The Genomics Platform proposes a complete service:

• advice on the selection of the approach and the design of the experiment
• advice on the preparation of the samples
• experiment
• data analysis and storage

Note: data analysis for genotyping studies is not currently provided.

The Platform is fully equipped with bench space to welcome collaborators. Collaborators appoint a person actually performing the experiments under full supervision of the Platform staff, which participates in your experiment and introduces you to the Platforms equipment.

Alternative forms of service can be envisaged upon request.

Collaborators are asked to fill an agreement form that contains information about the experiment, the type of arrays, the service that the Platform provides, and an estimate of the cost of the experiment planned.

The agreement form is available upon request.       ›› E-mail

Collaborators are strongly advised to consult our guidelines where we describe recommendations in order to maximize the rate of success of a microarray experiment.

	Download our Guidelines (1 page, 182 KB)

Workflow of an Affymetrix and Illumina gene expression experiment

1. Design of the experiment experiment (this initial step requires discussion with the manager of the platform)
2. RNA sample preparation (performed by the collaborator in his/her own laboratory; suggestions regarding extraction methods are available upon request)
3. Control of RNA quality on the 2100 Bioanalyzer
4. Preparation of targets
5. Hybridization of some targets on Test 3 arrays for quality control (applies only to Affymetrix)
6. Hybridization on GeneChips or BeadArrays
7. Data analysis and data mining

We currently propose the following protocols for targets preparation.

For Affymetrix GeneChips

1. For RNA quantities ≥ 1 µg total RNA: the classical amplification, which includes cDNA synthesis using oligo-dT-T7 primer, followed by in vitro transcription (one-cycle labeling).
2. For RNA quantities < 1 µg, down to 100 ng of total RNA: the small scale protocol, where all steps in the procedure described above are performed twice (two-cycle labeling).

	See schematic representations: Protocol A (one-cycle target labeling) Protocol B (two-cycle target labeling)

	Typical Bioanalyser profiles obtained for cRNA prepared for hybridization on Affymetrix GeneChips are shown here. • Intact cRNA from HeLa cells total RNA • Fragmented cRNA from HeLa cells total RNA • Intact cRNA from rat islets of Langerhans total RNA • Intact cRNA from Saccharomyces Cerevisiae total RNA

For Illumina BeadArrays

1. For RNA quantities ≥ 100 ng of total RNA: the Illumina® TotalPrep™ RNA Amplification Kit from Ambion, ABI (details on Ambion website), which includes cDNA synthesis using oligo-dT-T7 primer, followed by in vitro transcription (one-cycle labeling).
2. The Platform proposes the Ovation™ Biotin System from NuGEN (details on NuGEN website) as an alternative amplification method for samples available in very low quantities such as those obtained following FACS-based cell sorting or Laser Capture Microdissection (LCM).

Ordering reagents, GeneChips and BeadArrays

To guaranty homogeneity and reproducibility, all reagents (including GeneChips and BeadArrays) are ordered by the Platform.


Data analysis

For the initial treatment of raw data and statistical analysis, we currently use the following solutions.

For Affymetrix GeneChips

• The GCOS or Expression Console software of Affymetrix; data are further compiled using a program developed in MatLab or in R.
• RMA (Robust Multichip Average) (see RMAExpress web page, and Irizzary et al, 2003 - PDF; 16 pages, 960 KB).


For Illumina BeadArrays

BeadStudio software of Illumina; data are further compiled using a program developed in MatLab or in R.

Additional data analysis and data visualization are performed with GeneSpring (Agilent Technologies).


Data interpretation

The Plateform provides access to GeneGo to analyze and build hypothesis on data generated by global genomics approaches like microarrays. The GeneGo data mining tools and databases help to capture and define the underlying biology behind different types of high-throughput experimental data.

The Platform is a GeneGo recognized Center of Excellence (COE).


Data storage

In the frame of the Swiss Array Consortium, we have collaborated with Dr Mike Primig (formerly in Basel, currently at the University of Rennes, France) to develop MIMAS, a data warehouse to hold a vast amount of raw microarray data described in a complete and MIAME-compliant manner (see MIMAS web pages and Hermida et al., 2006). MIMAS is currently hosted by Vital IT. In order to guaranty confidentiality, access to the data stored in MIMAS will be restricted by login and password.


Publications

The Genomics Platform supports the MIAME standard for microarray experiment. Please consult these guidelines, based on the document called Minimum Information About a Microarray Experiment developed by the Microarray Gene Expression Data society.

Workflow for qRT-PCR

1. Selection of genes of interest
2. Design of amplicons and TaqMan® probes (when selected)
   
   Depending on the application and the specificity of the projects (number of amplicons to measure, number of samples), amplicons, primers and TaqMan® probes are designed with extremely high success rates using:
   • the software Primer Express Version 2.0 (ABI)
   • the Roche Universal Probe Library system (Roche)
   
   Alternatively, validated designs can be directly ordered from ABI.
   
   

   	Order designs on ABI website

   
   
3. RNA sample preparation (performed by the collaborator in his/her own laboratory)
4. Control of RNA quality on the 2100 Bioanalyzer
5. cDNA synthesis
   
   When very low amount of starting material are available, pre-amplification is performed using the NuGEN WT-Ovation™ kit (details on NuGEN website).
   
   
6. Reaction for qPCR assembly
   
   Assembly is performed in 384-well plates with a pipetting robot Biomek 2000 from Beckman (details on Beckman website) or Freedom EVO 150 from Tecan (details on Tecan website).
   
   
7. Data analysis and fold-change evaluation
   
   We use multiple normalization genes (so called “house keeping” genes) for data normalization. This approach provides much more accurate measures of fold-changes compared to the classical use of single normalization gene. The selection of adequate normalization genes is performed using the application geNorm (Vandesompele et al., 2002 - PDF; 12 pages, 141 KB). geNorm is implemented into our Excel macro. Subsequent data analysis (raw data QC, averaging of measures, normalization, computing of normalized data, fold-changes calculation and graphical display) are all covered by our Excel macro, available upon request.
   
   
   ›› geNorm web page

Workflow of sequencing experiment

We strongly encourage collaborators to contact the Platform to discuss the planning and design of sequencing experiments before samples preparation.

For precise information regarding the quantity of samples (RNA or DNA), as well as pricing, please contact us.



Samples

Samples can be quality controlled (integrity and quantity) on the Platform using:

• fluorimetry (QuBit™)
• capillary electrophoresis (Agilent 2100 Bioanalyzer)

Fragmentation of genomic DNA

The Platform is equipped with a Covaris S instrument for efficient and reproducible shearing of DNA using Adaptive Focused Acoustics (AFA™) (details on Covaris website).


Library preparation

The Platform proposes two modes of operation.

1. Collaborators can produce their libraries, following advice of the Platform.
2. The personnel of the Platform prepares the library.
   Our classical workflow includes:
   • preparation of single read or paired-end libraries using Illumina reagents
   • size fractionation of the library on E-Gels® SizeSelect™ 2% Agarose
   • quality control of the library (including Topo cloning and Sanger sequencing of a few clones)

Sequencing

Depending upon requirement for the project, sequencing of 38, 54, 76 or 105 bases, single read or paired-end, will be performed.


Data analysis

The Platform currently supports limited data analysis:

• quality control of the sequencing
• alignment of the reads onto a reference genome using Illumina pipe line (ELAND)

Data storage and data analysis are performed in close collaboration and thanks to the support of Vital-IT.