Introduction

Gene expression profiling methods enable the quantification of multiple transcripts from a single RNA sample. Powerful and continually evolving methods, such as short-read sequencing (RNA-seq), microarray analysis, quantitative real-time RT-PCR, as well as traditional methods for differential gene expression studies using multiplex endpoint PCR and northern blot analysis 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 2012 Gene Expression Profiling Dashboard™ is the fourth in a series that characterizes the dynamic market for products for profiling gene expression. This 2012 Dashboard provides a snapshot of the current market landscape that is compared with data from the 2010 and 2008 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 2012 Gene Expression Profiling Dashboard™ was developed from responses to a 21-question survey completed by 460 scientists predominantly located in North America and Europe. 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 endpoint PCR
• Digital gene expression/molecular barcodes
• Microarray-based gene expression studies (including bead arrays)
• 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 (RNA-seq) short-read sequencing

Survey Methodology

In February of 2012, Percepta fielded the Gene Expression Profiling Survey to a subset of the company’s panel of more than 60,000 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 February 12, 2012 and results collected through February 24, 2012. A total of 460 scientists that are actively engaged in performing gene expression profiling experiments completed the survey. 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 71.7% of the respondents employed in an academic setting, 23.1% in an industrial setting and 5.2% of respondents work for government organizations. 65.4% of respondents are from North America, while nearly 35.0% reside in Europe.

Junior (Lab Tech, Grad Students, Post-Doctoral Fellow), mid-level (Department Manager, Project Manager, Scientist, Core Manager, Professor, Instructor, Lab Manager) and senior (PI, Group Leader, Lab Director, Senior Scientist, CEO) scientists are well represented in the data set, with the most cited job titles being Post-Doctoral Fellow/Research Fellow (18.7%) and Principal Investigator (15.2%).

A wide variety of scientific areas of specialization is also evident, led by molecular biology (named by 25.9% of respondents as their primary area of expertise), cell biology (11.7%) and biochemistry (8.9%). Immunology (7.8%), microbiology/infectious disease/virology (6.7%), neuroscience (5.9%) and genetics (5.7%) are the only other areas of expertise named by more than 5.0% 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 35.9% of survey participants work in labs where one to five people perform experiments. 30.2% are employed in labs with six to ten scientists, while the remaining 33.9% of respondents work in labs where greater than 10 individuals work at the bench.

73.1% of respondents indicated that 1 to 5 people in their laboratories perform gene expression profiling experiments. An additional 18.5% of survey participants revealed that 6 to 10 individuals perform expression profiling in their laboratories. Only 8.5% of respondents work in labs where greater than 10 people perform expression profiling experiments.

Table of Contents

• 8 Figures and Tables
• 13 Executive Summary
• 15 Key Findings and Implications
• 19 Gene Expression Profiling Dashboard
• 27 Gene Expression Profiling Market Opportunity Matrix
• 28 Survey Methodology
• 30 Survey Invitation Text
• 31 Respondent Demographics
• 41 Frequency of Performance of Life Science Techniques
• 46 Frequency of Performance of Gene Expression Profiling Methods
• 75 Throughput and Market Growth Rates
• 83 Respondents’ Stated Price Per Reaction
• 86 Total Market Size, Market Segment Sizes and Total Market Growth Rate
• 88 Market Shares by Segment (Share of Mentions)
• 118 Customer Satisfaction And Interest In Switching Suppliers
• 126 Product Features That Influence Purchasing Decisions
• 139 Gene Expression Profiling Applications
• 176 Desired Changes to Gene Expression Profiling Products
• 202 Unmet Needs in Gene Expression Profiling Research
• 208 Survey Questionnaire
• 217 Appendix: Abbreviated Techniques

Figures and Tables

• 33 Figure 1: Respondents’ Place of Employment
• 34 Figure 2: Respondents’ Location
• 35 Figure 3: Respondents’ Job Title
• 37 Figure 4: Respondents’ Areas of Expertise/Specialization
• 40 Figure 5: Number of Employees in Respondents’ Laboratories
• 43 Figure 6: Percentage of Respondents Performing Various Life Science Techniques at Least a Few Times per Year
• 49 Figure 7: Percentage of Respondents Performing Gene Expression Profiling Experiments
• 50 Figure 7A: Change in Percentage of Respondents Performing Gene Expression Profiling Experiments
• 51 Figure 8: Percentage of Respondents Performing Various Gene Expression Profiling Techniques at Least a Few Times per Year
• 53 Figure 9: Percentage of Respondents That Perform Differential Gene Expression Studies Using Multiplex Endpoint PCR
• 54 Figure 9A: Change in Percentage of Respondents That Perform Differential Gene Expression Studies Using Multiplex Endpoint PCR
• 55 Figure 10: Percentage of Respondents That Perform Digital Gene Expression Studies/ Molecular Barcodes
• 56 Figure 10A: Change in Percentage of Respondents That Perform Digital Gene Expression Studies/ Molecular Barcodes
• 57 Figure 11: Percentage of Respondents That Perform Microarray-Based Gene Expression Studies
• 58 Figure 11A: Change in Percentage of Respondents That Perform Microarray-Based Gene Expression Studies
• 59 Figure 12: Percentage of Respondents That Perform qRT-PCR (cDNA Template) Using Gene Specific Fluorescent Probes
• 60 Figure 12A: Change in Percentage of Respondents That Perform qRT-PCR (cDNA Template) Using Gene Specific Fluorescent Probes
• 61 Figure 13: Percentage of Respondents That Perform qRT-PCR (cDNA Template) Using Non-Specific SYBR Green
• 62 Figure 13A: Change in Percentage of Respondents That Perform qRT-PCR (cDNA Template) Using Non-Specific SYBR Green
• 63 Figure 14: Percentage of Respondents That Perform Northern Blot Analysis
• 64 Figure 14A: Change in Percentage of Respondents That Perform Northern Blot Analysis
• 65 Figure 15: Percentage of Respondents That Perform Serial Analysis of Gene Expression (SAGE) Studies
• 66 Figure 15A: Change in Percentage of Percentage of Respondents That Perform Serial Analysis of Gene Expression (SAGE) Studies
• 67 Figure 16: Percentage of Respondents That Perform Transcriptome Studies Using Tiling Arrays
• 68 Figure 16A: Change in Percentage of Respondents That Perform Transcriptome Studies Using Tiling Arrays
• 69 Figure 17: Percentage of Respondents That Perform Transcriptome Studies via Short Read Sequencing
• 70 Figure 17A: Change in Percentage of Respondents That Perform Transcriptome Studies via Short Read Sequencing
• 93 Figure 18: Respondents’ Primary Supplier for Differential Gene Expression Studies Using Multiplex Endpoint PCR
• 95 Figure 18A: Change in Respondents’ Primary Supplier for Differential Gene Expression Studies Using Multiplex Endpoint PCR
• 96 Figure 19: Respondents’ Primary Supplier for Digital Gene Expression Studies/Molecular Barcodes
• 98 Figure 20: Respondents’ Primary Supplier for Microarray-Based Gene Expression Studies
• 100 Figure 20A: Change in Respondents’ Primary Supplier for Microarray-Based Gene Expression Studies
• 101 Figure 21: Respondents’ Primary Supplier for qRT-PCR (cDNA Template) Using Gene Specific Fluorescent Probes
• 103 Figure 21A: Change in Respondents’ Primary Supplier for qRT-PCR (cDNA Template) Using Gene Specific Fluorescent Probes
• 104 Figure 22: Respondents’ Primary Supplier for qRT-PCR (cDNA Template) Using Non-Specific SYBR Green
• 106 Figure 22A: Change in Respondents’ Primary Supplier for qRT-PCR (cDNA Template) Using Non-Specific SYBR Green
• 107 Figure 23: Respondents’ Primary Supplier for Northern Blot Analysis
• 109 Figure 23A: Change in Respondents’ Primary Supplier for Northern Blot Analysis
• 110 Figure 24: Respondents’ Primary Supplier for Serial Analysis of Gene Expression (SAGE) Studies
• 112 Figure 25: Respondents’ Primary Supplier for Transcriptome Studies Using Tiling Arrays
• 114 Figure 26: Respondents’ Primary Supplier for Transcriptome Studies via Short Read Sequencing
• 117 Figure 26A: Change in Respondents’ Primary Supplier for Transcriptome Studies via Short Read Sequencing
• 121 Figure 27: Respondent Satisfaction with Current Gene Expression Profiling Methods
• 124 Figure 28: Percentage of Respondents That Have Switched Suppliers in the Last Six Months
• 144 Figure 29: Respondents’ Primary and Secondary Applications for Differential Gene Expression Studies Using Multiplex Endpoint PCR
• 145 Figure 30: Respondents’ Primary and Secondary Applications for Digital Gene Expression Studies/Molecular Barcodes
• 147 Figure 31: Respondents’ Primary and Secondary Applications for Microarray-Based Gene Expression Studies
• 149 Figure 32: Respondents’ Primary and Secondary Applications for qRT-PCR (cDNA Template) Using Gene Specific Fluorescent Probes
• 151 Figure 33: Respondents’ Primary and Secondary Applications for qRT-PCR (cDNA Template) Using Non-Specific SYBR Green
• 153 Figure 34: Respondents’ Primary and Secondary Applications for Northern Blot Analysis
• 155 Figure 35: Respondents’ Primary and Secondary Applications for Serial Analysis of Gene Expression (SAGE) Studies
• 156 Figure 36: Respondents’ Primary and Secondary Applications for Transcriptome Studies Using Tiling Arrays
• 157 Figure 37: Respondents’ Primary and Secondary Applications for Transcriptome Studies via (RNA-seq) Short-Read Sequencing
• 163 Figure 38: Types of Analyses Performed by Respondents for Differential Gene Expression Studies Using Multiplex Endpoint PCR
• 164 Figure 39: Types of Analyses Performed by Respondents for Digital
  Gene Expression Studies/Molecular Barcodes
• 165 Figure 40: Types of Analyses Performed by Respondents for Microarray-Based Gene Expression Studies
• 166 Figure 41: Types of Analyses Performed by Respondents for qRT-PCR (cDNA Template) Using Gene Specific Fluorescent Probes
• 168 Figure 42: Types of Analyses Performed by Respondents for qRT-PCR (cDNA Template) Using Non-Specific SYBR Green
• 170 Figure 43: Types of Analyses Performed by Respondents for Northern Blot Analysis
• 172 Figure 44: Types of Analyses Performed by Respondents for Serial Analysis of Gene Expression (SAGE) Studies
• 173 Figure 45: Types of Analyses Performed by Respondents for
  Transcriptome Studies Using Tiling Arrays
• 174 Figure 46: Types of Analyses Performed by Respondents for Transcriptome Studies via (RNA-seq) Short Read Sequencing

• 38 Table 1: Respondents’ Areas of Expertise/Specialization (Values for Figure 4)
• 44 Table 2: Frequency of Performance of Various Life Science Techniques
• 45 Table 3: Frequency of Co-Performance of Various Life Science Techniques
• 52 Table 4: Frequency of Performance of Gene Expression Profiling Methods
• 72 Table 5: Frequency of Co-Performance of Life Science Techniques with Gene Expression Profiling Methods
• 73 Table 6: Frequency of Co-Performance of Gene Expression Profiling Methods with Life Science Techniques
• 74 Table 7: Frequency of Co-Performance of Gene Expression Profiling Methods
• 78 Table 8: Mean, Median and Trim Mean Monthly Throughput for Gene Expression Profiling Products
• 79 Table 9: Percentage of Respondents Processing Various Numbers of Gene Expression Profiling Experimental Units Per Month
• 80 Table 10: Highest Throughput Users: Comparison to 2010 Life Science Dashboard
• 82 Table 11: Projected Growth in the Performance of Various Gene Expression Profiling Techniques
• 85 Table 12: Mean, Median and Trim Mean Price Per Experimental Unit for Gene Expression Profiling Methods
• 87 Table 13: Estimated Market Size for Gene Expression Profiling Products
• 117 Table 14: Market Share Leaders for Various Gene Expression Profiling Methods
• 122 Table 15: Percentage of Respondents Satisfied with Various Gene Expression Profiling Products and Reasons for Dissatisfaction
• 123 Table 16: Respondents’ Interest in Switching to a New Supplier for Gene Expression Profiling Systems: Comparison to 2010 Dashboard
• 125 Table 17: Previous Suppliers for Respondents That Have Switched Suppliers for Gene Expression Profiling Methods Over the Last Six Months
• 130 Table 18: Important Product Features for Differential Gene Expression Profiling Experiments Using Multiplex Endpoint PCR
• 131 Table 19: Important Product Features for Digital Gene Expression/Molecular Barcodes
• 132 Table 20: Important Product Features for Microarray-Based Gene Expression Studies
• 133 Table 21: Important Product Features for qRT-PCR (cDNA template) Using Gene Specific Fluorescent Probes
• 134 Table 22: Important Product Features for qRT-PCR (cDNA template) Using Non-Specific SYBR Green
• 135 Table 23: Important Product Features for Northern Blot Analysis
• 136 Table 24: Important Product Features for Serial Analysis of Gene Expression (SAGE) Studies
• 137 Table 25: Important Product Features for Transcriptome Studies Using Tiling Arrays
• 138 Table 26: Important Product Features for Transcriptome Studies via Short-Read Sequencing
• 159 Table 27: Respondents’ Primary Applications for Various Gene Expression Profiling Methods
• 175 Table 28: Types of Analyses Performed by Respondents Using Various Gene Expression Profiling Methods

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