trees develop more and narrower vessels, enhancing hydraulic safety and reducing the risk of embolism. However, the molecular regulation of vessel formation is still not well understood. Using single-nucleus transcriptomics, we generated a cell type-specific gene expression map of the mature poplar stem under well-watered and drought conditions. Our findings revealed extensive gene expression reprogramming in xylem-forming cells, with changes in auxin homeostasis identified as a key mechanism for anatomical adaptation. Specifically, we showed that poplar WAT1-like genes control vessel spatial patterning. Additionally, the downregulation of WAT1-like gene expression in the dividing cells of the vascular cambium and the upregulation of MP-like gene in cells undergoing early vessel differentiation facilitate the formation of secondary xylem with narrower and more numerous vessels. Furthermore, the wat2 mutant exhibited greater drought tolerance than wild-type trees, underscoring its potential for developing drought-resilient tree varieties. These insights enhance our understanding of xylem plasticity and provide valuable targets for improving drought tolerance in woody plants.

plant biology↗
bioRxiv2024

InteracTor: A new integrative feature extraction toolkit for improved characterization of protein structural properties

Understanding the structural and functional diversity of protein families is crucial for elucidating their biological roles. Traditional analyses often focus on primary and secondary structures, which include amino acid sequences and local folding patterns like alpha helices and beta sheets. However, primary and secondary structures alone may not fully represent the complex interactions within proteins. To address this limitation, we developed a new algorithm (InteracTor) to analyze proteins by extracting features from their three-dimensional (3D) structures. The toolkit extracts interatomic interaction features such as hydrogen bonds, van der Waals interactions, and hydrophobic contacts, which are crucial for understanding protein dynamics, structure, and function. Incorporating 3D structural data and interatomic interaction features provides a more comprehensive understanding of protein structure and function, potentially enhancing downstream predictive modeling capabilities. By using the extracted features in Mutual Information scoring (MI), Principal Component Analysis (PCA), t-distributed Stochastic Neighbor Embedding (t-SNE), Uniform Manifold Approximation and Projection (UMAP), and hierarchical clustering analysis as use cases, we identified clear separations among protein structural families, highlighting distinct functional aspects. Our analysis revealed that interatomic interaction features were more informative than protein secondary structure features, providing insights into potential structural and functional properties. These findings underscore the significance of considering tertiary structure in protein analysis, offering a robust framework for future studies aiming at enhancing the capabilities of models for protein function prediction and drug discovery.

bioinformatics↗
bioRxiv2024

Mesophyll-Specific Circadian Dynamics of CAM Induction in the Ice Plant Unveiled by Single-Cell Transcriptomics

Crassulacean acid metabolism (CAM) is an evolutionary modification of the C3 photosynthetic carbon dioxide fixation pathway used by approximately 7% of terrestrial plants to live in drought-prone environments. Facultative CAM species, such as Mesembryanthemum crystallinum (common ice plant), possess the unique ability to switch from C3 to CAM photosynthesis in response to high-salinity and water-deficit stress. Here we characterized the environmentally-triggered transition from C3 to CAM in the ice plant using single nucleus RNA sequencing (snRNA-seq) to identify its putative regulators, supported by a novel high-quality assembled and annotated genome. Analysis of snRNA-seq datasets from ice plant leaves transitioning between C3 and CAM collected at dawn and dusk revealed substantial transcriptional changes in mesophyll cells at the onset of CAM induction. Notably, our findings identify mesophyll sub-cell types engaged in either CAM or C3 photosynthesis at dusk. Cell trajectory inference analysis reconstructed both 24-hour CAM and C3 cycles, enabling a direct comparison of gene expression profiles in these pathways. This comparative study uncovered divergent expression patterns of key circadian clock genes in CAM and C3 cell trajectories, pointing to a connection between circadian regulation and CAM induction.

plant biology↗
bioRxiv2023

The Single-Cell Transcriptome Program of Nodule Development Cellular Lineages in Medicago truncatula

Legumes can establish a symbiotic relationship with nitrogen-fixing rhizobia by developing nodules after root exposure to lipo-chito-oligosaccharides secreted by the bacteria. Nodule development initiates with anticlinal mitotic divisions in the pericycle and endodermal and inner cortical cells, establishing cell lineages that ultimately form each nodule compartment. We characterized these lineages by isolating and sequencing the transcriptome of Medicago truncatula single nuclei derived from uninoculated roots and roots undergoing early nodule development at 24, 48, and 96 hours after inoculation. To enrich samples for cells responding to the rhizobia, we complemented the analysis of the Medicago wild-type genotype A17 with a mutant for the autoregulation of nodulation, sunn-4. Analysis of cell lineage trajectories derived from the cortex indicates that their transcriptome is initially enriched for cytokinin perception and signaling while repressing auxin accumulation. As these cells differentiate to form nodules, expression of genes related to auxin biosynthesis, transport, and signaling was enhanced, while genes involved in cytokinin degradation were activated as lineages bifurcated to form the nodule meristem and infection zones. While the contribution of auxin and cytokinin in nodule development has been recognized, this single-cell resource quantifies the expression of each of their regulators, receptors and targets as cells divide and differentiate to form each nodule compartment.

plant biology↗
bioRxiv2022

The western redcedar genome reveals low genetic diversity in a self-compatible conifer

We assembled the 9.8 Gbp genome of western redcedar (WRC, Thuja plicata), an ecologically and economically important conifer species of the Cupressaceae. The genome assembly, derived from a uniquely inbred tree produced through five generations of self-fertilization (selfing), was determined to be 86% complete by BUSCO analysis - one of the most complete genome assemblies for a conifer. Population genomic analysis revealed WRC to be one of the most genetically depauperate wild plant species, with an effective population size of approximately 300 and no significant genetic differentiation across its geographic range. Nucleotide diversity, {pi}, is low for a continuous tree species, with many loci exhibiting zero diversity, and the ratio of {pi} at zero-to four-fold degenerate sites is relatively high ([~] 0.33), suggestive of weak purifying selection. Using an array of genetic lines derived from up to five generations of selfing, we explored the relationship between genetic diversity and mating system. While overall heterozygosity was found to decline faster than expected during selfing, heterozygosity persisted at many loci, and nearly 100 loci were found to deviate from expectations of genetic drift, suggestive of associative overdominance. Non-reference alleles at such loci often harbor deleterious mutations and are rare in natural populations, implying that balanced polymorphisms are maintained by linkage to dominant beneficial alleles. This may account for how WRC remains responsive to natural and artificial selection, despite low genetic diversity.

plant biology↗
bioRxiv2022

Two shifts in evolutionary lability underlie independent gains and losses of root-nodule symbiosis in a single clade of plants

Root nodule symbiosis (RNS) allows plants to access atmospheric nitrogen converted into usable forms through a mutualistic relationship with soil bacteria. RNS is a complex trait requiring coordination from both the plant host and the bacterial symbiont, and pinpointing the evolutionary origins of root nodules is critical for understanding the genetic basis of RNS. This endeavor is complicated by data limitations and the intermittent presence of RNS in a single clade of ca. 30,000 species of flowering plants, i.e., the nitrogen-fixing clade (NFC). We developed the most extensive de novo phylogeny for all major lineages of the NFC and an enhanced root nodule trait database to reconstruct the evolution of RNS. Through identification of the evolutionary pathway to RNS gain, we show that shifts among heterogeneous evolutionary rates can explain how a complex trait such as RNS can arise many times across a large phylogeny. Our analysis identifies a two-step process in which an ancestral precursor state gave rise to a more labile state from which RNS was quickly gained at specific points in the NFC. Our rigorous reconstruction of ancestral states illustrates how a two-step pathway could have led to multiple independent gains and losses of RNS, contrary to recent hypotheses invoking just a single gain and numerous losses. RNS may be an example of multi-level convergent evolution, thus requiring a broader phylogenetic and genetic scope for genome-phenome mapping to elucidate mechanisms enabling fully functional RNS.

evolutionary biology↗
bioRxiv2021

Single-cell analysis resolves the genetic program of primary vascular system formation in hybrid poplar

Despite the enormous potential of novel approaches to explore gene expression at a single-cell level, we lack a high-resolution and cell type-specific gene expression map of the shoot apex in woody perennials. We use single-nuclei RNA sequencing to determine the cell type-specific transcriptome of the Populus vegetative shoot apex. We identified highly heterogeneous cell populations clustered into seven broad groups represented by 18 transcriptionally distinct cell clusters. Next, we established the developmental trajectories of epidermal cells, leaf mesophyll, and vascular tissue. Motivated by the high similarities between Populus and Arabidopsis cell population in the vegetative apex, we created and applied a pipeline for interspecific single-cell expression data integration. We contrasted the developmental trajectories of primary phloem and xylem formation in both species, establishing the first comparison of primary vascular development between a model annual herbaceous and a woody perennial plant species. Our results offer a valuable resource for investigating the basic principles underlying cell division and differentiation conserved between herbaceous and perennial species, which also allows the evaluation of the divergencies at single-cell resolution. One Sentence SummarySingle-cell RNA-seq of the vegetative shoot apex resolved the genetic program of primary vascular development in hybrid poplar.

plant biology↗
bioRxiv2021

Temporal change in chromatin accessibility predicts regulators of nodulation in Medicago truncatula

Rhizobia can establish symbiotic associations with legumes to provide plants with nitrogen needed in agricultural systems. Symbiosis triggers extensive genome and transcriptome remodeling in the plant, yet the extent of chromatin changes and impact on gene expression is unknown. We profiled the temporal chromatin accessibility (ATAC-seq) and transcriptome (RNA-seq) dynamics of M. truncatula roots treated with rhizobia lipo-chitooligosaccharides. Using a novel approach, Dynamic Regulatory Module Networks, we predicted gene expression as a function of chromatin accessibility and accessible cis-regulatory elements. This approach identified the cis-regulatory elements and associated transcription factors that most significantly contribute to transcriptomic changes triggered by lipo-chitooligosaccharides. Regulators involved in auxin (IAA4-5,SHY2), ethylene (EIN3, ERF1) and abscisic acid (ABI5) hormone response, as well as histone and DNA methylation (IBM1), emerged among those most predictive of transcriptome dynamics. RNAi-based knockdown of EIN3 and ERF1 reduced nodule number in M. truncatula validating the role of these predicted regulators in symbiosis between legumes and rhizobia. Significance StatementLegumes can fix nitrogen through symbiosis with rhizobia in root nodules, a critical mutualistic relationship for crop productivity and agricultural sustainability. Introducing this symbiotic relationship into non-legume crops is of great interest, but limited knowledge of host genome modifications induced by rhizobia has hampered such efforts. We applied time-course analysis of chromatin accessibility and gene expression of M. truncatula roots treated with rhizobia lipochitooligosaccharides. We show that extensive remodeling of genome accessibility drives a large component of the temporal transcriptome dynamics. By predicting gene expression as a function of accessibility of regulatory features, we identified known and novel regulators that are associated with early nodule development, which may be critical for its engineering into crops.

plant biology↗
bioRxiv2021

Functional and comparative genomics reveals conserved noncoding sequences in the nitrogen-fixing clade

Nitrogen is one of the most inaccessible plant nutrients, but certain species have overcome this limitation by establishing symbiotic interactions with nitrogen-fixing bacteria in the root nodule. This root nodule symbiosis (RNS) is restricted to species within a single clade of angiosperms, suggesting a critical evolutionary event at the base of this clade, which has not yet been determined. While genes implicated in the RNS are present in most plant species (nodulating or not), gene sequence conservation alone does not imply functional conservation - developmental or phenotypic differences can arise from variation in the regulation of transcription. To identify putative regulatory sequences implicated in the evolution of RNS, we aligned the genomes of 25 species capable of nodulation. We detected 3,091 conserved noncoding sequences (CNS) in the nitrogen-fixing clade that are absent from outgroup species. Functional analysis revealed that chromatin accessibility of 452 CNS significantly correlates with the differential regulation of genes responding to lipo-chitooligosaccharides in Medicago truncatula. These included 38 CNS in proximity to 19 known genes involved in RNS. Five such regions are upstream of MtCRE1, Cytokinin Response Element 1, required to activate a suite of downstream transcription factors necessary for nodulation in M. truncatula. Genetic complementation of a Mtcre1 mutant showed a significant association between nodulation and the presence of these CNS, when they are driving the expression of a functional copy of MtCRE1. Conserved noncoding sequences, therefore, may be required for the regulation of genes controlling the root nodule symbiosis in M. truncatula.

plant biology↗
bioRxiv2021

Spatiotemporal cytokinin signaling imaging reveals IPT3 function in nodule development in Medicago truncatula

Most legumes can establish a symbiotic association with soil rhizobia that triggers the development of root nodules. These nodules host the rhizobia and allow them to fix nitrogen efficiently. The perception of bacterial lipo-chitooligosaccharide (LCO) signal in the epidermis initiates a signaling cascade that allows rhizobial intracellular infection in the root and de-differentiation and activation of cell division that gives rise to the nodule. Nodule organogenesis and rhizobial infection need to be coupled in space and time for successful nodulation. The plant hormone cytokinin (CK) acts as an essential positive regulator of nodule organogenesis, and specific CK receptors are required for nodule formation. Temporal regulation of tissue-specific CK signaling and biosynthesis in response to LCOs or Sinorhizobium meliloti inoculation in Medicago truncatula remains poorly understood. In the present study, using a fluorescence-based CK sensor (TCSn::nls:tGFP), we performed a high-resolution tissue-specific temporal characterization of the CK responses sequential activation during root infection and nodule development in M. truncatula after inoculation with S. meliloti. Loss-of-function mutants of the CK-biosynthetic gene ISOPENTENYL TRANSFERASE 3 (IPT3) showed impairment of nodulation, suggesting that IPT3 is required for nodule development in M. truncatula. Simultaneous live imaging of pIPT3::tdTOMATO and the CK sensor showed that IPT3 induction in the root stele at the base of nodule primordium contributes to CK biosynthesis, which in turn promotes expression of positive regulators of nodule organogenesis in M. truncatula. One-sentence summaryHigh-resolution spatiotemporal imaging of cytokinin signaling reveals IPT3 function during indeterminate nodule development in Medicago truncatula

plant biology↗
bioRxiv2021

Asc-Seurat - Analytical single-cell Seurat-based web application

SummarySingle-cell RNA sequencing (scRNA-seq) has become a popular approach for studying the transcriptome, providing a powerful tool for discovering and characterizing cell types and their developmental trajectories. However, scRNA-seq analysis is complex, requiring a continuous, iterative process to refine the data processing and uncover relevant biological information. We present Asc-Seurat, a feature rich workbench, providing a user-friendly and easy-to-install web application encapsulating the necessary tools for an all-encompassing and fluid scRNA-seq data analysis. Availability and implementationAsc-Seurat is available at https://github.com/KirstLab/asc_seurat/ and released under GNU 3 license. Contactmkirst@ufl.edu Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗
bioRxiv2021

Genomic Prediction in Family Bulks Using Different Traits and Cross-Validations in Pine

Genomic prediction (GP) integrates statistical, genomic and computational tools to improve the estimation of breeding values and increase genetic gain. Due to the broad diversity in biology, breeding scheme, propagation method, and unit of selection, no universal GP approach can be applied in all crops. In a genome-wide family prediction (GWFP) approach, the family bulk is the basic unit of selection. We tested GWFP in two loblolly pine (Pinus taeda L.) datasets: a breeding population composed of 63 full-sib families (5-20 individuals per family), and a simulated population with the same pedigree structure. In both populations, phenotypic and genomic data was pooled at the family level in silico. Marker effects were estimated to compute genomic estimated breeding values at the individual (GEBV) and family (GWFP) levels. Less than six individuals per family produced inaccurate estimates of family phenotypic performance and allele frequency. Tested across different scenarios, GWFP predictive ability was higher than those for GEBV in both populations. Validation sets composed of families with similar phenotypic mean and variance as the training population yielded predictions consistently higher and more accurate than other validation sets. Results revealed potential for applying GWFP in breeding programs whose selection unit are family bulks, and for systems where family can serve as training sets. The GWFP approach is well suited for crops that are routinely genotyped and phenotyped at the plot-level, but it can be extended to other breeding programs. Higher predictive ability obtained with GWFP would motivate the application of GP in these situations.

genomics↗
bioRxiv2021

A robust method of nuclei isolation for single-cell RNA sequencing of solid tissues from the plant genus Populus

Single-cell transcriptome analysis has been extensively applied in humans and animal models to uncover gene expression heterogeneity between the different cell types of a tissue or an organ. It demonstrated its capability to discover the key regulatory elements that determine cell fate during developmental programs such as brain or heart development. Single-cell analysis requires the isolation and labeling of the messenger RNA (mRNA) derived from each cell. These challenges were primarily addressed in mammals by developing microfluidic-based approaches. For plant species whose cells contain cell walls, these approaches have generally required the generation of isolated protoplasts. Many plant tissues secondary cell wall hinders enzymatic digestion required for individual protoplast isolation, resulting in an unequal representation of cell types in a protoplast population. This limitation is especially critical for cell types located in the inner layers of a tissue or the inner tissues of an organ. Consequently, single-cell RNA sequencing (scRNA-seq) studies using microfluidic approaches in plants have mainly been restricted to Arabidopsis roots, for which well-established procedures of protoplast isolation are available. Here we present a simple alternative approach to generating high-quality protoplasts from plant tissue by characterizing the mRNA extracted from individual nuclei instead of whole cells. We developed the protocol using two different plant materials with varying cellular complexity levels and cell-wall structure, Populus shoot apices, and more lignified stems. Using the 10x Genomics Chromium technology, we show that this procedure results in intact mRNA isolation and limited leakage, with a broad representation of individual cell transcriptomes.

plant biology↗