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Different microarray applications

Helle LybækIntroduction to Microarray technology

September 2009

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The understanding of a biological system requires knowledge of the molecular mechanisms involved in regulation at:

- DNA level - RNA level - Protein level

Systems biology – Microarray applications

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Gene expression

• Measuring of RNA transcripts in order to determine the gene expression profile in the (patient) sample

Measuring: RNA in order to find gene expression changes

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Gene expression

• Interpretation of data in a biological context

• Searching for gene patterns

• Samples and genes can be hierarchical clustered based on their similarity

Sample cluster

Gene

cluster

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Gene expression

Experimental studies- Gene affected by a given treatment - Time series (with and without a given treatment)- Patterns of gene activity (healthy vs. control)

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van’t Veer et al., Nature, 2002; http://www.agendia.com

Application - Gene expression

• Study of breast cancer and risk for metastases

• Correlation of metastasis development and specific gene expression profiles

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Application - Gene expression

Several other commercial gene expression signature microarrays for diagnostic and/or prognostic purposes are available

• MammaPrint is a prognostic breast cancer microarray

• Uses gene expression signature for predicting disease recurrence

http://www.agendia.com

• Patient-tailored therapy strategy

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Potential in gene expression profiling- Knowledge of the biological processes and molecular

mechanisms in a given system - Identification of novel candidate (disease) genes- Identification of potential therapeutic targets- Biological subgrouping (diagnostic and prognosis)

Application - Gene expression

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MicroRNA (miRNA)

• miRNAs are small non-coding RNAs(19-23 nucleotides)

• miRNAs act as antisense molecules by negatively regulating the expression of genes with sequences that are significantly complementary to the miRNAs

• > 800 human miRNA-encoding genes

• Regulate expression of at least one-third of all human genes

Measuring: RNA in order to determine miRNA expression profile

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Application - miRNA

Study of miRNA expression profiles in human lung cancer

43 miRNAs differentially expressed in lung cancer tissues vs. non-cancerous lung tissues

Correlation of miRNA expression profile of lung adenocarcinomawith patient survival

Yanaihara et al., Cancer Cell 2006

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Application - miRNA

Study of miRNA expression profiles in different types of sarcomas

Correlation of miRNA expression profile with sarcomas subgroups

http://sarcomahelp.org/sarcoma_research.html

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Application - miRNA

miRNAs have shown to be- Critical in the development of organisms- Differentially expressed in tissues- Involved in viral infection processes- Associated with oncogenesis

Potential in miRNA expression profiling- Insight in gene regulation mechanisms- Biological subgrouping (diagnosis and prognosis)- Identification of potential therapeutic miRNA targets

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DNA copy number

• DNA copy number changes in the genome are deletions (loss) and duplications (gain)

Measuring: DNA in order to find DNA copy number changes

duplication

deletion

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Lybæk et al., Clin Genet, 2008

Application - DNA copy number

• Can be used for identification of candidate (disease) genes

• Detection of a deletion containing genes involved in mental retardation

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Study of DNA copy number changes in sarcomas– Leiomyosarcomas– Gastrointestinal stromal tumours

DNA copy number changes reflexes the biology

Application - DNA copy number

Based on slide from: Leonardo A. Meza-Zepeda, The Oslo NMC-node

DNA copy number changes in cancers are often massive and complex

Meza-Zepeda et al., Cancer Res, 2006

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Potential in DNA copy number profiling- Identification of novel candidate (disease) genes- Identification of genetic disorders/syndromes (diagnosis)- Biological subgrouping (diagnosis and prognosis)- Information of genotype-phenotype correlations

Application - DNA copy number

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• SNPs are normally occurring DNA-variants (markers) located in the genome

• SNPs are DNA sequence variations occurring when a single nucleotide –A, T, C, or G- in the genome differs between members of a species (or between paired chromosomes in an individual)

• SNP-genotyping is used to study diseases since SNPs are inheritable

Single Nucleotide polymorphism (SNP)

Measuring: DNA in order to determine the SNP-genotype profile

A

B

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• Linkage study is a method that allows us to determine regions of chromosomes that are likely to contain a risk gene, and rule out areas where there is a low chance of finding a risk gene

• The linkage method works by linking a given SNP-genotype to a given disease and thereby to a DNA region containing the disease causing gene

• Patients needs to be related to each other

SNP - Linkage studies

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Dagbladet: 25. September 2004

Knappskog et al., AM J Hum Genet 2003

Application - Linkage studies

Linkage studies identified the gene responsible for Cold-induced sweating syndrome (CISS)

CISS is a very rare disease and has only been detected in 8 individuals from 5 different families

Nan-Therese inherited the same mutated gene-allele from both her parents

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SNP - Association studies

• Association study: The same as linkage (linking a disease to a DNA region with a gene/genes), but samples are not related

• Association studies are used to study so-called “common public health diseases” as:

- Diabetes- Rheumatism- Hearth-/Stroke diseases- Psychological diseases

• Such diseases are “multifactorial” i.e. influenced by both genetic-and environmental factors

• Therefore association studies requires thousands of patients with a certain disease and thousands of control samples

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• SNP-genotyping of genes involved in development of schizophrenia

- 4.718 persons with schizophrenia

- 41.201 control persons

- Individuals included from 10 countries

Application - Association studies

Stefansson et al., Nature 2008

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Application - Association studies

Chromosome 1

Chromosome 15

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• SNP-genotyping of genes involved in development of schizophrenia

- 4.718 persons with schizophrenia

- 41.201 control persons

- Individuals included from 10 countries

• The deletions were 12-15 times more frequent in persons with schizophrenia than in control persons

• Indicates that the genes located in these deletions are involved in development of schizophrenia

Stefansson et al., Nature 2008

Application - Association studiesm

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Potential in SNP-genotyping profiling- Identification of novel candidate (disease) genes- Genetic mapping of multifactorial conditions/diseases- Information of genotype-phenotype correlations- Knowledge of inheritance patterns

Application – SNP analysis

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• ChIP-on-chip: chromatin immunoprecipitation-on-chip

• Immuniprecipation of DNA-binding proteins and their target DNA sequences

• Regulatory proteins bind to promoter DNA regions and thereby regulate gene expression

ChIP-on-chip

Measuring: DNA fragments thathas been bound to a specific protein

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• Identification of protein-bound promoter sites

• Identification of target genes for the specific regulatory protein

Application – ChIP-on-Chip

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Boyer et al., Cell 2005

Application – ChIP-on-Chip

• Study of transcription factors and gene expression in human embryonic stem cells vs. in differentiated tissues and cell types

• Identification of target genesfor three stem cell specifictranscription factors

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Boyer et al., Cell 2005

Application – ChIP-on-Chip

• In stem cells: - the factors up-regulates genes

required for the maintenance of stem cell identity

- and down-regulates genesnecessary for development and differentiation

• Strong correlation of gene expression regulation and transcription factor-binding

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microarray.noApplication – ChIP-Chip

Potential in ChIP profiling- Insight into transcriptional regulation and epigenomic events- Information of mechanisms involved in cell proliferating,

cell fate determination, oncogenesis, apotosis, and gene silencing

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SNP

Transcription CNV

Transcriptome- mRNA expression- miRNA expression- Splice variance

Genome structure- DNA copy number

Genome variation- Single nucleotide polymorphism- Copy number variation

Proteome- Protein-protein interactions- DNA-protein interactions

Epigenetics- DNA methylation- Chromatin structure

Many biological questions to be asked –Many different microarray applications to answer them!

Based on slide from: Leonardo A. Meza-Zepeda, The Oslo NMC-node

Systems biology – Microarray applications