Biology Reference
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analyzing molecular data were more sophisticated, no firm conclusions could be
made.
Villablanca et al. (1998)
suggested that the origin of Californian Medfly
infestations might be determined through the use of microsatellites or single-
strand conformation polymorphism analysis. They noted,
“Due to its economic significance, the medfly infestation has become a model
system for the study of contemporary bioinvasions and has several important
lessons for other cases where limited funding is likely to restrict the amount
of research effort. The genetic analysis of new bioinvasions should begin
with mtDNA and allozymes; however, highly variable nuclear regions, such
as introns, should also be considered. Multilocus genotyping provides a rapid
method of determining the origin of invasions, whether using nonsequencing
methods of screening intron variation and/or other types of markers.”
Thirty Medfly microsatellites for
C. capitata
were developed as tools for popula-
tion analysis by
Bonizzoni et al. (2000)
. In addition, 11 microsatellite loci were
identified by RAPD-PCR and random genomic sequencing. Two additional loci
were identified in GenBank, for a total of 43 microsatellites. Ten of these mic-
rosatellite sequences were used to analyze 122 Medflies from six populations
(Kenya, Reunion, Madeira, South Italy, Greece, and Peru). The results obtained
were “consistent with results obtained from allozyme and single-copy DNA
studies with respect to the historically documented expansion of the medfly”
(
Bonizzoni et al. 2000
). As with the allozyme data (
Malacrida et al. 1998
), poly-
morphisms decreased as flies moved from tropical Africa to the Mediterranean
basin and to South America.
Microsatellite analysis was used by
Bonizzoni et al. (2001)
to resolve: was there
one established population or many invasive populations in California? The 10
previously characterized microsatellite loci were used to compare 109 Medflies
captured in California between 1992 and 1998 with 242 Medflies from Hawaii,
Guatemala, El Salvador, Ecuador, Brazil, Argentina, and Peru, using between six
and 30 flies per sample site. Their data analysis used a method that accounts for
heterogeneity in the size of samples to estimate allelic richness. The frequency
of each allele per locus, the observed heterozygosity and deviations from Hardy-
Weinberg expectations were computed using several methods (
Bonizzoni et al.
2001
). Genetic divergence between individuals, and within and between popula-
tions was estimated in terms of shared bands between individuals. Relationships
between populations were given in dendograms obtained from the dissimi-
larity index and Nei's unbiased genetic distance (D
A
). Trees were constructed
using the neighbor-joining method of
Felsenstein (1993)
, and bootstrap values
for the tree were obtained using the “gene frequency” option within the pro-
gram SEQBOOT. The Kenyan sample was used as the out-group because it is the
