Capture direct RBP–RNA interactions with HITS-CLIP—label-free, UV-based, and CLIP-aware. Powered by Creative Proteomics, built for confident binding site discovery.
High-Throughput Sequencing of RNA isolated by UV-Crosslinking and ImmunoPrecipitation (HITS-CLIP) captures direct RBP–RNA contacts in living cells or tissues. UV at 254 nm creates covalent bonds at protein–RNA contact points. Following partial RNase digestion and stringent immunoprecipitation, protected RNA fragments are ligated to adapters, reverse-transcribed, amplified, and sequenced. Crosslink scars in cDNA—classically small deletions—help localize binding sites when integrated with CLIP-aware peak models, replicate consistency, and matched controls.
Use HITS-CLIP when you need:
Deletion-Based Crosslink Site Mapping — Covalent UV-C Induced Contact Scars
Detects characteristic crosslink-induced deletions in cDNA, enabling base-level localization of direct RNA–protein contact sites with high specificity.
Tissue-Compatible — No Nucleoside Incorporation Required
Applies to primary tissues, in-vivo samples, and non-dividing cells without needing 4SU/6SG incorporation, broadening experimental applicability.
Replicate Concordance Scoring — IDR-Style Confidence Filtering
Integrates biological replicates using irreproducible discovery rate (IDR) or similar statistical frameworks to retain only high-confidence, condition-consistent peaks.
Control-Driven Signal Discrimination — IgG & No-UV Baselines
Uses multiple negative controls to subtract background noise, distinguish true RBP targets, and prioritize biologically relevant binding events.
Motif Discovery & Positional Enrichment — Sequence-Level Context Analysis
Identifies overrepresented motifs and their positioning relative to peak centers, enabling regulatory insight and validation of RBP binding logic.
Flexible Crosslinking Conditions — Optimized UV Exposure per Matrix
Utilizes calibrated UV-C energy dosed per sample type to maximize covalent adduct formation while preserving RNA integrity.
Multi-Condition Comparison — Differential Binding with Replicate Weighting
Supports condition-dependent analysis to reveal dynamic shifts in RBP binding across treatments, genotypes, or time points.
Identify high-confidence RBP–RNA interaction sites across coding and non-coding regions, annotated by transcript feature (e.g., 5'-UTR, CDS, 3'-UTR, intron) and prioritized by enrichment, motif presence, and crosslink evidence.
Profile binding shifts in response to perturbations (e.g., knockout, overexpression, drug treatment, stress induction), using matched replicate design and statistical control to highlight reproducible differential sites.
For RBPs with limited CLIP precedent, we offer pilot-scale validation of antibody performance, RNase titration curves, and IP stringency refinement to ensure signal specificity before full-scale execution.
Clients with internal crosslinking and IP capabilities may submit pre-enriched RNP complexes or immunoprecipitated RNA for downstream library construction, size QC, and Illumina sequencing.
From exploratory screens to publication-ready datasets, we tailor QC metrics, peak stringency, and annotation complexity to fit the intended application—whether hypothesis generation or functional validation.
For clients running multiple CLIP variants (e.g., PAR-CLIP, eCLIP, iCLIP), we can coordinate study design and deliverables to ensure consistent data structures and comparable output formats.
Consultation & Study Blueprint
Define hypotheses, contrasts, antibody options, replicates, controls, and analysis outputs.
Sample Receipt & UV Crosslinking
Controlled UV-C exposure of cells or tissues to create covalent RBP–RNA adducts.
Lysis, RNase Titration & Immunoprecipitation
Partial digestion to yield characteristic footprints; stringent IP enriches bona fide complexes.
On-Bead Processing & Library Prep
Adapter ligation, reverse transcription, and amplification with cycle monitoring; UMI optional.
Sequencing
Read length and depth tailored to footprint size, complexity, and comparison groups.
CLIP-Aware Data Analysis
Adapter/quality trimming → alignment → duplicate handling → peak calling with crosslink diagnostics → replicate concordance (e.g., IDR concepts) → annotation, motif, enrichment, and target ranking.
UV-C Crosslinker (254nm)
Programmable energy dose (150–250mJ/cm2) with chilled irradiation chamber to minimize RNA degradation. Optimized per sample type.
RNase Titration System
Fine-tuned enzymatic digestion to generate 25–80nt RNA footprints, balancing resolution and recovery.
Magnetic Bead IP System
High-stringency immunoprecipitation with validated antibody or tag-based pull-down. Low-retention tubes and cold-room handling ensure clean capture.
Library Preparation Modules
Low-input compatible ligation system with dimer suppression and optional UMI barcoding. Insert sizes typically range from 120–220bp.
Illumina Sequencing Platforms
NovaSeq & NextSeq available. Standard configurations: PE75 / PE100 / PE150. Depth per sample: 10–50 million reads.
| Feature | Typical Range |
| UV Dose | 150–250mJ/cm2 |
| Footprint Size | 25–80nt |
| Library Insert Size | 120–220bp |
| Read Length | SE75 / PE75–150 |
| Throughput per Sample | 10M–50M reads |
| UMI Support | Optional (8–12nt) |
| Item | Accepted Types | Recommended Amount | Minimum Acceptable | Notes / Controls |
| Cultured Cells | Adherent or suspension cell lines (mammalian/model) | 5–20 × 106 cells | 3–5 × 106 cells | For low-abundance RBPs or weak antibodies, plan 20–50 × 106. |
| Primary Tissue (Fresh/Snap-Frozen) | Human/mouse/rat, unfixed | 50–200 mg | ≥30 mg | Sample adjacent regions from the same condition; avoid necrotic zones. |
| Sorted / Rare Cells | FACS-enriched cells | 0.5–2 × 106 cells | ≥0.3 × 106 cells | Use low-input route; consider alternate CLIP if below minimum. |
| Subcellular Fractions (Optional) | Nuclear or cytosolic extracts | As above | As above | Helpful for nuclear RBPs; share fractionation method. |
| Antibody | IP-grade primary or tag-based | 5–10 μg per IP | — | Provide vendor/lot and any prior IP/CLIP evidence, if available. |
| Controls | IgG, Input, No-UV (as needed) | Project-defined | — | Chosen to match the study question; finalized at design stage. |
| Storage & Shipping | Cell pellets / tissue on dry ice | — | — | Avoid thaw cycles; use low-retention tubes; label groups clearly. |
| Not Accepted | FFPE or chemically fixed samples | — | — | Crosslinking is incompatible; supply fresh or snap-frozen material. |
Crosslink-Induced Deletion Signature Plot
Genome Browser View with Input / IgG Overlays
Motif Logo + Positional Enrichment Plot
Binding Region Distribution Barplot
| Method | HITS-CLIP | PAR-CLIP | iCLIP / eCLIP | RIP-seq |
| Crosslinking | UV-C 254 nm | UV-A 365 nm + 4SU/6SG metabolic labeling | UV-C 254 nm (enhanced protocols and recovery) | None (native IP) or mild crosslinking |
| Diagnostic Signature | Crosslink-induced deletions in cDNA | T→C transitions at crosslink sites | Truncation/start-site signatures; improved site precision | No nucleotide-level signature |
| Nominal Resolution | Near-nucleotide (deletion-enriched peaks) | Single-nucleotide (T→C) in labeling-competent systems | Single-nucleotide, highest site precision among CLIP variants | Region-level (enrichment only) |
| Sample Compatibility | Cells & snap-frozen tissues; no labeling required | Requires nucleoside labeling (best in cultured cells) | Cells & some tissues; more steps but broadly applicable | Broad (cells/tissues); simplest logistics |
| When It Excels | In-tissue mapping; projects where labeling is impractical | Precise site calling with strong T→C signal; high S/N in cell culture | Projects demanding maximal site precision & recovery | Rapid target discovery; screening & QC confirmation |
| Key Limitations | Deletion signal weaker than T→C; optimization needed | Labeling may alter biology; not feasible in many tissues/in vivo | More complex workflows; higher input/QC burden | Lower specificity; higher background without crosslinking |
| Typical Inputs | Moderate; tunable by RNase titration | Moderate; labeling competency required | Moderate–High; replicate-heavy designs common | Low–Moderate |
| Controls Required | IgG, input, ± no-UV | IgG, input; unlabeled controls | IgG, input, ± no-UV | IgG, input |
| Signature-Aware Peak Calling | Yes (deletion-aware models) | Yes (T→C transition models) | Yes (truncation/start-site aware) | No (enrichment-only peaks) |
| Best For | Tissue studies; broad applicability without labeling | Cell-based systems needing crisp single-nucleotide calls | High-precision mapping; publication-grade site catalogs | Hypothesis generation; antibody QC; quick target lists |
| Caveats to Plan For | UV dose/footprint tuning; antibody quality | 4SU/6SG uptake, phototoxicity, metabolic effects | Library complexity & duplication; stringent QC | Interpret with caution—binding ≠ direct contact |
Quick guidance:
How do you separate true binding from background while controlling false positives?
Matched controls (IgG/Input/±No-UV) plus peak-level FDR and replicate concordance (IDR-style). Crosslink-signature support is weighted but not mandatory.
People also ask: Which reference is best for CLIP—genome or transcriptome?
Genome for coordinate consistency; transcriptome views for UTR/CDS context. We report both.
How do you normalize across samples and handle contaminants?
Library-size/composition scaling with control-based offsets; rRNA/mtRNA fractions are quantified and excluded from denominator metrics.
How do you control batch effects in condition comparisons?
Replicate-aware GLMs with explicit batch covariates; contrasts reported with effect sizes and FDR.
How are multi-mapping reads and repeats treated?
MAPQ- and mappability-aware filtering; blacklist/flag peaks dominated by low-mappability loci.
People also ask: How many reads are enough for CLIP analysis?
Sufficiency is judged by within-project peak saturation curves and summit stability, not a fixed read threshold.
How do you rank targets for follow-up experiments?
Composite score combining enrichment over controls, replicate stability, deletion support, regional priors (e.g., 3'UTR), and functional annotation.
How do you avoid motif circularity (discover-then-select bias)?
Stratified backgrounds and hold-out validation; we report independent enrichment and positional bias.
What metrics define a high-quality HITS-CLIP dataset?
Low adapter-dimer and duplication, high unique-map rate, clear control separation, stable peak counts across replicates, and biology-consistent motif/region patterns.
Do you support non-model organisms?
Yes, with an available reference genome/transcriptome; version-pinned references/annotations can be used.
What are the interpretation limits of binding-only evidence?
Binding ≠ function. We provide evidence grading and recommend integrating RNA-seq/Ribo-seq to prioritize candidates.
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