lncRNA-RNA Interaction Prediction

lncRNAs represent a large class of non-protein coding RNA molecules longer than 200 nucleotides. They can regulate gene expression through RNA-RNA interactions, however, which is one of the least studied aspects of lncRNA biology. CD Genomics provides sample-to-data RNA-seq, ChIRP-seq and ChIRP-MS services for identifying RNA targets of lncRNAs and determining the functions and action mechanisms of lncRNAs.

Overview

Long non-coding RNAs (lncRNAs) play many vital roles in multiple biological processes, but we have little knowledge about the function of the majority of lncRNAs. Every lncRNA mechanism involves lncRNA-RNA interaction and/or lncRNA-protein interaction. So one approach for modeling lncRNA mechanisms is to identify their interaction target. Recent studies have found that lncRNA-mRNA interactions can regulate biological processes, demonstrating that lncRNA-RNA interaction prediction is helpful for estimating the function of a lncRNA. Besides, the interaction of microRNA (miRNA) and lncRNA has been identified to be important for gene regulations. However, the number of known lncRNA-miRNA interactions is still very limited. Several experimental protocols, databases, web servers and computational tools have been developed for prediction of lncRNA functions based on lncRNA-mRNA interactions or in silico screening.

CD Genomics has strong expertise and rich experience in comprehensively predicting lncRNA-RNA interactions, including lncRNA-mRNA interactions, lncRNA-miRNA interactions and integrated analysis of mRNA-lncRNA-miRNA (MLMI) network. We provide whole transcriptome sequencing, ChIRP-MS and ChIRP-seq to comprehensively identify potential lncRNA-RNA interactions. ChIRP (Chromatin isolation by RNA purification) experiments can capture lncRNA-binding chromatin and transcripts, which can be identified by next-generation sequencing (NGS) or mass spectrometry (MS) in a high throughput and accurate manner. lncRNA-RNA interaction prediction can provide a detailed lncRNA-RNA interaction network and reveal lncRNA function.

Features

Sample-to-DataTranscriptome-WideValidated ProcessesQuality Control
Provide one-stop, sample-to-data service with flexibilityTranscriptome-wide identification of lncRNA targets including mRNAs and miRNAs Perform advanced and validated experiments on NGS and MS instruments Quality control is executed following every procedure

Data Analysis Workflow

Whole Transcriptome Sequencing

Data Analysis Workflow

ChIRP-MS / ChIRP-Seq

Data Analysis Workflow

In-depth data analysis:

  • Genomic distribution of mapped reads
  • Peak identification and motif analysis
  • In silico lncRNA-RNA interaction prediction
  • lncRNA target mRNA GO enrichment
  • KEGG target mRNA KEGG enrichment
  • Prediction of lncRNA-microRNA interactions (lncRNA-associated ceRNA network analysis)
  • MLMI network analysis

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. Terai G, Iwakiri J, Kameda T, et al. Comprehensive prediction of lncRNA–RNA interactions in human transcriptome. BMC genomics. BioMed Central, 2016, 17(1): 12.
  2. Fukunaga T, Iwakiri J, Ono Y, et al. LncRRIsearch: a web server for lncRNA-RNA interaction prediction integrated with tissue-specific expression and subcellular localization data. Frontiers in genetics, 2019, 10: 462.
* For Research Use Only. Not for use in diagnostic procedures.


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