Biology subjects

Bargmann, B.

Publications and source records attributed to Bargmann, B..

3 recordsLinked to original sources

bioRxiv2026

Single nucleus transcriptome analysis of Arabidopsis thaliana roots infected with Phytophthora. capsici

Understanding how plant roots coordinate immune responses at the cellular level is key to unraveling host-pathogen interactions. Using single-nucleus RNA sequencing (snRNA-seq) of Arabidopsis thaliana roots 24 hours after Phytophthora. capsici(P. capsici)inoculation, we captured the transcriptional landscape of early infection at single-cell resolution. Four libraries (two infected and two mock-treated) were generated with approximately 26,000 high-quality nuclei with consistent sequencing depth and viability. A reference-based pipeline distinguished host and pathogen transcripts, enabling species-resolved mapping and host-focused single-nucleus transcriptomic analysis. Integration and clustering identified 12 transcriptionally distinct root cell types, encompassing major tissues such as the meristem, cortex, endodermis, and vasculature. Cluster-specific marker analysis confirmed cell-type identities, while differential expression and Gene Ontology enrichment revealed a global transcriptional shift from metabolic and translational processes in mock samples to defense-, stress-, and pathogen-response pathways upon infection. Hormone-related enrichment indicated broad salicylic acid activation across root tissues, spatially confined ethylene signaling in vascular-associated clusters, and localized jasmonic acid responses in cortex and phloem. Together, these results provide a high-resolution view of Arabidopsis root immunity, highlighting a coordinated yet tissue-specific defense architecture in which salicylic acid underpins systemic protection, ethylene modulates vascular defense, and jasmonic acid contributes targeted reinforcement during early P. capsici infection.

bioinformatics↗

bioRxiv2023

Identification of potential Auxin Response Candidate genes for soybean rapid canopy coverage through comparative evolution and expression analysis

Glycine max, soybean, is an abundantly cultivated crop worldwide. Efforts have been made over the past decades to improve soybean production in traditional and organic agriculture, driven by growing demand for soybean-based products. Rapid canopy cover development (RCC) increases soybean yields and suppresses early-season weeds. Genome-wide association studies have found natural variants associated with RCC, however causal mechanisms are unclear. Auxin modulates plant growth and development and has been implicated in RCC traits. Therefore, modulation of auxin regulatory genes may enhance RCC. Here, we focus on the use of genomic tools and existing datasets to identify auxin signaling pathway RCC candidate genes, using a comparative phylogenetics and expression analysis approach. We identified genes encoding 14 TIR1/AFB auxin receptors, 61 Aux/IAA auxin co-receptors and transcriptional co-repressors, and 55 ARF auxin response factors in the soybean genome. We used Bayesian phylogenetic inference to identify soybean orthologs of Arabidopsis thaliana genes, and defined an ortholog naming system for these genes. To further define potential auxin signaling candidate genes for RCC, we examined tissue-level expression of these genes in existing datasets and identified highly expressed auxin signaling genes in apical tissues early in development. We identified at least 4 TIR1/AFB, 8 Aux/IAA, and 8 ARF genes with highly specific expression in one or more RCC-associated tissues. We hypothesize that modulating the function of these genes through gene editing or traditional breeding will have the highest likelihood of affecting RCC while minimizing pleiotropic effects.

bioinformatics↗

bioRxiv2023

Cross-species single-cell annotation with orthologous marker gene groups

Single-cell RNA sequencing (scRNA-seq) technology has been widely used in characterizing various cell types from in plant growth and development1-6. Applications of this technology in Arabidopsis have benefited from the extensive knowledge of cell-type identity markers7,8. Contrastingly, accurate labeling of cell types in other plant species remains a challenge due to the scarcity of known marker genes9. Various approaches have been explored to address this issue; however, studies have found many closest orthologs of cell-type identity marker genes in Arabidopsis do not exhibit the same cell-type identity across diverse plant species10,11. To address this challenge, we have developed a novel computational strategy called Orthologous Marker Gene Groups (OMGs). We demonstrated that using OMGs as a unit to determine cell type identity enables assignment of cell types by comparing 15 distantly related species. Our analysis revealed 14 dominant clusters with substantial conservation in shared cell-type markers across monocots and dicots.

bioinformatics↗