KDM1A Monoclonal Antibody

What is KDM1A and what are its primary functions in cellular processes?

KDM1A (Lysine-specific histone demethylase 1A), also commonly referred to as LSD1, is a flavin-dependent monoamine oxidase that specifically demethylates mono- and di-methylated lysines on histone 3, particularly lysines 4 and 9 (H3K4 and H3K9) . This epigenetic regulator functions primarily through two distinct mechanisms: as a co-repressor when interacting with COREST or NURD complexes to demethylate H3K4me1/2, or as a co-activator when associated with androgen or estrogen receptors to demethylate H3K9me1/2 . KDM1A plays a critical role in epigenetic "reprogramming" during early developmental stages, and its deletion can severely impair the growth and differentiation of embryonic stem cells . Additionally, KDM1A is essential for maintaining topological boundaries of polycomb repressor complex (PRC2)-repressed domains in mature neurons, highlighting its importance in gene expression regulation across multiple cell types .

How do I validate the specificity of a KDM1A monoclonal antibody?

To validate KDM1A monoclonal antibody specificity, employ a multi-faceted approach:

• Western blot validation: Confirm a single band at the expected molecular weight (approximately 110 kDa for human KDM1A) across relevant cell/tissue types.

• Immunofluorescence cross-validation: Compare staining patterns with validated antibodies from different sources or against different epitopes.

• KDM1A knockout/knockdown controls: Use CRISPR-edited KDM1A-null cells or siRNA-mediated knockdown as negative controls to confirm antibody specificity .

• Peptide competition assay: Pre-incubate the antibody with the immunizing peptide to verify signal elimination.

• Cross-reactivity testing: Test against closely related family members (such as KDM1B) to ensure specificity.

When performing these validations, appropriate tissue controls are crucial - antibodies may show variable specificity in different contexts. For example, the rat KDM1A polyclonal antibody has been validated on mouse tissue and is recommended for immunofluorescence labeling (1:100 dilution), IHC, or western blot of materials from human and rodent tissues .

What are the appropriate applications for KDM1A monoclonal antibodies in epigenetic research?

KDM1A monoclonal antibodies serve multiple critical applications in epigenetic research:

These applications collectively enable researchers to investigate KDM1A's role in transcriptional regulation, chromatin organization, and disease pathogenesis . For optimal results, validation experiments should confirm antibody performance in the specific application and experimental system being used.

How can I design experiments to investigate KDM1A's role in cancer stem cell maintenance?

Designing experiments to investigate KDM1A's role in cancer stem cell (CSC) maintenance requires a multilayered approach:

• Functional assessment of stemness properties:

  • Implement methylcellulose colony formation assays using KDM1A-silenced versus control cancer cells to evaluate stem cell enrichment and clonogenic potential. A two-step plating approach can reveal self-renewal capacity differences, as demonstrated in colorectal cancer stem cells where KDM1A silencing significantly reduced colony numbers in both first and second platings .

  • Perform sphere formation assays in low-attachment conditions to assess anoikis resistance and self-renewal capacity.

  • Quantify the expression of established CSC markers before and after KDM1A modulation.

• Mechanistic investigation:

  • Conduct ChIP-seq experiments to identify direct KDM1A targets in the CSC population.

  • Employ multi-omics approaches (transcriptomic and proteomic) to reveal KDM1A-dependent pathways regulating stemness. Previous studies have shown that KDM1A silencing in colorectal cancer stem cells leads to cytoskeletal and metabolic remodeling toward a differentiated phenotype .

  • Analyze microRNA regulation, particularly focusing on tumor-suppressive miRNAs like miR-506-3p that are upregulated upon KDM1A silencing .

• In vivo validation:

  • Use limiting dilution assays with KDM1A-silenced cells in immunocompromised mice to assess tumor-initiating capacity.

  • Implement xenograft models with inducible KDM1A knockdown/knockout systems to evaluate the requirement for KDM1A in established tumors.

  • Analyze circulating tumor cells for KDM1A expression correlation with metastatic potential.

This comprehensive approach enables robust evaluation of KDM1A's role in maintaining cancer stem cell properties across multiple dimensions of stemness .

What are the optimal conditions for using KDM1A antibodies in ChIP-seq experiments?

Optimizing KDM1A ChIP-seq experiments requires attention to several critical parameters:

• Chromatin preparation:

  • Cross-link cells with 1% formaldehyde for precisely 10 minutes at room temperature to preserve protein-DNA interactions without over-fixation.

  • Sonicate chromatin to fragments of 200-500 bp, monitoring fragment size by gel electrophoresis.

  • Use ChIP-grade protease and phosphatase inhibitors in all buffers to preserve protein integrity.

• Antibody selection and validation:

  • Select monoclonal antibodies directed against KDM1A epitopes that are accessible in the native chromatin context.

  • Perform preliminary ChIP-qPCR validation at known KDM1A binding sites, comparing enrichment against IgG control and input.

  • Consider epitope interference with KDM1A complex formation; N-terminal epitope antibodies may be preferable as the N-terminus contains an intrinsically disordered region essential for gene segregation functions .

• Immunoprecipitation optimization:

  • Titrate antibody amounts (typically 2-5 μg per IP) against chromatin input (15-30 μg) to determine optimal signal-to-noise ratio.

  • Extend incubation time to 16 hours at 4°C with gentle rotation to maximize specific binding.

  • Include stringent wash steps with increasing salt concentrations to reduce non-specific binding.

• Controls and normalization:

  • Always include matched IgG isotype control, input control, and positive control loci.

  • Consider parallel H3K4me1/2 and H3K9me1/2 ChIP-seq to correlate KDM1A binding with substrate modifications.

  • Use spike-in chromatin from a different species for quantitative normalization between samples.

• Bioinformatic analysis considerations:

  • Account for KDM1A's association with both active and repressive chromatin marks when analyzing peak distribution.

  • Integrate with RNA-seq data to determine functional correlation with gene expression.

  • Compare with CoREST, HDAC, or nuclear receptor ChIP-seq data to distinguish co-repressor versus co-activator functions.

These optimizations will significantly improve the quality and interpretability of KDM1A ChIP-seq experiments for investigating its genome-wide distribution and regulatory functions .

How can I distinguish between KDM1A's histone and non-histone demethylation functions using antibody-based approaches?

Distinguishing between KDM1A's histone and non-histone demethylation functions requires sophisticated experimental designs:

• Differential co-immunoprecipitation strategy:

  • Perform sequential immunoprecipitation (IP) experiments using antibodies against KDM1A followed by antibodies against specific complex components (CoREST for histone functions, androgen/estrogen receptors for specific non-histone functions).

  • Analyze the methylation status of proteins in each fraction using pan-methylated lysine antibodies.

  • Conduct mass spectrometry on the differential IPs to identify and quantify methylated substrates.

• Proximity ligation assay (PLA) approach:

  • Use PLA between KDM1A and potential substrates to visualize direct interactions in situ.

  • Compare PLA signals between nuclear (likely histone) and cytoplasmic (likely non-histone) compartments.

  • Quantify changes in PLA signals after treatment with specific KDM1A inhibitors like SP2509, which attenuates binding of KDM1A with co-repressor CoREST .

• Domain-specific antibody strategy:

  • Utilize antibodies recognizing different functional domains of KDM1A.

  • Compare chromatin association patterns of these domain-specific antibodies to infer complex-specific functions.

  • Correlate with changes in specific histone marks (H3K4me1/2, H3K9me1/2) versus non-histone substrate methylation.

• Subcellular fractionation analysis:

  • Separate nuclear, chromatin-bound, nucleoplasmic, and cytoplasmic fractions.

  • Perform western blots with KDM1A antibodies to determine distribution.

  • Correlate with demethylase activity assays specific to each fraction.

• Mutant rescue experiments:

  • In KDM1A-depleted cells, reintroduce domain-specific mutants that selectively affect histone versus non-histone binding.

  • Use antibody-based techniques to assess restoration of specific demethylation functions.

This multi-faceted approach provides mechanistic insights into the substrate specificity and functional compartmentalization of KDM1A's demethylase activity across cellular contexts .

What are the best experimental designs to study KDM1A's role in neuronal function and intellectual disability disorders?

To study KDM1A's role in neuronal function and intellectual disability disorders, implement the following experimental designs:

• Conditional and inducible knockout models:

  • Develop forebrain-restricted, tamoxifen-inducible Kdm1a knockout mice (Kdm1a-ifKOs) to avoid developmental confounds and enable adult neuronal function studies .

  • Time knockout induction to distinguish between developmental versus maintenance roles of KDM1A.

  • Perform behavioral assays assessing learning, memory, and cognitive flexibility to model intellectual disability phenotypes.

• Multi-omic integrative approach:

  • Combine transcriptome (RNA-seq), epigenome (ChIP-seq), and chromatin conformation (Hi-C) analyses from the same neuronal populations.

  • Apply super-resolution microscopy to visualize 3D chromatin organization changes upon KDM1A deletion.

  • Correlate these datasets to identify direct versus indirect effects of KDM1A loss.

• Domain-specific functional analysis:

  • Focus on the N-terminus of KDM1A, which contains an intrinsically disordered region essential for segregating KDM1A-repressed genes from neighboring active chromatin .

  • Create domain-specific mutants to dissect chromatin boundary maintenance versus catalytic demethylase functions.

  • Express these constructs in KDM1A-deficient neurons to identify critical domains for neuronal function.

• Human patient-derived models:

  • Generate induced pluripotent stem cells (iPSCs) from patients with KDM1A mutations linked to Cleft palate, psychomotor retardation, distinctive facial features, and intellectual disabilities (CPRF; OMIM#616728) .

  • Differentiate these iPSCs into cortical neurons and organoids.

  • Apply electrophysiological recordings and calcium imaging to assess functional neuronal deficits.

• Neuronal isoform analysis:

  • Investigate the neuron-specific dominant-negative splicing isoform (neuroLSD1) expression and function .

  • Compare standard KDM1A versus neuroLSD1 distribution using isoform-specific antibodies.

  • Determine if intellectual disability-associated mutations differentially affect these isoforms.

This comprehensive approach addresses KDM1A's complex roles in neuronal development, gene expression, and chromatin organization while providing insights into therapeutic strategies for KDM1A-associated intellectual disability disorders .

What controls should be implemented when using KDM1A antibodies in combination with epigenetic inhibitors?

When combining KDM1A antibodies with epigenetic inhibitors, implement these essential controls:

• Antibody epitope accessibility controls:

  • Verify that the inhibitor does not mask the antibody epitope by comparing detection efficiency in fixed versus native conditions.

  • If using conformation-specific antibodies, confirm whether the inhibitor affects the recognized conformation.

  • Include positive control proteins whose detection should remain unaffected by the inhibitor.

• Inhibitor specificity validation:

  • Include parallel experiments with structurally similar but inactive analogs of the inhibitor.

  • Test multiple KDM1A inhibitors with different mechanisms (e.g., SP2509, which attenuates LSD1-CoREST binding, versus catalytic inhibitors) to distinguish between functional consequences .

  • Monitor known KDM1A substrates (H3K4me1/2, H3K9me1/2) to confirm on-target activity.

• Temporal controls:

  • Implement time-course experiments to distinguish between direct and indirect effects of inhibition.

  • Compare acute versus chronic inhibition outcomes to identify potential compensatory mechanisms.

  • Synchronize cells to account for cell cycle-dependent variations in KDM1A function and localization.

• Combinatorial treatment controls:

  • When combining KDM1A inhibitors with other epigenetic modulators (like HDAC inhibitors), include single-agent treatments to differentiate additive from synergistic effects.

  • Titrate inhibitor concentrations to identify optimal dosing for synergistic effects, as demonstrated with the combination of SP2509 (LSD1 antagonist) and panobinostat (HDAC inhibitor) in AML studies .

• Functional readout controls:

  • Accompany antibody-based detection with functional assays (e.g., clonogenic potential, differentiation markers).

  • Include genetic knockdown/knockout conditions to compare with pharmacological inhibition.

  • Monitor cell viability to ensure observed effects are not due to cytotoxicity.

These comprehensive controls ensure reliable interpretation of results when using KDM1A antibodies in conjunction with epigenetic inhibitors, particularly in therapeutic development contexts .

How can researchers troubleshoot inconsistent results when detecting KDM1A in different tissue samples?

Troubleshooting inconsistent KDM1A detection across tissue samples requires systematic evaluation of biological and technical variables:

• Biological variability considerations:

  • Isoform expression: Different tissues may express distinct KDM1A isoforms, including the neuron-specific neuroLSD1 variant . Use antibodies targeting conserved regions or isoform-specific antibodies as appropriate.

  • Post-translational modifications: Verify if phosphorylation, ubiquitination, or other modifications affect epitope recognition in specific tissues.

  • Complex formation: KDM1A engages in different protein complexes (CoREST, NuRD, androgen/estrogen receptors) that may mask epitopes in a tissue-specific manner .

  • Expression levels: KDM1A expression varies substantially between cell types; evaluate relative expression through qPCR to calibrate detection protocols.

• Sample preparation optimization:

  • Fixation protocol: Compare fresh-frozen versus fixed samples, and test different fixatives (paraformaldehyde, methanol) and durations.

  • Antigen retrieval: Systematically test different antigen retrieval methods (heat-induced, enzymatic, pH variations) for each tissue type.

  • Extraction buffers: For protein extracts, compare RIPA, NP-40, and specialized nuclear extraction buffers to optimize KDM1A solubilization.

  • Protease inhibitors: Include broad-spectrum protease and phosphatase inhibitors to prevent degradation during sample processing.

• Antibody selection and validation strategy:

  • Multiple antibodies approach: Use several antibodies targeting different KDM1A epitopes to confirm results.

  • Titration curves: Perform antibody dilution series for each tissue type to identify optimal concentration.

  • Blocking optimization: Test different blocking reagents (BSA, milk, commercial blockers) to reduce background in specific tissues.

  • Positive controls: Include tissues known to express high levels of KDM1A (brain, testis) as positive controls .

• Technical validation:

  • Orthogonal methods: Confirm protein expression using multiple techniques (Western blot, IHC, IF) and compare with mRNA expression data.

  • Loading controls: Select appropriate loading controls for each tissue type, as traditional housekeeping genes may vary across tissues.

  • Sensitivity enhancement: For low-expressing tissues, implement signal amplification methods (TSA, polymer-based detection systems).

  • Quantification methods: Use digital image analysis with appropriate thresholding to standardize quantification across samples.

By systematically addressing these variables, researchers can establish reliable protocols for consistent KDM1A detection across diverse tissue samples, enabling accurate comparative studies of KDM1A expression and function in normal physiology and disease states .

How can KDM1A monoclonal antibodies be utilized to investigate cancer progression and therapeutic response?

KDM1A monoclonal antibodies offer powerful tools for investigating cancer progression and therapeutic response through multiple applications:

• Biomarker validation in patient samples:

  • Implement tissue microarray (TMA) analysis using KDM1A antibodies to correlate expression levels with patient outcomes.

  • Perform multiplexed immunofluorescence to co-localize KDM1A with other cancer markers.

  • Quantify nuclear versus cytoplasmic KDM1A localization in different cancer stages.

  • Develop standardized scoring systems for KDM1A expression in specific cancer types, as studies have shown KDM1A overexpression is associated with poor prognosis in various cancers, including colorectal cancer .

• Therapy response monitoring:

  • Use KDM1A antibodies to track target engagement of LSD1 inhibitors via immunofluorescence or immunohistochemistry.

  • Establish chromatin immunoprecipitation protocols to monitor changes in KDM1A genomic occupancy following treatment.

  • Correlate changes in KDM1A binding with alterations in H3K4me1/2 and H3K9me1/2 levels as functional readouts of inhibitor efficacy.

  • Apply these techniques in preclinical models and patient-derived xenografts to predict clinical responses.

• Resistance mechanism investigation:

  • Compare KDM1A complex formation between treatment-naïve and resistant tumors using co-immunoprecipitation with KDM1A antibodies.

  • Analyze post-translational modifications of KDM1A in resistant populations.

  • Track changes in KDM1A subcellular localization during acquired resistance development.

  • Evaluate compensatory epigenetic modifications in KDM1A target genes.

• Combination therapy development:

  • Assess synergistic target engagement when combining KDM1A inhibitors with other epigenetic therapies, such as HDAC inhibitors.

  • Monitor differentiation markers in response to treatment combinations.

  • Implement KDM1A antibody-based assays in high-throughput screening of combination therapies.

  • For example, co-treatment with LSD1 antagonist SP2509 and pan-HDAC inhibitor panobinostat was synergistically lethal against cultured and primary AML blasts, significantly improving survival in mouse models .

• Metastasis and invasion studies:

  • Track KDM1A expression in circulating tumor cells and metastatic lesions.

  • Correlate KDM1A levels with invasion markers using multiplexed immunofluorescence.

  • Analyze epithelial-mesenchymal transition markers in relation to KDM1A expression.

  • Evaluate KDM1A's role in anoikis resistance and cell migration potential, as KDM1A silencing has been shown to impair these processes in colorectal cancer cells .

These applications collectively enable comprehensive investigation of KDM1A's role in cancer progression and therapeutic response, potentially leading to improved patient stratification and combination treatment strategies .

What are the optimal methods for detecting alterations in KDM1A activity rather than just expression levels?

Detecting functional alterations in KDM1A activity requires methods that go beyond simple expression analysis:

• Substrate-specific methylation monitoring:

  • Implement quantitative western blotting for H3K4me1/2 and H3K9me1/2 levels as direct readouts of KDM1A activity.

  • Use chromatin immunoprecipitation followed by qPCR (ChIP-qPCR) at known KDM1A target genes to measure local changes in histone methylation status.

  • Develop activity-based probes that selectively detect active versus inactive KDM1A conformations.

  • Compare histone methylation patterns with KDM1A occupancy to calculate a "demethylation efficiency index" at specific genomic loci.

• Enzyme activity assays:

  • Perform immunoprecipitation of KDM1A followed by in vitro demethylase activity assays using synthetic histone peptides.

  • Utilize fluorescence-based assays that measure hydrogen peroxide production (a byproduct of KDM1A-mediated demethylation).

  • Implement mass spectrometry-based approaches to quantify demethylation products.

  • Compare activity per unit of KDM1A protein to normalize for expression differences.

• Protein complex analysis:

  • Assess CoREST association with KDM1A via co-immunoprecipitation, as this interaction is critical for enzymatic function.

  • KDM1A inhibitors like SP2509 work by attenuating the binding of KDM1A with CoREST .

  • Use proximity ligation assays to visualize and quantify KDM1A-partner interactions in situ.

  • Analyze the ratio of complex-bound versus free KDM1A as an indicator of potential activity.

• Transcriptional readouts:

  • Quantify expression of well-established KDM1A target genes (p21, p27, C/EBPα) as functional surrogate markers of activity .

  • Implement reporter assays with KDM1A-responsive promoters to monitor activity changes.

  • Use RNA-seq to develop gene expression signatures that correlate with KDM1A activity states.

  • Compare active versus repressed target genes to distinguish between co-activator and co-repressor functions.

• Chromatin structure analysis:

  • Implement assays that detect changes in chromatin accessibility (ATAC-seq) at KDM1A target sites.

  • Use Hi-C or related techniques to analyze topological domain boundaries maintained by KDM1A .

  • Apply super-resolution microscopy to visualize changes in the spatial organization of KDM1A-regulated loci.

  • Monitor the segregation of KDM1A-repressed genes from neighboring active chromatin environments as a functional readout .

These methods collectively provide a comprehensive assessment of KDM1A functional status beyond simple expression levels, enabling researchers to detect subtle alterations in activity that may have significant biological consequences .

How might emerging antibody technologies enhance our understanding of KDM1A biology and function?

Emerging antibody technologies offer unprecedented opportunities to advance KDM1A research:

• Single-domain antibodies and nanobodies:

  • Develop KDM1A-specific nanobodies that can access sterically hindered epitopes within chromatin complexes.

  • Create intrabodies that can track KDM1A in living cells without disturbing its function.

  • Engineer conformation-specific nanobodies that distinguish between active and inactive KDM1A states.

  • These smaller antibody formats could reveal previously inaccessible aspects of KDM1A complex formation and dynamics.

• Proximity-dependent labeling antibodies:

  • Conjugate KDM1A antibodies with TurboID or APEX2 for proximity-dependent biotinylation of the KDM1A interactome.

  • Apply this technology to map tissue-specific and disease-state-specific interaction networks.

  • Combine with mass spectrometry to identify novel, transient, or context-dependent KDM1A binding partners.

  • These approaches would provide comprehensive insight into how KDM1A functions differently within various cellular contexts, such as cancer stem cells versus normal cells .

• Bi-specific antibodies for functional studies:

  • Develop bi-specific antibodies that target KDM1A and its binding partners simultaneously.

  • Create antibody-based tools that can selectively disrupt specific KDM1A interactions (e.g., KDM1A-CoREST) without affecting others.

  • Engineer antibody-based molecular glues to force novel KDM1A interactions for functional studies.

  • These tools would enable precise manipulation of KDM1A function with greater specificity than current small molecule inhibitors.

• Antibody-guided epigenome editing:

  • Conjugate KDM1A antibodies with epigenome editing tools (dCas9-based modifiers) for locus-specific recruitment.

  • Use antibody-directed degradation (AbTACs) to achieve tissue-specific KDM1A depletion.

  • Create antibody-photocaged inhibitors for spatiotemporal control of KDM1A function.

  • These approaches would allow unprecedented precision in studying KDM1A's role in specific genomic contexts and cell types.

• Super-resolution microscopy compatible antibodies:

  • Develop antibodies optimized for STORM, PALM, or STED microscopy to visualize KDM1A distribution at nanoscale resolution.

  • Create antibody pairs for advanced FRET applications to monitor KDM1A interactions in living cells.

  • Implement multiplexed antibody imaging to simultaneously track KDM1A, its substrates, and chromatin states.

  • These imaging approaches would reveal how KDM1A's intrinsically disordered N-terminal region contributes to the segregation of repressed genes from neighboring active chromatin environments .

These emerging antibody technologies promise to transform our understanding of KDM1A biology by enabling more precise, dynamic, and context-specific investigations of its multifaceted functions in health and disease .

What are the current knowledge gaps in KDM1A biology that require development of novel antibody-based approaches?

Despite significant advances in KDM1A research, several critical knowledge gaps remain that could be addressed through novel antibody-based approaches:

• Dynamic regulation of KDM1A activity:

  • Current gap: We have limited understanding of how KDM1A activity is dynamically regulated in response to cellular signaling or environmental cues.

  • Antibody solution: Develop conformation-specific antibodies that selectively recognize active versus inactive states of KDM1A, enabling real-time monitoring of activity fluctuations.

  • Implementation: Create biosensor systems using these antibodies coupled with FRET or bioluminescence resonance energy transfer (BRET) technologies to track KDM1A activation in living cells.

• Cell type-specific KDM1A complexes:

  • Current gap: The composition of KDM1A-containing complexes likely varies between cell types and disease states, but comprehensive mapping is lacking.

  • Antibody solution: Implement tissue-specific proximity labeling using KDM1A antibodies conjugated to engineered peroxidases or biotin ligases.

  • Implementation: Apply this approach across diverse tissues to generate cell type-specific KDM1A interactome maps, particularly focusing on neuronal subtypes where KDM1A plays critical roles in gene regulation and topological domain maintenance .

• Non-histone substrates identification:

  • Current gap: While KDM1A is known to demethylate non-histone substrates, comprehensive identification of these targets remains incomplete.

  • Antibody solution: Develop substrate-trapping antibodies that recognize the KDM1A-substrate transition state or stabilize enzyme-substrate complexes.

  • Implementation: Combine with proteomics approaches to identify novel methylated proteins that interact with KDM1A in various cellular compartments.

• KDM1A in 3D chromatin organization:

  • Current gap: The mechanistic role of KDM1A in maintaining chromatin topological boundaries is emerging but poorly understood .

  • Antibody solution: Create antibodies specifically targeting the N-terminal intrinsically disordered region of KDM1A that is essential for gene segregation functions.

  • Implementation: Apply these antibodies in combination with super-resolution microscopy and chromosome conformation capture techniques to visualize and manipulate KDM1A's role in 3D genome organization.

• Therapeutic resistance mechanisms:

  • Current gap: The mechanisms of resistance to KDM1A inhibitors in cancer therapy remain largely unexplored.

  • Antibody solution: Develop antibodies recognizing post-translational modifications of KDM1A associated with inhibitor resistance.

  • Implementation: Apply these antibodies to compare patient samples before and after treatment failure to identify biomarkers of resistance and inform combination therapy strategies.

• Neuron-specific KDM1A functions:

  • Current gap: The specific roles of neuron-specific KDM1A splice variants (neuroLSD1) and their contribution to intellectual disability disorders remain unclear .

  • Antibody solution: Generate splice variant-specific antibodies that can distinguish between standard KDM1A and neuroLSD1.

  • Implementation: Use these antibodies to map the distinct genomic binding profiles and protein interactions of each isoform in neuronal development and function.