Bioinformatics: DNA Microarrays Applications

The main general applications of DNA Microarrays are:

1- Determining the expression patterns of Proteines by looking at mRNAs.
2- For Genotyping, detection of different variations in gene sequences (Single Nucleotide Polymorphisms -SNP- for example).

An introduction to Microarrays can be found here in this post.

To achieve this we have to do a parallel hybridization analysis, where hybridization is the way to detect whether a particular sequence is present in a DNA sample or not.

In order to do a parallel hybridization analysis, we use a large number of DNA Oligomers that are fixed to known locations on a rigid support.

One DNA Chip or Array may contain 100.000 probe oligomers.

Applications of DNA microarrays include:

1- Investigating cellular states and processes: Patterns of expression that change with cellular
state can give clues to the mechanisms of processes such as sporulation, or the change
from aerobic to anaerobic metabolism.

2- Diagnosis of disease: Testing for the presence of mutations can confirm the diagnosis of a
suspected genetic disease, including detection of a late-onset condition such as
Huntington disease, to determine whether prospective parents are carriers of a gene that
could threaten their children.

3- Genetic warning signs: Some diseases are not determined entirely and irrevocably by
genotype, but the probability of their development is correlated with genes or their
expression patterns. A person aware of an enhanced risk of developing a condition can in
some cases improve his or her prospects by adjustments in lifestyle.

4- Drug selection: Detection of genetic factors that govern responses to drugs, that in some
patients render treatment ineffective and in others even cause serious adverse reactions.

5- Classification of disease: Different types of leukaemia can be identified by different patterns
of gene expression. Knowing the exact type of the disease is important in selecting optimal
treatment.

6- Target selection for drug design: Proteins showing enhanced transcription in particular
disease states might be candidates for attempts at pharmacological intervention (provided
that it can be demonstrated, by other evidence, that enhanced transcription contributes to
or is essential to the maintenance of the disease state).

7- Pathogen resistance: Comparisons of genotypes or expression patterns, between bacterial
strains susceptible and resistant to an antibiotic, point to the proteins involved in the
mechanism of resistance.

Any questions comment.

Bioinformatics:Genomics:Microarrays

Bioinformatics:Genomics:Microarrays:


Microarrays are micro-chips used in molecular biology and medecine to achieve a lot of useful tests including gene expression.

To inderstand this technology, we should put a thing in our minds, wich is:
1- Not all the genome codes for proteines.
2- Not all genes always turned on.

We use the term Gene Expression to describe the transcription of the information containes within the DNA into mRNA, which is after translated to proteines.

Scientists have to study these genes to identify which of theme are expressed and which are not.

Gene expression is a highly complex and tightly regulated process that allows a cell to respond dynamically both to environmental stimuli and to its own changing needs.

This mechanism acts as both an "on/off" switch to control which genes are expressed in a cell as well as a "volume control" that increases or decreases the level of expression of particular genes as necessary.

So thats what DNA microarrays are used for.

To inderstand such a process, there is nothing better then animations...!

Here are some animation that i found very useful to fully understand Microarrays:

Note: The first animation is pretty simple and good for beginners:

Animation1

Animation2

Animation3

Any question, you're welcome.