1. Genomics I: The Transcriptome
RNA Expression Analysis
Determining genomewide RNA expression levels

2. Genomewide expression analysis
Goal: to measure RNA levels of all genes in genome
RNA levels vary with the following:
Cell type
Developmental stage
External stimuli
Time and location of expression provide useful information as to gene function
Once every gene in a genome has been identified, it becomes feasible to measure each gene’s expression. One of the first goals along this line has been to measure the steady-state abundance of RNA made from each gene. There have also been ongoing attempts to measure the level of all proteins. (See the chapter on proteomics.) The levels of RNA vary depending on the cell type, the developmental stage, environmental stimuli, etc. For example, the RNAs expressed in a heart cell differ greatly from those expressed in a brain cell, and the RNAs expressed in fetal blood differ from those expressed in adult blood. In addition, exposure to high heat triggers the production of heat-shock RNAs, which are not present under normal conditions. Therefore, determination of the RNA levels found at a particular time and in a specific cell or organ can provide important information as to the function of the genes responsible for this expression. In addition, the spectrum or profile of RNAs found in a particular cell can be used as a means of disease diagnosis. For example, different types of cancer have been shown to have different RNA profiles. (See the example later in this chapter.)

3. Genomics expression analysis methods
Microarrays
Hybridization based
RNA-seq
Direct sequencing of cDNAs
SAGE (Serial Analysis of Gene Expression)
Sequence fragments of cDNAs
Real-time PCR
There are several different ways that have been developed to determine genomewide RNA expression levels. The most commonly used technique involves the attachment of DNA to a solid support and the hybridization of labeled RNA or DNA to the bound DNA. When thousands of different DNAs are attached to a solid support, it is known as a microarray. In this chapter, we will discuss how different types of microarrays are made and how they are used, and we will give some examples of microarray experiments. Two other genomics expression techniques use a step that involves DNA sequencing. These techniques are called Serial Analysis of Gene Expression (SAGE) and Massively Parallel Signature Sequencing (MPSS). We will give an overview of how these techniques are performed. Finally, we will discuss real-time PCR, which is increasingly used as a means of verifying RNA expression levels initially detected through microarray analysis.

4. Macroarray Analysis

5. Macroarray Analysis

6. Microarray Analysis of Transcription

7. Animation

8. Northern blots vs. microarrays
target –
loading –
control
Global expression analysis: Northern blot
Limited by number of probes that can be used simultaneously
Global expression analysis: microarrays
RNA levels of every gene in the genome analyzed in parallel
Microarrays permit the simultaneous analysis of the RNA expression of thousands of genes. For fully sequenced genomes, microarrays can be used to analyze the expression of every gene. Northern blots, on the other hand, are limited by the number of lanes on the gel and by the number of probes that can be used on the same blot. Northern blots normally have 20–40 lanes, and no more than three probes can be used simultaneously. Thus, microarrays increase the throughput by several orders of magnitude.

9. Basics of microarrays DNA attached to solid support RNA is labeled
Glass, plastic, or nylon
RNA is labeled
Usually indirectly
Bound DNA is the probe
Labeled RNA is the “target”
Another difference between microarrays and Northern blots is that microarrays have DNA attached to a solid support, which can be glass, plastic, or a nylon membrane, while the RNA is labeled either directly or through a cDNA intermediary. Thus, on the microarray, the bound DNA is in excess. To be consistent with the terminology of Northern blots, for microarrays the bound DNA is referred to as the “probe,” and the labeled RNA or cDNA is called the “target.”

10. Microarray hybridization
mRNA
cDNA
DNA
microarray
samples
Usually comparative
Ratio between two samples
Examples
Tumor vs. normal tissue
Drug treatment vs. no treatment
Embryo vs. adult
Most microarray experiments compare the RNA populations found in two different samples. The samples can be tumor tissue and normal tissue, cells that have received a drug treatment and cells that have not, cells at two different points in the cell cycle, etc.

11. Two major types of microarrays
cDNA arrays- PCR product corresponding to a portion of a cDNA is immobilized on the slide
oligonucleotide arrays- oligonucleotide complementary to transcript is synthesized on slide or immobilized on the slide

12. How microarrays are made: spotted microarrays
DNA mechanically placed on glass slide
Need to deliver nanoliter to picoliter volumes
Too small for normal pipetting devices
Robot “prints,” or “spots,” DNA in specific places
Different technologies are being used for the production of microarrays. The most commonly used microarray technologies are mechanical spotting and photolithography. Mechanical spotting involves placing very small quantities of DNA on glass slides. The volumes of liquid in which the DNA is suspended are in the nanoliter to picoliter range, which is too small for normal pipetting devices. Robots have been adapted to handle these small volumes and to “spot” or “print” them at precisely determined locations on glass slides.

13. DNA spotting I DNA spotting usually uses multiple pins
DNA in microtiter plate
DNA usually PCR amplified
Oligonucleotides can also be spotted
Most robotic spotters use pins that act by capillary action similar to that of fountain pens. Multiple pins are mounted together and dipped simultaneously into DNA aliquoted into the different wells of a microtiter plate. The DNA in the wells has usually been amplified from cDNA or genomic DNA, using PCR. Oligonucleotides can also be spotted in this way.

14. DNA spotting II Pins dip into DNA solution in microtiter wells
Robot moves pins with DNA to slides
Robot “prints” DNA onto slide
DNA sticks to slide by hydrostatic interactions
Same spots usually printed at different locations
Serves as internal control
Pins washed between printing rounds
Hundreds of slides can be printed in a day
After dipping the pins into the DNA solution in the microtiter wells, the robot moves the pins to a set of glass microscope slides. It brings the pins into contact with a slide, and the DNA sticks through hydrostatic interactions. The robot then returns to the microtiter wells, draws up more DNA, and prints it on the next slide. Normally, the same DNA is printed in more than one spot on the same slide. This repetition acts as an internal control for the uniformity of the hybridization reaction. After printing is completed for one set of DNAs, the pins are washed and the process is begun again with the next set of DNAs. Commercial spotters can handle multiple microtiter plates and can print hundreds of slides in a day.

15. Commercial DNA spotter
In this microarray spotter made by GeneMachines®, microtiter plates are stacked on the left, awaiting the pins, which are poised over a set of microscope slides. The action of printing microscope slides is shown in the next slide.

16. How microarrays are made: Affymetrix GeneChips
Oligonucleotides synthesized on silicon chip
One base at a time
Uses process of photolithography
Developed for printing computer circuits
The synthesis of oligonucleotides directly on a solid support was pioneered by Affymetrix®. The synthesis is performed by photolithography, a process that is used to print computer circuits—hence the name for the Affymetrix microarrays: “GeneChips®.”

17. Affymetrix GeneChips Oligonucleotides
Usually 20–25 bases in length
10–20 different oligonucleotides for each gene
Oligonucleotides for each gene selected by computer program to be the following:
Unique in genome
Nonoverlapping
Composition based on design rules
Empirically derived
On Affymetrix GeneChips, there are between 10 and 20 oligonucleotides for each gene. The choice of oligonucleotides is determined using a computer program that searches for nonoverlapping stretches of bases that are unique in the genome (in order to prevent cross-hybridization). Furthermore, the computer searches for oligonucleotides that will fit empirically derived design rules that dictate the ratio of G–C pairs vs. A–T pairs and that attempt to reduce the likelihood that the oligonucleotide will hybridize to itself, creating hairpin structures.

18. Photolithography Light-activated chemical reaction Custom masks
For addition of bases to growing oligonucleotide
Custom masks
Prevent light from reaching spots where bases not wanted
Mirrors also used
NimbleGen™ uses this approach
lamp
mask
chip
In photolithography, each step of the oligonucleotide synthesis process is activated by light. In the Affymetrix manufacturing process, masks are used to allow bases to be added to growing oligonucleotides at specific locations on the chip. The masks prevent light from reaching locations on the silicon wafer where a base is not to be added that round. Instead of masks, digitally controlled mirrors can be used to shine light only on those spots where activation is desired. The biotechnology company, NimbleGen™ is using this approach to produce chips through photolithography.

19. Example: building oligonucleotides by photolithography
light
Want to add nucleotide G
Mask all other spots on chip
Light shines only where addition of G is desired
G added and reacts
Now G is on subset of oligonucleotides
To understand how photolithography works with masks we use an example of adding the base G. A mask is used that prevents light from reaching all the oligonucleotides on the chip where G is not supposed to be the next base. When light is turned on, it reaches only those positions where a G is to be added. The light activates the growing chain, allowing a base to be added. A solution containing the base G is then added to the chip, and it becomes attached to the oligonucleotides activated by the light.

20. Example: adding a second base
light
Want to add T
New mask covers spots where T not wanted
Light shines on mask
T added
Continue for all four bases
Need 80 masks for total
20-mer oligonucleotide
To add the base T, a new mask is used that covers all spots except those where a T is needed. Light is then shined on the mask, activating the specified oligonucleotides, and the T is then added. This process is performed sequentially for all four bases, until all of the oligonucleotides on the chip are synthesized. Thus, 80 custom masks are needed to make a chip that has 20-base-long oligonucleotides. When mirrors are used to control the photolithography process, there is no need to manufacture the custom masks. This means that there is no cost associated with changing the sequences on the chip. The use of mirrors also allows for much longer oligonucleotide chains to be synthesized on chips.

21. Ink-jet printer microarrays
Ink-jet printhead draws up DNA
Printhead moves to specific location on solid support
DNA ejected through small hole
Used to spot DNA or synthesize oligonucleotides directly on glass slide
Use pioneered by Agilent Technologies, Inc.
Another method for depositing DNA on glass slides is the use of ink-jet printer technology. Ink-jet printers are designed to deposit very small quantities of ink in precise locations. As adapted for microarray spotting, the printhead draws up a small amount of DNA, moves to a particular point on the slide, and ejects the DNA through a very small hole. This technology has also been adapted to provide for the synthesis of oligonucleotides on slides. After each base is added through the printhead to the growing oligonucleotide, the slide is washed free of excess nucleotides, and the exposed bases are primed for the addition of the next nucleotide. Agilent Technologies has pioneered the use of ink-jet printing for making microarrays. The primary drawback of this approach as compared with photolithography is that the maximum number of spots on a slide is far fewer with the ink-jet printing of DNA.

22. Comparisons of microarrays
This slide compares the three methods for preparing microarrays. The top panel illustrates photolithography, the middle panel illustrates mechanical printing, and the bottom panel illustrates ink-jet printing.

23. Comparison of microarray hybridization
Spotted microarrays
Competitive hybridization
Two labeled cDNAs hybridized to same slide
Affymetrix GeneChips
One labeled RNA population per chip
Comparison made between hybridization intensities of same oligonucleotides on different chips
In addition to the differences in their manufacturing, spotted microarrays and GeneChips (as well as NimbleGen chips) differ in how the hybridization is performed. For spotted microarrays, usually the two labeled targets to be compared are hybridized to the same microarray. This procedure is known as competitive hybridization. For GeneChips, only one labeled target is hybridized to each chip. Comparisons are made at the analysis stage between hybridization intensities measured on two different chips. With competitive hybridization, one is measuring the relative difference between the signal intensity of two targets binding to the same spot of DNA. The practical reason for this approach is that there is often variability in the quality of the spotted DNA, in terms of amount and integrity. This measurement compensates for differences in the quality of the spot. Microarrays made with photolithography tend to have higher reproducibility from slide to slide, making competitive hybridization less important.

24. Target labeling: fluorescent cDNA
cDNA made using reverse transcriptase
Fluorescently labeled nucleotides added
Labeled nucleotides incorporated into cDNA
Labeling of the target RNA is usually performed by generating a single-stranded cDNA, using the enzyme reverse transcriptase. One method of labeling uses fluorescently labeled nucleotides that are incorporated into the cDNA during the reverse-transcription reaction. This is generally the way the nucleotides labeled with the dyes Cy3 and Cy5 are incorporated into targets used in competitive hybridization.

25. Target labeling: cRNA + biotin
cDNA made with reverse transcriptase
Linker added with T7 RNA polymerase recognition site
T7 polymerase added and biotin labeled RNA bases
Biotin label incorporated into cRNA +
Another alternative for labeling the target RNA population is first to make double-stranded cDNA and then to use a viral RNA polymerase to make cRNA. To accomplish this task, a linker is added to the cDNA that contains the recognition site for an RNA polymerase (e.g., T7 RNA polymerase). Labeling is done by adding modified RNA bases to the RNA polymerase reaction. This type of labeling is used for Affymetrix GeneChips as well as NimbleGen chips. The production of cRNA using T7 polymerase involves amplification of the original RNA population.

26. Labels Cy3 and Cy5 Biotin Fluoresce at different wavelengths
Used for competitive hybridization
Biotin
Binds to fluorescently labeled avidin
Used with Affymetrix GeneChips
Different labels are incorporated depending on the type of microarray experiment that is being performed. For experiments in which two different RNA populations are analyzed on the same microarray (competitive hybridization), two dyes are used that fluoresce at different wavelengths. The most commonly used dyes are Cy3 and Cy5. Labeling for hybridization to Affymetrix GeneChips and NimbleGen chips uses biotin-conjugated RNA bases. Fluorescently labeled avidin is then bound to the biotin.

27. Spotted-microarray hybridization
Control and experimental cDNA labeled
One sample labeled with Cy3
Other sample labeled with Cy5
Both samples hybridized together to microarray
Relative intensity determined using confocal laser scanner
For spotted-microarray hybridization, one target RNA is labeled with the fluorescent dye Cy3 and the other target with the fluorescent dye Cy5. Both targets are hybridized to the same microarray. The relative intensity of the hybridization is determined using confocal laser scanning microscopy.

28. Scanning of microarrays
laser
Confocal laser scanning microscopy
Laser beam excites each spot of DNA
Amount of fluorescence detected
Different lasers used for different wavelengths
Cy3
Cy5
detection
Confocal laser scanning microscopy is used to determine the amount of fluorescently labeled target that has hybridized to the DNA on the microarray. In this process, a laser beam is aimed at each spot on the microarray. The fluorescent light that is emitted upon excitation of the dye passes through a pinhole that effectively eliminates all surrounding light. This condition permits a precise determination of the level of fluorescence coming from the hybridized target at a single spot on the microarray. For competitive hybridization, the microarray is scanned twice, using different wavelengths for each of the fluorescent dyes Cy3 and Cy5.

29. Analysis of hybridization
Results given as ratios
Images use colors:
Cy3 = Green
Cy5 = red
Yellow
Yellow is equal intensity or no change in expression
Once the levels of fluorescence are determined for each spot, software is used to compare the relative levels for the two dyes. This comparison is usually given as a ratio and is depicted by gradations of color. The Cy3 hybridization is normally shown in green, and the Cy5 hybridization is given as red. These colors are actually pseudocolors generated by the software used to analyze the output from the confocal laser scanning microscope. Thus, when there are equal levels of hybridization, the resulting color is yellow. This condition indicates that there has been no change in the levels of RNA between the two experimental conditions that are being tested.

30. Example of spotted microarray
RNA from irradiated cells (red)
Compare with untreated cells (green)
Most genes have little change (yellow)
Gene CDKN1A: red = increase in expression
Gene Myc: green = decrease in expression
CDKNIA
An experiment performed with spotted cDNA microarrays was the comparison of RNA from cells that had been subjected to radiation (Cy5 = red) with RNA from untreated control cells (Cy3 = green). Most spots on the microarray were yellow indicating no change in gene expression. The spot with the gene CDKN1A was red, indicating an increase in its expression, while the spot where the myc oncogene was spotted was green, indicating that its expression had decreased.
MYC
-Flash animation
-YouTube video

31. Analysis of cell-cycle regulation
Yeast cells stopped at different stages of cell cycle
G1, S, G2, and M
RNA extracted from each stage
Control RNA from unsynchronized culture
An example in which far more genes were analyzed under several different conditions was the determination of gene expression changes during the cell cycle. Yeast cells were arrested at each of the cell cycle checkpoints G1, S, G2, and M. RNA was extracted from the arrested cells and labeled with Cy3. The control cells labeled with Cy5 were unsynchronized, thus representing cells at all different points of the cell cycle.

32. Results of yeast cell-cycle analysis
800 genes identified whose expression changes during cell cycle
Grouped by peak expression
M/G1, G1, S, G2, and M
Four different treatments used to synchronize cells
All gave similar results
Results from Spellman et al., 1998; Cho et al., 1998
Of the approximately 6,000 yeast genes on the microarray, over 800 showed changes in expression at some point during the cell cycle. These genes were then grouped, or “clustered,” based on when their expression rose and fell during the cell cycle. Comparison of results from four different treatments used to synchronize the cells found the same genes always clustered together.

33. Cell-cycle regulated genes
Brown and Botstein, 1999
Alpha
cdc15
cdc28
Elu
M/G1 G1 S G2 M
Each gene is a line on the longitudinal axis
Treatments in different panels
Cell-cycle stages are color coded at top
Vertical axis groups genes by stage in which expression peaks
The results were presented in a figure in which the expression of each gene was represented as a series of colors indicating the change in hybridization relative to its level in the control unsynchronized cells. Red indicates an increase in expression, and green indicates a decrease in expression. The algorithms used to cluster the genes are described in the chapter on bioinformatics. The four different treatments used to synchronize the cells are shown in separate panels in the figure. At the top of each panel, the different stages of the cell cycle are indicated by colored bars. Along the vertical axis, genes with similar expression patterns are grouped together.

34. Affymetrix GeneChip experiment
RNA from different types of brain tumors extracted
Extracted RNA hybridized to GeneChips containing approximately 6,800 human genes
Identified gene expression profiles specific to each type of tumor
An example of the use of Affymetrix GeneChips was an attempt to determine whether differences in gene expression could be used to diagnose brain tumors. RNA was extracted from biopsies of four different types of brain tumor. The labeled target was hybridized to GeneChips that contained approximately 6,800 human genes. Expression profiles were analyzed to identify patterns that were specific to each type of tumor.

35. Profiling tumors
Image portrays gene expression profiles showing differences between different tumors
Tumors:
MD (medulloblastoma)
Mglio (malignant glioma)
Rhab (rhabdoid)
PNET (primitive neuroectodermal tumor)
Ncer: normal cerebella
Across the top of the image are the four different types of tumors: medulloblastoma (MD), malignant glioma (Mglio), rhabdois (Rhab), and primitive neuroectodermal (PNET). Genes that had expression patterns specific to each type of tumor are listed along the vertical axis. The colors represent intensities read from the GeneChips, with red being the highest intensity and purple the lowest (shown on the bar at the bottom of the image). The algorithms used to cluster the genes are described in the chapter on bioinformatics. Very clear differences were found in the expression profiles of the four tumor types.

36. Cancer diagnosis by microarray
Gene expression differences for medulloblastoma correlated with response to chemotherapy
Those who failed to respond had a different profile from survivors
Can use this approach to determine treatment
60 different samples
A more detailed analysis was performed by the same authors for a single type of tumor, medulloblastoma. RNA from 60 different tumor samples was analyzed. The response to chemotherapy was known for each of the tumors. Analysis of the gene expression profiles indicated that it was possible to correlate specific gene expression patterns with response to chemotherapy: Patients who failed to respond had a different expression profile than those who did respond and survived longer. This result is shown in the graph at the top of the image and the clustered expression profiles beneath it. This type of analysis holds the promise that in the future, microarrays could be used to determine which tumors are likely to respond to different treatments.

37. Analysis of microarray results
Inherent variability: need for repetition
Biological and technical replicates
Analysis algorithms
Based on statistical models
Means of generating hypotheses that need to be tested
A feature of all microarray platforms is their inherent variability from experiment to experiment. The variability arises in part from the variation in the amount and quality of each probe, particularly for spotted microarrays. Even for oligonucleotides generated by photolithography, there can be variability in their manufacturing. But variability can also arise from differences in the abundance of RNA because of stochastic or environmental factors. For these reasons, it is important that all microarray experiments be repeated several times. There are two types of replicates: biological and technical. In a biological replicate, the entire experiment is repeated, while in a technical replicate the same labeled target is used on two different microarrays. Technical replicates can be useful in detecting manufacturing defects in microarrays. Biological replicates are essential for identifying variations that arise from some aspect of the biological process under study. There are several different algorithms used to analyze microarray results. Some are designed specifically for competitive hybridization experiments, while others are designed for single hybridization experiments. All are based on statistical models and are designed to identify significant differences in expression patterns. Ultimately, microarray experiments should be viewed as a means of generating hypotheses that need to be tested through independent approaches. Once a gene, or genes, has been identified with a particular expression profile, other techniques, such as real-time PCR, can be used to verify the expression. Then reverse genetic approaches can be used to determine the effect of modulating the gene’s expression pattern on the organism’s phenotype.