Microarray technique approach in animal production. BY Esteftah Mohamed Aly El-Komy

Introduction Central dogma

The production of mRNA is a reflection of the activity level of a gene, and a lot of genetic information can be understood by studying it. Older technologies to study gene expression pattern were often tedious and time consuming. Macroarrays Classical gene expression analysis methods such as Northern blotting Reverse transcriptase polymerase chain reaction (RT-PCR) and nuclease protection assays are best suited for analyzing a limited number of genes and samples at a time. these macroarrays have been widely adopted for gene expression studies.

Research in molecular biology increased its scope in recent decades from the need of monitoring expression level of few genes to thousands of genes. Today, we can get thousand-fold high sensitivity in just a few minutes using modern microarray slides, fluorescent dye probes and laser detectors. if we were to use older techniques for 100000 genes then we had to carry the experiment 100000 times. But if we use a DNA chip then we can have 100000 different probes where the single stranded RNA can hybridize with DNA probes.

The predecessors were the macroarrays, which differ from microarrays in the physical size of the chip surface and the spots.

What is a microarray?   Developed primarily by Patrick O. Brown et al. at Stanford University. In 1995 and 1996, the first papers in which the term ‘microarray. Microarrays are used to survey the expression of thousands of genes in a single experiment . They are a simple method for visualizing which genes are likely to be used in a particular tissue at a particular time under a particular set of conditions. The term microarray originally referred to spotted cDNA arrays, but now it is used for any hybridization-based array.

Types of Microarrays Sample type Interaction 1. Antibodies antibody–antigen 2. Bacterial artificial DNA– DNA, DNA–RNA, chromosomes (BACs) DNA–protein 3. Carbohydrates sugar–protein, sugar–antibody,sugar–receptor 4. Cell extracts general biochemical, proteins 5. Enzymes enzyme–substrate, enzyme–effector, enzyme–inhibitor 6. Oligonucleotides DNA–DNA, DNA–protein, RNA–DNA, RNA–RNA, RNA–protein 7. PCR products DNA–DNA, DNA–RNA, DNA–protein 8. Peptides protein–protein, protein–RNA, antigen–antibody 9. Phage artificial DNA–DNA, DNA–RNA, chromosomes (PACs) DNA–protein 10. Proteins protein–DNA, protein–RNA, protein–receptor 11. Small molecules small-molecule–protein 12. tRNAs, rRNAs, mRNAs RNA–DNA, RNA–RNA, RNA–protein 13. Whole cells receptor–hormone, receptor–antibody, sugar–antibody 14. Yeast artificial DNA–DNA, DNA–RNA, DNA–protein chromosomes (YACs)  Extracted from: Microarray Technology, September 2004, Tod Martinsky

Principles of microarray analysis All microarray systems share the following key components: the array, which contains immobilized nucleic acid sequences, or ‘targets’.( Array). 2. one or more labelled samples or ‘probes’, that are hybridized with the microarray. (Hybridization). 3. a detection system that quantitates the hybridization signal. (Data collection, normalization, and analysis).

1. Array. Constructing the chip: nucleic-acid probes for each gene are attached in a specific position in a small array of 10 -100x thousands of probes on the chip each spot contains lots of identical DNA molecules or fragments (probe lengths range from 20 to 100s of bases) each of these molecules ideally should identify one gene or one exon in the genome (difficult due to families of similar genes in a genome) the spots are either printed on the microarrays by a robot, or synthesized by photo-lithography (similarly as in computer chip productions) or by ink-jet printing - CAN BE EXPENSIVE

cDNA microarray slide 1 cDNA microarray slide 2 spot for gene 201 GATATG... GATATG... ... ... spot for gene 576 spot for gene 576 TTCCAG... TTCCAG... ... ... Each spot contains many copies of a sequence along with its complement (not shown).

(side view from the table top) Plate with wells containing probes vacuum wash station microarray slides

The print head holds up to 32 pins The PixSys 5500 Arraying Robot (Cartesian Technologies) Robotic arm Vacuum hold-down platform (50 slide capacity) Vacuum wash station The print head holds up to 32 pins in a 8x4 format

2. Hybridization: Primary application - analysis of gene expression mRNA is extracted from biological samples and converted to fluorescently labeled copies (sample or control solution) labeled sample or control applied to microarray and hybridizes to the probe spots corresponding to the expressed genes

Hybridizing to Microarrays

3. Detection: laser scanner detects the level of fluorescence of each probe spot high fluorescence indicates that a particular gene is expressed at a high level little or no fluorescence indicates a gene that is expressed at a very low level or not expressed at all for that condition

microarray_scanner_200 colorimetric_scanner_600

increased expression decreased expression

4. Analysis (general): Example comparative DNA experiment: GREEN - Control DNA, either DNA or cDNA derived from normal tissue is hybridized to the target DNA. RED - Sample DNA, either DNA or cDNA derived from diseased tissue hybridized to the target DNA. YELLOW - combination of Control and Sample DNA, both hybridized to the target DNA. BLACK - neither the Control nor Sample DNA hybridized to the target DNA.21 Each spot = a particular gene. The location and intensity of a color will tell us whether the gene, or mutation, is present in either the control and/or sample DNA. It will also provide an estimate of the expression level of the gene(s) in the sample and control DNA.

Analysis (statistical) Sample microarray data matrix downloaded from microarray.org Channel 1 is green, Channel 2 red MRAT is the ratio of channel 2 intensity:channel 1intensity

Expression profiling: overall patterns of gene expression can be used in diagnosis Each column is from a different tumor. Each row represents one gene. Rows are clustered by similar expression pattern. these genes are higher expression in normal tissue than breast cancers these genes are lower expression in basal-like breast cancers than in normal tissue or luminal breast cancers

Using cDNA Microarrays to Measure mRNA Levels Microarray Slide Sample 1 ACCTG...G TTCTG...A ?????????? ?????????? ?????????? Spots (Probes) Unknown mRNA Sequences (Target) ?????????? ?????????? GGCTT...C ATCTA...A Sample 2 ?????????? ACGGG...T CGATA...G ?????????? ?????????? ?????????? ??????????

Extract mRNA Sample 1 Sample 2 ACCTG...G TTCTG...A ?????????? GGCTT...C ATCTA...A Sample 2 ACGGG...T CGATA...G

Convert to cDNA and Label with Fluorescent Dyes Sample 1 Sample 1 ?????????? ?????????? ACCTG...G TTCTG...A GGCTT...C ATCTA...A Sample 2 Sample 2 ACGGG...T CGATA...G

Mix Labeled cDNA Sample 1 Sample 2 ?????????? ACCTG...G TTCTG...A GGCTT...C ATCTA...A Sample 2 ?????????? ACGGG...T CGATA...G ?????????? ?????????? ?????????? ??????????

Hybridize cDNA to the Slide Sample 1 ACCTG...G TTCTG...A ?????????? ?????????? ?????????? GGCTT...C ATCTA...A ?????????? ?????????? ?????????? ?????????? Sample 2 ?????????? ?????????? ?????????? ACGGG...T CGATA...G

Excite Dyes with Laser Sample 1 Sample 2 ?????????? ?????????? ACCTG...G TTCTG...A GGCTT...C ATCTA...A ACGGG...T CGATA...G ?????????? ?????????? ?????????? ?????????? ?????????? ?????????? ?????????? ?????????? Sample 2 ?????????? ??????????

Scan Sample 1 ACCTG...G TTCTG...A GGCTT...C ATCTA...A ACGGG...T CGATA...G ?????????? ?????????? ?????????? ?????????? ?????????? ?????????? ?????????? ?????????? Sample 2 ?????????? ??????????

Quantify Signals Sample 1 Sample 2 7652 138 5708 4388 8566 765 1208 ACCTG...G 7652 138 TTCTG...A 5708 4388 GGCTT...C 8566 765 ATCTA...A 1208 13442 Sample 2 ACGGG...T 6784 9762 CGATA...G 67 239

Experimental design Replicates within the array Replicate arrays Sample 1 Sample 2 Sample 1 Sample 2 Net result - 4 data points/ “gene”

Microarray Can Answer On Questions in functional genomics : Which genes are expressed in which tissues? How is the expression of a gene affected by extracellular influences? Which genes are expressed during the development of an organism? How does gene expression change during development and differentiation? What is the effect of misregulated expression of a gene? What patterns of gene expression cause a disease or lead to disease progression? What patterns of gene expression influence response to treatment?

Applications of microarray analysis. Gene expression analysis. Detecting cancerous cells. Enzyme specificities and protein interactions. Forensics. study Natural Variations . Biomedical Applications and drug screening. Application in Microbial Ecology Research. Tissue Microarrays. Microarray applications in infectious disease. Microarray screening in food safety.

Thank You

Fig 1: Microarray used in Multi-Pathogen Identification (MPID)

Analysis: image quantitative analysis Figure extracted from the ScanAlyze User’s Manual: http://rana.lbl.gov/EisenSoftware.htm Analysis: image quantitative analysis each spot on the array is identified, its intensity measured and compared to the background (image analysis software) all the quantities related to some gene on arrays measuring the same conditions in repeated experiments have to be combined in one matrix, and the entire matrix has to be scaled to make different arrays comparable

Analysis issues (statistical) 1. Measurement repetition the number of samples is very large, but the number of times that each measurement is repeated is very small 2. Determination of spot intensity General - measure the median green or red intensity for each pixel and subtract the background intensity 3. Intensity ratios Usually the red and green intensities are converted to a ratio or a log ratio 4. Determination of relevant gene expression differences Use t-test type approach to determine the difference of the means between two data sets

HepG2 Hela Schematic of the preparation of sample data Isolate RNA Cy3 Cy3 Cy5 Cy5 Cy5 Cy5 Cy3 Cy3 1a,b 2a,b 3a,b 4a,b

Hela HepG2 Hela HepG2 Raw Data Hela HepG2 Hela HepG2 1a 3a

General approach to performing microarray experiment Formulate the biological question Choose the microarray platform cDNA,oligonugleotide Balance cost, repeatability, availability, Decide on level of replication Consider technical and biological source of error. Estimate how many replicates are needed to see an effect. Settle on an experimental design For two color, which treatments are contrasted against which?

Reach biological conclusion Perform low-level analysis -Extract numerical data from microarray image. -Normalize data to allow comparison of different arrays and dyes Perform high-level analysis -.Fit statistical model to estimate significance of differential Gene expression across treatments and treatment interaction. -cluster gene expression profile and treatment profile. - Reach biological conclusion

Schematic of hybridization for a comparative microarray experiment: Extracted from EBI introductory microarray web article by Alvis Brazma, Helen Parkinson, Thomas Schlitt, Mohammadreza Shojatalab: http://www.ebi.ac.uk/microarray/biology_intro.html#Microarrays