Did you know gene expression can vary greatly between nearby cells? These differences majorly affect cancer growth, brain function, and immune responses. Understanding these patterns is crucial for advancing research in these areas.
In situ RNA sequencing helps by sequencing RNA directly within intact tissues or cells. Unlike traditional methods that require breaking down samples, this technique preserves RNA’s spatial arrangement, revealing insights that might otherwise be lost.
This blog will explain how in situ RNA sequencing works, highlight key techniques like HybISS and FISSEQ, and introduce Biostate AI’s affordable RNA sequencing services, which are designed to support your research.
What is In-Situ RNA-Sequencing?
The term “in situ,” meaning “in its original place” in Latin, refers to studying biological materials in their native environment.
In the context of RNA sequencing, in situ RNA sequencing (RNA-seq) is a technique that sequences RNA directly within intact tissues or cells, preserving their natural spatial arrangement.
Unlike traditional RNA-seq, which requires homogenizing samples, in situ RNA-seq maintains the original position of RNA molecules within their tissue or cellular environment.
This method provides a more accurate view of gene expression and molecular interactions in their true biological context, offering insights that conventional RNA-seq cannot capture.
Benefits of In-Situ RNA-Seq
In situ RNA sequencing offers unique advantages beyond traditional RNA sequencing methods. Combining spatial context with gene expression data enables researchers to gain deeper insights into cellular behavior, tissue organization, and molecular interactions.
This makes it particularly useful for studying complex systems such as brain tissue, tumors, and developing embryos.
Here are some benefits of In Situ RNA-Sequencing.
- Spatial Gene Expression Insights: In situ RNA sequencing retains the spatial context of RNA molecules within tissues. This allows researchers to study how gene expression varies across different tissue regions, offering valuable insights into tissue structure and function.
- Single-Cell Resolution: This method enables the identification of gene expression patterns at the individual cell level, revealing cellular heterogeneity and distinct gene activities across various cell types.
- High-Resolution Mapping: In situ RNA sequencing provides nanoscale detail, surpassing the resolution achievable with standard RNA sequencing methods. This improves the accuracy of gene expression mapping within tissues.
- Multiplexing Capabilities: Researchers can analyze multiple RNA species simultaneously, making studying complex gene expression networks and cellular interactions easier.
- Detection of Novel Transcripts: In situ RNA sequencing can identify previously unknown RNA variants, such as alternative splicing events or retained introns, without requiring prior knowledge of the genes involved.
- Improved Understanding of Gene Regulation: This method preserves tissue structure and offers insights into how gene expression is regulated across different regions or cell types, supporting research into tissue function and disease mechanisms.
These benefits highlight why in situ RNA sequencing is gaining attention in research. But how does it actually work? Let’s break down some key methods that make these insights possible.
What are the Effective Methods of In-Situ RNA-Seq?
Understanding how genes behave within tissues can be challenging, especially when key spatial details are lost during sample processing. In Situ RNA-seq solves this by allowing researchers to map gene expression directly within intact cells and tissues.
This method is particularly useful for studying complex biological structures where cellular organization and interactions play a vital role. Two prominent methods are Fluorescent in situ Sequencing (FISSEQ) and Hybridization-based in situ Sequencing (HybISS).
Let’s discuss each of these in detail.
Hybridization-based in situ sequencing (HybISS) is an advanced method for spatially resolved transcriptomics in tissues. It expands on traditional in situ sequencing (ISS) by combining padlock probes (PLPs) and rolling circle amplification (RCA) to provide detailed insights into gene expression, cell types, and tissue architecture.
Key Features and Improvements
HybISS introduces several advancements that improve RNA transcript detection, imaging clarity, and experimental flexibility. These features make it easier to analyze complex tissues while maintaining efficient workflows.
- Sequence-by-Hybridization Chemistry: HybISS uses SBH chemistry for barcoding, improving detection accuracy, especially for low-abundance transcripts, while reducing background noise. This faster process enhances efficiency in high-throughput studies.
| Barcoding in HybISS assigns unique DNA tags to RNA molecules, improving detection accuracy and enabling efficient identification in high-throughput sequencing. |
- Amplicon Visualization: The process amplifies RNA using rolling circle amplification (RCA), producing strong signals visible with standard epifluorescence microscopes. This improves detection in complex tissues without requiring advanced imaging systems.
- Flexibility and Multiplexing: Designed to support larger gene panels and adaptable workflows.
- Enhanced Signal-to-Noise Ratio: The optimized probe design improves detection clarity and reduces background noise, enabling better imaging in dense tissues.
- Broad Applicability: HybISS has been proven effective for analyzing detailed tissue structures, such as human and mouse brain samples. It excels at preserving spatial context and resolving complex gene patterns.
HybISS Workflow
The HybISS process involves multiple steps that build on traditional ISS techniques. Each step is designed to preserve spatial details, improve signal detection, and support sequential imaging for comprehensive gene mapping.
- Reverse Transcription
The process starts by converting mRNA into complementary DNA (cDNA) using random primers and reverse transcriptase. Random primers help capture diverse transcripts without sequence bias, ensuring comprehensive gene coverage.
- PLP Hybridization and Ligation
Phosphorylated padlock probes (PLPs) are designed to target specific RNA sequences. These probes partially bind to the cDNA, leaving a gap. Tth Ligase then seals this gap, forming a circular DNA structure. RNase H is added to remove any remaining RNA, ensuring only the circular DNA remains for amplification.
- Rolling Circle Amplification (RCA)
The circular DNA undergoes RCA using phi29 polymerase. This enzyme continuously copies the circular DNA, creating long, repeated sequences in a compact cluster known as an amplicon. These dense clusters improve detection by amplifying the signal from individual RNA molecules.
- Bridge-Probe Hybridization
Bridge probes are short DNA sequences that link RCA amplicons to fluorescent readout probes. This step enables clear visualization during imaging.
- Readout Detection
Fluorescent probes and DAPI for nuclear staining are introduced to reveal the amplified RNA sequences. Each fluorescent signal corresponds to a specific gene, enabling researchers to identify gene locations within the tissue.
| DAPI (4′,6-diamidino-2-phenylindole) is a fluorescent stain commonly used in biological research to label cell nuclei. |
- Stripping and Rehybridization
To expand gene coverage, fluorescent probes are removed, and new probes are applied in cycles. This method allows multiple genes to be visualized from the same tissue sample.
- Image Analysis
Specialized software analyzes the fluorescent signals to decode the sequence data, identify gene types, and map their spatial positions within the tissue.
This structured process improves accuracy, signal clarity, and flexibility, making HybISS effective for studying complex tissues like the human brain.
Applications
HybISS offers practical advantages for researchers studying spatial gene expression. Its improved scalability and precision make it suitable for analyzing complex tissue structures and generating high-throughput data.
- Spatial Mapping: Suitable for profiling large gene panels across tissue sections.
- Complex Tissue Analysis: Ideal for studying intricate structures such as the human and mouse brain.
- Enhanced Imaging Efficiency: Supports high-throughput imaging while improving transcript detection accuracy.
HybISS is a powerful tool for researchers seeking detailed insights into spatial gene expression with improved accuracy and efficiency.
2. FISSEQ
Fluorescent In Situ Sequencing (FISSEQ) is a genome-wide gene expression profiling technique directly within fixed cells and tissues. It combines the spatial resolution of in situ hybridization with the comprehensive transcriptome coverage of RNA sequencing.
Key Steps in FISSEQ
The FISSEQ process combines multiple techniques to preserve spatial details while achieving transcriptome-wide coverage. Each step is crucial in ensuring accurate gene expression profiling directly within cells and tissues.
- In Situ Reverse Transcription
The process begins by fixing cells or tissues to preserve their structure. The sample is then made permeable to allow reagents to enter. Reverse transcription converts RNA into complementary DNA (cDNA) using a special nucleotide called aminoallyl dUTP.
This modified nucleotide allows the newly formed cDNA to be chemically cross-linked to cellular structures, preventing it from diffusing away. This step ensures that gene expression data retains its spatial context.
- RNA Degradation and cDNA Circularization
Once cDNA is formed, the original RNA is broken down, leaving only the stable cDNA behind. The cDNA is then circularized — meaning its ends are joined to form a closed loop. Circular DNA is ideal for amplification because it resists degradation and provides a continuous template for the next step.
- Rolling Circle Amplification (RCA)
The circular cDNA is amplified through RCA using a DNA polymerase enzyme like phi29. This process generates long, continuous DNA strands that fold into dense clusters called amplicons. These clusters are rich in copies of the original cDNA sequence, making detection easier during imaging.
- Sequencing by Ligation
Short, fluorescently labeled DNA probes are designed to bind specific sequences within the RCA amplicons. They are attached through a process called ligation. Each fluorescent signal represents a particular nucleotide, allowing sequences to be gradually decoded. Confocal microscopy captures these fluorescent signals across the tissue sample.
- Image Analysis and Data Processing
The captured images are processed using specialized software that identifies the fluorescent patterns, reconstructs the sequence data, and maps it back to the original tissue structure. This step aligns the detected sequences with known genes, enabling researchers to study gene expression in its exact cellular location.
FISSEQ’s ability to combine sequencing with spatial mapping makes it highly effective for studying complex tissues, revealing insights into cellular interactions, developmental biology, and disease mechanisms.
Applications of FISSEQ
FISSEQ is widely used in research areas that require spatial insights into gene expression. It helps uncover cell identities, tissue structures, and molecular changes associated with diseases.
- Cell Type Identification: Maps gene expression to define cell identities.
- Tissue Architecture Studies: Reveals spatial organization in biological systems.
- Disease Research: Identifies gene expression changes linked to pathology.
- Drug Discovery: Evaluates spatially distinct drug effects on gene expression.
Limitations of FISSEQ
Despite its strengths, FISSEQ has some limitations that may impact efficiency or data accuracy. Understanding these challenges is essential for optimizing experimental outcomes.
- Limited mRNA Read Efficiency: FISSEQ does not include a ribosomal RNA (rRNA) depletion step. Since rRNA is highly abundant, this can reduce the proportion of mRNA reads, lowering the overall efficiency of gene expression analysis.
- Potential Biases: FISSEQ can introduce biases during cDNA synthesis or amplification. While techniques like Expansion Microscopy (ExM) can improve spatial resolution, further optimization may still be needed to achieve consistent results.
- Imaging Requirements: FISSEQ relies on high-resolution confocal microscopy to capture fluorescent signals from amplified cDNA. This requires specialized imaging equipment, which may limit accessibility for some laboratories.
The above are some limitations of FISSEQ. Researchers have developed Expansion Microscopy (ExM) to overcome these challenges. Let’s understand the method in more depth.
Enhancing In-Situ RNA Sequencing with Expansion Sequencing
A promising advancement in in situ RNA sequencing. ExSeq combines the power of in situ RNA-seq with expansion microscopy (ExM), a technique that physically expands tissue samples to improve spatial resolution.
This innovation allows researchers to achieve nanoscale resolution using conventional microscopes, which standard in situ RNA-seq cannot achieve independently.
Procedure of Expansion Sequencing
Expansion sequencing involves steps designed to improve spatial resolution while preserving RNA integrity. The process begins with tissue preparation and ends with generating a sequencing library for transcript analysis.
Here are the key steps.
1. Tissue Fixation and RNA Anchoring
The biological specimen is fixed to preserve its structure and RNA integrity. Optionally, immunostaining can label specific cellular components. RNA molecules are then anchored using a reagent (LabelX) that covalently binds them to a cleavable linker, ensuring RNA retention during expansion and sequencing.
2. Gel Embedding and Expansion
The tissue is embedded in a swellable hydrogel polymerized to form a solid matrix. This gel supports the tissue and allows for isotropic expansion, typically around 4x. Expansion increases the distance between RNA molecules, enhancing resolution for subsequent sequencing.
3. In Situ Sequencing Library Generation
- Untargeted ExSeq: Random primers reverse transcribe RNA into cDNA, followed by rolling circle amplification (RCA) to generate spatially localized amplicons.
- Targeted ExSeq: Padlock probes hybridize to target transcripts, followed by gap filling and ligation. RCA amplifies the circularized probes into localized amplicons.
4. Imaging and Data Conversion
In situ sequencing is performed using a sequencing-by-ligation method. Fluorescently labeled probes are hybridized, ligated, and imaged. A high-resolution imaging system captures a series of 3D images to localize and sequence the amplicons. Fluorescence signals are processed to assign nucleotide bases and determine spatial coordinates.
5. Reference Generation (For Untargeted ExSeq)
cDNA amplicons are extracted from the hydrogel and sequenced using standard next-generation sequencing (NGS) to create a reference library. In situ, reads are then aligned to this more extended reference library to improve reading accuracy and coverage.
6. Data Analysis and Spatial Gene Expression Mapping
The data is normalized for sequencing depth and quality. Spatial gene expression patterns are analyzed using computational methods to identify cell populations, gene co-expression patterns, and correlations with tissue morphology. The final output is a spatial gene expression map visualized through various graphical representations.
To build on these foundations, effective RNA sequencing services are crucial for translating high-quality data into meaningful insights. Biostate AI provides tailored solutions to support this process.
How Biostate AI Supports RNA Sequencing?
Biostate AI offers specialized RNA sequencing services designed to simplify the process for researchers while delivering accurate and reliable data.
Here’s how Biostate AI helps:
- Affordable RNA Sequencing Services
Biostate AI provides cost-effective RNA sequencing for large projects at $80 per sample. For smaller studies, flexible pricing options are available, with rates of $110 per sample for 30-99 samples and $100 per sample for 100-299 samples. This makes high-quality sequencing accessible to a wider range of researchers.
- Versatile Sample Compatibility
Biostate AI accepts a range of sample types, including FFPE tissue, 10 µL blood samples, and samples from various organisms. This flexibility ensures compatibility with diverse research needs.
- Comprehensive RNA Coverage
Biostate AI sequences multiple RNA types, including mRNA, lncRNA, miRNA, and piRNA. This comprehensive coverage supports studies on gene expression, regulatory functions, and genome stability.
- Efficient and Reliable Insights
Biostate AI streamlines the sequencing process, delivering accurate data with minimal effort. This allows researchers to focus on interpreting results rather than managing complex sequencing workflows.
- Support for Low Sample Volumes
Unlike many services that require large sample batches, Biostate AI accommodates smaller sample sizes. This makes it ideal for research projects with limited material or exploratory studies.
Biostate AI combines affordability, flexibility, and scientific expertise to meet the needs of researchers working across various fields. Whether you’re studying gene expression, disease mechanisms, or biomarker discovery, Biostate AI offers tailored RNA sequencing solutions designed to support your research goals.
Winding Up!
Understanding the capabilities and limitations of RNA sequencing can help you make informed decisions about your research. While technologies continue to evolve, selecting a reliable sequencing partner is crucial for accurate data and meaningful insights. Choosing methods that align with your sample type, budget, and research goals can significantly improve your outcomes.
At Biostate AI, we understand the challenges researchers face in obtaining high-quality RNA sequencing data. Our services cater to diverse sample types, including FFPE tissue and small blood volumes, ensuring you get the insights you need without unnecessary complexity.
If you’re looking for a trusted RNA sequencing partner, Biostate AI is here to help. Contact us today to learn how we can support your research with reliable data, expert guidance, and cost-effective solutions. Get a quote for your experiment today!
FAQs
1. How does in situ RNA sequencing differ from spatial transcriptomics?
In situ RNA sequencing directly sequences RNA within intact tissues or cells, preserving their spatial context. Spatial transcriptomics, on the other hand, typically involves placing tissue sections on barcoded slides to capture spatial gene expression data. While both techniques offer spatial insights, in situ RNA sequencing achieves higher resolution by maintaining RNA molecules in their original cellular location.
2. Can in situ RNA sequencing be used with formalin-fixed paraffin-embedded (FFPE) samples?
Yes, certain in situ RNA sequencing methods, such as HybISS, can be adapted for FFPE samples. However, FFPE processing may reduce RNA quality, so optimized protocols are crucial for improving detection accuracy in these preserved samples.
3. What factors influence the success of in situ RNA sequencing experiments?
Key factors include sample preparation quality, probe design, imaging conditions, and data analysis techniques. Maintaining tissue integrity, selecting appropriate fluorescent markers, and ensuring optimal probe hybridization are essential for achieving accurate results.