Reference-Based Transcriptome Sequencing

CD Genomics, a biotechnology company with many years of experience in genomics and sequencing, provides reference-based transcriptome sequencing and analysis solutions for eukaryotes or their tissues and cells. By comparing with the reference genome, we can not only quantify the changes in transcript expression levels, but also provide an in-depth analysis of gene structure and reveal important transcriptional information. Our services are widely used in basic and biomedicine research, drug discovery and molecular breeding.

Overview

RNA-seq is considered the most powerful, robust and adaptable technique for measuring gene expression and transcriptional activation at the genome-wide level. Reference-based (RB) transcriptome analysis methods are based on comparing sequenced reads to an existing reference genome and then assembling the overlapping comparisons into transcripts. As high-quality genomes of various organisms are assembled, the genome-guided transcriptome assembly approach can map and quantify transcriptomes and determine the structure in the transcriptional landscape in a more accurate and comprehensive manner.

CD Genomics RB transcriptome sequencing service, based on Illumina and long read sequencing platforms (Pacbio SMRT and Nanopore sequencing) is capable of detecting the overall transcript level of any species at the single nucleotide level. Customized bioinformatics analysis can yield changes in gene expression levels under different growth and development or stress conditions, and in turn can analyze gene structure, alternative splicing and SNPs to reveal the molecular mechanisms involved in specific biological processes. In addition to basic research, we also focus on model organisms such as human samples and mice to advance biomedical research, and can provide advanced transcriptomics customization services to reveal disease pathogenesis, discover biomarkers, identify disease therapeutic targets, etc. according to customer needs.

Features

Any Species Transcriptome-Wide Bioinformatics Analysis One-Stop Solution
This method can be applied to any species, Including fungi, animals, plants and humans. Profile all lncRNAs, circRNAs, mRNAs, and small RNAs, either known or unknown. 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; ribosomal RNA depletion and fragmentation

Library Preparation

2. Library Preparation

Size fractionation selection; 18~40bp insert cDNA Library; 250~300bp insert cDNA Library.

Sequencing

3. Sequencing

HiSeq X10/4000; PE50/75/100/150; >10G clean data

Data Analysis

4. Data Analysis

Visualize and preprocess results, and perform custom bioinformatics analysis.

Bioinformatics Analysis Pipeline

Reference-Based Transcriptome Sequencing

In-depth data analysis:

  • Mapping on the reference genome
  • Gene fusion detection
  • Differential expression analysis
  • Pathway analysis
  • SNV & InDel detection
  • Splicing analysis
  • Prediction of novel miRNAs, lncRNAs, circRNAs and small RNAs
  • Discovery of novel transcripts and mutations

Sample Requirements

RNA sample (concentration ≥ 200 ng/uL, quantity ≥ 2 ug)

1.8 ≤ OD260/280 ≤ 2.2, OD260/230≥2.0, RIN ≥ 6.5, 28S:18S≥1.0, 25S:18S≥1.0, 23S:18S≥1.0.

Please make sure that the RNA is not 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 a 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.

Reference:

  1. Kovi MR, Amdahl H, Alsheikh M, et al. De novo and reference transcriptome assembly of transcripts expressed during flowering provide insight into seed setting in tetraploid red clover. Scientific reports, 2017, 7(1): 1-11.
* For Research Use Only. Not for use in diagnostic procedures.


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