Slide 1
In the second class of this course we will see the most general methodological
approaches to detect genetic variation.
Slide 2
Organization of the presentation
In this second class we will focus in three main topics: the technical approach to
detect genetic variation, the different types of molecular markers and their properties,
and the most important conceptual principles and external factors that mould the
genetic variation in biological species.
Slide 3
Molecular techniques
We will see three basic techniques in this course: the complete process of Southern
Blott, and spin-offs and derivatives of it; the principles of the Polymerase Chain
Reaction and DNA sequencing.
Slide 4
Southern blot
This technique was developed by Sir Edwin Southern in 1977, to detect single genes
in complex genomes. This technique was developed further by Sir Alec Jeffreys, who
utilized the variation at minisatellite loci to identify individuals.
The method consist of the following steps:
1. Fragmentation of genomic DNA in a reproducible way
2. Separation of the fragments in an electric field
3. Transfer of the fragments from to a membrane
4. Probing of the membrane with known DNA
5. Detection of the probe
For
laterhttp://www.bio.davidson.edu/COURSES/GENOMICS/method/Southernblot.html
Slide 5
The first step consists of a controlled fragmentation of genomic DNA. For this we use
RESTRICTION ENZYMES. These are protein whose enzymatic activity consists of
recognition of a 4 – 6 base pairs palindrome and cutting the DNA double chain.
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The products of the digestion are loaded onto an agarose gel, which is subjected to an
electric field. The “mesh” formed by the agarose will difficult the mobility of the
DNA fragments according to their size: small fragments will migrate faster to the
positive electrode, and the bigger fragments will migrate slower.
When repetitive DNA is recognised by restriction enzymes, the product of the
digestion are distinctive bands. The interspersed repetitive human sequences Alu
were named after the restriction enzyme (Alu I) that recognised a site within these
repeat units.
Genomic single copy DNA is as a semar in the gels.
After the DNA hast been separated in the gel according to size, this DNA is
transferred to a nylon membrane by capillarity. The membrane is placed on top of the
gel, and a pile of dry paper on top will “suction” a solution that will pass onto the
paper while the DNA keeps stopped and attached to the membrane.
This membrane is then incubated along with a probe: a fragment of DNA of known
origin that is labelled with a radioactive nucleotide (with P32). The radioactivity is
detected by exposure to an X- film, indicating the position in the gel where the probe
found homologous DNA.
Although this method was developed for locating single genes within a gemome, its
great potential allowed the application of “sub-techniques “ and the development of
derivatives of it. Following, we will see a few examples.
Southern blot image: http://www.mun.ca/biology/scarr/Gr12-18.html
Slide 6
DNA fingerprinting
See Slide 19 Class I
DNA fingerprinting is a thechnique that derived from the genral Southern blot
method. By contrast to the original Southern Blot technique, instead of using a probe
that is himilogous to a single copy gene, DNA fingerprinting use probes that come
from the repetitive regions of the genome. Sometimes these repreat motifs are
scattered throughout the genome and are located in the same or in different
chromosomes. These are called multilocus fingerprinting. Unilocus fingerprinting is
produced by probes that detect repeat unit that occur at ONLY ONE locus. These are
more important in the studies of individual identification.
In the graph on top of the slide, we see a diagram of a single locus minisatellite in an
heterozygote individual: the two chromosomes present different number of repeat
units, two different alleles. The arrows are indicating the recognition site for a
restriction enzyme.
The diagram on the left shows the radioautography of the DNA fingerprinting profile
of 5 individuals of rainbow trout, digested with the restriction enzyme Hinf I. Two
probes were used to detect multilocus minisatellites with the repeats motifs GATA
and GGAT. Multilocus DNA fingerprinting was extensively used in the ‘80s to detect
genetic variation in natural populations.
The radioautography on the right shows a single locus DNA fingerprinting profile.
An homozygote and an heterozygote individuals are indicated.
2
DNA fingerprinting of trout image: Genet. Mol. Biol. vol. 21 n. 2 São
Paulo June 1998
Unilocus DNA fingerprinting image: http://www.chm.bris.ac.uk/motm/dna/dna.htm
Slide 7
RFLP
For PCR see Slide 9, this presentation
Restriction Fragments Length Polymorphism is a technique that allows detecting
changes (point mutations) at a very low cost, with the use of restriction enzymes.
The main objective is to subject a fragment of DNA, usually obtained by PCR, to
digestion with multiple restriction enzymes to detect as many polymorphic sites as
possible. This technique was also applied in the initial studies of polymorphism in
mtDNA. The whole mtDNA was extracted from tissues, digested with restriction
enzymes and the fragments were separated by electrophoresis in agarose gels.
Although relatively cheap and fast, some information is lost in the process as it is
impossible to know which of the bases at the recognition site has changed, unless we
obtain the sequence information for the fragment of interest.
The RFLP in the slide shows a restriction analysis of a 500 bp of the mitochondrial
gene COI in the oyster Crassostrea ariakensis. Each lane is representing DNA of one
individual digested with a restriction enzyme. We can say, then that this population or
species shows two haplotypes with, e.g., the restriction enzyme Hae III. More
accurate information about the level of genetic diversity in this species would be
obtain with the use of multiple restriction anzymes.
http://www.biology.arizona.edu/human_bio/problem_sets/human_genetics/02t.html
http://www.vims.edu/vsc/images/gel.jpg
Slide 8
PCR Kary Mullis
Polymerase Chain Reaction is a technique that revolutionized the study of DNA, and
replaced the utilization of the Southern Blot in studies of single genes. The technique
was visualized by Kary Mullis in 1981, and received the Nobel Price in 1993.
http://nobelprize.org/chemistry/laureates/1993/index.html
Slide 9
PCR
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Conceptually, PCR is the replication of DNA in a tube, in a controlled manner. Unlike
the DNA replication before cell division, these replication only copies a fragment of
DNA framed by small complementary DNAs called primers. Primers are usually 2025 base pairs in length.
The separation of the strands for DNA replication is performed by the action of
enzymes within the cell. However, in the reaction tube we use temperature (93 to 95˚
C) to disrupt the Hydrogen bond between complementary bases. In high temperature
conditions, the DNA polymerases or organisms living in standard conditions of
temperature would be denatured. Therefore, the DNA polymerase utilized in PCR was
isolated from thermofilic bacteria that live in temperatures above 100 ºC). The DNA
polymerisation is carried out from the starting point of the primers.
This reaction is repeated for about 30-40 cycles, and then increase in the number of
chains present in the reaction tube can be expressed as 2n. Thus, at the end of the 30th
cycle, the reaction tube would contain 107 x106 copies of the original template DNA.
http://personalpages.manchester.ac.uk/staff/j.gough/lectures/the_cell/visualising_cells
3/pcr.jpg
Slide 10
Applications of PCR: microsatellite genotyping.
See Slide 20, Class I.
In this slide we show an example of the application of the PCR. The upper scheme
shows an heteroztgote individual for a microsatellite locus, and the flanking regions
that are used as a priming site for the PCR.
Microsatellites are co-dominant multiallelic markers: both alleles can be detected and
multiple alleles per loci are frequent. For instance, an average number of alleles per
loci in fish species ranges from 10-25; some herring loci have 60 alleles.
The PCR products are resolved in a gel. Each individual is expected to show 1 or 2
bands for each microsatellite locus. In the example below, there is a controlled
crossing between two heterozygote fish and the offspring shows all the possible
expected combinations of genotypes.
Slide 11
Applications of PCR: microsatellites for study of reproductive strategies.
See Slide 20, Class I.
In this slide we show an example of the application of microsatellite markers to
elucidate mating strategies in bryozoan organisms.
The marine bryozoans form the order Cyclostomata, have incubating chamber for
their embryos, that are occupied by many embryos at different stages of development
before they are released into the environment. These embryos were proposed to have
originated from a single fertilization event, followed by subdivision and
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multiplication of embryos within the chamber. This reproductive strategy is called
polyembryony. However, the hypothesis of polyembryony was only based on
observation of embryos in the chamber; multiple fertilization events or
parthenogenesis (the development of an egg without contribution from father) could
not therefore be excluded till confirming the genotypic composition of the offspring
and mother.
For this, in many colonies, many embryos within a chamber were genotyped along
with their mother. The results are shon in the Table of the slide. The numbers indicate
the allele sizes in base pairs, just as there are read after resolving the PCR products in
an automatic sequencer.
The table in the slide shows the genotyping of two colonies (A and BA) at 5
microsatellite loci. For the first, 8 chambers were genotyped, and 3 chambers were
genotyped for the second colony. N is indicating the number of embryos that were
genotyped per chamber.
As these animals have external fertilization, it was not possible to genotype the father.
The most important results can be summarized as follows
1. There is a father. Paternal alleles are indicated in red. This observation
discards parthenogenesis
2. all embryos within the same chamber show the same genotype, therefore
confirming the hypothesis of polyembryony.
The genotypes for loci Cd17-3 at the first chamber show unexpected genotypes: some
of the chambers shows alleles that are not present in the mother. The mother’s and the
embryo’s genotypes are all apparently homozygotes.
However, these are not the true genotypes and this example is reflecting one problem
not rarely encountered in microsatellite loci and other PCR-based genotyping
techniques: the problem of null alleles. Sometimes, the mutations occur at the priming
sites, preventing the primer from binding to the template DNA, and, therefore, the
PCR reaction from proceeding. The result is that in heterozygote individuals only one
allele will be amplified.
In our case, the genotype of the mother in 233/ null allele. The genotypes 229/229 and
237/237 in the embryos are showing inheritance of the mother’s null alleles and the
paternal (either 229 or 2370 allele.
The problem of null alleles induces then to underestimation of genetic diversity in
natural populations.
Roger N. Hughes1, M. Eugenia D’Amato, John D. D. Bishop, Gary R. Carvalho, Sean
F. Craig, Lars J. Hansson, Margaret A. Harley and Andrew J. Pemberton
(2005).Paradoxical polyembryony? Embryonic cloning in an ancient order of
marine bryozoans. Biol. Lett. 1, 178–180.
http://biology.bangor.ac.uk/~bss122/Celleporella.html
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Slide 12
Anonymous loci
Sometimes, the generation of genetic profiles is difficult for some organisms of
relatively unknown genomes: no “universal primers” are available, if they are
available they may not match well enough as to allow the PCR reaction to proceed,
‘universal probes” for multilocus DNA fingerprinting do not detect variation.
In these cases, a PCR-based technique may solve the problem. In relaxed PCR
conditions, using very short primers, only one primer per reaction (oligomers 10 bases
long) and low annealing temperatures (e.g. 37 ˚C) to allow these primers to match the
genome, a relatively large amount of PCR products are obtained. These products,
however, are ‘anonymous” as we their content is unknown. However, the structure of
the amplified region, an intervening stretch of DNA situated between inverted repeats,
resembles the structure of transposon-like elements; therefore, the RAPD fragments
are more likely to contain repetitive elements.
Although it is a very straightforward, easy and cheap technique, the RAPD profiles
are sometimes difficult to reproduce.
The scoring of the diversity in these RAPD loci is as follows: each band is considered
a biallelic locus, one allele being “band present” and another allele being “band
absent”. The associated problem with this, is that an heterozygote individual BAND
PRESENT/ BAND ABSENT cannot be distinguished from an homozygote individual
BAND PRESENT/ BAND PRESENT. For this reason RAPDs are called
DOMINANT MARKERS.
In contrast: microsatellites are co-dominant multiallelic markers.
AFLPs (Amplified Fragment Length Polymorphism) are conceptually similar to
RAPDs: dominant biallelic systems. However, are more reproducible across labs after
a “molecular trick” that adds adaptor, fragments of DNA of known sequence, that are
used as priming sites for PCR.
On the left: RAPD profiles of different strains of Bradyrhizobium japonicum, a
nitrogen-fixing microorganism, frequently used for seed inoculation of soybean to
increase the crop yield.
http://www.elchrom.com/public/index.php?article=113
http://www.mcb.uct.ac.za/Sequencing%20Service/aflprun.htm
Slide 13
DNA sequencing
There are several methods available to determine the actual sequence of nucleotides in
a segment of DNA. One procedure uses specially altered nucleotides called
dideoxynucloetides that have been made either radioactive or fluorescent.
When enough of the targeted DNA fragment has been amplified by PCR, the mix is
put through a series of DNA sequencing reactions that are a variation of PCR. The
amplified product from the PCR is added to a reaction tube containing the same Taq
DNA polymerase used in the PCR, one primer that can hybridize at the desired
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location (as opposed to both strands in PCR), and all four of the nucleotide bases (A,
T, C, G.)
In addition, small amounts of fluorescence labelled dideoxynucleotides (A, T, C, G)
are added to the mixture. Dideoxynucleotides are human-made nucleotides whose
sugar component is slightly different from that of the nucleotides that make up DNA.
The sugar lacks of the hydroxyl group that covalently links to the phosphate of the
next nucleotide in the growing chain. Therefore, the DNA polymerisation process
stops at a dideoxynucleotide as no more nucleotides can be added to that chain. Each
dideoxynucleotide is labelled with a different fluorescent compound so that it will
give off an identifying colour in a laser beam. Prior to the automatic sequencing, the
ddNTPS were labelled with radioactivity and these products were resolved in gels
(see Figure on the right) and exposed to X-ray films. We can read the DNA sequence
from bottom to top.
After 20 - 30 cycles of the PCR heating and cooling, the resulting mixture will contain
a series of fragments of different lengths depending on how many bases had been
added to the chain before one of the dideoxynucleotides sneaked in and blocked
further growth.
In evolutionary studies we often want to see the pattern of genetic variation at a
certain loci. For this, we obtain DNA sequence information for many individuals and
we compare the variation through aligning the different sequences, an example of a
DNA alignment is given in Slide 25, in the previous class.
See graphic explanation at
http://www.contexo.info/DNA_Basics/dna_sequencing.htm
Images:
http://www.schoolscience.co.uk/content/5/chemistry/proteins/images/p43fig6.gif
http://www.medprobe.com/img/dnaseq.gif
Slide 14
Molecular markers
Molecular Marker: is an identifiable physical location or LOCUS in the genome
(e.g., restriction enzyme cutting site, gene) whose inheritance can be
monitored. Markers can be expressed regions of DNA (genes) or some segment of
DNA with no known coding function but whose pattern of inheritance can be
determined. In general, we use markers of biparental, Mendelian inheritance, or
markers of only-maternal or only-paternal inheritance.
The molecular markers should detect genetic variation or polymorphism.
The development of the PCR, automated sequencing and advent of microsatellites
made a profound impact in Molecular Ecology and population genetics. Also
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important are the latest developments of statistical methods and user-friendly
computer packages.
In general, different molecular markers can suit better the type of question we want to
answer. In terms of molecular change we can distinguish three different levels of
population biology at which we can access information:
1. individual identification
2. genic variation
3. gene genealogies
As for individual identification and analysis of relatedness you can see examples in
Slides 10 and 11. The changes in allele frequencies in population can be originated by
many different processes. First, we will see how mendelian principles apply to
genetics in populations.
Slide 15
Population genetics 1
The genetic information contained in a group of organisms in the gene pool. More
practically, we can think of the set of all copies of all alleles than can be potentially
contributed to the next generation.
One important, central question in the understanding of how the gene pool is
transmitted to the next generation is if we can predict the genetic composition of the
next generation. The answer is YES, applying the principles of mendelian inheritance
(Slide 5, Class I). We can think of the following example in a biallelic system:
If there are N GAMETES carrying allele A and N gametes carrying the allele a, we
can call their respective frequencies in the population p and q. In a graphical example
similar to that of the Punnet square (Slide 5, Class I)., in which the frequencies are
represented by a fraction of the sides of the square, we can predict the genotypic and
allelic frequencies of the next generation. As the sum of all alleles frequencies for a
given locus in a population should sum up 1, the side of the square is 1, and the area
of the square is also 1.
In the present example, the frequency of ovules with allele A is 0.6, and the frequency
of ovules with allele a is 0.4; the frequency for spermatozoid carrying allele A is 0.6
and the frequency of spermatozoids carrying the allele a is 0.4. In this example the
allele frequencies in sperm and eggs are equal.
From the Mendelian laws, we can predict all the possible genotypic combinations that
can result from a fertilization event. Now, imagine what happens to a population with
several hundreds of individuals: we can still predict all the possible combinations and
their proportions, the frequency in which they will appear in the next generation, and
the allele frequencies in the next generation.
We obtain the frequency of a specific combination simply by multiplying the
frequency in the population of the gametes that gave them origin. For instance, the
frequency of individuals of genotype AA is the frequency of ovules carrying allele A
multiplied by the frequency of spermatozoids carrying allele A. In our case, this
frequency is 0.36.
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Again, the genotypic proportions 1:2:1 for homozygotes for the dominant allele,
heterozygotes and homozygote for the 2nd or recessive allele and their respective
frequencies in the population are p2, 2pq and q2 respectively. All these frequencies
also sum 1.
Slide 16
HWE
We can summarize the combination of ovules and spermatozoids by the expression
(p + q) 2
and
the resulting combinations as the expansion of the above expression, which results in
p2 + 2pq + q2. In other words, the chance of two gametes with allele A coming
together is, p x p = p2 , the chance of gametes A and a coming together (or the
occureence of heterozygotes has a probability of. ) 2pq, and finally, the chance of two
gametes a coming together is q2.
This is the fundamental concept of the equilibrium of Hardy-Weinberg.
This is no more than a model that can help us making predictions about the fate of
alleles in populations. As all models, it is based on assumptions:
 the organism is diploid
 with sexual reproduction
 generations are non overlapping
 loci are biallelic
 allele frequencies are identical in males and females
 random mating
 population size is infinite
 no migration
 no mutation
 no selection
Slide 17
Implications of HWE
The Hardy-Weinberg model is only a reference model in which no evolutionary
forces are acting. The main basic implications of this model are that
(1) Allele frequencies in a population will no change, generation after generation
(2) If allele frequencies in a population are given by p and q, the genotype
frequencies can be predicted from allele frequencies by p2 ,2pq and q2. A
similar principle can be applied to multiallelic loci.
If populations are out of equilibrium, and allele frequencies are the same in males and
females, and generations do not overlap, the equilibrium of allele frequencies are
attained after only one genration. If genberations are overlapping the HWE is attained
gradually after a few generations of random mating.
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Slide 18
Example HWE
In the examples of the table, we show the genotypic observed frequencies of 4
hypothetical populations. Although all show the same allelic frequencies, the
genotypic frequencies differ. For the first population, we estimated the expected
genotypc frequencies from the expansion of the expression (p + q)2 using the allele
frequencies. After obtaining the expected genotypic frequencies we are interested in
knowing how different they are from the observed frequencies. For that we use a X
square non-parametric test, at the 0.5 level of significance for 2 degrees of freedom.
Degrees of freedom are calculated as the product of (columns –1) multiplied by (rows
–1) of the contingency with observed and expected values.
The chi-square table for 0.5 significance level and 2 degrees of freedom show a value
of 5.99, which is much lower than our obtained chi-square value of 44.4. Therefore,
we reject the null hypothesis of no difference between observed and expected values.
In biological terms, the population is out of HW equilibrium.
Follow a similar approach, we will see that populations 3 and 4 are also out of HWE.
If generations are non overlapping and female and male allelic frequencies are the
same, all these populations will attain equilibrium after one generation of random
mating.
Slide 19
Selection
In the following slides we will show several examples of factors that determine
departures from equilibrium. This happens when the assumptions of the model are
violated. We should start with “mutation”, an assumption that is clearly violated in
diploid organisms as new combinations can arise by recombination (see e.g. unequal
crossing over in microsatellites an other repeated elements). Point mutations and other
types of mutation along with mutation rates are reviewed in Class 1, Slides 25, 26, 27,
28.
Selection is differential survival and reproductive success of genotypes. Evolution by
natural selection was the central idea in Darwin’s “On the Origin of Species by
Means of Natural Selection”, published in 1859. A famous slogan “survival of the
fittest” transcended the barriers of biology and was unfortunately taken to justify
political agendas during the XIX and early XX century.
Selection can change allele frequencies generation after generation, and therefore is
not possible to calculate genotype frequencies from allelic frequencies, thus violating
the consequences of HWE.
Sometimes the adaptive value of heterozygotes is higher than in homozygotes. This
type of heterozygote superiority is called heterosis.
In human ß-hemoglobin, a point mutation changes the glutamic acid (allele A) for
valine (allele S), which is obtained by a transversion at second codon of aminoacid 6.
This mutation in the hemoglobine causes the erythrocytes to change their shape
dramatically: they are more fragile than normal cells and they can block blood flow in
capillaried, depriving the tissues from oxygen and causing anemia. This condition is
10
called sickling anemia. However, the individuals that carry a normal and a mutated
allele are more resistant to malaria, as parasited cells are selectively destroyed. The
selective pressure of malaria parasites, then, favours the occurrence of allele S at a
higher frequency in populations exposed to malaria.
The situation in which selection maintains two or more alleles at a locus is called
balancing selection. Sickle anemia is a case of balancing selection in which
heterozygotes have a higher selective advantage than homozygotes.
Another type of selection favours only one allele instead of many, and therefore the
frequency of this allele shifts continuously in one direction. This principle also applies
to phenotypes. This type of selection is called directional selection and favours
individuals with extreme traits in a population. We present several examples:
Mosquitos Culex pipiens exposed to the insecticide chlorpyrifos blocks the ACE gene
(acetyl choline esterase) and produces death for malfunction of the nervous system.
However, some mosquitos carry a resistant gene ACER. The study of the allele
frequencies of several genes along a transect of 54 km in the Mediterranean coast in
France, taking in a few sites where the insecticide was previously used, showed
higher frequency of the resistance gene only in this sites. All other studied genes
showed allele frequencies equally distributed among populations (Chevillon et al.,
1995). This shows the effect of selection on the resistance allele in areas where it
conferred higher adaptive value. In the figure, the first 4 sites were affected by
utilization of insecticide.
Other examples of directional selection are breeding programs of domestic animals
and plants, where extreme phenotypes are artificially selected. Resistance to
antibiotics and pesticides function as selective agents for the resistant phenotypes.
Other type of selection depends on the frequency of certain variants or phenotypes in
the population. The central American butterflies Heliconius erato have many morphs,
all poisonous for birds. When a morph is common, birds learn to avoid them,
therefore favouring the rare morphs to become more frequent. The same process starts
again for the formerly rare but at present frequent morph. This is frequencydependent selection.
Nowadays we know other mechanisms than selection that are responsible for changes
generation after generation. Selection is a non-random process. There are other nonselective processes of evolution. For example, the random fluctuation of allelic or
genotypic frequencies when they do not confer any adaptive advantage. This is
genetic drift.
Sickle cells image: www.studentbmj.com
Mosquito image: http://www.bio.pu.ru/win/entomol/Kipyatkov/educ/images/c_pipiens.gif
Recommended read: Interview to Douglas Futuyma
http://www.actionbioscience.org/evolution/futuyma.html
http://en.wikipedia.org/wiki/Directional_selection
Reference;
C Chevillon, N Pasteur, M Marquine, D Heyse, M Raymond (1995) Population
Structure and Dynamics of Selected Genes in the Mosquito Culex pipiens.
Evolution, 49, 997-1007.
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Slide 20
Genetic drift
Drift results from the vagaries of sampling of the gametes that will unite to form the
next generation. This process by which allele frequencies do not change in a
predetermined way in called random genetic drift.
The change in allelic frequencies from one generation to another can be expressed as
q = q1 – q0, where q1 is the allele frequency in generation 1 and q 0 the allele
frequency in generation 1.
The magnitude of variation of allelic frequencies because of the random sampling is
given by
pq = (p0 q0 ) / 2N
where N is the effective population size (number of individuals that are actually
reproducing in the population). It is obvious then, that smaller populations will
display a higher variance.
In a simulation process in which several biallelic genes with initial frequency 0.5. we
see the effect of genetic drift in a population of size 10 (above) and a population of
size 100. We can see that the frequencies fluctuate longer (for more generations) in
the population of bigger size than in the other. Another interesting observation is that
the alleles have either of two finals fates: they become fixed (frequency = 1) or they
are lost (frequency = 0). The direct consequence of fixation is the decrease in
diversity: loci loose heterozygosity and become monomorphic. If alleles are lost in
multiallelic loci, the loose in diversity is seen in the reduction of allelic number (Na).
It is important to emphasize that the effect of genetic drift is more pronounced in
small populations.
Slide 21
Bottlenecks
A special case of random sampling is the bottleneck effect. Bottlenecks are a
extraordinary reduction in the population size due to outbreak of diseases, natural
disasters, habitat reduction of predation. The direct consequence of bottlenecks is that
the natural diversity is lost: rare alleles tend to disappear, heterozygosis is reduced and
inbreeding increases.
An example of severe bottleneck is that of the cheetah, species that suffered an
important reduction in population size by the end of the last glacial age, 10 000 years
ago (Menotti-Raymond and O’Brien 1993), when massive extinction of large
mammals took place on several continents.
Another example of bottleneck effects is that of overhunted species, such as the
American bison, with estimated population sizes of over 60 million before 1492, that
were reduced to only 750 animals in 1890. The present population size recovered to
350000 animals.
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References
Menotti-Raymond M and O'Brien S J (1993). Dating the genetic bottleneck of the
African cheetah. Proc Natl Acad Sci U S A. 15; 90: 3172–3176.
http://en.wikipedia.org/wiki/Population_bottleneck
Cheetah image: www.worldalmanacforkids.com
Bison image: www.ownbyphotography.com
Slide 22
Founder effect
Founder effect is another special case of random sampling in populations. It is a
special case of bottleneck in which a new population is established by a small number
of individuals from the original population that are not representative of the total
genetic variation.
The occurrence of porphyria in South Africa at a higher frequency than in other
populations is a case of founder effect. Variegate porphyria is an autosomal dominant
trait that consists of a mutated (and therefore deficient) protoporphyrinogen oxidase,
the last enzyme in the chain to synthesize the hoem group. This causes foto sensibility
in the skin and neurovisceral crisis. The origin of all south Africans suffering from
prophyria can be traced back to Ariaantje and Gerrit Jansz, who emigrated in the
1680s from Holland to South Africa, one of them bringing along an allele for the mild
metabolic disease porphyria. They had 8 children, 4 of them suffered from
porphyria. Today more than 30000 South Africans carry this allele.
Porphyiria
Hift RJ, Meissner PN, Corrigall AV, Ziman MR, Petersen LA, Meissner DM,
Davidson BP, Sutherland J, Dailey HA, Kirsch RE.(1997) Variegate porphyria in
South Africa, 1688-1996--new developments in an old disease. S Afr Med J.
87:722-31.
http://www.usoe.k12.ut.us/curr/science/core/bio/genetics/porphyria.htm
http://users.rcn.com/jkimball.ma.ultranet/BiologyPages/P/Polymorphisms.html
http://wiki.cotch.net/index.php/Founder_effect
image: http://www.nlm.nih.gov/medlineplus/ency/images/ency/fullsize/2573.jpg
Slide 23
Migration
Migration in the evolutionary sense implies movement of alleles from one population
to another population. In other words, there is gene flow between populations.
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Mechanisms of gene flow are dispersal of juveniles or larvae, transport of pollen,
sores, etc. by wind, occasional long distance dispersal, etc.
One of the most widely utilized models of migration is the continent-island model, in
which the direction of the migration in one direction is more important than the
almost negligible migration from the island to the continent.
In the slide we see the picture of the continent-island migration model. Imagine that
allel A1 is fixed in the island and allele A2 is fixed in the continent [ in other words
genotypic frequencies for the locus A are, in the island: A1A1=1; A1A2 = 0 and
A2A2 = 0; and in the continent A2A2=1; A1A2 = 0 and A1A1 = 0]. After a major
migration event from the continent, 80 % of the island population is A2A2 (q2 = 0.8)
and 20% A1A1 (p2 = 0.8). These genotypes are out of HWE, but the eqiolibrium is
attained after 1 generation of random mating. Migration can thus act as an
homogenizing factor.
Slide 24
Population structure
Population structure is almost universal among organisms. Many occur as flocks,
herds, colonies, and display patchy distribution. Besides, the natural habitat can
become fragmented because of the onset of barriers and subpopulations consequently
undergo isolation.
In this scenario, genetic differentiation occurs because different subpopulations would
acquire different allelic frequencies through the processes of selection and drift in the
presence of non-random mating (inbreeding) and restricted migration (gene flow).
The opposite of this situation is panmixia or random mating.
The differences in allele frequencies among subpopulations caused by local
inbreeding and fixation of alleles by random drift, determine that the overall
heterozygosity is lower than the expected under HWE in panmixia. This effect was
described by sewen statistitian Sten Wahlund, and therefore was so called “Wahlund
effect” after him.
The breeding structure of a population can be described by a hierarchical grouping of
inclusive levels: within a subpopulation, between subpopulations, overall
subpopulations. The inbreeding effect at each of these levels is described by a specific
fixation index F for multiple loci (Nei 1977):
FIS = (Hs – Ho) / Ho
Where Hs is the average expected H within a certain subpopulation.
Ho is the average expected H within subpopulations overall loci
Fis measures the correlation of alleles with individuals, the correlation between 2
uniting gametes within the subpopulation. It indicates the degree of inbreeding of a
subpopulation; it is a measure of deviation of HWE within a subpopulation. A
positive value indicates deficiency of heterozygotes.
FIT = (HT – H0) / HT
Where HT is the average expected H in the total population overall loci.
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FIT is the correlation between 2 uniting gametes relative to the total population. It is
the overall inbreeding coefficient (F) of an individual relative to the total population
(Individual within the Total population). Fit is rarely used
FST = (HS – HT) / HT
Fst is the correlation between two gametes drawn at random from each subpopulation
and measures the degree of differentiation between subpopulations. It measures the
reduction in heterozygosity in a subpopulation due to genetic drift. In other words, it
is the proportion of the total heterozygosity that is explained by the subpopulation
heterozygosity. When Fst = 0 subpopulations are not differentiated.
See example in Slide 11, Class III.
Population genetics webpages and links
http://dorakmt.tripod.com/genetics/popgen.html
Slide 25
Examples of population subdivision
In this slide we see two numerical examples of a study of genetic differentiation
between 2 populations. Imagine we want to investigate the level of gene flow between
two sites on the geographical distribution of a species.
In the first example we have two population with same allele frequencies, but one of
them is out of HWE, with deficiency of heterozygotes, which is indicated by the
deviation of Fis from 0. The deficit of heterozygote in the second population deviates
Fit from 0. However, because the allelic frequencies between these populations are
similar, the Fst value is 0, indicating gene flow and no genetic differentiation.
The second example shows two population in HWE, but because of the variation in
allele frequencies between them, Fit and Fst are different from 0. Fst ≠ 0 indicates no
gene flow, population structure, population subdivision.
Slide 26
Gene lineages
The examples we saw in the previous slides show a snapshot of the present situation
of a population or group of populations. If we add history to the distribution of genetic
diversity we have a historical perspective: lineages are represented by phylogenetic
trees or networks, that implicit time.
An evolutionary lineage (also called a clade) is composed of species, taxa, or
individuals that are related by descent from a common ancestor. Lineages are often
determined by the techniques of molecular systematics. A lineage can be
distinguished from a mere collection of species by the fact that it contains only and all
individuals that share a common ancestor.
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In phylogenetic reconstructions above the species level, the lineages are represented
by dicotomic trees, where the nodes represent an extinct common ancestor and the
legth of the branches represent the amount of change accumulated since the
divergence.
Below the species level, the lineages can also be represented by phylogenetic trees,
but are better represented by networks, as the “ancestors” (represented by individuals
at the nodes) are alive, and networks allow polytomies.
In the slide we present an example of a phylogenetic tree of several Diptera, and a
network of all detected mtDNA haplotypes for the microfrog Microbatrachella
capensis.
Within species, the most common genetic markers to reconstruct genealogies are
those of uniparental inheritance: DNA sequencies in mtDNA and markers (DNA
sequencies or microsatellites) in the Y chromosome in mammals.
When the lineages are superimposed to their biogeographic distribution, the analysis
of population structure takes a biogeographic and historical perspective.
Fly phylogeny image:
http://www.inhs.uiuc.edu/cee/FLYTREE/images/flyphylogeny.jpg
Network image: unpublished work of Will L. N., Scott E., Kryger U., Dawood A.,
D’Amato M.E., De Villiers A.L.. Genetic variability between populations of the
critically endangered frog Microbatrachella capensis, Boulenger 1910 (Anura:
Ranidae: Cacosterninae;)
Definition in: http://en.wikipedia.org/wiki/Lineage_(evolution)
Slide 27
Diversity in uniparental markers
The most utilized measure of diversity for diploid markers is H (heterozygosity).
Equivalent measures of diversity were also designed for uniparental markers like
mtDNA sequences.
The simplest one is the “haplotype diversity” h, which is simply the relative number
of haplotypes present in a population. It is obtained by dividing the different
haplotype counts by the total number of individuals.
The other well-extended measure is the nucleotide diversity, which is equivalent to
the heterozygosity at the nucleotide level. It measure the average number of
nucleotide differences between haplotypes at the population. It is given by the
equation
n / (n-1) Σ xixj ij
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where  ij is the proportion of different nucleotide between sequence i and sequence j.
n is the total number of sequences in the sample. Xi and xj are the frequencies of
sequences xi and xj in the population.
For instance, a sample with high haplotype diversity means that the proportion of
different haplotypes in the population is high. A value of h = 0.9 indicates that 90% of
the individuals carry a different haplotype.
A value of 0.001 indicates that, on average, the sequences in this sample differ in
0.1 %, or that, in pairwise comparisons, 2 any sequences taken from this sample
would differ in 1 out of 1000 nucleotides. This is a very low nucleotide diversity
value.
Now, assuming that these two measure were taking in the same population we can say
that this sample is composed by a high number of haplotypes, and that all are very
similar to each other. A possible evolutionary scenario for this case is that of a recent
population expansion, where a considerable number of new haplotypes have recently
originated from one or a few haplotypes. When this is portrayed as a network, it is
represented as a star-shaped phylogeny.
Slide 28
Phylogeography (See example in Slides 1-3, Class III)
Phylogeography is the study of the processes controlling the geographic distributions
of lineages by constructing the genealogies of populations and genes (Avise 2000).
Phylogeographical inferences are usually made by studying the reconstructed
genealogical histories of individual genes (gene trees) sampled from different
populations. The processes that can be inferred from a tree or network are historical
demographical factors like population bottlenecks, population expansions, and levels
of gene flow (e.g. vicariance).
The network in the slide was reconstructed from variation at the mtDNA control
region of 300 haplochromine cichlids from Lake Victoria region. Cichlids underwent
an explosive radiation (rapid diversification and speciation) during the Pleistocene.
The size of the circles represent the frequency in the sample, the colours indicate the
geographical origin of the sample. The star-shaped phylogenies represent a population
expansion: the diversification process starts from a frequent haplotype. The presence
of the same haplotype in different regions indicates gene flow (e.g. the biggest circle
on the left hand side represent a haplotype that is present in Lake Kivu and Uganda
lakes.
References
Avise, J. C. (2000). Phylogeography: the history and formation of species, Harvard
University Press.
The figure was taken from
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Verheyen E, Salzburger W, Snoeks J, Meyer A (2003). Origin of the Superflock of
Cichlid Fishes from Lake Victoria, East Africa. Science 300:325-329.
Slide 29
ESU
Several factors have to be taken into account to decide whether or which populations
are of value to maintain the evolutionary potential of the species. The principles of
population genetics and the utilization of a variety of molecular markers facilitated in
the last 2 decades the identification of population or species that can be particularly
vulnerable to extinction due to, e.g., reduction in diversity, or populations that
represent unique or rare lineages. Most of the phylogenetic reconstruction and
identification of lineages utilized neutral variation. Thus, the concept of ESU gave
major importance to identification of lineages and phylogenetic reconstruction.
Nowadays, the adaptive value of a population, although sometimes difficult to
measure, it proposed to be taken into account. Following, we review the concepts of
ESU that have been utilized in the last 15 years:
Ryder 1986: populations that actually represent significant adaptive variation based
on concordance between sets of data derived by different techniques.
Waples 1991: populations that are reproductively separate from other populations and
have unique or different adaptations.
Moritz 1994: populations that are reciprocally monophyletic for mtDNA alleles and
show significant divergence of allele frequencies at nuclear loci.
More recently, Crandall (Crandall 2000) incorporated the concepts of “genetic” and
“ecological exchangeability” to define ESUs
Ecological exchangeability implies that individuals can be moved to the area occupied
by other individuals of the same species and occupy the same niche or selective
regime. Characters that confer ecological exchangeability should be heritable.
Ecological exchangeability is rejected when populations underwent differentiation
due to drift or selection, if they display different loci under selection or different life
history traits.
Genetic exchangeability is directly related to the level of gene flow. Unique alleles,
low gene flow estimates and phylogenetic divergence concordant with geographic
barriers are criteria for rejecting genetic exchangeability.
References
Crandall KA, Bininda-Emonds ORP, Mace GM, Wayne RK (2000) Considering
evolutionary processes in conservation biology. Trends Ecol. Evol., 15, 290-295.
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Moritz, C. (1994) Defining ‘evolutionary significant units’ for conservation. Trends
Ecol. Evol. 9, 373–375.
Ryder, O.A. (1986) Species conservation and systematics: the dilemma of subspecies.
Trends Ecol. Evol. 1, 9–10
Waples, R.S. (1991) Pacific salmon, Oncorhynchus spp., and the definition of
‘species’ under the endangered species act. Mar. Fish. Rev. 53, 11–22
For reciprocal monophyly:
Phylogeography of the barbel (Barbus barbus) assessed by mitochondrial DNA
variation. Molecular Ecology Volume 10 Page 2177 - September 2001
Bats: Nature 424, 187-191 (10 July 2003) | doi: 10.1038/nature01742
Strong population substructure is correlated with morphology and ecology in a
migratory bat
Cassandra M. Miller-Butterworth1,2,3, David S. Jacobs1 and Eric H. Harley2
http://www.clanlindsay.com/genetic_dna_glossary.htm
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