Create a global picture of cell function

Profile gene expression and transcriptome changes for a deeper understanding of biology

Gene Expression and Transcriptome Analysis

Transcriptome analysis experiments enable researchers to characterize transcriptional activity (coding and non-coding), focus on a subset of relevant target genes and transcripts, or profile thousands of genes at once to create a global picture of cell function. Gene expression analysis studies can provide a snapshot of actively expressed genes and transcripts under various conditions.

Next-generation sequencing (NGS) capabilities have shifted the scope of transcriptomics from the interrogation of a few genes at a time to the profiling of genome-wide gene expression levels in a single experiment. Find out how NGS-based RNA sequencing (RNA-Seq) compares to other common gene expression and transcript profiling methods, gene expression microarrays and qRT-PCR. Learn how to analyze gene expression and identify novel transcripts using RNA-Seq.

Gene Expression Profiling eBook
Benefits of Gene Expression Profiling with RNA-Seq

Explore the advantages of NGS for analysis of gene expression, gene regulation, and methylation.

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Gene Expression Microarrays

Pros: Familiar workflow, high sample throughput for analysis of known genes and transcripts

Cons: Inability to detect novel transcripts; gene expression measurement is limited by background at the low end and signal saturation at the high end1

Learn About Arrays vs. RNA-Seq
qRT-PCR

Pros: Familiar workflow, effective for low target numbers

Cons: Can only detect known sequences, low scalability

Learn About qRT-PCR vs. RNA-Seq
RNA-Seq

Pros: Broad dynamic range, can be applied to any species, and can detect both known and novel features in a single assay1

Cons: May be less cost-effective when interrogating a limited number of samples for a small set of known transcript variants

Learn More About RNA-Seq

Learn how to analyze gene expression using the following NGS-based RNA-Seq methods:

  • mRNA Sequencing: Discover alternative transcripts, gene fusions, and allele-specific expression patterns with a clear, comprehensive view of the coding transcriptome.
  • Targeted RNA Sequencing: Select and sequence specific genes or transcripts of interest. Profile gene expression for dozens to thousands of targets simultaneously.
Gene Expression Patterns in Breast Cancer

In episode 41 of the Illumina Genomics Podcast, Dr. Ake Borg discusses classification of breast tumors based on patterns of gene expression, methylation, and other genomic alterations.

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Learn how to capture the broad effects of gene expression changes using whole-transcriptome analysis with total RNA sequencing (total RNA-Seq). This method detects both coding and multiple forms of noncoding RNA for a comprehensive view of the entire transcriptome. 

Learn More About Total RNA-Seq

 

Mapping Neural Diversity with Single-Cell Transcriptome Sequencing

The ability to analyze gene expression signatures from individual cells is transforming the way neurons are classified.

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Featured Gene Expression and Transcriptome Research

 
Tumor RNA-Seq
Uncovering Drug-Susceptible Tumorigenic Pathways

Researchers use NGS-based RNA-Seq to profile biomarkers and analyze transcriptomic signatures of activated pathways in cancer samples.

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RNA
Library Prep Comparison for Differential Gene Expression Analysis

Researchers describe their RNA-Seq library prep protocol comparison study and discuss kit selection considerations.

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Breast Cancer
Searching for Gene Expression Profiles Associated with Cancer

Researchers use RNA-Seq and other NGS methods to uncover cancer-associated gene expression biomarkers.

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To understand disease mechanisms and cell development, researchers frequently investigate differential expression in specific tissues, during development, or in response to varying conditions. RNA-Seq has been shown to detect a higher percentage of differentially expressed genes compared to expression arrays, especially genes with low abundance.1 BaseSpace Sequence Hub apps such as DESeq2 can help researchers perform differential gene expression analysis on RNA-Seq data for a wide variety of species.

Single-Cell Transcriptome Analysis of Endometrial Tissue

This study presents a pipeline for endometrial single-cell gene expression profiling. RNA-Seq was used to identify differentially expressed genes in biopsies vs. cultured individual cells.

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Gene Panel and Array Finder

Identify sequencing panels or microarrays that target your genes of interest. Search panels by gene, or find genotyping arrays by genomic location, variant ID, or species.

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Gene Panel and Array Finder
AmpliSeq for Illumina Transcriptome Human Gene Expression Panel

Targeted research panel that measures expression levels of >20,000 human RefSeq genes.

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TruSeq RNA Exome

Provides a reproducible, economical solution for sequencing RNA from FFPE tissues and other low-quality samples. Accuracy from as little as 10 ng total RNA.

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NextSeq 550 System

This benchtop sequencer enables whole-genome, transcriptome, and targeted resequencing plus microarray scanning, with tunable output and high data quality.

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Cancer Gene Expression Profiling
Cancer Transcriptome Analysis

Analyzing gene expression and transcriptome changes with RNA sequencing can help researchers understand tumor classification and progression. Learn more about cancer RNA-Seq.

Microbial Transcriptome Analysis
Microbial Transcriptome Analysis

Bacterial, viral, and other microbial RNA-Seq experiments enable annotation and quantification of comprehensive microbial transcripts. Learn more about microbial RNA-Seq.

Complex Disease Research
Complex Disease Research

Gene expression and transcriptome profiling studies can help researchers better understand neurological, immunological, and other complex diseases on a molecular level. Learn more about complex disease genomics.

Drug Response Biomarker Studies
RNA-Based Drug Response Biomarker Analysis

Find out how to utilize RNA-Seq to discover and profile RNA-based drug response biomarkers. Access resources designed to help researchers adopt this application. Learn more about drug response RNA biomarker analysis.

The HumanHT-12 v4 Expression BeadChip gene expression array has been discontinued. Suggested alternatives include the TruSeq Stranded Total RNATruSeq RNA Exome, and TruSeq Stranded mRNA kits for RNA-Seq. Illumina remains committed to providing you with high-quality support and service.

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Analyze Gene Expression in Single Cells
Analyze Gene Expression in Single Cells

Highly sensitive RNA-Seq methods enable gene expression analysis of very low-input samples, even single cells.

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RNA-Seq Data Analysis
RNA-Seq Data Analysis

User-friendly software tools simplify mRNA-Seq data analysis for biologists, regardless of bioinformatics experience.

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RNA-Seq for Gene Expression Analysis
RNA-Seq for Gene Expression Analysis

Illumina offers a complete, accessible RNA-Seq workflow solution for gene expression and transcriptome profiling studies.

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Methods Guide
Methods Guide

All the information you need, from BeadChips to library preparation to sequencer selection and analysis. Select the best tools for your lab.

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Untangling Alzheimer's Secrets
Untangling Alzheimer's Secrets

Amanda Myers, PhD uses a combination of genomics, transcriptomics, and proteomics to explain the complexity of Alzheimer’s disease.

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RNA-Seq with the NextSeq Series
RNA-Seq with the NextSeq Series

A flexible, cost-effective solution for RNA sequencing provides a deeper understanding of biology.

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References
  1. Zhao S, Fung-Leung WP, Bittner A, and Ngo K, Liu X. Comparison of RNA-Seq and microarray in transcriptome profiling of activated T cells. PLoS One. 2014;16;9(1):e78644.