Analysis of global gene expression patterns provides researchers with valuable insight into the role of differential expression in normal biological and disease processes.

High-Throughput Digital Gene Expression Analysis With the 5500xl Genetic Analyzer

Shorter sequencing runs and more samples per lane save you time and money.

The SOLiD® SAGE™ Kit With Barcoding Adaptor Module provides:

  • A highly sensitive, hypothesis-neutral method for quantifying gene expression levels on a genome-wide scale.
  • A small number of optimized steps to generate a library of 27 bp 3’ tags for all the transcripts in a cell.

Focusing on the 27 bp 3’ ends of a tag means you can achieve highly accurate quantification of expression profiles with far fewer reads than required for whole-transcriptome analysis, translating to shorter sequencing runs and more samples per lane, saving you time and money.

Digital gene expression analysis is further simplified using the included SOLiD® SAGE™ software package.

Advantages Over Microarrays

High-density microarrays designed to globally assay mRNA expression levels:

  • Are limited in their dynamic range
  • Can be relatively ineffective at measuring low-copy genes
  • Depend upon 3’ biased sample preparation and hypothesis-driven probe design, limiting the ability to detect novel exons or differentiate between splice variants

Together, the SOLiD® SAGE™ Kit with Barcoding Adaptor Module and the ultra–high-throughput 5500xl Genetic Analyzer:

  • Increase sensitivity—detect expression of transcripts from <1 copy per cell to over 100,000 copies per cell, corresponding to a dynamic range of >105, orders of magnitude greater than microarrays. Do it with reproducibility exceeding 0.9.
  • Detect novel RNAs—in addition to known transcripts.
  • Simplify mapping—by isolating 27 bp 3’ tags, you can achieve highly accurate quantification of expression profiles with significantly fewer reads, allowing for more samples per run.
  • Analyze and quantify—determine genome-wide expression levels of both traditional poly(A) and non-poly(A) transcripts.
  • Multiplex—the Barcoding Adaptor Module in combination with any of the SOLiD® RNA Barcoding Kits allow you to multiplex multiple research samples in a single lane for cost-effective gene expression profiling.

For Research Use Only. Not intended for any animal or human therapeutic or diagnostic use.

Step-by-Step Guide to Gene Expression Profiling on the 5500 Genetic Analyzer

Your interest will direct you to one of our three RNA application pages; small RNAs (see Small RNA Analysis), novel exons and the splice variants (see Whole Transcriptome Analysis) or known and novel gene expression profiling (where you are now).

The focused 3' tag based gene expression of SOLiD® SAGE™ analysis requires a limited amount of data compared to whole transcriptome analysis. Generally 2-5 M mappable reads per sample are needed. You can make the most of the SOLiD® System's throughput by leveraging the SOLiD® RNA barcodes for this application.

The remainder of this workflow will focus on SAGE™ on the SOLiD® System.

 

Align sequence tags back to a reference genome and quantify expression levels. The SOLiD™ SAGE™ Analysis Software v1.10 is available as a free download from the SOLiD™ SAGE™ project page or on the SOLiD™ Software Development Community page.

The tools you need for each step in the SAGE data analysis workflow:

Data Analysis StepApplied Biosystems Software3rd-Party Software***
1. Align reads to reference in color space
 
2. Generate quality metrics
  • LifeScope™ Genomic Analysis Software
  • LifeScope™ Cluster
  • LifeScope™ Workstation
 
3. Generate sequencing and alignment statistics
 
4. Count and quanitate tags
 
5. Translate color space to base space
 
6. Visualize in context of annotation
 
7. Convert to SRF for publishing  
Step 1 : Design Experiment

Your interest will direct you to one of our three RNA application pages; small RNAs (see Small RNA Analysis), novel exons and the splice variants (see Whole Transcriptome Analysis) or known and novel gene expression profiling (where you are now).

The focused 3' tag based gene expression of SOLiD® SAGE™ analysis requires a limited amount of data compared to whole transcriptome analysis. Generally 2-5 M mappable reads per sample are needed. You can make the most of the SOLiD® System's throughput by leveraging the SOLiD® RNA barcodes for this application.

The remainder of this workflow will focus on SAGE™ on the SOLiD® System.

 

Step 2 : Isolate RNA
Step 3 : Template Preparation
Step 4 : Sequence
Step 5 : Analyze Data

Align sequence tags back to a reference genome and quantify expression levels. The SOLiD™ SAGE™ Analysis Software v1.10 is available as a free download from the SOLiD™ SAGE™ project page or on the SOLiD™ Software Development Community page.

The tools you need for each step in the SAGE data analysis workflow:

Data Analysis StepApplied Biosystems Software3rd-Party Software***
1. Align reads to reference in color space
 
2. Generate quality metrics
  • LifeScope™ Genomic Analysis Software
  • LifeScope™ Cluster
  • LifeScope™ Workstation
 
3. Generate sequencing and alignment statistics
 
4. Count and quanitate tags
 
5. Translate color space to base space
 
6. Visualize in context of annotation
 
7. Convert to SRF for publishing  
Step 6 : Validate Results
Products

Step-by-Step Guide to Gene Expression Profiling on the 5500 Genetic Analyzer

Your interest will direct you to one of our three RNA application pages; small RNAs (see Small RNA Analysis), novel exons and the splice variants (see Whole Transcriptome Analysis) or known and novel gene expression profiling (where you are now).

The focused 3' tag based gene expression of SOLiD® SAGE™ analysis requires a limited amount of data compared to whole transcriptome analysis. Generally 2-5 M mappable reads per sample are needed. You can make the most of the SOLiD® System's throughput by leveraging the SOLiD® RNA barcodes for this application.

The remainder of this workflow will focus on SAGE™ on the SOLiD® System.

 

Align sequence tags back to a reference genome and quantify expression levels. The SOLiD™ SAGE™ Analysis Software v1.10 is available as a free download from the SOLiD™ SAGE™ project page or on the SOLiD™ Software Development Community page.

The tools you need for each step in the SAGE data analysis workflow:

Data Analysis StepApplied Biosystems Software3rd-Party Software***
1. Align reads to reference in color space
 
2. Generate quality metrics
  • LifeScope™ Genomic Analysis Software
  • LifeScope™ Cluster
  • LifeScope™ Workstation
 
3. Generate sequencing and alignment statistics
 
4. Count and quanitate tags
 
5. Translate color space to base space
 
6. Visualize in context of annotation
 
7. Convert to SRF for publishing  
Step 1 : Design Experiment

Your interest will direct you to one of our three RNA application pages; small RNAs (see Small RNA Analysis), novel exons and the splice variants (see Whole Transcriptome Analysis) or known and novel gene expression profiling (where you are now).

The focused 3' tag based gene expression of SOLiD® SAGE™ analysis requires a limited amount of data compared to whole transcriptome analysis. Generally 2-5 M mappable reads per sample are needed. You can make the most of the SOLiD® System's throughput by leveraging the SOLiD® RNA barcodes for this application.

The remainder of this workflow will focus on SAGE™ on the SOLiD® System.

 

Step 2 : Isolate RNA
Step 3 : Template Preparation
Step 4 : Sequence
Step 5 : Analyze Data

Align sequence tags back to a reference genome and quantify expression levels. The SOLiD™ SAGE™ Analysis Software v1.10 is available as a free download from the SOLiD™ SAGE™ project page or on the SOLiD™ Software Development Community page.

The tools you need for each step in the SAGE data analysis workflow:

Data Analysis StepApplied Biosystems Software3rd-Party Software***
1. Align reads to reference in color space
 
2. Generate quality metrics
  • LifeScope™ Genomic Analysis Software
  • LifeScope™ Cluster
  • LifeScope™ Workstation
 
3. Generate sequencing and alignment statistics
 
4. Count and quanitate tags
 
5. Translate color space to base space
 
6. Visualize in context of annotation
 
7. Convert to SRF for publishing  
Step 6 : Validate Results
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For Research Use Only. Not for use in diagnostic procedures.