Comparative Transcriptomics of Lowland Rice Varieties Uncovers Novel Candidate Genes for Adaptive Iron Excess Tolerance

Genome-Wide Association-Based Identification of Alleles, Genes and Haplotypes Influencing Yield in Rice (Oryza sativa L.) Under Low-Phosphorus Acidic Lowland Soils

Rice provides poor yields in acidic soils due to several nutrient deficiencies and metal toxicities. The low availability of phosphorus (P) in acidic soils offers a natural condition for screening genotypes for grain yield and phosphorus utilization efficiency (PUE). The objective of this study was to phenotype a subset of indica rice accessions from 3000 Rice Genome Project (3K-RGP) under acidic soils and find associated genes and alleles. A panel of 234 genotypes, along with checks, were grown under low-input acidic soils for two consecutive seasons, followed by a low-P-based hydroponic screening experiment. The heritability of the agro-morphological traits was high across seasons, and Ward's clustering method identified 46 genotypes that can be used as low-P-tolerant donors in acidic soil conditions. Genotypes ARC10145, RPA5929, and K1559-4, with a higher grain yield than checks, were identified. Over 29 million SNPs were retrieved from the Rice SNP-Seek database, and after quality control, they were utilized for a genome-wide association study (GWAS) with seventeen traits. Ten quantitative trait nucleotides (QTNs) for three yield traits and five QTNs for PUE were identified. A set of 34 candidate genes for yield-related traits was also identified. An association study using this indica panel for an already reported 1.84 Mbp region on chromosome 2 identified genes Os02g09840 and Os02g08420 for yield and PUE, respectively. A haplotype analysis for the candidate genes identified favorable allelic combinations. Donors carrying the superior haplotypic combinations for the identified genes could be exploited in future breeding programs.

The role of ascorbate redox turnover in iron toxicity tolerance

Iron (Fe) toxicity is a major abiotic stress in lowland rice production. Breeding tolerant varieties has proven challenging due to the complex genetic architecture of Fe toxicity tolerance and the strong genotype-by-environment interactions. Additionally, conventional methods for phenotyping visible stress symptoms are often inaccurate, inconsistent, and lack reproducibility. In our previous work, we identified that ascorbate redox regulation, mediated by the activities of dehydroascorbate reductase (DHAR) and ascorbate oxidase (AO), contributed to high tolerance in an indica rice genotype across various environments. To explore whether this mechanism is common among other rice genotypes, we selected ten genotypes with contrasting stress symptoms under Fe-toxic conditions to examine the roles of DHAR and AO in regulating Fe toxicity tolerance. Additionally, we aimed to develop objective and accurate image-based phenotyping methods to replace the traditional leaf bronzing scoring method. Among the ten genotypes we tested, we found significant positive correlations between DHAR activity and stress symptoms in plants grown under both Fe toxicity and control conditions, suggesting a general link between ascorbate redox regulation and Fe toxicity tolerance. Using RGB signals from leaf images of plants exposed to 1000 mg/L Fe2+, we evaluated 36 different color indices to quantify stress symptoms. We identified the normalized green‒red difference index as most significant in quantifying stress symptoms under Fe toxicity conditions. Our findings suggest that DHAR activity could be potentially employed as a biomarker in the screening of rice germplasms and breeding tolerant cultivars to Fe toxicity.

You can't always get as much iron as you want: how rice plants deal with excess of an essential nutrient

Iron (Fe) is an essential nutrient for almost all organisms. However, free Fe within cells can lead to damage to macromolecules and oxidative stress, making Fe concentrations tightly controlled. In plants, Fe deficiency is a common problem, especially in well-aerated, calcareous soils. Rice (Oryza sativa L.) is commonly cultivated in waterlogged soils, which are hypoxic and can cause Fe reduction from Fe3+ to Fe2+, especially in low pH acidic soils, leading to high Fe availability and accumulation. Therefore, Fe excess decreases rice growth and productivity. Despite the widespread occurrence of Fe excess toxicity, we still know little about the genetic basis of how rice plants respond to Fe overload and what genes are involved in variation when comparing genotypes with different tolerance levels. Here, we review the current knowledge about physiological and molecular data on Fe excess in rice, providing a comprehensive summary of the field.

Meta-analysis of transcriptomics studies identifies novel attributes and set of genes involved in iron homeostasis in rice

Iron (Fe) is an important micronutrient for humans as well as for plant growth and development. Rice employs multiple mechanisms to counteract the negative effects of Fe deficiency and Fe toxicity. Previously, many transcriptomics studies have identified hundreds of genes affected by Fe deficiency and/or Fe toxicity. These studies are highly valuable to identify novel genes involved in Fe homeostasis. However, in the absence of their systematic integration, they remain underutilized. A systematic meta-analysis of transcriptomics data from such ten previous studies was performed here to identify various common attributes. From this meta-analysis, it is revealed that under Fe deficiency conditions, root transcriptome is more sensitive and exhibits greater similarity across multiple studies than the shoot transcriptome. Furthermore, under Fe toxicity conditions, upregulated genes are more reliable and consistent than downregulated genes in susceptible cultivars. The integration of data from Fe deficiency and Fe toxicity conditions helped to identify key marker genes for Fe stress. As a proof-of-concept of the analysis, among the genes consistently regulated in opposite directions under Fe deficiency and toxicity conditions, two genes were selected: a proton-dependent oligopeptide transporter (POT) family protein and Vacuolar Iron Transporter (VIT)-Like (VTL) gene, and validated their expression and sub-cellular localization. Since VIT genes are known to play an important role in Fe homeostasis in plants, the entire OsVTL gene family in rice was characterized. This meta-analysis has identified many novel candidate genes that exhibit consistent expression patterns across multiple tissues, conditions, and studies. This makes them potential targets for future research aimed at developing Fe-biofortified rice varieties, as well as varieties tolerant to sub-optimal Fe levels in soil.

SEC14-GOLD protein PATELLIN2 binds IRON-REGULATED TRANSPORTER1 linking root iron uptake to vitamin E

Organisms require micronutrients, and Arabidopsis (Arabidopsis thaliana) IRON-REGULATED TRANSPORTER1 (IRT1) is essential for iron (Fe2+) acquisition into root cells. Uptake of reactive Fe2+ exposes cells to the risk of membrane lipid peroxidation. Surprisingly little is known about how this is avoided. IRT1 activity is controlled by an intracellular variable region (IRT1vr) that acts as a regulatory protein interaction platform. Here, we describe that IRT1vr interacted with peripheral plasma membrane SEC14-Golgi dynamics (SEC14-GOLD) protein PATELLIN2 (PATL2). SEC14 proteins bind lipophilic substrates and transport or present them at the membrane. To date, no direct roles have been attributed to SEC14 proteins in Fe import. PATL2 affected root Fe acquisition responses, interacted with ROS response proteins in roots, and alleviated root lipid peroxidation. PATL2 had high affinity in vitro for the major lipophilic antioxidant vitamin E compound α-tocopherol. Molecular dynamics simulations provided insight into energetic constraints and the orientation and stability of the PATL2-ligand interaction in atomic detail. Hence, this work highlights a compelling mechanism connecting vitamin E with root metal ion transport at the plasma membrane with the participation of an IRT1-interacting and α-tocopherol-binding SEC14 protein.

A2TEA: Identifying trait-specific evolutionary adaptations

Background: Plants differ in their ability to cope with external stresses (e.g., drought tolerance). Genome duplications are an important mechanism to enable plant adaptation. This leads to characteristic footprints in the genome, such as protein family expansion. We explore genetic diversity and uncover evolutionary adaptation to stresses by exploiting genome comparisons between stress tolerant and sensitive species and RNA-Seq data sets from stress experiments. Expanded gene families that are stress-responsive based on differential expression analysis could hint at species or clade-specific adaptation, making these gene families exciting candidates for follow-up tolerance studies and crop improvement. Software: Integration of such cross-species omics data is a challenging task, requiring various steps of transformation and filtering. Ultimately, visualization is crucial for quality control and interpretation. To address this, we developed A2TEA: Automated Assessment of Trait-specific Evolutionary Adaptations, a Snakemake workflow for detecting adaptation footprints in silico. It functions as a one-stop processing pipeline, integrating protein family, phylogeny, expression, and protein function analyses. The pipeline is accompanied by an R Shiny web application that allows exploring, highlighting, and exporting the results interactively. This allows the user to formulate hypotheses regarding the genomic adaptations of one or a subset of the investigated species to a given stress. Conclusions: While our research focus is on crops, the pipeline is entirely independent of the underlying species and can be used with any set of species. We demonstrate pipeline efficiency on real-world datasets and discuss the implementation and limits of our analysis workflow as well as planned extensions to its current state. The A2TEA workflow and web application are publicly available at: https://github.com/tgstoecker/A2TEA.Workflow and https://github.com/tgstoecker/A2TEA.WebApp, respectively.

Physiological and proteomic dissection of the rice roots in response to iron deficiency and excess

Iron (Fe) disorder is a pivotal factor that limits rice yields in many parts of the world. Extensive research has been devoted to studying how rice molecularly copes with the stresses of Fe deficiency or excess. However, a comprehensive dissection of the whole Fe-responsive atlas at the protein level is still lacking. Here, different concentrations of Fe (0, 40, 350, and 500 μM) were supplied to rice to demonstrate its response differences to Fe deficiency and excess via physiological and proteomic analysis. Results showed that compared with the normal condition, the seedling growth and contents of Fe and manganese were significantly disturbed under either Fe stress. Proteomic analysis revealed that differentially accumulated proteins under Fe deficiency and Fe excess were commonly enriched in localization, carbon metabolism, biosynthesis of amino acids, and antioxidant system. Notably, proteins with abundance retuned by Fe starvation were individually associated with phenylpropanoid biosynthesis, cysteine and methionine metabolism, while ribosome- and endocytosis-related proteins were specifically enriched in treatment of Fe overdose of 500 μM. Moreover, several novel proteins which may play potential roles in rice Fe homeostasis were predicted. These findings expand the understanding of rice Fe nutrition mechanisms, and provide efficient guidance for genetic breeding work. SIGNIFICANCE: Both iron (Fe) deficiency and excess significantly inhibited the growth of rice seedlings. Fe deficiency and excess disturbed processes of localization and cellular oxidant detoxification, metabolisms of carbohydrates and amino acids in different ways. The Fe-deficiency and Fe-excess-responsive proteins identified by the proteome were somewhat different from the reported transcriptional profiles, providing complementary information to the transcriptomic data.

Meta-Analysis of Immune Induced Gene Expression Changes in Diverse Drosophila melanogaster Innate Immune Responses

Simple Summary

Organisms can be infected by a wide range of pathogens, including bacteria, viruses, and parasites. Following infection, the host mounts an immune response to attempt to eliminate the pathogen. These responses are often specific to the type of pathogen and mediated by the expression of specialized genes. We have characterized the expression changes induced in host Drosophila fruit flies following infection by multiple types of pathogens, and identified a small number of genes that show expression changes in each infection. This includes genes that are known to be involved in pathogen resistance, and others that have not been previously studied as immune response genes. These findings provide new insight into transcriptional changes that accompany Drosophila immunity. They may suggest possible roles for the differentially expressed genes in innate immune responses to diverse classes of pathogens, and serve to identify candidate genes for further empirical study of these processes.

Abstract

Organisms are commonly infected by a diverse array of pathogens and mount functionally distinct responses to each of these varied immune challenges. Host immune responses are characterized by the induction of gene expression, however, the extent to which expression changes are shared among responses to distinct pathogens is largely unknown. To examine this, we performed meta-analysis of gene expression data collected from Drosophila melanogaster following infection with a wide array of pathogens. We identified 62 genes that are significantly induced by infection. While many of these infection-induced genes encode known immune response factors, we also identified 21 genes that have not been previously associated with host immunity. Examination of the upstream flanking sequences of the infection-induced genes lead to the identification of two conserved enhancer sites. These sites correspond to conserved binding sites for GATA and nuclear factor κB (NFκB) family transcription factors and are associated with higher levels of transcript induction. We further identified 31 genes with predicted functions in metabolism and organismal development that are significantly downregulated following infection by diverse pathogens. Our study identifies conserved gene expression changes in Drosophila melanogaster following infection with varied pathogens, and transcription factor families that may regulate this immune induction.