Services: Microarray


How to Use | Quality Assurance | Support | Educational Courses

Available Arrays | Sample Preparation (Protocols) | Equipment and Software

How to Use

What You Do

  1. Before you start your experiment, you schedule a meeting with Technical Director, Rafael Gama (Ext: 4-8420) to discuss your experimental design, microarrays of choice, and other technical issues.
  2. You place an order for a gene expression experiment via our online form click here.
  3. You prepare total RNA samples using our recommended extraction procedures and provide 5 - 10μg of total RNA at a minimum concentration of 1μg/μl (preferable concentration: > 2μg/μl). RNA samples must be completely free of ethanol and phenol contamination.
  4. You bring your *clearly marked* RNA samples on dry ice together with a hard copy of the service request form and a completed and signed Interdepartmental order to the Functional Genomics Facility (room G405).

What We Do

  1. We will use a small portion of your RNA sample for analysis to recheck the RNA's quality and quantity. If your RNA is degraded or otherwise unsuitable for application to an array we will notify you immediately.
  2. We will perform all subsequent hybridization procedures.
  3. We will conduct the image analysis needed to accurately quantitate the level of expression of each Gene in the microarray.
  4. We will upload your expression data to our storage area in the network.

What You Get

  1. You access all hybridization images (these are available for re-analysis if needed) by using your Web browser. Your data is protected by username and password and is available only to you.
  2. You can easily download the data file which include qualitative and quantitative data for each Gene within experiment, and comparative data between experiments.
  3. You can take advantage of additional bioinformatics tools to assist you in data mining or modeling.
  4. You can consult with Bioinformatics staff for additional assistance in the analysis and interpretation of your expression data.

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Quality Assurance

1. Quality control for RNA samples

The Functional Genomics Facility will independently determine the quality, quantity and purity of customers' RNA samples. Quantity and purity are determined using spectrophotometric measures (Total RNA should be provided at a minimal concentration of 0.5 μg/μl and OD260 / OD280 ratio must be equal or above 1.8), and quality is assessed using an Agilent 2100 Bioanalyzer. If your RNA is degraded or otherwise unsuitable for application to an array we will notify you immediately. Below is an example of intact RNA and degraded RNA evaluated by Agilent 2100 Bioanalyzer.

Note: If your RNA is approved and the data are not satisfactory, we will repeat the microarray hybridization free of charge

2. Quality control for Affymetrix arrays

The performance of hybridization procedures will be checked at each key step, including cDNA production, in vitro transcription, cRNA fragmentation and target hybridization (internal hybridization controls are included). By having multiple controls, the quality of performance can be closely monitored and continuously improved.

3. Quality control for custom cDNA arrays

A. Array printing
Before printing, purified PCR products will be analyzed using agarose gels to check yield and product size. The optimum DNA concentration for printing will be determined. During printing, control elements will be included in each array for hybridization control. After printing, An array from each print run is stained with SYBR Green to determine spot quality. The below is an example of effect of DNA concentration on spotting quality.

The effect of DNA concentration on reproducibility of microarray hybridization. The microarray image of Hemoglobin alpha gene is shown for three independent hybridizations using mRNA isolated from the liver of different Mrl mice. The rows represent 16 replicates and columns represent 7 DNA concentrations for printing (from left to right: 1μg/μl, 0.4μg/μl, 0.3μg/μl, 0.2μg/μl, 0.1μg/μl, 0.05μg/μl, and 0.01μg/μl). 0.2μg/μl was determined to be the best DNA concentration for reproducibility in consideration of variation within and among experiments

B. cDNA array hybridization
A small quantity of control RNA molecules will be mixed with sample RNA for monitoring the quality of reverse transcription reaction as well as hybridization condition.

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Support

You are encouraged to consult with Functional Genomics Facility staffs before you start your experiments. We will:

  1. assist you in your experimental design;
  2. provide instruction in tissue dissection (click here for suggested procedures) and RNA isolation (click here for suggested protocols);
  3. give guidance in data analysis and data mining;
  4. answer any other questions related to this service;

The Functional Genomics Facility will also:

  1. provide support for preparation of grant applications if you have proposed to use this facility in your grant. Please contact us at least two weeks before your grant deadline. We will assist in helping you prepare descriptions of the resources and budget justifications for your grant ;
  2. provide educational courses to help you systematically understand microarray technology, methodology and more efficient analysis of your microarray data.

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Educational courses

Course 1. How to design and perform a microarray experiment

One-day training course will be available quarterly through the Functional Genomics Facility beginning in 2002. This course will include:

  • Points to consider for microarray experimental design
  • Key issues to remember for sample collection/tissue dissection
  • Factors affecting RNA quality and quantity
  • Proper evaluation of RNA quality Hands-on demonstration of the key microarray procedures
  • Hands-on demonstration of Affymetrix Microarray Suite Software for the first phase of data analysis

Course 2. How to make biological sense out of microarray data: advanced microarray data analysis

Additional bioinformatics classes will be offered for in-depth discussions of the numerous algorithms used in data analysis. These courses will include:

  • Significant Analysis of Microarrays - Commonly used software for aggregated signal-level analysis.
  • dCHIP - A free software used for model-based analysis of Affymetrix arrays.
  • GeneSpring - Most popular data analysis software and particular effective for data visualization.
  • GenMAPP/MAPPFinder - Used for molecular pathways and gene ontology analysis
  • ingenuity - software application that enables biologists and bioinformaticians to identify the biological mechanisms, pathways and functions most relevant to their experimental datasets or genes of interest.

Please contact Dr. Rafael Gama (email: rgama@bsd.uchicago.edu, ph: 773 834 8420) for detailed course information.

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