Which nuclear compartments can TSA-Seq map (speckles, lamina, nucleolus) and how do you choose a marker?

TSA-Seq can be designed around a compartment marker compatible with HRP-mediated labeling (commonly nuclear speckles or nuclear lamina, and in some settings other defined structures). Marker choice is driven by your biological hypothesis, antibody performance, and whether you need proximity-to-speckle or proximity-to-lamina style interpretation. We align marker selection to your decision goal during the method-fit review.

How should TSA-Seq be interpreted: proximity scores vs absolute distance estimates?

TSA-Seq produces genome-wide proximity-style profiles that are most robustly interpreted as relative proximity along a compartment axis. Distance-style estimates can be supported by calibration strategies, but interpretation depends on the experimental staining condition and model assumptions. We report interpretation boundaries and provide tracks suitable for compartment-aware comparisons (RUO).

What QC evidence will I receive to audit mapping, replicates, and normalization?

You receive a QC report covering mapping summaries, replicate concordance, and documentation of normalization/calibration choices. We also provide reusable browser tracks and summary plots that allow you to audit signal consistency and interpretability across conditions (RUO).

What experimental controls or design choices reduce background and improve interpretability?

Key design choices include selecting a compartment marker with clear nuclear localization, maintaining consistent labeling conditions across samples, and using replicates to support concordance checks. We document design choices and highlight interpretation risks when background or marker specificity could affect proximity-style profiles (RUO).

Can TSA-Seq be compared across conditions or batches (what evidence is provided)?

Comparisons are supported when design and labeling conditions are harmonized and replicate concordance supports stability. We provide evidence artifacts (replicate concordance summaries and track-level deliverables) so you can judge whether condition shifts are biologically credible rather than technical (RUO).

How does TSA-Seq complement Hi-C sequencing for 3D contacts and Micro-C for higher resolution?

TSA-Seq reports proximity to a nuclear compartment, while contact-mapping assays report interaction frequencies between loci. Many projects use TSA-Seq to frame compartment context and then follow up with 3D contact assays such as Hi-C sequencing or Micro-C for contact-level hypotheses (RUO).

How do you validate findings with orthogonal methods such as 3D DNA FISH?

Orthogonal validation commonly uses imaging-based measurements to test predicted proximity patterns at selected loci. TSA-Seq can be used to prioritize loci for follow-up experiments and guide targeted validation designs (RUO).

What are RUO limits of interpretation and what you will not claim?

This service is for research use only. We do not provide clinical interpretations, diagnostic conclusions, or treatment recommendations. Proximity-style profiles support mechanistic hypotheses and comparative studies, but they do not by themselves prove causality or clinical relevance.

TSA-Seq Service | Nuclear Compartment Proximity Mapping (RUO)

Sample type	Minimum input	Recommended input	Shipping
Cells / nuclei	Project-dependent (feasibility review)	Project-dependent (replicates recommended)	Cold chain per sample type (RUO)
Fresh tissue	Project-dependent (feasibility review)	Project-dependent (replicates recommended)	Cold chain per sample type (RUO)
Frozen tissue	Project-dependent (quality-dependent feasibility)	Project-dependent (replicates recommended)	Cold chain per sample type (RUO)

Compartmentalization is a core feature of nuclear genome organization, but many experiments need a genome-wide way to estimate proximity to defined nuclear structures rather than only contact frequencies between loci.

In the TSA-Seq framework, HRP-mediated tyramide labeling creates a spatially decaying labeling field around a compartment marker. Sequencing readouts are converted into genome-wide proximity-style profiles that can be interpreted as a cytological ruler under defined assumptions (RUO).

Chen et al. demonstrated genome-wide proximity mapping relative to nuclear compartments and established a compartment-axis interpretation that connects proximity patterns with genome activity. The figure below is reproduced from the publication for methodological context (RUO).

TSA-Seq literature figure illustrating genome-wide proximity mapping relative to nuclear compartments and cytological ruler interpretation.

Figure source: Mapping 3D genome organization relative to nuclear compartments using TSA-Seq as a cytological ruler (Journal of Cell Biology). PDF.

TSA-Seq provides a compartment-proximity layer that can guide mechanistic hypotheses, locus prioritization, and orthogonal validation planning (RUO).

TSA-Seq Service (RUO)

What this service is and when it’s the right fit

What you get (evaluation-focused)

Use cases mapped to decisions

1) Compartment-aware regulation hypotheses

2) Perturbation or condition comparisons

3) Prioritizing loci for 3D follow-ups

4) Integrating proximity with RNA/chromatin context

End-to-end TSA-Seq workflow (RUO)

Demo results you can expect (illustrative; RUO)

A) Genome browser proximity tracks

B) Compartment-axis interpretation panels

C) QC and replicate concordance snapshot

Sample requirements (RUO)

Data analysis & deliverables (audit-ready)

Case study: TSA-Seq maps genome organization relative to nuclear compartments

Decision-blocking FAQs