Bioc 300: Bioinformatics

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Bioc 300 Bioinformatics

• www.geneticsplace.com

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Goals of the Course

• Understand Methods and Research Questions
• Analyze Real Data
• Engage in a Realistic Learning Environment
• Utilize Online Databases
• Appreciate Complexity of Research Systems
• Integrate Different Types of Information
• Reconsider Cells as Intracellular Ecosystems
• Integrate Bioinformatics with Biology

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What is bioinformatics?

• "Bioinformatics is the term coined for the new
  field that merges biology, computer science, and
  information technology to manage and analyze the
  data, with the ultimate goal of understanding and
  modeling living systems."
• Genomics and Its Impact on Medicine and Society -
  A 2001 Primer U.S. Department of Energy Human
  Genome Program

Bioinformatics also represents a paradigm shift
for molecular biology, instead of taking a
reductionist approach, the sub-disciplines of
bioinformatics are more expansionist they
attempt to study the entire complement of a
particular cellular molecule or process.
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The omics revolution

• Genomics

The study of the entire DNA complement of an
organism
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Genome Sequence Information
Basic Research

• Acquiring Sequence
• Human Genome Draft
• Evolution

Applied Research

• Identification of Biological Unknowns
• Biomedical Research

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Genomic Variations
Ecology

• Tracking Ivory Sales
• Diatoms and Global Warming

Human Variations

• SNPs
• Disease Analysis

Ethics

• GMOs
• Genetic Testing

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DNA Microarrays
Basic Research

• Introduction to Method
• Data Analysis

Applied Research

• Cancer
• Pharmacogenomics

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The omics revolution

• Genomics

The study of the entire DNA complement of an
organism

• Proteomics

The study of the entire set of proteins in a
particular cell type
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Proteomics
Cellular Roles
Protein-Protein Interactions
permission from Benno Schwikowski
permission form Stan Fields
permission form Stan Fields
Identification and Quantification
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The omics revolution

• Genomics

The study of the entire DNA complement of an
organism

• Proteomics

The study of the entire set of proteins in a
particular cell type

• Transcriptonomics

The study of all mRNA transcripts in a particular
cell type

• Metabolomics

The study of all metabolites in a particular cell
type

• Glycomics

The study of all polysaccharides in a particular
cell type

• Variomics

The study of all possible drug targets in a
particular cell type
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Genomic Circuits
Single Gene Circuit
Toggle Switches
www.bio.davidson.edu/courses/genomics/circuits.htm
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Integrated Circuits
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Sequencing of Whole Genomes

• Three Phases of Genome Sequencing
• Preliminary sequencing
• Finishing
• Annotating

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Preliminary sequencing

• 1970s
• Maxam-Gilbert sequencing (chemical cleavage)
• Sanger sequencing (dideoxy method)

Autorad
You could sequence 100s of bases per day!
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Genomics took off with automated sequencing

• 1990s
• Leroy Hood made modifications to dideoxy
  sequencing

• ddNTPs were coupled to fluorescent dyes (instead
  of radioactivity)

DNA fragments were separated via capillary gel
electrophoresis
Sequence read by lasers, data was directly
recorded into computer
Now, instead of an autorad, we have a
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Chromat!
The newest DNA sequencers can determine millions
of bases of sequence in a day!
The increasing ease of obtaining sequence data
has lead to a logarithmic growth of Genbank, the
main repository of sequence data which is housed
at the National Library of Medicine at NIH.
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Growth of Genbank
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Sequencing Entire Organisms
Before the 1990s, sequencing was somewhat
haphazard. Depending on the researcher,
different pieces of different organisms genomes
had been sequenced.
No concerted effort had been made to sequence the
entire genome of an organism.
HUGO changed all of that, its mission was to
sequence the human genome, as well as a number of
the genomes of model organisms.
While small genomes could be sequenced directly,
larger genomes were first mapped out.
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Mapping large genomes
Sequencers needed some reference sequences to
know what part of a genome they were dealing with.
STSs - sequence tagged sites These are defined by
a pair of PCR primers that amplify only one
segment of a genome (ie. unique sequence).
ESTs- expressed sequence tags These are short
sequences of cDNA that indicate where genes are
located within the genome.
Now genomes could be cut into pieces, sequenced,
and the pieces reassembled.
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Cutting up genomes
Vectors designed to carry large pieces of DNA
include
BACs- bacterial artificial chromosomes- can carry
about 150 kb of insert
YACs- yeast artificial chromosomes- can carry up
to 1.5 Mb of insert
BACs or YACs containing overlapping DNA can be
assembled into contigous overlapping fragments.
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Shotgun sequencing
While HUGO was busy mapping large genomes and
sequencing some small genomes, Craig Venter
founded TIGR.
TIGR took a completely different approach.
Instead of mapping a genome, they simply cut it
into thousands of pieces, sequenced the pieces,
and reassembled the data using overlapping
fragments.
It was TIGR, not HUGO, who produced the worlds
1st completed genome in 1995- H. influenzae.
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Finishing a Genomic Sequence

• A finished sequence is defined as one that
  contains no more than 1 error in 10,000 bases.
• Finishing a sequence involves aligning a number
  of preliminary sequences and correcting any
  inconsistencies.
• Overlapping segments are combined into larger
  assemblies of contiguous DNA (contigs).
• If contigs do not overlap, a gap remains in the
  sequence.

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Finishing continued

• The human draft sequence, published in 2001,
  contained 147,821 gaps.
• The finished sequence, published in 2004,
  contained 341 gaps.
• A gap usually contains highly repetitive DNA
  that complicates attempts to clone and sequence
  it.
• Finishing is a very expensive process, many
  genomes have not been finished.

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Annotating Genomes

• Annotation involves the identification of
  functionally important sections of a genome.
• This includes, but is not limited to, making an
  educated guess about what kind of protein is
  encoded by a given coding sequence.
• Annotation is performed using various computer
  programs.

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Locating genes within a genome
Process is different in prokaryotes vs. eukaryotes

• Prokaryotes contain ORFs with no introns and very
  little intergenic sequence.
• Eukaryotes contain introns, complex promoters,
  and enhancers
• Introns range between 70 and 30,000 bp
• One eukaryotic gene can encode more that one
  different protein via alternate splicing
  mechanisms
• Eukaryotes also contain pseudogenes, ORFs which
  have been rendered nonfunctional by mutation
• Mammalian genomes contain about 23 pseudogenes

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Tools for gene hunting

• GeneMark - originally created for prokaryotes but
  adapted for some model eukaryotes

• GenScan - accepts up to 1 million bp of sequence
  online, more if downloaded

• Glimmer GlimmerM - developed by TIGR, accepts
  up to 200 kb online, more if downloaded

Once a genome is annotated

• One can use a genome browser to locate specific
  loci on specific chromosomes

• One can then use resources such as GeneCard to
  find out more about a specific gene

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Progress of Genome Sequencing

• Sequenced Euk. Genomes
• Yeast
• Drosophila
• C. elegans
• Arabidopsis
• Mosquito
• Human
• Mouse
• Rat
• Chicken
• Dog
• Zebra fish

• Euk. Genomes in Progress
• Xenopus
• Cow
• Cat
• Horse
• Kangaroo
• Honey Bee
• Turkey
• Lobster
• Bat
• Hedgehog

and others
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Tools had to be developed to make sense of the
dearth of genomic data being produced

• Genomic Search Engines include
• BLAST- searches sequence information, either
  nucleotide (BLASTn) or protein (BLASTp)
• BLAST2- aligns two sequences, checking similarity
• Enterez- searches databases for textual
  information
• PubMed- searches scientific literature for text
• ORF finder- finds Open Reading Frames (genes)
• PREDATOR- predicts secondary structure of
  proteins
• ExPASy- analysis of protein sequence and
  structure as well as 2D gel information

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Calculating E(expect)-values
E-values measure the significance of a match,
the smaller E-value, the better

• E-values are calculated using
• S, the bit score, a measure of the similarity
  between the hit and the query
• m, the length of the query
• n, the size of the database

E mn2-S
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So, how do you get the bit score?
S is calculated from the raw score, R
R aI bX - cO - dG
Where I is the of identities, X is the of
mis-matched nucleotides, O is the of gaps, and
G is the of spaces in the gap.
a, b, c, and d are the rewards, and penalties,
for each of these variables.
The defaults of these lower-case letters are set
at 1, -3, 5, and 2, respectively.
These values can be changed on the Other
advanced line.
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Now that we have a raw score, the bit score can
be obtained by normalizing the data
S (lR - ln K)/ln 2
(where l and K are the normalizing parameters)
These parameters are printed at the bottom of a
BLAST report.
Normalization enables a direct comparison of
E-values and bit scores, even if the reward and
penalty variables have been changed by the user.
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More databases of interest

• SwissProt- protein sequence database
• PDB- contains protein structural information
• OMIM- catalogs human disease genes
• TIGR- many searchable genomes, esp. bacterial
  ones
• GeneCard- genomic, proteomic and phenotypic
  info.
• Unigene- catalogs human ESTs
• Human map viewer- shows chromosomal location of
  genes

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Protein structure and function
For most researchers, the final goal of genomic
research is not the genomic data itself but an
understanding of the proteins encoded for by a
genome.
Steps to determining protein structure and
function

• Find ORFs, or coding sequences (CDSs)

• Translate ORFs

• Is this a known protein? If not, find protein
  orthologs, similar proteins in different species

• Check if 3D structure has been determined

• Predict hydropathy using a Kyte-Doolitle plot

• Predict secondary structure of your protein

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What do we mean by function?
The term function is too simplistic and is
somewhat outdated. A consortium called Gene
Ontology decided that a complete description of
function must include not only why? but also
what? and where?

• Why biological process. The objective toward
  which this protein contributes.
• What molecular function. The biochemical
  activity that the protein accomplishes.
• Where cellular component. The location of
  protein activity.

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One example isocitrate dehydrogenase (IDH)

• OMIM - IDH3A
• COG - functional categories, dendograms,
• isoforms- distinct genes encoding similar
  proteins
• Enzyme Commission, EC numbers
• Swiss-Prot
• Phylogenetic trees
• rooted vs. unrooted

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Terms used to describe phylogeny

• - genes which arose from a common ancestral gene
  within one species (isoforms)

• paralogs

• orthologs

• - genes from two organisms which arose from a
  common ancestral gene

• genetic loci located on the same chromosome
• (or multiple genetic loci from different species
  which are located on a chromosomal region of
  common ancestry)

• synteny

• homology

• - sequences which are similar due to a common
  evolutionary origin

• - terms used to describe sequences without regard
  to evolutionary relationships

• similarity or identity

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Searching for related proteins
PSI-BLAST allows one to search outward in a
spiraling pattern from a central starting point.
First iteration- finds proteins with similar
sequences.
Second iteration- can be performed using a
consensus sequence computed from your first
iteration.
More iterations can be performed as desired.
Or, one can choose a species and perform another
first iteration using the results of the original
search.
This approach can be used to annotate ORFs from a
newly sequenced genome
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Alternate Splicing

• 60 of human genes produce more than 1 mRNA
• Only about 22 of genes in C. elegans fit into
  this category

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Epigenetic Control

• It is not just the coding regions which matter.
• Methylation, such as that found in
  heterochromatin
• and CpG islands, also plays a role in gene
  expression.

• At any given time, there are 400,000 mC in a
  given cell. Since there are about 100 different
  human cell types, this totals 40 million
  methylation events in our methylome.

• Nonmammalian animals lack this form of epigenetic
  control.

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The of CpG islands correlates with the of
genes on a chromosome
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CpGs are usually associated with genes
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Imprinting

• About 20 mammalian genes are known to be
  methylated during gametogenesis in either the
  parental or maternal copy.

• Imprinting may represent a genetic tug-of-war
  between male and female interests.

For example, the insulin-like growth factor 2,
Igf2, is expressed only in the paternal allele.
Igf2 promotes the growth of the developing embryo.
The expression of its receptor, Igf2r, is
controlled by the maternally inherited allele.
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Expression of Paternal Allele of Igf2 in embryo
and placenta
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How does silencing work?
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What is the effect a loss of imprinting?

• Loss of Igf2 imprinting can lead to colorectal
  cancer and Beckwith-Wiedemann Syndrome

• There is a cluster of CpG islands in an insulator
  region near Igf2

CTCF is a protein which only binds to
unmethylated DNA.
17/20 tumor samples taken from cancer patients
were found to be hypermethylated in this region.
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What about the rest of our genome?

• Since only 1-2 of our genome is coding sequence
  what does the rest do?

A majority of our DNA is repetitive sequence

• There are 5 classes of repetitive sequence

1) transposon derived
2) pseudogenes
3) simple repeats such as VNTRs
4) segmental duplications
5) heterochromatic regions
The first category alone accounts for 45 of our
genome!
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Transposons

• Transposons fall into 4 categories

1) SINEs, short interspersed elements, such as
Alu comprise 13 of our genome These may help a
cell cope with stress, RNA produced from these
bind to an inhibitor of translation.
2) LINEs, long interspersed elements, comprise
21 of our genome
3) LTR retrotransposons comprise 8 of our genome
4) Other DNA transposons 3 of our genome
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More Transposon Facts

• About 50 genes appear to be derived from
  transposons, including RAG1 and RAG2, necessary
  for antibody diversity.

• The X chromosome has the highest concentration of
  transposons- one 525 kb section is 89
  transposon-derived.

• The Y chromosome has the highest concentration of
  LINEs, it is the most gene-poor of the
  chromosomes and probably tolerates insertions
  well.