Recombinant Pinus koraiensis DNA-directed RNA polymerase subunit alpha (rpoA)

What is the structure and function of DNA-directed RNA polymerase subunit alpha in Pinus koraiensis?

The DNA-directed RNA polymerase subunit alpha (rpoA) in Pinus koraiensis is a critical component of the transcriptional machinery responsible for DNA-dependent RNA synthesis. The rpoA subunit plays a dual role:

• Assembly function: It serves as a platform for RNA polymerase assembly, with its dimerization being the initial step in the sequential assembly of subunits to form the functional holoenzyme .

• DNA binding role: The carboxy-terminal domain (αCTD) specifically recognizes and binds to promoter regions, particularly upstream (UP) elements, through characteristic minor groove interactions .

The P. koraiensis rpoA likely contains a nonstandard helix followed by four alpha-helices, with DNA binding regions corresponding to the first alpha-helix and the loop between the third and fourth alpha-helices, similar to what has been observed in other species . While specific structural data for P. koraiensis rpoA is limited, comparative genomics indicates that this conifer contains one of the most comprehensive sets of coding sequences in chloroplast genomes (273 CDS), suggesting evolutionary conservation of essential transcriptional components .

What are the optimal expression systems for producing recombinant P. koraiensis rpoA?

The selection of an appropriate expression system is critical for successful production of functional recombinant P. koraiensis rpoA. Based on research with similar proteins, the following methodological approach is recommended:

Expression System Comparison for P. koraiensis rpoA:

Methodology for E. coli expression (preferred system):

• Clone the P. koraiensis rpoA coding sequence into a vector containing an N-terminal His-tag for purification

• Transform into BL21(DE3) cells and select transformants on appropriate antibiotics

• Grow cultures to mid-log phase (OD600 of 0.6-0.8) at 37°C

• Reduce temperature to 16-18°C and induce with 0.1-0.5 mM IPTG

• Continue expression for 16-24 hours at the reduced temperature

• Harvest cells and use nickel affinity chromatography for initial purification

• Apply additional purification steps (ion-exchange and size exclusion chromatography) to obtain homogeneous protein

When working with P. koraiensis rpoA, codon optimization based on chloroplast gene usage patterns may improve expression yields, as this gene is originally part of the chloroplast genome .

What purification strategies yield the highest activity for recombinant P. koraiensis rpoA?

Purification of recombinant P. koraiensis rpoA requires a strategic approach to maintain structural integrity and functional activity. The following methodological workflow is recommended:

• Cell Lysis and Initial Clarification:

  • Use gentle lysis methods (e.g., lysozyme treatment followed by sonication in short bursts)

  • Lysis buffer: 50 mM Tris-HCl (pH 8.0), 300 mM NaCl, 10% glycerol, 10 mM imidazole, 5 mM β-mercaptoethanol, and protease inhibitors

  • Clarify by centrifugation at 20,000g for 30 minutes at 4°C

• Sequential Chromatography Approach:

  Purification Step	Buffer Composition	Expected Results	Quality Control
  Ni-NTA affinity	Binding: 50 mM Tris-HCl (pH 8.0), 300 mM NaCl, 10 mM imidazole Elution: Same with 250 mM imidazole	>80% purity	SDS-PAGE; Western blot with anti-His antibodies
  Heparin affinity	20 mM HEPES (pH 7.5), 50-1000 mM NaCl gradient	DNA-binding activity enrichment	EMSA with consensus UP element
  Size exclusion	20 mM HEPES (pH 7.5), 150 mM NaCl, 1 mM DTT	>95% homogeneity	Analytical SEC; DLS for oligomeric state

• Activity Preservation:

  • Add glycerol (10-20%) to final preparations

  • Store in small aliquots at -80°C to avoid freeze-thaw cycles

  • Validate functional activity using transcription assays with template DNA containing UP elements

Research findings with other rpoA proteins indicate that maintaining reducing conditions throughout purification is essential, as the alpha subunit contains cysteine residues that may form inappropriate disulfide bonds affecting functional assembly with other polymerase subunits .

How can I design effective promoter binding assays for P. koraiensis rpoA?

Based on research with alpha subunits from other organisms, the following methodological approach can be adapted for P. koraiensis rpoA promoter binding studies:

Electrophoretic Mobility Shift Assay (EMSA) Protocol:

• DNA Probe Design:

  • Synthesize 30-50 bp DNA fragments containing putative UP elements

  • Incorporate a short A-tract (6 bp) which is known to facilitate alpha CTD binding

  • Include controls with mutations in the minor groove width regions

• Binding Reaction Setup:

  Component	Concentration	Volume (μL)	Notes
  Purified rpoA	0.1-1 μM	1-5	Test multiple concentrations
  Labeled DNA probe	10 nM	1	Fluorescent or radioisotope labeling
  Binding buffer	10X	2	200 mM Tris (pH 8.0), 600 mM KCl, 100 mM MgCl2
  Poly(dI-dC)	1 μg/μL	1	Non-specific competitor
  DTT	100 mM	1	Reducing agent
  Glycerol	50%	2	For loading
  H2O	-	to 20	-

• Analysis Methods:

  • Native PAGE (6%) at 4°C

  • Quantitative analysis of band shifts using densitometry

  • Calculate apparent Kd values from titration experiments

Surface Plasmon Resonance (SPR) Alternative:
For more precise kinetic measurements, SPR can be employed using biotinylated DNA probes immobilized on streptavidin-coated chips, with recombinant rpoA injected at increasing concentrations (10 nM to 1 μM).

When analyzing binding data, incorporate DNA shape parameters in your analysis, as research has shown that the minor groove width and electrostatic potential significantly influence alpha CTD binding . Pay particular attention to the role of arginine residues (especially those corresponding to R265 in E. coli) that may insert into the DNA minor groove.

What are the optimal conditions for in vitro transcription assays using recombinant P. koraiensis rpoA?

To establish functional in vitro transcription assays with recombinant P. koraiensis rpoA, the following methodological approach is recommended:

In Vitro Transcription System Assembly:

• Core Components Required:

  • Purified recombinant P. koraiensis rpoA (0.5-2 μM)

  • Additional RNA polymerase subunits (either from P. koraiensis or compatible species)

  • Template DNA with appropriate promoter elements

  • Ribonucleotide triphosphates (ATP, GTP, CTP, UTP)

• Reaction Conditions Optimization:

  Parameter	Range to Test	Optimization Strategy
  Buffer pH	7.0-8.5	Test at 0.5 pH unit intervals
  Mg2+ concentration	5-15 mM	Critical for catalytic activity
  Monovalent salt (K+)	40-100 mM	Affects template binding
  Temperature	25-37°C	May need species-specific optimization
  Reaction time	15-60 min	Monitor time course for linearity

• Transcription Activity Assessment:

  • Incorporate radioactive [α-32P]UTP or fluorescently labeled UTP for product detection

  • Analyze transcripts by denaturing PAGE (6-8% polyacrylamide/7M urea)

  • Quantify transcription products by phosphorimager analysis

Control Experiments:

• Omit individual components to verify their necessity

• Use known inhibitors of RNA polymerase (e.g., rifampicin) to confirm specificity

• Compare activities with and without UP elements in template DNA

Research findings with bacterial RNA polymerases indicate that the alpha subunit primarily contributes to initiation complex formation rather than elongation . Therefore, when designing transcription templates for P. koraiensis rpoA, include extended upstream regions containing potential UP elements to assess the contribution of rpoA to promoter recognition and transcription initiation.

How can structure-function analysis be used to identify critical domains in P. koraiensis rpoA?

Structure-function analysis of P. koraiensis rpoA requires a systematic approach combining computational modeling, site-directed mutagenesis, and functional assays:

Methodological Approach:

• Computational Structural Analysis:

  • Generate homology models based on characterized rpoA structures (e.g., E. coli)

  • Identify conserved residues across species, particularly in the C-terminal domain

  • Predict DNA-binding regions based on electrostatic surface mapping

  • Pay particular attention to regions corresponding to the first alpha-helix and the loop between the third and fourth alpha-helices, which are known to be important for DNA binding in other species

• Site-Directed Mutagenesis Strategy:

  Domain	Target Residues	Mutagenesis Approach	Expected Effect
  N-terminal	Dimerization interface	Conservative substitutions	Assembly defects
  C-terminal (αCTD)	Basic residues in DNA-binding regions	Alanine scanning	Reduced UP element binding
  αCTD	Residues corresponding to R265 in E. coli	R→A and R→K substitutions	Altered minor groove recognition
  Inter-domain linker	Flexible region between domains	Length variations	Positioning effects

• Functional Assessment of Mutants:

  • DNA binding assays (EMSA, fluorescence anisotropy)

  • Holoenzyme assembly assays (gel filtration, analytical ultracentrifugation)

  • In vitro transcription with various promoters

  • Protein-protein interaction assays with other transcription factors

Recent research on rpoA has shown that the minor groove width and electrostatic potential are critical for recognition by the C-terminal domain . For P. koraiensis rpoA, special attention should be paid to arginine residues that might insert into the minor groove of A-tract DNA, as these interactions could be essential for species-specific promoter recognition.

What approaches can be used to study the interaction of P. koraiensis rpoA with other transcription factors?

Investigating interactions between P. koraiensis rpoA and other transcription factors requires a multi-technique approach:

Methodological Framework:

• Identification of Potential Interaction Partners:

  • Bioinformatic analysis of P. koraiensis genome for conserved transcription factors

  • Co-expression analysis from transcriptomic data

  • Leverage knowledge from other conifer species and model organisms

• Protein-Protein Interaction Techniques:

  Technique	Methodology	Strengths	Limitations
  Pull-down assays	Immobilize tagged rpoA and incubate with nuclear extracts	Identifies native interactions	May miss transient interactions
  Yeast two-hybrid	Screen for interactions using rpoA domains as bait	High-throughput screening	Potential false positives
  Biolayer interferometry	Measure real-time binding kinetics	Provides kinetic parameters	Requires purified proteins
  Hydrogen-deuterium exchange MS	Map interaction interfaces	Identifies specific binding regions	Complex data analysis

• Validation in Plant Systems:

  • Bimolecular fluorescence complementation (BiFC) in plant protoplasts

  • Co-immunoprecipitation from P. koraiensis tissue if antibodies are available

  • In vitro reconstitution of transcription complexes with purified components

Research in other organisms suggests that rpoA CTD interacts with specific activator proteins, with these interactions often occurring at regions distinct from but close to the DNA-binding surfaces . When studying P. koraiensis rpoA, consider examining interactions with conifer-specific transcription factors that might have co-evolved with RNA polymerase to regulate genes involved in adaptation to specific environmental conditions, such as cold tolerance genes that are particularly relevant for this species native to Northeast Asia .

How can recombinant P. koraiensis rpoA be used in chromosome conformation capture studies?

Chromosome conformation capture (3C) and its derivatives are powerful techniques that can be adapted to study chromatin organization using recombinant P. koraiensis rpoA as a probe:

Methodological Integration of rpoA in 3C Technologies:

• ChIP-3C Approach:

  • Cross-link P. koraiensis chromatin from relevant tissues (e.g., needles, embryogenic cells)

  • Perform chromatin immunoprecipitation using antibodies against recombinant rpoA

  • Digest, ligate, and analyze interaction frequencies

  • Map genome-wide binding sites and long-range interactions

• Recombinant rpoA as a Probe for Promoter Interactions:

  Experimental Approach	Protocol Elements	Expected Outcomes	Analysis Methods
  ChIP-seq with rpoA	Standard ChIP protocol with anti-rpoA antibodies	Genome-wide binding map	Peak calling; motif analysis
  HiChIP with rpoA	Combine Hi-C with rpoA ChIP	Long-range interaction map	Identify regulatory interactions
  CUT&RUN with rpoA	In situ protein-DNA complex cleavage	Higher resolution binding data	Compare with ChIP-seq results

• Biological Applications:

  • Identify higher-order chromosome organization in conifer genomes

  • Map enhancer-promoter interactions in developmentally regulated genes

  • Study chromatin reorganization during responses to environmental stresses

Research shows that RNA polymerase alpha subunits contribute to the formation of transcription hubs and DNA looping through their interactions with UP elements and transcription factors . For P. koraiensis, these studies could reveal how chromatin organization contributes to conifer-specific gene regulation, particularly in processes related to stress responses, development, or specialized metabolite production that characterize this species .

How should sequencing data be analyzed to identify P. koraiensis rpoA binding sites genome-wide?

Analysis of next-generation sequencing data to identify P. koraiensis rpoA binding sites requires a specialized bioinformatics pipeline:

Comprehensive Analytical Workflow:

• Quality Control and Preprocessing:

  • Trim adapter sequences and low-quality bases (Q<20)

  • Filter out reads <20 bp after trimming

  • Align to the P. koraiensis reference genome using Bowtie2 with parameters optimized for transcription factor binding (-k 2 --sensitive)

• Peak Calling and Annotation:

  Analysis Step	Software Options	Parameters	Output
  Peak calling	MACS2	--nomodel --extsize 200	BED files of binding regions
  Peak annotation	HOMER annotatePeaks.pl	default	Genomic context of peaks
  Motif discovery	MEME-ChIP	-nmotifs 10 -minw 6 -maxw 30	Enriched sequence motifs
  DNA shape analysis	DNAshapeR	default	Minor groove width profiles

• Integrative Analysis:

  • Correlate binding sites with gene expression data (if available)

  • Analyze minor groove width characteristics in binding regions

  • Compare binding patterns to known promoter structures

  • Identify enrichment near genes with specific functions

Research with bacterial RNA polymerase alpha subunits shows preferential binding to sequences with narrow minor grooves and enhanced negative electrostatic potential . For P. koraiensis rpoA, focus the analysis on A-tract containing regions and their structural properties, as these are likely to be preferred binding sites based on the mechanistic conservation of alpha subunit interactions with DNA.

What statistical approaches are most appropriate for analyzing P. koraiensis rpoA binding affinity data?

Statistical analysis of binding data for P. koraiensis rpoA requires appropriate models that account for the complexity of protein-DNA interactions:

Statistical Framework for Binding Data:

• Equilibrium Binding Analysis:

  • Apply nonlinear regression to fit binding isotherms

  • Use models that account for potential cooperativity (Hill equation)

  • Calculate apparent Kd values with 95% confidence intervals

  • Compare binding to different DNA sequences using extra sum-of-squares F test

• Comparative Statistical Approaches:

  Data Type	Statistical Method	Advantages	Implementation
  EMSA band density	Nonlinear regression	Visual validation	GraphPad Prism or R (drc package)
  SPR sensorgrams	Global kinetic fitting	Provides kon and koff	BIAevaluation or R (SPR package)
  Competitive binding	Cheng-Prusoff equation	Accounts for probe affinity	Custom scripts in R
  Multiple sequence comparison	ANOVA with post-hoc tests	Compares multiple sequences	R (stats package)

• Advanced Analysis for Complex Binding Models:

  • Bayesian approaches for multi-site binding using MCMC methods

  • Information theory to quantify sequence specificity

  • Machine learning to predict binding from sequence/shape features

Research with other RNA polymerase alpha subunits suggests that binding is influenced by both base sequence and DNA shape parameters . For P. koraiensis rpoA, statistical models should incorporate both direct base readout and shape readout components. Consider using biophysical models that account for the contribution of minor groove width and electrostatic potential alongside sequence-specific interactions.

How can I integrate transcriptomic and functional genomic data to understand P. koraiensis rpoA regulatory networks?

Integrating multiple omics datasets to decipher P. koraiensis rpoA regulatory networks requires sophisticated computational approaches:

Multi-omics Integration Methodology:

• Data Collection and Standardization:

  • ChIP-seq of rpoA binding sites

  • RNA-seq under various conditions

  • DNA accessibility data (ATAC-seq or DNase-seq)

  • Potential protein-protein interaction data

• Integration Strategies and Tools:

  Integration Approach	Methodology	Suitable Tools	Expected Outcomes
  Network inference	Correlation-based	WGCNA, ARACNe	Gene regulatory networks
  Enrichment analysis	Gene set testing	GSEA, clusterProfiler	Functional pathways regulated by rpoA
  Multi-omics factor analysis	Dimensionality reduction	MOFA, iCluster	Identification of major sources of variation
  Bayesian network modeling	Probabilistic relationships	BNlearn, bnstruct	Causal inference between variables

• Biological Validation and Interpretation:

  • Identify hub genes in the network

  • Determine condition-specific regulatory modules

  • Validate key interactions experimentally

  • Compare with known regulatory networks from related species

Research in conifer species suggests complex transcriptional networks controlling development and stress responses . For P. koraiensis rpoA, focus on identifying genes involved in adaptation to the species' native cold environments and stress responses, as these may represent specialized regulatory networks that have evolved in this conifer. The analysis should account for the genomic and evolutionary context of P. koraiensis, including its divergence from related species approximately 1.37 million years ago and its subsequent adaptation to specific environmental niches .

What are common challenges in expressing recombinant P. koraiensis rpoA and how can they be addressed?

Expression of recombinant P. koraiensis rpoA presents several challenges that researchers should anticipate and address methodically:

Common Challenges and Solutions:

• Protein Solubility Issues:

  Challenge	Potential Causes	Solution Strategies	Implementation Notes
  Inclusion body formation	Rapid expression; improper folding	Lower induction temperature (16°C); co-express chaperones (GroEL/ES)	Reduce IPTG to 0.1 mM; extend expression time to 24h
  Aggregation during purification	Hydrophobic patches exposed; improper buffer	Include stabilizing agents (glycerol, arginine); optimize ionic strength	Add 10% glycerol and 50-100 mM arginine to buffers
  Low expression yield	Codon bias; protein toxicity	Codon optimization; use T7-lysY strains to reduce leaky expression	Consider Rosetta strains for rare codons

• Protein Functionality Issues:

  • Validate DNA-binding activity immediately after purification

  • Test different buffer compositions for storage stability

  • Consider expressing separate domains if full-length protein is problematic

  • Use circular dichroism to confirm proper secondary structure

• Technical Troubleshooting:

  • For co-purification of contaminants, add DNase I treatment during lysis

  • For proteolytic degradation, include additional protease inhibitors

  • For loss during concentration, use spin filters with PEG coating

  • For precipitation during storage, add reducing agents and avoid freeze-thaw cycles

Research with other transcription factors suggests that maintaining reducing conditions is critical for preserving the activity of cysteine-containing proteins . For P. koraiensis rpoA, include DTT or TCEP in purification and storage buffers to prevent disulfide bond formation that could disrupt native structure.

How can I address inconsistent results in chromatin immunoprecipitation experiments with P. koraiensis rpoA?

Chromatin immunoprecipitation (ChIP) with P. koraiensis rpoA can present various technical challenges that require systematic troubleshooting:

ChIP Troubleshooting Decision Tree:

• Antibody-Related Issues:

  • Challenge: Poor antibody specificity or affinity

  • Diagnostic: Western blot shows multiple bands or weak signal

  • Solutions:

    • Generate new antibodies against conserved epitopes

    • Use epitope-tagged recombinant rpoA for ChIP

    • Validate antibodies with recombinant protein controls

• Chromatin Preparation Challenges:

  Issue	Diagnostic Signs	Remediation Strategies	Quality Control
  Insufficient crosslinking	Low DNA recovery; poor enrichment	Optimize formaldehyde concentration (1-2%) and time (10-20 min)	Check DNA smear after sonication
  Over-crosslinking	Difficult to shear; high background	Reduce crosslinking time; increase sonication	Verify fragment size (200-500 bp)
  Inappropriate sonication	Fragments too large or too small	Adjust sonication cycles and power	Bioanalyzer analysis of fragment distribution

• IP Procedure Optimization:

  • Increase antibody amount or incubation time

  • Test different IP buffers with varying salt and detergent concentrations

  • Include blocking agents (BSA, salmon sperm DNA) to reduce background

  • Perform more stringent washes for high-specificity results

• Bioinformatic Considerations:

  • Use appropriate controls (input, IgG) for normalization

  • Apply consistent peak calling parameters across experiments

  • Consider biological replicates for statistical confidence

  • Use spike-in controls for quantitative comparisons

Research with plant ChIP experiments indicates that tissue-specific factors can significantly affect results . For P. koraiensis, consider that different tissues (needles, embryogenic cells) may require optimized protocols. The high resin content in conifer tissues may interfere with chromatin preparation, requiring additional purification steps before immunoprecipitation.

What strategies help resolve conflicts between in vitro binding data and in vivo ChIP-seq results for P. koraiensis rpoA?

Resolving discrepancies between in vitro and in vivo data for P. koraiensis rpoA binding requires a systematic investigation of potential biological and technical factors:

Methodological Reconciliation Framework:

• Comparative Analysis of Datasets:

  • Map in vitro binding motifs onto ChIP-seq peaks

  • Calculate enrichment of in vitro motifs in ChIP data

  • Identify regions with concordant and discordant results

  • Analyze DNA shape features in both datasets

• Investigating Biological Factors:

  Potential Explanation	Investigative Approach	Validation Method	Expected Outcome
  Chromatin accessibility	Integrate ATAC-seq or DNase-seq data	Correlate accessibility with binding	In vitro motifs may be inaccessible in vivo
  Cooperative binding partners	Perform ChIP-seq for potential cofactors	Identify co-occupied regions	Partners may alter binding specificity
  DNA modifications	Analyze DNA methylation patterns	Correlate methylation with binding differences	Modifications may inhibit binding
  Indirect binding	Perform protein-protein interaction studies	Identify bridge proteins	Some in vivo sites may be through protein-protein interactions

• Technical Considerations:

  • Compare binding conditions (salt, pH, temperature) between in vitro and in vivo

  • Test binding to chromatinized templates vs. naked DNA

  • Examine potential biases in both experimental approaches

  • Consider the effect of formaldehyde crosslinking on binding site detection

Research with other transcription factors suggests that in vivo binding is influenced by multiple factors beyond intrinsic DNA sequence preference . For P. koraiensis rpoA, consider the native chromatin environment and potential conifer-specific factors that might modulate binding. The evolutionary adaptation of P. koraiensis to specific environmental conditions may have resulted in specialized regulatory mechanisms that are not fully recapitulated in simplified in vitro systems .

How might CRISPR/Cas9 genome editing be applied to study P. koraiensis rpoA function in vivo?

CRISPR/Cas9 technology offers promising approaches for studying P. koraiensis rpoA function, though applying these techniques to conifers presents unique challenges:

Methodological Framework for CRISPR in P. koraiensis:

• Technical Adaptation for Conifer Systems:

  • Optimize protoplast isolation from embryogenic tissue of P. koraiensis

  • Develop efficient DNA delivery methods (PEG-mediated transformation or biolistics)

  • Design conifer-optimized Cas9 expression cassettes with appropriate promoters

  • Establish regeneration protocols for edited cells

• Experimental Design Strategies:

  Editing Approach	Target Design	Expected Outcome	Analytical Methods
  Knockout of rpoA	Multiple gRNAs targeting conserved regions	Lethal if chloroplast-encoded; altered transcription if nuclear	PCR genotyping; phenotypic analysis
  Domain-specific mutations	gRNAs targeting DNA-binding domains	Altered promoter recognition	ChIP-seq comparison; transcriptome analysis
  Promoter editing	Target regulatory elements of nuclear genes interacting with rpoA	Modified expression patterns	qRT-PCR; reporter assays
  Homology-directed repair	Template with epitope tag	Tagged protein for in vivo studies	Immunoprecipitation; localization

• Applications for Functional Analysis:

  • Study the role of specific residues in promoter recognition

  • Investigate the function of rpoA in stress responses

  • Examine the impact of rpoA variants on gene expression networks

  • Create reporter systems to monitor transcriptional activity in vivo

Considering that P. koraiensis embryogenic cells have been successfully cultured and manipulated in laboratory settings , these cells provide a promising starting material for CRISPR/Cas9 experiments. The glutathione-responsive proliferation of these cells suggests that redox-sensitive pathways are important in this species, which could be relevant for optimization of transformation and regeneration protocols.

What role might P. koraiensis rpoA play in climate adaptation mechanisms?

Given the native distribution of P. koraiensis in cold regions of Northeast Asia, its transcriptional machinery likely plays a vital role in climate adaptation:

Research Framework for Climate Adaptation Studies:

• Comparative Genomic Approaches:

  • Compare rpoA sequences and activity across pine species from different climates

  • Identify signatures of selection in rpoA sequences from different populations

  • Correlate genetic variants with environmental parameters

• Experimental Climate Response Analysis:

  Climate Variable	Experimental Approach	Parameters to Measure	Data Integration
  Cold stress	Expose trees to controlled temperature regimes	ChIP-seq of rpoA binding; transcriptome profiling	Identify cold-responsive rpoA binding sites
  Drought stress	Water limitation experiments	Compare rpoA occupancy before/after stress	Map drought response regulons
  Multiple stress factors	Factorial design with temperature and water	Multi-omics profiling	Identify shared/unique response mechanisms

• Ecological and Evolutionary Context:

  • Analyze rpoA function in populations across latitudinal/altitudinal gradients

  • Study the co-evolution of rpoA with climate-adaptive genes

  • Investigate potential epigenetic regulation of rpoA activity under changing conditions