Long non-coding RNA Sequencing (lncRNA-seq)

Overview Features Workflow & Analysis Pipeline Sample Requirements Cases & FAQ Resources Inquiry

CD Genomics provides highly sensitive strand-specific lncRNA-seq service for lncRNA profiling and quantification, novel lncRNA identification and annotation, revealing lncRNA functions and biology and providing vital insights into disease mechanisms and cell biology. Please contact our expert team to discuss how our lncRNA-seq service can refine your NGS projects.

Overview

Long non-coding RNAs (lncRNAs) are a large class of RNA molecules exceeding 200 nucleotides in length that do not encode proteins. lncRNAs encompass nearly 30,000 different transcripts in humans, hence lncRNA transcripts account for the major part of the non-coding transcriptome. lncRNAs take part in a variety of biological processes such as organization of nuclear domains and regulation of transcription, and have been implicated in several diseases. However, compared with mRNAs, most lncRNA are less well studied and their functions are largely unknown. With the development of next-generation sequencing (NGS) technologies, RNA-seq is emerging as the major transcriptome profiling method that has many advantages over traditional methods such as microarray in many aspects such as novel transcript and splice junction identification, as well as allele-specific expression analysis. lncRNA sequencing (lncRNA-seq) provides a genome-wide picture of lncRNAs in a given sample under specific conditions, revealing changes in the expression of lncRNAs, as well as lncRNA functions and biology. Strand-specific RNA-seq protocol that retains strand of origin information provides a greater resolution for sense/antisense profiling, which is necessary for the accurate identification of antisense lncRNAs.

Features

Flexibility Transcriptome-Wide High Quality Novel Transcripts
The flexibility to prepare libraries and analyze data according to your needs. Providing transcriptome-wide lncRNAs profiling in your sample. Generating high quality data with a guaranteed Q30≥ 80%. High-sensitive detection of novel and rare transcripts and transcript variants.

Project Workflow

Sample Preparation

1. Sample Preparation

RNA purification; quality assessment and quantification

Library Preparation

2. Library Preparation

Ribosomal RNA Removal
250~300 bp Insert cDNA Library

Next-generation Sequencing

3. Sequencing

Illumina Novaseq, PE 150
≥ 80 million read pair per sample

Advanced Data Analysis

4. Data Analysis

Visualize and preprocess results, and perform custom bioinformatics analysis.

lncRNA Seq

Bioinformatics Analysis Pipeline

In-depth data analysis:

  • Remove unqualified transcripts
  • Mapping to genome
  • Transcript assembly
  • Transcript expression profiling and differential expression
  • Novel lncRNAs prediction
  • Functional annotation
  • Target gene prediction

Sample Requirements

Total RNA sample (quantity ≥ 2 μg, concentration ≥ 50 ng/μL)

Exosomal RNA (quantity ≥ 5 ng), for more information about Exosome lncRNA-seq

Cells sample (quantity ≥ 2×106)

Tissue sample (quantity ≥ 500 mg)

RIN ≥ 7.0, with smooth baseline; OD260/280: 1.8-2.2; OD260/230: ≥ 1.8.

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: raw data as BAM files, coverage summary, QC report, custom bioinformatics analyses.

Case Studies

FAQ

References:

  1. Liu X, Ma Y, Yin K, et al. Long non-coding and coding RNA profiling using strand-specific RNA-seq in human hypertrophic cardiomyopathy. Scientific data, 2019, 6(1): 1-7.
  2. Zhu W, Tian L, Yue X, et al. LncRNA expression profiling of ischemic stroke during the transition from the acute to subacute stage. Frontiers in neurology, 2019, 10: 36.
  3. Elsayed, Ahmed K., Nehad M. Alajez, and Essam M. Abdelalim. "Genome-wide differential expression profiling of long non-coding RNAs in FOXA2 knockout iPSC-derived pancreatic cells." (2023).
* For Research Use Only. Not for use in diagnostic procedures.


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