Abstract
Overview
Gene expression profiling methods enable the quantification of multiple
transcripts from a single RNA sample. Powerful and continually evolving
methods, such as microarray analysis, multiplex PCR and quantitative real-time
RT-PCR, as well as novel methods for transcriptome analyses using tiling
arrays and short read sequencing are employed by scientists to analyze gene
function, identify new therapeutic and diagnostic targets, and to map pathways
involved in development and disease.
Percepta's 2010 Gene Expression Profiling Dashboard™ is the third in a series
that characterizes the dynamic market for products for profiling gene
expression. This 2010 Dashboard provides a snapshot of the current market
landscape that can be compared with data from the 2008 and 2007 Gene
Expression Profiling Dashboards, providing an ongoing story of how the market
is adapting to new products, new competitors and new sales and marketing
strategies.
The 2010 Gene Expression Profiling Dashboard™ was developed from responses to
a 22-question survey completed by 485 scientists predominantly located in
North America and Europe. 301 of these respondents perform gene expression
profiling methods on a regular basis.
This Dashboard reveals key market indicators for the gene expression profiling
market as a whole as well as for the following methods representing market
sub-segments:
- Differential gene expression studies using multiplex PCR
- Digital gene expression/molecular barcodes
- Microarray-based gene expression studies
- qRT-PCR (cDNA template) using gene specific fluorescent probe
- qRT-PCR (cDNA template) using non-specific SYBR Green
- Northern blot analysis
- Serial Analysis of Gene Expression (SAGE) studies
- Transcriptome studies using tiling arrays
- Transcriptome studies via short-read sequencing
Survey Methodology
In January of 2010, Percepta fielded the Gene Expression Profiling Survey to a
subset of the company's panel of more than 40,000 life scientists. Individuals
were invited by e-mail blast to click through to a webpage at bioanalytix.com
where the survey was hosted. Invitations were delivered on January 10, 2010
and results collected through January 20, 2010. A total of 485 scientists
completed the survey, of which 301 are actively engaged in performing gene
expression profiling experiments. Results based on the aggregate of collected
responses are revealed in this Gene Expression Profiling Dashboard
Respondent Demographics
Respondents from the academic, government and commercial market segments are
well represented, with approximately 22% of respondents employed in an
industry setting. About 70% of respondents are from North America, while
nearly 30% reside in Europe.
Junior (Lab Tech, Grad Students), mid level (Post-Doc, Lab Manager) and senior
(Professor/PI, Group Leader) scientists are well represented in the data set,
with the most cited job titles being Scientist/Senior Scientist (25.5% of
respondents), Professor/Principal Investigator (16.5%) and Post-Doctoral
Fellow (13.0%).
A wide variety of scientific areas of specialization is also evident, led by
molecular biology (named by 34.8% of respondents as their primary area of
expertise), cell biology (9.9%) and biochemistry (7.6%). Immunology (6.5%),
microbiology/infectious disease/virology (6.3%), and genomics (6.0%) are the
only other areas of expertise named by more than 5% of respondents.
Small (1 to 5 scientists), mid-size (6 to 10 scientists) and large
laboratories (>10 scientists) are well represented in the respondent data set.
A total of 37.2% of survey participants work in labs where one to five people
perform experiments. 30.9% are employed in labs with six to ten scientists,
while the remaining 32.0% of respondents work in labs where greater than 10
individuals work at the bench.
Table of Contents
- 6. Figures and Tables
- 10. Executive Summary
- 12. Key Findings and Implications
- 16. Gene Expression Profiling Dashboard
- 20. Gene Expression Profiling Market Opportunity Matrix
- 22. Survey Methodology
- 24. Survey Invitation Text
- 25. Respondent Demographics
- 37. Frequency of Performance of Life Science Techniques
- 42. Frequency of Performance of Gene Expression Profiling Methods
- 68. Reaction Throughput and Market Growth Rates
- 75. Respondent' s Stated Price Per Reaction
- 78. Total Market Size, Market Segment Sizes and Total Market Growth
Rate
- 80. Market Shares by Segment (Share of Mention)
- 101. Customer Satisfaction And Interest In Switching Suppliers
- 109. Product Features That Influence Purchasing Decisions
- 113. Gene Expression Profiling Applications
- 147. Desired Changes to Gene Expression Profiling Products
- 154. Survey Questionnaire
Figures and Tables
- Figure 1: Respondent' s Place of Employment
- Figure 2: Respondent' s Country/Region
- Figure 3: Respondent' s Job Title
- Figure 4: Respondent' s Areas of Expertise/Specialization
- Figure 5: Number of Employees in Respondent' s Laboratories
- Figure 6: Percentage of Respondents Performing Various Techniques at
Least a
- Figure 7: Percentage of Respondents Performing Gene Expression Profiling
Experiments
- Figure 7A: Change in Percentage of Respondents Performing Gene Expression
Profiling Experiments
- Figure 8: Percentage of Respondents Performing Various Gene Expression
Profiling Techniques at Least a
- Figure 9: Percentage of Respondents That Perform Differential Gene
Expression Studies Using Multiplex PCR
- Figure 9A: Change in Percentage of Respondents That Perform Differential
Gene Expression Studies Using Multiplex PCR
- Figure 10: Percentage of Respondents That Perform Digital Gene Expression
Studies/ Molecular Barcodes
- Figure 11: Percentage of Respondents That Perform Microarray-Based Gene
Expression Studies
- Figure 11A: Change in Percentage of Respondents That Perform
Microarray-Based Gene Expression Studies
- Figure 12: Percentage of Respondents That Perform qRT-PCR (cDNA Template)
Using Gene Specific
- Figure 12A: Change in Percentage of Respondents That Perform qRT-PCR (cDNA
Template) Using Gene Specific
- Figure 13: Percentage of Respondents That Perform qRT-PCR (cDNA Template)
Using Non-Specific SYBR Green
- Figure 13A: Change in Percentage of Respondents That Perform qRT-PCR (cDNA
Template) Using Non-Specific SYBR Green
- Figure 14: Percentage of Respondents That Perform Northern Blot Analysis
- Figure 14A: Change in Percentage of Respondents That Perform Northern
Blot Analysis
- Figure 15: Percentage of Respondents That Perform Serial Analysis of Gene
Expression (SAGE) Studies
- Figure 15A: Change in Percentage of Percentage of Respondents That
Perform Serial Analysis of Gene Expression (SAGE) Studies
- Figure 16: Percentage of Respondents That Perform Transcriptome Studies
Using Tiling Arrays
- Figure 17: Percentage of Respondents That Perform Transcriptome Studies
via Short Read Sequencing
- Figure 18: Respondent' s Primary Supplier for Differential Gene Expression
Studies Using Multiplex PCR
- Figure 19: Respondent' s Primary Supplier for Microarray-Based Gene
Expression Studies
- Figure 19A: Change in Respondent' s Primary Supplier for Microarray-Based
Gene Expression Studies
- Figure 20: Respondent' s Primary Supplier for qRT-PCR (cDNA Template) Using
Gene Specific
- Figure 20A: Change in Respondent' s Primary Supplier for qRT-PCR (cDNA
Template) Using Gene Specific
- Figure 21: Respondent' s Primary Supplier for qRT-PCR (cDNA Template) Using
Non-Specific SYBR Green
- Figure 21A: Change in Respondent' s Primary Supplier for qRT-PCR (cDNA
Template) Using Non-Specific SYBR Green
- Figure 22: Respondent' s Primary Supplier for Northern Blot Analysis
- Figure 23: Respondent' s Primary Supplier for Transcriptome Studies via
Short Read Sequencing
- Figure 24: Respondent Satisfaction with Current Gene Expression Profiling
Methods
- Figure 25: Percentage of Respondents That Have Switched Suppliers in the
Last Six Months
- Figure 26: Most Important Features of Products for Gene Expression
Profiling Experiments
- Figure 27: Respondent' s Primary Downstream Application for Differentia l
Gene Expression Studies Using Multiplex PCR
- Figure 28: Respondent' s Primary Downstream Application for
Microarray-Based Gene Expression Studies
- Figure 29: Respondent' s Primary Downstream Application for qRT-PCR (cDNA
Template) Using Gene Specific
- Figure 30: Respondent' s Primary Downstream Application for qRT-PCR (cDNA
Template) Using Non-Specific SYBR Green
- Figure 31: Respondent' s Primary Downstream Application for Northern Blot
Analysis
- Figure 32: Respondent' s Primary Downstream Application for Transcriptome
Studies via Short Read Sequencing
- Figure 33: Types of Analyses Performed by Respondents for Differential
Gene Expression Studies Using Multiplex PCR
- Figure 34: Types of Analyses Performed by Respondents for Microarray-
Based Gene Expression Studies
- Figure 35: Types of Analyses Performed by Respondents for qRT-PCR (cDNA
Template) Using Gene Specific
- Figure 36: Types of Analyses Performed by Respondents for qRT-PCR (cDNA
Template) Using Non-Specific SYBR Green
- Figure 37: Types of Analyses Performed by Respondents for Northern Blot
Analysis
- Figure 38: Types of Analyses Performed by Respondents for Transcriptome
Studies via Short Read Sequencing
- Table 1: Respondent' s Areas of Expertise/Specialization (Values for Figure
4)
- Table 2: Frequency of Performance of Various Techniques
- Table 3: Frequency of Co-Performance of Various Life Science Techniques
- Table 4: Frequency of Performance of Gene Expression Profiling Methods
- Table 5: Frequency of Co-Performance of Life Science Techniques with Gene
Expression Profiling Methods
- Table 6: Frequency of Co-Performance of Gene Expression Profiling Methods
with Life Science Techniques
- Table 7: Frequency of Co-Performance of Gene Expression Profiling Methods
- Table 8: Median and Average Monthly Throughput for Gene Expression
Profiling Products
- Table 9: Percentage of Respondents Processing Various Numbers of
Expression Profiling Samples Per Month
- Table 10: Highest Throughput Users: Comparison to 2008 Life Science
Dashboard
- Table 11: Projected Growth in the Performance of Various Gene Expression
Profiling Techniques
- Table 12: Median and Average Price Per Prep for Gene Expression Profiling
Products
- Table 13: Estimated Market Size for Gene Expression Profiling Products
- Table 14: Market Share Leaders for Gene Expression Profiling Products
- Table 15: Number of Mentions as Primary Supplier for Methods with Low
Numbers of Respondents
- Table 16: Percentage of Respondents Satisfied with Various Gene Expression
Profiling Products and Reasons for Dissatisfaction
- Table 17: Respondent' s Interest in Switching to a New Supplier for Gene
Expression Profiling Systems: Comparison to 2008 Dashboard
- Table 18: Previous Suppliers for Respondents That Have Switched Supplier
for Gene Expression Profiling Methods Over the Last Six Months
- Table 19: Most Important Features of Products for Gene Expression
Profiling Experiments - Comparison to 2007 Gene Expression Profiling Dashboard
- Table 20: Respondent' s Primary Application After Various Gene Expression
Profiling Methods
- Table 21: Number of Mentions of Primary Downstream Applications for
Methods with Low Numbers of Respondents
- Table 22: Types of Analyses Performed by Respondents Using Various Gene
Expression Profiling Methods
- Table 23: Number of Mentions of Types of Analyses Performed for Methods
with Low Numbers of Respondents
