Genomica - Microarreglos de DNAPresentation Transcript
Prof. Ulises Urzúa ICBM, Facultad de Medicina, Universidad de Chile [email_address] DNA microarrays in genomics and cancer Clase ToxGen-Nov08
(1982 - 2002)
Actualizado, 31 Dic 2008
One gene…or many genes? Environment and life-style are major contributors to the pathogenesis of complex diseases
Legal Issues in Genomic Medicine "We won't be able to offer you a position with our company. The results of our genetic tests suggest that you have a predisposition to attention deficit disorder. Mr. Jones? Mr. Jones?"
Tumor classification, risk assessment, prognosis prediction Microarray CGH Drug development, therapy development, disease progression Mutation &Polymorphism analysis Drug development, drug response, therapy development Transcriptional analysis Application Approach Major microarray applications
Microarray : ordered arrangement of known DNA sequences on a solid- planar substrate which allows the hybridization binding of labeled sample RNAs or DNAs.
A single microarray contains from few hundreds to 400.000 microscopic elements of uniform size and spacing.
Immobilized DNAs are oligonucleotides (20-80 mer), cDNAs (0.5-5 Kb) or BAC clones (10-50 Kb). Substrates are rigid, thermostable, optically flat surfaces like nylon, glass or silica.
DNAs are spotted onto chemically modified substrates and then immobilized using UV. Oligonucleotides can be either spotted or synthesized in situ .
Affimetrix GeneChip ® MicroArrays 20µm Millions of copies of a specific oligonucleotide probe Image of Hybridized Probe Array >400,000 different complementary probes Single stranded, labeled RNA target Oligonucleotide probe 1.28cm GeneChip Probe Array Hybridized Probe Cell Suited for both expression profiling and genotyping * * * * *
Affimetrix GeneChip ® 5´ 3´ Oligo arrays Gene PerfectMatch Mismatch Multiple oligo probes on off 24 µm
The photolitographic technique used in Affimetrix GeneChips TM allows obtaining ultra high-density microarrays (up to 10 6 probes/cm 2 ) GeneChip workstation
Glass slide microarrays
Up to 48,000 spotted “off-line” DNA probes
Spotted cDNA clones, ESTs or oligos
Gene expression, CGH, and SNPs
A comparative hybridization experiment
Mouse NIA 15K cDNA microarray, block 15 (from 32 total) - Cy5 mouse ovarian cell line (total RNA) - Cy3 reference whole newborn mouse (total RNA) Microarrays allows only comparative (relative) measurements Genes up-regulated in mouse ovarian cells Genes up-regulated in the reference RNA Genes equally expressed in both samples
BioRobotics Arrayer Plate loader and lid remover Refrigerated Biobank (holds up to 24 microtiter plates) Wash baths for cleaning the pins The four platforms are capable of holding 120 slides
A 32 pin holder with pins loaded
- Deposits ~0.4nl a spot
Each spot ~100µm diameter
Total uptake volumes 0.25 0.6 2.5 µl Contact deposition
50% DMSO Advantages : denatures the DNA; low evaporation rate; interacts well with GAPS coating thus generating uniform spots. Disadvantages : Strong irritant; tends to form spots of large diameter, sometimes causing them to merge; DNA aggregates when DMSO concentration is above 70%. 3X SSC Advantages : Aqueous solvent; produces spots of small diameter, allowing high printing density. Disadvantages : Does not denature the DNA; evaporates quickly so that carefully controlled printing environment is required. 150 mM NaPO4, pH 8.5 Similar to 3X SSC in terms of advantages and disadvantages Spotting solutions
Crosslinking of DNA to polylysine coated glass - GAPS (gamma aminopropyl silane) coating.
Hybridization Manual hybridization chambers (TELECHEM-Arrayit ) - 20 to 50 µ l of hyb cocktail - prone towards significant experimental variability. Automatic hybridization station: - Over 120 µ l of hyb cocktail - less variability in replicates - washing also automated
Fluorescence scanners ScanArray Lite (Perkin-Elmer) GenePix 4000B (Axon)
Exercise # 1
GenePix Pro 3.0 (Axon) Local
mAdb (NCI`s Microarray database)
Experimental design and variability
Sources of variability:
Due to attributes or conditions
Biological variation is intrinsic; influenced by genetic & environmental factors, as well as whether samples are from populations or individuals
Due to technical issues, results during sample extraction ( quality ), labeling and hybridization
Due to fluorophore stability during laser scanning and fluorescence detection
Microarray data workflow
Experimental Analisis numérico Interpretacion
Corrección técnica (experimental)
Print-tip Loess normalization 3 6
Array #3 Print-tip display
Array #6 Print-tip display
Array #3 “MA” plot M = log 2 R - log 2 G A = (log 2 R + log 2 G ) / 2
Differentially expressed genes: the problem of multiple testing - ANOVA test, 40 arrays, 7 samples - FWER (family wise error rate), type I error or false positive. Urzúa et al. (2006) J. Cell. Physiol. 206, 594-602
Dataset structure -filtering hierarchy Statistical tests Co-expression Correlation, etc (multiple test control) Raw dataset Processed and normalized subset Candidate genes Functional groups Pathway analysis Text-mining (interpretation) Interaction gene/groups networks
Case # 1
An in vitro mouse model of ovarian cancer
Ovarian cancer: risk factors and possible etiology
There is no reliable screening test for early detection. Over 75% is detected late (5-year survival is below 30%).
S ymptoms are often vague and easily confused with other diseases.
risk: No children, continuous ovulation (never used birth control pills)
risk: Pregnancies, lactation
Generation of a mouse model Roby et al., Carcinogenesis 21, 585-594, 2000. pass 5 MOSE (mouse ovarian surface epithelial) cells
MOSE clonal cells produce tumors in immunocompetent mice Roby et al., Carcinogenesis 21, 585-594, 2000 .
Self organizing tree algorithm (SOTA) clustering Urzúa et al. (2006) J. Cell. Physiol. 206, 594-602
SOM clustering of IG10 and IF5 cell lines compared to human ovarian tumors based on 872 genes with equivalent biological function. Samples description is as follows:
Urzúa et al. (2006) J. Cell. Physiol. 206, 594-602
Gene expression array Microarray-CGH Microarray-CGH… How to deal with the genome complexity? RNA (cDNA) hybridized Genomic DNA hybridized
RNA vs DNA raw data distribution
Test RNA and DNA obtained from the same source were hybridized against their respective reference RNA and DNA. Statistical values are shown for 13,417 clones from the NIA-15K cDNA mouse clone set. Upper and lower box boundaries indicate the 75 th and 25 th percentile, respectively. Whiskers above and below the box indicate the 90 th and the 10 th percentiles. A line within the box mark the median .
Real-time Q-PCR validation (2) Urzúa et al. (2008) in preparation
Tal como una casa se construye con ladrillos, la ciencia se construye en base a hechos... Pero un conjunto de hechos no constituye por sí sólo ciencia, tal como un montón de ladrillos no constituyen una casa. Henri Poincaré La Science et l'Hypothese, Paris, 1908.
Dra Carmen Romero (Hosp Clinico U de Chile)
Dr Luigi Devoto (IDIMI, U de Chile)
Dr. David Munroe (NCI Frederick)
Dra Julieta Gonzalez, (Prog Biol Cel Mol, ICBM)
Dr Claudio Martínez (USACH)
Dra Sandra Ampuero (Virología, ICBM)
VID, U de Chile, Proyecto de Iniciación
Gracias! Dr. Ulises Urzúa [email_address] Fono 978-6877
Systems biology integrates different levels of information to understand how biological organisms function. In contrast to molecular biology, systems biology does not break down a system into all of its parts and study one part of the process at a time. Systems biologists argue that this reductionist approach is not robust, either because of nature's redundancy and complexity, or because we have not understood all the parts of the processes. The ultimate goal of systems biology is to mathematically model biological processes. Such models are used to predict how different changes affect the phenotype of a cell, and can be iteratively tested to prove or disprove the model. Adapted from http://en.wikipedia.org/
Seminarios 9 de Diciembre, 2008 http://www.ncbi.nlm.nih.gov/pubmed/18596974 http://www.ncbi.nlm.nih.gov/pubmed/17766027