Bioinformatics FAQ (Frequently Asked Questions) - Glossary of bioinformatics terms
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Robotic technology is employed in the preparation of most arrays.
The DNA sequences are bound to a surface such as a nylon membrane or
glass slide at precisely defined locations on a grid. Using an
alternate method, some arrays are produced using laser lithographic
processes and are referred to as biochips or gene chips. The
composition of DNA on the arrays is of two general types:
- Oligonucleotides or DNA fragments (approximately 20-25
nucleotide bases). These arrays are frequently used in genotyping
experiments. The sequences of alternate gene forms may be included
for detection of mutations or normal variants (polymorphisms).
- Complete or partial cDNA (approximately 500-5 000 nucleotide
bases). These arrays are generally used for relative gene
expression analysis of two or more samples; however,
oligonucleotide-based arrays may also be used for these studies.
DNA samples are prepared from the cells or tissues of interest.
For genotyping analysis, the sample is genomic DNA. For expression
analysis, the sample is cDNA, DNA copies of RNA. The DNA samples are
tagged with a radioactive or fluorescent label and applied to the
array. Single stranded DNA will bind to a complementary strand of
DNA. At positions on the array where the immobilized DNA recognizes
a complementary DNA in the sample, binding or hybridization occurs.
The labeled sample DNA marks the exact positions on the array where
binding occurs, allowing automatic detection. The output consists of
a list of hybridization events, indicating the presence or the
relative abundance of specific DNA sequences that are present in the
sample.
What is a
homologue?
"Homology"
is a much-misused term and existed in biology long before the
notion of protein sequences. Strictly homology cannot be qualified;
it is not correct to state that two proteins are "30% homologous"
with each other, for example. If we could look back far enough in
the evolutionary histories of any two molecules under comparison, we
would be guaranteed to find a common ancestor eventually, but this
is not true homology. An example of this would be the relationship
between two variants of a single ancestral enzyme resulting from a
gene duplication event. As a rule-of-thumb, true homology should
be assigned only when the feature which leads us to suspect a
relationship between molecules is one we consider likely to have
derived from the molecules' common ancestor. To quote Page
and Holmes [Molecular Evolution: A Phylogenetic
Approac, Roderick D. M. Page and Edward C. Holmes; Blackwell
Scientific; ISBN 0865428891]:
"The classic molecular example is the parallel
evolution of amino acid sequences in the lysozyme enzyme in
leaf-eating langur monkeys and in cows. Both animals have
independently evolved foregut fermentation using bacteria, and in
both cases lysozyme has been recruited to degrade these bacteria.
Therefore, langur and cow lysozymes are homologous as genes;
however, as digestive enzymes they are not homologous because this
functionality was not present in the ancestral lysozyme"
Although sequence determines structure, it is possible
for two proteins to have very different sequences and functions and
share a common fold. In fact, most gene products with similar
three-dimensional structures are insufficiently similar at the
sequence level for true homology or analogy (non-homologous
similarity) to be distinguished.
What is an
ontology?
Biology is changing from being a descriptive to an analytical
science. Accurate and consistent descriptions are, however, vital to
analysis. The idea of ontologies has been co-opted from philosophy and artificial
intelligence to partition bioinformatic knowledge in a way which
can be reliably navigated by computers.
This
preprint of a review by Ele
Holloway of the European
Bioinformatics Institute gives a more detailed insight into the
varied approaches to ontologies in bioinformatics by covering a
recent meeting on the subject. The final version appears in Comparative
and Functional Genomics.
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