JMJ15 Antibody

Basic Research Questions

What experimental applications require JMJ15-specific antibodies, and how are they validated?

JMJ15 antibodies are critical for chromatin immunoprecipitation (ChIP), Western blot (WB), and immunofluorescence to study its role as a histone H3K4me3 demethylase. Validation involves:

• Specificity testing: Knockout mutants (e.g., jmj15-3, jmj15-4) should show no signal in WB, while gain-of-function lines (e.g., 35S:JMJ15-HA) exhibit strong signals .

• Functional assays: Co-localization with H3K4me3 marks in ChIP-seq (e.g., hypermethylation at WRKY46/70 loci in jmj15 mutants under salt stress) .

• Cross-reactivity checks: Ensure no binding to homologous proteins (e.g., JMJ14, JMJ18) via peptide competition assays .

How does JMJ15 antibody facilitate the study of salt stress responses in Arabidopsis?

JMJ15 regulates stress-responsive genes by modulating H3K4me3 levels. Key methodologies include:

• Transcriptomic profiling: RNA-seq of jmj15 mutants under salt stress identifies 1,852 differentially expressed genes (DEGs), including WRKY46/70 .

• ChIP-seq: Compare H3K4me3 peaks in wild-type vs. mutants to map JMJ15 targets (e.g., 7,722 hypermethylated genes in jmj15 under salt stress) .

• Phenotypic assays: Germination rates and root elongation under NaCl treatment (e.g., 50% reduction in jmj15 germination at 150 mM NaCl) .

What controls are essential when using JMJ15 antibody in chromatin studies?

• Negative controls:

  • IgG instead of JMJ15 antibody in ChIP-qPCR .

  • jmj15 knockout mutants for background signal assessment .

• Positive controls:

  • 35S:JMJ15-HA overexpression lines for antibody specificity .

  • Known H3K4me3-rich loci (e.g., FT, SOC1) validated in prior studies .

Advanced Research Questions

How to resolve contradictions between JMJ15 gain-of-function and loss-of-function phenotypes?

Gain-of-function mutants (e.g., jmj15-1, jmj15-2) show salt tolerance, while loss-of-function (jmj15-3, jmj15-4) are hypersensitive . To address discrepancies:

• Context-dependent analysis: Test phenotypes under varying stress durations (e.g., 5h vs. 24h salt exposure) .

• Epistatic analysis: Cross jmj15 with wrky46/70 mutants to dissect genetic hierarchies .

• H3K4me3 dynamics: Time-course ChIP-seq to track demethylation kinetics at target loci .

How can JMJ15 antibody be used to study its interaction with SnRK1-CRF6 signaling?

The SnRK1-JMJ15-CRF6 module integrates energy status and stress responses. Key approaches:

• Co-IP/MS: Immunoprecipitate JMJ15-HA to identify binding partners (e.g., SnRK1a1, CRF6) .

• Phosphorylation assays: Treat plants with SnRK1 inhibitors (e.g., antimycin A) and monitor JMJ15 stability via WB .

• Transcriptomic correlation: Compare DEGs in jmj15, crf6, and SnRK1a1-OE lines under mitochondrial stress .

What methodologies optimize JMJ15 antibody use in low-abundance tissue samples?

• Signal amplification: Tyramide-based amplification for immunofluorescence in floral tissues .

• Chromatin crosslinking: Prolonged formaldehyde fixation (20 min) for ChIP in roots .

• Multiplexing: Combine JMJ15 antibody with H3K4me3-specific probes in sequential ChIP (Re-ChIP) .

Data Analysis & Interpretation

How to reconcile JMJ15’s role as a transcriptional repressor with its stress-induced expression?

JMJ15 is transiently induced early in stress (0.5–1h) to fine-tune H3K4me3 levels, while its targets (e.g., WRKY46/70) activate later (3–6h) . Strategies:

• Time-resolved RNA-seq/ChIP-seq: Profile at 0h, 1h, 3h, 6h post-stress.

• Mutant complementation: Express JMJ15 under inducible promoters (e.g., dexamethasone) to uncouple its timing from targets .

How to address off-target effects in JMJ15 immunoprecipitation studies?

• Peptide competition: Pre-incubate antibody with JMJ15 immunogen (Recombinant AT2G34880 protein) .

• CRISPR-Cas9 epitope tagging: Endogenously tag JMJ15 with HA/FLAG in jmj15 mutants .

• Cross-reference datasets: Overlap ChIP-seq peaks with JMJ15-dependent DEGs (e.g., 58% of downregulated genes have promoter H3K4me3) .

Tables: Key Findings from JMJ15 Studies

Methodological Recommendations

• For ChIP-seq: Use ≥1 g of seedling tissue, fragment chromatin to 200–500 bp, and include spike-in controls (e.g., Arabidopsis histone H3) .

• For stress assays: Standardize seed batches and harvest times to minimize phenotypic variability .

• Data integration: Combine RNA-seq, ChIP-seq, and phosphoproteomics via tools like Weighted Gene Co-expression Network Analysis (WGCNA) .