SF2 Antibody

About the Target

SF2 also known as SRSF1/ASF is a serine/arginine-rich (SR) RNA-binding protein that plays a crucial role in pre-mRNA splicing, mRNA stability, export, and translation. Structurally, it contains two RNA recognition motifs (RRMs) connected by a glycine- and arginine-rich linker, which synergistically enhance RNA binding specificity. Depending on the literature source, SF2 may also be discussed as ASF and SRSF1.

Reported cellular context includes cytoplasm, nucleus, and spliceosome, which can matter when signal is compared across treatments or changing cell states. Following SF2 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.

Research Context

SF2 is commonly interpreted in the context of neuroscience research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm, nucleus, and spliceosome, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.

Consider these angles when interpreting target-level changes:

• apparent redistribution between cytoplasm, nucleus, and spliceosome across matched conditions
• compartment-specific patterns relevant to neuronal polarity, transport, or synaptic context
• co-patterning with orthogonal markers and control conditions that clarify pathway state
• time-matched comparisons so changes reflect biology rather than handling or sampling drift

Variant Considerations

If your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for SF2. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.

Standardize sampling time, control choice, and downstream analysis thresholds so apparent differences in SF2 reflect biology rather than handling. When interpreting SF2, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.

For multi-run studies, a shared reference condition can keep SF2 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.