Recombinant Oryza sativa subsp. japonica Probable E3 ubiquitin-protein ligase BAH1-like 2 (Os07g0673200, LOC_Os07g47590)

What is the functional classification of E3 ubiquitin-protein ligase BAH1-like 2 in rice?

E3 ubiquitin-protein ligase BAH1-like 2 (LOC_Os07g47590) functions within the ubiquitin-proteasome system, one of the most important protein degradation pathways in eukaryotic organisms. This pathway plays a critical role in protein turnover and regulation of numerous cellular processes, including stress responses and hormone signaling . The protein is classified as an expressed protein based on experimental evidence, suggesting confirmed expression but incompletely characterized function . Within the broader rice proteome, this E3 ligase belongs to a large family of proteins that selectively target substrates for ubiquitination and subsequent degradation. The ubiquitin-proteasome system in plants like rice contains numerous E3 ubiquitin ligases, with research indicating that E3 ligases play crucial roles in both biotic and abiotic stress responses . Experimental approaches to determine functional classification typically involve quantitative PCR analysis, protein interaction studies, and phenotypic analysis of knockout or overexpression lines.

What genomic and structural characteristics define LOC_Os07g47590?

LOC_Os07g47590 is located on chromosome 7 of the rice genome, as indicated by its locus ID prefix "LOC_Os07" . The gene structure likely contains multiple exons and introns, which is common for genes encoding regulatory proteins like E3 ubiquitin ligases. In terms of protein domain architecture, E3 ubiquitin ligases typically contain specific structural elements necessary for their function, including substrate recognition domains and catalytic domains responsible for the transfer of ubiquitin to target proteins . While specific details about LOC_Os07g47590's structure are not fully characterized in the provided research, comparative genomic approaches suggest it shares homology with other BAH1-like E3 ubiquitin ligases. The BAH (bromo-adjacent homology) domain is often associated with protein-protein interactions, suggesting this protein may have specific interaction partners in its functional pathway. Structural analysis would typically involve protein modeling, crystallography, and domain prediction algorithms to fully elucidate the functional elements within this protein.

How is the expression of Os07g0673200 regulated under normal physiological conditions?

Under normal physiological conditions, the expression of Os07g0673200 (LOC_Os07g47590) appears to be constitutive but tightly regulated, as is common for many regulatory proteins involved in cellular homeostasis. Experimental data suggests that this gene shows detectable baseline expression in standard growth conditions, allowing it to maintain normal cellular functions . The regulation likely involves transcription factors and potentially epigenetic mechanisms that respond to developmental cues and environmental inputs. Quantitative expression analysis methods, including RT-PCR and microarray studies, have been employed to measure baseline expression levels in different tissues and developmental stages. Research on E3 ubiquitin ligases in rice suggests that many members of this family show tissue-specific expression patterns, with some predominantly expressed in particular organs or during specific developmental windows . When studying baseline expression, researchers typically employ reference genes with stable expression profiles to normalize data and account for experimental variation across samples and conditions.

How does the expression pattern of LOC_Os07g47590 change under environmental stress conditions?

Experimental evidence indicates that LOC_Os07g47590 exhibits significant changes in expression under stress conditions, with statistical analysis showing a highly significant genotype × environment interaction (p-Inter = 0.000) . The protein was identified among genes responding differentially to water-limiting conditions in rice cultivars with varying drought tolerance. Specifically, quantitative RT-PCR analysis revealed that while the treatment contrast (drought vs. control) showed a p-value of 0.288, the interaction effect was highly significant, suggesting that this gene's response to drought stress varies considerably between tolerant and susceptible rice varieties . This expression pattern indicates potential involvement in adaptive responses to water limitation, where the gene may contribute to stress tolerance through targeted protein degradation via the ubiquitin-proteasome system. The differential response between cultivars suggests that allelic variation or regulatory differences in this gene might contribute to natural variation in stress tolerance. Researchers investigating this gene should consider not only direct expression changes under stress but also the interaction effects with genetic background when designing experiments to elucidate its function in stress adaptation.

What experimental approaches are most effective for characterizing the function of E3 ubiquitin ligase BAH1-like 2?

Functional characterization of E3 ubiquitin ligase BAH1-like 2 requires a multi-faceted experimental approach combining genetic, biochemical, and phenotypic analyses. CRISPR-Cas9 gene editing represents a powerful initial step, allowing creation of knockout or knockdown lines to observe phenotypic consequences of gene loss, particularly under stress conditions where the gene shows significant interaction effects . In parallel, yeast two-hybrid screens or co-immunoprecipitation followed by mass spectrometry can identify substrate proteins targeted by this E3 ligase, providing critical insights into its biological pathways. In vitro ubiquitination assays with recombinant protein can confirm enzymatic activity and substrate specificity, while transient expression systems can evaluate subcellular localization. Transcriptomic and proteomic analyses of mutant lines under various environmental conditions, particularly drought stress where interaction effects are significant (p-Inter = 0.000), can reveal downstream pathways affected by this protein . Expression analysis should include multiple biological replicates and carefully selected reference genes to ensure robust quantification, as demonstrated in previous studies where LOC_Os07g47590 expression was measured across different experimental conditions .

How does LOC_Os07g47590 interact with hormone signaling pathways during stress responses?

The interaction between LOC_Os07g47590 and hormone signaling pathways represents a complex regulatory network in stress responses. Several phytohormone signaling pathways depend on the ubiquitin-proteasome system, with E3 ubiquitin ligases often serving as key components that perceive signals and initiate signal transduction . While direct evidence for LOC_Os07g47590 specifically is limited, research on related E3 ubiquitin ligases in rice shows that some are induced by treatment with jasmonic acid (JA), ethylene (ACC), and salicylic acid (SA), suggesting involvement in hormone-mediated stress responses . The significant genotype × environment interaction observed for LOC_Os07g47590 (p-Inter = 0.000) suggests that its function may be influenced by or influence hormone signaling during stress adaptation . Experimental approaches to study these interactions should include expression analysis under various hormone treatments, protein-protein interaction studies with known components of hormone signaling pathways, and phenotypic characterization of mutant lines under hormone treatment. Hormone measurements in wild-type versus mutant plants under stress conditions can reveal whether LOC_Os07g47590 affects hormone biosynthesis, signaling, or downstream responses during environmental challenges.

What expression analysis techniques provide the most reliable data for studying LOC_Os07g47590 regulation?

Reliable expression analysis of LOC_Os07g47590 requires careful experimental design and appropriate technical approaches. Quantitative real-time PCR (qRT-PCR) with appropriate reference genes is essential for accurate quantification, as demonstrated in previous studies where LOC_Os07g47590 was among genes validated using this technique after initial microarray screening . RNA-seq provides comprehensive transcriptome-wide context for expression changes, allowing identification of co-regulated genes and potential regulatory networks. For both approaches, biological replication is critical—previous research used three replicate plants per treatment, though larger sample sizes (e.g., 12 plants used in array experiments) provide greater statistical power for detecting subtle expression changes . Time-course experiments capturing expression dynamics over the stress period rather than endpoint measurements provide more comprehensive understanding of regulation patterns. Cell-type specific expression analysis using techniques like INTACT (isolation of nuclei tagged in specific cell types) or laser-capture microdissection can reveal tissue-specific regulation that might be masked in whole-organ studies. Normalization strategies should account for potential global transcriptome changes under stress conditions, and statistical analysis must properly assess interaction effects, as these proved significant for LOC_Os07g47590 (p-Inter = 0.000) .

What protein purification and activity assays are appropriate for recombinant E3 ubiquitin ligase studies?

Successful biochemical characterization of recombinant E3 ubiquitin ligase BAH1-like 2 requires optimization of protein expression, purification, and activity assays. For prokaryotic expression, the E3 ligase coding sequence should be codon-optimized for the host system (typically E. coli BL21(DE3)) and expressed with an affinity tag (His6 or GST) to facilitate purification. Eukaryotic expression systems (insect cells or yeast) may be preferable if proper folding or post-translational modifications are required for activity. Purification should employ affinity chromatography followed by size exclusion chromatography to ensure protein homogeneity. In vitro ubiquitination assays require purified E1 activating enzyme, E2 conjugating enzyme, ubiquitin (often fluorescently labeled for detection), ATP, and potential substrate proteins. Activity is measured by detecting ubiquitin transfer to substrates via Western blotting or fluorescence detection. Auto-ubiquitination assays can confirm catalytic activity even when specific substrates are unknown. Enzyme kinetics should be assessed under various conditions (pH, temperature, ionic strength) to determine optimal parameters. Substrate identification can be approached through protein arrays, where purified E3 ligase is used to screen for ubiquitination of candidate proteins. All biochemical assays should include appropriate positive controls (known active E3 ligases) and negative controls (catalytically inactive mutants) to validate results.

How can CRISPR-Cas9 gene editing be optimized for functional studies of Os07g0673200?

CRISPR-Cas9 gene editing of Os07g0673200 requires careful design and optimization for successful functional characterization. Guide RNA (gRNA) selection should target conserved exons, preferably those encoding critical functional domains, with multiple computational tools used to identify guides with high on-target efficiency and minimal off-target effects. For rice transformation, the optimized CRISPR construct typically includes rice-specific promoters (e.g., OsU3 for gRNA expression and maize ubiquitin promoter for Cas9) and is delivered via Agrobacterium-mediated transformation of embryogenic callus. Genotyping strategies should combine PCR amplification of the target region with methods to detect indels, including T7 endonuclease I assay, Sanger sequencing, or next-generation sequencing for large-scale screening. Homozygous knockout lines should be advanced to T2 or T3 generation to ensure stable inheritance of the mutation before phenotypic analysis. Complementation assays, where the wild-type gene is reintroduced into knockout lines, are essential to confirm that observed phenotypes result from the targeted mutation rather than off-target effects. For more sophisticated functional studies, precision editing to introduce specific mutations (using homology-directed repair) or transcriptional modulators (CRISPRa/CRISPRi) can provide insights into domain functions or expression-level effects without complete gene knockout.

What phenotyping approaches effectively capture the function of LOC_Os07g47590 in stress responses?

Comprehensive phenotyping of LOC_Os07g47590 mutants requires multi-level analysis spanning molecular, physiological, and whole-plant responses to stress. Given the significant genotype × environment interaction observed for this gene (p-Inter = 0.000), drought stress experiments should be carefully designed with precise control of water limitation, monitoring soil moisture content and vapor pressure deficit to ensure reproducibility . Physiological measurements should include photosynthetic parameters (gas exchange, chlorophyll fluorescence), water relations (relative water content, osmotic potential, stomatal conductance), and oxidative stress markers (hydrogen peroxide, malondialdehyde content, antioxidant enzyme activities). Growth parameters (biomass accumulation, root architecture, leaf area) should be quantified under both control and stress conditions. Molecular phenotyping should include transcriptomic and proteomic analysis to identify downstream pathways affected by the mutation, particularly focusing on known stress-responsive genes and proteins. Metabolomic analysis can reveal changes in osmolytes, hormones, and signaling molecules that contribute to stress responses. High-throughput phenotyping platforms using RGB and hyperspectral imaging can detect subtle phenotypic differences and temporal changes in plant responses. All phenotypic analyses should compare multiple independent mutant lines with appropriate wild-type controls grown simultaneously under identical conditions to distinguish gene-specific effects from background variation.

How can multi-omics approaches enhance understanding of LOC_Os07g47590 function?

Multi-omics integration provides a comprehensive framework for elucidating LOC_Os07g47590 function beyond individual molecular techniques. Integration of transcriptomics, proteomics, metabolomics, and phenomics data using bioinformatic approaches can reveal functional networks and causal relationships that single-omics approaches might miss. Transcriptomic data from microarray or RNA-seq experiments can identify co-expressed genes and potential regulatory networks, while proteomics can confirm which expression changes translate to altered protein levels and identify post-translational modifications. Metabolomic profiling can detect biochemical consequences of altered LOC_Os07g47590 activity, particularly focusing on stress-related metabolites and signaling molecules. Network analysis algorithms can integrate these datasets to construct regulatory networks, identifying potential feedback loops and regulatory hubs. Machine learning approaches applied to integrated datasets can predict gene function and phenotypic outcomes of genetic perturbations. Time-series multi-omics analysis during stress progression can identify early molecular events versus downstream consequences of altered E3 ligase activity. Comparative multi-omics across different rice varieties with varying stress tolerance can contextualize LOC_Os07g47590 function within natural variation for stress adaptation, particularly valuable given the significant genotype × environment interaction observed for this gene (p-Inter = 0.000) .

What are the practical applications of understanding LOC_Os07g47590 function for rice improvement?

Understanding LOC_Os07g47590 function has significant implications for rice improvement strategies targeting stress resilience. The significant genotype × environment interaction observed for this gene (p-Inter = 0.000) suggests its potential involvement in differential stress responses between rice varieties, making it a candidate for marker-assisted selection in breeding programs focused on drought tolerance . If functional characterization confirms its role in stress adaptation, natural variation in this gene could be explored across diverse rice germplasm to identify superior alleles for introgression into elite varieties. Genome editing approaches could be employed to introduce beneficial modifications into existing varieties, potentially accelerating breeding compared to conventional approaches. Transgenic approaches might include overexpression or precision regulation of LOC_Os07g47590 in stress-susceptible varieties to enhance their resilience. Haplotype analysis across rice populations adapted to different environments could reveal evolutionary signatures associated with adaptive variation in this gene. Functional markers developed from this gene could facilitate marker-assisted selection in breeding programs, particularly if specific alleles are associated with enhanced performance under water-limiting conditions. Knowledge transfer to other cereal crops through identification and modification of orthologous genes could extend the impact beyond rice improvement.