Poly(A) RNA-Seq

Poly(A) RNA sequencing (RNA-seq) is a next-generation sequencing-based method to comprehensively analyze RNAs with poly(A) tails such as message RNAs (mRNAs) and long non-coding RNAs (lncRNAs). This technique accurately reveals the level of gene expression in your biological sample under specific conditions and generates a complete picture of the transcriptome for the identification of novel alternative splicing, transcripts, gene fusion events, etc.

Overview

After RNA is transcribed, lncRNAs and mRNAs are subjected to many post-transcriptional modifications. The 3′ end of most lncRNAs and mRNAs is cleaved co-transcriptionally with poly(A) tails added by poly(A) polymerases. It has been known that poly(A) tails are one of the critical factors regulating translational efficiency and RNA stability. Poly(A) selection has been used to enrich for poly(A) RNA molecules and the method has proved essential for the construction of cDNA libraries and useful for analysis of low-abundance poly(A) RNAs. The benefit of this approach is that the prepared libraries and data predominantly relate to protein coding transcripts, which is ideal for comparative gene expression analysis and makes full use of the capacity of each sequencing lane by targeting the full length, mature poly-A transcripts alone.

Poly(A) RNA-seq using the latest next-generation sequencing technology can generate poly(A) RNAs profiles including lncRNAs and mRNAs and reveal the complexity of the transcriptome, identifying genes as well as transcript structures, alternative splicing, RNA editing, polyA-tailed non-coding RNAs, and new transcripts. Poly(A)-seq is a common method for expression profiling and transcript quantification in a sample under specific conditions. Researchers can cheaply and quickly identify novel transcripts and estimate the gene abundances, by directing sequencing to only the 3′ end of poly-adenylated RNA transcripts, such as many RNA viruses and eukaryotic mRNAs.

Features

Any Species Transcriptome-Wide Bioinformatics Analysis One-Stop Solution
This method can be applied to any species, from microorganisms to humans. Profile all poly-A transcripts, either known or unknown, in your biological sample. Our integrated bioinformatics pipeline can be tailored to suit your project. One-stop solution from sample QC, library construction, to sequencing and data analysis.

Project Workflow

Sample Preparation

1. Sample Preparation

Quality assessment and quantification

Library Preparation

2. Library Preparation

Poly(A) tail RNA selection; PE100/PE125/PE150

Sequencing

3. Sequencing

150 bp PE; >6G clean data

Data Analysis

4. Data Analysis

Visualize and preprocess results; perform custom bioinformatics analysis

Bioinformatics Analysis Pipeline

Bioinformatics Analysis Pipeline

In-depth data analysis:

  • Alignment, classification, and functional annotation of all the mapped reads
  • Statistical analysis – sequencing error rate distribution, length distribution, multi-parameter data analysis, expression analysis, comparisons of transcript copy number, etc.
  • Differential expression analysis of transcripts/genes
  • GO annotation
  • KEGG analysis
  • Detection and annotation of Indels/SNPs

Sample Requirements

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. Bonfert T, Friedel C C. Prediction of Poly(A) Sites by Poly(A) Read Mapping. PLoS One, 2017, 12(1): e0170914.
  2. Krause M, Niazi A M., Labun K, et al. tailfindr: alignment-free poly(A) length measurement for Oxford Nanopore RNA and DNA sequencing. RNA, 2019, 25(10): 1229–1241.
* For Research Use Only. Not for use in diagnostic procedures.


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