Overview of Microarray. 2/71 Gene Expression Gene expression Production of mRNA is very much a reflection of the activity level of gene In the past, looking.

Slides:



Advertisements
Similar presentations
What if we want to know what allele(s) of beta-globin an individual has?
Advertisements

Microarray Simultaneously determining the abundance of multiple(100s-10,000s) transcripts.
1 MicroArray -- Data Analysis Cecilia Hansen & Dirk Repsilber Bioinformatics - 10p, October 2001.
Microarray technology and analysis of gene expression data Hillevi Lindroos.
Statistics for Microarrays
Technologies and utility
DNA microarray and array data analysis
DNA Microarray: A Recombinant DNA Method. Basic Steps to Microarray: Obtain cells with genes that are needed for analysis. Isolate the mRNA using extraction.
Additional Powerful Molecular Techniques Synthesis of cDNA (complimentary DNA) Polymerase Chain Reaction (PCR) Microarray analysis Link to Gene Therapy.
The Human Genome Project and ~ 100 other genome projects:
Chip arrays and gene expression data. Motivation.
Microarray Technology Types Normalization Microarray Technology Microarray: –New Technology (first paper: 1995) Allows study of thousands of genes at.
Arrays: Narrower terms include bead arrays, bead based arrays, bioarrays, bioelectronic arrays, cDNA arrays, cell arrays, DNA arrays, gene arrays, gene.
Microarrays: Theory and Application By Rich Jenkins MS Student of Zoo4670/5670 Year 2004.
Introduce to Microarray
Gene Expression BMI 731 Winter 2005 Catalin Barbacioru Department of Biomedical Informatics Ohio State University.
Gene Expression Data Analyses (1) Trupti Joshi Computer Science Department 317 Engineering Building North (O)
Genomics I: The Transcriptome RNA Expression Analysis Determining genomewide RNA expression levels.
Microarrays: Basic Principle AGCCTAGCCT ACCGAACCGA GCGGAGCGGA CCGGACCGGA TCGGATCGGA Probe Targets Highly parallel molecular search and sort process based.
and analysis of gene transcription
By Moayed al Suleiman Suleiman al borican Ahmad al Ahmadi
Analysis of microarray data
Gene Expression Microarrays Microarray Normalization Stat
with an emphasis on DNA microarrays
Lecture 189Functional Genomics Based on chapter 8 Functional and Comparative Genomics Copyright © 2010 Pearson Education Inc.
Microarrays, RNAseq And Functional Genomics CPSC265 Matt Hudson.
HC70AL Spring 2009 Gene Discovery Laboratory RNA and Tools For Studying Differential Gene Expression During Seed Development 4/20/09tratorp.
CDNA Microarrays Neil Lawrence. Schedule Today: Introduction and Background 18 th AprilIntroduction and Background 25 th AprilcDNA Mircoarrays 2 nd MayNo.
Affymetrix vs. glass slide based arrays
This Week: Mon—Omics Wed—Alternate sequencing Technologies and Viromics paper Next Week No class Mon or Wed Fri– Presentations by Colleen D and Vaughn.
Genomics I: The Transcriptome RNA Expression Analysis Determining genomewide RNA expression levels.
DNA MICROARRAYS WHAT ARE THEY? BEFORE WE ANSWER THAT FIRST TAKE 1 MIN TO WRITE DOWN WHAT YOU KNOW ABOUT GENE EXPRESSION THEN SHARE YOUR THOUGHTS IN GROUPS.
Lecture 22 Introduction to Microarray
How do you identify and clone a gene of interest? Shotgun approach? Is there a better way?
Data Type 1: Microarrays
Library screening Heterologous and homologous gene probes Differential screening Expression library screening.
Microarray Technology
Literature reviews revised is due4/11 (Friday) turn in together: revised paper (with bibliography) and peer review and 1st draft.
Scenario 6 Distinguishing different types of leukemia to target treatment.
ARK-Genomics: Centre for Comparative and Functional Genomics in Farm Animals Richard Talbot Roslin Institute and R(D)SVS University of Edinburgh Microarrays.
Introduction to DNA microarray technologies Sandrine Dudoit, Robert Gentleman, Rafael Irizarry, and Yee Hwa Yang Bioconductor short course Summer 2002.
Monday Human and chimp DNA is ~98.7 similar, But, we differ in many and profound ways, Can this difference be attributed, at least in part, to differences.
Microarrays and Gene Expression Analysis. 2 Gene Expression Data Microarray experiments Applications Data analysis Gene Expression Databases.
What Is Microarray A new powerful technology for biological exploration Parallel High-throughput Large-scale Genomic scale.
Genomics I: The Transcriptome
MICROARRAY TECHNOLOGY
Gene Expression Analysis. 2 DNA Microarray First introduced in 1987 A microarray is a tool for analyzing gene expression in genomic scale. The microarray.
Introduction to Microarrays.
LEQ: HOW DOES DNA PROFILING WORK? 12.8 to NUCLEIC ACID PROBES  Short single strands of DNA w/ specific nucleotide sequences are created using.
Lecture 7. Functional Genomics: Gene Expression Profiling using
Microarrays and Gene Expression Arrays
Lecture 6. Functional Genomics: DNA microarrays and re-sequencing individual genomes by hybridization.
Idea: measure the amount of mRNA to see which genes are being expressed in (used by) the cell. Measuring protein might be more direct, but is currently.
Microarray Technology. Introduction Introduction –Microarrays are extremely powerful ways to analyze gene expression. –Using a microarray, it is possible.
Microarray (Gene Expression) DNA microarrays is a technology that can be used to measure changes in expression levels or to detect SNiPs Microarrays differ.
Microarray hybridization Usually comparative – Ratio between two samples Examples – Tumor vs. normal tissue – Drug treatment vs. no treatment – Embryo.
Introduction to Microarrays. The Central Dogma.
ANALYSIS OF GENE EXPRESSION DATA. Gene expression data is a high-throughput data type (like DNA and protein sequences) that requires bioinformatic pattern.
Lecture 23 – Functional Genomics I Based on chapter 8 Functional and Comparative Genomics Copyright © 2010 Pearson Education Inc.
Molecular Genetic Technologies Gel Electrophoresis PCR Restriction & ligation Enzymes Recombinant plasmids and transformation DNA microarrays DNA profiling.
Microarrays and Other High-Throughput Methods BMI/CS 576 Colin Dewey Fall 2010.
DNA Microarray Overview and Application. Table of Contents Section One : Introduction Section Two : Microarray Technique Section Three : Types of DNA.
Functional Genomics Carol Bult, Ph.D. Course coordinator The Jackson Laboratory Winter/Spring 2011 Keith Hutchison, Ph.D. Course co-coordinator.
Introduction to Oligonucleotide Microarray Technology
Microarray: An Introduction
MICROARRAY. Microarray  A multiplex lab-on-a-chip  A 2D array on a solid substrate (Usually a glass slide or silicon thin-film cell) that assays large.
The Central Dogma. Life - a recipe for making proteins DNA protein RNA Translation Transcription.
Microarray Technology and Applications
Lecture 11 By Shumaila Azam
Introduction to Microarrays.
Presentation transcript:

Overview of Microarray

2/71 Gene Expression Gene expression Production of mRNA is very much a reflection of the activity level of gene In the past, looking at whether a specific gene is turned up (upregulated) or turned off (downregulated) under certain condition

3/71 Microarray Data Microarray: a technological advancement study the genes of an organism’s at once Microarrays are a massively-parallel Northern Blot High throughput method allow for the global study of changes in gene expression → complete cellular snapshot

4/71 Reverse Transcription Clone cDNA strands, complementary to the mRNA

5/71 Microarray Experiments mRNA levels compared in many different contexts Different tissues, same organism (brain vs. liver) Same tissue, same organism (tumor vs. non-tumor) Same tissue, different organisms (wild-type or mutant) Time course experiments (development)

6/71 Expression Profiles in Tissues In any type of tissue, only a limited set of the genes are switched on at any given time. Also, from one tissue type to another, the limited set of genes involved will vary. Thus, each tissue can be identified by its unique pattern of gene expression. This pattern is often called an “expression profile” or a “molecular signature”. Here is an example of a normal breast cell and a normal prostate cell. Although both of these cells have many mRNAs and proteins in common (grey), they also have unique differences.

7/71 Expression Profiles in Cancer It is possible to measure differences between a normal and a cancer tissue of the same type--- for example, normal and cancerous prostate. When a normal prostate tissue is transformed into cancerous prostate tissue, the expression profile changes.  Any changes in gene expression ultimately cause alterations in protein production.  New expression profiles in a cancer cell can dramatically alter the network of proteins that interact.  A critical protein may no longer be available, another may be overproduced, yet another may be flawed. And when new genes become activated, entirely new proteins may be introduced. Many different combinations of gene changes and protein interactions are seen in cancerous tissue.

8/71 Cells and Gene Expression The repertoire of gene products produced by a cancer cell might differ in two ways from its normal counterpart: Quantitatively As shown for gene B, which is expressed at an abnormally high level, and gene A, which is not expressed at all. Qualitatively As shown for gene C*, which is mutated such that it produces an altered gene product.

9/71 Two Main Technologies for Making Microarrays Robotic spotting From D. Steke ’ s Microarray Bioinformatics

10/71 nylon array 10pmol/mm 2 glass array 0.1pmol/mm 2 From prof. 陳同孝 ’ s slide

11/71 Two Main Technologies for Making Microarrays (cont’d) In situ synthesis Using photolithography

12/71 Two Type of Microarrays (Harrington et al. 2000) cDNA Array Oligo. Array

13/71 cDNA Array (Harrington et al. 2000)

14/71 cDNA Probe Preparation

15/71 Sample Preparation Compare the genetic expression in two samples of cells SAMPLES cDNA labelled red/green

16/71 Dye Labelling aminoally-dUTP

17/71 Hybridization and Scanning HYBRIDIZE Add equal amounts of labelled cDNA samples to microarray. SCAN Expression profiling using cDNA microarrays Nature, 21, 1999

18/71

19/71 cDNA Array (cont’d) cDNA Array: e.g. Agilent One probe  one gene Processing steps: Experimental design Sample preparation RNA extraction Prepare cDNA Labeling cDNA with dye Hybridization Quantitation Hybridization Microarray manufacturing Sample preparation Quantitation Data analysis Experiment Probe preparation

20/71 cDNA Array (cont’d)

21/71 Oligonucleotide Array Synthesized on a chip: e.g. Affymetrix Using photolithography Each gene may have several probe sets; each probe sets have above 10 probes.

22/71 Cross-Hybridization

23/71 PM/MM

24/71 PM/MM (cont’d)

25/71 Oligonucleotide Array (cont’d)

26/71 Oligonucleotide Array (cont’d)

27/71 Oligonucleotide Array (cont’d)

28/71 cDNA Array vs. Oligo. Array Probes are cDNA fragments, usually amplified by PCR. At least two samples are hybridized to chip. One probe one gene. Probes of varying length Fluorescence at different wavelengths measured by a scanner. Probes are deposited on a solid support, either positively charged nylon or glass slide. Probes are oligos synthesized in situ using a photolithographic approach. One target sample per array probe-pairs per gene. Probes are 25-mers. The apparatus requires a fluidics station for hybridization and a special scanner. There are at least 5 oligos per cDNA, plus an equal number of negative controls. From Dr. 吳漢銘 ’ s slide

29/71 Advantages and Disadvantages of cDNA Array compared with Oligo. Array Advantages Can choose the DNA on the array Cheaper Fluorescence at different wavelengths measured by a scanner Can hybridize closely related species Disadvantages Less specificity (will cross hybridize to genes ~80% homology) Cannot distinguish closely related gene families May need to confirm DNA sequence Repeated amplification and quality control From Dr. 吳漢銘 ’ s slide

30/71 Advantages and Disadvantages of cDNA Array compared with Oligo. Array Advantages High specificity (small probe length means gene family members can be differentiated) Very robust protocols and results are very reproducible Can use small amount of RNA Widely used, so annotation of probe sets is of relatively high quality Disadvantages Very expensive to design (~US$300,000) Expensive to perform experiments (~US$400 + $300 labeling/hybridization) Limited to the species for which there are chips available sequence required Single target hybridization, so comparison always involves two experiments, and dye swaps are impossible Match/mismatch technology has major limitations: mismatch signal often higher than match, and dose response curve is different for each pair From Dr. 吳漢銘 ’ s slide

31/71 Microarray Experimental Flowchart R=Rf-Rb G=Gf-Gb M=log2R/G A=1/2 log2RG Microarray Life Cycle