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Cryopreservation of Prunus padus L. seeds: emphasising
the significance of Bayesian methods for data analysis
Journal: Canadian Journal of Forest Research
Manuscript ID cjfr-2016-0020.R1
Manuscript Type: Article
Date Submitted by the Author: 20-Mar-2016
Complete List of Authors: Popova, Elena; University of Guelph, Department of Plant Agriculture Moltchanova, Elena; University of Canterbury, 2 School of Mathematics and Statistics Han, Sim Hee; Korea Forest Research Institute, Division of Forest Genetic Resources Saxena, Praveen; University of Guelph, Plant Agriculture
Kim, Du Hyun; DongA University, Department of Genetic Engineering
Keyword: cryopreservation, Prunus padus, hydration window, Bayesian statistics, seed cryopreservation
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Cryopreservation of Prunus padus L. seeds: emphasising the significance 1
of Bayesian methods for data analysis 2
3
Elena Popova1, Elena Moltchanova
2 , Sim Hee Han
3, Praveen Saxena
1, Du Hyun Kim
4* 4
1 Gosling Research Institute for Plant Preservation (GRIPP), Department of Plant Agriculture, 5
University of Guelph, Guelph N1G 2W1, Ontario, Canada 6
2 School of Mathematics and Statistics, University of Canterbury, Christchurch 8041, New 7
Zealand 8
3 Department of Forest Genetic Resources, National Institute of Forest Science, Suwon 16631, 9
Republic of Korea. 10
4 Department of Life Resources Industry, Dong-A University, Busan 49315, Republic of 11
Korea 12
* Corresponding author. E-mail: [email protected] 13
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Abstract 14
Conservation of Prunus padus L., a tree of high ecological and pharmacological importance, has been 15
evaluated by storing seeds at subzero (-20°C, -80°C) and cryogenic (-196°C) temperatures for various 16
durations. The effect of seeds water content (WC) ranging from 3.5 to 21.1%, fresh weight basis, as 17
well as the effect of cooling and rewarming procedure on seed viability was investigated. Emergence 18
of seedlings was observed for 40-55% non-cryopreserved seeds with no significant effect of WC. 19
The same seedling emergence was recorded for seeds cryopreserved by direct immersion in liquid 20
nitrogen within the WC range between 3.5 and 15.0%. Seeds rehydrated above 17% WC were unable 21
to tolerate cryopreservation. Seedling emergence was not affected by cooling regime but decreased by 22
10% after step-wise rewarming compared to rapid rewarming in a water bath or on air. No reduction 23
in seedling emergence was recorded after storage at -20°C, -80°C and -196°C for 1h, 1 week and 1 24
month. We recommend seed storage at subzero or cryogenic temperatures as an effective conservation 25
option for P. padus and possibly other Prunus species. We also demonstrated high effectiveness and 26
reliability of Bayesian statistical methods for analyzing binomial data, such as the data obtained in 27
seed conservation experiments. 28
29
Keywords: Bayesian statistics, hydration window, Prunus padus, seed cryopreservation, water 30
content. 31
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Introduction 32
Rapid increase in human populations in the past decades accompanied by dramatic ecological changes 33
has been the cause of enormous worldwide depletion of plant biodiversity (Wang et al. 2014). Ex situ 34
conservation of orthodox seeds dried to 3–7 % water content (WC) at low temperature (-18 to -22°C) 35
is one of the most effective means of preserving diverse plant species (Pritchard and Nadarajan 2008). 36
However, recent studies have shown that sub-orthodox, or short-lived, seeds can age quicker in seed 37
banks than predicted from seed viability equations (Pritchard and Dickie 2003). Abnormal storage 38
behavior and high variations in desiccation tolerance has been recorded for large seeds with stone-like 39
endocarp and high lipid content such as in the genus Prunus (Chmielarz 2009b; Michalak et al. 40
2015b). 41
Prunus padus, or bird cherry, is considered ecologically important in Europe and Western and 42
Central Asia as it provides an early source of nectar and pollen for bees, while the cherries are eaten 43
by birds and mammals (Uusitalo 2004). Mature trees are valued for their attractive scented flowers 44
and dark-colored bark and are often planted for ornamental purpose. The plant is a potential source of 45
amygdalin, a cyanogenic diglucoside with a strong anticancer activity (Frank and Santamour 1998). In 46
contrast to the majority of cultivated Prunus genotypes, the need for conserving wild Prunus species 47
has been often neglected, while the loss of genetic diversity within these species continues to diminish 48
the genetic base on which breeding programmes depend (Vujović et al. 2015). In nature, seeds of 49
wild Prunus species remain viable for at least two years. However, recent studies recorded a marked 50
decline in viability from 79 % of one-year-old seeds to 27 % of two-year old seeds which caused their 51
erosion from soil seed banks (Flagstad et al. 2010). Therefore several researchers advocated the 52
necessity of conserving Prunus genetic material in ex situ genetic banks (Towill and Forsline 1999; 53
De Boucaud et al. 2002; Chmielarz 2009b; Cheong 2012; Michalak et al. 2015b; Vujović et al. 2015). 54
The research on ex situ storage behaviour of P. padus seeds and their longevity at different 55
storage regimes is fragmented. In Seed Information Database (SID 2015) of the Royal Botanic 56
Gardens, Kew the bird cherry seeds are referred to as orthodox. Gordon and Rowe (1982) 57
recommended 3°-5°C and 12 % water content (WC, fresh weight basis) as the conditions for their 58
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medium-term storage. Seeds of a related species Prunus avium (mazzard cherry) tolerated drying to 9-59
11 % WC followed by 3 years of storage at -1 to 3°C without a considerable loss of viability (Suszka 60
et al. 1996). However, storage behavior of Prunus padus seeds and their tolerance to subzero and 61
cryogenic temperatures have not been investigated. 62
Cryopreservation in liquid nitrogen (LN, -196°C) or its vapour phase (-160 ‒ -180°C) is an 63
alternative and potentially very effective method for the long-term storage of biological samples of 64
plant origin (Wang et al. 2014). At cryogenic temperatures, nearly all cell division and metabolic 65
activities of cells are arrested and the plant materials remain viable for much longer durations than at 66
any other storage regime (Walters et al. 2004). Consequently, cryopreservation may be of particular 67
importance for the long-term (10-100s years) storage of otherwise inherently short-lived orthodox 68
seeds and seeds with high lipid content (Pritchard and Nadarajan 2008; Popova et al. 2013; Michalak 69
et al. 2013). During the past decade, cryopreservation has been successfully tested for seeds of 70
important trees such as silver birch (Ryynänen and Aronen 2005; Chmielarz 2010a), ash (Chmielarz 71
2009a), elms (Harvengt et al. 2004; Chmielarz 2010b), European chestnut and cork oak (Vidal et al. 72
2010), willows and poplars (Popova et al. 2012; 2013; Michalak et al. 2013; 2015a), and others (see 73
Häggman et al. 2008 for a review). However, the possibility of cryogenic storage of P. padus seeds 74
remains to be evaluated. . 75
The key to successful cryopreservation of seeds is identification of the “hydration window”, 76
i.e. the safe range of water content at which seeds can be exposed to cryogenic temperatures without 77
decreasing their viability (Daws and Pritchard 2008). For Prunus species information on hydration 78
window for seed cryopreservation is scarce and often controversial. For example, seeds of Prunus 79
avium showed ca. 25% seedling emergence only if cryopreserved within a safe WC range of 9-16.9 % 80
(Chmielarz 2009b). Cryopreservation of seeds hydrated to WC above this level resulted in complete 81
loose of germination (Chmielarz 2009b). However, Michalak et al. (2015b) reported that seeds of this 82
species could tolerate cryopreservation at higher WC (ca. 20%) with seedling emergence of 47 to 83
57%, depending on seed provenance. By contrast, desiccation of seeds to WC ranging from 7.6 to 84
10.9% significantly reduced seedling emergence in both control and cryopreserved seeds (Michalak et 85
al. 2015b). In addition, the regimes of cooling and rewarming may significantly affect viability of 86
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lipid-rich seeds after cryopreservation (Dussert and Engelmann 2006). In this study we investigated 87
various temperature regimes and duration of storage to recommend efficient options for conservation 88
of P. padus seeds. The also determined, for the first time, the safe seed WC range and the effect of 89
different regimes of cooling and rewarming oncryopreservation of P. padus seeds and subsequent 90
seedling development. 91
Development of effective conservation programmes is commonly based on quantitative data 92
from scientific experiments and/or observations. Thus, the statistical methods of data analysis have a 93
significant impact on the decision making in developing conservation strategies, particularly when the 94
decisions are made under conditions of uncertainty, lack of observations or unknown interactions 95
between various factors (Ellison 1996; Marin et al. 2003; Muthusamy et al. 2005). Application of 96
Bayesian statistical methods for analysing data from biological experiments is increasing (Olge and 97
Barber 2008) due to their flexibility and success in resolving problems associated with classical 98
arcsine transformation required by ANOVA. Such problems include significant loss of information, 99
lack of interpretability and failure to guarantee normality and homoscedasticity (Warton and Hui 100
2011). In this communication we demonstrate successful application of Bayesian statistical methods 101
in the analysis of data from experiments in seed conservation research using Prunus padus as a model 102
species. 103
104
Materials and Methods 105
Conservation of Prunus padus seeds 106
Plant material 107
Mature seeds of Prunus padus L. were collected mid-September, 2011 from eight open-pollinated 108
trees of the same population in Chungcheongbuk-do province, Republic of Korea. Collected seed 109
were soaked in tap water to soften fruits. After fruits were removed and floating seeds and pulp 110
fragments were discarded, clean seeds were air-dried at room temperature in darkness. Dry seeds 111
with ca. 12 % WC were mixed together, packed in a plastic container and stored in the refrigerator at 5 112
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± 1°C for two months before the experiments. All experiments and water content measurements were 113
performed on seeds with the endocarp. 114
Water content of seeds 115
To determine the water content, 30 seeds were placed in pre-weighted open aluminum containers and 116
dried for 48 h in an oven at 105°C to a constant weight (Daws and Pritchard 2008; Chmielarz 2009b). 117
Water content was evaluated as the average of three independent replications and expressed on fresh 118
weight basis (% FW). 119
120
Hydration window for cryopreservation 121
Experiments were performed to determine the “hydration window”, i.e. the safe range of water 122
content, for P. padus seed storage at -196°C. At the first step, model desiccation and hydration curves 123
were plotted following desiccation or hydration of seeds to WC ranging from 3.5 to 21.1 % FW. For 124
desiccation, 120 seeds were placed on a mesh over 50 g of activated silica gel inside plastic containers 125
(110 x 110 x 35 mm) which were then sealed and kept at 20 °C. For hydration, 120 seeds were 126
dispersed on a mesh placed over 90 ml of distilled water in sealed containers of the same size and kept 127
at 20°C. Water content was monitored during desiccation and hydration by collecting the samples 128
after 2, 5, 8, 17, 24 and 48 h of desiccation and 1.5, 3, 5, 8, 17, 24, 48 and 72 h of hydration following 129
the method described above. The resulting model curves (Fig. 1) were used to predict desiccation or 130
hydration time required to achieve targeted WC for cryopreservation studies. 131
To determine hydration windows for cryopreservation, seeds were desiccated or hydrated to 132
targeted WC (Fig. 2), sealed in 5 ml cryo-tubes (Nunc, USA), which were attached to an aluminum 133
holder and immersed into LN directly. After 1 week of storage in LN, ampules were rewarmed in a 134
water bath at 37°C for 15 min. Four ampoules each containing 25 seeds (100 seeds in total) were used 135
for each WC treatment. Unfrozen seeds desiccated or hydrated to the same WC served as a control. 136
Stratification, germination and data collection were performed as described below. 137
138
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Effect of cryopreservation protocol 139
Untreated seeds of P. padus had 12.7 % WC which was within a safe range of WC for 140
cryopreservation based on the results of previous experiments. Therefore these seeds were used in the 141
second series of experiments to investigate the effect of cooling and rewarming procedures on 142
seedling emergence after cryopreservation. Seeds were sealed in 5 ml cryo-tube (Nunc, USA) which 143
was attached to aluminum holder and exposed, directly or step-wise, to liquid nitrogen (see Table for 144
the description of protocols). After one month of LN storage, seeds were rewarmed using different 145
regimes: slowly at ambient temperature (22 ± 1°C), step-wise at -80°C and -20°C, or rapidly in a 146
water bath at 37°C for various durations (Table1). Four ampoules each containing 25 seeds (100 seeds 147
in total) were used for each treatment. Untreated seeds were used as a control. Stratification, 148
germination and data collection were performed as described below. 149
Storage duration at different temperatures 150
The effect of storage duration on seedling emergence was studied for freshly collected P. padus seeds 151
(12.7 % WC) stored at -20°C, -80°C and -196°C for 1 h, 1 week and 1 month (Table 1). For each 152
combination of temperature and storage duration, four ampoules, each containing 25 seeds (100 seeds 153
in total) were treated. 154
Stratification, germination and data collection 155
Stratification and germination of P. padus seeds were performed according to Suszka (1967). Seeds 156
were stratified in the moist quartz sand fraction < 1 mm in 250 ml plastic bottles at 5°C in darkness 157
for 8 weeks. Stratified seeds were germinated on the top of double-layered filter paper moisturized 158
with distilled water in 9 cm Petri dishes at 20 ± 1°C under fluorescent light (16 h light/8 h dark). After 159
45 days, seeds that developed both shoots and roots were counted to assess “seedling emergence”, 160
which was expressed as percentage out of the total number of seeds sown for each treatment. In 161
addition, viability of control (non-cryopreserved) seeds at 12.7 % WC was tested by staining with 1 % 162
solution of 2,3,5-triphenyltetrazolium chloride (TTC) according to International Seed Testing 163
Association (ISTA, 1999). 164
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165
Statistical analysis 166
Bayesian Methods 167
Bayesian methods were followed to analyse the data obtained in cryopreservation studies. These 168
methods are different from the classical statistics, in which the data are assumed to result from an 169
experiment infinitely repeatable under unchanging conditions. The observed frequencies may thus 170
serve to estimate the unknown theoretical parameters – therefore, this methodology is often called 171
frequentist. In the Bayesian framework, a datum is supposed to result from a unique experiment, and 172
the unknown parameter is viewed as a realisation from an unobserved distribution, which is the object 173
of our inference. For example, in our study, the parameter of interest is the proportion of seeds 174
expected to develop seedlings under certain conditions. Bayesian inference is a process of updating 175
prior information about the parameter of interest θ with the observed data y to produce a posterior 176
distribution p(θ|y). The inference about θ can be made from this distribution in terms of estimated 177
posterior means and standard deviations, credible intervals (a Bayesian counterpart to confidence 178
intervals) and the Bayesian P-values. The latter refer to the probability that some statement of interest 179
is true given the observed data. This is in contrast to the classical p-value, which is the probability of 180
erroneously rejecting the null hypothesis. Therefore, Bayesian P-values are close to one, when the 181
statement is well supported by the data (see Ellison 1996 and Marin et al. 2003 for details). 182
Model comparison can be performed using the Deviance Information Criterion (DIC) 183
(Spiegelhalter 2002), which is a Bayesian measure of model fit, similar to classical AIC and BIC (see, 184
e.g., Hastie et al. 2009). The smaller DIC corresponds to a better model. DIC in a range from 5 to 10 185
can be considered substantial, while a difference of over 10 would definitely rules out the model with 186
the higher DIC. 187
One can also perform Bayesian ANOVA, i.e. estimation and comparison of variance 188
components via plots of credible intervals as suggested by Gelman (2005) and demonstrated by Qian 189
and Shen (2007) using several examples. In this approach the aim would be to assess estimated 190
standard deviations of the effects being sufficiently different from zero. 191
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Finally, Bayes Factors (BFs), which can sometimes be interpreted as the odds in favour of the 192
null hypothesis against the alternative hypothesis, that are given by the data can also be used for 193
testing the hypothesis (Lee 1997). 194
Bayesian model estimation is often not analytically feasible and is therefore normally 195
performed via numerical simulations. We used WinBUGS software (Lunn et al. 2000) and an R-196
package R2WinBUGS (R Core Team 2014) for graphing and posterior data analysis and simulation 197
chains of length 45000, thinned to 5000, after 5000 burn-in for determining the inference. 198
Convergence was assessed visually. 199
Binomial logistic regression 200
We used binomial logistic regression, a standard tool for analysing a response variable, which 201
represents a number of successes in a set of identical trials. Mathematically, the model can be 202
specified as follows. 203
In the equations below denotes the number of seeds that showed seedling emergence out 204
of taken for treatment and water content level . Then is binomially 205
distributed with some treatment- and WC-specific probability of seedling emergence : 206
(1)
The probability can then be modelled via logistic regression parametrised as follows: 207
(2)
where is the global mean log-odds, is the expected effect of treatment i, is the expected 208
effect of WC level , and is the effect of interaction between the treatment and the WC level. Since 209
we have only two different treatments, other obvious parametrisations are possible. 210
Note, that in order to test for the non-negligible interaction effect, one could fit the model 211
with it and without it and report the difference in the associated DIC values: . 212
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To complete the Bayesian model, we need to specify the prior distributions for the parameter 213
vectors , and . Since we do not have any particular information on them, a common solution is 214
to specify the so-called vague or uninformative Gaussian priors: 215
(3)
(4)
(5)
where and The WinBUGS code can be found in the Supplement A1. 216
It is noteworthy, that beta-prior can be used directly instead of (2-5) if separating the effects 217
of treatment and WC need not be analysed: 218
(6)
where and are hyperprior parameters, which we have set to resulting in uniform prior 219
distribution between 0 and 1 for . The code for this model formulation can be found in the 220
Supplement A2. 221
The two models: (1-5) and (1,6) provide alternative prior formulations for the same parameter 222
matrix and their results are interesting to compare for the purposes of sensitivity analysis, i.e. to 223
ensure that prior formulation does not affect posterior inference. 224
Credible intervals for water contents 225
The water contents, which can be considered an actual proportion observation (rather than a summary 226
of binomial trial as above), can be transformed via the logit transformation: 227
228
and can then be modelled using Gaussian distribution with standard vague priors for the parameters 229
and : 230
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(7)
231
where is the observation made after hours. 232
(8)
(9)
The () refers to the gamma distribution, and the implementation of model (7-9) in WinBUGS is 233
shown in Supplement A3. The means and 95 % credible intervals are then backtransformed using the 234
expit function (inverse of logit). 235
Results 236
Hydration Window for cryopreservation 237
Water content of Prunus padus seeds before the experiments was 12.7 %. Controlled 238
desiccation and hydration of seeds is a common approach which allows investigation of the effect of 239
seed WC on their longevity under different storage regimes ( Kim et al. 2008; Chmielarz 2010a). In 240
the present study, manipulations with WC allowed the construction of model desiccation and 241
hydration curves for P. padus seeds covering the WC from 3.1 to 22.8 % (Fig. 1). Within the first 24 h 242
over silica gel, seed WC dropped from 12.7 to nearly 5 % followed by gradual decrease to 3 % during 243
the next 24 h. Seeds could be hydrated to 17 % WC within 17 h and to 21 % within 72 h. Based on the 244
model curves presented in Figure 1, seeds were desiccated or hydrated to target WC (Fig. 2, X axis) 245
and cryopreserved in liquid nitrogen to determine the safe hydration window for their cryogenic 246
storage. Fig. 2 shows seedling emergence of control and cryopreserved seeds at different WC and the 247
associated 95 % credible intervals. Seedling emergence of control (non-cryopreserved) seeds varied 248
from 40 to 55 % with no evidence for WC having an effect on the probability of seedling emergence 249
( ). By contrast, there was a significant difference between seeds 250
cryopreserved at WC below 15 % and above 17.2 % ( ) with the 251
seedling emergence decreasing from an average of 47 % to 0.6 %, respectively (P>0.9999). In this 252
study seedling emergence of non-cryopreserved seeds was relatively low, therefore the safe hydration 253
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window was defined as a range of WC which allowed seeds to tolerate cryogenic temperatures and 254
ensured at least 40 % seedling emergence (expected probability of seedling emergence E(p|data) > 0.4 255
as indicated in Figure 2 by the horizontal dotted line). As Fig. 2 shows, all tested levels of WC 256
ensured germination of control seeds while only the range between 3.5 to 15% WC was safe for seed 257
cryopreservation. 258
It would also be pertinent to know the level of certainty with which at least 40 % seedling 259
development from the seeds can be predicted under each regime. In Bayesian framework, this 260
question can be answered easily by evaluating the posterior probability 261
. 262
The results expressed as Bayesian P-values are shown in the upper panel of Figure 2. The dotted 263
horizontal line corresponds to the posterior probability of 0.95. 264
265
Effect of cryopreservation protocol 266
As shown in Fig. 3, the cooling regime had no influence on seedling emergence of cryopreserved 267
seeds ( ). By contrast, the effect of rewarming method on seedling emergence was 268
highly significant ( ). The lowest seedling emergence of 30 % was recorded for seeds 269
subjected to stepwise cooling and cryopreservation followed by stepwise rewarming at -80°C and -20 270
°C (protocol 10 in the Table). Seeds that have been rewarmed rapidly showed 49-51 % seedling 271
emergence regardless of the cooling procedure (protocols 2 to 5 in Table 1). Interestingly, there was 272
no difference in seedling emergence after rewarming on air (22 ± 1 °C) or rapidly in a water bath at 273
37°C for various durations (Fig. 3). 274
Effect of storage temperatures and duration 275
There was no evidence of the effect of storage temperature (-20 °C, -80 °C or -196°C) and storage 276
duration (1h, 1 week or 1 month) on seedling emergence of P. padus seeds ( , Fig. 4). 277
Average seedling emergence varied from 47 to 55 % regardless of storage conditions. 278
279
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Discussion 280
Conservation of Prunus genetic diversity has been addressed by applying both in situ and ex situ 281
conservation programmes (Cheong 2012). Ex situ conservation methods included tree cultivation in 282
orchards, seed banks, storage of vegetative organs at low temperature and cryopreservation (Niino et 283
al. 1997; De Boucaud et al. 2002; Michalak et al. 2015b). Among available options of ex situ 284
conservation, seed banking is the most practical due to ease of application and the amount of diversity 285
which can be conserved using limited space (Pritchard and Nadarajan 2008). Prunus seeds can also 286
serve a convenient model to study storage behavior of large-sized seeds with high lipid and protein 287
content (SID 2015). In this study we accomplished cryopreservation of Prunus padus seeds and 288
applied the Bayesian statistical methods to evaluate the influence of various parameters such as seed 289
water content, cooling and rewarming method, short- and middle-term storage duration and storage 290
temperature on seedling emergence in order to develop methodology for ex situ conservation for this 291
species. 292
It has been previously shown that seed viability after treatment may be significantly 293
overestimated if the decision is based on germination test only (Popova et al. 2013; Michalak et al. 294
2015). Therefore, in this study, seedling emergence, i.e. the ability of seeds to produce healthy 295
seedlings with well-developed shoots and roots, was used as the main parameter for evaluation of 296
treatment impact. 297
In the present study, control (non-cryopreserved) seeds of Prunus padus at 12.7 % WC 298
showed seedling emergence of 43 % (Fig. 2), which was lower than 60.4 % viability determined by 299
the TTC test (data not shown). By contrast, higher seed germination (75 - 98 %) was reported for P. 300
arabica, P. andersonii, P. campanulata, P. domestica and P. mexicana (SID 2015). Michalak et al. 301
(2015) suggested that low seed germination observed for some Prunus species may result from pre-302
drying of seeds. Thus, germination was relatively low (44-59 %) for seeds of Prunus avium pre-dried 303
to ca. 13 % WC (Chmielarz 2009b) while freshly collected seeds of the same species at ca. 20 % WC 304
showed 76 and 86 % germination, depending on provenance (Michalak et al. 2015). This suggestion 305
was supported by another study, where germination of Prunus avium seeds decreased from 93 % to 306
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39-43 % when fresh seeds were dried for 3-5 days (Suszka 1962, cited by Michalak et al. 2015). It is 307
possible that low percentage of seedling emergence observed in our study was caused by drying the 308
seeds prior to the experiments. However, this suggestion does not correspond to the observation that 309
seeds of P. padus are desiccation tolerant (see below). Since the germination tests for the above-310
mentioned species were performed under similar conditions, these differences in germination ability 311
can be attributed to inner dormancy or other yet unknown mechanism in P. padus seeds. 312
According to the Royal Botanic Gardens Kew Seed Information Database (SID 2015), mature 313
seeds of Prunus padus are orthodox. This means that seeds withstand dehydration to around 5 % FW, 314
and their longevity increases with reducing seed WC and storage temperature in a mathematically 315
predictable and quantifiable way (Berjak and Pammenter 2004). Indeed, in our study seeds of P. 316
padus tolerated severe desiccation to 3.5 % WC without a reduction in viability. These results are 317
consistent with high dehydration tolerance reported earlier for mazzard cherry (Jensen and Eriksen 318
2001; Chmielarz 2009b) and other Prunus species (SID 2015). By contrast, seeds of Prunus avium 319
collected from two provenances showed noticeable decrease in seedling emergence when desiccated 320
to WC below 11 %, and were considered suborthodox (Michalak et al. 2015b). 321
For many trees such as of genus Citrus (Hor et al. 2005), Fraxinus (Chmielarz 2009a), Salix 322
(Popova et al. 2012; 2013), and Populus (Popova et al. 2013) the ability of seeds to germinate after 323
exposure to LN can be retained only within a short range of WC. In our study, seeds of Prunus padus 324
could be safely cryopreserved if their WC was below 15 %, The lower limit of WC remained unclear 325
as seeds were not desiccated to WC below 3.5 %. %. Yet, the hydration window of 3.5 – 15 % 326
determined for P. padus seeds is wider than that for oily and/or suborthodox seeds of other tree 327
species. For example, hydration window for cryopreservation was 9.0 - 16.9 % WC of Prunus avium 328
seeds (Chmielarz 2009b), 9.9 – 14.5 % for Populus nigra seeds (Michalak et al. 2015a), 9.1 – 14.5 % 329
for seeds of Salix gracilistyla (Popova et al. 2013) and 12.3 – 23.7 % for seeds of Salix hallaisanensis 330
(Popova et al. 2013). Oily seeds of Corylus avellana that were considered orthodox could only 331
tolerate cryopreservation at 7.4 – 9.1 % WC, and their germination and seedling emergence were still 332
lower than those of control seeds (Michalak et al. 2013). Not only the hydration window is species-333
dependent, it may be also affected by seed provenance and initial viability. For example, seeds of 334
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three clones of Salix caprea showed very different hydration windows: 4.8 – 21.9 %, 9.1 – 19.4 % and 335
16.7 – 27.0 % for seed lots with high, intermediate and low initial germination, respectively (Popova 336
et al. 2012). For both orthodox and intermediate seeds, it is important to determine their “high 337
moisture freezing limit” (HMFL). When seeds are cryopreserved above their HMFL, ice crystal 338
formation leads to cell damage and death (Pritchard and Nadarajan 2008). For seeds of P. padus, 339
HMFL was 15 % WC, as indicated by sharp decrease in seed viability above this point (Fig. 2). By 340
contrast, for seeds of some other species the upper limit was as high as 19-21 %, and even 27 % 341
(Popova et al. 2012; 2013). Michalak et al. (2015b) reported that seeds of Prunus avium could tolerate 342
cryopreservation by direct immersion in LN at 19.7 and 20.2 % WC. High seed tolerance for LN at 343
high WC was also observed for intermediate seeds of some coffee species (Dussert et al. 2001). These 344
differences in response to LN exposure at high WC species may be attributed to lipid composition in 345
seeds and the amount of unfrozen water (Dussert et al. 2001; Michalak et al. 2015b). However, further 346
studies are required to understand the mechanisms underlying the response of suborthodox seeds to 347
ultra-low temperatures. In the present study, the precision of critical WC determination between 15 348
and 17 % for P. padus seeds (Fig. 2) may raise concern, however, the situation is still better than that 349
for recalcitrant seeds where critical water content cannot be unequivocally determined due to high 350
variability of desiccation and storage responses within a species (Berjack and Pammenter 2004). 351
Using seeds within the safe range of WC is a necessary but not a sufficient prerequisite to 352
ensure seed germination after cryogenic storage. Other factors such as the regimes of cooling and 353
rewarming are particularly important for successful cryopreservation of some species (Dussert and 354
Engelmann 2006). Thus, among seeds of 103 plant species native to Russian Far East tested for 355
cryogenic storage, cryopreservation by direct immersion in LN reduced germination of 11 species 356
(Kholina and Voronkova 2008). Seeds of three of them (Cardamine impatiens, Plantago lanceolata 357
and Salicornia europaea) are known to be rich in lipids, triglycerides and fatty acids (Kholina and 358
Voronkova 2008). Another example includes seeds of mazzard cherry cryopreserved by direct 359
immersion in LN: even within the safe range of WC cryopreserved seeds showed reduced viability 360
and developed less seedlings compared to unfrozen seeds (Chmielarz 2009b). In the present study, 361
cooling regime did not produce significant effect on seedling emergence after cryopreservation. The 362
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effect of rewarming conditions was also insignificant, except for the protocol 10, where both cooling 363
and rewarming were performed step-wise at -80°C and -20°C. Interestingly, if step-wise precooled 364
seeds were rewarmed rapidly at 37°C, their post-cryostorage seedling emergence was not affected 365
(Fig. 3). In all experiments, plantlets developed from cryopreserved seeds appeared normal and their 366
morphology was the same as that of seeds from non-frozen seeds. 367
Since the information on storage behavior and cryopreservation of Prunus padus seeds is not 368
available, observations on other species may reveal a useful comparison. Slow rewarming decreased 369
emergence of seedling from coffee seeds cryopreserved either by direct immersion into LN or 370
precooled at -75°C (Dusset and Engelmann 2006), which is in agreement with our results. Seeds with 371
higher lipid content have been found to be more sensitive to cryogenic exposure (Pence 1991). Such 372
sensitivity may be associated with phase transitions/crystallization of lipids during the cooling-373
rewarming cycles (Pritchard and Nadarajan 2008). Lipid crystallization events normally occur during 374
cooling at onset temperatures ranging from +16°C to -59°C. Some authors suggested that lipid 375
composition is of primary significance for seed tolerance to dehydration and cooling (Crane et al. 376
2003; Hor et al. 2005; Kim et al. 2008). For instance, Crane et al. (2003) found that low viability of 377
seeds of some Cuphea species after storage at -18°C can be the result of phase transition in specific 378
groups of lipids. Hor et al. (2005) analysed storage behaviour of seeds of four Citrus, seven Coffee, 379
two Quercus, and one each of Azadirachta indica, pea and soybean species based on open literature 380
sources and found a prominent negative relationship between the amount of lipid content and 381
unfrozen water, which affected the ability of seeds to recover after cryopreservation. Earlier Dussert 382
et al. (2001) found no direct relationship between lipid content of coffee seeds and their survival after 383
LN exposure. However, there was a significant correlation between the percentage of seedling 384
emergence and the content of unsaturated fatty acids in the seeds (Dussert et al. 2001). 385
During cooling, time is often insufficient for the accumulation of ice-induced damage in seeds 386
while rewarming at low rate may give the ice crystals time to grow. During rewarming, the 387
temperature range between -130°C and -20°C seems to be particularly important as re-crystallization 388
and conformational changes in lipids are most likely to occur at these temperatures (Crane et al. 2003; 389
Walters et al. 2004). This idea is supported by the results of the experiments with Coffee seeds: 5 min 390
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exposure at -80°C had no effect on seed viability while maintaining seeds at this temperature for one 391
week caused complete loss of survival (Dussert and Engelmann 2006). In our study, however, seeds 392
of P. padus could be stored at -80°C for at least one month without a decline in their seedling 393
emergence ability (Fig. 4). A moderate detrimental effect of step-wise rewarming was only visible 394
with seeds cryopreserved in LN at -196°C and was probably caused by pere-crystallization events or 395
conformational changes in specific lipid groups provoked by cryogenic cooling (Walters et al. 2004). 396
For seeds of many plant species, cryoconservation at -196°C provides higher longevity and 397
thus has been considered more secure than storage at -20°C or -80°C. For example, seeds of silver 398
birch (Betula pendula) showed higher germination when stored for 3 years at -196°C compared to the 399
same seed lot stored at -3°C (Chmielarz 2010a). Seeds of some 400
American coniferous and deciduous trees fully retained their germination ability after being dried and 401
stored in LN for 3 years (Barbour and Parresol 2003). We found no evidence of the effect of storage 402
temperature and duration on seedling emergence of P. padus seeds. However, assuming that 403
germination remained the same under all temperature tested, cryopreservation can be still 404
recommended, at least for the short-term . Though some deterioration effects can be detected in 405
seeds during long-term cryogenic storage (Walters et al. 2004), the ability of cryogenic temperature to 406
arrest metabolic processes in cells and decrease mobility of molecules seems to be beneficial for 407
genebanking (Pritchard and Nadarajan 2008). Walters et al. (2004) estimated half-lives of fresh 408
lettuce seeds stored in the vapor and liquid phases of LN to be 500 and 3400 years, respectively. 409
Though this estimation cannot be projected directly to other species, it gives the conservation 410
specialist the first clue of how effective cryogenic storage can be for seed conservation. 411
Bayesian methods proved to be effective in plant conservation biology, for example, to assess 412
alternative actions in recovery plans, matrix population modeling, and predicting germination using 413
logistic models (Marin et al. 2013). It seems to be particularly useful when analysing the results of the 414
experiments with binomial data as an outcome (Bazán et al. 2014). Binomial data may be recorded as 415
a number of successes or failures out of the total number of tests such as germination of seeds in the 416
genetic collections (Walters et al. 2004; Pritchard and Nadarajan 2008). Such data are commonly 417
analyzed by assessing proportion of successes, data transformation (often with arcsine), and 418
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performing ANOVA on transformed data, followed by the test of significance using Tukey HSD, 419
Fisher or Duncan MRT (see e.g. Kim et al. 2008; Chmielarz 2009a; 2009b). There are several 420
problems associated with the arcsine transformation including loss of information (10 observed 421
successes out of 25 is not statistically the same as 1000 out of 2500, but the proportion of successes is 422
0.4 in both cases), lack of interpretability and failure to guarantee normality and homoscedasticity 423
required by ANOVA (Warton and Hui 2011). The methodological problem is not specific to 424
biological sciences, but is also of interest to, for example, epidemiologists and social scientists. 425
Recently, a move to binomial generalized linear (mixed) models GL(M)M has been advocated (Jaeger 426
2008; Warton and Hui 2011;). Although GL(M)M suffers from none of the above mentioned 427
problems, the maximum likelihood estimation fails in the cases of ‘degenerate’ estimates when 0 428
successes (or, alternatively, 0 failures) have been observed in any one category (Albert and Anderson 429
1984; Silvapulle 1981). This results in infinite parameter estimates and invalid inference. 430
Unfortunately for an inexperienced practitioner, statistical software often fails to alert the user to this 431
problem. For example, the GENLIN procedure in SPSS (IBM 2013) will give warning about the 432
convergence criteria not being satisfied, but will still proceed with the output. A glm function in R (R 433
Core Team 2014), on the other hand, will produce no warnings at all, although an experienced user 434
will recognize the problem from unreasonably high standard error estimates and, as a result, p-values 435
close to one. 436
This problem of observed zero counts, also called ‘separation’ has been known for some time 437
and methods have been developed to resolve it (see e.g. Heinze and Schemper 2002). In this paper, 438
however, we choose not to use the classical methods and followed Bayesian framework instead. The 439
use of Bayesian methods in plant physiology, ecology and genetics studies is increasing as more and 440
more practitioners are becoming familiar with them (Marin et al. 2003; Olge and Barber 2008). The 441
popularity of Bayesian statistics can be attributed to its flexibility in formulating models appropriate 442
to the questions of interest rather than molding questions according to what the model is able to do as 443
well as to the increasing computational capabilities and the availability of a free and reasonably user-444
friendly software WinBUGS (Lunn et al. 2000). 445
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In this study we have demonstrated successful application of Bayesian methods to analyze the 446
data obtained in conservation of Prunus padus seeds using a number of treatments and different 447
storage regimes. We have shown that within the Bayesian statistics it is possible to avoid a separation 448
problem caused by zero level of seedling emergence in some treatments. Direct application of arcsine 449
and similar transformations to such data would give a very poor approximation to normality. Also, the 450
assessment of the possibility of seedling emergence level in the performed treatments exceeding the 451
40 % threshold was straightforward within the Bayesian framework. Thus, we are in agreement with 452
Marin et al. (2003) in encouraging the use of Bayesian paradigms for data analysis in conservation 453
studies. 454
Conclusion 455
In conclusion, the results of this study show that freshly collected mature seeds of Prunus padus 456
tolerated dehydration to 3.5 % WC and thus can be considered orthodox. We determined, for the first 457
time, the safe hydration window for cryopreservation of P. padus seeds in LN to be 3.5-15 % and 458
showed that the majority of tested cooling and rewarming regimes had no profound effect on seed 459
viability after cryogenic storage. Our results suggest that seed storage in liquid nitrogen is an effective 460
conservation option for conservation of Prunus padus and possibly for other Prunus species. We also 461
demonstrated the simplicity and efficacy of Bayesian methods in analyzing binomial data obtained in 462
seed experiments and as such this approach may be very useful in developing effective conservation 463
technologies for a range of species. 464
Acknowledgments. This work was supported by the research fund of Dong-A University (Busan, 465
Republic of Korea) and by Gosling Research Institute for Plant Preservation (GRIPP), Guelph, 466
Canada. 467
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Table 1. Combinations of cooling, storage and rewarming procedures investigated in the present 617
study for conservation of Prunus padus seeds. 618
Variant
(Protocol)
Cooling Storage
tempe-
rature
Storage
duration
Rewarming
1 Untreated control seeds N/A N/A N/A
Effect of cooling regime
2 Direct to -196°C -196°C 1 month 37°C, 15 min
3 -20 °C (1 h) → -196°C -196°C 1 month 37°C, 15 min
4 -80 °C (1 h) → -196°C -196°C 1 month 37°C, 15 min
5 -20°C (1h) → -80°C (1 h) → -196°C -196°C 1 month 37°C, 15 min
Effect of rewarming regime
6 -80 °C (1 h) → -196°C -196°C 1 month 37°C, 7 min
7 -80 °C (1 h) → -196°C -196°C 1 month 37°C, 30 min
8 -80 °C (1 h) → -196°C -196°C 1 month Air (22°C), 15 min → 37°C, 7 min
9 -80 °C (1 h) → -196°C -196°C 1 month Air (22°C), 30 min
10 -20°C (1h) → -80°C (1 h) → -196°C -196°C 1 month -80°C, 1 h → -20°C, 1 h → air (22°C), 30 min
Effect of storage temperature and duration
11 Direct -20°C 1 h Air (22°C), 30 min
12 Direct -20°C 1 week Air (22°C), 30 min
13 Direct -20°C 1 month Air (22°C), 30 min
14 Direct -80°C 1 h 37°C, 15 min
15 Direct -80°C 1 week 37°C, 15 min
16 Direct -80°C 1 month 37°C, 15 min
17 -80 °C 1 h → -196°C -196°C 1 h 37°C, 15 min
18 -80 °C 1 h → -196°C -196°C 1 week 37°C, 15 min
19 -80 °C 1 h → -196°C -196°C 1 month 37°C, 15 min
N/A: not applicable 619
620
621
622
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27
Figure captions 623
624
Figure 1. Model desiccation and hydration curves recorded for Prunus padus seeds. Data are 625
presented as posterior estimated means and the respective 95 % credible intervals. Water content is 626
calculated on fresh weight basis. 627
Figure 2. A - Posterior probabilities of seedling emergence of at least 40 % for different water content 628
(WC) values under the control (-LN) and cryopreservation (+LN) treatments. The dotted horizontal 629
line corresponds to the posterior probability of 0.95. B - Estimated posterior mean proportions of 630
seedling emergence for different water content (WC) under the control (-LN) and cryopreservation 631
(+LN) treatments. Bars correspond to 95 % credible intervals. 632
633
Figure 3. Seedling emergence of Prunus padus seeds after different cooling and rewarming 634
treatments performed according to protocols (Variants) 1-10 in Table 1. Data are presented as 635
posterior estimated means and the respective 95 % credible intervals. 636
637
Figure 4. Seedling emergence of Prunus padus seeds after storage at -20°C, -80°C and -196°C for 638
various durations compared to untreated control. Data are presented as posterior estimated means and 639
the respective 95 % credible intervals. 640
641
642
643
644
645
646
647
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05
1015
Dessication (hours)
Wat
er c
onte
nt (
%)
0 5 24 4810
●
●
●
●
●
●
●
1015
2025
Hydration (hours)W
ater
con
tent
(%
)
0 10 24 48 725
●
●●
●
●
●●
●
●
Figure 1.
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0.0
0.2
0.4
0.6
0.8
1.0
Water content (%)
Pr(
p>.4
0|da
ta)
3.5 7.6 12.7 15.0 17.6 20.05.0 9.6 14.6 17.2 18.4 21.1
●
●
●
●
●
●●
●
●●
●
●
● − LN+LN
Water content (%)
See
dlin
g em
erge
nce
(%)
010
2030
4050
6070
3.5 7.6 12.7 15.0 17.6 20.05.0 9.6 14.6 17.2 18.4 21.1
− LN+LN
A
B
Figure 2.
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1 2 3 4 5
020
4060
8010
0
Variants
See
dlin
g em
erge
nce
(%)
● ●●
●●
020
4060
8010
0
VariantsS
eedl
ing
emer
genc
e (%
)
1 6 7 8 9 10
● ●
●
●
●
●
Figure 3.
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020
4060
8010
0
See
dlin
g em
erge
nce
(%)
Control1 hour1 week1 month
− 20°C − 80°C − 196°C
Figure 4.
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A1. Supplement: WinBUGS code for model (1-5)
model{
for(i in 1:N){
Y[i] ~ dbin(p[trt[i],fw[i]],25)
}
# logistic structure
for(ti in 1:2){
for(fi in 1:12){
p[ti,fi] <- 1/(1+exp(-logitp[ti,fi]))
}}
for(ti in 1:2){
for(fi in 1:12){
logitp[ti,fi] <- alpha0+alpha*(ti-1)+beta[fi]+gamma[fi]*(ti-1)
}}
# priors
alpha0 ~ dnorm(0,1.0E-5)
alpha ~ dnorm(0,1.0E-5)
beta[1] <- 0
for(fi in 2:12){
beta[fi] ~ dnorm(0,1.0E-5)
}
gamma[1]<- 0
for(fi in 2:12){
gamma[fi] ~ dnorm(0,1.0E-5)
}
}
A2. Supplement: WinBUGS code for model (1,6)
model{
for(i in 1:N){
Y[i] ~ dbin(p[trt[i],fw[i]],25)
}
# priors for p
for(ti in 1:2){
for(fi in 1:12){
p[ti,fi] ~ dbeta(1,1)
}}
}
A3. Supplement: WinBUGS code for model (7-9)
Please note, that the logit transformation has been performed prior to
running the code for reasons of computational efficiency.
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model{
for(i in 1:N){
Y[i] ~ dnorm(mu[hour[i]],tau)
}
for(h in 1:H){
mu[h] ~ dnorm(0,1.0E-5)
}
tau ~ dgamma(.01,.01)
}
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