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Section 13
Use of molecular genetics in forensics &
to understand species biology
Genetic markers contribute to the conservation
of species by aiding in detection of illegal
hunting and by resolving important aspects of
species biology; genetic markers have been used
for the following:
To detect bottlenecks & other demographic
events in a populations history
Estimating effective population size
Detecting selection
Determining parentage, gender, mating systems,
population structure, dispersal rates, population
Size, diet, and disease status
Poaching and illegal harvest are threats to a wide
variety of endangered species, especially large
cats, elephants, bears, rhinos,parrots, whales,
and some plants.
Most countries have laws to protect threatened
plants and animals.
However, it is often difficult to obtain evidence
to convict individuals suspected of illegally taking
or trading in threatened species -- case of
Australian airport, person, eggs.
Molecular genetic techniques have assumed an
important and growing role in the detection of
illegal hunting of wildlife.
The US Fish and Wildlife Service has established
The Clark Bevin Forensics Laboratory in Oregon
specifically for the purposes of providing
evidence in cases involving illegal exports,
imports & hunting of endangered species.
Following many years of
commercial exploitation,
The numbers of most whale
species collapsed.
This led the International Whaling Commission
(IWC) to institute a global moratorium on
Commercial whaling that took effect in 1985/86
Some IWC members have
continued to hunt a few
whale species (primarily
minke whales) for scientific
purposes and the whale
meat can be sold for human
consumption.
There were suspicions that protected whale
species were being marketed as species that
could be taken legally.
At the request of Earthtrust, Baker & Palumbi
developed a PCR based system for monitoring
trade in whale and dolphin products based on
mtDNA sequence variation.
First, they reliably distinguished a variety of
whale and dolphin species from each other using
mtDNA control region sequence variation.
Samples of whale products were subsequently
purchased in retail markets in Japan and Korea.
Samples of whale products were subsequently
purchased in retail markets in Japan and Korea.
To avoid the possibility of violating laws governing
transport of endangered species, Baker & Palumbi
set up a portable PCR laboratory in their hotel
room and amplified the mtDNA control region
from the samples.
The amplified DNA was taken back to their labs
in New Zealand and the USA and sequenced.
Following is their results from the original 16
purchases:
Minke whale
Minke whale
Sample #19a
Sample WS3
Sample #9
Sample #15
Sample #29
Sample #30
Sample #36
Sample #6
Minke whale
Sample #18
Sample #19b
Humpback whale
Humpback whale
Gray whale
Gray whale
Blue whale
Blue whale
Sample #41
Sample #3
Sample #11
Sample WS4
Fin whale
Fin whale
Sei whale
Sei whale
Bryde’s whale
Bowhead whale
Bowhead whale
Right whale
Pygmy right whale
Sperm whale
Pygmy sperm whale
Sample #16
Harbor porpoise
Sample #13
Sample #28
Hector’s dolphin
Commerson’s dolphin
Killer whale
By 1999, 954 samples of “whale meat” had been
purchased in Japan and Korea and analyzed by
various scientific groups; 773 (81%) were from
whales, approximately 9% coming from protected
whale species.
Samples not from whales included dolphins,
porpoises, sheep, and horses.
Not only were consumers being misled, but there
were questions regarding the origin of the meat.
The possibility that meat from protected species
had been sourced from frozen stores collected
prior to bans on whaling cannot be excluded, but
this explanation does not apply to fresh meat.
This has led to stricter controls over the
distribution of “scientifically harvested” whale
meat and demands that legally harvested whales
and meat stockpiled prior to whaling bans be
genetically typed to monitor distribution.
Similar to the example with whales, a PCR-based
mtDNA analysis revealed that 23% of caviar
samples in New York was mislabelled.
The sources of the caviar have conservation
implications, as most of the 27 members of the
sturgeon group are endangered due to overfishing
and habitat degredation.
The identity of a poached endangered Arabian
oryx was confirmed by microsatellite analyses
and mtDNA-based methods are being developed
to detect tiger products in Asian medicines.
Forensic DNA methods have been used to
determine the source of poached chimpanzees.
Sequencing of mtDNA established that 26
confiscated chimpanzees in Uganda belonged to
the eastern subspecies.
This identified the region where poaching was
taking place, and where these animals could be
reinstated into the wild.
Gene Trees and Coalescence
Coalescence and gene trees derived from data on
sequence differences among individuals and
populations are important tools for exploring
evolutionary processes and demographic events
in a species’ past.
Based on neutral theory, these provide a null
hypothesis against which to test data and to
discriminate possible reasons for deviations.
Moreover, calescent methods work backwards in
time and allow time dimensions (generations) to be
added to the analyses.
Consequently, they are more powerful than
conventional analyses that use only current
distributions and patterns of DNA sequence
difference.
Coalescence is based on the concept that current
allelic sequences in a population can be traced
back through time to a point at which they
coalesce to a single individual sequence.
Other alleles, once present in the past, have
been lost by genetic drift or selection, and new
alleles have been generated through mutation.
The evolutionary pattern of the extant distribution
of alleles at a locus can be represented as the
branches of a tree coalescing back to a single
ancestral allelic sequence.
Coalescent patterns are usually depicted using
gene trees, which show the genealogy of the alleles
in the current population.
The nodes (coalescent events) and branch lengths
in the tree reflect the origins and time frames
involved in deriving the observed patterns.
Gene trees trace the evolutionary history of alleles
in the same manner as tracing the origin, or loss,
of alleles through pedigrees.
DIVERGENCE
PAST
0
A
B
C
D
E
F
PRESENT
PAST
0
A
B
C
D
COALESCENCE
E
F
PRESENT
The basis of the coalescence method is that DNA
sequence differences among alleles at a locus
retain information about the evolutionary history
of those sequences.
For example, two alleles that differ by 2 bases
are more closely related and diverged more
recently than 2 alleles that differ by 11 base
pairs.
Neutral theory allows us to predict the time in
generations back to coalescence, thus adding a
time dimension to analyses.
Under neutral theory, two alleles may descend
from the same ancestral allele in the previous
generation with a probability 1/Nef for mtDNA,
or 1/2Ne for a nuclear diploid locus.
Alternatively, two alleles may derive from two
different alleles in the previous generation (or
derived from the same allele many generations
ago) with probabilities 1 - 1/Nef, or 1 - 1/2Ne.
This is the same reasoning used to determine loss
of genetic diversity.
Under the neutral model of genetic drift, the
coalescence process takes a characteristic time.
In a diploid population with k alleles at a neutral
locus, the average time Tk back to the previous
coalescent event (i.e., where there were k - 1
alleles) is:
Tk = 4Ne/[k(k-1)] generations.
T2 E(T2) = 2N
Thus, the times
Past
during which
T3 E(T3) = 2N/3
T4 E(T4) = 2N/6
There are 5, 4,
T5 E(T5) = 2N/10
Present
3, and 2
1 2 3 4 5
lineages are 2Ne/10, 2Ne/6, 2Ne/3, and 2Ne
generations, respectively.
The time for all alleles in the population to
coalesce is 4Ne/[1 - (1/k)] generations.
Thus, the coalescence is quicker, and gene trees
shorter, in smaller than larger populations.
Thus, it should be obvious to see that gene tree
analyses can provide information about
differences in historical population size for
different populations or species.
Example: In a population with Ne = 50 with 3
alleles, the expected time to its previous
coalescence (when the population had only 2
alleles) is:
T3 = 4Ne/[k(k-1)] = (4X50)/(3X2) = 33 generations
Thus, 3 alleles will coalesce to 2 alleles on average
in 33 generations in a population of size Ne = 50.
For Ne = 100 coalescence takes:
T3=4Ne/[k(k-1)] = (4X100)/(3X2) = 67 generations.
Thus, the coalescence takes twice as long in a
population with twice the size.
Therefore, the coalescence times increase in
direct proportion to population size.
The structure of gene trees and patterns of
coalescence are strongly influenced by deviations
from neutrality and random mating.
For example, different forms of selection affect
the coalescence time in characteristics ways;
directional selection reduces the coalescence
time, while balancing selection increases
coalescence time, compared to the expectation
with genetic drift.
Neutral
Balancing
Selection
Directional
Selection
After long periods of isolation and lack of gene
flow, populations show deep divisions among them.
Migration yeilds characteristic signatures when
gene trees are mapped onto geographic locations,
alleles characteristic of one geographic region
are found in another, partially isolated, region.
Fluctuations in population size of population
bottlenecks foreshorten coalescence time.
Mutations generate sequence differences, slowing
coalescence times.
Neutral
Locality A
Locality B
Geographic
Isolation
Locality A
Locality B
Migration
Population
Bottleneck
When patterns are
Similar, such as those
For directional selection
And population
Bottlenecks, additional
Iniformation is required
Directional
To resolve the cause.
Selection
Population
Bottleneck
For example, information on multiple unlinked loci
Allows discrimination of directional selection and
Bottlenecks; bottlenecks affect all loci in a similar
Manner while directional selection will affect each
Locus in a different manner.
Differences in DNA sequences, gene tree
structure and coalescence rates allow us to
infer details about population structure and
evolution that are not easily, or less acurately,
found using other techniques.
Analysis of gene trees, using coalescence
analysis, have been used to:
Estimate effective population size (using
selectively neutral markers)
Measure neutral mutatation rates
Infer selection and determine its form
Determine migration events and measure
migration rates
Determine phylogenetic relationships among
geographically separated populations
Detect secondary contact of diverged pops.
Estimate divergence times among pops.
Infer changes in population sizes
Reconstruct the origins and history of disease
epidemics
Demographic History
The distribution of the number of sequence
differences between pairs of alleles ( a “mismatch”
analysis) has characteristic shapes for populations
with different demographic histories.
Populations with historically stable population size,
exponentially growing populations, population
bottlenecks, or populations experiencing secondary
contact leave different signals.
Frequency
Stable population growth
results in a geometric
distribution.
Stable
Pairwise Differences
Frequency
Exponential growth is
expected to generate
a smooth unimodal
distribution.
Exponentially
growing
Pairwise Differences
Frequency
Population
Bottleneck
Pairwise Differences
Secondary
Contact
Frequency
Bottlenecks yeild either a
distribution close to zero,
or a bimodal distribution,
depending on whether the
bottleneck reduced genetic
diversity, or completely
removed it (so that diversity
represents mutations since
that point).
Humans exhibit a unimodal distribution
Pairwise Differences
characteristic of exponential growth, which
accords with known human history.
Undocumented past bottlenecks can be detected
and their severity inferred from the loss of
genetic diversity.
Even when there are no samples of the
pre-bottleneck population, they can often be
identified using information from multiple
microsatellite loci.
Reintroduction of koalas
in southeastern
Australia: a poorly
designed program with
adverse genetic
impacts.
The koala is a unique marsupial
endemic to eastern Australia.
It is both a cultural icon and an
important contributor to tourist
income (~$70 million/yr).
The koala once ranged down
the East Coast from
Queensland to Victoria and
South Australia but its
numbers have been reduced
by hunting, habitat loss, and
disease.
At the peak of hunting in 1924,
2 million animals were shot.
By the 1930s, koalas inhabited
less than 50% of their former
range.
They had disappeared in South Australia
and were nearly extinct in Victoria.
However, they were still considered common in
Queensland where they subsequently recovered
without large-scale assistance.
The fur trade ceased by the 1930s when koalas
were accorded legal protection in all states.
Subsequently, much effort has
gone into koala conservation.
Extensive translocations of
animals occurred in the
southeast.
A population was founded from as few as 2 - 3
individuals on French Island (FI) in Victoria late
in the 19th century.
FI
This population grew rapidly in
the absence of predators and
rapidly reached carrying
capacity.
KI
Surplus individuals from this
FI
population were used to found an additional PI
population on Kangaroo Island (KI) (18 adult
Founders plus young) in 1923 - 1925, and to
supplement a population founded on Phillip Island
(PI) in the 1870s.
The French and Phillip Island
populations were used widely to
supplement mainland South
Australia.
KI
The restocked South Australia
mainland population has gone through threePI
bottlenecks: Mainland Victoria --> French Is.
--> Kangaroo Is. --> mainland South Australia.
Since 1923, 10,000 individuals have been
translocated to 70 locations.
FI
Stocking of populations using
individuals from bottlenecked
populations is expected to
result in loss of genetic
diversity and inbreeding.
KI
FI
PIof
As predicted, the southeastern populations
Victoria and South Australia have about half
the genetic diversity found in the less-perturbed
populations further north: 5.3 vs. 11.5 microsatellite
alleles per locus and heterozygosities (He) of
0.44 vs. 0.85.
DNA fingerprint and RAPD
analyses provide similar results.
As expected, the Kangaroo Is.
population had the lowest
genetic diversity of all surveyed
populations.
KI
PI
FI
All southeast populations showed similar
microsatellite allele frequencies, and similar mtDNA
haplotypes, while the more northern populations
exhibited considerable differentiation.
MT
GC
IL
NC
WNSW
ML
CB
TB
SZ
SG
KI
BR
SR
PI
FI
SP
MT
SP
GC
IL
ML
WNSW
CB
SG
BR
SR
KI
FI
PI
NC
Gene tree for koala populations, based on mtDNA sequence
divergence. Populations from Victoria & South Australia
(bottom), derived mainly from bottlenecked island
populations, are essentially indistinguishable. The remaining
populations generally show their closest affinities with
geographically adjacent populations, as expected with
isolation by distance.
Thus, translocations using individuals with low
genetic diversity have reduced genetic diversity
and distorted natural allele frequencies.
The translocations may have contributed to
reductions in reproductive fitness, including
lowered resistance to Chlamydia infection, to a
lowering of sperm concentrations and motility,
and to an increased frequency in testicular
abnormality.
What might have been done to avoid such
problems?
Loss of genetic diversity and inbreeding depression
would have been averted if the French Island
population had been founded with more individuals,
or if its genetic diversity had been augmented
to give it a greater base of genetic diversity.
The situation would have been much better if the
more diverse Phillip Island population had not been
“swamped” with French Island individuals.
What can be done to reverse the problem?
The most efficient strategy would be to introduce
more genetic diversity into the southeastern
populations (both mainland and island).
Since the koala population is somewhat
differentiated, this would best be done from
nearby populations.
The ideal solution would be discovery of a
remnant population in Victory with high genetic
diversity.
If none exist, then the best source of genetic
diversity is from New South Wales.
Genetic diversity should be checked in source
populations before they are used for
translocations.
Bottleneck effects have been measured by
comparing microsatellite genetic diversity from
the current populations with that from
museum speciemens as was done for Mauritius
kestrels.
The decline of the Mauritius kestrel began with
the destruction of native forest and the plunge
towards extinction resulted from thinning of
eggshells and greatly reduced hatchability
following use of DDT insecticides beginning in
the 1940s.
In 1974, its population numbered only four
individuals, with the subsequent population
descending from only a single breeding pair.
Under intensive management the population grew
to 400 - 500 birds by 1997, but it experienced
six generations at numbers less than 50.
While this is a success story, the Mauritius kestrel
carries genetic scars from its near extinction.
It now has a very low level of genetic diversity for
12 microsatellite loci, compared to six other
kestrel populations.
The Mauritius kestrel has 72% lower allelic
diversity and 85% lower heterozygosity than the
mean of the non-endangered kestrels.
Prior to its decline, the Mauritius kestrel had
substantial genetic diversity, based on ancestral
museum skins from 1829 - 1894, but even then its
genetic diversity was lower than the nonendangered species.
The Seychelles kestrel went through a parallel
decline and recovery and also has low genetic
diversity.
The Seychelles kestrel was rare during the 1960s
and had become extinct on many outlying islands.
However, it has now recovered to a population
size of 400 pairs.
The reproductive fitness of the Mauritius kestrel
has been adversely affected by inbreeding in the
early post-bottleneck population; it has lowered
fertility and productivity than comparable falcons
and higher adult mortality in captivity.
Not only can bottlenecks in population size be
detected, but also the size of the bottleneck
can often be inferred from loss of genetic
diversity.
Northern elephant seals
underwent a bottleneck
due to hunting with the
last major hunt occurring
in 1884.
Subsequently, the population expanded to 350 in
1922, to 15,000 in 1960 to well over 100,000 by
2000.
During this bottleneck, the seals lost both nuclear
and mitochondrial genetic diversity.
Only two mtDNA haplotypes occur in postbottleneck northern elephant seals, while 23
haplotypes are found in related southern elephant
seals.
No allozyme variation was found in the northern
elephant seals, while the average heterozygosity
is 0.03 in southern elephant seals.
The acutal size and duration of the bottleneck
is unknown.
Since loss of genetic diversity is related to
population size, we can estimate the bottleneck
size and duration.
The expected loss of mtDNA diversity is:
t
Ht = H0∏(1 - 1/Nefi)
i= 1
Where Nefi is the effective number of females in
generation i and t is the number of generations
from the beginning of the bottleneck until the
population is censused.
This equation is similar to one we learned earlier
but 2Ne is replaced by Nef as mtDNA is
maternally inherited and genetic diversity is lost
at a rate of 1/Nef.
The mtDNA diversity in southern elephant seals
is 0.980 (assumed to represent H0), while that
in northern elephant seals is 0.409 (Ht).
Many combinations of bottleneck size and durations
can fit these data, but only a limited range will
allow realistic growth in population numbers.
A single generation bottleneck would require the
effective number of females to be:
Ht/H0 = (1 - 1/Nef) = 0.409/0.980 = 0.417
yeilding Nef = 1.7
Thus, the effective number of females would be
less than 2. This is not compatible with the
observed population Growth, which requires a
minimum of about 12 females, unless the ratio of
effective number of females to actual number of
females is 0.14.
Further, additional genetic diversity is lost during
approximately 14 generations between the
bottleneck and 1960.
Hedrick (1995) assumed that Nef/Nf ratios lay
between 0.25 and 0.125.
The combination of parameters that best fit the
loss of mtDNA diversity and the changes in
population size were:
(a) A single generation female bottleneck of 12.4
with Nef/Nf = 0.25 (Nef=3.1) or
(b) A bottleneck of three generations with 44
females and Nef/Nf = 0.125 (Nef=5.5).
In both cases, population numbers were projected
To be close to those observed in 1922 and 1960.
Halley & Hoelzel (1996) reached similar conclusions,
Based on detailed computer simulations.
This bottleneck is not sufficient to account for
complete absence of allozymic variation.
Therefore, other factors must have come into
play to explain this loss of genetic variation in
northern
elephant seals.
Gene Flow and Population Structure
Genetic management recommendations vary
significantly depending on population structure.
Populations in different habitat fragments may be
totally isolated, partially isolated, effectively a
single population, or a metapopulation, depending on
the extent of gene flow and population extinction
rates.
Small and totally isolated populations may
experience severe inbreeding.
The delineation of population structure is usually
only possible using genetic data.
The degree of population differentiation can be
determined using FST and related measures for
any type of polymorphic genetic marker.
More powerful and informative analyses are
possible using gene trees.
Population structure can be identified by mapping
sequences of different alleles onto geographic
locations.
The cause of genetic
differentiation, restricted
gene flow, past
fragmentation, or range
expansion can then be
determined.
East African populations
of buffalo and impala
show similar FST-values
of 0.08 and 0.10,
respectively.
However, the distribution of mtDNA haplotypes over geographic locations is entirely
different in the two species.
27
20
19
8
26
4
3
12
2
5
17
22
9
21
14
6
18
13
10
16
1
28
15
8
24
21
21
12
15
11
11
23
13
14
7
25
16
5 10
1
9
6
4
7
3
2
25
20
17
18
23
19
24
The distribution of Chobe haplotypes (Chobe is most isolated location) is random in buffalo
but tightly clustered in impala. Consequently, buffalo exhibit recurrent genetic maternal
interchange between Chobe and more northerly populations.
Conversely, impala have restricted female gene flow that either reflects isolation-by-distance
or isolation of the Chobe population from northern populations.
Sexing of Birds and Mammals
Males and females of many bird species are
morphologically indistinguishable.
Birds must be sexed prior to pairing, as several
Cases of “infertile” pairs in zoos have turned out
to be two birds of the same sex.
Some mammals are also difficult to sex, especially
cetaceans and secretive species, as it may not be
possible to sex individuals when collecting samples
by skin biopsies, hair, etc. The sex of stored
DNA samples may not be known.
Birds have ZZ male and ZW female
sex-determination.
Consequently, PCR primers for W-chromosome
specific sequences have been developed to
distinguish males from females.
W-specific fragments will amplify from the DNA
of a ZW female but not a ZZ male.
Molecular sexing is an important component in
the program to recover the Norfolk Island
boobook owl.
While the program
had produced 12 - 13
individuals, of which
7 were F2, only 2
pairs were breeding.
It was unclear whether this was due to hybrid
sterility, unequal sex-ratio, or individuals of one
sex being immature.
As females and males could not be distinguished
by external morphology, a PCR-based technique
was used to sex the birds.
The population was found to consist of 6 females
and five males.
A scarcity of mature males was the main factor
slowing recovery efforts.
Disease
The disease status of animals is critical in
identifying causes of population decline, and for
checking candidates for translocation or
reintroduction.
PCR-based methods provide rapid, reliable and
highly sensitive means for detecting disease
organisms.
For example, PCR has been used to study avian
malaria in Hawaii, one of two diseases thought to
have been major factors in the decline of Hawaiian
birds.
Higher-elevation habitats, considered safe from
malaria-carrying mosquitos, have been preserved
for endangered forest birds.
However, Cann et al. (1996) identified malaria in
blood of birds from high-elevation habitats on
Maui and Hawaii, indicating that these areas are not
as safe as previously thought.
Reservoirs of the disease were also detected in
introduced bird species in low-elevation habitats.
Gene trees based upon DNA sequences have been
employed to determine the source of new diseases.
HIV-1, one of the viruses that causes AIDS in
humans, has been found to be most closely related
to SIV from chimpanzees, while HIV-2 originated
from soot mangabeys.
Similarly, an epidemic causing high mortality in
African lions in the Serengeti in 1994 was shown
to be due to canine distemper, presumed to have
switched species from local dogs.
Recommendations were made to vaccinate local dogs
against distemper to minimize the risk of repeat
epidemics in lions and, especially, in other rare
carnivores.
Diet
Diet is difficult to determine by direct observation
in nocturnal and secretive species.
Food items can be identified from faeces by using
PCR with primers specific to suspected food items.
This has been demonstrated in bears, where the
plant Photinia was identified as a food item.
The role of predators in causing the decline of
a threatened species has also been assessed
using a PCR-based application.
Microsatellite typing of stomach contents of
glaucous gulls in Alasks revealed that they were
preying on emperor geese, but not on threatened
spectacled eiders (Scribner & Brown 1998).
Since gull numbers have increased, gull predation
appears to be the major factor in the decline in
emperor geese numbers and their inability to
recover.
Gull removal has resulted in improved gosling
survival.