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BIOCHIP
TECHNOLOGY OVERVIEW
SNP MICROARRAYS
SNP (single nucleotide polymorphism)
microarrays provide an efficient and relatively inexpensive
tool for studying several genetic variations in multiple samples
simultaneously. Numerous methods have been developed for SNP
genotyping, of which we are currently primarily utilizing
two array-based methods, namely allele-specific primer extension
on microarray and single base extension combined to TAG array
detection.
For allele-specific primer extension two amino-modified detection
primers, each containing one of the variable nucleotides of
the SNP as their 3’ nucleotide, are spotted and covalently
linked to chemically activated microscope slides. Genomic
DNA flanking the SNP is amplified with SNP-specific primers
containing T7 or T3 RNA polymerase recognition sequence in
their 5’ end. Multiple SNPs can be amplified in one multiplex
PCR reaction simultaneously. By using T7 (or T3) RNA polymerase
PCR products are subsequently transcribed to RNA, which is
then hybridized to the SNP array. Reverse transcriptase enzyme
and fluorescently labeled nucleotides are then employed to
visualize the sequence specific extension reaction of the
allele defining detection primer(s). Up to 80 different samples
can be analyzed on one slide when as many identical subarrays
of detection primers are spotted on a slide, which is then
partitioned into small hybridization chambers. Genotypes are
determined by comparing the signals of the two detection primers
representing the SNP on the array.
For the single base extension reaction, multiple SNP sites
are amplified from the genomic DNA using SNP-specific primers.
After enzymatic removal of the excess primers and nucleotides
single base extension is carried out with a detection primer
containing sequence complementary to predefined TAG sequence
spotted on the array and the SNP-specific sequence just preceding
the variation. One allele-defining nucleotide, each labeled
with different fluorescent dye, is added to the detection
primer in the SBE reaction. Finally, detection primers are
hybridized to the TAG sequences spotted on an array. Genotypes
are determined by comparing the signals of two possible nucleotides
labeled with different fluorescent dyes on each spot.
 References
GENE EXPRESSION MICROARRAYS
DNA microarrays provide a tool for rapid identification of differentially expressed genes. In this technique, thousands of gene fragments (typically oligos or cDNA clones) are robotically arrayed or in situ synthesized on a solid support, such as membrane or glass. The principle of the technique is to compare the relative abundance of expressed sequences in two RNA samples (test and reference). RNAs are first extracted from the test and reference samples and labeled using two different fluorescent dyes (typically Cy3 and Cy5). The labeling of the samples is accomplished by direct incorporation of fluorescent nucleotides during a reverse transcription (RT) reaction. The quality of the RNA going into the RT reaction is critical. After the labeling reaction, the two samples are mixed and hybridized together on the arrayed spots on a glass slide. The ratio of the fluorescence intensities of both colors (for example red and green) are measured which gives the relative abundance of each specific gene in the two RNA samples. Alternatively, only one sample (e.g. labeled with biotin) is hybridized on a microarray (such as Affymetrix GeneChip) and the bound targets are detected by streptavidin-conjugated fluorochromes. The resulting ratio or intensity data can be analyzed by different microarray analysis software. Various tools have been developed to process and visualize the enormous amounts of data generated from each microarray experiment. Microarray technology has been used in a wide variety of applications such as subclassification of different disease entities and identification genes that have clinical relevance in various types of disease.
References
CGH MICROARRAYS
CGH microarrays can be constructed either by spotting genomic clones, cDNAs or oligos on a glass slide by
using a robotic arrayer. We are primarily using oligo microarrays
in copy number analysis, which allows one to study copy numbers
in a single gene level resolution. Compared to the chromosomal
comparative genomic hybridization (CGH), which has a mapping
resolution of 10-20 Mb, arrayCGH has provided substantial
advantage in the analysis of gene copy number changes across
the whole genome. Genomic DNA hybridized onto oligo microarray
is first fragmented with AluI and RsaI restriction enzymes.
Fragmented test and control DNAs are then
labeled with Cy3 and Cy5 fluorescent dyes by using random
priming. The unincorporated nucleotides are removed and probes
are hybridized onto oligo microarrays together with Cot-1 DNA.
The ratios of red and green fluorescence intensities are measured
which gives the relative copy number of each specific gene
in the test sample as compared to the control sample. The
advantage of using oligos as targets in arrayCGH is
that one can study both the expression and copy number on
a gene-by-gene basis.
References
LabChip®
LabChip® technology developed in collaboration with Caliper
and Agilent technologies allows one to perform molecular assays
in a chip format in microfluidics environment. 2100 Bioanalyzer
(Agilent Technologies) uses semiconductor-like microfabrication
techniques where analysis of RNA, DNA and proteins are performed
in a chip that consists of interconnected fluid reservoirs.
Fluid transport is effected by electrodes which create electrokinetic
forces that drive fluids through selected pathways in microchannels.
Bioanalyzer can replace most of the agarose gel based assays.
RNA applications can be used e.g. to detect RNA degradation,
ribosomal contamination of mRNA, efficiency of Cy5 labelling
and the success rate of cRNA fragmentation prior to microarray
hybridization. DNA applications can be used e.g. to determine
the sizes of PCR products. Twelve samples can be analyzed
at a time and the preparation of one chip takes only half
an hour. The advantages of the LabChip® technology are
the sensitivity, fast run time and the small volume of the
sample (1 µl) needed for each analysis.
References for SNP MICROARRAYS
Syvanen AC (1994) Detection of point mutations in human
genes by the solid-phase minisequencing method. Clin Chim
Acta 226:225-36.
Z Guo, RA Guilfoyle, AJ Thiel, R Wang and LM Smith (1994)
Direct fluorescence analysis of genetic polymorphisms by
hybridization with oligonucleotide arrays on glass supports.
Nucleic Acids Res, 22: 5456-5465.
Pastinen T, Raitio M, Lindroos K, Tainola P, Peltonen L, Syvanen
AC. (2000) A system for specific, high-throughput
genotyping by allele-specific primer extension on microarrays.
Genome Res 10:1031-42.
Hirschhorn JN, Sklar P, Lindblad-Toh K, Lim YM, Ruiz-Gutierrez
M, Bolk S, Langhorst B, Schaffner S, Winchester E, Lander
ES. (2000) SBE-TAGS: an array-based method for efficient
single-nucleotide polymorphism genotyping. Proc Natl Acad
Sci USA 97:12164-9.
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to SNP MICROARRAYS
References for GENE EXPRESSION MICROARRAYS
Alizadeh A, Eisen M B, Davis R E, Ma C, Rosenwald A, Sherlock
G, Boldrick J C, Sabet H, Tran T, Yu X, Powell J I, Yang L,
Marti G E, Moore T, Hudson J, Chan W C, Greiner T, Weisenberger
D, Tibshirani R, Armitage J O, Lossos I, Levy R, Wilson W,
Grever M, Byrd J, Botstein D, Brown P O, Staudt L. Identification
of clinically distinct types of diffuse large B-cell lymphoma
based on gene expression patterns. Nature 2000; 403: 503-511.
Bittner M, Meltzer P, Chen Y, Jiang Y, Seftor E, Hendrix M,
Radmacher M, Simon R, Yakhini Z, Ben-Dor A, Sampas N, Dougherty
E, Wang E, Marincola F, Gooden C, Lueders J, Glatfelter A,
Pollock P, Carpten J, Gillanders E, Leja D, Dietrich K, Beaudry
C, Berens M, Alberts D, Sondak V. Molecular classification
of cutaneous malignant melanoma by gene expression profiling.
Nature 2000; 406: 536-540.
DeRisi J, Penland L, Brown P O, Bittner M L, Meltzer P S,
Ray M, Chen Y, Su Y A, Trent J M. Use of a cDNA microarray
to analyse gene expression patterns in human cancer. Nat
Genet 1996; 14: 457-460.
Golub T R, Slonim D K, Tamayo P, Huard C, Gaasenbeek M, Mesirov
J P, Coller H, Loh M L, Downing J R, Caligiuri M A, Bloomfield
C D, Lander E S. Molecular classification of cancer: class
discovery and class prediction by gene expression monitoring.
Science 1999; 286: 531-537.
Hedenfalk I, Duggan D, Chen Y, Radmacher M, Bittner M, Simon
R, Meltzer P, Gusterson B, Esteller M, Kallioniemi O P, Wilfond
B, Borg Å, Trent J. Gene-expression profiles in hereditary
breast cancer. New Engl J Med 2001; 244: 539-548.
Perou C M, Jeffrey S S, van de Rijn M, Rees C A, Eisen M B,
Ross D T, Pergamenschikov A, Williams C F, Zhu S X, Lee J
C, Lashkari D, Shalon D, Brown P O, Botstein D. Distinctive
gene expression patterns in human mammary epithelial cells
and breast cancers. Proc Natl Acad Sci U S A 1999; 96:
9212-9217.
Perou CM, Sorlie T, Eisen M B, van de Rijn M, Jeffrey S S,
Rees C A, Pollack J R, Ross D T, Johnsen H, Akslen L A, Fluge
O, Pergamenschikov A, Williams C, Zhu S X, Lonning P E, Borresen-Dale
A L, Brown P O, Botstein D. Molecular portraits of human
breast tumours. Nature 2000; 406: 747-752.
Schena M, Shalon D, Davis R W, Brown P O. Quantitative
monitoring of gene expression patterns with a complementary
DNA microarray. Science 1995; 270: 467-470.
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to cDNA AND OLIGO MICROARRAYS
References for CGH MICROARRAYS
Heiskanen MA, Bittner ML, Chen Y, Khan J, Adler KE, Trent
JM, Meltzer PS (2000) Detection of gene amplification by
genomic hybridization to cDNA microarrays. Cancer Res
60:799-802
Monni O, Bärlund M, Mousses S, Kononen J, Sauter G, Heiskanen
M, Paavola P, Avela K, Chen Y, Bittner M L, Kallioniemi A
(2001) Comprehensive copy number and gene expression profiling
of the 17q23 amplicon in human breast cancer, Proc Natl
Acad Sci USA 98:5711-5716
Pollack JR, Perou CM, Alizadeh AA, Eisen MB, Pergamenschikov
A, Williams CF, Jeffrey SS, Botstein D, Brown PO (1999) Genome-wide
analysis of DNA copy-number changes using cDNA microarrays.
Nat Genet 23:41-46
Hyman E, Kauraniemi P, Hautaniemi S, Wolf M, Mousses S, Rozenblum E,
Ringer M, Sauter G, Monni O, Elkahloun A, Kallioniemi OP, Kallioniemi A
(2002) Impact of DNA amplification on gene expression patterns in breast
cancer. Cancer Res 62: 6240-6245
Autio R, Hautaniemi S, Kauraniemi P, Yli-Harja O, Astola J, Wolf M, Kallioniemi
A (2003) CGH-Plotter: MATLAB toolbox for CGH-data analysis.
Bioinformatics 19:1714-1715
Wolf, M., Mousses, S., Hautaniemi, S., Karhu, R., Huusko, P., Allinen, M.,
Elkahloun, A., Monni, O., Chen, Y., Kallioniemi, A. and Kallioniemi, O.-P. (2004)
High-resolution analysis of gene copy number alterations in human
prostate cancer using CGH on cDNA microarrays: Impact of copy number on
gene expression. Neoplasia 6: 240-247
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to CGH MICROARRAYS |
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