Digital RNA-seq Analysis

CD Genomics as one of the providers of Digital RNA-seq Analysis, we use bioinformatics methods to help you accurately quantify gene expression quickly and accurately. If we are fortunate to cooperate, we will provide you with a high-quality data analysis platform, a fast analysis cycle and a high-quality result report.

Introduction of Digital RNA-seq

There are repeated reads in the process of conventional transcriptome sequencing, part of which is the natural repeats generated by fragmented RNA during library construction and needs to be retained. Others are caused by uneven PCR amplification and over-amplification by the sequencer during the sequencing process, and these repetitive sequences need to be removed. However, ordinary transcriptome technology cannot remove these duplications, resulting in inaccurate gene expression quantification, which may lead to inconsistencies between the gene expression level of the sequencing data and the experimental results. Digital RNA-seq is also called UMI RNA-seq to avoid this situation to the greatest extent. Digital RNA-seq uses specific molecular tags (UMI) to label each fragment before library amplification, combined with high-throughput sequencing, So as to accurately quantify the expression of genes.

When analyzing sequencing data using bioinformatics methods, repetitive fragments with the same digital tag are combined to remove the repetition caused by PCR amplification and sequencer, retain natural molecular repetition, and restore the real reads composition. By comparing with the database, small RNA sequence identification, target gene analysis and functional analysis can be realized, as well as the analysis and research needs of various small RNA types including miRNA, siRNA, piRNA, etc.

Fig 1. Scheme of digital RNA-Seq. (Katsuyuki S, et al. 2012)

Application of Digital RNA-seq Analysis

In terms of animal and plant research, it is mainly used in the study of animal and plant growth and development regulation, disease resistance and stress regulation, biological traits and mutation regulation.

In terms of disease research, it can study the regulation mechanism of disease occurrence, search for biomarkers, and research on targeted drugs.

Advantages of Digital RNA-seq

By adding UMI to remove duplication, the duplication introduced during PCR or sequencing can be eliminated, making sequencing results more accurate, and this effect is more significant for low-to-medium expression genes.

Digital RNA-seq can correct basic errors and accurately analyze RNA editing and SNP detection.

Digital RNA-seq can easily distinguish between natural duplication and amplified duplication, and accurately identify alternative splicing events.

CD Genomics Analysis Pipeline

Fig 2. Pipeline of digital RNA-seq analysis.

Bioinformatics Analysis Content

For digital RNA-seq data analysis, if you have any other needs, such as small RNAs analysis (including miRNA, piRNA, siRNA), SNP and Indel analysis and son on. Please contact our technical support, we will provide you with a suitable data analysis program according to your requirements. For data analysis, if you have any needs, please click online inquiry.

How It Works

CD Genomics is a high-tech company specializing in multiomic data analysis. We provide services such as project design, data analysis, and database construction. With a focus on developing breakthrough products and services, we are a pioneer in the biotechnology industry, serving researchers and partners worldwide.

Bioinformatics-Analysis, a division of CD Genomics, staffed by highly experienced biological scientists in digital RNA-seq data analysis. For digital RNA-seq analysis, if you have any questions, please feel free to contact us and see how we can help you address your problems.

Reference

1. Katsuyuki S, et al. Digital RNA sequencing minimizes sequencedependent bias and amplification noise with optimized single-molecule barcodes[J]. PNAS, 2012, 109 (4): 1347–1352.