Calculating and comparing levels of genetic diversity in populations:

1
Calculating and comparing levels of genetic
diversity in populations
2
When trends from H and P do not agree Lion
Park Klaserie Locus 1 AA AA AA AA AA AA
AA AA AA AA AA AA AA AA AA AA AA AA
AA AB Locus 2 AA AB AB AC BB AA AA AA
AA AA CC AC BC CC AB AA AA AA AA
AB Locus 3 AA AA AA AA AA AA AA AA AA
AA AA AA AA AA AA AA AA AA AA
AB (How can this happen? Founder event)
3
Locus 1 Lion Park Klaserie AA AA AA AA
AA AA AA AA AA AA AA AA AA AA AA AA
AA AA AA AB
Allele frequencies A 20/20 1.0 A 19/20
0.95 B 0/20 0.0 B 1/20
0.05 Single locus heterozygosity h h 1
(1.02 0.02) h 1 (0.952 0.052) 1
1 1 0.905 0.0 0.095
4
Locus 2 Lion Park Klaserie AA AB AB AC
BB AA AA AA AA AA CC AC BC CC AB AA
AA AA AA AB
Allele frequencies A 7/20 0.35 A 19/20
0.95 B 6/20 0.30 B 1/20 0.05 C
7/20 0.35 Single locus heterozygosity h
h 1 (0.352 0.32 0.352) h 0.095 1
(0.335) 0.665
5
Locus 3 Lion Park Klaserie AA AA AA AA
AA AA AA AA AA AA AA AA AA AA AA AA
AA AA AA AB
Allele frequencies A 20/20 1.0 A 19/20
0.95 B 0/20 0.0 B 1/20 0.05
Single locus heterozygosity h h 1
(1.02 0.02) h 0.095 1 (1.0)
0.0
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Single locus heterozygosity values (h) Lion
Park Klaserie Locus 1 0.0 0.095 Locus
2 0.665 0.095 Locus 3 0.0 0.095 Average
heterozygosity (H) H 0 0.665 0 3 (
0.095) 3 3 0.222 0.095
7
Lion Park Klaserie Locus 1 AA AA AA AA
AA AA AA AA AA AA AA AA AA AA AA AA
AA AA AA AB Locus 2 AA AB AB AC BB AA
AA AA AA AA CC AC BC CC AB AA AA AA
AA AB Locus 3 AA AA AA AA AA AA AA AA
AA AA AA AA AA AA AA AA AA AA AA AB
Average no. of alleles per locus (A) ( allelic
diversity) A 1 3 1 2 2 2
3 3 1.667 2.0
8
Lion Park Klaserie Locus 1 AA AA AA AA
AA AA AA AA AA AA AA AA AA AA AA AA
AA AA AA AB Locus 2 AA AB AB AC BB AA
AA AA AA AA CC AC BC CC AB AA AA AA
AA AB Locus 3 AA AA AA AA AA AA AA AA
AA AA AA AA AA AA AA AA AA AA AA AB
Polymorphism (P) P 1 / 3 3 / 3
33 100
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• Overall diversity
• Lion Park Klaserie
• Average Heterozygosity 0.222 0.095
• Allelelic diversity 1.667 2.0
• Polymorphism 33 100
• Therefore
• estimates of diversity should be based on more
  than one coefficient
• some coefficients of diversity may be
  biologically more significant than others.

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Chapter 18 Quantitative Genetics
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18.1 Types of quantitative traits Continuous
traits A continuum of possible phenotypes,
e.g. - height, weight, milk yield, growth
rate (minimum lt x lt maximum) Meristic
traits Phenotypes are expressed as discrete
classes, e.g. - no of petals on a flowers, no
of bristles on fruit fly Threshold
traits Discrete traits that are either present
or absent, e.g. - diabetes, schizophrenia
12
18.3.2 Average effect Definition the average
effect of a certain allele is the mean deviation
from the population mean of individuals which
received that allele from one parent (the allele
received from the other parent having come at
random from the population).
13
18.3.3 Breeding value
The individuals expected progeny performance
relative to the population mean BV the value
of an individuals genes to its offspring.
the sum of the average effects of the alleles it
carries.
14
Chapter 19 Quantatative Trait Loci (QTLs)
15

• It can be useful to identify individual genes
  coding for specific traits, because
• it would improve the efficacy of selective
  breeding
• transgenic technology might be applied to
  quantitative traits
• ID of genes causing predisposition to common
  diseases could lead to improved methods of
  prevention and
• quantitative genetic theory will be more
  realistic when the numbers of genes affecting
  traits and their role in evolution is fully
  understood.

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QTLs are genetic markers that are strongly
associated with given characteristics. The
genotype of the QTL can be determined that of
the trait cannot.
17

• QTLs are not necessarily genes themselves, but
  are stretches of DNA closely linked to the genes
  that control the characteristic in question.
• QTLs are usually associated with continuous
  rather than discrete characters.
• Since a single trait is often controlled by
  several genes, many QTLs may be associated with a
  single trait. (Some of these may be on different
  chromosomes).
• QTLs identify a particular region of the genome
  as containing a marker that is associated with
  the trait being measured.

18
The presence of these markers in an individual
would suggest that the individual is likely to
possess the specific trait. Plus the
individual will likely pass these markers - and
therefore the trait - to its offspring.
19

• The most valuable QTL markers will be those that
  detect the actual genes coding for proteins
  involved in the expression of specific
  characteristic.
• At present most QTLs detect regions of the DNA
  that are located in close physical proximity to
  such genes.
• The tests for QTLs such as these are known as
  "linked tests." These "linked" markers may be of
  any of several types, for example microsatellite
  regions that detect varying allele sizes in
  physically close regions of the chromosome.

20
After testing a population and collecting data
for the trait, researchers attempt to
statistically associate markers with the
trait(s). The rate with which a marker is
associated with a given trait is usually reported
as a percentage "This QTL is associated with
the trait at a rate of 60."
21

• Limitations
• Several factors affect researchers' ability to
  confidently state that an individual "possesses"
  a characteristic (based on marker information).
• Quantitative traits are almost always the
  expression of numerous genes working together.
  The test for a given desired trait must therefore
  include markers for all of the genes associated
  with that trait. If a QTL test fails to include
  markers for one or more of the genes, the
  conclusions of the test will be incorrect or of
  low significance. To ensure the inclusion of
  markers for all genes, it is first necessary to
  determine which genes work together to control
  the trait.

22

• All estimates of the number of QTLs associated
  with a trait are probably minimum estimates (i.e.
  underestimate the real number of loci associated
  with a trait).
• Reasons
• The effects of some loci are probably just too
  small to be detected.
• The loci found are those differentiating the two
  strains being compared at that point. Other loci
  may well be found in other strains and under
  other circumstances.

23

• The nature of markers
• A marker is a locus where the genotype can be
  determined unambiguously.
• (Microsatellites, RFLPs, AFLPs).
• To perform a whole-genome QTL scan, it is
  desirable to have a saturated marker map ( cover
  as much of the genome as possible).

24

• Identifying QTLs
• A method used in agriculture
• Create a cross between 2 different inbred
  genotypes
• F1 offspring will be heterozygous at all loci
  (all chromosomal positions). (marker and trait)
• Following meiosis, the F1 gametes will carry a
  mosaic of the genotypes of the two parents.

25

• Now consider F2s
• Create a saturated map and genotype each marker.
• Measure phenotype of each individual.
• If a chromosomal region (marker) is linked to a
  given trait (segregate with the trait), then
  genotypes for the marker should be correlated
  with the phenotype.
• The closer the marker to the gene, the better
  the correlation will be.

26

• The circled region of the chromosome is
  correlated with body size.
• Homozygous red for marker small cattle
• Heterozygous for marker intermediate size
  cattle
• Homozygous blue for marker big cattle
• For the regions outside the box, there is no
  specific correlation between the marker genotype
  and the trait.

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QTLs and other traits

• This paper attempts to find QTLs for conditions
  such as
• PKU
• Fragile X syndrome
• Rett syndrome