Biology Reference
In-Depth Information
correlate with these foci. If there is high mixing and dispersal of
parasites across the human population, then the parasites would have
a panmictic population structure. Thus, people would effectively be
acquiring infections from a common parasite population (i.e. a single
source pool of infection). In contrast, repeated transmission that is
localized at particular foci across the human population would limit
parasite mixing, leading to parasite genetic differentiation within
a single human population. The finding of multiple genetic clusters of
parasites, therefore, is an indication that there could be multiple
infection foci (see Figure 1 in Criscione and colleagues
41
). Adult
A.
lumbricoides
were collected from 320 people across 165 households that
spanned an area approximately 14 km
2
. In addition to spatial sampling,
two temporal samples (~3 years apart, so a total of 211 household-by-
year samples) were taken for some regions of the village. For logistic
reasons, temporal sampling was staggered for three regions of Jiri such
that one group of houses was sampled in 1998 and 2001, a second group
in 1999 and 2002, and a third in 2000 and 2003. As noted below, time of
collection explained less than 1% of the variance in the genetic structure
of the parasite population.
41
A total of 1094 roundworms were geno-
typed at 23 autosomal microsatellite markers.
10
Model-based Bayesian
clustering (implemented in the program
STRUCTURE
23
)wasusedto
analyze the multilocus parasite genotypes to determine if there was
underlying genetic structure among the sampled worms. Importantly,
no prior spatial or temporal information was included (or needed) in
this analysis.
There was strong support for local-scale genetic structuring with 13
genetic clusters of parasites identified. The results of the population
clustering analyses were subsequently incorporated into a non-
parametric multivariate analysis of variance
42,43
to elucidate spatial,
geographical, or epidemiological features associated with the partitioning
of genetic variation among the sampled worms. This analysis provided
a novel approach to integrating individual-based genetic assignment
results with downstream statistical analyses.
41
The independent variables
included a nested design (household and hosts nested within household)
and eight covariates: host age, host sex, host density (number of people
living in the house), elevation, geographic distance among households
(latitude
longitude combined), infection intensity, parasite sex, and time
of collection. When variables were analyzed independently, household
explained
e
63% of the variance in genetic structuring whereas each
covariate always accounted for
>
15%. When the nested design was
conditioned on the eight covariates (i.e. variance due to the covariates was
accounted for first), the contribution of household was still high and
explained
<
36%. In contrast, none of the eight covariates were significant
after accounting for the nested design. Interestingly, time had no impact
>
