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Biology subjects

Bargmann, B.

Publications and source records attributed to Bargmann, B..

2 recordsLinked to original sources

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↗

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↗