What is Pandora-Seq and how does it differ from traditional small RNA sequencing?

Pandora-Seq is a specialized sncRNA sequencing method that uses sequential enzymatic treatments (T4PNK + AlkB) to repair RNA termini and remove internal methylation, enabling the detection of modified sncRNAs like tsRNAs and rsRNAs—all while producing unbiased small RNA profiles.

Which small RNAs can Pandora-Seq detect?

It captures a broad range of small non-coding RNAs, including miRNAs, piRNAs, tsRNAs (tRNA-derived), rsRNAs (rRNA-derived), snoRNAs, and snRNAs—far beyond the miRNA-dominated results of conventional sequencing.

Why are tsRNAs and rsRNAs invisible to standard methods?

These sncRNAs often carry terminal or internal modifications (e.g. m¹A, m³C, 5′-OH, 2′,3′-cP) that block adaptor ligation and reverse transcription, making them invisible in standard small RNA-seq workflows.

How does Pandora-Seq overcome these modification barriers?

First, T4PNK repairs fragmented RNA ends for adaptor ligation; then AlkB removes methylation that blocks reverse transcription; this combines to create a fully compatible sncRNA library.

Can Pandora-Seq detect sncRNAs in archived or low-quality samples?

Yes. Rigorous enzymatic treatments and optimized library preparation make Pandora-Seq well suited for challenging samples like frozen tissue or degraded RNA—and still able to uncover hidden sncRNAs.

Is the bioinformatics part of Pandora-Seq comprehensive?

Yes. The protocol couples with the SPORTS pipeline for sncRNA annotation and quantification, mapping reads to genomic loci and parental RNAs for deep, publication-ready analysis.

What types of downstream analysis are typical for Pandora-Seq data?

Clients receive visualisations and tables including length/statistics distributions, differential expression (volcano/heatmaps), cluster analysis, and optional functional enrichment (GO/KEGG) and target prediction.

Does Pandora-Seq work for human and non-human samples?

Absolutely. The method has been validated across organisms—from bacteria and archaea to mice and human tissues—and is highly versatile.

How does barcode or Y-RNA detection benefit from Pandora-Seq?

Pandora-Seq has uncovered small RNAs derived from Y-RNAs and other non-canonical sources that are usually missed—opening new opportunities for discovery in gene regulation and reproductive biology.

What types of research benefit most from Pandora-Seq?

Ideal for studies in biomarker discovery, epigenetics and inheritance, cardiovascular research, stem cell differentiation, cancer biology—any research where sensitive and comprehensive small RNA detection matters.

Pandora-Seq: Advanced Small RNA Sequencing for tsRNA & rsRNA Detection

What is Pandora-Seq?

Pandora-Seq is an advanced small non coding RNA sequencing (sncRNA sequencing) technology that overcomes the limitations of traditional small RNA sequencing (sRNA-seq). Standard workflows mainly detect miRNAs and piRNAs with canonical 5′ and 3′ ends, leaving many modified RNAs undetected.

Pandora-Seq introduces a unique enzymatic strategy:

T4 PNK repairs RNA termini, making them suitable for adaptor ligation.

AlkB demethylase removes internal RNA modifications that normally block reverse transcription.

The result is a complete, unbiased sncRNA profile, including tsRNAs, rsRNAs, snoRNAs, and snRNAs. This makes Pandora-Seq especially valuable for researchers who need accurate detection of both modified and unmodified small RNAs.

Pandora-Seg Principle

Comparison with Competing Methods

Feature	Pandora-Seq (PANDORA)	Traditional Small RNA-Seq
Terminal & Internal Modifications	Employs T4PNK to normalize termini and AlkB to remove methylation blocks, enabling full sncRNA recovery	Fails to capture RNAs with modified ends or internal methylation; biased toward miRNAs
sncRNA Diversity Detected	Captures a full spectrum, including tsRNA, rsRNA, snoRNA, snRNA—revealing hidden sncRNA layers	Primarily detects canonical miRNAs and some piRNAs, underrepresenting other sncRNAs
Quantitative Accuracy	Provides unbiased quantification across sncRNA classes due to modification removal	Quantification skewed by failure to capture modified small RNAs.
Landscape Coverage	Extends coverage across tissues and organisms, revealing previously "invisible" sncRNAs across multiple species	Limited to highly expressed, standard sncRNAs; hidden signals remain undetected.
Bioinformatics Analysis	Integrates with SPORTS pipeline for detailed mapping, classification, and annotation to parental RNAs	Often restricted to miRNA mapping and general alignment without locus-specific detail.
Overall Profiling Capability	Offers a panoramic, comprehensive view of the small RNA universe	Captures a narrow subset—primarily canonical miRNAs—failing to reflect true complexity.

Data Analysis in Pandora-Seq

Pandora-Seq provides a comprehensive sncRNA sequencing analysis pipeline, combining quality control, alignment, annotation, and advanced statistical evaluation. This ensures that every class of small non-coding RNA (sncRNA) is accurately profiled and interpreted.

Standard Bioinformatics Analysis

Raw Data Filtering – Removal of low-quality reads and adaptor sequences to ensure reliable downstream analysis.

Genome and Database Alignment – Mapping against reference genomes and curated databases of miRNA, piRNA, tRNA, rRNA, snoRNA, and snRNA.

Length and Classification Statistics – Distribution plots (histograms and pie charts) to visualise the abundance and length range of different sncRNA classes.

Differential Expression Analysis – Identification of significantly altered sncRNAs between sample groups using fold-change and p-value thresholds.

Clustering and Heatmaps – Hierarchical clustering to highlight group-specific sncRNA expression patterns.

Advanced Functional Analysis (Optional)

Target Prediction – Computational prediction of mRNA targets for specific sncRNAs.

Pathway Enrichment – Gene Ontology (GO) and KEGG analyses to connect sncRNA changes with biological pathways.

Locus Visualisation – Site-specific mapping of tsRNAs or rsRNAs to reveal origin and sequence variation.

Pandora-Seq integrates specialised annotation tools, offering deeper resolution than conventional small RNA sequencing (sRNA-seq), particularly for modified tsRNAs and rsRNAs.

Package	Description	Key Features
miRNA Sequencing	Specific enrichment and profiling of microRNAs (miRNAs).	High data yield, precise detection of low-abundance miRNAs, publication-ready QC.
piRNA Sequencing	Targeted enrichment and sequencing of PIWI-interacting RNAs (piRNAs).	Higher effective read ratios compared with conventional sRNA-seq.
tsRNA/tRF Sequencing	Comprehensive detection of transfer RNA-derived small RNAs (tsRNAs, tRFs, tiRNAs).	Reference to curated databases, detailed expression profiling.
rsRNA Sequencing	Profiling of ribosomal RNA-derived small RNAs (rsRNAs).	Improved coverage of rsRNAs often missed by standard workflows.
Bacterial sRNA Sequencing	Enrichment and sequencing of 50–300 nt bacterial small RNAs.	Optimised for microbial samples, effective data ratio higher than standard RNA-seq.

Applications of Pandora-Seq

Pandora-Seq expands the scope of small non coding RNA sequencing (sncRNA sequencing) beyond conventional sRNA-seq, enabling researchers to address a wide range of biological and translational questions.

Biomarker Discovery

Identification of tsRNAs and rsRNAs as diagnostic and prognostic biomarkers in cancer and metabolic disorders.
Supports early detection strategies and precision medicine research.

Epigenetics and Inheritance

Detection of sperm sncRNA changes linked to environmental exposures.
Provides insights into intergenerational and transgenerational inheritance mechanisms.

Cardiovascular Research

Reveals rsRNAs and tsRNAs associated with atherosclerosis and vascular remodeling.
Expands understanding of regulatory sncRNAs beyond miRNAs.

Stem Cell and Developmental Biology

Tracks dynamic sncRNA regulation during cell reprogramming and differentiation.
Facilitates studies of lineage specification and cellular plasticity.

Pandora-Seq therefore offers a powerful tool for uncovering hidden layers of the sncRNAome, supporting both fundamental biology and applied research in health, agriculture, and biotechnology.

Sample Type	Minimum Amount Required	Quality Requirements	Storage & Transport
Cells	≥ 1 × 10⁵ cells	Healthy, intact, no contamination	Freeze at –80 °C, ship on dry ice
Tissues	≥ 50 mg	Fresh or snap-frozen, no degradation	Preserve in RNAlater or liquid nitrogen
Whole Blood / Serum / Plasma	≥ 2 mL	Clear, free from haemolysis	Store at –80 °C, ship on dry ice
Urine	≥ 50 mL	Collect in sterile container	Store at –80 °C, ship on dry ice
CSF	≥ 5 mL	Collect in RNAse-free tubes	Store at –80 °C, ship on dry ice
Total RNA	≥ 1–2 µg (≥50 ng/µL concentration)	Intact RNA, RIN ≥ 7, no visible degradation (28S/18S bands)	Store in RNase-free water/ethanol at –80 °C

Frequently Asked Questions (Pandora-Seq Service)

- What is Pandora-Seq and how does it differ from traditional small RNA sequencing?
  - Pandora-Seq is a specialized sncRNA sequencing method that uses sequential enzymatic treatments (T4PNK + AlkB) to repair RNA termini and remove internal methylation, enabling the detection of modified sncRNAs like tsRNAs and rsRNAs—all while producing unbiased small RNA profiles.
- Which small RNAs can Pandora-Seq detect?
  - It captures a broad range of small non-coding RNAs, including miRNAs, piRNAs, tsRNAs (tRNA-derived), rsRNAs (rRNA-derived), snoRNAs, and snRNAs—far beyond the miRNA-dominated results of conventional sequencing.
- Why are tsRNAs and rsRNAs invisible to standard methods?
  - These sncRNAs often carry terminal or internal modifications (e.g. m¹A, m³C, 5′-OH, 2′,3′-cP) that block adaptor ligation and reverse transcription, making them "invisible" in standard small RNA-seq workflows.
- How does Pandora-Seq overcome these modification barriers?
  - First, T4PNK repairs fragmented RNA ends for adaptor ligation; then AlkB removes methylation that blocks reverse transcription; this combines to create a fully compatible sncRNA library.
- Can Pandora-Seq detect sncRNAs in archived or low-quality samples?
  - Yes. Rigorous enzymatic treatments and optimized library preparation make Pandora-Seq well suited for challenging samples like frozen tissue or degraded RNA—and still able to uncover hidden sncRNAs.
- Is the bioinformatics part of Pandora-Seq comprehensive?
  - Yes. The protocol couples with the SPORTS pipeline for sncRNA annotation and quantification, mapping reads to genomic loci and parental RNAs for deep, publication-ready analysis.
- What types of downstream analysis are typical for Pandora-Seq data?
  - Clients receive visualisations and tables including length/statistics distributions, differential expression (volcano/heatmaps), cluster analysis, and optional functional enrichment (GO/KEGG) and target prediction.
- Does Pandora-Seq work for human and non-human samples?
  - Absolutely. The method has been validated across organisms—from bacteria and archaea to mice and human tissues—and is highly versatile.
- How does barcode or Y-RNA detection benefit from Pandora-Seq?
  - Pandora-Seq has uncovered small RNAs derived from Y-RNAs and other non-canonical sources that are usually missed—opening new opportunities for discovery in gene regulation and reproductive biology.
- What types of research benefit most from Pandora-Seq?
  - Ideal for studies in biomarker discovery, epigenetics and inheritance, cardiovascular research, stem cell differentiation, cancer biology—any research where sensitive and comprehensive small RNA detection matters.

Case Study: sncRNA Dynamics during Somatic Cell Reprogramming Revealed by PANDORA-Seq

Source: Shi et al., PANDORA-seq expands the repertoire of regulatory small RNAs by overcoming RNA modifications, Nature Cell Biology, 2021

During reprogramming of mouse embryonic fibroblasts (MEFs) into induced pluripotent stem cells (iPSCs), regulatory sncRNAs such as tsRNAs and rsRNAs may play critical roles in lineage specification. However, traditional small RNA sequencing fails to capture many modified sncRNAs, limiting our understanding of their dynamic regulation.

The study applied PANDORA-Seq to capture sncRNAs across three reprogramming stages: MEFs (day 0), intermediate (day 3), and iPSCs. The protocol included sequential treatments with T4PNK and AlkB demethylase, followed by optimized library prep and SPORTS1.1 pipeline analysis for sncRNA annotation and quantification.

PANDORA-Seq revealed dynamic shifts in sncRNA composition during reprogramming:

Heatmap of tsRNA expression (Figure 5d) showed distinct clusters of tsRNAs up- or downregulated across stages.
In contrast, miRNAs did not display comparable dynamics.
rsRNA expression patterns across stages were captured in a comparison matrix (Figure 5g).

Heatmap showing tsRNA expression dynamics during somatic cell reprogramming via Pandora-Seq. Heatmap illustrating tsRNA expression changes across reprogramming stages (MEFs → intermediate → iPSCs) detected by PANDORA-Seq.

PANDORA-Seq unveils previously hidden dynamics of tsRNAs and rsRNAs during cell fate transitions. These sncRNAs likely modulate translation and lineage commitment, underscoring the method's value in developmental biology and functional genomics.

Pandora-Seq Service: Unlock the Hidden Small RNA Landscape

What is Pandora-Seq?

Key Advantages of Pandora-Seq

Comprehensive Detection

Accurate Profiling

High Sensitivity

Advanced Bioinformatics