はじめに： トランスクリプトームおよび遺伝子発現解析
トランスクリプトーム解析は、転写活性（コーディングおよびノンコーディング）を特徴づけ、関連するターゲット遺伝子や転写産物のサブセットにフォーカスし、数千もの遺伝子を一度にプロファイリングして細胞機能の全体像を描出することができます。遺伝子発現解析は、さまざまな条件下で活性に発現している遺伝子やトランスクリプトームのスナップショットを提供します。
イルミナは、広範な種類のサンプルについて高いクオリティの遺伝子発現およびトランスクリプトーム解析データが得られる包括的な次世代シーケンサー（NGS）およびアレイソリューションを提供します。NGSベースのRNAシーケンス（RNA-Seq）法により、新規の転写産物を含む活性遺伝子または転写産物を検出し定量することができます。発現マイクロアレイテクノロジーが既知の既定の遺伝子および転写産物の相対的活性を測定します。
Common Gene Expression Analysis Methods
A variety of methods may be used to profile gene expression for select targets of interest and/or analyze the coding transcriptome, based on your study goals. Learn about the pros and cons of several key gene expression and transcriptome analysis methods.
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-SeqqRT-PCR
Pros: Familiar workflow, effective for low target numbers
Cons: Can only detect known sequences, low scalability
Learn About qRT-PCR vs. RNA-SeqRNA-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シーケンスによる遺伝子発現解析
RNA-Seqは全トランスクリプトームカバレッジ、感度、精度のユニークな組み合わせにより、遺伝子発現の変化を包括的に示します。イルミナのRNA-Seqソリューションにより、正確なストランド情報の測定、均一なカバレッジ、選択的転写産物および融合遺伝子の信頼性が高いマッピングが可能になります。新規の遺伝子アイソフォームの発見、選択ターゲット遺伝子または全コーディングトランスクリプトームの発現のプロファイリング、転写産物量および倍率変化の正確な測定を行います。
詳細は以下をご覧ください：
- mRNAシーケンス: コーディングトランスクリプトームの明確で完全な情報により、選択的転写産物や融合遺伝子、アリル特異的遺伝子発現パターンを発見します
- ターゲットRNAシーケンス: 関心のある特定の転写産物を選択してシーケンスを行います。数十から数千のターゲット遺伝子または転写産物を同時にプロファイリングします。
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.
Whole-Transcriptome Analysis
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.
Featured Gene Expression and Transcriptome Research
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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Precision Immunotherapies Using Tumor-Specific HLA Ligands
Annika Sonntag, PhD explains how using NGS helped her team obtain broader RNA data and measure exon-specific RNA expression.
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Searching for Gene Expression Profiles Associated with Cancer
Researchers discuss how they use RNA-Seq and other NGS methods to uncover cancer-associated gene expression biomarkers.
Read InterviewSpatial Transcriptomics
Unlock a New Spatial View of Multicellular Tissues
The Visium Spatial Gene Expression from 10x Genomics enables you to visualize tissue morphology overlaid with gene activity, revealing the spatial relationships between cells and how they contribute to tissue development, function, and disease state.
View Technical Note
Revealing the Tissue Architecture of Kidney Disease
This application note outlines an integrated workflow for spatially resolved transcriptomics and demonstrates the exceptional performance of the solution for profiling the heterogeneous pathology of diabetic kidney disease.
View App NoteUnlock a New Spatial View of Multicellular Tissues
The Visium Spatial Gene Expression enables you to visualize tissue morphology overlaid with gene activity, revealing the spatial relationships between cells and how they contribute to tissue development, function, and disease state.
View Technical Note
Gene Expression and Regulation in Plants
In this webinar, the speakers assess the effects of tissue heterogeneity on gene regulation in Arabidopsis thaliana. They characterize cell type-specific motif enrichments of large transcription factor families and examine link gene expression to changes in chromatin accessibility. Their approach provides an analytical framework to infer the gene regulatory networks that execute plant development.
View Webinar
Differential Expression Analysis
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, our genomics cloud computing environment, offers a variety of user-friendly tools, including the BaseSpace RNA-Seq Differential Expression App. This app helps researchers perform differential gene expression analysis on RNA-Seq data for a 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.
Featured Products
NextSeq 1000 & 2000 Systems
Groundbreaking benchtop sequencers allow you to explore new discoveries across a variety of current and emerging applications, with higher efficiency and fewer restraints.
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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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Ampliseq for Illumina
AmpliSeq chemistry offers a highly multiplexed PCR-based workflow for a few to hundreds of targets in a single run.
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AmpliSeq for Illumina Transcriptome Human Gene Expression Panel
Targeted research panel that measures expression levels of >20,000 human RefSeq genes.
View ProductDRAGEN Bio-IT Platform
Provides accurate, ultra-rapid secondary analysis of sequencing data, including RNA-Seq data.
View ProductNextSeq 550 System
This benchtop sequencer enables whole-genome, transcriptome, and targeted resequencing plus microarray scanning, with tunable output and high data quality.
View ProductRelated Solutions
Cancer Gene Expression Profiling
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
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
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
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. We recommend our RNA-Seq solutions as an alternative. Illumina remains committed to providing you with high-quality support and service.
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追加リソース
Analyze Gene Expression in Single Cells
Highly sensitive RNA-Seq methods enable gene expression analysis of very low-input samples, even single cells.
User-Friendly RNA-Seq Data Analysis
Access user-friendly tools that support a broad range of gene expression and transcriptome analysis studies.
RNA-Seq for Gene Expression Analysis
Illumina offers a complete, accessible RNA-Seq workflow solution for gene expression and transcriptome profiling studies.
Untangling Alzheimer's Secrets
Amanda Myers, PhD uses a combination of genomics, transcriptomics, and proteomics to explain the complexity of Alzheimer’s disease.
References
- 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.