text:
Evidence that Adaptation in Drosophila Is Not Limited by
Mutation at Single Sites
Talia Karasov., Philipp W. Messer., Dmitri A. Petrov*
Department of Biology, Stanford University, Stanford, California, United States of America
Adaptation in eukaryotes is generally assumed to be mutation-limited because of small effective population sizes. This view
is difficult to reconcile, however, with the observation that adaptation to anthropogenic changes, such as the introduction
of pesticides, can occur very rapidly. Here we investigate adaptation at a key insecticide resistance locus (Ace) in Drosophila
melanogaster and show that multiple simple and complex resistance alleles evolved quickly and repeatedly within individual
populations. Our results imply that the current effective population size of modern D. melanogaster populations is likely to
be substantially larger ($100-fold) than commonly believed. This discrepancy arises because estimates of the effective
population size are generally derived from levels of standing variation and thus reveal long-term population dynamics
dominated by sharp—even if infrequent—bottlenecks. The short-term effective population sizes relevant for strong
adaptation, on the other hand, might be much closer to census population sizes. Adaptation in Drosophila may therefore
not be limited by waiting for mutations at single sites, and complex adaptive alleles can be generated quickly without
fixation of intermediate states. Adaptive events should also commonly involve the simultaneous rise in frequency of
independently generated adaptive mutations. These so-called soft sweeps have very distinct effects on the linked neutral
polymorphisms compared to the standard hard sweeps in mutation-limited scenarios. Methods for the mapping of adaptive
mutations or association mapping of evolutionarily relevant mutations may thus need to be reconsidered.
Citation: Karasov T, Messer PW, Petrov DA (2010) Evidence that Adaptation in Drosophila Is Not Limited by Mutation at Single Sites. PLoS Genet 6(6): e1000924.
Editor: Harmit S. Malik, Fred Hutchinson Cancer Research Center, United States of America
Received December 4, 2009; Accepted March 24, 2010; Published June 17, 2010
Copyright: ? 2010 Karasov et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work was funded by the NIH and NSF grants to DAP, funds from CEEG and Conservation Biology Centers at Stanford University, and a HFSP
fellowship to PWM. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: email@example.com
. These authors contributed equally to this work.
The speed of adaptation in eukaryotes is commonly assumed to
be limited by the waiting-time for an appropriate adaptive
mutation. This notion is based on estimates of the population
parameter H=4Nem (the product of effective population size Ne
and per-site mutation rate m) derived from levels of standing
neutral variation. H can be interpreted as the rate at which new
mutations arise in the population . In contrast to many
prokaryotes or viruses, where H can easily be on the order of one
or larger - and consequently most single nucleotide mutations exist
in the population at every given time – estimated values of H in
eukaryotes are typically much smaller than one . Adaptation
should thus be substantially retarded, especially when adaptive
alleles need to carry several independent mutations.
However, adaptation to anthropogenic changes such as the
evolution of insecticide resistance has been observed to occur very
rapidly and often involves complex alleles [2–7]. One possible
explanation for such cases of rapid adaptation is that complex
resistant alleles predate environmental changes [8,9]. The other
possibility is that adaptive mutations emerge more quickly in
eukaryotic populations than commonly believed. The latter would
imply that estimates of H have to be reconsidered in the context of
In order to understand the population parameters that allow for
rapid adaptation in eukaryotes, we study here a well-documented
example: the evolution of pesticide resistance in D. melanogaster.
Acetylcholinesterase (AChE), a key neuronal signalling enzyme,
is the major target of the most commonly used insecticides,
organophosphates (OPs) and carbamates (CMs) . Introduced
in the 1950–1960’s, these insecticides have been used pervasively
around the world since then. Within a few years of their
introduction cases of insecticide-resistant AChE alleles emerged
 and today insecticide-resistant AChE has been observed and
characterized in numerous arthropod species [2–7].
In D. melanogaster, four particular point mutations at highly
conserved sites (I161V, G265A, F330Y, G368A) of Ace (the gene
coding for AChE) lead to resistance to OPs and CMs [5,12]
(Figure S1). Alleles carrying these mutations singly and in
combination have been found in natural populations worldwide
. In the presence of OPs, these mutations confer semi-additive
resistance: single mutations provide moderate levels of resistance
to ,75% of OPs, any two mutations in combination provide
higher levels of resistance to ,80% of OPs, while alleles with three
or four mutations lead to strong resistance to practically all OPs
. One 3-mutation allele (I161V, G265A, F330Y) was found
worldwide at particularly high frequencies and is a key
determinant of resistance to OPs . In the absence of pesticides
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all resistant alleles are strongly deleterious with the selective
coefficient on the order of negative 5–20% [13,14].
Here we collect data and provide quantitative arguments (both
analytical and simulation-based) that the observed signatures of
adaptation at Ace imply a much larger (,100-fold or more)
effective population size than is commonly assumed for D.
melanogaster. We discuss the implications of our results for the
study of adaptation in Drosophila and other species with large
Fast and repeated evolution of simple and complex
resistance alleles within individual subpopulations of D.
D. melanogaster evolved in sub-Saharan Africa (AF) and spread
worldwide over the past 10–16 thousand years . The
worldwide spread was associated with a severe bottleneck that
resulted in sub-sampling of AF diversity by the out-of-Africa
strains . Resistant alleles found outside of AF may either have
arisen in situ in the derived out-of-Africa populations or were
present in the AF population prior to the bottleneck (similar to
[8,9]). These two hypotheses can be distinguished by studying
haplotype backgrounds of the resistant alleles. Resistant mutations
that evolved in derived populations in situ, unlike ancient AF
resistant alleles, should reside on the background of sensitive
haplotypes common in the exposed out-of-Africa populations that
passed through the bottleneck.
We collected D. melanogaster sequence data (,1.5 kb covering the
known four sites of resistant mutations in Ace) from 93 resistant and
sensitive strains. We sequenced 9 alleles from the ancestral AF
populations, 10 alleles from the derived Eurasian and American
populations collected prior to the 1950s (M strains) , and 74
alleles from the recently collected (1990–2009) derived populations in
North America (NA) and Australia (AUS) (Table S1 and Table S2).
We detected resistant mutations at the first three sites (I161V,
G265A, F330Y) but did not find the resistant mutation at the
fourth site (G368A). We estimated that ,40% of the strains
contain resistant mutations in the modern NA and AUS
populations of D. melanogaster. Figure 1 shows the most parsimo-
Figure 1. Haplotype network at Ace. Alleles containing mutations
I161V, G265A and F330Y are numbered 1, 2 and 3 respectively. Sizes of
the circles correspond to the number of identical sequences
representing each haplotype; tick marks along a branch indicate the
number of mutations between two neighbouring haplotypes. Sensitive
haplotypes are labelled with capital letters and resistant haplotypes
with lowercase letters. Note that our sample is enriched for resistant
haplotypes. Resistant NA alleles containing a single mutation (all at the
first site) appear to have arisen on the common out-of-Africa haplotype
L, with one specific L-related allele (labelled p) present at the highest
frequency. The resistant AUS alleles also cluster together. AUS resistant
alleles containing a single resistant mutation in the first or second site
appear to have arisen either on the background of the common out-of-
Africa sensitive haplotype L, or on the background of the specifically
AUS haplotype N. The alleles containing two mutations in NA (first plus
second or first plus third sites) are all related to the sensitive L
haplotype and the common resistant allele (labelled p) containing the
mutation in the first site. The 3-mutation alleles are present both in NA
and AUS populations (v and w) and are the most closely related to the
sensitive L haplotype. There are two resistant alleles containing single
mutations in the first and the second site that we detected in AF. One of
these is very similar to the AUS alleles containing the second mutation
and is likely a migrant from out-of-Africa back to AF. The other appears
to have arisen in situ in AF (u).
Adaptation in eukaryotes is often assumed to be limited by
the waiting time for adaptive mutations. This is because
effective population sizes are relatively small, typically on
the order of only a few million reproducing individuals or
less. It should therefore take hundreds or even thousands
of generations until a particular new mutation emerges.
However, several striking examples of rapid adaptation
appear inconsistent with this view. Here we investigate a
showpiece case for rapid adaptation, the evolution of
pesticide resistance in the classical genetic organism
Drosophila melanogaster. Our analysis reveals distinct
population genetic signatures of this adaptation that can
only be explained if the number of reproducing flies is, in
fact, more than 100-fold larger than commonly believed.
We argue that the old estimates, based on standing levels
of neutral genetic variation, are misleading in the case of
rapid adaptation because levels of standing variation are
strongly affected by infrequent population crashes or
adaptations taking place in the vicinity of neutral sites. Our
results suggest that many standard assumptions about the
adaptive process in eukaryotes need to be reconsidered.
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nious haplotype network of the sequenced alleles. Figure 2 shows
the segregating sites for sensitive haplotypes, as well as the I161V
1-mutation and the 3-mutation haplotypes (Table S2 shows
segregating sites for all sequenced alleles).
In all cases the NA and AUS resistant alleles show no signs of
having predated the spread of D. melanogaster out-of-Africa. Instead,
the resistant alleles appear to have arisen in situ in different
populations, as indicated by the observation that locally common
resistant alleles are present on the locally common sensitive
haplotypes. For instance, AUS alleles with the resistant mutation
in the first site (marked t) have the haplotype background that is
identical to the sensitive haplotype N that is common in AUS but
has not been detected by us in NA. In contrast, the NA first site
mutation alleles (marked p through s) have the haplotype
backgrounds that are nearly identical to the sensitive haplotype
L that is common in NA. Additionally, the haplotype background
of one of the AF alleles (marked u) with the resistant mutation
I161V is substantially diverged from the NA and AUS resistant
strains and is more similar to the sensitive alleles common in AF.
This suggests a third independent origin of the mutation I161V in
Figure 2. Soft sweeps at Ace. The table shows segregating sites within the 1.5-kb region of Ace. Each strain is named according to the
corresponding letter in Figure 1. When multiple strains shared the same haplotype, they were named with the same letter but with different numbers
(i.e. w-1, w-2, w-3). For the names and origins of the strains refer to Table S1 and Table S2. The nucleotide position and the consensus sequence at the
top of the table correspond to the y1; cn1bw1sp1strain. The positions of the three resistant mutations are shaded. The table shows all sensitive
haplotypes observed more than once as well as all haplotypes containing the resistant mutation at the first site (I161V) and the ones that contain all
three resistant mutations.
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AF. Note that the complex 2- and 3-mutation haplotypes also
appear to have arisen in situ in the derived populations as their
haplotype backgrounds are most closely related to the common
out-of-Africa sensitive haplotype L.
In summary, the sequence analysis of the resistant and sensitive
alleles reveals two signatures of the adaptive evolution of pesticide
resistance at the Ace gene. First, adaptation has been rapid enough
such that in the past 50 years (1000 to at most 1500 generations
) multiple resistant alleles including a complex allele
containing three independent mutations at three different sites
evolved and spread to high frequencies worldwide. Second, many
resulting resistant alleles are present on distinct haplotypes that
differ in the immediate vicinity of the adaptive sites, such as the
adaptive change from A to G at the first site (I161V) in NA and
AUS that is located on the haplotypes p, q, r, s, and t (Figure 2).
Patterns of evolution at Ace are inconsistent with small
values of H: analytical considerations under simple
Below we consider a simple scenario of a single locus in a
panmictic population of effective size Ne. We assume that the
resistant alleles were in mutation-selection balance prior to
pesticide application with a strongly deleterious selection coeffi-
cient of 25% [13,14] and that they became advantageous after the
application of pesticides.
In Box 1 we show that if H,0.01 the probability of successful
adaptation from standing genetic variation is less than 1% even if
positive selection is extremely strong (s,100%). Thus, if H,0.01,
as previously estimated based on analyses of neutral loci in
Drosophila [18,19], we only need to consider the case of
adaptation from de novo mutations.
The probability of successful adaptation from de novo mutations
depends on the expected waiting time for an adaptive mutation to
emerge and to reach substantial frequencies in the population.
This waiting time is the sum of the expected times to complete two
distinct phases: (1) the establishment phase in which an adaptive
mutation arises and reaches the frequency at which its escape from
stochastic loss is assured and (2) the sweep phase in which the
adaptive allele reaches an intermediate population frequency such
that it can be readily observed. In Box 1 we show that the overall
waiting time can be estimated as
This equation implies that selection must already be very strong
for a single 1-mutation allele to arise and to become prevalent in
less than 1500 generations (s.20% for H=0.01). Selection
coefficients associated with the 2-mutation and 3-mutation alleles
need to be even stronger given that they have to outcompete the 1-
mutation and 2-mutation alleles respectively.
We have established that under this simple model if H is 0.01,
the adaptation at Ace likely involved very strong positive selection
acting on de novo mutations. Can we then explain the second
empirical observation, namely that the same adaptive mutation by
state is observed on several haplotypes that differ in the immediate
vicinity of the adaptive site?
We can imagine two scenarios that would generate this
observation. In the first, the so called hard sweep scenario, a
single adaptive mutation arises in frequency in the population and
eventually ends up on different haplotypes due to recombination
or mutation events that take place in its vicinity during the sweep.
Box 1. Probability of adaptation from standing
genetic variation and waiting time for de novo
mutation. Consider a single locus in a panmictic diploid
population of constant effective size Ne. New resistant
alleles arise at rate Hu=H/3 (only one out of three
mutations give rise to an adaptive allele). Evolution is
modelled in a Wright-Fisher infinite alleles framework with
selection. Heterozygotes have fitness 1+s, fitness is
multiplicative, and the locus evolves independently of
other loci. Prior to pesticide application resistant alleles are
deleterious with selection coefficient sd,0. The density
function g(x) for the frequency distribution of resistant
alleles in mutation-selection balance is then given by
We thus do not expect resistant alleles to be present in the
population most of the time for H=0.01 (Ne,106) and
become advantageous (s.0). The probability of successful
adaptation from standing genetic variation is approxi-
After the onset of pesticide application, resistant alleles
Under the above scenario, Psgvis very low even in the case
of extremely strong positive selection (Psgv,1% for
Let us now consider de novo resistant mutations that arise
after the onset of pesticide application. The average time it
takes for an adaptive mutation to emerge and to reach
sufficiently high frequency, x,1/(4Nes), assuring its escape
from initial stochastic loss, the so-called establishment
time Te, is on the order of [34,48]
Once established, the frequency trajectory x(t) of the
adaptive mutation becomes essentially deterministic and
can be modelled by
From establishment it takes on the order of
generations for the mutation to rise to intermediate
population frequency (,50%). The overall expected
waiting time Twfor a de novo adaptive mutation to reach
intermediate frequencies is then
which is Equation (1) in the main text.
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In the other, an example of the so-called soft sweep scenario,
several independent adaptive mutations take place on different
haplotypes and increase in frequency simultaneously.
Theoretical investigations under simple scenarios by Pennings
and Hermisson [20–22] showed that such soft sweeps are
extremely uncommon if H per site is on the order of 0.01
independently of the strength of positive selection. The probability
of the hard sweep scenario resulting in the observation of the
haplotypic diversity in the vicinity of the adaptive allele is
calculated in Box 2. Specifically, we demonstrate that the
probability Pdthat at least two haplotypes are observed at the
end, where the minor haplotype is present in at least a fraction d of
the population, is approximately
Here R is the total rate of mutation or recombination in the locus
per individual per generation and s is the strength of positive
selection. For our locus of length ,1500 bp we have R,6*1026
when assuming a recent estimate for the single-site mutation rate in
D.melanogaster of m,2.5*1029 and a measured recombination
rate of r,0.15 cM/Mbp . The probability to observe different
haplotypes is therefore still very small (Pd,1%) even for a low
population frequency of d=2% and assuming s to be 5%. Note that
this calculation is very conservative given that in our data multiple
haplotypes are present at much higher frequency than 2%, multiple
haplotypes vary at sites extremely close to the adaptive allele (within
38 bp), and positive selection was likely much stronger.
In conclusion, under this simple scenario, our empirical
observations at Ace are unexpected if H is indeed on the order
of 0.01. Specifically, considering how strong selection must be, we
should not be seeing more than one distinct haplotype containing
the same adaptive mutation.
Note that if H were much higher, for example on the order of
one or larger, then all of our observations are expected. Soft
sweeps would be commonplace because many more mutations
enter the population in every generation and can increase in
frequency simultaneously thereby generating multiple haplotypes
containing the same adaptive mutations , as observed in the
data. The establishment time would become smaller making it
easier to observe complex, 3-mutation alleles at Ace in less than
1500 generations. However, selection would still need to be strong
because the time it takes for an adaptive allele to reach
intermediate frequencies is only weakly (logarithmically) depen-
dent on the effective population size and inversely proportional to
the selection coefficient.
Patterns of evolution at Ace require large values of H:
numerical investigations for a large range of evolutionary
We have shown above that under very simple population
scenarios the pattern of adaptive evolution at Ace requires large
Box 2. Probability of distinct haplotypes in a hard
sweep. Consider a single adaptive mutation that reaches
establishment frequency in generation t=0. Its subsequent
frequency trajectory is x1(t). Mutated or recombined variants
of its original haplotype become established in the
population at rate
Here R is the rate of either mutation or recombination taking
place on the sweeping initial haplotype per individual per
generation, and the factor 2s is the probability of an adaptive
overestimate of the establishment probability of the second
with a probability that is closer to 2s(12x1).
What is the probability that a mutated or recombined
haplotype also reaches at least frequency d in the population?
Such a second haplotype has to emerge within a limited
number Td of generations after the first. Otherwise the
population will already be dominated by the first haplotype,
neutralizing any selective advantage of the second.
Let us assume that the second haplotype becomes
established at time Td. We denote its frequency trajectory
by x2(t). The crucial observation allowing us to calculate Tdis
that the ratio x1(t)/x2(t) remains constant for all t$Td, as both
haplotypes have the same fitness. In particular, because we
require that the second haplotype is eventually present in a
fraction d of the population, we have
The latter approximation applies for small d%1. At t=Td, the
trajectory x1(t) can still be modelled by Equation (B4); no
interference between different adaptive haplotypes has
occurred until then because the second allele has been
extremely rare or absent for t,Td. Recalling that the second
haplotype becomes established when it reaches a frequency
x2,1/(4Nes), we thus have:
Solving Equations (B8) and (B9) for Tdand assuming Nesd&1
The condition Nesd&1 is justified when positive selection is
strong and d is large enough that there is a chance of
sampling the second allele.
Mutations establishing after Tdcan only reach a population
frequency smaller than d. The probability of observing two
different haplotypes with the minor haplotype being present
in at least a small fraction d of the population can therefore
be estimated from the probability that a new variant of the
initial adaptive haplotype emerges within the first Td
generations. We obtain
where we again assumed Nesd&1. Note that Pddoes not
depend on H.
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values of H. However, it is unclear whether such large values of H
are required under more complex and realistic scenarios.
Variation in strength of selection, recombination rate, and
population structure might affect the probability of evolving
complex 3-mutation alleles from the simpler 1- or 2-mutation
alleles  and the probability of observing multiple haplotypes
containing the same adaptive mutations.
To investigate quantitatively the potential impact of such effects
we conducted extensive simulations of adaptation at Ace under a
large number of selective (s=2.5% to 500%) and demographic
scenarios (1 to 100 subpopulations, migration rates M=0.01 to 10
individuals per generation between any two subpopulations), and
with varying recombination rate (r=0 to 10 cM/Mbp) (Table
In Figure 3A and 3B we show the frequency trajectories of
adaptive haplotypes for two representative simulation runs in a
simple single population scenario together with summary statistics
across a large number of runs for the two key H regimes (H=0.01
and H=1). We use four statistics: P1m and P3m are the
probabilities that a single adaptive mutation (1m) allele or the 3-
mutation allele (3m) were ever present in at least 10% of the
population during the simulation; Pssis the probability that a single
adaptive mutation is present on distinct haplotypes in a sample of
reasonable size (the observation that we will call the soft sweep
signature from now on); and Pcis the combined probability of
observing both the complex 3-mutation allele and a single-
mutation soft sweep signature during the same simulation.
Figure 3A and 3B show results consistent with our analytical
considerations. When H,0.01 and selection is of moderate
strength, neither the evolution of complex 3-mutation alleles nor
soft sweeps signatures are likely. Only when H approaches one do
both observations become commonplace.
Figure 3C shows the summary of the results for the more
complex scenarios (complete results are shown in Table S3). In
these more complex scenarios we assessed H by using coalescent
simulations to estimate the average heterozygosity per site (Hp) at
neutral sites and by summing H across all subpopulations (HS)
. Our simulations confirm that only when both Hpand HS
become on the order of one or larger is it likely to observe fast
evolution of complex 3-mutation alleles and at the same time soft
sweep signatures. Strong selection does indeed improve the
probability of seeing complex adaptive alleles but also, as expected,
does not generate signatures of soft sweeps when H is small.
Interestingly our simulations show that if H,1, then most of the
observed signatures of soft sweeps are generated by multiple de novo
mutations and are not due to the recombination of the same
adaptive mutation onto different haplotypes. This is because
signatures of soft sweeps are still commonly observed in
simulations even when the recombination level is set at zero. It
is also consistent with analytical considerations under simple
scenarios (Text S1).
Our data and analysis strongly suggest that the patterns of
adaptation observed at Ace in the last 1000–1500 generations are
highly unlikely in a population in which H per site is on the order
of 0.01 as it is commonly assumed. Instead, it appears that H per
site must have been at least 0.1 and more likely on the order of one
or larger. It is possible to elevate H by increasing the mutation rate
or by increasing the effective population size. We assessed whether
Ace had an unusually high mutation rate by estimating divergence
of Ace in D. melanogaster from its D. simulans ortholog at synonymous
sites. We found the divergence to be 7.9%, which is similar to the
genome average of ,10% [27,28]. In addition, Hp per site
estimated from polymorphisms at synonymous sites in sensitive
alleles is 0.008, which is also consistent with the genome average
. Thus we conclude that the effective population size in D.
melanogaster over the past 1000–1500 generations is likely to be very
Such a large value of Nemight appear puzzling given that levels
of standing neutral polymorphism suggest that Neis much smaller
[18,19]. To resolve this discrepancy it is necessary to take a closer
look at the concept of an effective population size. Effective
population size is commonly defined by the inverse magnitude of
the frequency-fluctuations of a neutral allele in two consecutive
generations . Over a number of generations, effective
Figure 3. Population dynamics of resistance adaptation for
different H regimes. (A) Frequency trajectories of resistant haplo-
types from a typical simulation of a single population with H=0.01
during the first 1500 generations after pesticides are applied. The
selection scenario is s1m=0.05, s2m=0.1, s3m=0.2. Trajectories are
shown for all resistant haplotypes that reached a population frequency
above 2%. On the right, summary statistics for P1m, P3m, Pss, and Pc
estimated from 105runs are shown. (B) Frequency trajectories of a
typical simulation run and summary statistics for a single population
with H=1. This simulation shows a soft sweep for the 3-mutation allele
(two different haplotypes at high frequencies; their frequencies
together add to 100%). Also, note that 2-mutation alleles do not rise
to high frequencies before being taken over by the fitter 3-mutation
alleles. (C) Pcfor a variety of different selection, recombination, and
population substructure scenarios as specified in Table S3. Probabilities
Pcof each scenario are plotted against the average heterozygosity Hp
of the entire population estimated from coalescent simulations.
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population size is the harmonic mean of the effective population
sizes over individual generations and thus is dominated by the
smallest values of Ne. (Equivalently, frequency fluctuations over
many generations are dominated by the largest fluctuations over
single generations). Estimates of the effective population size using
frequent neutral polymorphisms reflect Neharmonically averaged
over long periods of time and are therefore very sensitive to any
periods of low population size even far back into the past .
In sharp contrast, adaptation at Ace occurred within less than
1500 generations. The Ne relevant to adaptation at Ace is the
harmonic mean of Nevalues over the past 1500 generations or
even fewer. Unlike Nemeasured from ancient standing variation, it
is not reduced by the bottlenecks and nearby selective sweeps that
occurred more than 1500 generations ago. Consider a simple
bottleneck scenario outlined in Figure 4 that is similar to the out-
of-Africa scenario of Thornton and Andolfatto . It is apparent
that even if the current Ne is 100-fold larger than commonly
assumed, population behaviour of a frequent neutral allele does
not change substantially and the estimates of H from standing
variation are not altered. To give another example, if D.
melanogaster populations were to spend 90% of their time with Ne
of 1010and 10% at Neof 105with the shifts occurring about every
1000 generations, the harmonic mean Nederived from common
neutral polymorphisms would be ,106and yet the adaptive
process would take place primarily in populations of 1010with
H.1 per site. In this case, strong adaptation in Drosophila would
not be limited by mutation most of the time.
The short-term Neis bounded by the census population size (N)
and thus if N is much smaller than the reciprocal of the mutation
rate per site we can be certain that adaptation would be mutation-
limited. In many species N can be much larger than the reciprocal
of mutation rate and thus in these species it is possible that
adaptation is not limited by mutation at single sites. However, it is
Nemeasured over time scales relevant for adaptation and not N
that needs to be assessed to answer this question. Even short-term
Nemight be much smaller than N if populations crash regularly on
very fast temporal scales (such as those induced by winters in
temperate climates) or if the numbers of successfully reproducing
adults in each generation is sharply limited by extrinsic factors, for
example by available substrates for laying eggs. Thus the studies of
strong adaptation, such as the one presented here, are essential to
determining whether adaptation in general is mutation-limited in a
It is reasonable that Drosophila and many other organisms
undergo recurrent boom-bust cycles thereby reducing the long-
term Nestrongly but allowing adaptation during the boom years to
occur in populations of large short-term Ne. In addition, Drosophila
appears to undergo pervasive adaptation [30,31] with most
common neutral polymorphisms estimated to have been affected
by several selective sweeps in their genomic vicinity . Such
pervasive adaptation generates dynamics similar to recurrent
bottlenecks and will also reduce the long-term Nevalues even if the
short-term Nemight be consistently large. This situation is similar
to that found in HIV, where the effective population size estimated
from observed diversity underestimates the census size by many
orders of magnitude and is likely to underestimate the short-term
Nerelevant for adaptation as well .
The possibility that adaptation at single sites in D. melanogaster is
not limited by mutation has profound implications. The distinction
between standing variation and de novo mutations at single sites is
blurred since virtually all single-site mutations then exist in the D.
melanogaster population at any given time. Strong adaptation should
be much more rapid and generally result in soft sweeps. Complex
adaptations that require multiple changes can be generated
without fixation of interim states and with an enhanced chance
of crossing fitness valleys . This raises the question of whether
the widespread use of the weak mutation, strong selection
(‘‘WMSS’’) model for the study of adaptation should be broadened
to include cases of strong mutation [34,35].
The number of sweeps (hard or soft) might also in general be
lower than the number of adaptive substitutions if complex
adaptations requiring multiple substitutions are common. Indeed,
in our simulations of evolution at Ace in the strong mutation regime
(H per site on the order of 1), the complex 3-mutation alleles
generally evolve without fixation of intermediate 1- and 2-
mutation alleles (Figure 3). The number of adaptive substitutions
estimated using McDonald-Kreitman approaches should then be
larger than the number of independent adaptive fixations and the
prediction of the number of selective sweeps derived from the
number of adaptive substitutions should be upwardly biased .
Note that all of these expectations hold especially well for strong
selection because it operates over shorter time scales and is
therefore less sensitive to recurrent but infrequent bottlenecks
and neighbouring selective sweeps.
Most of the current statistical approaches for the study of
adaptation rely on the expected signatures of hard sweeps .
Such methods should regularly miss or misidentify strong
Figure 4. Population dynamics of neutral and adaptive alleles
in a population with a bottleneck. (A) The population history
similar to that inferred by Thornton and Andolfatto for D. melanogaster
. Values of Hpand Watterson’s Hwwere obtained from coalescent
simulations with 100 sampled genomes. (B) Same scenario as (A) except
for the current population size is changed to 108.
Adaptation in Drosophila Not Limited by Mutation
PLoS Genetics | www.plosgenetics.org7June 2010 | Volume 6 | Issue 6 | e1000924
adaptation if it in fact commonly involves soft sweeps as in the case
of Ace . For example, if one searches exclusively for hard
sweeps, then complete soft sweeps might appear as ongoing hard
sweeps and the polymorphisms associated with the most frequent
haplotype would appear as the likeliest candidates for the adaptive
mutation whereas the true adaptive mutation would be fixed in the
population. Methods exist that have high power to detect soft
sweeps , but they are used less often because soft sweeps have
been considered unlikely a priori. However, a number of cases of
adaptation in Drosophila and mosquitoes show clear signatures of
soft sweeps [38–40]. Soft sweeps might also be common in
humans, with the soft sweep associated with lactase persistence
providing the strongest signature of adaptation in humans [41,42].
Our results suggest that the possibility of pervasive soft sweeps
needs to be taken seriously.
Recurrent boom-bust cycles are a general feature in population
dynamics of most studied organisms. Adaptation and recurrent
selective sweeps reducing the long-term but not the short-term Ne
might also be common. It follows then that short-term and long-
term Nevalues are likely to be different as a rule. The shortest term
Neis only bounded by the census population size, which is often
very large and can easily be in the billions, particularly for insects
or marine organisms. It is thus possible that strong adaptation at
single sites may not be limited by mutation in many eukaryotes,
similar to the situation found in bacteria and viruses .
Materials and Methods
Ace locus genotyping
We sequenced 1450 bp encompassing exons 2 through 4 of Ace.
Resistant mutations I161V and G265A lie in the 3rd exon while
F330Y and G368A lie in the 4th exon (Figure S1). Initially we
sequenced this locus in 68 strains from 20 populations chosen to
represent the Ace locus in a variety of geographical locations. The
list of the populations and the number of lines investigated are
given in Table S1 and Table S2. For some of the strains that
appeared heterozygous after sequencing of the PCR product, the
DNA was first amplified using a proofreading DNA polymerase
(Platinum Pfx; INVITROGEN) and cloned using Zero Blunt
TOPO PCR cloning kit (INVITROGEN) before sequencing.
Note that not all heterozygous strains were cloned, only those that
contained a resistant mutation and the AF strains. The primers
used for PCR amplification of the Ace locus were:
PCR products were then sequenced. Of the 68 sequenced
strains, 26/68 (,40%) have a single or multiple resistant
mutations. Mutations at I161V, G265A and F330Y were
identified in isolation and in combination in multiple populations,
while G368A was never observed. We then used PASA  to
identify strains that contained one or more of the three observed
mutations and sequenced the identified strains. The primers used
for PASA were:
The 161 primer pair amplifies more effectively in the presence
of the mutation I161V. The 265 primer pair is specific to G265A
and the 330 primer pair is specific to G330Y. The annealing
temperatures required for allele specific priming used for 161, 265
and 330 were 61.5uC, 59.5uC and 60.6uC respectively. As positive
and negative controls we performed PASA on strains in which the
resistant sites had been previously characterized. We sequenced 37
strains from 8 populations that had amplified with one or more of
the allele-specific primers. 31/37 (84%) of these strains contained
resistant mutations. The incorrect classification of the 6 strains is
likely due to the addition of excess template to these PCR reactions
resulting in non-specific priming. In total, we sequenced the Ace
locus in 105 strains from 27 populations from five different
continents (Table S1). Twelve of these strains were excluded from
the analysis due to poor sequence quality.
Construction of haplotype network
The most parsimonious haplotype network was constructed
using TCS 1.21 . All resistant alleles, except those for which
we had poor sequence data, and all sensitive alleles observed more
than once were used for the construction of the network. All AF
strains and M strains were also included in the network to provide
information on ancestral and modern variation respectively at the
Estimation of Hpand divergence
Measures of Hpand divergence with Drosophila simulans at the
Ace locus were obtained using DnaSP . All sensitive strains
analyzed in this study were used for the estimation.
Forward simulations of Ace adaptation
Our simulation models the population frequency dynamics of
haplotypes at the 1.5 kb-long sequenced Ace locus and incorpo-
rates mutation, recombination, selection, and population sub-
Haplotypes are classified by their particular adaptive allele
configuration at the three adaptive sites. We describe this
configuration in terms of a vector a1a2a3, indicating whether at
site i the resistance-conferring mutation is present (ai=1) or not
(ai=0). A configuration 101, for example, specifies resistant
mutations at sites one and three, but no resistant mutation at
We use an infinite alleles model for new haplotypes, i.e. every
mutation or recombination event at the locus is assumed to give
rise to a new haplotype, which can be distinguished from all other
haplotypes in the population. This is implemented in our
simulations by assigning a unique ID to every new haplotype.
The specific nucleotide sequence of the new haplotype is not
relevant for our purposes; only changes in the adaptive-allele
configuration are modelled explicitly. We also do not distinguish
different sensitive haplotypes as we focus on the population
dynamics of adaptive haplotypes. These simplifications substan-
tially increase the performance of our simulations, allowing us to
investigate scenarios with population sizes up to 109in reasonable
Mutations at adaptive sites and recombination events where the
recombination breakpoint lies between two adaptive sites can
generate new haplotypes with different adaptive-allele configura-
tion (Table S4). Note that at each site only one specific nucleotide
Adaptation in Drosophila Not Limited by Mutation
PLoS Genetics | www.plosgenetics.org8June 2010 | Volume 6 | Issue 6 | e1000924
is the resistant allele and thus only one out of three mutations of a
sensitive allele will give rise to it.
The evolution of haplotype frequencies is simulated in terms of
a Wright-Fisher model with directional selection, i.e. we assume
panmictic subpopulations of constant size and non-overlapping
generations . Every haplotype h has a specific selection
coefficient s(h). The mean fitness of a subpopulation at time t is
generation t+1 are obtained by sampling from a multinomial
We group resistant haplotypes into three classes according to
the number of resistance-conferring mutations they bear: 1m
haplotypes have one resistant allele (100,010,001), 2m haplotypes
have two (011,101,110), and 3m haplotypes have all three
resistant alleles (111). For simplicity, we assume that all
haplotypes in the same class have equal selection coefficients
s1m, s2m, and s3m, respectively. Prior to pesticide application all
resistant haplotypes are modelled to be deleterious with selection
The key simulation parameters are the selection scenario
defined by the selection coefficients s1m, s2m, and s3m, the
recombination rate r, the number n of subpopulations, the
migration rate M between subpopulations, and the value of H
within subpopulations. We use a constant mutation rate of m=2.5
* 1029per site per generation . Different H-values thus
correspond to different subpopulation sizes. In particular,
H=0.01 corresponds to N=106, and H=1.0 corresponds to
N=108. We estimated a recombination rate of r=0.15 cM/Mbp
for our locus , but investigate also other recombination rates in
Simulation runs start with one single sensitive haplotype present
in all subpopulations at 100% frequency. Before pesticide
application commences, mutation-selection equilibrium of resis-
tant haplotypes is established within a burn-in period of 1000
generations. This fully suffices to establish equilibrium due to the
strong purifying selection against all resistant haplotypes prior to
pesticide application (Box 1). We also verified that longer burn-in
times do not change our results. After the burn-in period, pesticide
application starts by switching to the corresponding selection
scheme. The simulation is then followed for another 1500
generations representing approximately 50 years of pesticide
usage. During every generation individual subpopulations evolve
according to the following steps:
h½s(h)xh(t)?, where xh(t) is the frequency of haplotype
h in the subpopulation at time t. Haplotype frequencies in
1)A random number of mutation events is drawn from a
Poisson distribution with mean m * 1.5 kb * 2N. For each
mutation a random haplotype is drawn from the subpop-
ulation and mutated at a randomly chosen position.
2) A random number of recombination events is drawn from a
Poisson distribution with mean r * 1028* 1.5 kb * 2N. For
each recombination event two random haplotypes are
drawn from the subpopulation and recombined at a
randomly chosen breakpoint.
3) The numbers of migrating individuals to each other
subpopulation are drawn from a Poisson distribution with
mean M. For each migrating individual two random
haplotypes are drawn from the source population and
added to the destination subpopulation.
4)All haplotype frequencies are evolved one generation
according to the above-described binomial sampling proce-
During a simulation run we analyze whether resistant
haplotypes emerged and whether soft sweep signatures among
1m haplotypes were observed. We define 1m resistance by at least
one of the three 1m adaptive-allele configurations (001, 010, or
100) ever being present in more than 10% of the population
during the run. Accordingly, 3m resistance is defined by the
complex 3-mutation allele (111) ever present in at least 10% of the
population. A soft sweep signature (ss) is ascertained if at any time
during the run two independently drawn alleles have greater than
10% probability to bear the same 1m configuration on different
haplotypes. The statistics P1m, P3m, and Pss are the respective
probabilities averaged over many runs. Pcdenotes the combined
probability that 3m resistance emerged and a soft sweep signature
was observed during the same run.
A crucial assumption of our simulation is the applicability of an
infinite alleles model, i.e. all mutation or recombination events are
assumed to be detectable. This can lead to an overestimation of
the probabilities to observe soft sweep signatures in our simulations
if independent mutation events frequently occur on the same
haplotype, or if newly recombined haplotypes often resemble
haplotypes already present in the population. We can estimate the
resulting error from the probability that an individual is
homozygous for the 1.5 kb-long locus. From coalescent simula-
tions using ms  we infer it to be on the order of ,10% when
assuming a per site heterozygosity of out-of-Africa D. melanogaster
subpopulations of Hp,0.5% [18,19] and the above specified
recombination and mutation rates for our locus. Note, however,
that in any case the infinite alleles model can only lead to an
overestimation of the probability to observe soft sweep signatures.
It is therefore always conservative in terms of our analysis. The
probabilities P1mand P3mare not affected by the choice of an
infinite alleles model.
The simulation was implemented in C++. Runs were performed
on the Bio-X2 cluster at Stanford University. All source code is
available from the authors upon request.
Found at: doi:10.1371/journal.pgen.1000924.s001 (0.04 MB PDF)
Structure of the Ace gene.
Found at: doi:10.1371/journal.pgen.1000924.s002 (0.05 MB PDF)
Description of D. melanogaster strains.
Found at: doi:10.1371/journal.pgen.1000924.s003 (0.07 MB PDF)
Segregating sites at the Ace locus in all strains
Found at: doi:10.1371/journal.pgen.1000924.s004 (0.06 MB PDF)
Dynamics of resistance adaptation for different
Found at: doi:10.1371/journal.pgen.1000924.s005 (0.04 MB PDF)
Change of mutation configuration due to mutation or
Found at: doi:10.1371/journal.pgen.1000924.s006 (0.11 MB PDF)
Origin of soft sweep signatures.
We thank members of the Petrov lab, Hunter Fraser, Ward Watt, Marcus
Feldman, Joanna Kelley, Graham Coop, Molly Przeworski, Joachim
Hermisson, Richard Lewontin, Daniel Fisher, John Novembre, Georgii
Bazykin, two anonymous reviewers, and the participants of the Aspen 2010
Biophysics Conference ‘‘Populations, Evolution and Physics’’ for helpful
comments and discussion.
Adaptation in Drosophila Not Limited by Mutation
PLoS Genetics | www.plosgenetics.org 9June 2010 | Volume 6 | Issue 6 | e1000924
Conceived and designed the experiments: TK PWM DAP. Performed the
experiments: TK PWM. Analyzed the data: TK PWM DAP. Contributed
reagents/materials/analysis tools: TK PWM DAP. Wrote the paper: TK
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Adaptation in Drosophila Not Limited by Mutation
PLoS Genetics | www.plosgenetics.org 10June 2010 | Volume 6 | Issue 6 | e1000924

domain: biology


text:
Kerala nurses find a voice that echoes all over
- Powerful bomb rips through bus in Peshawar in Pakistan, 16 killed
- India acts on Pakistan NSA’s tip-off, kills 3 terrorists: Home official
- Kolkata: Two Jamat-ul-Mujahideen Bangladesh members arrested
- BJP is 'most anti-national of all', tweets Arvind Kejriwal
- The 11 Trinamool Congress leaders caught on video allegedly accepting bribes
Nurses in Kerala, an unorganised sector so far, have plunged into an agitation that has been gathering support despite the absence of the backing of any political trade union.
Inspired by the spate of agitations across the world, nurses at a super-specialty hospital in Kochi, run by spiritual leader Mata Amritanandamayi Devi who is known as the hugging saint, staged a three-day stir last week for better pay and working conditions.
The United Nurses Association (UNA), launched on November 16, has set up units at 120 hospitals since, include one last week at the Mata's Amrita Institute of Medical Sciences. Its agitation at AIMS has already got the management to agree to "study the nurses' outstanding issues, including demand for minimum wages, within three months". This has inspired nurses elsewhere, with the UNA going on to serve notices to two Thrissur hospitals run by the powerful Catholic Church. In Thrissur alone, the UNA now has 10,000 nurses under its fold.
The agitating nurses did not enjoy the enthusiastic coverage that the Kerala media had given to recent nurses' agitations in Delhi and Mumbai. Support, however, poured in from online communities, with networking sites discussing the AIMS agitation.
After the launch of the unit, the AIMS management had taken disciplinary action against two office-bearers of the union, dismissing one and transferring the other. The UNA took this up; the agitation began when six office-bearers were assaulted on the campus.
"We went to meet the HR manager to discuss the disciplinary action taken against two male nurses. The management had been irked by the formation of the unit," said Muhammed Shihab, UNA state vice-president. "The assistant HR manager took us to the manager's office, outside the hospital building but on the institution compound," Shihab said.
He said they were going upstairs to the manager's chamber when a group of people attacked them with rods and sticks. One of the office-bearers, Bibu Paulose, suffered a kneecap fracture. Even after the injured were taken to the casualty ward, the attackers remained on the campus. For fear of further attack, the injured were shifted to another hospital.
- Why criticism of the Ujwal Discom Assurance Yojana is misplaced and unwarranted
- Dear Governor Solanki, please withhold your assent to the Punjab SYL bill
- To optimise the potential for medical tourism, stop formulating and implementing policies in silos
- Why riots, agitations are often accompanied by heightened levels of violence against women
- Telescope: On Women’s Day only
- Punjab has a small share of its own rivers, a farming crisis. Solution doesn’t lie in court

domain: news


text:
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Curtis Stone's Honey-Glazed Ham
Linguini with Honey-Sauced Prawns
Chinese Orange Chicken
Roast Chicken with Tangerines
Spicy Chicken Thighs with Rhubarb-Cucumber Salsa
Buffalo Chicken Marinara
Ribs, Hoisin-Glazed Baby Back Pork (Boom)
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Sesame Pork Tenderloin
Spaghetti Squash Noodle Bowl + Lime Peanut Sau...
Crockpot Chipotle Pulled Pork and Pumpkin Chili...

domain: food


text:
A fantastic opportunity has arisen for a Sexual Health specialist Nurse, to manage a team to run a group of Sexual Health clinics.
A reputable group in Chester is seeking a Nurse Manager to run their sexual health clinic with a team of specialist Band 6 Practice Nurses.
This is a unique opportunity for a skilled Practice Nurse or Nurse Practitioner that will combine general Nurse duties and management to create an all-round role to utilise all these skills. The existing team of Nurses are compassionate and friendly, offering advice and treatment to the Chester community. Key Duties
Your key duties will primarily be managing your team of Nurses and HCAs. You will provide clear clinical leadership which involves regular meetings, guidance, support and response to problems that arise. Other duties include:
- Delivering appraisals and developing your team
- Managing the rota and covering for clinics when needed
- Assist in recruitment for the service
- Organise and supervise group and individual meetings
- Ensure the clinic is adhering to the NMC Code of Professional Conduct and following protocol for referrals and documentation
- Work with external health professionals and attend regular clinical governance and audit meetings
- Keeping record of your personal development
You will be keen to get involved in education and research to maintain the clinical competence of your team. It is expected that as a role model, you will attend specialist courses and use your experience to mentor your team. There are chances to lead clinical audits and research projects to present your findings.
Your clinical duties will involve the delivery of sexual health care to your patients on an initial telephone triage basis. You must be keen to reduce the stigma attached to sexual health by bringing an open and positive attitude every day.
You will be well informed on issues including:
- Pregnancy, testing and abortion
- Contraception, particularly IUD fitting
- Emergency contraception
- Confidential Sexual Health counselling and advice
- Screening and treatment of STIs, including HIV
- Cervical screening
You will be managing an existing team of specialist Band 6 Nurses and HCAs to ensure smooth running of the clinic. Prior experience of managing teams is therefore essential. You will be a decision maker for the team with Nurses accountable to you.
This role is for 37.5 hours. Training is supported and encouraged to ensure that you are fully compliant. Package and Benefits
Key Skills, Qualifications and Client Requirements
- A very generous salary of up to £44,000 is offered for the right candidate, based on experience and full time hours (37.5 hours)
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As this is a Nurse Manager role, you will have extensive experience of managing a team in a healthcare setting.
This role requires you to have Sexual Health experience and will involve IUD fitting, amongst other sexual health clinic duties. IUD experience or a willingness to train in this is essential. Ideally, you will be an independent prescriber, although if you are willing to gain this qualification, you will be considered. You will be delivering advice and treatment related to sexual health, it is there essential that you have experience in sexual health.
General Practice Nurses and Nurse Practitioners are welcome to apply, if you have the relevant experience and are open to gaining additional training for this role.
What Happens Next?
- Management experience essential
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- IUD fitting desirable, or willingness to train is essential
- Independent Prescribing qualification desirable, willingness to gain is essential
If you are interested in finding out more about this Nurse role then please click the 'Apply'
button. On submission an email alert is sent to the specialist consultant handling this role to register your interest.
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or call our Primary Care team on 01423 813454
Please attach a copy of your most up to date CV to any emails sent for ease. Not the right job for you? Click here for more Practice Nurse Jobs

domain: medical


It’s all well and good giving fuel saving tips, on paper they look great but its another thing putting them into practice on the open road. The MPG Marathon puts these tips and techniques into practice and is billed as a ” live demonstration of how both car and driver can make a massive difference to fuel costs and emissions”.
The MPG Marathon is in it’s twelfth year and will pit teams of contestants together over a two-day event to push for the best fuel economy in each class. This year, Transport Minister Norman Baker MP will be the guest of honour and will be presenting prizes to the winners at a special event at the Royal Automobile Club in Pall Mall on October 10.
There are 10 classes in this years event and they range from fuel sipping passenger cars all the way up to vans over 3.5 tonnes.
Last year’s winner was Mick Linford and co-driver Ella Flynn who managed an epic 99.24 mpg (2.85 liters/100 km) over a total distance of 370.9 miles (597 km) in his Smart fortwo Cdi. As yet we are unsure if they will be competing in this years event but it would be great to see someone achieve a result over the 100MPG mark.
For more information regarding the event head over to the MPG Marathon website, we’ll update you as events unfold throughout the two day competition.


Boeing to build a factory in Illinois for MQ-25 Stingray production
Boeing will build a new high-tech facility in Illinois, the United States, which will be dedicated to the production of the MQ-25 Stingray, its new unmanned aircraft for the US Navy, the company revealed on September 17, 2021.
The new 300,000 square-foot (27,870.91 square-meters) facility, which will be based at MidAmerica St. Louis Airport (BLV), Illinois, will be equipped with “state-of-the-art” tools, such as robotic automation systems and advanced assembly technologies.
Initially, it will employ approximately 150 mechanics, engineers, and support staff but Boeing hopes the staff numbers could double in the future if it lands more orders.
The unmanned aircraft system MQ-25 was designed for the US Navy missions and it will be capable of providing the Navy with robust refueling capabilities. Aerial refueling is necessary for the Navy to extend the range of its fighter jets and other aircraft. The MQ-25, which will operate from aircraft carriers, will be able to refuel all carrier-capable aircraft of the US Navy.
“The team and state-of-the-art technology we’re bringing to the Navy’s MQ-25 program is unprecedented, and we’re incredibly proud to be expanding both as we build the future of autonomous systems in Illinois,” Kristin Robertson, vice president, and general manager of Autonomous Systems, Boeing Defense, Space & Security, was quoted in the statement.
The MQ-25 facility is expected to be completed in 2024.
On September 13, 2021, the MQ-25 T1 test asset refueled an F-35C Lightning II fighter jet of the US Navy for the first time.
Boeing is already building the first seven MQ-25 aircraft but expects the US Navy to procure more than 70.
China ‘on track’ for 6th-gen fighter, US needs to focus on own development: ACC
A US official said China is going forward with the development of its own sixth generation fighter jet...
USAF F-15 fighter shoots down Iranian drone near coalition base in Iraq
A USAF F-15 fighter shot down an Iranian Mohajer-6 unmanned aircraft as it was heading toward US soldiers in Erbil, Iraq...
France to order 42 Dassault Rafale fighters in 2023
The French Ministry of Armed Forces will order 42 Dassault Rafale fighters in 2023 and replace the 24 second-hand aircra...


Soft skirt with a checked pattern all over and with suspenders in 100% organic cotton. The skirt has a square bib with small flounces all around the bib. The skirt has elastic at the waist with a small flounce all around the edge. The skirt has a lot of gatherings at the waist which gives the skirt a lot of width.The suspenders has a buttons closure at the back. The skirt has a regular and comfortable fit.
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POTD: Full Auto! M4 Carbine at Prince Sultan Air Base, Saudi Arabia
By Eric B
Welcome to TFB’s full auto Photo Of The Day! Shooting full auto is something everyone wants to do, as often as possible. In reality, only a few get to do it, ever. I’ve only shot full auto a few times in the military, and once in the deserts of Nevada. Talking about deserts, above you […]
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The post POTD: Full Auto! M4 Carbine at Prince Sultan Air Base, Saudi Arabia appeared first on The Firearm Blog.


Every year I look out some great Christmas music online, avoiding the big name artists and million sellers you can hear on the radio and TV. They all feature in the ‘Christmas Rocktacular’ podcast which you can stream online, or download for free. Here’s this year’s festive collection.
Under Your Christmas Tree, by Jericko Rose (Jericko Rose on Reverb Nation).
O Come All Ye Faithfull, by Geoff Smith (thegeoffsmith.com).
Christmas In A Cup, by Erica Sunshine Lee (ericasunshinelee.com).
Broke The Bank This Christmas, by Mitch Benn (mitchbenn.com).
St. Benedicts Christmas Fayre, by Lisa Redford (lisaredford.com).
Space Christmas, by Shonen Knife (shonenknife.net).
Lonely Night (Silent Knight), by Rachel Bloom (racheldoesstuff.com).
Some Christmas Hugginâ€™ and a Kissinâ€™, by Geoff SmithÂ (thegeoffsmith.com).


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Probabilistic homogenization of solid foams with application to sandwich structures
The present study is concerned with a numerical analysis of the scatter in the effective material response of solid foams deriving from the microstructural disorder of the material. The effective stress and strain components are determined numerically by means of an volume averaging procedure. In a probabilistic enhancement, the approach is applied to small-scale testing volume elements in order to obtain the stochastic information regarding the local scatter in the effective material properties. As a case study, a single edge clamped sandwich beam with foam core is considered. The material parameters of the foam core are defined as a random field whose properties are determined by the probabilistic homogenization procedure.

domain: chemistry


Inspiration, motivation and practical information for today’s travelling woman. Join your hosts Megsy and Alice for the Girls Talk Travel podcast, as they chat with women who have (trust us) been there and done that!
In this episode, Megsy and Alice are chatting about some kickass and inspirational female travellers that we think you will love too. Be inspired by these amazing women to see the world!
Like the episode on your phone
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Health Minister T Harish Rao said the culture of Congress was to make fake promises, distribute cash bags and create communal tensions.
Speaking after laying the foundation stone to Padthanpalli Lift Irrigation Scheme and a 33/11 kv power substation at Donabanda village in Hajipur mandal on Saturday, he said the Congress was daydreaming to win the mandate of the public by distributing money brought from Karnataka. But communal violence and curfews would be an order of the day. The Congress failed to keep its several promises made at the time of polls in the past.
The Minister, who criticised the Congress for eliminating banned Maoists under the guise of consultations, exuded confidence that the BRS would be able to form the government for the third time in a row.
Certain opposition party leaders were trying to spoil the tranquility of Mancherial by wooing the public with baits. A leader who ran a gambling club and looted several banks in Hyderabad was now eying the constituency, he said, cautioning voters against such people and asked them to elect BRS nominee N Diwakar Rao, who was known for his accessibility round the clock.
Rao said BJP president JP Nadda could not save his party from failure in the elections to Himachal Pradesh Legislative Assembly. What would he do in Telangana, he asked. Stating that the BJP would not get a single seat in Telangana, he asked Nadda to form a committee to save deposits of BJP nominees.
Government whip Balka Suman, MLC Dande Vittal, Peddapalli MP Dr Venkatesh Netha, MLAs Diwakar Rao Durgam Chinnaiah, Collector Badavath Santosh, DCP Sudhir Kekan and others were present.
The irrigation scheme, which can lift 1 TMC of water, is envisaged to irrigate agriculture fields in 16 villages of Hajipur and two villages of Luxettipet mandal, spending Rs 80.50 crore. The estimated cost of the power sub-station is Rs 3 crore.


Motivation: The availability of genome-wide location analyses based on chromatin immunoprecipitation (ChIP) data gives a new insight for in silico analysis of transcriptional regulations. Results: We propose a novel discriminative discovery framework for precisely identifying transcriptional regulatory motifs from both positive and negative samples (sets of upstream sequences of both bound and unbound genes by a transcription factor (TF)) based on the genome-wide location data. In this framework, our goal is to find such discriminative motifs that best explain the location data in the sense that the motifs precisely discriminate the positive samples from the negative ones. First, in order to discover an initial set of discriminative substrings between positive and negative samples, we apply a decision tree learning method which produces a text-classification tree. We extract several clusters consisting of similar substrings from the internal nodes of the learned tree. Second, we start with initial profile-HMMs constructed from each cluster for representing putative motifs and iteratively refine the profile-HMMs to improve the discrimination accuracies. Our genome-wide experimental results on yeast show that our method successfully identifies the consensus sequences for known TFs in the literature and further presents significant performances for discriminating between positive and negative samples in all the TFs, while most other motif detecting methods show very poor performances on the problem of discriminations. Our learned profile-HMMs also improve false negative predictions of ChIP data.


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Guide to Feline AIDS
immunodeficiency virus, also commonly referred to as FIV,
feline AIDS or cat AIDS, is a contagious disease which can
be passed from one cat to another.
Feline immunodeficiency virus is similar in many ways to the feline leukemia
(FeLV) virus. Both viruses are retroviruses and both viruses are contagious
to other cats. However, the FIV and FeLV viruses are two completely different
Feline immunodeficiency virus is normally passed from one cat to another
through contact with body secretions. Bite wounds from cat fights are
the most common means of transmission. However, the virus can also be
passed less frequently through sharing food dishes, water bowls, litter
boxes, grooming, and other cat-to-cat contact.
Symptoms of feline immunodeficiency virus can be extremely variable.
The FIV virus has the ability to depress the immune system of an infected
cat, leaving the cat susceptible to secondary infections. Symptoms will
depend on the type of infection present, but basically any time a cat
becomes ill, FIV is something which needs to be ruled out as the cause,
particularly if the cat's lifestyle puts the cat at risk of exposure
to feline AIDS.
Testing for feline AIDS is recommended for all cats. Feline immunodeficiency
virus testing is often done concurrently with feline leukemia virus testing.
Recently, a new test which also includes a feline heartworm antigen test
in conjunction with FIV and FeLV testing has been introduced and is being
Testing is recommended for kittens (though there is the risk of maternal
antibody interference with the test at a young age), for cats that are
to be introduced to households with other cats, for cats that have been
exposed to the virus and for cats that are ill. Kittens that test positive
for FIV initially are often retested in several months to confirm that
the test is truly positive and many test negative on a follow-up test.
These combination tests are good screening tests for FIV. However, more
sensitive testing is recommended for cats which test positive on these
tests to rule out the possibility of a false positive test and confirm
the presence of an FIV infection.
A positive FIV test means that the cat has been exposed to the feline
immunodeficiency virus. It does not mean that the cat is dying from the
infection or is going to die from the infection, although the risk of
disease is present.
A positive test does indicate that the exposed cat could be a carrier
of the disease and therefore capable of passing the disease to other
cats. Therefore, cats which test positive for feline AIDS should be housed
separately indoors and not allowed contact with other uninfected cats.
Cats with positive FIV tests need to be monitored closely for signs of
illness and medical attention should be pursued promptly should any signs
of illness occur. Keeping these cats healthy, providing proper nutrition,
avoiding stress as much as possible and encouraging a strong active immune
system creates the basis for caring for a FIV positive cat.
Healthy cats testing positive for feline immunodeficiency virus do not
need to be euthanized. However, it should be noted that FIV is usually
fatal for those cats which are showing clinical signs of illness as a
result of the virus.
There is a vaccination available for FIV. However, the vaccine is controversial
and veterinarians do not always agree on whether the vaccine should be
used. The feline immunodeficiency virus vaccine is a non-core vaccine
and is recommended only for at-risk cats, if it is recommended at all.
Vaccination produces a positive FIV test which may be mistaken for a
FIV infection in some cats, leading to the controversy surrounding the
vaccine. Cat owners should discuss the vaccine with their veterinarian
to best determine whether their cat would benefit from the vaccine.


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What Is Oil ETF?
Oil ETF is the exchange-traded funds which invests in the firms operating across commodities in the oil and gas industry. It tracks a particular segment of the market and comes up with a unique proposition that allows investors to take positions without worrying much about the threshold or margin requirements and trade very much like they do inequities.
Given its size and importance in the global economic and political scenario, the oil industry is the darling of investors and traders. Consequently, the corresponding contracts are equally popular but riskier because of the very nature of the derivative markets. However, using oil ETF, one can understand and take positions in the oil commodity and reap profits.
- The “oil ETF” invests in companies that deal in oil and gas-related commodities.
- It tracks a specific market segment and offers investors a unique opportunity to take positions without worrying too much about threshold or margin requirements. It trades very similarly to how they would with stocks.
- Investors keep a watch on crude oil and the derivatives contracts related to it. Since this commodity is so popular, even the five- and ten-year contracts are active and very volatile.
- Because of the rewards it provides, the erratic oil business is highly well-liked by investors.
Oil ETF Explained
Oil ETF is a kind of investment in which the investors can gain exposure to the performance of the oil industry either through derivatives like future contracts and options or by investing in shares of companies in the oil industry.
Oil ETF stock invests in companies across oil and gas commodities through commodity pools with limited partnershipsLimited PartnershipsIn a limited partnership, two or more individuals form an entity to undertake business activities and share profits. At least one person acts as a general partner against one limited partner who will have limited liability enjoying the benefits of less stringent tax laws. through both derivative contracts such as futures and options and shares of the firms dealing in these commodities.
It works as a proxy for investors who want to participate in oil traded firms and reap potential benefits. These investors can only focus on the oil index without worrying about operational issues like logistics, delivery, storage, etc.
The volatile industry of oil is quite popular among investors because of the returns that it offers. It offers huge returns, but with huge returns, the huge risk is involved. The prices of oil contracts move up and down in a very short span of time. This is because the underlying commodity – oil, is highly volatile and is affected to a huge extent by the global political conditions. If the global economic growth and political conditions are stable, oil prices would be stable.
Following are some examples of top traded oil ETF stock in international markets:
#1 – XLE
- Full Name – Energy select sector SPDR
- Assets Under Management – $ 13 Billion
- Expense Ratio – 0.14%
- Performance – 21.47% (1-year return as per 2015 stats)
#2 – CRAK
- Full Name – Vleck vectors Oil refiners ETF
- Assets Under Management – $ 24.82 million
- Expense Ratio – 0.59%
- Performance – 36.57% (1-year return as per 2018)
#3 – USO
- Full Name – United states Oil fund
- Assets Under Management – $ 3.95 billion
- Expense Ratio – 0.72%
- Performance – 45.97% (1-year return as per 2018)
The gas and oil ETF is not very different from mutual fundsMutual FundsA mutual fund is a professionally managed investment product in which a pool of money from a group of investors is invested across assets such as equities, bonds, etc with the only difference that they can trade at an exchange in real-time much like shares. Mutual funds, on the other hand, are valued based on the final settlement price at the end of the day. Also, there is no minimum threshold, and even retail investors can sell an oil ETFETFAn exchange-traded fund (ETF) is a security that contains many types of securities such as bonds, stocks, commodities, and so on, and that trades on the exchange like a stock, with the price fluctuating many times throughout the day when the exchange-traded fund is bought and sold on the exchange. with small amounts. There are four main types of Oil ETF:
#1 – Leveraged Oil ETF
Leveraged gas and oil ETF focuses on the amplified returns compared to the benchmark index while maintaining the minimum losses. For example, a double ETF focuses on getting the double returns to the movement in the benchmark index.
#2 – Inverse Oil ETF
Inverse oil ETF price focuses on getting returns if the oil prices move in the opposite direction. For example, if the oil prices dropped by 7%, such would be the composition of the index that the returns would be approx. 7%. Because of this, most often than not, the inverse oil ETF is the best hedging mechanism among the available Oil ETF options.
#3 – Smart Beta Oil ETF
Smart Beta Oil ETF does not have a specified strategy, but these funds focus on maximizing returns based on smart, unconventional strategies and tactics. They are very risky but equally rewarding.
#4 – Index ETF
Last but not least is the index ETFs. These are the vanilla products that try to mirror the basket of different varying products.
Some of the advantages of this kind of ETFs are as follows:
- Investors always an eye for crude oil and its derivativesDerivativesDerivatives in finance are financial instruments that derive their value from the value of the underlying asset. The underlying asset can be bonds, stocks, currency, commodities, etc. The four types of derivatives are - Option contracts, Future derivatives contracts, Swaps, Forward derivative contracts. contracts. In fact, such is the penchant for this commodity that even the five year and 10-year contracts are liquid and highly volatile. Unlike bitcoinBitcoinBitcoin is a digital currency that came into existence in January 2009, speculated to be created by Satoshi Nakamato, whose true identity is yet to be authenticated. It provides lower transaction fees than the traditional online payment systems, is controlled by the decentralized authority, and is not like government-issued currencies. or cryptocurrenciesCryptocurrenciesCryptocurrency refers to a technology that acts as a medium for facilitating the conduct of different financial transactions which are safe and secure. It is one of the tradable digital forms of money, allowing the person to send or receive the money from the other party without any help of the third party service., it is not one of those assets which have been conceptualized only on paper where valuations are defined based on the euphoria created by the speculatorsSpeculatorsA speculator is an individual or financial institution that places short-term bets on securities based on speculations. For example, rather than focusing on the long-term growth prospects of a particular company, they would take calculated risks on a stock with the potential of yielding a higher return. with fundamentals being left behind.
- Oil, on the other hand, is one of the richest industries of the last century. In fact, it is the backbone of other major capital-intensive industries like airlines, auto majors, and to some extent, fast-moving consumer goods. As per independent research in 2018, the oil industry size was estimated at 2.5 trillion $.
- In fact, the expenditure on this industry by consumers is much more than other commodities like iron, gold, silver, etc. however, because of the huge volatility involved, many retail investors are not able to participate in this industry and are forced to be away from this unpredictable but fundamentally sound commodity marketCommodity MarketThe commodity market is a place where people buy and sell positions in commodities such as oil, gold, copper, silver, barley, wheat, and so on. Started with agricultural commodities, there are now fifty main commodity markets throughout the world, dealing with over a hundred commodities..
- It helps those investors in investing as a basket without worrying about the multiple industries which might be located very far geographically and thus eliminating country riskCountry RiskCountry risk denotes the probability of a foreign government (country) defaulting on its financial obligations as a result of economic slowdown or political unrest. Even a little rumour or revelation can make a state less attractive to investors who want to park their hard-earned income in a reliable place..
- Dealing in oil ETF price provides the best hedge for the retail investorsThe Best Hedge For The Retail InvestorsA retail investor is a non-professional individual investor who tends to invest a small sum in the equities, bonds, mutual funds, exchange-traded funds, and other baskets of securities. They often take the services of online or traditional brokerage firms or advisors for investment decision-making. as well as for the firms that already have oil positions. Consider the example of the aviation industry that unknowingly has huge exposure to oil contracts because of the very industry they worked on fuels on this energy source. It helps these firms in hedging their naked positions and making sure the profitability is intact.
Let us look at some of the disadvantages of the ETF alongside its benefits.
- If there is a global turmoil or a war-like situation or a political crisis, oil prices are impacted hugely, and conversely, the oil contracts rise or fall multi-folds. Also, oil prices are impacted even when there are talks about recession as the receding economy requires less oil, which is again a concern for the investors and affects the oil prices, thereby oil contracts. To cut the story short, trading in oil requires a good amount of volatility, which everyone cannot digest. However, trading in Oil ETF helps investors in taking positions without worrying much about volatility.
- Any kind of political instability in the areas where oil production takes place will affect the oil prices and in turn have an effect on the ETFs. Problems like sanctions, wars or any type of natural disasters will negatively impact the demand and the supply of oil and consequently affect the ETFs.
• The management fee charged by the ETFs can reduce the returns on them. In case the investors invest on a long term basis, then over time the returns might reduce substantially.
• Investors may be concerned about the effect on the environment because investment in the oil industry means higher production of oil which is a fossil fuel and is non- renewable. Thus, over production will deplete them faster and also lead to a negative effect on the climate. So there is an ethical concern in this field also.
• There may be a contango effect on this type of ETFs leading to a decrease in value of the same. Contango is the situation in which the price of futures of the commodity is more than the spot price. Thus, the ETF’s value comes down.
How To Buy?
Now let us try to understand the various steps that are to be followed in order to invest in the best oil ETF.
• Good Research – Proper research and clear information is always helpful before any kind of investment. Therefore the investor should do a through research, find out the performance fees to be charged and compare them with their peers, and also look for the strategies that will be used. This will help in selecting an ETF that aligns with the risk tolerance of the investor and their aim of investment.
• Place the trade – next comes the step of placing the trade which will happen only after identifying the correct ETF for investment. The investor will place a buy order form the brokerage account and specify the number of stocks that they want to invest in along with the price.
• Investment monitoring – It is very important to keep track of the ETF’s performance regularly. This can be done by tracking the performance of the oil industry, the economic and political conditions of the country, etc.
- Brokerage account – It is necessary to have a brokerage account to buy it. It is always better to select a brokerage that offers ETFs commission free or allows trading an a minimum fee so that the investment cost is reduced.
Thus, the steps of investing in the best oil ETF are given in detail above. However, since risk is involved in the entire process, it is always recommended that the investor take the help of a financial advisor to understand whether the selected ETF aligns with their profileand then go ahead with the investment.
Frequently Asked Questions (FAQs)
Whether oil ETFs are a good buy depends on various factors, including your investment goals, risk tolerance, and the outlook for the oil market. It is essential to conduct thorough research, analyze the current oil market conditions, and consider your investment needs before deciding.
Oil ETFs typically do not pay dividends in the same way as individual stocks. Unlike stocks of respective companies that may distribute dividends to shareholders, most oil ETFs are structured to reflect the performance of the underlying assets they track, such as oil futures contracts or energy company stocks. However, there are a few exceptions where certain oil ETFs may distribute dividends.
Oil ETFs aim to mirror the performance of the underlying assets they track. They can be structured as commodity ETFs, equity ETFs, or a combination. Investors can buy and sell shares of the ETF on stock exchanges like regular stocks.
This has been a guide to what is Oil ETF. We explain how to buy it along with examples, types, advantages and disadvantages. You can learn more about investment from the following articles –

domain: finance


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Fluorine teams up with water to restore inhibitor activity to mutant BPTI.Ye, S., Loll, B., Berger, A.A., Mulow, U., Alings, C., Wahl, M.C., Koksch, B.
(2015) Chem Sci 6: 5246-5254
- PubMed: 29449928
- DOI: 10.1039/c4sc03227f
- Primary Citation of Related Structures:
- PubMed Abstract:
Introducing fluorine into molecules has a wide range of effects on their physicochemical properties, often desirable but in most cases unpredictable. The fluorine atom imparts the C-F bond with low polarizability and high polarity, and significantly ...
Introducing fluorine into molecules has a wide range of effects on their physicochemical properties, often desirable but in most cases unpredictable. The fluorine atom imparts the C-F bond with low polarizability and high polarity, and significantly affects the behavior of neighboring functional groups, in a covalent or noncovalent manner. Here, we report that fluorine, present in the form of a single fluoroalkyl amino acid side chain in the P1 position of the well-characterized serine-protease inhibitor BPTI, can fully restore inhibitor activity to a mutant that contains the corresponding hydrocarbon side chain at the same site. High resolution crystal structures were obtained for four BPTI variants in complex with bovine β-trypsin, revealing changes in the stoichiometry and dynamics of water molecules in the S1 subsite. These results demonstrate that the introduction of fluorine into a protein environment can result in "chemical complementation" that has a significantly favorable impact on protein-protein interactions.
Department of Biology, Chemistry, and Pharmacy , Freie Universität Berlin , Institute of Chemistry and Biochemistry , Takustr. 3 , Berlin, 14195 , Germany . Email: email@example.com ; ; Tel: +49-30-83855344.


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Andrew Garfield Plays Basketball Dressed as Spider-Man
Andrew Garfield has been making rounds to promote "The Amazing Spider-Man 2" but nothing quite beat his visit at Brixton charity Kid's City. The actor donned full costume of the web-slinging hero and played basketball with the children.
Garfield dropped by the local charity in London borough of Lambeth on Wednesday, April 9 afternoon. The charity provides out of school activities for children between the ages of 3 and 11. Garfield was happy to accompany them playing ball at a nearby basketball court in Brixton Hill Place.
During the game, Garfield took his time to chat with the kids and gave them encouragement. He was later given a tour of the grounds and enjoyed some pizza with the kids after taking off his ensemble.
Garfield and his on and off-screen girlfriend Emma Stone will next attend the movie's premiere at Leicester Square on Thursday evening.
More Andrew Garfield News
- Louis Tomlinson Files for Joint Custody of His Son With Briana Jungwirth
- Iggy Azalea Addresses Nick Young Baby Rumor, Reveals She Caught Him Cheating on Camera
- 'Ghostbusters' Cast Show Off the New Gadgets in Latest Featurette
- HBO Officially Confirms Jon Snow's True Parentage With This 'Game of Thrones' Infographic
- New 'Star Trek Beyond' Character Poster Shows Jaylah on Cap's Chair
- Lady GaGa and Taylor Kinney's Wedding Plan Reportedly Shelved Because of This
- Taylor Swift and Tom Hiddleston Make Out in Rome, Fans Say Their Romance Is 'Staged'
- Watch James Van Der Beek Channel Diplo to Promote Mad Decent Block Party

domain: entertainment


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Batman Animated Joker Jumbo
In the fall of 1992, a new animated series debuted from Warner Bros. Animation on weekday afternoons, Batman: The Animated Series. Gentle Giant celebrates this much-loved television show with the Jumbo Batman: The Animated Series: The Joker figure. Based on digital scans of the original Kenner 5" action figure, this Jumbo figure stands 12" tall in 1/6-scale. Every detail is meticulously recreated from the original figure, capturing perfectly the design aesthetic and tone of the series embodied in the Clown Prince of Crime. Relive part of Batman history and afternoon nostalgia with this new figure!


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Explore, connect, and unlock the potential for growth and collaboration within Saskatchewan’s dynamic business community.
Lodging & Travel
Welcome to the Riviera Motor Inn, located in Saskatoon, Saskatchewan. Where you're in ''For the Best Sleep of Your Life.''
Come visit today to take advantage of our good location, minutes from Saskatoon's Airport, Sasktel Centre and downtown shopping. Our facilities contain all of the amenities the traveler requires. Also enjoy great food and friendly service from Crazy Eggs Restaurant.

domain: travel