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estimate.
49
Model-based genealogical simulations are preferable to esti-
mate
,
75
though these are computationally intensive. For simplicity, I
q
estimated
with Eq.
(8.1)
, which has the assumption that the population
under consideration is closed to immigration.
49
In comparison to samples
from China and Guatemala,
Ascaris
from Jiri are highly genetically
differentiated.
22
Thus, on a global scale the Jiri metapopulation of
A. lumbricoides
is likely relatively isolated. Nonetheless, sampling of
locations around Jiri is needed to ascertain potential regional influences
on the long-term
N
e
estimate provided below. To estimate the coalescent
N
e
of the metapopulation, I used
H
e
¼
q
0.71, which was reported over all
1094 genotyped nematodes;
41
thus,
2.45. There are no estimates of
u
for microsatellites in
Ascaris
; therefore, I used estimates from the nema-
tode
Caenorhabditis elegans
.
76
Repeat motif and length can affect
u
so I
calculated the average
u
from the six di- and five tetra-nucleotide motif
loci with lengths less than 70 repeats
76
(mean
u
q ¼
0.000542 and 0.0000362,
respectively) as this would reflect the microsatellite loci in my data set. I
had 19 di- and 4-tetra microsatellites, and used a weighted average to
obtain an estimate of
u
¼
0.000454. Using this value of
u
,thecoalescent
¼
N
e
¼
1347. This long-term estimate is nearly identical to the single-
sample “best” estimate of
N
eT
(1291).
CONCLUDING REMARKS
Above I discussed how population genetics data can be used to iden-
tify cross-transmission and focal transmission. In addition, I introduced
N
e
as a means to help genetically monitor epidemiologically relevant
parasites. All the methods I have used come with assumptions and
require appropriate sampling. With regards to cross-transmission and
focal transmission, more discussion can be found in prior studies.
7,22,41
Here, I will conclude with a discussion of using
N
e
estimators for parasites
especially in relation to
Ascaris
biology.
Single-sample, contemporary estimators assume closed populations
with discrete generations.
49
In regards to the assumption of a closed
population, simulations showed that the LD-
N
e
estimator is little affected
by migration unless
m
0.1, in which case an estimate from a subpopu-
lation will approach
N
eT
.
77
The latter does not appear to be an issue in this
Ascaris
data set. Because
Ascaris
has a “seed bank” life history, it clearly
does not have discrete generations. When dealing with a species with
overlapping generations, generational
N
e
is of most significance for
monitoring adaptive potential or modeling the effects of selection. How
then can one estimate generational
N
e
for
Ascaris
? As conjectured and
assumed in this chapter, the use of single-sample estimators on a sample
with a mixed-age cohort (adult worms in the case of
Ascaris
) may actually
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