RNA sequencing (RNA-Seq) is a highly effective method for studying the transcriptome qualitatively and quantitatively. It can identify the full catalog of transcripts, precisely define gene structures, and accurately measure gene expression levels.
Our RNA-Seq services provide unparalleled flexibility in analyzing different RNA species, including coding, non-coding, and small transcripts, from a wide range of starting material using long- or short-read sequencing. Various RNA-Seq service options are available, including total, small, and single-cell RNA-Seq with RNA-Seq data analysis from a wide range of starting materials using short- or long-read sequencing. Our U.S.-based processing and support provides the fastest and most reliable service for customers in North America.
For RNA-Seq experiments using FFPE tissue or other low-quality samples, submit an inquiry about our highly-sensitive RNA exome solution.
Having performed over 220,000 sample extractions, our experienced scientists can extract RNA from over 30 standard and hundreds of custom samples types to ensure RNA integrity and quality.
We also offer several library preparation protocols tailored to meet your project requirements. In addition to standard and stranded poly(A) selection methods, we offer rRNA depletion for FFPE, poor-quality, and ultra-low input samples containing as few as 10pg of RNA or just a few cells. We also offer optional controls such as unique molecular identifiers (UMIs) and ERCC (External RNA Controls Consortium) RNA spike-ins to improve RNA-Seq data quality and quantification accuracy.
Single-cell RNA sequencing analyzes gene expression at single-cell resolution for heterogeneous samples. The 10x Genomics® Chromium™ platform provides advanced transcriptional profiling of thousands of individual cells.
Standard RNA sequencing is our most popular option for profiling gene expression, enabling the analysis of coding (mRNA) and long non-coding RNA (lncRNA).
RNA-Seq services performed in a CAP/CLIA laboratory for clinical applications. Custom CLIA validations for specific assays.
Find the right NGS solution for your project using our interactive selection tool.
There are multiple factors to consider when selecting which RNA-Seq technique is the right approach for your project. In this eBook, discover the what, why, and how of RNA-Seq, the most common types of assays and platforms, and uncover insights into how to select the best method to achieve optimal results for your research.
For those new to bioinformatics, analyzing massive amounts of NGS data can be a daunting task. Download Azenta’s bioinformatics quick start guide to learn how to analyze whole genome sequencing (WGS) and RNA sequencing (RNA-Seq) data with bioinformatics tools to reveal biological insights for your research.
With this two-part webinar series, go beyond traditional transcriptomics and learn about the various NGS approaches available for gene expression analysis. In part 1, we take an in-depth look at various gene expression approaches, including RNA-Seq, single-cell RNA-Seq, digital spatial profiling, and more. In part 2, we explore the data generated from these approaches and how they can complement each other and confirm findings.
RNA-Seq bioinformatics can be complex and difficult to decipher. To help make it more approachable, this workshop and roundtable discussion, led by Azenta Life Sciences' bioinformatics manager Brian Sereni, explores the bioinformatics pipeline, explains NGS results, and addresses common challenges and FAQs for RNA-Seq bioinformatics analysis.
Developing immunotherapies for cancer can be difficult due to the variation of immune response from patient to patient. In this webinar, Dr. Litchfield from UCL Cancer Institute presents his team’s exploratory research using a multiomics approach to better understand the diversity of immune response to cancer and highlights their findings of an alternative source of a tumour-specific antigen in checkpoint inhibitor (CPI) response.
Obtaining samples with high cell viability can be difficult for many experiments but is necessary for success on the 10x Genomics® Chromium™ platform. This tech note describes how Azenta scientists used optimized single-cell workflows, including dead cell removal, to overcome low viability and generate high-quality sequencing data.
Biomedical specimens are often restricted to minute quantities, posing major limitations to RNA-Seq. This case study shows how approximately 50 sorted cells from a glioblastoma can produce transcriptomic data comparable to RNA-Seq experiments that use millions of cells.
Cell populations are rarely homogeneous and synchronized in their characteristics. Standard RNA-Seq approaches are limited to reporting general expression levels thus omitting minor subpopulation profiles. This study highlights new single-cell RNA sequencing capabilities for identifying rare cells, characterizing their transcriptomes, and discovering potential biomarkers.
Strict quality control is required to maintain the integrity of manufactured products for RNA therapies, but current assays often present limitations. Learn how the novel full-length RNA-Seq approach from Azenta allows you to preserve the entire length of and effectively sequence the poly(A) tails of your mRNA products.
Contiguous mRNA full-length sequencing (Iso-Seq) greatly simplifies genome annotation efforts and revolutionizes the discovery of novel RNA isoforms. This Tech Note discusses the advantages of the latest technologies combined with Azenta’s optimized workflow, and how this increases output and accuracy.
High-throughput technologies are critical in performing phenotypic profiling for drug discovery applications. In this tech note, Azenta Life Sciences discusses the challenges associated with traditional approaches, such as microarrays and RNA sequencing, and offers an optimized assay to achieve high-quality phenotypic profiling at a reduced cost for rapid drug discovery.
RNA sequencing, or RNA-Seq, is used to identify the nucleotide sequence of the RNA strand and detect the quantity of RNA in a sample.
RNA-Seq provides a deeper insight into the transcriptome of a cell— enabling discovery of novel transcripts and differential gene expression analysis—by generating count data. In analyzing the count data, researchers can quantify RNA fragments and associate RNA sequences to respective genes in the sample.
The process of RNA-Seq starts by isolating and fragmenting the RNA strand, then undergoing reverse transcription— synthesizing complementary DNA (cDNA)— and adding nucleotides to an RNA strand while copying the RNA strand simultaneously using next generation sequencing (NGS) technology.
RNA sequencing (RNA-Seq) analysis works by using a reference genome or transcriptome to map sequencing reads, quantifying the expression levels of the individual genes and transcripts, and identifying target genes and transcripts that are differentially expressed between samples. Researchers can perform de novo transcriptome assembly for new species with RNA-Seq using low concentrations of a starting sample, and/or with low-quality sample solutions.
For information on our NGS platforms as well as recommended configurations of your projects, please visit the NGS Platforms page. Azenta does not guarantee data output or quality for sequencing-only projects.