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Molecular analysis of genetic variation in trees

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Molecular analysis of genetic variation in trees Caroline Agufa Tree Domestication Course, 17 to 22 November 2003 World Agroforestry Centre Molecular analysis of ... – PowerPoint PPT presentation

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Title: Molecular analysis of genetic variation in trees


1
Molecular analysis of genetic variation in trees
Caroline Agufa Tree Domestication Course, 17 to
22 November 2003 World Agroforestry Centre
2
Molecular analysis of genetic variation in trees
  • Introduction Why molecular analysis?
  • Techniques for molecular genetic analysis
  • What does molecular analysis reveal about genetic
    variation in trees?
  • Molecular genetic variation and the impact of
    tree cultivation
  • Case Studies of molecular analysis
  • Limitations of molecular analysis

3
Introduction Why molecular analysis?
  • Utility of traditional techniques is limited
    because
  • Influenced by environmental factors
  • The number of characters available are few
  • Long time for evaluation (trees)
  • Therefore, molecular genetic markers are now
    often used
  • These provide information on the underlying
    diversity and genetic constitution of trees and
    allow more optimal genetic management strategies
    to be developed

4
Techniques for molecular genetic analysis
  • The most commonly applied are isozyme and
    PCR-based approaches
  • Isozyme analysis
  • Detection of different allelic forms of the same
    enzyme by electrophoresis and staining
  • Inherited in a Mendelian and codominant manner
  • Disadvantage Need fresh material because relies
    on enzyme activity

5
Techniques for molecular genetic analysis II
  • Polymerase Chain Reaction (PCR) analysis
  • amplified fragment length polymorphism
  • random amplified polymorphic DNA (RAPD)
  • restriction fragment length polymorphism-PCR
  • simple sequence repeats
  • Disadvantage Expensive

RAPD profile Arrows indicate polymorphisms
6
What does molecular analysis reveal
about genetic variation in trees?
  • Genetic variation within tree populations is high
  • Molecular genetic differentiation among
    populations is generally low (but statistically
    significant). However, there are exceptions, and
    under-differentiation of some tropical taxa

7
Prunus africana
Clustering of genetic distances (48 RAPD markers)
Genetic distance
0.0
0.1
0.2
0.3
0.4
Ethiopia
Kenya
Mount Kilum
Ntingue
Mendankwe
Mount Cameroon
Uganda
Manakambahiny


Antsevabe

Mantadia
Cameroon ? Madagascar
8
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9
Prunus africana
Clustering of genetic distances (41 RAPD markers)
Mt Kilum 1 (planted)
ONADEF (nursery)
Mendankwe (planted)
Ntingue 2 (natural)
Mt Cameroon (natural)
Cameroon
Mt Kilum 2 (natural)
Sop (natural)
Ntingue 1 (planted)
MESG (nursery)
Bwindi (Uganda)
Kobujoi (natural)
Western Kenya
Muguga (planted)
Maseno (nursery)
Lepsi-Arsi (Ethiopia)
Nyeri 1 (natural)
Nyeri 2 (planted)
Eastern Kenya
Chuka 2 (natural)
Meru (natural)
populations established using seeds from
Kobujoi area
Chuka 1 (nursery)
Tigoni (natural)
0.6
0.3
0
Genetic distance
10
Sclerocarya birrea
Clustering of genetic distances (80 RAPD markers)

0.12
11
Sclerocarya birrea
Principal component analysis for populations of
Sclerocarya birrea based on 80 RAPD markers
Magamba
4
Country
Kenya
Swaziland
Mali
Namibia
Malawi
2
Zambia
Tanzania
Botswana
0
Second principal component (7 of variation)
-2
-4
Makadaga, Mialo, Mandimu
-6
-2
2
10
6
-4
0
4
8
First principal component (11 of variation)
12
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13
Uapaca kirkiana
Principal component analysis for populations of
Uapaca kirkiana based on 132 RAPD markers
14
Molecular genetic variation and the impact of
tree cultivation
  • Levels of genetic variation in cultivated
    material are generally lower than in wild
    populations
  • A narrow genetic base in cultivated material can
    have serious negative implications for
    sustainable utilisation
  • With the trend to tree populations on-farm, more
    focus is required on assessing genetic variation
    in cultivated trees, to devise sustainable
    on-farm management strategies

15
Limitations of molecular analysis
  • Molecular markers are by nature neutral
    indicators of underlying genetic variation,
    rather than linked to any one character trait
  • Molecular markers ought to be used in combination
    with field evaluation techniques
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