About genomics and getting started

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About genomics and getting started
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Contents

• What is genomics?
• Why is genomics important?
• How did genomics start?
• Basic background concepts

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What is genomics?

• The term genomics means different things to
  different people. Furthermore, the meaning has
  changed over time, causing a lot of confusion.
• The word genome was coined in 1920 by H. Winkler
  to concatenate the words GENes and chromosOMEs
  (Genomics 1997).
• The term genomics was coined much later, in 1986,
  when it was proposed to represent both a new
  discipline and a new journal that was being
  planned (McKusick and Ruddle 1987).

There are now a large number of genomics-related
journals in publication.
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Definitions

• The original definition of genomics as envisioned
  by McKusick and Ruddle was
• a marriage of molecular and cell biology with
  classical genetics and is fostered by
  computational science. 1
• But here are a few other definitions that may be
  helpful in trying to understand this field
• Big (large scale) molecular biology
• a set of evolving technologies that allow
  researchers to decode the DNA sequence, or
  blueprint, of any organism (Kamer 2000)
• a new science that studies whole genomes by
  integrating the traditional disciplines of
  cytology, Mendelian genetics, quantitative
  genetics, population genetics, and molecular
  genetics with new technology from informatics and
  automated robotic systems. The purpose of genomic
  research is to learn about the structure,
  function and evolution of all genomes, past and
  present (Liu 1998).

1For more detail see McKusick VA and Ruddle FH
(1987) A new discipline, a new name, a new
journal. Genomics 1 (1) 1-2.
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A note of caution
The term genomics can mean different things to
various people or in different contexts. In
addition, the word is often misused or overused.
Be careful to clearly define your meaning when
using it in formal situations (e.g proposals).
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Why is genomics important?It has created new
knowledge and data at a speed unprecedented in
the history of science
Figure. Growth of the International Nucleotide
Sequence Database Collaboration (includes
GenBank, the European Molecular Biology
Laboratory, and the DNA Databank of Japan), in
billions of base pairs.
From The National Center of Biotechnology
Information, announcing that the database had
exceeded 100 gigabases of data.
http//www.ncbi.nlm.nih.gov/Genbank/index.html,
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Genomics has changed the paradigm of how research
is conducted, both in terms of scale..
The combination of new technologies and the
amount of data available is allowing for
experimentation on a scale previously
unimaginable (for example, entire genomes at
once).
At left is an example of a microarray chip.
These chips can now be made to contain up to
300,000 elements (DNA or RNA segments, for
example) per just over a square centimeter,
essentially allowing a researcher to view a whole
genome at once (at one point in time, or in
response to a particular stimuli, etc.).
Figure from Alba R et al. (2004).
Note microarrays will be further discussed in
later chapters
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. and in terms of perspective
Making possible systems approaches to
biological questions by integrating different
kinds of information (sequence, function,
expression, gene networks and structure, etc. )
from a whole genome or even genomes from many
different organisms.
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Resulting in new approaches to experimental
science.
One result of this, as correctly predicted by
Michelmore (2000) and others, has been that
hypotheses can be derived and even tested through
in silico analyses of databases.
Testing of hypotheses will still require
detailed phenotyping, but experimental studies
will access a broad range of new tools capable of
global analyses of RNAs, proteins, and
metabolites rather than a gene-by-gene or
protein-by-protein approach. Michelmore R (2000)
Genomic approaches to plant disease resistance.
Current Opinion in Plant Biology 3 125-131
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The unifying power of genomics
One of the key initial discoveries in the
beginning of genomics research was the discovery
of a high amount of conservation of sequence
among all organisms, much more than was expected
at the time. This, together with the ability
to use whole-genome information of many types, is
leading to more cross-disciplinary research and
collaborations, integrating many of the
biological sciences.
Animals as different as nematodes, flies and
mammals use similar genes for similar
developmental purposes (Holland 1999).
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Tying together information across species
Scientists, crops, and information are now
connected in ways previously not possible
In the pre-genomics era, scientists usually
worked on a very specific concept, such as a
particular plant species or even one particular
gene. Now that we know the great extent to which
plants and gene functions are conserved (in
common) a scientist can take advantage of (and
therefore must be aware of) information in other
plants. This means one must try to keep current
with a large amount of ongoing research, however.
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Orphan plant research benefits
The ability to share information across species
is a great advantage for so-called orphan
plants for which previously there was little
information available. This is particularly
providential as these crops tend to be very
important to developing countries, where money to
fund research is less available (DeVries
Toenniessen 2001).
Sweet potato, tef and millet examples of orphan
crops
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Tying together information across species an
example
This figure has become the classic example of
comparative genomics. It depicts how many of the
genomes in the grass family can be described in
terms of corresponding to the rice genome.
Although by no means absolute, knowing the
location or function of a gene in one of the
grasses can have predictive value for the other
grasses. We will discuss this further in section
4. (From Gale and Devos 1998).
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Tying together information across disciplines
Evolutionary biology
Genetics
Genomics
Metabolic processes
Cell biology
When you look at an organism as a whole, on a
genomic scale, it becomes difficult and
unnecessary to separate the processes of life
into disciplinary divisions. Thus, genomics gives
us a unified perception of life, possibly
impacting how we teach science as well.
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The unifying necessity of genomicscost
In addition to the way genomics research can tie
together the biological sciences with new
information that cuts across traditional
disciplines, genomics encourages, even mandates,
interdisciplinary and highly collaborative
research for another reason the price tag. The
costs of the equipment and people needed to carry
out these large scale projects is prohibitive for
any single researcher.
Large multi-institution and multi-country
collaborations are now typical.
Example The Arabidopsis Genome Initiative (AGI)
which accomplished the sequencing of the first
plant genome (see http//www.arabidopsis.org for
more information).
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The potential of plant genomics

• The general public is more aware of the potential
  of genomics in the medical arena. It is, for
  example, plausible that in the near future
  personal, specifically designed treatment and
  preventative health plans will be based on a
  persons own genome sequence.
• However, the results of plant genomics could be
  equally profound. New information about gene
  function and organization could lead to the
  development of plants that
• Are more resistant to pests and disease
• Yield better under conditions of drought or
  nutrient-poor soil
• Contain higher proportions of nutritional
  compounds that are important to human health
• --gt Potentially leading to the day when hunger
  and malnutrition are obsolete

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The power of public information

• A key characteristic of genomics has been that
  much of the new data and information is publicly
  available via the Internet. This has
• greatly increased the speed of research since
  data can be accessed immediately
• reduced redundancy in research since work is made
  public more quickly
• made collaborations much easier since scientists
  can share data over the Internet

There is, however the caveat, that it is so easy
to put data out into the public databases that it
is difficult to have stringent quality controls
so researchers must be careful to confirm all
information they receive.
Our knowledge base is much larger now
Genomes to Life program, U.S. Department of
Energy Genome Programs http//genomics.energy.gov
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Importance to biodiversity conservation
Although one of the exciting results from
genomics is how much is in common among
organisms, conversely, genomics offers a way to
look at the differences among organisms at their
most basic level as well, allowing us to
discover, catalogue, and compare biodiversity.

• Understanding this diversity will enable us to
  protect it better
• Knowing where hotspots of biodiversity are can
  improve the efficiency of conservation work and
  reduce costs
• This new knowledge may also help find new ways to
  make use of biodiversity, e.g. new cures for
  cancer and other illnesses

(Pimm et al. 2001 Phillips and Freeling 1998
Serageldin and Persley 2000)
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Other possibilities of the future.
In addition to their obvious use as food, plants
are important to our global environment in many
other ways including providing oxygen, fuel,
shelter, clothing and medicinals. Thus plant
genomics could have far-reaching and powerful
results.
Research is now demonstrating that plants can
even be used as a source of new raw materials,
such as those in oils and plastics, and as a way
of eliminating waste products such as sewage
(Meagher 2000, Pyper 2003).
Pictures Taken From Exhibit Panels U.S. Botanic
Gardens, Washington, D.C. (June-August 2003),
http//www.mountain.org/work/resedu/usbg02.html
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How did genomics start?
Genomics became possible because of simultaneous
advances in technology and molecular biology.
The cornerstone of the field of genomics was the
discovery in 1953 of the structure of DNA, that
it is comprised of 4 main bases (adenine,
guanine, cytosine, and thymine, known more simply
as A,G,C, and T), which are repeated in a
particular order (sequence) for every living
organism (Watson and Crick 1953).
From http//www.doegenomes.org/ A Primer From
DNA to Life. Department of Energy, Human Genome
Project Information
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The tools of molecular biology
Next came the technologies that allowed us to
manipulate and study DNA, for example, DNA
cloning
The whole genome of an organism can be up to
billions of base pairs and difficult to work with
Cleavage of the genome into smaller fragments,
usually between 200-2000 bp in size, can be
carried out via a number of methods
Smaller pieces can now be cloned (inserted into
carrier vectors), or characterized in a variety
of ways
Many other techniques
sequencing
cloning
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Key background conceptDNA structure
These illustrations from the Human Genome Project
Information site (http//www.doegenomes.org/)
show two views of the structure of DNA. Recall
that each strand of DNA is composed of a string
of nucleotides, each consisting of a pentose
sugar, a phosphate group, and a nitrogenous base
which is either adenine, guanine, thymine or
cytosine (abbreviated as A, G, T, or C). The
shapes of A and T, and of C and G can bind
together, creating the complementariness of the 2
strands of DNA, producing the double helix
structure and allowing replication. The order
of the 4 bases throughout the DNA sequence of an
organism is particular to each organism and
carries all the information it needs to function.
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Key background conceptDNA sequencing
The key to DNA sequencing is that the 4 bases are
slightly different in size, and thus can be
distinguished when the DNA is broken up into
small enough fragments to allow discrimination.
The most commonly used method of sequencing DNA
was developed by Fred Sanger in 1977 (winning him
a Nobel prize). The key to the method is the use
of modified bases which cause DNA synthesis to
stop prematurely.
This creates a set of nested fragments, each
differing in length by a single base, which can
be identified (as A,C,G, or T) after separation
on a polyacrylamide gel. (picture from de Vicente
Fulton 2004).
Note This is, of course, a vastly simplified
explanation. For more details, see De Vicente
Fulton 2004, http//web.utk.edu/khughes/main.html
, http//www.doegenomes.org/, and other resources
listed at the end of this module
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Advances in technologyautomated DNA sequencers
The concept of genomics is predicated on the
ability to determine the sequence of DNA,
acquired shortly after Watson and Cricks
breakthrough. However, genomes range in size from
a few thousand base pairs (e.g. a virus) to
nearly 3 billion (humans)(see Table 1), and until
the late 1970s it was not feasible to decipher
sequences of more than 20 bases. This changed
when 2 new sequencing methods were published in
1977 (Maxam Gilbert 1977, Sanger et al. 1977),
and even more dramatically so in 1991 when
automated sequencing machines were developed
(Hunkapiller et al. 1991).
Figure 1. The AB3700 sequencer from Applied
Biosystems. The advent of capillary systems and
robotics has pushed the current capacity of DNA
sequencing to over 1 million bases per day.
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Automated DNA sequencing
Automated sequencing machines now also use a
fluorescently labeled tag where each of the bases
is a different color. This allows the 4 reactions
to be run through a single capillary tube, rather
than in separate lanes on a gel, and a detector
at the bottom reads or calls the bases as
they emerge.
After an amplification reaction, each of the 384
wells in the plate now contain billions of copies
of the original fragment, but they are all
different lengths and each ends with a dye
terminator. The fragments, which have a negative
charge, move through the capillaries of the
sequencing machine toward the positively charged
pole. Shorter fragments move faster than longer
ones. At the detection window, a laser excites
the dyes. A detector "reads" the colors, one at a
time, to determine the sequence of the tagged As,
Ts, Gs, and Cs.
From The DOE Joint Genome Institute,
http//jgi.doe.gov/education/how/
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Sequencing output
The result is a 4-color chromatogram such as the
one seen below.
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Advances in enabling technologiescomputational
ability
Still, genomics would not have progressed had it
not been for advances in computational ability
happening around the same time. The more
efficient the sequencing machines became, the
more readily the data was available. Researchers
wanted not only to store this data, but to be
able to search it, compare it, and analyze
it--all requiring storage capacity and processing
power.
IBM began selling the first personal computer in
1982, the same year that GenBank launched, with
over 600 sequences and 680,000 bases (McCook
2005, Smith 1990). GenBank exceeded 1 billion
bases by 1997.
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Large-scale sequencing became possible, and a new
field is born
The simultaneous and complementary advances in
DNA sequencing and computation allowed for the
possibility of large-scale sequencing, even of
whole genomes. The 1990s were a period of massive
large-scale sequencing, including the whole
genomes of organisms including yeast
(Saccharomyces cerevisiae), a number of bacteria,
and the roundworm (Caenorhabditis elegans).
This marriage of biology and computation also
gave rise to the new field of bioinformatics, the
handling and studying of large amounts of data.
1988 saw the formation of a center that would
become one of the most important computational
tools for biologists The National Center for
Biotechnology Information (NCBI).
Available at http//www.ncbi.nlm.nih.gov/
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The Human Genome Project
The most public large-scale sequencing project
has been the Human Genome Project. Started by the
Department of Energy, who realized the possible
implications on human health-related issues, it
began in 1990, with collaborative funding from a
number of sources. After much drama and
bickering in the scientific community, the genome
was actually sequenced twice by 2 different
groups (the publicly funded group headed by
Francis Collins and Craig Venters company
Celera) and the completion announced
simultaneously at a joint press conference.
J. Craig Venter (l) and Francis Collins (r) at
the historic announcement June 26, 2000
Published separately International Human Genome
Sequencing Consortium (2001) and Venter et al.
(2001) For more information see
http//www.ornl.gov/sci/techresources/Human_Genome
/home.shtml
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Impact of the HGP

• The Human Genome Project had a essential impact
  on the burgeoning field of genomics, even in
  plants, in many ways
• Developing new technologies
• Advancing public awareness
• Boosting funding for scientific research
• Training new scientists
• Increasing awareness of ethical issues

There is a very informative website about the
Human Genome Project at http//www.ornl.gov/sci/te
chresources/Human_Genome/home.shtml
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Plants catch up
Plant research has always lagged behind research
on humans, partly due to the fact that the
implications are often more personal to humans
and so the funding more easily justifiable by
politicians. In the U.S., and most countries,
until the late 1990s the amount of funding
available for research in plants was a small
fraction of that available for the life sciences
as a whole (NRC 1992). Fortunately, plants had
a champion in Dr. Mary Clutter of the National
Science Foundation. At her urging, a federal
committee was established to reaffirm the
importance of plant research, leading to a large
increase in government funding plant science in
the U.S. This paved the way for the U.S. to join
with Europe and Japan to form The Arabidopsis
Genome Initiative for the sequencing of the first
plant genome, that of Arabidopsis thaliana,
completed in 2000. As of this writing, a
number of plants have been sequenced or are in
progress (see Table 1).
Tomato, sequencing in progress Rice, completed
2002 Arabidopsis, 2000.
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Key definition libraries
In genomics research, a library is a set of
sequences or clones, usually generated in mass
for a specific purpose
Types of libraries Genomic when a whole genome
is cleaved into many small pieces EST (expressed
sequence tag) short fragments of cDNA, more
likely to be from genes BAC (bacterial
artificial chromosome) larger inserts, used to
create physical maps, screen for particular
genes Specific tissue libraries for example,
one might construct a library using only tissue
from the root of a plant, to study this type of
gene exclusively
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Key background concept physical mapping
A physical map of an organism is the linear order
of sequences along the chromosome. It is
usually generated by creating a library of BAC
clones, and putting them into a contiguous order
by finding overlaps.
Here is an example of a small piece of the
physical map of Arabidopsis, taken from The
Arabidopsis Information Resource (TAIR,
http//www.arabidopsis.org/)
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Whole genome sequencing
While we will not go into technical details or
pros and cons here, you should be aware of the
two main approaches to sequencing a whole genome.
Top-down strategy An anchored physical map is
needed overlapping clones (a minimal tiling
path) are sequenced in order. Since the
positions of the clones (and therefore the
sequences) are already known, little
post-sequencing work is needed.
Images from The Creative Science Quarterly,
Helmut Kae (2003) http//www.scq.ubc.ca/?p392
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Whole genome sequencing, contd.
Shotgun strategy Large numbers of random
sequences are produced, and then lined up
computationally by using the overlaps. A physical
map is not needed prior to sequencing however a
high level of computation is needed
post-sequencing to line up the sequences
(assembly).
Images from The Creative Science Quarterly,
Helmut Kae (2003) http//www.scq.ubc.ca/?p392
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Sequencing considerations

• In deciding which sequencing method to utilize
  there are a number of considerations to weigh,
  both in regards to the genome of the organism you
  wish to sequence and your resources and
  priorities. For example
• Does the organism contain large regions of
  repetitive DNA? This will be hard to assemble
  with the shotgun method.
• Do you have the bioinformatics capability needed
  for assembling shotgun sequences? If not perhaps
  the top-down method would be best.

These approaches are not mutually exclusive,
however, and indeed the best approach seems to be
a combination of the two.
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Emerging technologies
DNA sequencing and genomics are fast moving
fields with new technologies frequently changing.
As of this writing, 2 new sequencing technologies
were being tested that could increase the speed
of sequencing by orders of magnitude

• 454 An instrument that contains both optics and
  fluidics subsystems, which are controlled by a
  computer subsystem. It has the potential to
  sequence millions of bases per hour.
  http//www.454.com/
• Solexa Genome Analysis System Includes
  propietary Clonal Single Molecule Array
  technology and reversable terminator chemistry,
  which can generate upwards of one billion bases
  of data in a single run and includes expression
  profiling. http//www.solexa.com/

The 454 system
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Whole genome sequencing vs. sampling strategies
Sequencing an entire genome is still
prohibitively expensive in most cases. Often
researchers are mainly interested in the genes of
an organism (rather than the whole genome
sequence necessarily).
In the next section we will learn about sampling
strategies and methods of discovering genes
without sequencing the whole genome, such as the
use of ESTs. In deciding whether to sequence the
whole genome or just sample it, scientists must
balance the savings in cost with the loss of some
information.
This figure shows the sequencing strategy of the
Human Genome Project. From Stephen Scherer,
Human Genome Project, http//www.isuma.net/v02n03/
scherer/scherer_e.shtml
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Table 1. Sequenced genomes
Over 350 genomes have been completely sequenced
as of this writing but this includes just a
handful of plants
Genome Size in Millions of Base Pairs
Homo sapiens(human) 2900 Mus musculus (mouse)
2500 Zea mays (corn) 2500 Canis familiaris
(dog) 2400 Solanum lycopersicon (tomato)
950 Sorghum bicolor (sorghum) 730 Orzya
sativa (rice) 430 Drosophila
melanogaster(fruit fly) 180 Arabidopsis
thaliana 125 Caenorhabditis
elegans(roundworm) 97 Saccharomyces
cerevisiae(yeast) 12 Haemophilus influenzae
(bacteria) 1.8
In progress as of this writing For more see
http//genomesonline.org, http//www.genomenewsnet
work.org, http//www.ornl.gov/,
http//www.jgi.doe.gov
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Which genomes to sequence?
With the cost of sequencing an entire genome
still being quite prohibitive in most cases,
there are many decisions that go into the
selection of which genomes to fully sequence.
Some questions that may be asked include

• What new information would be gained?
• Is there already sequence available of a related
  species? Is it worth sequencing the entire genome
  again, or just certain regions to compare the
  differences?
• What biological questions do we want to ask with
  this project? Do we really need the whole genome
  sequence or could partial sequencing answer these
  questions just as well?
• Who will fund the project? Will the data be
  publicly available?

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Getting specific DNA sequences
DNA sequencers are very expensive and difficult
to maintain most researchers do not have one of
their own. However, there are now many facilities
that specialize in DNA sequencing. Often, you may
not need or be able to afford to sequence the
whole genome of the organism youre interested
in, but just need a few specific sequences. How
can you acquire the sequences of DNA segments of
interest to you?

• Generate PCR product of one or more segments of
  DNA you are interested in. These can be specific
  genes, or any unknown DNA segments that have been
  generated with primers such as SSRs, etc. This
  product can be taken or mailed to a DNA
  sequencing facility.
• Generate many fragments of DNA, for example a
  whole library of fragments or an entire genome.
  Regardless of the organism or size of genome, all
  genomes must be broken down into small fragments
  before sequencing. One cost-effective strategy
  for producing many sequences without having to
  sequence the whole genome is the use of Expressed
  Sequence Tags (ESTs), described in detail in
  Section 3 (methods and tools).
• 3. Find available sequences in public databases
  that you can use.

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DNA sequencing output

• If you have DNA sequence produced from a PCR
  product or a library of ESTs, the sequence of
  your DNA segment(s) will be given to or, more
  usually, emailed or electronically transferred to
  you. Depending on the facility and your needs,
  the output might be in the rough form of a
  chromatogram, such as we saw in a previous slide,
  or just a simple text file of a string of G, A,
  C, and Ts as in the example below.
• If the data is in the chromatogram form, you will
  need to manually generate a text file such as the
  one below (by reading the bases yourself) or,
  more typically, use one of the many software
  programs available to do this for you.
• If you retrieve a sequence from a public
  database, it will already be in this format for
  you.

Well see more about sequence format and
retrieval later in the module.
The first 480 bases of the DNA sequence of GAN, a
drought tolerance related gene in Arabidopsis
(GenBank Accession AY986818). Numbers to the left
signify the numbered bases in that row (ie. the
first row contains bases 1-60, the second row
contains bases 61-120, etc.)
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On to.comparative genomics
Now that you have seen what genomics is, you
probably have a good idea of what comparative
genomics means the analysis and comparison of
two or more genomes simultaneously.

• Sequencing or mapping the genome of a single
  species provides a static picture of a single
  point in evolutionary time. However, to
  understand how genes and genomes have changed
  over time to create the many life forms on this
  planet, we must be able to compare genomes on a
  detailed basis. To do so may allow us to
• unravel the evolutionary history of genome
  structure
• uncover the rules and mechanisms by which genomes
  change over time
• discern how genetic changes lead to new and
  adapted life forms
• understand how current life forms develop and
  function

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Example of comparative genomics
An example of comparing genomes from the Human
Genome Project. In this figure several genes are
found to be quite similar in both the human and
mouse genome.
From Stephen Scherer, Human Genome Project,
http//www.isuma.net/v02n03/scherer/scherer_e.shtm
l
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Comparative genomics

• Comparative genomics can happen at any scale,
  either with just a few genes, or on a
  whole-genome scale. One can compare any genomes
  for which there is genomic information.
  Obviously, the amount of type of useful
  information that results will vary with the type
  of information available and the genetic
  distances between the organisms.
• Examples of genomes that have been compared in
  various ways
• and have yielded very useful, new information
  are, to name
• just a couple
• The human and mouse genomes
• The maize and sorghum genomes
• The Arabidopsis genome to many plant genomes

How this is done will be the focus of the next
sections.
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Other types of -omics
Once the word genomics became widely used,
immediately many other terms were created using
the -omics suffix. Here are a few, along with
their basic definitions. We will not be covering
these topics in depth in this module, but you
should understand what they refer to.
Structural genomics the determination of genome
structure at the sequence level Functional
genomics determining the function of
genes Proteomics the large-scale analysis of an
organism's proteins to reveal expression and
functions Transcriptomics depicts the
expression level of genes, often using techniques
capable of sampling tens of thousands of
different mRNA molecules at a time (eg. DNA
microarrays) Metabolomics the "systematic study
of the unique chemical fingerprints that specific
cellular processes leave behind" -specifically,
the study of their small-molecule metabolite
profiles Phylogenomics a method of assigning a
function to a gene based on its evolutionary
history in a Phylogenetic tree Phylogenomics
uses knowledge on the evolution of a gene to
improve function prediction.
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Post-genomics?
You may have already heard the term
post-genomics era-- does this mean genomics is
already obsolete? No! This just refers
specifically to the work that needs to be done
after sequencing. This can include gene
identification, comparative genomics, and in fact
all of the methodologies that we discuss in this
learning module and more. The term is misleading
because it implies that genomics equals
sequencing, when as we will see it is much more
than that. Sequencing in and of itself doesnt
tell us anything without further analysis.
Indeed, the exploitation of genome information
is still in its infancy and new methodologies may
be required to make the most of them. (Saccone
and Pesole 2003)
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Resources more information
Genome Research Limited (GRL) (2001)
http//www.yourgenome.org Molecular Techniques.
Karen Hughes, University of Tennessee. http//web.
utk.edu/khughes/main.html National Center for
Biotechnology Information (NCBI). A Science
Primer. Available at http//www.ncbi.nlm.nih.gov/
About/primer/index.html National Institutes of
Health, National Institute of General Medical
Sciences (2001) Genetics Basics. NIH Publication
No. 01-662. Also available at http//publications
.nigms.nih.gov/genetics/ Smith, T. F. (1990).
The history of the genetic sequence databases.
Genomics, 6, 701-707 The DOE Joint Genome
Institute. How sequencing is done.
http//jgi.doe.gov/education/how/ (includes
animated videos)