PS401- Lec. 3

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					     Mapping Basics



MUPGRET Workshop
  June 18, 2004
Randomly Intermated
           P1 x       P2

                 
                F1
                 SELF

                F2
   1 2 3 4 5 6 7 ……
   One seed from each used for next generation
   Recombination.

   After recombination self to create line.
       Randomly Intermated.

 Very high resolution.
 Accumulates recombination events across
  generations and fixes them.
 Excellent for fine mapping
 Only homozygous genotypes.
          Population Size
 Dependent on type of population
 Generally 200-300 individuals
 If doing trait analysis, the number of
  individuals determines the maximum
  number of QTL you can find.
 Two samples from the same population will
  produce different maps because they sample
  different gametes.
    Genetic Mapping Basics
 Gene: a particular sequence of nucleotides
  among a molecule of DNA which
  represents a functional unit of inheritance.
  (Johannsen, 1909)
 Locus: the position of a gene on a
  chromosome or a genetic map. (Morgan,
  Sturtevant, Muller, and Bridges, 1915)
          More terminology
 Linkage: the association in inheritance of
  certain genes and their associated
  phenotypes due to their being localized in
  the same chromosome. (Morgan, 1910)
 Linked: two genes showing less than 50%
  recombination.
              More terms
 Recombination: Any process which gives
  rise to cells or individuals (recombinants)
  associating the alleles of two or more genes
  in new ways. (Bridges and Morgan, 1923)
 Recombinants are the end products of
  exchange of alleles from parental types as a
  result of crossing-over.
              Terminology
 Phenotype: the observable properties of an
  organism, produced by the interaction
  between the organism’s genotype and the
  environment (Johannsen, 1909).
 Genotype: the genetic constitution in
  respect to the alleles at one or a few genetic
  loci under observation. (Johannsen, 1909).
           Recombination




Parental          Recombinant
 Recombination and Mapping
 Assume the frequency of crossing-over is
  equal along the chromosome.
 Two genes that are very close to one
  another will have a lower likelihood of
  having a cross-over between them than two
  genes that are far apart.
Recombination and Mapping
   So, we can determine the relative distance
    between genes by counting the number of
    recombinant genotypes for each pair of
    genes.
    – Lots of recombinants = far apart
    – Fewer recombinants = close together
           Two Point Analysis
   Parental Types      Recombinant Types
    Tall, Green          Tall, White
        42                  7


    Short, White         Short, Green
       39                   12


       =81%                 =19%
                 Map Units
   1 map unit is equal to 1% recombination.

   Map units are also called centimorgans after
    geneticist Thomas Hunt Morgan who won
    the Nobel Prize for discovering how
    chromosomes govern inheritance.
                 Challenge
   How do we merge the information about
    each pair of genes together into one
    common framework?

   How do we order the genes relative to one
    another?
    Three-Point Analysis
                Single cross-over
A    B    C



a    b    c
                Double cross-over
Double cross-overs and Map
         Distance
If we only look at the outer markers A and C
  on the previous slide, we will underestimate
  the true distance between them because we
    have not accounted for the double cross-
                      overs.
       Three-Point Analysis
 Distance = # Singles +2 * Doubles
                       Total
 If cross-overs are equally likely along the
  chromosome and closer genes have few
  cross-overs, then the likelihood of two
  cross-overs close to one another would be
  small.
         Double cross-overs
   So mapping algorithms can order genes by
    minimizing the number of double cross-
    overs.
Maximum Likelihood Method
   Gives an estimate of the distances and the
    relative orders of the loci which would
    maximize the probability that the observed
    data would have occurred.
  How Maximum Likelihood
          Works

BHBBAHBHHBHHBHB   umc157
HHBBABBHHBBBBAB   umc76
BHBBABHAHHBHBAB   asg45
BHBBABBAHHBHBAB   zb4
BHBBHBHAHHBHBAB   csu3
BHBBAHBHHBHHBHB   umc157
BHBBABHAHHBHBAB   asg45
HHBBABBHHBBBBAB   umc76
BHBBABBAHHBHBAB   zb4
BHBBHBHAHHBHBAB   csu3
               MapMaker
 Mapping program that uses maximum
  likelihood method.
 Initially calculates what is linked (< 50%
  recombination).
              MapMaker
 Works one linkage group at a time.
 Randomly picks two genes with the group
  and calculates the distance between them.
 Adds another gene from the group and
  determines the correct placement by using
  maximum likelihood to minimize the
  double cross-overs.
              MapMaker
 Does this by calculating a LOD value for
  the placement of the gene in each of the
  intervals.
 Accepts the placement with the highest
  LOD value.
 Can be used for molecular markers or for
  trait data.
                   LOD
 Log likelihood.
 LOD = log 10 (Probability that the observed
  data would have occurred /probability that
  the gene is unlinked).

				
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