Biology subjects

Rhee, S. Y.

Publications and source records attributed to Rhee, S. Y..

25 records · Page 2Linked to original sources

bioRxiv2021

Interdependent Iron and Phosphorus Availability Controls Photosynthesis Through Retrograde Signaling

Iron deficiency hampers photosynthesis and is associated with chlorosis. We recently showed that iron deficiency-induced chlorosis depends on phosphorus availability. How plants integrate these cues to control chlorophyll accumulation is unknown. Here, we show that iron limitation downregulates photosynthesis genes in a phosphorus-dependent manner. Using transcriptomics and genome-wide association analysis, we identify two genes, a chloroplastic ascorbate transporter (PHT4;4) and a nuclear transcription factor (bZIP58), which prevent the downregulation of photosynthesis genes leading to the stay-green phenotype under iron-phosphorus deficiency. Joint limitation of these nutrients induces ascorbate accumulation by activating expression of an ascorbate biosynthesis gene, VTC4, which requires bZIP58. Exogenous ascorbate prevents iron deficiency-induced chlorosis in vtc4 mutants, but not in bzip58 or pht4;4. Our study demonstrates chloroplastic ascorbate transport is essential for preventing the downregulation of photosynthesis genes under iron-phosphorus combined deficiency. These findings uncover a molecular pathway coordinating chloroplast-nucleus communication to adapt photosynthesis to nutrient availability.

plant biology↗

bioRxiv2020

Hydration-dependent phase separation of a prion-like protein regulates seed germination during water stress.

Many organisms evolved strategies to survive and thrive under extreme desiccation. Plant seeds protect dehydrated embryos from a variety of stressors and can even lay dormant for millennia. While hydration is the key trigger that reactivates metabolism and kick-starts germination, the exact mechanism by which the embryo senses water remains unresolved. We identified an uncharacterized Arabidopsis thaliana prion-like protein we named FLOE1, which phase separates upon hydration and allows the embryo to sense water stress. We demonstrate that the biophysical states of FLOE1 condensates modulate its biological function in vivo in suppressing seed germination under unfavorable environments. We also find intragenic, intraspecific, and interspecific natural variations in phase separation propensity of FLOE1 homologs. These findings demonstrate a physiological role of phase separation in a multicellular organism and have direct implications for plant ecology and agriculture, especially the design of drought resistant crops, in the face of climate change.

cell biology↗

bioRxiv2020

Genome-Enabled Discovery of Anthraquinone Biosynthesis in Senna tora

Senna tora is a widely used medicinal plant. Its health benefits have been attributed to the large quantity of anthraquinones, but how they are made in plants remains a mystery. To identify the genes responsible for plant anthraquinone biosynthesis, we sequenced and annotated the genome of S. tora at the chromosome level with contig N50 and super-scaffold N50 of 4.03 Mb and 41.7 Mb. Comparison among related plant species showed that a chalcone synthase-like (CHS-L) gene family has lineage-specifically and rapidly expanded in S. tora. Combining genomics, transcriptomics, metabolomics, and biochemistry, we identified a CHS-L responsible for biosynthesis of anthraquinones, the first example in plants. The S. tora reference genome will accelerate the discovery of biologically active anthraquinone biosynthesis pathways in medicinal plants. One Sentence SummaryThe chromosome-scale reference genome of a medicinal plant Senna tora, transcriptomics, metabolomics, and biochemical analysis provide new insights into anthraquinone biosynthesis in plants.

plant biology↗

bioRxiv2020

QTG-Finder2: a generalized machine-learning algorithm for prioritizing QTL causal genes in plants

Linkage mapping has been widely used to identify quantitative trait loci (QTL) in many plants and usually requires a time-consuming and labor-intensive fine mapping process to find the causal gene underlying the QTL. Previously, we described QTG-Finder, a machine-learning algorithm to rationally prioritize candidate causal genes in QTLs. While it showed good performance, QTG-Finder could only be used in Arabidopsis and rice because of the limited number of known causal genes in other species. Here we tested the feasibility of enabling QTG-Finder to work on species that have few or no known causal genes by using orthologs of known causal genes as training set. The model trained with orthologs could recall about 64% of Arabidopsis and 83% of rice causal genes when the top 20% ranked genes were considered, which is similar to the performance of models trained with known causal genes. We further extended the algorithm to include polymorphisms in conserved non-coding sequences and gene presence/absence variation as additional features. Using this algorithm, QTG-Finder2, we trained and cross-validated Sorghum bicolor and Setaria viridis models. The S. bicolor model was validated by causal genes curated from the literature and could recall 70% of causal genes when the top 20% ranked genes were considered. In addition, we applied the S. viridis model and public transcriptome data to prioritize a plant height QTL and identified 13 candidate genes. QTL-Finder2 can accelerate the discovery of causal genes in any plant species and facilitate agricultural trait improvement.

bioinformatics↗

bioRxiv2019

Epigenomic Landscape of Arabidopsis thaliana Metabolism Reveals Bivalent Chromatin on Specialized Metabolic Genes

Metabolism underpins development and physiology, but little is known about how metabolic genes and pathways are regulated, especially in multicellular organisms. Here, we identified regulatory patterns of 16 epigenetic modifications across metabolism in Arabidopsis thaliana. Surprisingly, specialized metabolic genes, often involved in defense, were predominantly regulated by two modifications that have opposite effects on gene expression, H3K27me3 (repression) and H3K18ac (activation). Using camalexin biosynthesis genes as an example, we confirmed that these two modifications were co-localized to form bivalent chromatin. Mutants defective in H3K27m3 and H3K18ac modifications showed that both modifications are required to determine the normal transcriptional kinetics of these genes upon stress stimuli. Our study suggests that this type of bivalent chromatin, which we name a kairostat, controls the precise timing of gene expression upon stimuli.\n\nOne Sentence SummaryThis study identified a novel regulatory mechanism controlling specialized metabolism in Arabidopsis thaliana.

systems biology↗

bioRxiv2018

QTG-Finder: a machine-learning algorithm to prioritize causal genes of quantitative trait loci in Arabidopsis and rice

Linkage mapping is one of the most commonly used methods to identify genetic loci that determine a trait. However, the loci identified by linkage mapping may contain hundreds of candidate genes and require a time-consuming and labor-intensive fine mapping process to find the causal gene controlling the trait. With the availability of a rich assortment of genomic and functional genomic data, it is possible to develop a computational method to facilitate faster identification of causal genes. We developed QTG-Finder, a machine-learning algorithm to prioritize causal genes by ranking genes within a quantitative trait locus (QTL). Two predictive models were trained separately based on known causal genes in Arabidopsis and rice. With an independent validation analysis, we demonstrate the models can correctly prioritize about 80% and 55% of Arabidopsis and rice causal genes when the top 20% ranked genes were considered. The models can prioritize different types of traits though at different efficiency. We also identified several important features of causal genes including non-synonymous SNPs at conserved protein sequences, paralog copy number, and being a transporter. This work lays the foundation for systematically understanding characteristics of causal genes and establishes a pipeline to predict causal genes based on public data.

systems biology↗

bioRxiv2018

Systems approaches provide new insights into Arabidopsis thaliana root growth under mineral nutrient limitation

The molecular genetic mechanisms by which plants modulate their root growth rate (RGR) in response to nutrient deficiency are largely unknown. Using a panel of Arabidopsis thaliana natural accessions, we provide a comprehensive combinatorial analysis of RGR variation under macro- and micronutrient deficiency, namely phosphorus (P), iron (Fe), and zinc (Zn), which affect root growth in opposite directions. We found that while -P stimulates early RGR of most accessions, -Fe or -Zn reduces it. The combination of either -P-Fe or -P-Zn leads to suppression of the growth inhibition exerted by -Fe or -Zn alone. Surprisingly, Arabidopsis reference accession Columbia (Col-0) is not representative of the species under -P and -Zn. Using a genome wide association study, we identify candidate genes that control RGR under the assayed nutrient deficiency conditions. By using a network biology driven search using these candidate genes, we further identify a functional module enriched in regulation of cell cycle, DNA replication and chromatin modification that possibly underlies the suppression of root growth reduction in -P-Fe conditions. Collectively, our findings provide a framework for understanding the regulation of RGR under nutrient deficiency, and open new routes for the identification of both large effect genes and favorable allelic variations to improve root growth.

plant biology↗