plant surface microbiology.pdf

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Emanuele G. Biondi
two strains with respect to the total ones. One commonly used parameter is
the Euclidean distance whose formalisation is E=n(1–2n xy /2n), where n is
the total number of bands of strain x and y and n xy the number of bands
shared by strains x and y. Another widely used parameter is the Nei’s
distance which, using the same notation, can be formalised as
D=1–[2n xy/(n x+n y)], where n x and n y are the number of bands present in the
strains x and y,respectively.
3. Examples of techniques for ordering the genetic diversity to analyse the
genetic structure of a population are the analysis of molecular variance
(AMOVA) and the principal component analysis (PCA). The AMOVA is a
methodology for the analysis of variance which makes use of molecular
data. AMOVA allows us to uncover the structure of the population and to
test the validity of the hypotheses on the subdivision of the analysed population.
AMOVA was designed by Excoffier, Smouse and Quattro in 1992
(Excoffier et al. 1992) as “an alternative methodology that makes use of
available molecular information gathered in population surveys, while
remaining flexible enough to accommodate different types of assumptions
about the evolutionary genetic system” (Excoffier et al. 1992). Assuming
that a set of samples belongs to different populations and that these populations
could be arranged in genetically distinguishable groups, the aim of
AMOVA is to perform statistical tests on the hypothesised genetic structure.A
hierarchical analysis of variance splits the total genetic variance into
components due to intra-population differences among individual samples,
inter-population differences and inter-group differences.
The PCA is an analysis in which a data set is searched for some significant
independent variables, with respect to all possible variables. These variables
are termed ‘components’ and interest attaches especially to the principal,
or most important, components, hence the name ‘principal component
analysis’. The output of the analysis is a plot in which the samples are
dispersed in a two- or three-dimensional space allowing the recognition of
the clusterisation pattern with respect to one of the dimensions (components).
4. The genetic relationships among populations can be estimated as the
results of AMOVA with respect to the variance between populations. The
parameter of the genetic separation between populations is F ST (Wright
1965) which derives directly from the analysis of variance. The F ST values
can be used to construct a matrix of distances whose representation takes
the form of a dendrogram or tree. Two tree-building methods are applicable
to the distance matrix: UPGMA and Neighbor-Joining (Saitou and Nei
1987). The UPGMA is based on a simple mathematical algorithm in which
a step-wise clusterisation is made. The Neighbor-Joining method is a simplified
version of a minimal evolution method; a star-like tree is made and
then the topology is reconstructed on the basis of the minimisation of the
overall length of the tree.