circRNA-Protein Interaction Prediction

Circular RNAs (circRNAs) are covalently closed, endogenous non-coding RNAs without 5' end caps or 3' poly(A) tails. These RNAs are conserved across species and display tissue-specific, cell-specific, and developmental stage-specific expression patterns. CD Genomics provides next-generation sequencing (NGS) and mass spectrometry (MS) based approaches for identifying circRNA-protein interactions and reveal mechanisms underlying circRNA biology.

Overview

Recently, accompanied by advances in RNA sequencing (RNA-seq) technologies and bioinformatics tools, thousands of circRNAs in eukaryotes have been identified and various databases and computational approaches have been developed for circRNAs, such as circBase, CIRCpedia, CircR2Disease and CircInteractome. Previous studies have found that the regulatory functions of circRNAs largely rely on their interactions with microRNAs (miRNAs) and proteins, acting as miRNA sponges and RNA-binding-proteins (RBPs) sponges. RNA-protein interactions can influence protein expression and function, as well as regulate circRNA synthesis and degradation. CD Genomics provides integrative circRNA solutions including circRNA-miRNA interaction analysis, circRNA-protein interaction prediction and circRNA modification analysis.

We offer in vitro and in vivo experiments to detect circRNA-protein interactions. RNA pull-down and RNA immunoprecipitation (RIP) are the most commonly used methods and they can be coupled to MS or NGS for analyzing global circRNA-interactions in a high-throughput manner. RNA pull-down method uses designed anti-sense oligonucleotide probes specific to circRNAs to capture circRNA interactome. Back-spliced regions are circRNA-specific sequence elements that can be targeted to enrich circRNAs. RIP allows for effective mapping of circRNA binding proteins and circRNA modifications such as ac4C using high affinity antibody. We also provide in vivo detection of circRNA-protein interactions using ChIRP and CLIP. These assays are further coupled with NGS or MS to profile global cirRNA-protein interactions. Our services for circRNA-protein interaction prediction consist of CLIP-seq, RIP-seq, ChIRP-seq, ChIRP-MS and other custom assays. We are dedicated to offering accurate and reproducible data to support your circRNA research.

Features

Rich Experience Genome-Wide Integrative Solution Quality Control
Rich experience in circRNA experiments and bioinformatics analysis. Genome-wide identification of circRNA interactome such as miRNA, mRNA and protein. Integrative circRNA solution to reveal mechanisms underlying circRNA biology. Quality control is executed following every procedure.
circRNA-Protein Interaction Prediction

Data Analysis Workflow

In-depth data analysis:

  • Prediction of binding sequence signature(s)
  • Gene Ontology (GO) functional annotations
  • KEGG pathway analysis
  • Prediction of circRNA-protein interaction networks
  • Creation of circRNA–miRNA–mRNA network
  • Measure the effect of circRNA on global protein levels

Sample Requirements

(NGS platform) RNA sample (concentration ≥ 200 ng/uL, quantity ≥ 4 ug), 1.8 ≤ OD260/280 ≤ 2.2, OD260/230 ≥ 2.0, RIN ≥ 6.5, 28S:18S ≥ 1.0. Please make sure that RNA is not significantly degraded.
(MS platform) We work with a wide range of sample types including protein solution, fresh tissue, cultured cells, blood, and microbial sample. Please feel free to contact us for sample size.

Sample storage: The sample should be stored at -80°C. Avoid repeated freezing and thawing.

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

Deliverable:
(NGS analysis) FastQ, BAM, coverage summary, QC report, GO enrichment histogram, GO terms DAG (directed acyclic hierarchical graph), and KEGG enrichment scatter plot, and other designated report.
(MS analysis) Data QC report, MS results, integrated experimental report (materials, methodologies, and bioinformatics analysis).

References:

  1. Huang A, Zheng H, Wu Z, et al. Circular RNA-protein interactions: functions, mechanisms, and identification. Theranostics, 2020, 10(8): 3503.
  2. Zhang K, Pan X, Yang Y, et al. Predicting circRNA-RBP interaction sites using a codon-based encoding and hybrid deep neural networks. bioRxiv, 2018: 499012.
* For Research Use Only. Not for use in diagnostic procedures.


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