CLIP Sequencing

Crosslinking-immunprecipitation and high-throughput sequencing (CLIP-seq) is a next generation sequencing (NGS)-based method to comprehensively study the situation of intracellular RNA and its binding protein, with the ability to provide a genome-wide map of protein-RNA interactions. We provide one-stop CLIP-seq service to help customers discover new RNA-protein interaction sites and explore more gene regulation functions.

Overview

RNA binding protein (RBP) is one key protein that regulates gene expression at the post-transcriptional level and play an important role in post-transcriptional regulation. RBP usually binds to the transcribed RNA to form ribonucleoprotein complexes. The complex can regulate RNA biogenesis, stability, cellular localization and transport, and determine the fate and function of RNA molecules. Therefore, a high-resolution and accurate protein-RNA interaction map is essential for deciphering posttranscriptional regulation under various biological processes. CLIP is an antibody-based technology for studying RNA-protein interactions related to RNA immunoprecipitation. We provide comprehensive CLIP-seq to describe the interaction between RNA molecules and RNA binding proteins in vivo. Based on the coupling of RNA molecules and RNA-binding proteins under ultraviolet irradiation, the technology uses specific antibodies of RNA-binding proteins to precipitate RNA-protein complexes, and recover RNA fragments for high-throughput sequencing, revealing in-depth the regulatory effects of RNA-binding proteins and RNA molecules and their significance to life. CLIP-seq can provide a genome-wide map of protein-RNA interactions and has been increasingly used to decipher protein complex-mediated post-transcriptional regulation. Meantime, the method can reveal the function of RNA in some important biological processes, and is a revolutionary technology that reveals the interaction between RNA molecules and RNA binding proteins at the whole genome level.

Features

High Sensitivity High Coverage Wide Application One-stop Service
Each sample can get millions of sequence tags and find rare protein binding sites on the transcriptome. Screen and identify protein binding sites across entire transcriptome. Suitable for research on splicing factor RNA binding profiles, miRNA targets, etc. Provides one-stop service for library construction, sequencing, sample QC and data analysis.

Project Workflow

Sample Preparation

1. Sample Preparation

RNA purification; quality assessment and quantification.

Library Preparation

2. Library Preparation

RNA fragmentation; cDNA library preparation.

Sequencing

3. Sequencing

Illumina HiSeq; PE 50/75/100/150.

Data Analysis

4. Data Analysis

Visualize and preprocess results, and perform custom bioinformatics analysis.

Bioinformatics Analysis Pipeline

CLIP Sequencing

In-depth data analysis:

  • Sequencing quality distribution
  • Peak calling and visualization
  • Peaks width and distance analysis
  • Identify potential miRNA target(s)
  • Distribution analysis of peak.
  • Analyze microRNA-mRNA interactions
  • Identification of protein binding site
  • Differential binding analysis
  • Motif search of enrichment sites
  • GO and KEGG pathway analysis

Sample Requirements

RNA sample quantity ≥ 50 ug.

Please make sure that the RNA is not significantly degraded.

Sample storage: RNA can be dissolved in ethanol or RNA-free ultra-pure water and stored at -80°C. RNA should avoid repeated freezing and thawing.

Shipping Method: When shipping RNA samples, the RNA sample is stored in a 1.5 mL Eppendorf tube, sealed with sealing film. Shipments are generally recommended to contain 5-10 pounds of dry ice per 24 hours.

Deliverable: FastQ, BAM, coverage summary, QC report, custom bioinformatics analysis.

References:

  1. Liu Q, Zhong X, Madison B B, et al. Assessing Computational Steps for CLIP-Seq Data Analysis. Biomed Res Int, 2015:196-202.
  2. Wang T, Chen B, Kim M, et al. A model-based approach to identify binding sites in CLIP-Seq data. PLoS One, 2014, 9(4): e93248.
  3. Uhl M, Houwaart T, Corrado G, et al. Computational analysis of CLIP-seq data. Methods, 2017,118: 60-72.
  4. Zhang Z, Xing Y. CLIP-seq analysis of multi-mapped reads discovers novel functional RNA regulatory sites in the human transcriptome. Nucleic Acids Res, 2017, 45(16): 9260-9271.
* For Research Use Only. Not for use in diagnostic procedures.


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