Inquiry
Tell Us About Your Project

We are dedicated to providing outstanding customer service and being reachable at all times.

Request a Quote

SMRT-Based Transcriptomics Analysis

Inquiry      >
Overview

CD Genomics has the capability to assist you with the most challenging transcriptomics sequencing projects. Using our single molecular real-time (SMRT)-based transcriptomics analysis, we can easily obtain full-length cDNA sequences covering complete transcripts from the 5′ end to the 3′ poly-A tail by using PacBio SMRT sequencing without the need of fragmentation. This analysis is useful to identify novel transcript isoforms, fusion gene expression, and alternative splicing events, and also improve genome annotation.

Our Advantages:
  • Strict quality control following each procedure to ensure accurate and reproducible results.
  • Discover novel genes, transcripts, and alternative splicing events.
  • Identify gene structure, coding regions, and regulatory elements.
  • Longest average read lengths and highest consensus accuracy.
Tell Us About Your Project

We are dedicated to providing outstanding customer service and being reachable at all times.

Request a Quote

Introduction to Our SMRT-based Transcriptomics Platform

Transcriptomics enables genome-wide analysis of transcription at single-nucleotide resolution, including determination of the relative abundance of transcripts, unbiased identification of alternative splicing events and post-transcriptional RNA editing events, and detection of single nucleotide polymorphisms (SNPs). While analyzing co-post-transcriptional processing events is difficult with the short-read sequencing, SMRT isoform sequencing (Iso-Seq) is a long-read sequencing strategy that can span the full-length of transcripts. It is able to sequence the full-length isoforms without the need for assembly.

Our SMRT-based transcriptomics platform represents an easy and accurate way for various applications, like gene annotation, identification of transcript isoforms and fusion transcripts, long non-coding RNA (lncRNA) discovery, microRNA (miRNA) discovery, and prediction of potential mRNA target molecules. It also helps improve genome annotation by identifying gene structures, coding regions, and regulatory elements. Additionally, we also provide Nanopore-based microbial epigenomics service. Our SMRT-based transcriptomics can be used to address a variety of research questions, like early embryo development, phylogenetic inference, cellular differentiation, biomarker discovery, identification of drug targets, etc.

SMRT-based transcriptomics workflow

Bioinformatics Analysis

Our bioinformatics analysis includes four parts: data QC, transcriptome annotation, gene structure analysis, gene expression analysis, and custom analysis. We are flexible to your needs.

Pipeline Details
Data QC Correction, classification, reduced redundancy, etc.
Transcriptome annotation Gene ontology, KEGG pathway, KOG or COG, Swissport, etc.
Gene structure analysis Prediction of alternative splicing events, LncRNAs, miRNAs, SSR, and CDS, novel transcript discovery, identification of fusion genes, etc.
Gene expression analysis Gene expression level analysis, differential expression gene analysis, etc.
Custom analysis We provide custom data analysis according to your needs.

Sample Requirement

    1. RNA amount: Total RNA ≥ 5 ug
    2. RNA purity: 1.8 < OD260/280 < 2.2; OD260/230 ≥ 1.5 (without RNA degradation or DNA contamination)
    3. RNA quality: 28S:18S ≥ 1.5, RIN ≥ 7

Sampling kits: We provide a range of microbial sampling kits for clients, including MicroCollect™ oral sample microbial collection products and MicroCollect™ stool sample collection products.

Deliverables: Raw data files in BAM format, demultiplex CCS reads in FASTQ format, quality-control dashboard, statistic data, and your designated bioinformatics analysis report.

References

  1. JT Bjerrum, et al. Integration of transcriptomics and metabonomics: improving diagnostics, biomarker identification and phenotyping in ulcerative colitis. Metabolomics, 2014; 10(2): 280–290.
  2. R Lowe, et al. Transcriptomics technologies. PLoS Comput Biol, 2017; 13(5): e1005457.
  3. Jure Tica, et al. Combined Transcriptomics, Proteomics and Bioinformatics Identify Drug Targets in Spinal Cord Injury. Int J Mol Sci. 2018; 19(5): 1461.
* For Research Use Only. Not for use in diagnostic procedures or other clinical purposes.



Solutions
Featured Resources
Copyright © 2024 CD Genomics. All rights reserved. Terms of Use | Privacy Notice