How does Disome-seq differ from Ribo-seq?

Ribo-seq captures single ribosomes to map where translation is happening. Disome-seq captures pairs of ribosomes (collisions) to map where translation is failing or stalling. Ribo-seq measures efficiency; Disome-seq measures stress and quality control.

Can I use frozen samples for Disome-seq?

Yes, provided the samples were snap-frozen in liquid nitrogen immediately after harvest. However, to preserve the 'in vivo' state of ribosome collisions, cell lysis with elongation inhibitors prior to freezing is often the gold standard.

What is the 'Pause Score' in your analysis report?

The Pause Score is a bioinformatic metric calculated by comparing the density of Disome reads to Monosome (Ribo-seq) reads at a specific locus. A high score indicates that ribosomes are colliding/stacking at that site more frequently than expected by chance.

Do I need to perform Ribo-seq alongside Disome-seq?

Highly recommended. To accurately calculate a 'Pause Score' (Collision vs. Normal Translation), you need the Monosome data (Ribo-seq) as a baseline. We offer bundled pricing for performing both.

Is Disome-seq suitable for studying viral infection?

Absolutely. Viruses often hijack host ribosomes and can induce collisions due to their highly structured RNA or rapid translation rates. Disome-seq is excellent for studying host-virus translational conflict.

Disome-seq Service - Map Ribosome Collisions

Feature	Polysome Profiling	Ribo-seq (Standard)	Disome-seq (Advanced)	RNC-seq (3rd Gen)
Core Technology	Sucrose Gradient + UV	RNase Digestion + NGS	Disome Enrichment + NGS	Full-length TGS (Nanopore)
Resolution	Global / Component Level	Codon (Single Ribosome)	Codon (Colliding Pair)	Transcript Isoform Level
Primary Output	Translation Efficiency (TE)	ORF Localization	Pause Sites & Stress	Active Isoform Identity
Fragment Size	N/A (Full RNA)	~28-32 nt	~50-65 nt	Full Length (>1kb)
Solves For...	"Is translation active?"	"Where is the ribosome?"	"Where is it stuck?"	"Which splice variant?"
Ideal Context	General Phenotype Screen	Gene Expression Control	RQC & Protein Folding	Complex Transcriptomes

Sample Type	Cell Lines, Animal Tissue, Plant Tissue	Fresh samples preferred; Snap-frozen accepted.
Input Amount	≥ 2 × 10^7 cells or 200mg tissue	Disomes are low-abundance; high input is critical.
RIN Value	≥ 7.0 (Recommended)	High integrity RNA ensures valid collision data.
Sequencing Depth	> 50 Million reads / sample	Deep sequencing required to detect rare stall sites.
Bioinformatics	Included	Mapping, Pause Score, Motif Analysis, GO Enrichment.

The researchers aimed to understand how cellular stress (oxidative stress) impacts translational dynamics globally. They utilized Disome-seq to differentiate between normal translation and pathological stalling.

System: HeLa cells treated with reagents to induce amino acid starvation or oxidative stress.
Technique: Disome-seq libraries were constructed by isolating the disome fraction from sucrose gradients after RNase digestion.

Structural Validation: The study confirmed that Disome-seq captures a precise ~62 nt footprint, corresponding to two tightly packed ribosomes.
Stress Response: Under oxidative stress, there was a global accumulation of disomes, specifically at sites encoding amino acids sensitive to oxidation.

Disome-seq data from Zhao et al 2021 showing ribosome collisions accumulating at stop codons under stress. A Metagene plot showing a dramatic accumulation of disome reads (peaks) at the Stop codon and specific internal pause sites under stress conditions, compared to untreated controls.

The study demonstrated that Disome-seq is a powerful tool for monitoring translational distress, revealing that "ribosome traffic jams" are a regulated aspect of the cellular stress response.