In Situ Sequencing for Targeted RNA Analysis in Tissue

Analyzing RNA within intact tissues provides crucial insights into gene expression while preserving spatial context. Traditional sequencing methods require tissue dissociation, losing valuable positional information. In situ sequencing overcomes this by enabling targeted RNA analysis directly in fixed samples, maintaining cellular architecture and localization.

This approach has wide applications in neuroscience, cancer research, and developmental biology, where understanding gene activity at a single-cell level is essential. By combining molecular barcoding with advanced imaging, researchers can visualize transcripts with high specificity.

Key Components of the Technique

In situ sequencing integrates molecular and imaging technologies to detect RNA while preserving spatial information. Targeted padlock probes hybridize to specific RNA sequences, followed by rolling circle amplification (RCA) to generate localized amplicons. These amplified products serve as the foundation for sequencing, ensuring transcript identification occurs within the tissue environment. Unlike bulk RNA sequencing, which averages gene expression across dissociated cells, this approach retains native tissue architecture, enabling single-cell resolution mapping.

Molecular barcoding assigns unique sequences to individual transcripts, enhancing specificity and minimizing errors. Error-correcting codes further improve accuracy, reducing misinterpretation. This precision is particularly valuable for studying heterogeneous tissues where gene expression varies across cell types.

Sequencing relies on iterative rounds of fluorescent nucleotide incorporation, revealing transcript sequences step by step. Advanced imaging systems capture these fluorescent signals, translating them into digital readouts corresponding to gene sequences. Multiple sequencing cycles allow detection of diverse transcripts, even at low expression levels.

Sample Preparation and Fixation

Preserving RNA integrity while maintaining tissue architecture is critical for in situ sequencing. Fixation methods influence probe hybridization and signal detection. Formaldehyde-based crosslinking stabilizes RNA and protein structures, preventing degradation while preserving spatial relationships. Paraformaldehyde (PFA) at 3–4% is commonly used, effectively crosslinking nucleic acids without excessive modification that could hinder probe accessibility. However, fixation duration must be carefully controlled to prevent excessive crosslinking, which reduces hybridization efficiency.

Alcohol-based fixation methods, such as ethanol or methanol, precipitate nucleic acids while minimizing enzymatic degradation, making them useful for tissues with high RNase activity. However, they may compromise protein integrity, limiting compatibility with multiplexed analyses that combine RNA sequencing with immunohistochemistry. Optimizing fixation conditions is essential to balance RNA stability and tissue morphology.

Tissue sections must be prepared precisely to ensure optimal probe penetration and sequencing efficiency. Cryosectioning and paraffin embedding are two primary strategies. Fresh-frozen tissues, sectioned at 5–10 µm thickness, maintain RNA in a near-native state, making them suitable for in situ sequencing. However, freezing can introduce ice crystal artifacts that disrupt cellular architecture. Formalin-fixed paraffin-embedded (FFPE) samples provide excellent structural preservation, though paraffin removal must be carefully optimized to prevent RNA degradation. Deparaffinization with xylene followed by gradual rehydration ensures effective probe accessibility while maintaining transcript integrity.

Probe Design and Hybridization

Designing probes for in situ sequencing requires balancing specificity, sensitivity, and accessibility to target RNA sequences. Padlock probes, short single-stranded DNA molecules, recognize specific transcript regions and form circularized structures upon hybridization. Target site selection must account for RNA secondary structures that can hinder probe binding, necessitating computational analysis to identify accessible regions. Probe sequences must also be optimized to minimize off-target binding, which can introduce background noise. Locked nucleic acids (LNAs) or modified bases strengthen probe-target interactions, ensuring stable hybridization.

Hybridization efficiency depends on factors such as temperature, salt concentration, and buffer composition. Formamide-containing buffers reduce non-specific interactions while maintaining probe accessibility, though excessive stringency can weaken signal intensity. Optimizing hybridization kinetics is particularly important in complex tissues where transcript distribution varies. The diffusion properties of probes also affect hybridization outcomes, with smaller probes offering superior tissue penetration but potentially reduced specificity.

Enzymatic ligation ensures that only perfectly hybridized padlock probes are circularized and amplified. Ligases such as T4 DNA ligase or SplintR ligase selectively join probe ends, preventing amplification of mismatched sequences. This step is particularly useful for distinguishing homologous transcripts, such as splice variants or closely related gene family members. Rolling circle amplification (RCA) then generates localized amplicons, creating distinct molecular signals for sequencing. RCA efficiency depends on polymerase selection, with phi29 DNA polymerase being preferred for its high processivity and strand displacement activity, allowing robust signal amplification.

Sequencing Chemistry

Decoding RNA sequences within intact tissues requires a chemistry that balances precision, efficiency, and compatibility with fluorescent imaging. The process typically relies on cyclic enzymatic reactions where fluorescently labeled nucleotides are incorporated into amplified RNA amplicons, revealing sequence identity step by step. Unlike bulk sequencing, which operates in solution, in situ sequencing functions within fixed tissue environments, requiring modifications to conventional sequencing chemistries.

Sequencing-by-ligation uses fluorescently labeled oligonucleotides that hybridize to target sequences and are enzymatically ligated. This method offers high specificity, as ligation occurs only when probe sequences perfectly match the template. However, its throughput is limited by multiple hybridization and ligation rounds. Alternatively, sequencing-by-synthesis (SBS) employs DNA polymerases to incorporate reversible terminator nucleotides, generating a sequential readout of the transcript. This approach benefits from rapid reaction kinetics and strong signal intensities but requires optimization to prevent premature termination or incomplete incorporation of labeled bases.

Imaging Systems and Signal Detection

Capturing sequencing signals within intact tissue requires advanced imaging systems capable of high sensitivity and spatial precision. Fluorescence microscopy is the foundation for signal detection, with confocal and wide-field microscopy commonly used depending on resolution and throughput needs. Confocal microscopy offers superior optical sectioning, reducing background fluorescence and enhancing signal clarity, making it useful for densely packed tissues. However, its point-scanning nature can limit imaging speed. Wide-field microscopy enables faster acquisition by capturing signals across a broad field of view but may require computational post-processing to correct for out-of-focus light.

Super-resolution techniques, such as stochastic optical reconstruction microscopy (STORM) and structured illumination microscopy (SIM), enhance resolution beyond the diffraction limit, improving transcript visualization within cellular compartments. Image processing algorithms further refine signal extraction, using machine learning-based approaches to differentiate true sequencing signals from background noise. By integrating high-resolution imaging with computational deconvolution, researchers achieve accurate transcript identification even in complex tissue environments where fluorescence overlap complicates analysis.

Spatial Resolution of Transcripts

Mapping transcript locations with subcellular precision enables researchers to investigate gene expression patterns in their native tissue context. Spatial resolution depends on probe design, amplification strategy, and imaging optics. Rolling circle amplification (RCA) generates discrete amplicons, allowing transcripts to be visualized as distinct fluorescent spots. The distance between these signals determines practical resolution limits, with most in situ sequencing methods achieving single-molecule resolution when combined with high-performance microscopy.

Tissue architecture adds complexity, as tightly packed cells or overlapping signals can obscure transcript localization. Computational tools, such as spatial deconvolution algorithms, resolve ambiguities by integrating fluorescence intensity data with known tissue structures. Single-cell segmentation techniques further refine spatial mapping, ensuring transcripts are assigned to individual cells rather than misattributed to neighboring regions. By combining precise molecular labeling, optimized imaging, and computational post-processing, in situ sequencing enables detailed spatial transcriptomics, shedding light on cellular heterogeneity and microenvironmental influences on gene expression.