Download Chapter 4 The remedy to genetic erosion problems

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Supporting information
Appendix S1 Factors expected to affect the magnitude of genetic rescues for fitness
The magnitude of genetic rescue due to outcrossing within species is expected to
equal the extent of inbreeding depression if inbreeding is totally eliminated and there
is no outbreeding depression. Empirical findings from several studies supports this
prediction (see main text).
The magnitude of inbreeding depression (ID) depends upon the increase in
inbreeding coefficient (∆F), and the genetic load in the population, as indicated by the
following equation (after Falconer & Mackay 1996):
# loci
ID = ∑2piqidi∆F
(eqn S1)
i = 1,
where 2piqi is the heterozygosity for each polymorphic locus and di its dominance
deviation (deviation of the heterozygote mean from the mean of the homozygotes)
and the summation is over all polymorphic loci with genotypes differing in their
impacts on the quantitative traits (reproductive fitness in the current context). The
2piqi term is reduced by a history of small population sizes or for selfing species. For
habitually inbreeding species, this term will be very small, such that there will be at
best a weak relationship between inbreeding depression and F while for mixed
mating species the relationship is likely to be highly variable. Thus, tests for impacts
of ∆F are best restricted to outbreeding species (as I did).
As expected from this equation (with the effects of loci combining additively on
average), inbreeding depression is usually approximately linearly related to the
inbreeding coefficient (see Falconer & Mackay 1996; Lynch & Walsh 1998). An
alternative formulation is provided by Morton et al. (1956) for the ratio of survival in
inbred (SI) and outbred (So) populations where the effects of loci are expected to
combine multiplicatively:
SI/SO = eA – BF
(eqn S2)
where B is the number of haploid lethal equivalents (a measure of the genetic load in
the population) and eA is the survival of the non-inbred population. In this case, the
natural logarithm of survival is expected to decline linearly with F, as is usually found
empirically (Ralls et al. 1988). Thus, by extension the magnitude of genetic rescue
effects should be positively correlated with the difference in inbreeding coefficient
(ΔF) between the inbred and outcrossed populations.
The amount of benefit (heterosis) on fitness from crossing two populations is
predicted to depend on the genetic distinctiveness (y - difference in allele frequencies
between the target and rescuing populations summed across loci affecting fitness),
as illustrated by the following equation for F1 heterosis for traits determined by
zygotic genotypes (Falconer & Mackay 1996) (the F2 heterosis is half that in the F1):
# loci
F1 heterosis = ∑diyi2
(eqn S3)
i = 1,
The extent of inbreeding depression is expected to differ with ploidy level
(diploid ≥ polyploid > haplodiploid > haploid: Frankham et al. 2010, 2014), but there
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were too few data to make meaningful comparisons of genetic rescue effects among
ploidy levels in my analyses.
The predictions about genetic rescue being tested are:
1. The outcrossing of inbred populations to isolated populations of the same
sexually reproducing species (with the same karyotype, adapted to the same
environment and isolated for ≤ 500 years) will be beneficial, especially in
naturally outbreeding species (Frankham et al. 2011).
2. Genetic rescue effects will be positively correlated with ΔF for naturally
outbreeding species (see above). Relationships are expected with both the
maternal and the zygotic ΔF, as discussed in Appendix S2 below.
3. The magnitude of genetic rescue effects will be larger in wild or stressful
environments than in benign/captive ones (Dudash 1990; Fox & Reed 2011;
Enders & Nunney 2012).
4. The benefits of outcrossing will be greater in naturally outbreeding species
than inbreeding (selfing or mixed mating) ones (Byers & Waller 1999).
5. Outbred immigrants will yield larger average benefits than inbred ones (Pickup
et al. 2013). This assumes that the populations being crossed have been
isolated for sufficient generations to have differences in their contents of
deleterious alleles. No rescue is expected if the crossed populations are
recent derivatives from the same source, such as source-sink populations.
6. The magnitude of rescue effects will be larger for composite fitness than for
individual fitness components (Frankham et al. 2010)
7. There will be little difference in the magnitude of genetic rescue among major
eukaryotic taxa.
8. Genetic rescue effects will be greater in F1 than in F2 and later generations
for zygotically determined traits, but F2 > F1 for maternally determined traits
(see Appendix S2).
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Appendix S2 Inbreeding depression and genetic rescue for maternally and
zygotically determined traits
As some traits are determined by maternal genotypes, others by zygotic genotype
and total and composite fitness by a combination of these (Wright 1977; Roach &
Wulff 1987; Wolfe 1993; Montalvo 1994; Falconer & Mackay 1996), changes in both
maternal and zygotic inbreeding coefficients need to be considered both during
inbreeding and following crossing of populations (Falconer & Mackay 1996). In
general, the maternal inbreeding coefficient lags the zygotic one by a generation. For
example inbreeding depression in litter size for mice is modest until the mothers are
inbred, whilst adult survival typically exhibits inbreeding depression as soon as the
zygotes are inbred (Bowman & Falconer 1960). Similarly in plants, seed number and
weight show little inbreeding depression when maternal plants are outbred and
zygotes are inbred, but substantial inbreeding depression when maternal plants are
inbred (Wolfe 1993; Montalvo 1994).
In genetic rescue experiments, the reversal of inbreeding depression is
likewise delayed for maternally determined compared to zygotically determined traits
(Table A1) and the two inbreeding levels are not equal until the F3 generation.
Consequently, genetic rescue effects for total and composite fitness are expected to
be dependent on both maternal and zygotic ΔF values. In the F1, the maternal ΔF
(ΔFm) is zero, as the inbreeding coefficient is that of the mothers and is not changed
by crossing. Conversely the zygotic ΔF (ΔFz) is the difference between the maternal
F [½ (Fa + Fb)] and the zygotic F (0) = ½ (Fa + Fb).
Table A1 Maternal and zygotic inbreeding coefficients in F1, F2 and F3 crosses
(involving multiple individuals in each case) between (a) different inbred populations,
or (b) between inbred females and outbred males from different populations (with
random mating of the parents of each generation) and ΔFm and ΔFz values for
comparisons between crosses and the inbred parent population.
__________________________________________________________________
Maternal F
Zygotic F
ΔFm
ΔFz
__________________________________________________________________
(a) Reciprocal crosses between different inbred parental populations with inbreeding
coefficients of Fa and Fb with comparisons being made between crossed populations
and the mean of the two inbred parents
__________________________________________________________________
F1
½ (Fa + Fb)
0
0
½ (Fa + Fb)
F2
0
¼ (Fa + Fb) ½ (Fa + Fb) ¼ (Fa + Fb)
F3
¼ (Fa + Fb)
¼ (Fa + Fb) ¼ (Fa + Fb) ¼ (Fa + Fb)
(b) Crosses between inbred female and outbred male parent populations with
inbreeding coefficients of Fa and 0 with comparison being made between crossed
populations and the inbred parent
___________________________________________________________________
F1
Fa
0
0
Fa
3
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F2
F3
0
¼ Fa
¼ Fa
¼ Fa
4
Fa
¾ Fa
¾ Fa
¾ Fa
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Appendix S3 Additional details of data selection criteria
Within studies of the same populations, I preferentially used data on the most
inclusive fitness characters I could find or construct. Where there were data only on
multiple separate fitness components, I computed composite fitness from the
component data, as is commonly done in plant studies (e.g. Hereford 2009a).
Species with permanent translocation heterozygosity across much of their
genomes were excluded, as they exhibit little or no homozygosity or inbreeding
depression (Heiser & Shaw 2006).
I did not exclude any outbred/inbred comparisons purely on the basis of small
sample size and low statistical power to minimize bias. However, I did exclude the
F2/inbred parent comparison in the song sparrow data of Marr et al. (2002) as the
inbreeding coefficient in the F2 (0.076) was higher than that in the inbred parent
population (0.066).
In assessing the risk of outbreeding depression, adaptive differentiation,
where not directly known, was inferred from differences in biotic and/or physical
environmental between the populations (e.g. temperature, day length, soils, large
geographic distances, different host plants, and diets; (Turesson 1922; Antonovics
1976; Snaydon & Davies 1982; Bradshaw 1984; Hoffmann & Weeks 2007).
Where information was unclear, I emailed authors in an attempt to clarify details.
Assessments of the above characteristics were made on the balance of probabilities
to include as many studies as possible. Where information on one characteristic in
the outbreeding depression screen was not available (often the case for
chromosomes) the risk assessments were based on the remaining information
(potentially increasing the risk of outbreeding depression).
In minimizing pseudoreplication, I chose traditional measures of mean
populations fitness (composite fitness, or survival or fecundity), rather than
demographic measures such as population growth rate or increase in populations
size (recommended by Whiteley et al. 2015), as fitness differences may not be
detectable under conditions of density regulation when populations are at carrying
capacity (Frankham et al. 2010 p. 292), as observed, for example by Adams et al.
(2011). However, genetic rescue in traditional measures of population fitness are
expected when populations are recovering from low population sizes (Frankham et
al. 2010 p. 292).
Since there were often uncertainties in information for screening against a
high risk of outbreeding depression, especially in inbreeding levels, isolation of
populations and likelihood of adaptive differentiation of populations, data were
categorised as higher versus lower certainty of assessments, based on strength of
evidence relating to risk of outbreeding depression and the statistical power of the
data, and the two categories compared. As the two had similar characteristics and
did not differ significantly in the fitness benefits of outcrossing, analyses reported
here were completed on the combined data.
Information on variables expected to affect the magnitude of genetic rescue
effects were recorded, namely items 2-7 in Appendix S1, with the addition of number
of inbred and outcrossed populations (for computing the weighting factor used in
tests for publication bias).
Inbreeding coefficients
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The inbreeding coefficients (F) in the inbred and crossed populations were based on
the probability that two alleles at a locus in an individual are identical by descent
(Malécot 1969; Falconer & Mackay 1996). F values were zygotic inbreeding
coefficients, except were indicated otherwise. When inbreeding coefficients were not
reported (often), indirect estimates were obtained where possible from allozyme or
microsatellite heterozygosity data using the equation (Frankham et al. 2010):
F = 1 – (HI/HO)
(eqn S4)
where HI is the heterozygosity of the inbred populations and Ho that of the non-inbred
comparator population. Only estimates from outbreeding species were used in
analyses.
The inbreeding coefficients for admixed populations (after two or more
generations) formed from populations with inbreeding coefficients of Fi with
proportions pi of alleles from each population were computed using the following
equation (Margan et al 1998):
Fpooled = ∑pi2Fi
(eqn S5)
This assumes that there is no selective difference between immigrant and resident
alleles, as do pedigree inbreeding coefficients.
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Table S1. Genetic rescue (GR) data set 1 for fitness (uploaded as a separate Supporting Information Excel file).
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Table S2 Genetic rescue data set for evolutionary potential (GREvP) for fitness traits
Generations
Finbredb
1.179
3.55
0.405
0.203
1.34073
Holleley et al. (2011)
1.064
12
0.165
0.03
1.16168
Invertebrate
Holleley et al. (2011)
1.036
26
0.165
0.115
1.05988
mysid shrimp
Invertebrate
Market et al. (2010)
1.270
3
0.313
0.156
1.22727
Americamysis bahia
mysid shrimp
Invertebrate
Market et al. (2010)
1.861
3
0.313
0.052
1.37879
Americamysis bahia
mysid shrimp
Invertebrate
Market et al. (2010)
1.847
3
0.313
0.039
1.39773
Species
Common name
Major taxa
Reference
Drosophila melanogaster
fruit fly
Invertebrate
Margan et al. (1998)
Drosophila melanogaster
fruit fly
Invertebrate
Drosophila melanogaster
fruit fly
Americamysis bahia
GREvP/Gena
aGenetic
Fcrossc
GDX/GDId
Comments
Comparison of Ne =
50 vs 2x50
treatments
Comparison of N =
50 migration rates of
0.04 vs 0.0025
Comparison of N =
50 migration rates of
0.01 vs 0.0025
Comparison of 1X
vs 2X treatments
Comparison of 1x vs
6X treatments
Comparison of 1x vs
8X treatments
rescue ratio per generation.
coefficient of inbred parent population(s).
cInbreeding coefficient of zygotes in crossed population.
dRatio of genetic diversity in outcrossed population to that in the inbred parent population, estimated from (1 - F
cross)/(1 – Finbred).
bInbreeding
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Appendix S4 Effect size for evolutionary potential and variables expected to
affect it
Effect size
The response ratio was used as the effect size for evolutionary potential, but
was expressed on a per generation basis, as different studies had different
durations in generations (t). Selection responses (selected – control) per
generation in the outcrossed/inbred populations was converted to a per
generation basis by raising the response ratio to the power of 1/t. Response
ratios for Margan et al. (1998) data were obtained by subtracting the NaCl
concentrations at extinction for the fully inbred control populations from that of
the populations of interest. For the remaining studies where population sizes
under selection were reported after different numbers of generations (t, and t
– x), the ratio of Nt/Nt-x for the crossed populations was divided by the
corresponding ratio for inbred parent populations, and the resulting ratio
raised to the power of 1/x.
Variables affecting genetic rescue for evolutionary potential
The extent of evolutionary genetic adaptation (GA) in the short term is
predicted by the breeders’ equation GA = h2S, where h2 is the heritability and
S the selection differential (Falconer & Mackay 1996). This provides a basis
for determining the variables expected to predict genetic rescue for
evolutionary potential (GREvP), as follows:
GREvP = hX2 Sx
hI2 SI
(eqn S6)
where the subscripts I and X stand for the inbred parent and the crossed
population in F2 and later generations. The effect of crossing on heritability is
predicted to be closely related to the increase in genetic diversity, as follows:
hX2 = VAX/VPX = VAX (VPI) = ∑2pixqixaix2(VPI)
hI2 VAI/VPI
VAI (VPX) ∑2piIqiIaiI2 (VPX)
(eqn S7)
where VA is the additive genetic variation, VP the phenotypic variation, 2pq is
the heterozygosity for alleles affecting fitness, and a is half the difference in
mean between the two homozygotes at the locus. Thus, genetic rescue for
fitness will depend on the increase in heterozygosity in the crossed population
after Hardy-Weinberg equilibrium has been established, compared to that in
the inbred parent population. While VA for fitness traits often increases initially
before decreasing with inbreeding in the environment to which the population
is adapted (Willi et al. 2006), this is unlikely in the context of adaptation to new
environments, as then genetic variation for fitness is primarily additive, rather
than non-additive (Frankham et al. 1999; England et al. 2003; Frankham et al.
2011). The benefits of gene flow on evolutionary potential should depend
upon the proportionate increase in genetic diversity for fitness, if there is no
outbreeding depression. In the current context this proportion should typically
be similar to that for neutral markers (Briscoe et al. 1992; Frankham et al.
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1999; England et al. 2003; Gilligan et al. 2005). It there is heterozygosity data,
then GREvP should be related to the ratio of
heterozygositycross/heterozygosityparent (GDX/GDI) while if there are only
inbreeding coefficient, the ratio can be estimated as (1- FX)/(1 - FP). The latter
expression has been used to determine the ratios in this paper.
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Table S3 Characteristics of the nine studies that reported deleterious effects of outcrossing.
Species
Mating
system
GR
Caenorhabditis
elegans
Selfing
0.90
Inbreeding
difference
ΔF
≥ 0.75
Environment
Fitness
measure
Statistical
power
Gen
Details
Benign
Total
Good
F1
Two F1 crosses of
populations were mildly
deleterious, compared to the
inbred parent strains
collected from <10cm and
15m apart. Convincing
evidence for mild
outbreeding depression
A panmictic population
formed from four isolated Ne
= 100 populations (at an
advanced generation) was
mildly deleterious compared
to the mean of the parent
populations, when assessed
in benign conditions, but
strongly beneficial under
stressful conditions (GR =
2.14). Other related crosses
of replicates of different Ne
treatments were also
beneficial.
Five lines subject to a single
generation of full-sib mating
had a slightly higher
average fitness than their 10
F1’s. Two other related
treatments from the same
base population with higher
F’s showed beneficial
Drosophila
melanogaster
Outbreeding
0.91
0.18
Benign
Composite
Low
>F2
Drosophila
melanogaster
Outbreeding
(but inbred
base
population)
0.98
0.25
(0.0375)a
Benign
Egg-adult
survival
Low
F1
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References
Dolgin et al.
(2007)
Woodworth et al.
(2002)
Tantawy (1957);
Falconer (1954)
Drosophila
melanogaster
Outbreeding
(but inbred
base
population)
1.00
0.51
(0.0765)a
Benign
Egg-adult
survival
Low
F1
Lymnaea
stagnalis
Mixed mating
0.86
0.0625
Benign
Composite
Low
F1
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effects of crossing. The
base population was highly
inbred (F > 0.85) before this
experiment commenced, as
it originated from a single
inseminated wild females
and was maintained with a
small population size (~ 20
pairs/generation) for ~ 6
years (~ 150 generations).
Thus, the ΔF with respect to
similar inbreeding from an
outbred base population is
effectively only ~ 0.04).
Five lines inbred by double
first-cousin mating had a
slightly lower fitness than
their 10 F1’s under benign
conditions. Another related
treatment with higher F
showed beneficial effects of
outcrossing. The base
population was already
highly inbred (F > 0.85)
before this experiment
commenced (see above).
The effective ΔF is only ~
0.08.
Six F1 crosses of four Ne = 8
bottlenecked populations
were mildly deleterious
compared to their parent
lines, but crosses of a
related treatment with Ne = 5
were beneficial compared to
Tantawy (1957);
Falconer (1954)
Coutellec &
Caquet (2011)
Musca
domestica
Outbreeding
0.95
< 0.20
Benign
Egg-adult
survival
Low
>F2
Diodia teres
Mixed mating
0.94
≥ 0.76 (FIS)
Benign
Pollination
success
Low
F1
Echinacea
angustifolia
Selfincompatible
0.89
NAb
Field
Composite
Low
F1
Viola stagnina
Mixed mating
0.91
NA
Benign
Seeds/capsule
Very low
F1
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their parent populations.
A comparison of isolated
inbred populations versus
the same sized populations
with low migration (0.025)
every generation exhibited a
slightly lower fitness in the
migration treatment at
generation 5, but a strongly
beneficial effect at
generation 24, as were both
assessments for a treatment
with a high immigration rate.
Pollination success in F1
crosses was variable, but
mildly deleterious on
average, compared to
parent populations
(variable), but composite
fitness in F2 crosses in the
field were beneficial
compared to inbred parents.
Inbred parents had slightly
higher average fitness than
their F1 but the comparison
was strongly affected by one
major outlier in within
population cross with about
double the achene count of
the next highest. Many
plants were alive but had not
yet flowered (much of the
life-cycle was not included).
Cross of two populations
had slightly lower fitness
Backus et al.
(1995); Bryant et
al. (1999)
Hereford
(2009b)
Wagenius et al.
(2010)
Eckstein & Otte
(2005)
than the F1, but this was a
very small study (9 plants),
with no information
presented on the habitats of
the populations.
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aThe
numbers in brackets are the equivalent inbreeding coefficients from similar inbreeding in an outbred base population.
not available
bInformation
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Appendix S5 Additional consideration of results
Mating system effect on genetic rescue
When mating system was tested at a finer scale, the fitness benefit was 78%
in self-incompatible species, 59% in other outbreeders, 16% in mixed mating
and 39% in selfers (Kruskall-Wallis H = 10.76, df = 3, P = 0.013). While the
latter two are in reverse order compared to expectations, the numbers of data
points were only 6 for selfing species.
Difference between F1 and F2 genetic rescue effects
An alternative explanation for F2 > F1 genetic rescue effects is that the
inbreeding levels and ΔF values might be higher for studies reporting F2 than
F1 data. This can be excluded, as differences are in the opposite direction to
this. Mean F values in inbred parental populations were 0.615 and 0.440 for
studies with F1 and F2 data, respectively, while corresponding ΔFz values
were 0.567 and 0.261.
ΔFzygotic and ΔFmaternal effects
Conclusion about the predictive power of ΔFz depended on whether
regression models fitted an intercept or not, while ∆Fm was significantly
supported irrespective of whether the single factor regressions were fitted with
an intercept, or through the origin. For both simple regressions and both AICc
model selection analyses the intercept terms were significant, so I
preferentially reported analyses with intercepts fitted, despite tests of
inbreeding effects being more powerful when regressed through the origin
(e.g. Montgomery et al. 2010).
In simple linear regressions using data set 2 with an intercept fitted, ∆Fm
was a significant predictor of ln GR for outbreeding species (Fig. 1: b = 0.563
+ 0.298, P = 0.032, n = 69), whilst ΔFz was not (b = - 0.109 + 0.177, P =
0.770, n = 68). There is much lower power associated with ∆Fm, compared to
∆Fz, as it is only F2 and later generation data (26 of 69) that have non-zero
values of ∆Fm, while all ∆Fz are > 0.
Single fitness component versus composite fitness effect
The prediction that genetic rescue effects would be greater for composite
fitness than its components was not supported in either single variables tests
(Table 1) or AICc model selection with multiple variables (Table 2). This is, at
least partially, an artefact due to a low proportion of self-incompatible species
having composite fitness data, but predominantly showing large genetic
rescue effects.
Best fitting AICc model
The best fitting model as defined by Akaike model selection in Table 2 was:
ln GR = 0.4468 + 0.587 Environment
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where environments are coded 0 benign and 1 stressful.
Effect of outbred versus inbred immigrants on genetic rescue
Gene flow from both outbred and inbred donors were beneficial (GR of 2.136
and 1.519, respectively), but the benefits were 40.6% greater with outbred
than inbred immigrants. The test for effects of outbred versus inbred
immigrants was supported by the non-parametric single variable test, but not
by either of the AICc model selections. These tests had low statistical power
as differences are only expected in F2 and later generations and there were
very few such data points for outbred immigrants beyond the F1.
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Fig. S1 Histograms of natural logarithm of genetic rescue ratio (ln GR) for
composite fitness in outbreeding species in benign versus stressful
environments. Medians for ln GR and de-transformed GR values are also
presented.
Benign
Median = 0.412
GR = 1.509
40
Percent
30
20
10
0
0
1
2
3
4
5
ln GR
335
40
Stressful
Median 0.954
GR 2.625
Percent
30
20
10
0
0
1
2
3
ln GR
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Table S4 Variables affecting the magnitude of genetic rescue for composite
fitness based on model selection statistics using the Akaike AICc procedure
on dataset 5 (n = 29). The best fitting model is bolded.
Model
C, environment,
σ2
C, ΔFm,
environment, σ2
C, ΔFm,
environment,
immigrant source,
σ2
C, ΔFm, ΔFz,
environment,
immigrant source,
σ2
C, σ2
Ki
AICc
3 - 48.090
Δi
0
wi
0.6580
4
-46.092
1.998
0.2423
5
- 43.884
4.206
0.0803
6
- 40.674
7.416
0.0161
2
- 37.439
10.661
0.0032
Ki = number of parameters estimated, AICc = Akaike’s information criteria
adjusted for small sample size, Δi = deviation of the model from the best fitting
model, and wi = Akaike weights (approximate probability that the model is the
best information theoretic one), C is the constant (intercept), ΔFm and ΔFz are
the difference in maternal and zygotic inbreeding coefficient between crossed
and inbred populations.
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Fig. S2 Funnel plot for all genetic rescue data for fitness (ln GR) from data set
1 against logarithm of the sample size weighting factor (log w) with line of best
fit inserted (the slope is non-significant).
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Table S5 Mean genetic rescue ratios (GR: F1/inbred parents) for outcrosses
of inbred parental populations for fitness traits in several domestic plant and
animal species
Species
Plants
Maize
Sorghum
Cotton
Wheat
Barley
Tomato
Animals
Poultry
Swine
GR
Trait
Mating system
Reference
2.90
2.00
1.48
1.29
1.32
1.45
grain yield
grain yield
grain yield
grain yield
grain yield
fruit yield
outcrossing
mainly selfing
selfer
selfer
selfer
selfer
Sinha & Khanna (1975)
Sinha & Khanna (1975)
Sinha & Khanna (1975)
Sinha & Khanna (1975)
Sinha & Khanna (1975)
Williams & Gilbert (1960)
1.22
eggs to
500 days
litter weight
at 154 days
outbreeding
Shoffner et al. (1966)
outbreeding
Dickerson et al. (1946)
1.79
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Appendix S6 Additional Discussion
On the basis that genetic rescue is the reversal of inbreeding depression (see
Introduction), the proportion of studies reporting beneficial effects of
outcrossing should equal the proportion of studies reporting inbreeding
depression (given similar sized studies and environmental regimes). This
prediction was supported, as 92.9% of studies herein exhibited beneficial
effects following outcrossing of inbred populations, compared to inbreeding
depression for fitness traits in 93.2% of captive mammal populations (Ralls
and Ballou 1983) and 91.2% for a broad array of animal and plant taxa in wild
environments (Crnokrak & Roff 1999).
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Appendix S7 Beneficial effects of outcrossing on evolutionary potential for
traits peripherally related to fitness
Benefits of crossing on evolutionary potential for traits peripherally related to
fitness have also been reported for sternopleural bristle number in Drosophila
(Robertson 1969; Swindell & Bouzat 2006), body weight in mice (Falconer &
King 1953; Roberts 1967 [only in a line selected for high, not in a line selected
for low weight]; Eisen 1975) and nesting-building behavior in mice (Bult &
Lynch 2000). In the Robertson (1969) study (the largest one), response to
selection in crossed lines exceeded that of the mean of the parent lines in
27/30 cases. The crosses that failed to exceed the parents in response or only
gave limited response typically involved conditions where there was little
differentiation between crossed populations and little effective augmentation
of genetic diversity, as expected.
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Appendix S8 Additional discussion of genetic rescue guidelines
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(i)
Jonathan D. Ballou and Robert C. Lacy (pers. comm.) are currently working
on means for managing gene flow in fragmented populations.
My guidelines for genetic rescue are less stringent, than those of
Edmands (2007) and Hedrick and Fredrickson (2010), due to:
the urgency to act promptly, as conservation biology is a crisis
discipline (Soulé 1985) where inaction is often a recipe for further
decline and extinction of threatened populations for genetic and nongenetic reasons,
(ii)
the ubiquity of inbreeding depression in adequately studied naturally
outbreeding diploid species, due to either recent matings between
relatives, and/or longer term genetic drift effects due to increase in
frequency and fixation of deleterious alleles plus fixation of alleles at
loci exhibiting heterozygote advantage (the latter issues are also
referred to as increased genetic load) (Lacy 1997; Frankham et al.
2014),
(iii)
the low power of most experiments on threatened populations to
detect inbreeding or outbreeding depression, even if it truly exists (e.g.
Lacy 1997; Kalinowski & Hedrick 1999), while meta-analyses will
usually give a more reliable overview of likely effects. For example,
Ralls & Ballou (1983) reported that 41/44 mammal populations had
high juvenile mortality for inbred than outbred progeny, but only 34%
of the comparisons were significantly different. Further, 90% of the
valid data sets in the Crnokrak & Roff (1999) meta-analysis indicated
that inbreeding reduced means, but only 53% were significant.
(iv) the low power of experiments on genetic rescue of threatened,
populations in captivity, the long-time involved and possible difficulties
in getting permission to do experiments on them. First, an experiment
in captivity would likely involve only a single replicate with low sample
sizes and would likely yield a lower benefit or disadvantage than in
wild conditions. Second, this approach is not feasible for species that
have not been successfully bred in captivity (e.g. northern hairy-nosed
wombats). Third, to be convincing the experiment would need to go to
at least the F3 generation (Appendix S2) and to encompass the full life
cycle for that generation, leading to substantial delays during which
the wild population may well be extirpated. This would not be feasible
in large long-lived species such as elephants, or long-lived trees
where > 100 years would be required,
(v)
the development of effective means to predict the risk of outbreeding
depression (Frankham et al. 2011), and
(vi) evidence of consistent and highly beneficial effects of outcrossing on
fitness and evolutionary potential documented herein.
Edmands (2007) recommended that genetic rescue only proceed when there
is clear evidence of inbreeding depression and where evaluations have
already been done of crosses over two generations (wherever possible). I
disagree with these recommendations for all five of the reasons above.
Edmands (2007) also recommended that the population(s) chosen for
outcrossing be as similar genetically and adaptively as possible. I agree with
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the need for adaptive similarity (Frankham et al. 2011), but query the
requirement for genetic similarity, as theory predicts that the benefits of
outcrossing increase with differences in allele frequencies between target and
donor populations (Appendix S1).
My guidelines are closer to those of Hedrick & Fredrickson (2010) but
also less stringent than theirs. For example, I have stronger views about the
urgency of action to avoid population extinction, and do not require
experimental data from captive populations prior to proceeding, as
outcrossing of inbred populations is consistently beneficial in such species as
shown herein. I also place more emphasis on the mating system and modes
of inheritance of the species involved.
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