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
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Molecular analysis of genetic variation in trees Caroline Agufa
Tree Domestication Course, 17 to 22 November 2003 World
Agroforestry Centre 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 Molecular analysis of genetic
variation in trees 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
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
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 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 Clustering of genetic distances (48 RAPD markers)
Prunus africana * Cameroon Madagascar Genetic distance Ethiopia
Kenya * Mount Kilum * Ntingue * Mendankwe * Mount Cameroon Uganda
Manakambahiny Antsevabe Mantadia populations established using
seeds from Kobujoi area Prunus africana Clustering of genetic
distances (41 RAPD markers) Mt Kilum 1 (planted) ONADEF (nursery)
Mendankwe (planted) Ntingue 2 (natural) Mt Cameroon (natural) Mt
Kilum 2 (natural) Sop (natural) Ntingue 1 (planted) MESG (nursery)
Bwindi (Uganda) Kobujoi (natural) Muguga (planted) Maseno (nursery)
Lepsi-Arsi (Ethiopia) Nyeri 1 (natural) Nyeri 2 (planted) Chuka 2
(natural) Meru (natural) Chuka 1 (nursery) Tigoni (natural) Genetic
distance Cameroon Western Kenya Eastern Kenya Sclerocarya birrea
Clustering of genetic distances (80 RAPD markers) 0.12 Sclerocarya
birrea Principal component analysis for populations of Sclerocarya
birrea based on 80 RAPD markers First principal component (11% of
variation) Second principal component (7% of variation) Country
Kenya Swaziland Mali Namibia Malawi Zambia Tanzania Botswana
Magamba Makadaga, Mialo, Mandimu Uapaca kirkiana Clustering of
genetic distances (132 RAPD markers) B Sumbawamga (Tanzania) L
Kapelula (Malawi) D Mbeya (Tanzania) K Luwawa (Malawi) J Litende
(Malawi) E Songea (Tanzania) A Mpwapwa (Tanzania) C Iringa
(Tanzania) M Furacungo (Mozambique) I Chipata (Zambia) H Kanona
(Zambia) F Kasama (Zambia) G Kitwe (Zambia) S Mpanzure (Zimbabwe) R
Murewa (Zimbabwe) P Musana (Zimbabwe) N Domboshewa (Zimbabwe)
Genetic distance Uapaca kirkiana Principal component analysis for
populations of Uapaca kirkiana based on 132 RAPD markers 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 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
