We're focusing here in Part 2 on how scientists study gene expression, including two resources
at NCBI that contain expression data, UniGene and GEO, the Gene Expression Omnibus.
But, first, one slide about why we study gene expression.
And it is for the reasons you would expect, including correlation with disease, and some
you might not immediately think about, such as applications to genetically modified organisms.
You can artificially group studies into those that focus on a small number of genes and
those that try to sample as many genes as possible in the tissue or cell type being
investigated.
These older, but still useful, techniques -- Northern and Western blots -- allow a qualitative
measure of changes in gene expression, but these types of image data are not deposited
at NCBI.
Another technique uses cDNA cloning, where full-length mRNA, or messenger RNA, is isolated
and the corresponding cDNA sequence is deposited at NCBI.
One example of a global, or batch, approach is the generation of expressed sequence tags,
or ESTs.
For our purposes, just know that these are relatively short sequences, say, 200-500 bases,
and that they often represent only part of a given gene.
So let's say that you are a scientist and you have generated a large number of EST sequences
from liver tissue.
You can submit these sequences, in bulk, to the NCBI EST database.
Each sequence gets its own GenBank record, including an accession number, and the record
notes the tissue source.
One important step that we take at NCBI is to cluster ESTs based on their sequence, which
has the effect of placing ESTs from the same gene into the same cluster.
This automated process occurs in the UniGene database.
Here we have a UniGene record for the REL gene, or R-E-L gene, containing 47 ESTs in
the cluster.
You can see that they are from several different tissues, including kidney, lymph, and blood.
Okay, that's all for Unigene.
Let's look at other high throughput methods for generating gene expression data.
Of course, there are many types of high throughput technologies.
We're going to focus on technologies and data that are submitted to GEO, the Gene Expression
Omnibus.
This slide is here simply to point out where to find GEO documentation, including some
featured projects.
The most common types of data submitted to GEO are those from studies of global expression
of protein coding genes, using microarrays.
So I'm going to give some background on how these arrays work.
The text here is for your reference; I'm going to focus on the image, where each position
in the array represents the position of a bit of unique sequence for a gene.
Binding of the applied sample mRNA, which was converted to a cDNA, to a gene sequence
is measured as light intensity and color.
In this example, there are two cDNA preps: one from control cells and one from cells
treated in some way.
They are labeled so that the bound control cDNAs emit green light and the treated sample
cDNAs emit red light.
Light intensity and color is measured for each spot.
Let's look at an example experiment.
Here we have a research team that studies a gene called TNF, tumor necrosis factor.
It is an important gene in tumor growth and they want to look at global gene expression
in tumor cells that grow in mice with and without the TNF gene.
If you want an analogy to help understand the experiment...Say that TNF is a middle
school teacher.
We can study the role of Mr. TNF by observing his students when he is present in the classroom
and when he is absent.
The approach is global, because we want to know the behavior of each and all students.
In the real experiment, they injected wild type mice and mice lacking TNF with tumor
cells.
After a period of growth, they harvested mRNA from tumor cells from the two types of mice
and determined the overall gene expression using microarrays.
The experiment generated four samples, where each sample is a pool of mRNA from a replicate.
The mRNA is processed and labeled so that it can be applied to a microarray.
The samples are applied in pairs, a sample from TNF+ and TNF- mice is applied to each
microarray.
These arrays, sometimes called chips, are usually purchased from biotech companies and
later we will see that in GEO they are called platforms.
This is a closeup of spots for nine different genes.
Each spot where a cDNA from the two samples binds, emits two colors of light.
Here there is more cDNA from the wild type sample, remember, those were labeled with
green dye.
When the experiment is completed, Dr. Pitroda is ready to submit the data to GEO.
We'll pick up with that GEO submission in the Part 3 video.
Click on the note to open that video in a new window.