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Anhang 4 zu Schlussbericht GZA – Teilproject C 1 Unpubliziertes Manuskript (bitte vertraulich behandeln) 2
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Tolerance against pathogen-induced stress: no hybrid vigor, but genetic and maternal 4
environmental effects vary with embryo developmental stage 5
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Emily S. Clark*§, Adin Ross-Gillespie§, Rike B. Stelkens+, & Claus Wedekind§ 8
§ Department of Ecology and Evolution, Biophore, University of Lausanne, 1015, Lausanne, 9
Switzerland, + Institute of Integrative Biology, University of Liverpool, Liverpool L69 7ZB, 10
UK 11
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* Tel: +41 21 692 42 49; Fax: +41 21 692 42 65; [email protected] 13
Tel: +41 21 692 42 49; Fax: +41 21 692 42 65; [email protected] 14
Tel: +44 151 795 4528; Fax: 0044 151 795 4408; [email protected] 15
Tel: 41 21 692 42 50; Fax: +41 21 692 42 65; [email protected] 16
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Abstract 18
Salmonids are in decline worldwide, and like any threatened species, their survival is 19
dependent on their ability to respond quickly to environmental change. Phenotypic plasticity 20
can, to some extent, increase tolerance to heterogeneous environments; however, the 21
elevations and slopes of reaction norms are often population-specific, and disruption, via 22
stocking or interbreeding, can lower fitness. We investigated the effects of population 23
mixing in brown trout. Five genetically distinct populations were crossed in a full-factorial 24
design, and resulting embryos were challenged with the opportunistic pathogen, P. 25
fluorescens. By virtue of our design, we were able to disentangle interbreeding effects from 26
sire and dam effects on early life-history traits. We found the bacterium did not increase 27
mortality, but decreased fitness by delaying hatching, as well as dwarfing larval length and 28
reducing yolk sac reserves. Contrary to expectations, hybrids did not differ in phenotypic 29
means or reaction norms in comparison to pure population crosses, and genetic variability in 30
traits remained stable across environments. While our findings indicate that interbreeding 31
had neutral effects on offspring fitness, with respect to the examined traits, further 32
investigation of later developmental stages is warranted. Moreover, our results suggest that 33
the impact of stress on the expression of genetic variability is likely dependent on the trait 34
and stressor in question. 35
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Keywords: Salmo trutta, Pseudomonas sp., plasticity, reaction norms, hybridization, additive 37
genetic variation, quantitative genetics 38
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Introduction 39
The ability for a genotype to adopt different phenotypes according to environmental 40
condition permits organisms to maximize fitness in the face of heterogeneous biotic and 41
abiotic risks (Pigliucci 2001). As natural populations are increasingly exposed to habit-42
altering anthropogenic activities (Kinnison et al. 2008; Smith and Bernatchez 2008), this 43
plasticity can be a key factor in increasing tolerance to environmental change (Via et al. 44
1995). The capacity of such traits to evolve in a population relies on the persistence of 45
heritable variation therein (Schlichting and Pigliucci 1998). While studies in both the 46
laboratory and the wild have demonstrated significant genetic variation in both trait means 47
and reaction norms (Stinchcombe et al. 2004; Nussey et al. 2005; Hansen et al. 2008), 48
environmental stress can affect the genetic organization, at times resulting in reduced 49
expression of additive genetic variance (Merilä 1997; Laugen et al. 2005). Notably, the 50
impact of stress on trait heritability is not unidirectional, with studies also showing that 51
genetic variance can increase (Hoffmann and Merilä 1999; Agrawal et al. 2002; Relyea 52
2005), or remain stable (Merilä and Fry 1998; Pakkasmaa et al. 2003; Merilä et al. 2004) 53
across environments. 54
Taken together, there appears to be no clear consensus on how environmental change 55
affects genetic variability in quantitative traits, with indications that it is not only trait-56
dependent, but also reliant on the stressor in question. To add an additional level of 57
complexity, the effect of ecological stressors on the genetic variability of plastic traits cannot 58
be generalized for a species. Rather, populations often diverge in the genetic architecture of 59
traits and trait plasticities, as a result of selective pressures varying in type and intensity over 60
space and time (for examples see Laurila et al. 2002; Jensen et al. 2008). This divergence can 61
indicate local adaptation (Hutchings et al. 2007), and as such, changes to the elevation and/or 62
slopes of the reaction norms can have negative effects on fitness. Events including 63
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intrapopulation hybridization can bring about such alterations (Fraser et al. 2008; Piché et al. 64
2008; Darwish and Hutchings 2009). This may be attributed to that fact that interbreeding 65
can disrupt co-adapted gene complexes (i.e. via segregation and recombination), modify 66
interactions between genes and the environment, and combine novel groups of mutations 67
(Edmands 2007). 68
In this context, we wished to investigate how interbreeding in a salmonid would affect 69
the expression and plasticity of early life-history traits. Interbreeding occurs more commonly 70
in fish than any other vertebrate taxa (Leary et al. 1995), and frequently arises in salmonids 71
because of stocking and infiltration of wild populations with farmed animals (Araki et al. 72
2007; Fraser et al. 2008). This mixing can result in hybrids with maladapted genes and lower 73
fitness (McGinnity et al. 2003; Muhlfeld et al. 2009). As our study organism we chose the 74
brown trout (Salmo trutta), a species which has complex population structures and is 75
characterized by vast diversity in terms of both phenotype (Hermida et al. 2009) and life 76
history strategies (Nielsen et al. 2003). Moreover, Stelkens et al. (in press) recently 77
demonstrated that significant genetic differentiation can occur in brown trout on a 78
microgeographic scale. 79
For our study, we conducted full-factorial in vitro fertilizations between five 80
genetically distinct populations of brown trout (described in Stelkens et al. in press). Since 81
environmental changes arising from human activities are predicted to result in increased 82
occurrences of infectious disease (Daszak 2000; Dobson and Foufopoulos 2001; Harvell et al. 83
2002), and have already been linked to declines in salmonids (Krkosek et al. 2006), we chose 84
to create different ecologically-relevant situations by inoculating a subset of embryos with 85
the opportunistic pathogen, P. fluorescens (Wedekind 2002; von Siebenthal et al. 2009). Our 86
experimental design allowed us to assess how bacterial challenge affected a suite of fitness-87
related traits in trout embryos, and determine whether population crossing impacted 88
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phenotypic means and the norms of reaction. Moreover, as we were effectively able 89
disentangle interbreeding effects from sire and dam effects on offspring phenotype, we could 90
globally assess if the pathogen stress changed the genetic organization of different early life-91
history traits. 92
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Methods and Materials 94
Artificial fertilizations and rearing of brown trout embryos 95
Adult brown trout were caught by electro-fishing from five tributaries of the river Aare 96
(Figure 1) in the Canton of Bern, Switzerland shortly before spawning season in November 97
2009, and were kept in the Reutigen hatchery until maturation. Four females and four males 98
from each of the five populations was randomly selected, weighed, measured (total length), 99
and stripped of their gametes. Gametes from the different populations were crossed full-100
factorially in a block design. Specifically, five females (one from each population) were each 101
crossed with five males from each tributary, and this was replicated four times (i.e. four 102
blocks), yielding 100 full sibships. Resulting embryos were transported back to the 103
laboratory, washed as described in von Siebenthal et al. (2009), and distributed singly to 24-104
well plates (Falcon, Becton-Dickonson), filled with 2ml of sterile standardized water per well 105
(see OECD guidelines: OECD 1992). Distributions were perfomed such that one plate 106
contained eggs from all four females in one population, each crossed with males of the five 107
populations. A set of five plates, therefore, contained all sibling combinations. This was 108
replicated 50 times, resulting in 250 plates with 5000 embryos. Embryos were stored in a 109
6.5oC climate chamber and were examined weekly with a light table (Hama professional, LP 110
555) and a stereo zoom microscrope (Olympus SZX9) until the beginning of hatching, at 111
which point they were monitored daily. 112
Preparation of bacterial inoculum and infections 113
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At 177 degree days (DD) post-fertilization, a strain of P. fluorescens, which was isolated 114
from whitefish gills and had proven deleterious to their embryos (Clark et al. in preparation), 115
was inoculated into two flasks containing 100 ml of nutrient broth (5g bacto-peptone and 3g 116
meat extract per liter of distilled water; Fluka Chemie). Cultures were incubated for 36 hours 117
at 22 oC until reaching exponential growth phase. Cultures were then pelleted at 4000 rpm 118
and washed three times with sterile standardized water (ssH2O). Pellets were pooled and 119
resuspended in 50 ml of ssH2O. Bacterial densities were calculated using a Helber counting 120
chamber and examined at 400X on a phase-contract microscope (Olympus CX41). The P. 121
fluorescens culture was then diluted, so that an inoculation of 100µl would result in a 122
concentration of 108 bacterial cells per ml in each well. Nine replicates per sibship were 123
treated with the bacterial solution, while another 12 served as controls, and accordingly 124
received 100µl of sterile standardized water. The remaining replicates were used for another 125
experimental setup. 126
Measurements of length and yolk sac volume 127
Each trout was photographed on the day of hatching with an Olympus C-5060 and was 128
subsequently measured using ImageJ ( http://rsb.info.nih.gov/ij/ ). Standard length was 129
measured, as well as the length and width of the yolk sac. The volume of the latter was 130
calculated as in Jensen et al. (2008). While measuring, the relative quality of the image was 131
also scored, and those with the lowest resolution were excluded from the analysis. 132
Statistical analysis 133
Survival was analyzed as a binomial response variable in general linear mixed effect 134
models (GLMM), and hatching age, hatchling size, and yolk sac volumes as continuous 135
response variables in linear mixed effect models (LMM). All analyses were conducted in R 136
(R Development Core Team 2011) using the lme4 package (Bates et al. 2011). Treatment 137
and population cross type (factor with two levels, i.e. mixed or pure) were entered as a fixed 138
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effects, while sire, dam, sire x dam interactions, and crossing block were entered as random 139
effects. For hatchling size and yolk sac volumes, image quality was also added as a random 140
effect, as it appeared to account for a significant part of variation in these measurements. To 141
assess the importance of each effect, a reference model including all relevant terms was 142
compared to a model lacking the term of interest. To investigate the importance of 143
interactions, a model incorporating the interaction term was compared to the reference model. 144
Likelihood ratio tests (LRT) were used to compare model fits. 145
Variance components were extracted from the mixed effect models and used to 146
calculate the components of phenotypic variation (Lynch and Walsh 1998). Assuming that 147
epistatic effects are negligible, additive genetic variance (VA) can be calculated as 4x the sire 148
component of variation (VS). Dominance genetic variance (VD) were calculated as 4x the sxd 149
component. Maternal environmental variance was estimated as VM = VDam – VS. Residual 150
variance included environmental variance as well as ½ VA and ¾ VD (Laurila et al. 2002). 151
Narrow-sense heritability estimates were calculated as in Lynch and Walsh (1998) and 152
coefficients of additive genetic variation (CVA) as in Houle (1992). In the case of yolk sac 153
measurements, the CVA was divided by three to account for the dimensionality of the 154
measurement (Houle 1992). Cross-environmental trait correlations were calculated using 155
paternal sibgroup means and Pearson’s product moment correlations. Using the family-mean 156
approach to estimate genetic correlations provides a conservative test of whether the 157
correlation coefficient is significantly different from zero, with the added benefit that the 158
correlation cannot exceed ±1 (for discussion see: Lynch and Walsh 1998). Pearson’s product 159
moment correlations were also used to examine the relationship between egg size and 160
maternal sibgroup trait means. 161
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Results 163
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Mean hatching success (±SE) in P. fluorescens-treated embryos (97.7 ± 0.5%) was not 164
significantly lower than the control (98.2 ± 0.4%) (GLMM: Z = -0.5, p = 0.59). On the other 165
hand, treatment did significantly delay hatching time, and was associated with smaller larvae 166
with reduced yolk sac volumes (Figure 2; Table 1). 167
Population cross type, i.e. pure or mixed, was not found to have a significant effect on 168
time to hatching in either the control (LRT: χ2 = 2.3, p = 0.13) or the treated group (LRT: χ2 169
= 0.45, p = 0.50). Similarly, population cross was not important in terms of hatching size or 170
yolk sac volume in neither the control (LRT: χ2 = 0.06, p = 0.80; χ2 = 0.20, p = 0.16) nor the 171
P. fluorescens treatment (LRT: χ2 = 0.11, p = 0.73; χ2 = 2.9, p = 0.09). We also did not find 172
any indication of an interaction between population cross and treatment for any trait (Table 1, 173
Figure 3). 174
Dam effects were significant across treatments for every examined trait (Table 2). 175
Sire effects also accounted for significant variation in all traits and treatments (Table 2). 176
Additive genetic variance tended to be slightly reduced in the pathogen treatment for 177
hatching time and length. Dominance interaction effects never accounted for an important 178
amount of variation. Heritability of hatching time was moderate to high, while that of the 179
other early life history traits was low. 180
We observed significant genetic variation for hatching plasticity, as indicated by the s 181
x t interaction (Table 1; Figure 3). No genetic variation for length or yolk sac reaction norms 182
was found (Table 1). Treatment x dam effects were evident for hatching time and hatchling 183
length, suggesting an interaction between maternal factors and treatment. The three-way 184
interaction (t x s x d) was significant only for hatching time. 185
Egg size was not correlated to hatching time in either treatment (p always > 0.05). 186
Egg size was also not correlated to hatchling length in the control (rp = 0.31, p = 0.19), but 187
was in the pathogen treatment (rp = 0.45, p = 0.05). Egg size was always positively 188
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correlated to yolk sac volume (control: rp = 0.93, p < 0.001; P. fluorescens: rp = 0.92, p < 189
0.001). Hatching time was positively correlated across treatments (rp = 0.81, p < 0.001), as 190
was hatchling length (rp = 0.90, p < 0.001) and yolk sac volume (rp = 0.92, p < 0.001). 191
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Discussion 193
We have used a full factorial breeding approach between five populations of brown trout to 194
investigate how interbreeding affects the expression of early life history traits across 195
environments. Moreover, by virtue of our design, we were able disentangle population 196
crossing effects from sire and dam effects, and examine how pathogen stress influences the 197
genetic organization of fitness-related traits. 198
Treatment effects on early life-history traits 199
We found that inoculation of brown trout embryos with P. fluorescens did not 200
increase mortality. In contrast, treatment with other strains of this bacterium was previously 201
found to cause embryonic mortality in another salmonid (Coregonus sp.) (Wedekind et al. 202
2004; von Siebenthal et al. 2009). Notably, pathogen virulence is strain specific (e.g. Forbes 203
et al. 2008; Byrne 2010; Garigliany et al. 2010). Moreover, the studies on whitefish 204
described infections during later stages of embryonic development, and susceptibility is often 205
age-dependent (Schotthoefer et al. 2003; Sollid et al. 2003; Ryce et al. 2005; Kelly et al. 206
2010; Johnson et al. 2011), possibly due to changes in host resistance to infection and/or 207
tolerance to pathologies (Rohr et al. 2010). 208
While inoculation did not increase mortality, it did delay hatching time and result in 209
smaller hatchlings with reduced yolk sac volumes. Given that these traits are plastic, the 210
phenotype which best fits the environment should, in theory, be expressed (Pigliucci 2001). 211
Hatching time may be induced or delayed depending on whether the risk is specific to eggs or 212
larvae (Warkentin 2011), and morphological traits can tailored to maximize fitness in 213
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accordance to the ecological stressor (Relyea 2005); however, the plasticity that we observed 214
is most likely not adaptive. Late hatching is often selected against in salmonids, as it delays 215
access to feeding territories (Einum and Fleming 2000). Moreover, mortality during early 216
life stages is size-selective, with larger fry being more resistant to starvation, and better able 217
to evade predators and hunt larger prey items (Einum and Fleming 1999; Jensen et al. 2008). 218
The changes in phenotypes are, therefore, probably ‘negative direct effects’ (Gotthard and 219
Nylin 1995) of infection, resulting from physiological constraints on trait expression (Nussey 220
et al. 2007). Indeed, the reduced size of the larvae may reflect increased metabolic demands 221
associated with an immune response (Uller et al. 2009), i.e. proteins in the yolk sac, e.g. 222
antibodies, that could have served as sources of nutrition were instead used to fight infection 223
(Uribe et al. 2011). 224
Effects of population mixing on fitness 225
We found that interbreeding between the five populations of brown trout had no apparent 226
effect on fitness-related traits in terms of either phenotypic means or reaction norms. In 227
contrast, Darwish and Hutchings (2009) found significant changes in life-history reaction 228
norms in Atlantic salmon (Salmo salar) when individuals were crossed either with members 229
of another wild population, or those belonging to captive populations. Similarly, Fraser et al. 230
(2008) observed that hybridization between wild and farmed Atlantic salmon resulted in 231
decreased survival at low pH and maladaptive changes in the reaction norms. 232
A few factors may explain the general uniformity between pure and mixed population 233
crosses in their reaction to the pathogen stressor. First, the overall genetic differentiation 234
among the five populations was moderate, which is expected as all originated from the same 235
river catchment (Stelkens et al. in press). While interbreeding between populations with few 236
genetic differences can be sufficient to substantially reduce vigor (Goldberg et al. 2005), 237
hybrid fitness is generally expected to decrease with increasing population divergence 238
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(Edmands 2002). Second, our study assessed the impact of population mixing on early life-239
history traits in F1 crosses, and decreased fitness is often more apparent in or following the 240
F2 generation, as noxious interactions between homozygous loci become evident (Edmands 241
2007). Thirdly, although interpopulation crossing did not impact fitness-related traits during 242
the time points that we examined, it is possible that it could become influential at later 243
developmental stages (McGinnity et al. 2003) 244
Genetic organization of early life-history traits across environments 245
Time to hatching, hatchling length, and yolk sac reserves are all traits that are tightly linked 246
to fitness, and as such, they are expected have reduced genetic variation because of 247
directional selection (Mousseau and Roff 1987). The genetic variability in these traits is 248
instead anticipated to be largely maintained by dominance interaction effects (Roff 1997). 249
However, we found little evidence of nonadditive genetic variance, and rather observed that 250
these traits harbored significant additive genetic variance. A number of other studies have 251
also noted significant genetic variability in fitness traits (e.g. Houle 1992; Laurila et al. 252
2002). Comparatively, both hatchling length and yolk sac volume appeared to have lower 253
heritabilities than hatching time; however, this seemed attributable to the larger residual 254
variances in these traits—a factor that often leads to the underestimation of the amount of 255
genetic variability in a character (Merilä and Sheldon 1999). 256
Interestingly, we found no evidence of stress-dependent effects on the expression of 257
genetic variability in any of the traits, despite the fact that treatment resulted in significant 258
changes in phenotype. Our findings are consistent with other studies that have found no 259
pronounced effect of stress on the genetic organization of traits (Bubliy et al. 2001; 260
Pakkasmaa et al. 2003). Notably, stress-dependent changes on additive genetic variation are 261
common (Hoffmann and Merilä 1999), so our results simply highlight that fact that the effect 262
may be dependent on both the trait in question, as well as the stressor. 263
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Like additive genetic variance, maternal effects were also consistently significant, 264
which is to be expected for early life-history traits (Heath et al. 1999). Notably, their 265
magnitudes appeared smaller than that of genetic effects for hatching time, were comparable 266
for hatchling length, and were much larger for yolk sac volume, suggesting that their relative 267
importance was somewhat trait-dependent. In the case of hatching age, the maternal effects 268
appeared largely independent of egg size. On the contrary, egg size was highly correlated 269
with yolk sac reserves across environments, as well as hatchling length in the pathogen 270
treatment. Egg size, while not always an indicator of quality (Laugen et al. 2005), has been 271
linked to increased fitness (i.e. survival and growth) in Chinook salmon (Oncohynchus 272
tshawytscha) and brown trout (Einum and Fleming 1999). The consequences of maternal 273
effects also appeared to vary according to the treatment for hatching time and hatchling 274
length, as suggested by the dam by treatment effects. Einum and Fleming (1999) similarly 275
demonstrated that adaptive value of maternal traits can change with the environment. 276
Genetic variation for trait plasticity and cross environment correlations 277
Although the plastic responses we observed after pathogen challenge may not have been 278
strictly adaptive, this does not exclude the possibility that trait plasticities are beneficial. For 279
instance, certain genotypes may be better adapted to the stressor and more capable of 280
achieving optimal phenotypes (Gotthard and Nylin 1995). As in other studies on plasticity in 281
salmonids (reviewed in: Hutchings 2011), we found evidence of genetic variation for 282
hatching age reaction norms; however, we found no such indication for hatchling length or 283
yolk sac volume. At the same time, we found that all traits in question were correlated across 284
environments. Cross-environmental correlations imply that trait expression is mediated by 285
the same loci in both settings (Via 1984). Consequently, traits cannot evolve independently, 286
and the evolutionary potential of the reaction norm is constrained. 287
288
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Conclusions 289
Treatment of brown trout embryos with P. fluorescens did not increase embryonic mortality, 290
but did decrease fitness in that it delayed hatching time, and resulting in smaller larvae with 291
diminished yolk sac reserves. Our results, therefore, indicate that a multi-trait approach may 292
be necessary in assessing the virulence of a given pathogen. Contrary to expectations, we 293
also observed that interbreeding did not appear to decrease fitness. However, we do not 294
wish to suggest that population mixing is always benign, as deleterious effects many only 295
come to light at later developmental stages. Finally, while we did not find evidence of stress-296
dependent changes in the expression of genetic variability, this effect may be contingent on 297
both the trait and stress in question. 298
299
Acknowledgements 300
We would like to thank the Fischereiinspektorat Bern for their permissions and support, 301
including U. Gutmann, J. Gutruf, C. Küng, M. Schmid and H. Walther. We also wish to 302
acknowledge E. Baumgartner, A. Bréchon, M. dos Santos, L. Kocjancic-Curty, L. Müller, R. 303
Nicolet, M. Pompini, and L. Wilkins for help in the field and/or useful discussions. This 304
project was funded by the Swiss National Science Foundation. 305
306
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477
478
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Figure Legends 479
Figure 1. Locations of the five study populations in the Aare River catchment (adapted from 480
Stelkens et al. in press) 481
Figure 2. Mean time to hatching (A), larvae length, and yolk sac volume (B) (±SE) by 482
treatment. In panel B, dark grey corresponds to larval length, and light grey to yolk sac 483
volume. 484
Figure 3. Reaction norm plots of hatching time, larvae length, and yolk sac volume. In the 485
upper panel, lines correspond to sire means. Lines in the lower panel represent means (±SD) 486
per pure population cross (black) or mixed cross (light grey). 487
22
Figure 1 488
489 !
23
Figure 2 490
491
456 458 460 462 464 466 468 470 472 474 476 478
Control P. fluorescens
Deg
ree
Day
s to
Hat
chin
g
50
51
52
53
54
55
56
0.8
0.85
0.9
0.95
1
1.05
1.1
1.15
1.2
1.25
Control P. fluorescens Le
ngth
(cm
)
Yolk
sac
vol
ume
(mm
3 )
A B
24
Figure 3 492
493
25
Table 1. Likelihood ratio tests on mixed model logistic regression on plastic traits. Reference 494
models are indicated in bold. 495
Model Effect tested AIC Χ2 p
a) Hatching time
s + d + sxd 15750
t + s + d + sxd t 15213 539.2 < 0.001
t*p + s + d + sxd t x p 15214 2.8 0.24
t + t|s + d + sxd t x s 15203 14.1 < 0.001
t + s + t|d + sxd t x d 15182 35.3 < 0.001
t + s + d + t|sxd t x s x d 15188 29.0 < 0.001
b) Length
s + d + sxd -2962.8
t + s + d + sxd t -3154.1 193.3 <0.001
t*p + s + d + sxd t x p -3150.2 0.2 0.90
t + t|s + d + sxd t x s -3150.1 0.1 0.96
t + s + t|d +sxd t x d -3168.5 18.4 < 0.001
t + s + d + t|sxd t x s x d -3150.1 0 1
b) Yolk sac volume
s + d + sxd 9677.7
t + s + d + sxd t 9669.2 10.5 0.001
t*p + s + d + sxd t x p 9669.3 3.9 0.14
t + t|s + d + sxd t x s 9672.2 1.0 0.62
t + s + t|d + sxd t x d 9672.7 0.5 0.78
t + s + d + t|sxd t x s x d 9673.2 0 1
t: treatment; p: population cross; s: sire; d: dam 496
26
Table 2. REML estimates of variance components (VA: additive genetic; VDam: dam; VM: 497
maternal environmental; VD: dominance genetic; VRes: residual) for hatching time, larval 498
length, and yolk sac volume for each treatment. Heritabilities and coefficients of additive 499
genetic variation (CVA) are provided. 500
Hatching Time Length Yolk Sac Volume
Control PF Control PF Control PF
VA 74.8*** 45.6*** 0.002*** 0.001** 4.8* 5.8**
VD 5.2 0 0 0 0 4.4
VDam 58.9*** 36.3*** 0.002*** 0.001*** 172.5*** 164.3***
VM 40.2 24.9 0.002 0.001 171.3 162.8
VBlock 0 12.8 0.0003 0.0005 17.0 26.7
VResidual 105.1 92.6 0.01 0.01 49.4 37.1
h2 0.40 0.30 0.13 0.07 0.02 0.03
CVA 1.9 1.4 3.7 2.8 1.3 1.5
*** p < 0.001, ** p < 0.01, * p < 0.05, + p < 0.10 501
502