Molecular Evolution: Selection

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Molecular Evolution Selection

• the ratio between the number of non-synonymous
  substitutions (KA) and synonymous substitutions
  (KS) in a gene during a specific evolutionary
  period.
• Assuming that KS provides an index of the random
  mutation rate, the KA/KS ratio measures whether
  the rate of protein evolution differs from the
  rate expected under neutral drift.
• If KAgtKS, this is taken to indicate accelerated
  amino-acid change, which might be due to positive
  selection.
• Conversely, if KAltKS, this suggests purifying
  selection.

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Brain Development in Primates

• MCPH1 (the gene that encodes microcephalin)
• and ASPM (abnormal-spindle-like, microcephaly
  associated)
• Both MCPH1 and ASPM are evolutionarily ancient,
  with orthologues that are likely to be present in
  all chordates

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MCPH
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MCPH
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(A) Schematic representation of the alignment.
Promoter regions, exons, and introns are marked
in gray, red, and blue, respectively. White
segments correspond to gaps. (B) Positions of
long (50 bp or longer) insertions/deletions. O
denotes orangutan, M macaque, OGCH the
orangutangorillachimpanzeehuman clade, and
GCH the gorillachimpanzeehuman clade. (C)
Positions of polymorphic bases derived from the
GenBank single nucleotide polymorphism (SNP)
database. (D) Positions of the CpG island. The
approximately 800-bp-long CpG island includes
promoter, 5' UTR, first exon, and a small portion
of the first intron. (E) Location of an
approximately 3-kb-long segmental
duplication. (F) Positions of selected motifs
associated with genomic rearrangements in the
human sequence. Numbers in parentheses reflect
number of allowed differences from the consensus
motif (zero for short or two ambiguous motifs,
two for longer sites). (G) Distribution of
repetitive elements. The individual ASPM genes
share the same repeats except of indels marked in
(B). (H) DNA identity and GC content. Both plots
were made using a 1-kb-long sliding window with
100-bp overlaps. The GC profile corresponds to
the consensus sequence the individual sequences
have nearly identical profiles.
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Linkage Studies

• Monogenic and Complex Studies

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Nail-Patella Syndrome

• Nail Patella Syndrome (also called Fong's
  Disease, Hereditary Onycho-Osteodysplasia
  'HOOD' is characterized by several typical
  abnormalities of the arms and legs as well as
  kidney disease and glaucoma

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Recombination Frequency

• to determine the linkage distance between the two
  genes (B/O and NP genes). The original mating in
  generation I and the first two matings in
  generation II are test cross. The third mating in
  generation II is not informative because it
  involves the A allele which we are not following.
  We have a total of 16 offspring that are
  informative. Of these three were recombinant. As
  with all test crosses, this gives a genetic
  distance of 18.8 cM 100(3/16).

http//www.ndsu.edu/instruct/mcclean/plsc431/link
age/linkage6.htm
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Lod Score Method of Estimating Linkage Distances
The following pedigree will be used to
demonstrate a method developed to determine the
distance between genes. This approach has been
widely adapted to various system and genetic
programs have been developed based on this
technique.                                        
                     
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Pedigree

• Even though we are working with the same two
  genes, nail-patella and blood type, in this
  pedigree the dominant allele seems to be coupled
  with the A blood type allele.
• Remember in the previous example, the dominant
  nail-patella allele was linked with the B allele.
  This is an important point in genetics --- not
  all linkages between alleles of two genes are
  found to be constant throughout a species.
• Why??? Because at some point in the lineage of
  this family, the disease (nail-patella) allele
  recombined and became linked to a different blood
  type allele. In even other lineages, the
  nail-patella causing allele is linked to the O
  blood type allele.

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Recombination Frequency

• we have one recombinant among the eight progeny.
  This gives us a recombination frequency of 0.125
  and a distance of 12.5 cM.

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LOD Score Method

• developed by Newton E. Morton, and is an
  iterative approach that include a series of lod
  scores calculated from a number of proposed
  linkage distance.

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LOD Score Method

• A linkage distance is estimated, and given that
  estimate, the probability of a given birth
  sequence is calculated. That value is then
  divided by the probability of a given birth
  sequence assuming that the genes are unlinked.
  The log of this value is calculated, and that
  value is the lod score for this linkage distance
  estimate.

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LOD Score Method
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Example

• In this first birth sequence, we have an
  individual with a parental genotype. The
  probability of this event is (1 - 0.125). Because
  there are two parental types, this value is
  divided by two to give a value of 0.4375. In this
  pedigree we have a total of seven parental types.
  We also have one recombinant type. The
  probability of this event is 0.125 which is
  divided by two because two recombinant types
  exist.

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Example

• What would the sequence of births be if these
  genes were unlinked?
• When two genes are unlinked the recombination
  frequency is 0.5. Therefore, the probability of
  any given genotype would be 0.25.

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Linkage Probability

• The probability of a given birth sequence is the
  product of each of the independent events. So the
  probability of the birth sequence based on our
  estimate of 0.125 as the recombination frequency
  would be equal to (0.4375)7(0.0625)1 0.0001917.

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Non-linkage Probability

• The probability of the birth sequence based on no
  linkage would be (0.25)8 0.0000153.

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Calculation of LOD score

• Now divide the linkage probability by the
  non-linkage probability and you get a value of
  12.566. Next take the log of this value, and you
  obtain a value of 1.099. This value is the lod
  score.
• LOD 0.0001917/ 0.0000153log(12.566)

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In practice, we would like to see a lod score
greater that 3.0. What this means is that the
likelihood of linkage occurring at this distance
is 1000 times greater that no linkage.
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Case Control Studies

• Modified from Iris A. Granek, M.D., M.S.

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Case-control studies

• Search for differences in allele frequency
  between disease carriers (cases) and non carriers
  (controls) with the assumption differences in
  frequencies are associated with disease outcome.
• Can be applied to exposure to a chemical or a
  carcinogen instead of allele (genotypes).

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Case Selection

• Define the source population
• residents of a geographic region
• hospital inpatient or clinic
• Strict case definition
• inclusion criteria

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Control Selection

• Same source population as the cases
• Choose the controls by random from the source
  population
• spouses
• associates
• patients within the same facility
• matched for certain criteria

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Hospital Controls

• Without regard to diagnosis
• Excluding certain diseases
• Including only diseases believed to be unrelated
  to the exposures (or alleles) being studied
• Clinic patients from same hospital

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Case Control Study Design

• Compares distribution of exposure
• cases (disease)
• vs.
• controls (without disease)

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Exposure History Cases Controls

• CASES CONTROLS
• Exposed a b
• Not Exposed c d
• Totals ac bd
• Proportions a b exposed ac bd

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Distribution of past benzene exposure among
leukemia cases vs. controls

• 20 leukemia cases found among large group of
  chemical workers
• 16 cases had past benzene exposure
• Proportion of cases exposed to benzene
• 16/2080

• 100 healthy controls randomly selected from same
  group of chemical workers
• 12 controls had past benzene exposure
• Proportion of controls exposed to benzene
• 12/10012

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Odds Ratio Unmatched Analysis

• CASES CONTROLS
• EXPOSED a b
• NOT EXPOSED c d
• Ratio of odds of exposure in cases a/c
• odds of exposure in controls b/d
• Odds Ratio OR ad
• bc

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Odds Ratio Unmatched Analysis

• LUNG CA CONTROLS
• BENZENE 16 12
• NO BENZENE 4 88
• Ratio of odds of exposure in cases 16/4
• odds of exposure in controls 12/88
• Odds Ratio OR 16 X 88 29.3
• 4 X 12

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Odds Ratios

• OR gt 1 indicates a positive association between
  the factor and the disease
• The lung cancer patients were 29 times more
  likely than the controls to have been exposed to
  benzene
• OR lt 1 indicates the factor is protective
• OR 1 indicates no association

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95 Confidence Limits

• 95 probability that the true value lies within
  the confidence interval or between the confidence
  limits
• Odds ratios are statistically significant if they
  do not include 1
• OR 7 (0.5 - 15.0) not statistically significant
• OR 7 (3.0 - 12.0) is statistically significant

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Advantages of Case Control

• Quick and Inexpensive
• Optimal for rare diseases
• Useful for diseases of long latency from exposure
  to disease development
• Can evaluate multiple risk factors

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Bias in Case Control Studies

• Bias is a systematic error in the study that
  distorts the results limits the validity of the
  conclusions.
• Selection Bias
• Confounding
• Observation Bias (recall bias, interviewer bias,
  misclassification)

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Selection Bias

• Systematic errors arising from the way the
  subjects are selected
• Study subjects are selected in a way that can
  misleadingly increase or decrease the magnitude
  of an association
• Exposure of cases differs from exposure of all
  cases in source population or exposure of
  controls selected differs from non diseased in
  source population

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Selection Bias
Source Population
Study Sample
E E E E X X X X X X X X With disease
E E E E X X Cases
E E E E E E E E X X X X Without disease
E E X X X X Controls
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Confounding

• Distortion of the true relationship between the
  exposure and outcome due to a mutual relationship
  with another factor
• Can be the reason for an apparent association
  also may cause a true association to not be
  observed
• Confounder must be associated with the outcome
  and the exposure

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Confounding Factors
Benzene Exposure
Lung Cancer
Cigarette Smoking
(Confounder)
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Controlling for Confounding

• The effect of confounding variables
• can be controlled during the data analysis by
  various methods
• stratification
• multivariate analysis
• can be controlled during the study design by
  matching controls and cases for the factor

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Matched Case Control Design

• Controls selected matched to cases on factors
  associated with the disease
• age, sex, race, socioeconomic status
• Makes the two groups similar on factors other
  than the exposure of interest
• Cannot compare groups on matched factors
• Must used matched analysis

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Observation Bias

• Interviewer (data collection) bias
• keep data collection same for cases and controls
• Misclassification Bias
• incorrect characterization of exposure
• Recall Bias
• recall of exposures may be influenced by current
  disease status

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Calculate the Odds Ratio
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Esophagial cancer and alcohol
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Fishers Exact Test
http//www.matforsk.no/ola/fisher.htm
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