Lecture 18 - Cancer
Four most common types of Cancer in Canada
• Prostate, breast, lung, and colon
Most likely factors contributing to cancer incidence in Canada
• There is a lot of old people in the population and old people have a lot of
Role of cyclin/CDK complexes in cell cycles regulation
• Cell cycle checkpoints are monitored by CDK’s and cyclins
• In G1/S checkpoint, the G1/S cyclin binds onto CDK2, this activated CDK2 then
phosphorylates target proteins used for the G1 to S transition(commits cell to
DNA replication). These targeted proteins that get phosphorylated by activated
CDK2 then function to release the G1/S checkpoint
As a result DNA replication begins. (S phase begins)
Role of proto-oncogenes, tumor suppressor genes and oncomirs in cancer
• Proto-oncogene is a gene that once deregulated can cause cancer
▯ An example is the EGFR gene that creates the EGF-R(protein receptor) -
a protein that binds EGF(protein) to signal the cell to continue to divide. So if
EGFR gene has been mutated or deregulated such that it is always ‘on’, it is
considered an onco-gene that will cause rapid/excessive cell division and can
form a tumor.
▯ ANY of the genes coding for the proteins that have to do with EGFR
signaling can be possibly considered onco-genes when deregulated
• Tumor suppressor genes are essentially genes that shut down rapid cell growth
during embryology when need be.
▯ An example is p53 - a transcription factor that can be activated by DNA
damage and can result in increased DNA repair. It can also block the cyclin
CDK’s at the ﬁrst checkpoint; stopping cell cycle. p53 is in charge of the G1/S
checkpoint (Does not allow G1/S cyclin to bind to CDK2 for e,g) ▯ This genes job is to prevent cell division, but if mutates can result in loss of
function or possibly even out of control cell division.
▯ BRCA1 is a breast cancer tumor suppressor gene - rarely, one suffers
mutations to BOTH BRCA1 alleles and so you lose all tumor suppressor activity
▯ OR you can inherit a shitty allele from you dad and so the chances are
much higher to become homozygous in a certain tissue, in a certain cell now
because only ONE mutation is needed has to mess up your moms BRCA1 allele
• Micro RNA’s (miRNA) that can be deregulated to cause cancer are called
▯ miRNA’s are very diagnostic - using a heat map, tissue with lots of blue are
located in a tumor and tissue with lots of red are just normal.
▯ Each tumor has a speciﬁc micro mRNA expression.
• Some miRNA’s regulate the expression of mRNAs that are the transcripts of
tumour suppressor genes. If these miRNAs are over-expressed because of
alterations of the genes encoding them, expression of the target mRNAs can be
completely blocked, thereby removing or decreasing inhibitory signals for cell
proliferation. Other miRNAs regulate the translation of mRNAs that are
transcripts of particular proto-oncogenes. If these miRNAS genes are
inactivated, or expression of these genes is markedly reduced, expression of
the proto-oncogenes is higher than normal and cell proliferation is stimulated. Role of p53 gene
• It is a tumor suppressor gene that is activated by DNA damage. p53 codes for a
transcription factor whose activity results in : increased DNA repair, cell cycle
arrest by blocking cyclin/CDK and apoptosis if need be.
Explanation for why increased cancer risk can be inherited
• Varies depending on type of cancer but heritability ranges from 0.27 to 0.42
• Possibility that your mom or dad gives you and your sibling a bad tumor
suppressing allele (BRCA1)
Explanation for why increased cancer incidence tends to increase with age
• Older people have been exposed to more mutagens and have been around
longer and so they have accumulated more mutations.
• Most cancers require several mutations / several successive changes to occur
before a tumor is formed.
Role of stem cells in tumor growth
• Close to all of our tissues have pleuri potent stem cells that are able to
differentiate into a wide range of tissue types.
• When a stem cell divides, one of the daughter cells remains a stem cell (which
will go on to divide into another stem cell and a progenitor) and the other one
becomes a progenitor cell - progenitor then goes on to differentiate into
something (differentiated cells)
• Stem cells and progenitor cells and differentiated cells can all suffer mutations
and become cancer stem cells
• This ﬁnding shows that tumors may be driven by cancer stem cells and
that maybe if you do not develop the cancer stem cell, then you do not
get a tumor.
• So cells are not the same in tumors, some of them divide rapidly and
some of them do not Evidence that epigenetic regulation may be relevant in cancer
• If a mouse has one defective tumor suppressor allele and then they suffer
another mutation to the other allele, this will lead to a brain tumor.
• You take the mouse’s egg cell and take out its nucleus and then replace the
nucleus of the egg cell with the nucleus from the tumor cell.
• Take this tumor nucleus in egg cell (isolate it) and give it an electric shock which
makes it think its being fertilized. This causes the cell to start dividing and
surprisingly this cell goes on to make a mouse NOT a tumor
• So when you take a tumor’s nucleus and put it in the environment of an egg, it
gets reprogrammed and makes all the normal tissues of a mouse.
• This suggests that maybe cancer is epigenetic - maybe the the egg cell is
epigenetically reprogramming this nucleus.
• Maybe tumors start due to epigenetic changes that are potentially reversible (as
seen in the mouses case) but then mutations occur that much less likely to be
reversed and so cancer progresses. MAYBE epigenetic changes induce
mutations. * Cancer is Deregulation - uncontrolled growth can arise from upsetting the
balance between the activity of gene products that promote cell cycling vs those
products that suppress cell cycling.
▯ Lecture 19 - Molecular Homology
Strategies for determining if features are homologous
• One way of doing this is using comparative genomics (5 steps) :
1) Sequence Genomes - Cheap, doesn’t take much effort and no sophisticated
2) Genome annotation - attaches biological meaning to the sequence
- Gene prediction - does the sequence code for protein or for RNA ?
- Look for regulatory elements
- Look for biological functions through similarity searches
- Automated (uses algorithms to search)
3) Protein Prediction - certain sequences detect open reading frames and then
the computer gives an estimation of how many PREDICTED proteins there are
in the genome.
4) Align Sequences - Use CLUSTAL or BLAST - algorithms for comparing
sequences of DNA or proteins
5) Determine Homology - observe similarity scores and e-values
Sequences detected by annotation programs to detect open reading frames (orf)
• Computer can go through the genome and detect regions/motifs that are
common to genes, especially protein coding genes
• It looks for things like promoter elements and more importantly; intron-exon
boundaries which the computer can detect.
• Computer splices out the exons and puts them together giving you a predicted
protein coding sequence - however the most probably open reading frame
(there are 6) must then be found for that protein coding sequence. +1
• Green bar = start codon , Purple = stop codon - the one with the longest
(most a.a in b/w start and stop) open reading frame (ORF) is most likely the
frame read that codes for the protein. In the above diagram +3 has the longest
ORF and is therefore the reading frame.
• In lecture, there are 15,000 genes with 15,000 probably ORFs , which allows us
to approximate 15,000 total proteins in chlamy’s genome
Characteristics that are, and are not, common between homologous genes
• They do NOT have identical nucleotide sequences - however they are very
• They do NOT have the same protein sequence - very high in similarity though
(more so than amino acids)
• They are NOT the same length and they do NOT have the same function.
▯ The above three are usually similar but never identical.
Low e values and high percentage of similarity infers homology but never
conﬁrms it - it is based on probability and is not a fact
Usefulness of BLAST analysis of sequences in Genbank at NCBI
• CLUSTAL (global alignment) - starts at the beginning of the gene and tries to
align all the similar bases.
• BLAST (basic local alignment search tool) - looks for regions of very high
similarity, doesn’t try to force two sequences to align perfectly - instead it looks for smaller areas of very high similarity and aligns those (this is much faster
than CLUSTAL) -- BLAST is a local alignment
• So you send the PREDICTED protein coding
sequences (of chlamy for e.g) over to NCBI
(National Center for Biotechnology) where they
have a Genbank that has over 23,500 nuclear
genomes sequenced from organisms.
• So lets say you send the predicted proteins to NCBI and get 155 BLAST hits
against a certain Chlamy gene
• This means there are155 sequences at NCBI which are similar to chlamy gene,
the top most red bar (not the query) has the most similarities and it is the volvox
gene GlsA (which is also found in chlamy - it is an orthologue)
• This BLAST analysis can be used to infer homology. Reasons why amino acid sequence comparisons are more informative than
nucleotide sequence comparisons
• A.A is more ‘powerful’ (can infer much more information from it) than a
nucleotide sequence of the same length because it has more information
primarily due to the larger ‘alphabet’ of 20 characters (20 amino acids)
Mathematical relationship among total information, # of symbols, # of letters in
• I = G
• I is the total information in a message with G symbols in an “alphabet” of n
• The message can be G symbols long (3 amino acids or 3 nucleotides long)
• Alphabet of nucleotides is 4 characters, and alphabet of amino acids is 20
Relative number of bits of information in a single nucleotide vs single amino acid
Bits of info in an amino acid Bits of info in a single nucleotide?
n=20 (length of amino acid alphabet)
n= 4 (length of nucleotide alphabet)
G=1 (message is one amino acid in G= 1 (message is one nucleotide
I = ( 1 x ln20 ) / ln2 = 4.32 I = ( 1 x ln4 ) / ln2 = 2
Relationship between E-value and likelihood of homology
• Decisions about homology are made based on probability, the higher the
similarity between two sequences, the lower the probability that they originated
independently of each other and became similar just by chance.
• Sequences that are highly similar are probably/more likely homologous One of the parameters obtained from sequence alignments is called the e-
• The lower the e-value, the greater the likelihood of real homology.
• High scores of similarity and VERY low e values can be found with certain
genes when you blast a chlamy sequence of GlsA - given the high similarity
scores and the very low e-values , the chances you had two different
sequences come together to be the same, doesn't make any scientiﬁc sense --
the two sequences are thus homologous based on probability.
Whats the information content in a sequence that consists of a single amino acid
n = 20 G=1 I = ln(20) / ln(2) = 4.32
• Amino acid sequence is based on a larger “alphabet” of 20 characters and thus
has more information
Think about underlying reasons to explain that two proteins have weak global
alignment (CLUSTAL) but strong local alignment (BLAST)
• They may have weak global alignment because their structure differs as a
whole, BUT similar local alignments suggests similar functions in the proteins -
for e.g :
• Areas of the protein that catalyze a similar reaction would be the same
• Areas of the protein that bind to regions of DNA that are similar in sequence
• Areas that codes for the ATP binding site
These local areas of similarity are expected if two proteins carry out relatively
*See lecture 20* Lecture 20 - Molecular Convergence
Synonymous vs non-synonymous mutations
Synonymous - change in the nucleotide sequence that does not change change
the amino acid.
Non-synonymous - change in the nucleotide sequence that changes the amino
• * Higher levels of conservation are found at the level of the amino acid (versus
conservation at the level of the nucleotides)
Characteristics of the neutral theory of molecular evolution
• Neutral theory of molecular evolution - mutations occur and exist, that do not
affect the protein at all. These mutations do not have a positive or a negative
effect (no selective advantage or disadvantage) and so they’re simply neutral.
• Selection theory classiﬁes mutations as either being deleterious or
Relationship between frequency of amino acid substitutions in given proteins vs.
time since common ancestor
• Number of differences between protein sequences of different species is
proportional to the time since the species diverged (diverged long ago = more
differences between protein sequences)
• There are fewer a.a differences if the two organisms diverged more recently Fibrinopeptides > Hemoglobin > Cytochrome c for the number of amino acids
substitutions per 100 residues (or per 100 amino acids) since divergence.
• The relationship for these three proteins is linear and they all have different
rates but each protein is moving at its own constant rate (# of amino acid
substitutions as a function of time)
• Molecular clock - Used when the rate of mutation are fairly constant for a
• Molecular clock technique compares rates of molecular change (in nucleotide
or amino acid sequences) to estimate when two species diverged.
•If # of differences in cytochrome c
for two different species is 20 amino
acids - they roughly diverged 400
Relative rates of accumulation of synonymous vs
• Synonymous mutation rate is higher than non-
synonymous mutation rate
• Mutations that change the nucleotide sequence in a
way that does not change the amino acid, occur at
a higher rate. Variables that affect the rate of evolution of a particular protein
• The main variable is the amount of constraint the protein can withstand.
• For e.g the histone H4 protein is more constrained than the alpha-globin protein
• Proteins that are more constrained CANNOT undergo many non synonymous
changes to their amino-acid sequence without it affecting the structure of
function of the protein.
• The speciﬁcity of the 3-D structure - a protein used for clotting (ﬁbrinopeptide) is
less strict about the 3-D structure it needs to maintain because its function is
less complex and does not require extremely speciﬁc structure.
Characteristics of the “molecular” clock
• Usually a linear constant rate and is based on the neutral theory
Compares rates of molecular change in nucleotide and amino acid sequences.
• Powerful tool used alongside geological records to obtain estimated times of
• Uses number of amino acid differences for e.g in a given protein (hemoglobin)
between two organisms to get a rough idea of time of divergence.
• The molecular clock is based on neutral theory and the idea that rates of
mutation are pretty constant
For example, imagine that a length of DNAfound in two species differs by four bases and we
know that this entire length of DNAchanges at a rate of approximately one base per 25 million
years. That means that the two DNAversions differ by 100 million years of evolution and that
their common ancestor lived 50 million years ago. Since each lineage experienced its own
evolution, the two species must have descended from a common ancestor that lived at least 50
million years ago. (Each lineage had two base-pair mutations in two different places leading to 4
differences all together)
http://evolution.berkeley.edu/evosite/evo101/IIE1cMolecularclocks.shtml# Regions of two unrelated proteins that would be expected to be similar if they
were the products of convergent evolution
• If two unrelated proteins are the products of convergent evolution, they should
NOT be pretty similar across their entire nucleotide sequence.
However, there should be localized areas of similarity such as:
• Areas of the protein that catalyze a similar reaction would be the same
• Areas of the protein that bind to regions of DNA that are similar in sequence
• Areas that codes for the ATP binding site
Localized regions of similarity are expected because proteins tend to be modular
in their function - they have speciﬁc active sites and binding sites and their
functionality of the protein is represented by localized regions
• Mutations and other processes cause nucleotide sequences to change , which
can lead to selective advantage and ultimately convergent evolution if the
mutations are advantageous for two organisms in their given environments.
• E.g of important amino acids represented by localized areas are
• the location of cysteins (give rise to disulﬁde bonding necessary for tertiary
• Speciﬁc a.a/ a.a sequences necessary for catalysis (enzymes)
• DNA binding domains/ Receptor binding sites.
Function of lysozyme
• Antibacterial enzyme that attacks the peptidoglycan wall of bacteria and
• Gene duplication occurred back in the day and lysozyme evolved the new
function of acting as a stomach enzyme in ruminants (animals that digest
Characteristics of ruminant organisms that enable them to extract energy from
• Ruminant organisms contain bacteria in their stomachs which break down the
cellulose found in the plants ruminants eat After the bacteria has broken down the cellulose, the lysozymes break down
the bacteria and extract the nutrients from the bacteria.
Role of lysozyme in digestive physiology of ruminants, langur monkeys and
• Lysozymes found in the stomach must acquire new properties that allows them
to remain catalytically active in an environment with very low pH (the stomach)
• Digestive lysozyme evolved convergently in cow and langur monkey and
they’re not phylogenetically related AT ALL
• Baboon and Langur monkey are very closely related but their lysozyme amino
acid sequence is more divergent than you would predict (14 amino acid
differences) -- between langur and humans (18 amino acid differences)
• This digestive lysozyme has evolved convergently in all 3 organisms\
• Langur and cow share 5 amino acids in their lysozymes and they’re NOT even
• Hoatzins (bird) also developed similar amino acids in similar places in their
• ***Three unrelated organisms convergently develop a lysozyme that can
function at low pH and is resistant to pepsin and due to natural selection, the
three proteins all look pretty similar.
• Through convergent evolution, the substitutions in the amino acid have resulted
in these sequences being much more similar.
Characteristics that distinguish “digestive” lysozyme from “non-digestive”
• Attacks peptidoglycan wall and destroys it (found in blood and tears) - has
• Has an aspartic acid-proline bond which is very susceptible to cleavage at low
• NOT resistant to pepsin DIGESTIVE
• Digestive lysozyme is able to digest peptidoglycan at low pH in the presence of
pepsin (a proteosome) -- it is more resistant to pepsin
• Found in stomach of ruminant animals
• Digestive enzyme don’t look too different (both similar in structure/have
essentially the same 3D shape) but has much more structural stability and is
rigid and it doesn’t ﬂex as much
• Pepsin cannot easily access the bond it wants to break in the digestive
lysozyme due to the minimal ﬂex of the lysozyme.
• Since it does not ﬂex as much, pepsin has a much harder time accessing the
bonds within lysozyme it wants to break
• The main bond it wants to break is the aspartic acid-proline bond , which DOES
NOT exist in digestive lysozymes (found in all other lysozymes)
• Has the same overall surface charge as pepsin and so it repels it, resisting
• Urea is a very strong denaturant and the digestive lysozyme can withstand
higher concentrations of urea before it begins to unfold (or unfolds at a slower
rate than the non-digestive lysozyme does) Lecture 21 - Experimental Evolution (ISO)
From the paper: Looking at Figure 1, What is meant by Potentiation, Actualization
• Potentiating mutations (unclear nature) are required for cells to acquire
• Actualizing mutations - consist of speciﬁc rearrangement of a few genes and
allowed for some growth - although poor- on citrate in the presence of oxygen
• made the cells wall weakly Cit+
• Reﬁning mutations - involved duplication of the rearranged DNA sequence and
were needed for strong and healthy growth under such conditions (growing on
citrate in the presence of oxygen)
Where does glucose and citrate come in to cellular respiration?
• Glucose comes from the food we eat (OR can be placed in the medium of the
cells and then taken into the cytosol) - it is then sent to the cytosol of our cells
where glycolysis can begin
• In the mitochondrial matrix where the citric acid cycle takes place - a two
carbon acetyl group carried by coenzyme A is transferred to oxaloacetate (4
carbons) forming citrate (6 Carbons) Lecture 21 - Experimental Evolution
Characteristics of model systems that can be used for experimental evolution
Model systems used in experimental evolution MUST reproduce very quickly --
they must have a short generation time.
• They reproduce asexually - easier to observe and less complex things
clouding the experiment. Also allows us to assume that any change we see is
due to one of the 3 genetic novelties and not something like sexual
• Organisms used usually have a generation time anywhere from a few minutes
to a few days
• Generation time - time it takes for an offspring to have their own offspring
• Model systems with short generation times used in experimental evolution allow
us to observe things like selection and changes in the genome in a matter of
• Large population - brings about new alleles that can be sustained
Origins of genetic novelty (variation)
Spontaneous mutation - very rare and is usually neutral or deleterious.
Gene duplication aka Gene Ampliﬁcation - also rare, an area surrounding the
gene is usually duplicated not JUST the gene
• Structural gene and the promoter are both copied
Gene rearrangement - genetic processes that rearrange the genome move a
gene or a promoter such that the gene is now under the regulation of a different
promoter and since the gene is now under distinctly different control and this can
lead to genetic novelty. Possible fates of duplicated genes
• Most of the time one of the copies gets destroyed and so the duplication had
• However, if the second copy is retained, there is a lot less selective pressure
on it (because there is a ‘back up’) and so the rate of mutation can be higher
this can lead to a new function for the duplicated gene - the structural gene
is now different, it evolves fast than the original and gives rise to
neo- functionalization - this gene can do many more ‘different’ things
because it can evolve faster
• If mutation does not affect the structural gene but just the promoter element
and so as a result the gene is switched on our activated in different
environments/tissues, this is called sub-functionalization - no change in
gene, but change in the regulatory element which changes the regulation of
• If you change the structural gene and the promoter , it gives rise to really
strong neo-functionalization because the gene will have a much different
Relative impact of selection on duplicated genes
• Selection pressure is reduced on the duplicated gene because you have the
original copy to fall back on if the duplicated gene is destroyed. So there is
more freedom for the second copy to mutate and change and thus the rate of
mutation is higher and this can lead to new function (neo-functionalization)
Design of Lenski’s long term evolutionary experiment (LEE) WITH E.coli
• Lenski’s group wanted to see how/if evolution can produce adaptation if random
mutations are not only harmful, but extremely rare.
• He took a clone (a group of genetically identical cells derived from a single cell)
of E.Coli(are asexual and have a huge population size) and founded 12
independent populations (populations are genetically identical)
• 12 populations are grown in a simple medium containing glucose as the sole
source of carbon (In 10mL culture there is 5x10^8 cells - once you subculture
the 0.1mL - you transfer 5 million cells to the next ﬂask.) Everyday he transfers 0.1 ml of each population into a new fresh ﬂask that
contains 9.9ml of DM25 with a new supply of glucose and allowed to grow/
divide. Old ﬂask are stored for a day in the freezer before they are replaced by
the ‘new’ ﬂask the next day
• Every 75th day (500 generations) the evolving populations are stored away in a
Value of cryopresevation to LEE
• Every 500 generations (75 days), he cryopreserves (freezes) a portion the
• Anytime he wants he can warm up the frozen sample and then start a culture
again, you can compare a culture at generation 500 with with a culture at
• You can compare their genomes and see how the 20,000th generation evolved
by subjecting it to some kind of selective pressure and seeing what it does
differently - you can also subject these populations to adaptations at low
temperatures and see how they respond.
• For e.g - compare 10,000th generation to ancestral generation (generation 0)
Where citrate enters metabolism
• After more than 30k generations, one of the 12 populations (Ara-3) changed
• Upon sub-culturing 0.1mL , the Ara 3 population was more turbid (more cells
per mL) - this is so because it turns out the Ara 3 population acquired the ability
to metabolize citrate (use it as a carbon source)
• Occurred after 30k generations in which every population has undergone
BILLIONS of mutation (genome is 4.6 million bases) and so each base has
undergone several mutations -- and so eventually these mutations lead to a
citrate positive phenotype.
• So, citrate is contained in the medium of all these ﬂask and its job is to keep
iron in solution (forms a complex with it) and allows for iron to be efﬁciently
taken up into the cells to be used for oxygen transport (hemoglobin) • The populations CANNOT grow on citrate under (normal) oxic conditions, they
can only grow on glucose and not all that well either. After about 8 hours the
25ug/mL glucose in the medium becomes depleted and until they are sub-
cultured or cryopreserved - the cells remain in stationary phase and can no
longer divide because they’ve run out of glucose.
• The cit+ generation (Ara 3) has an ecological opportunity - they can grow on
glucose AND on citrate and divide for more than 8 hours and as a result they
are more turbid (higher concentration of cells)
Role of glucose limitation in LEE experiment
• Tells you whether culture can grow on citrate or not
How to determine if Cit+ phenotype arose from one single mutation or was
dependent on previous mutations
They want to ﬁnd out if a single mutation was responsible for cit+ e.coli or was
this phenotype contingent upon prior mutations (E.G- you needed a mutation to
occur in the 10,000 generations that in addition with some mutation that occurs
at 30,000th generation leads to the cit+ )
• So what you do is you take the generations around 30k (30k -35k) , thaw them
out and plate a portion of them on an agar that contains citrate:
u •So 30k and 31k
u generation do not use
r citrate at all
D But for 32 and 33 -
n yes there is a slight
i citrate positive
y phenotype - There is a sense that there is a slight citrate positive phenotype around 32-33k
and this is called actualization - and after 33k, there seems to be some other
mutation that led to crazy growth on citrate
Genetic changes giving rise to potentiation, actualization and reﬁnement of Cit+
• At some point, for e,g - 20k generation - there was a mutation (they don’t know
exactly what this mutation is - but it is a potentiating mutation and the
actualization and reﬁnement mutation to develop cit+ phenotype is dependent
on this potentiating mutation.
• At around 31k generations - cells have appeared that are SLIGHTLY citrate
positive - this is an actualization mutation
• Reﬁnement - mutation that leads to a full blown increase in the use of citrate as
a source of reduced carbon.
Actualization (genetic level)
• citT - citrate transport is usually not expressed when there is oxygen around
• So in the actualization step a gene duplication occurred and the segment was
stuck back in slightly downstream of another copy.
• This resulted in the citT gene now being downstream of the rnk promoter (black
arrow on second pic) • The rnk promoter is strongly constitutive and as a result, is always on
(especially when there’s oxygen around) and so now citT gets expressed even
in the presence of oxygen.
• So when the polycistronic mRNA is processed, the citT protein gets synthesized
and this is how actualization occurs - this gene duplication accounts for the
slight cit+ phenotype.
Reﬁnement (genetic level)
• Reﬁnement is just the duplication of the rnk-citT modules - and so as more
generations occur (33k-34k), you begin to have many of these modules (9
copies sometimes) - so more mRNA for that gene and as a result - more citrate
transport protein being produced.
• Increased culture density is directly related to the number of copies of this
construct/module (the are proportional)
Result of “replaying” evolution of Cit+ phenotype
• So if you go back and ‘replay’ evolution - grow out MANY replicates starting
from generation 0 for e.g to see if Cit+ phenotypes independently occur - it
does happen - but the most important point is that there is NO capacity to
generate Citrate positive phenotype before 20k generations - this shows it
cannot be just one single mutation and that the age of the culture/how many
generations occurred is important
• A majority of them appear at around 30,000 generations which indicates that
the materialization of cit+ phenotype is contingent on other mutations. • Red box is the boundary of ampliﬁcation or duplication of original Cit+ line
• Blue boxes are the boundaries of ampliﬁcations of the 14 replay experiments
• So all of these gene ampliﬁcations are slightly different in the lengths that they
amplify (or duplicate) - but they ALL give rise to cit+ phenotypes.
• So long as some of citG and all of citT are moved in front of the rnk promoter -
cit+ phenotype will occur.
Why Cit+ lines do not drive Cit- lines to extinction
• In the Ara-3 line, 99% of the cells are citrate positive but they never drive citrate
minus(cit-) to extinction
• This is the case because the citrate minus lines are more efﬁcient at glucose
utilization than are cit+ and so they can have their own ecological niche.
• So both populations are using a different niche - one uses glucose effeciently
and one can use citrate. Lecture 23 - The Elysia/Vaucheria System (ISO)
• The primers are made of DNA (not RNA as in natural DNA replication)
• Left primer binds to one strand while the right primer binds to the opposite strand of
the original DNA
• Of all the DNA sequences put into the PCR reaction tube, only the target sequence,
the sequence between the primers, is ampliﬁed
• DNA polymerase is reading the template from 3’ to 5’ in BOTH strands
** Number of molecules produced in a given cycle = 2^ (cycle #) ,
3rd cycle: 2^3 = 8 molecules produced
• In cycle 3 - 2 molecules match the exact length of the target DNA sequence.
• In cycle 4 - 8 molecules will match the exact length of the target DNA sequence
• In cycle 5 - 24 molecules will match the exact length of the target DNA sequence.
• In cycle 6 - 64 molecules in total, ... I don’t even know Lecture 23 - The Elysia/Vaucheria System
Location of PsbO gene in photoautotrophic organisms
• The PsbO gene is found in the nucleus of photoautotrophic organisms
Location and role of Psbo gene product in photosynthesis electron transport