Sample Submission Guidelines
Why Choose Our Ribo-seq Services
Built for scientists. CD Genomics delivers Ribo-seq with codon-level resolution—combining optimised wet-lab methods and a transparent ribo-seq analysis pipeline for reproducible results.
- Translation-aware QC: 3-nt periodicity, P-site offsets, start/stop metagene, replicate concordance.
- Flexible delivery: End-to-end or analysis-only from purified RPFs/raw FASTQ.
- Deep analytics: TE & differential translation, uORF/sORF, stalling, codon usage, GO/KEGG.
- TE-ready design: Optional matched RNA-seq for robust translation efficiency.
- Optimised lab workflow: Inhibitor → RNase → rRNA depletion → PAGE.
- Broad inputs: Cells, tissues, bacteria, or RPFs; non-model species by review.
- Publication-ready outputs: Clean figures (PNG/SVG), tables (CSV/TSV), concise report.
- Traceable & secure: Versioned command logs, full metadata, SOP-driven handling.
- Expert support: Scientist consults on design, QC gates, and ribo-seq analysis pipeline options.
Technology Introduction — What Ribosome Profiling (Ribo-seq) Measures
Ribosome Profiling (Ribo-seq) captures ribosome-protected fragments to quantify active translation. Our ribo-seq service combines wet-lab execution with expert ribo-seq data analysis in a validated ribo-seq analysis pipeline.
Ribosomes are stabilised on mRNA. Unprotected RNA is digested by RNase. ~28–30 nt fragments (RPFs) are purified, converted to libraries, and sequenced. Position-resolved footprints reveal initiation, elongation dynamics, pausing, and termination behaviour.
Why Ribo-seq matters
- Distinguishes transcriptional changes from translational control using translation efficiency (TE).
- Maps initiation sites and uORFs/sORFs with frame-aware P-site calling.
- Detects ribosome stalling or frameshift signals along coding regions.
- Links findings to pathways via GO/KEGG enrichment.
Core workflow (lab → analysis)
1. Translation stabilisation → RNase digestion → rRNA depletion → PAGE size selection.
2. Library preparation → short-read sequencing.
3. Ribo-seq analysis: alignment, P-site assignment, 3-nt periodicity QC, TE and differential translation, uORF/sORF, stalling, codon usage, enrichment.
Ribo-seq Analysis Pipeline
Our ribo-seq analysis pipeline combines a standardised wet-lab workflow with transparent ribo-seq analysis steps. Each stage is traceable and quality-gated.
Wet-lab workflow
1. Stabilise translation — freeze ribosomes on mRNA.
2. RNase digestion — remove unprotected RNA; retain RPFs (~28–30 nt).
3. rRNA depletion & PAGE — reduce rRNA carryover; size-select targets.
4. Library construction — adaptor ligation, reverse transcription, PCR.
5. Sequencing — short-read platforms; depth matched to goals.
Data processing (ribo-seq data analysis)
1. Raw-read QC — adapter/quality filtering; length distribution.
2. Alignment — genome/transcriptome mapping; remove rRNA/tRNA reads.
3. P-site assignment — frame-aware offsets for codon positioning.
4. 3-nt periodicity — start/stop metagene profiles verify translation.
5. Quantification — gene/ORF/uORF counts; normalisation.
6. Comparisons — TE with matched RNA-seq; differential translation/TE.
7. Advanced modules — uORF/sORF, stalling maps, codon usage, GO/KEGG.
Ribo-seq Research Strategy
Analysis Menu — Pick and Extend
Select the modules you need; outputs integrate with the package above.
Ribo-seq and Multi-omics Integration Analyses
Quantitative Ribo
- Gene/ORF counts, normalisation, differential translation.
- Replicate correlation and outlier review.
Sequence-level
- P-site metagene; 3-nt frame distribution.
- uORF/sORF discovery with coordinates.
Cross-omics (with RNA-seq)
- Translation efficiency (TE) estimation and differential TE.
- Concordant/discordant mRNA–RPF sets.
Advanced interpretation
- Ribosome stalling maps; codon-usage patterns.
- GO/KEGG enrichment to connect biology.
For deliverables, see What You Will Receive.
Quality & Study Design
Plan for reproducible Ribo-seq with clear acceptance criteria and full traceability.
Experimental design
- Define contrasts; include ≥3 biological replicates per group when feasible.
- Add matched RNA-seq when TE is a primary endpoint.
Acceptance criteria (translation-aware QC)
- Strong 3-nt periodicity and correct P-site offsets.
- Expected RPF length distribution and robust mapping rates.
- Low residual rRNA/tRNA fractions.
- High replicate concordance; formal outlier review.
Traceability & audit
- Run sheet records instruments, kit lots, and key parameters.
- Versioned command logs for every analysis step; metadata retained with outputs.
Depth & risk controls
- Increase depth for uORF/sORF or fine-scale stalling.
- If periodicity is weak, refine offsets and re-assess frames.
- High rRNA: adjust depletion and size-selection SOPs.
Consult us for non-model species or low-input designs.
What You Will Receive
A complete, publication-ready package designed for rapid interpretation.
Data files
- FASTQ; BAM/indices on request.
- Count tables (genes/ORFs/uORFs/sORFs, CSV/TSV).
- Metadata: instrument settings, run notes, sample manifest.
QC pack
- Read quality, mapping, rRNA/tRNA residuals, RPF length modes.
- P-site metagene and 3-nt periodicity plots.
- Replicate correlation heatmap and outlier flags.
Analyses delivered
- TE and differential TE; differential translation per gene/ORF.
- uORF/sORF discovery, stalling hotspots, codon-usage profiles.
- Functional enrichment: GO/KEGG terms and pathways.
Report & support
- Concise PDF with figures and interpretation notes.
- Editable figures (PNG/SVG) and tables (CSV/TSV).
Recommended add-ons
- Matched mRNA/long-RNA-seq for robust TE.
- Custom genomes/annotations for non-model organisms.
- Extended biostatistics and figure polishing.
Sample Requirements
| Sample Type | Minimum Input | Preferred / Notes |
|---|---|---|
| Cells | ≥ 4 × 10^7 cells | Low-input by review: ≥ 1 × 10^7 |
| Tissue (animal/plant) | ≥ 400 mg | ~3 g preferred; low-input by review: ≥ 50 mg |
| Bacteria | ≥ 4 × 10^7 cells | — |
| Purified RPFs | ≥ 200 ng/µL, ≥ 10 µL total | Purified ribosome-protected fragments |
Applications & Use Cases — Outcomes You Can Expect
Use Ribo-seq when RNA levels are not enough. Our ribo-seq service and ribo-seq analysis pipeline turn footprints into decisions—fast, auditable, and ready for action.
Drug mechanism of action
- Pinpoint translation-level responses to treatment using ribo-seq data analysis.
- Readouts: TE shifts, initiation changes, pausing hotspots, pathway impact.
Target validation & biomarkers
- Link TE changes to protein output for prioritisation.
- Readouts: ranked TE tables, uORF/sORF evidence, GO/KEGG summaries.
Resistance and off-target assessment
- Detect translation rewiring under stress or chronic dosing.
- Readouts: differential translation, stall maps, codon-usage patterns.
Immune research
- Quantify how RNA modifications shift regulator TE and clonal expansion.
- Readouts: start/stop P-site metagene, regulator-focused TE panels.
Virology
- Measure frameshifting and pausing in viral polyproteins at codon resolution.
- Readouts: ORF-level occupancy, frameshift locus coverage, TE differentials.
Plant and agriculture
- Resolve uORF-mediated gating under stress and discover robust markers.
- Readouts: uORF call-lists, TE contrasts across treatments or genotypes.
Sequencing quality distribution
A/T/G/C Distribution
Correlation Analysis Between Samples
Statistics Results of GO Annotation
KEGG Classification
P-site Analysis
Differential Translation Efficiency (TE) 一Gene Distribution
Quick Answers for Researchers
1. What does Ribo-seq measure vs RNA-seq?
Ribosome Profiling (Ribo-seq) sequences ~28–30 nt ribosome-protected fragments to quantify active translation and translation efficiency (TE). RNA-seq measures transcript abundance; use both to separate transcription from translation.
2. What is an ORF, and what can Ribo-seq detect?
An open reading frame (ORF) runs from a start codon (often AUG) to a stop codon (UAA/UAG/UGA). Ribo-seq can reveal ORFs in mRNA and detect translation from lncRNA or circRNA loci (uORFs/sORFs included).
3. What is the protocol for ribosome profiling?
Stabilise ribosomes on mRNA → lyse and apply RNase to remove unprotected RNA → enrich RPFs (e.g., sucrose gradient or PAGE) → build libraries and sequence → run the ribo-seq analysis pipeline (alignment, P-site assignment, 3-nt periodicity QC, TE/differential translation, uORF/sORF, pathways).
4. What will I receive from the ribo-seq service?
FASTQ (BAM on request), QC (3-nt periodicity, P-site metagene, mapping), analysis tables/figures (TE, differential translation, uORF/sORF, stalling, GO/KEGG), and a concise report.
5. Do I need matched RNA-seq for TE?
Recommended. Matched RNA-seq enables robust TE estimation and clarifies whether changes are transcriptional or translational.
6. What proves library quality in ribo-seq analysis?
Clear 3-nt periodicity, correct P-site offsets, expected RPF length distribution, good mapping rates, and strong replicate correlation.
7. What are the main limitations of Ribo-seq?
Residual rRNA can reduce usable reads; footprints are short, complicating ORF calling; TE infers protein output rather than measuring it directly; typical protocols require substantial input material.
8. What inputs and species are supported?
Cells, tissues, bacteria, or purified RPFs. Human/mouse/rat by default; others on feasibility review. See Sample Requirements for minimum inputs.
9. Can you run analysis-only or custom pipelines?
Yes. We accept purified RPFs or raw data and run a transparent, modular ribo-seq analysis pipeline tailored to your study.
Customer Publication Highlight
Ribo-seq Reveals Translation Efficiency Shifts Under Pol III/tRNA Disruption
Journal: PLOS Biology (2024).
Authors: Yasir Malik; Yavuz Kulaberoglu; Shajahan Anver; et al.
1) Background
tRNAs are core to decoding mRNA during translation. The authors asked whether partially lowering RNA polymerase III (Pol III)—which makes tRNAs—reshapes translation and organismal health across species (worms, flies, mice). They report conserved tRNA disruption and improved proteostatic resilience, with benefits to late-life health and lifespan.
2) Methods
- Design: Reduce Pol III function genetically or by RNAi across model organisms; assess translation and stress resilience.
- Ribo-seq & RNA-seq (Drosophila): Sample prep and sequencing performed by CD Genomics; RNase I digestion; NEBNext small-RNA library kit; Illumina HiSeq X10. Analysis used FastQC, Cutadapt, RiboToolkit, Salmon, and DESeq2 to compute differential translation and translation efficiency (TE). Data deposited to GEO (GSE232724).
3) Results
- Genome-wide coverage: Ribo-seq footprints mapped to >19,000 ORFs in flies, despite expected rRNA carryover typical for Drosophila.
- TE remodeling: Integrating Ribo-seq with RNA-seq identified >400 mRNAs with altered TE in Pol III mutants vs wild type at 10% FDR.
- Mechanistic link: Modeling predicted codon-specific decoding changes from shifted tRNA pools; experimental assays confirmed translation changes and increased proteostatic resilience across species.
4) Conclusions
Ribo-seq revealed system-level reprogramming of translation when tRNA biogenesis is perturbed. Combining Ribo-seq with RNA-seq enabled TE-based mechanism readouts that connected molecular decoding to organism-level resilience and longevity, illustrating how Ribosome Profiling supports mechanism-of-action studies.
Predicted and observed changes in translation upon partial inhibition of Pol III across worms, flies, and mice.
Here are some publications that have been successfully published using our services or other related services:
Disruption of tRNA biogenesis enhances proteostatic resilience, improves later-life health, and promotes longevity
Journal: Plos Biology
Year: 2024
Circular DNA tumor viruses make circular RNAs
Journal: Proceedings of the National Academy of Sciences
Year: 2018
Repeated immunization with ATRA-containing liposomal adjuvant transdifferentiates Th17 cells to a Tr1-like phenotype
Journal: Journal of Autoimmunity
Year: 2024
Role of the histone variant H2A.Z.1 in memory, transcription, and alternative splicing is mediated by lysine modification
Journal: Neuropsychopharmacology
Year: 2024
FAK loss reduces BRAFV600E-induced ERK phosphorylation to promote intestinal stemness and cecal tumor formation
Journal: Elife
Year: 2023
Identification of circular RNAs regulating cardiomyocyte proliferation in neonatal pig hearts
Journal: JCI insight
Year: 2024
See more articles published by our clients.
