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Understanding local adaptation in a freshwater salmonid fish: evolution of a research program.
Journal: ICES Journal of Marine Science Manuscript ID ICESJMS-2019-075.R1
Manuscript Types: Food for Thought Date Submitted by the
Author: n/a
Complete List of Authors: Vøllestad, Leif Asbjørn; University of Oslo Centre for Ecological and Evolutionary Synthesis, Department of Biosciences
Primmer, Craig; Organismal and Evolutionary Biology Research Programme, Institute of Biotechnology, University of Helsinki
Keyword: population genetics, ecology, Thymallus thymallus, genomics, adaptation, transcriptomics, proteomics, grayling
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1 Understanding local adaptation in a freshwater salmonid fish: evolution of a research 2 program.
3 4
5 L. Asbjørn Vøllestad1 & Craig R. Primmer2,3,4 6
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8 1 University of Oslo, Department of Biosciences, Center for Ecological and Evolutionary 9 Synthesis CEES, Post Office Box 1066 Blindern, NO-0316 Oslo, Norway
10 [email protected], https://orcid.org/0000-0002-9389-7982
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13 2 Organismal and Evolutionary Biology Research Programme; 3 Institute of Biotechnology; 4 14 Helsinki Institute of Sustainability Science, PO Box 56, 00014, University of Helsinki, FINLAND 15 [email protected], https://orcid.org/0000-0002-3687-8435
16 17 18
19 Key words: population genetics, ecology, adaptation, genomics, transcriptomics, proteomics, 20 grayling, Thymallus thymallus, climate
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23 For: ICES Journal of Marine Science 24 Theme section: Food for thought 25
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27 Abstract
28 Linking ecology and evolution can be challenging, particularly as these fields evolve rapidly 29 tracking technological and theoretical developments. Thus, it has become ever more 30 important for practitioners of different biological disciplines to understand new
31 opportunities and challenges. Since theory and methods evolve, so will research programs – 32 often tracking opportunity. Here, we describe a research program where we have
33 investigated the population biology of grayling Thymallus thymallus in a Norwegian alpine 34 landscape over three decades. Starting with classical ecological studies we identified a set of 35 populations that had evolved population-specific phenotypic traits over a relatively short 36 time span (10-30 generations). These observations led us into evolutionary studies at various 37 levels of biological organization, using population and quantitative genetic, transcriptomic 38 and proteomic approaches. Overall the results show that the populations exhibit
39 evolutionary responses to local-scale differences in environment (mainly water temperature 40 during early development). Further, plastic responses are very important in the early phase 41 of population diversification. Population genomic studies are now becoming possible
42 following the completion of an annotated genome. This will help us and others in addressing 43 questions about the genetic architecture of traits important for local adaptation, thus
44 emphasizing that combining ecological and evolutionary approaches is more important and 45 interesting than ever.
46 47
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48 Introduction
49 In the history of science, we often see scientific subfields developing concepts and ideas in 50 parallel without too much communication between them. This can lead to development of 51 different terminologies and theories for the same concepts. The general fields of population 52 biology and evolutionary biology have, over time, blossomed into wide-ranging fields with a 53 variety of mature theories. In parallel, fisheries science struggled with many of the same 54 concepts and problems, but maybe too often in isolation from the more classical fields. This 55 was unfortunate, since the fertilizing effect of being challenged with problems and questions 56 from close-by areas of inquiry may have been lost.
57 One classic problem in fisheries biology is the definition of the stock (Ryman and 58 Utter, 1987; Booke, 1999; Waldman, 2005; Hawkins et al., 2016). Throughout the history of 59 fisheries management, it has been difficult to define the management unit, and the number 60 of definitions abound. David Secor's new book on the migration ecology of marine fishes 61 devotes one chapter to this topic (Secor, 2015). It is a key assumption that a stock or
62 management unit can be rigorously defined (Hawkins et al., 2016), and also that the level of 63 connectivity among such stocks or populations can be estimated (Lowe and Allendorf, 2010).
64 Populations can be delineated using a variety of methods, all with various drawbacks and 65 limitations (Cadrin et al., 2005).
66 It took time before the profound knowledge from population genetics (Hartl and 67 Clark, 1997) and population ecology and life history theory (Roff, 1992; Stearns, 1992; Roff, 68 2002) was absorbed by the fisheries community. But, as discussed by Waples and Gaggiotti 69 (2006), also the way the population concept was used by the ecological and evolutionary 70 community may at times have been confusing (see Mayr, 1963). Ecologists and evolutionary 71 biologists working with freshwater organisms rapidly absorbed new insights from the more 72 theoretical biological fields, and general population thinking was included into research 73 programs on freshwater fish more or less at the same time as theory and methods were 74 developed. In particular, the development of methods for studying genetic differences 75 between populations using neutral genetic markers was an important milestone in our 76 understanding of population structuring and also differentiation.
77 The interaction between population genetics and ecology has not always been as 78 close as one should wish. Studies on the population differentiation of salmonid fishes 79 probably started with the early works in the 1970's of Fred Utter, Nils Ryman and Fred
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80 Allendorf (Utter et al., 1973; Allendorf et al., 1976, 1977; Ryman et al., 1979). In the more 81 that 50 years that have passed since these novel observations, the field of population 82 genetics has evolved with a tremendous development of methods and also of theory (Hahn, 83 2018). A large number of population-genetic studies on how fish populations are structured 84 can now be found in the literature. However, far fewer studies actually investigate how such 85 population structuring have led to local adaptation (see early discussion by Taylor, 1991). To 86 show that populations are adapted to a certain environment requires a quite specific set of 87 methods and approaches, using insights from diverse fields of inquiry (see the still
88 interesting book by Williams,1966, and the very useful review by Kawecki and Ebert, 2004).
89 The most used approaches for studying adaptation up until recently have been various 90 quantitative genetic approaches (Roff, 1997; Naish and Hard, 2008; Blanquart et al., 2013), 91 such as different types of common garden or reciprocal transplant experiments. More
92 recently, functional genetics and genomics approaches have become common (Savolainen et 93 al., 2013). And, to cite Michael Whitlock, "the study of local adaptation is at an exciting 94 time" (Whitlock, 2015).
95 A worrying aspect when scanning the literature is the very biased set of study 96 organisms chosen for detailed investigation of local adaptation. A few selected model 97 species of fish are intensively studied, examples are the guppy Poecilia reticulata (Reznick et 98 al., 1990; Reznick and Ghalambor, 2001) and the threespine stickleback Gasterosteus
99 aculeatus (Colosimo et al., 2005; Jones et al., 2012). Some species of salmonid fishes in the 100 genus Salmo and Oncorhynchus have also been intensively studied (see recent books: Aas et 101 al., 2011; Jonsson and Jonsson, 2011; Quinn, 2018). These species are popular study objects 102 due to their large economic, social and political value. A quick search on the Web of Science 103 (August 8, 2018) gave 23,816 hits when searching for "Salmo salar", and 38,174 hits for 104 "Oncorhynchus mykiss", these species are the two most studied salmonid species. Of course, 105 few of these studies focus on local adaptation or evolution as such. Many of the other 106 salmonid species gave between 2,000-11,000 hits in similar searches. Clearly, some species 107 are not popular as study objects. For example, the European grayling Thymallus thymallus, 108 the species to be discussed here, only gave 1,070 hits by the search.
109 Even if only relatively few studies focus on local adaptation in salmonid fishes, deep 110 and important insights can be gleaned from many of the studies that do. In particular, 111 studies merging the classical ecologically-based approaches with the use of functional
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112 genetics/genomics and/or high-throughput sequencing technology carry great promise 113 (Barson et al., 2015; Hoban et al., 2016; Prince et al., 2017). These insights can to some 114 degree be translated to other species. However, using knowledge from other species cannot 115 fully substitute the information that can be found by detailed studies of the target species 116 itself. Studies on species with low economic or societal interest are classically difficult to 117 fund and long-term research programs are difficult to maintain. This ultimately leads to a 118 global knowledge base that is strongly biased towards either a few model species that are 119 well suited (adapted) for experimental work in the lab or towards species with great 120 economic interest. This is unfortunate.
121 We more or less by chance started a "research program" on a set of grayling
122 populations in Norway around 30 years ago. This curiosity-driven research program (see Fig.
123 1 for a conceptual “map” over the program) has "evolved" both through a kind of directional 124 selection and to a large degree by the stochastic process of drift (randomness of funding 125 opportunities and availability of logistical and human resources) as well as migration (driven 126 by the skills and interests of the numerous researchers than have worked on the system in 127 our research teams over the years) and even mutation (e.g. a freezer breakdown shifting the 128 research focus, and various weather-related incidents). We think this is a rather common 129 way research programs develop and evolve. The program started out as an ecological 130 endeavour, becoming more evolutionary over time as we moved into the realms of 131 population and quantitative genetics, and is now at various phases of studying population 132 genomics (and other ‘omics). Our studies have focused on investigating to what degree 133 populations are differentiated and at what scale, to what degree the populations have 134 evolved genetically defined phenotypic differences, and lastly trying to understand the 135 different mechanisms underlying the observations.
136
137 The European grayling
138 The European grayling belongs to the family Salmonidae and the species-poor subfamily 139 Thymallinae, which presently contains 14 species, all in the genus Thymallus (Nelson, 1994).
140 The grayling is an iteroparous spring-spawning salmonid, with limited sex dimorphism 141 (Northcote, 1995). Spawning usually occurs in running water, with the female depositing 142 eggs in a gravel substrate without the digging of redds in contrast to most other salmonid 143 species (Fabricius and Gustafson, 1955; Northcote, 1995). The female is courted by a
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144 dominant male, and usually also attended by several satellite males during actual spawning.
145 The breeding system can be classified as polygynandrous (Kratt and Smith, 1980; Haddeland 146 et al., 2015). The spawning season is short, lasting mainly a few days.
147 Spawning usually starts when water temperatures reaches 4-7 C (Northcote, 1995).
148 Soon after hatching and exhaustion of the yolk sac the larvae establishes territories along 149 the banks, or drift downstream before establishing the territory (Bardonnet and Gaudin, 150 1991; Bardonnet et al., 1993; van Leeuwen et al., 2017). Juvenile and adult grayling feed on 151 various aquatic insects and zooplankton, rarely switching to feeding on fish (Northcote, 152 1995).
153
154 The study system
155 Our study system is found at elevations varying from ca. 600 to 1200 m above sea level, but 156 within a relatively constrained geographic area (Fig. 2). The system was "discovered" when 157 two graduate students investigated the population biology of grayling and brown trout 158 Salmo trutta in an alpine hydroelectric reservoir (Haugen and Rygg, 1996a, b). During
159 conversations with locals they found that the grayling in the reservoir had a relatively recent 160 history, as had the grayling in all the lakes in the area. Grayling were allowed to invade the 161 lake Lesjaskogsvatnet during the 1880's following construction works in the outflowing river.
162 Some decades later people carried grayling, probably in buckets, for stocking into smaller 163 high-elevation lakes. From these lakes the grayling could then disperse downstream.
164 Translocation of fish, mainly brown trout, into alpine lakes has been a 1000-year long 165 tradition in inland Norway (Huitfeldt-Kaas, 1918). The founding number of individuals, and 166 thus the effective population size, was probably very low. Based on the local information it 167 was possible to reconstruct the history of when the various grayling populations were 168 established (Haugen, 2000a, b; Haugen and Vøllestad, 2000). This then became the start of 169 our research program into what can be called "contemporary evolution".
170 The post-glacial history of grayling in this part of Norway can be reconstructed, both 171 using historical sources (Huitfeldt-Kaas, 1918) and more modern phylogeographic methods.
172 The Nordic countries have experienced several glaciations followed by deglaciations
173 (Wohlfarth et al., 2008). The post-glacial invasion of Fennoscandia of grayling populations in 174 the region has been inferred by (Koskinen et al., 2000; Koskinen et al., 2002b). Microsatellite 175 data indicated a close genetic relationship between populations from the southern Swedish
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176 Lake Vättern and Lesjaskogsvatn. Two mitochondrial haplotype lineages are found in the 177 upper parts of the Gudbrandsdalslågen river system (downstream of Lesjaskogsvatn). These 178 lineages constitute the remnants of two different postglacial invasion waves from two 179 hypothesized glacial refugia in the eastern and central Europe, respectively. However, the 180 upper parts of the river were not invaded before relatively recently because of natural 181 barriers to upstream dispersal (Huitfeldt-Kaas, 1918). Upriver dispersal past these barriers 182 has been facilitated by various human interventions, and the barriers still hinder dispersal.
183 The various barriers to migration within the river have led to significant genetic
184 differentiation among sub-population units contained by these barriers (Junge et al., 2013;
185 van Leeuwen et al., 2018). The upper parts of Gudbrandsdalslågen was the upper limit of the 186 distribution of the grayling until the late 1880's. After invading Lesjaskogsvatnet, the grayling 187 established spawning populations in the numerous tributaries to that lake.
188 These various tributaries to Lesjaskogsvatnet differ strongly in morphometry and 189 temperature; some can be classified as small and warm during spring and others can be 190 classified as large and cold (Gregersen et al., 2008). The tributaries are devoid of fish during 191 winter as they freeze completely over. When mature and ready to spawn during spring, 192 grayling migrate into the various tributaries for spawning. Migration starts when water flow 193 decreases following the most intense snow melting and when water temperatures reach 194 over 4-5 °C. Spawning is usually over in a few days. After hatching and development into 195 swim-up larvae the juveniles drift or migrate into the lake where they remain until they 196 reach maturity (Haugen and Vøllestad, 2001; Haddeland et al., 2015). In the lake, the 197 grayling from the various tributaries use large parts of the available lake habitat for feeding 198 (Bass et al., 2014), indicating that grayling from different spawning populations are exposed 199 to the same environmental conditions in this environment. However, due to the different 200 temperature conditions during spring, spawning happens at different time periods, 201 development varies depending on the temperature (Elliott et al., 1987), and thus juvenile 202 fish from different tributaries will have very different opportunities for growth during their 203 first summer of life.
204 In the early 1910's grayling were further transplanted by humans into higher- 205 elevation lakes in the system, leading to subsequent downstream dispersal into yet more 206 lakes (Haugen and Vøllestad, 2001). Local knowledge has made it possible to infer the timing 207 of appearance of grayling in the different lakes. Thus, by making assumptions about grayling
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208 generation time, we can estimate for how many generations the various populations have 209 been evolving in isolation (without gene flow). The lakes differ in morphometry, elevation, 210 local climate and human impact through fishing (mainly by using gill nets). We have taken 211 advantage of this when investigating the population ecology of the grayling in different 212 lakes, and further try to investigate to what degree the populations have evolved 213 adaptations to the local conditions.
214
215 Investigating local adaptation without gene flow
216 The first questions that we asked were classical ecological questions. It was clear that the 217 grayling populations in the five different lakes that we studied were experiencing very 218 different environmental conditions. These environmental differences could potentially lead 219 to different growth and survival patterns. Based on general life history theory we also 220 expected differences in maturation schedules (Stearns, 1992; Roff, 2002). Based on analyses 221 of grayling sampled by gill nets and by analysis of age and growth patterns from otoliths, it 222 was evident that individual growth rates and annual mortality rates differed strongly among 223 populations (Haugen, 2000b), and these differences had led to selection for differential 224 maturation schedules.
225 The different population-specific phenotypic trait values were further compared in 226 order to estimate evolutionary rates (estimated as Darwins and Haldanes; see Hendry and 227 Kinnison, 1999). These rates were estimated over 9-22 generations (44-88 years). The
228 estimated evolutionary rates were high compared to other divergence rates measured at the 229 same temporal scale (Hendry and Kinnison, 1999; Haugen and Vøllestad, 2001; Kinnison and 230 Hendry, 2001), indicating either strong selection, high levels of genetic drift, or strong 231 phenotypic plasticity. Since these first results were based on measurements of fish sampled 232 in the field it was impossible to conclude what was the driving force leading to the
233 divergence. Other approaches were needed.
234 A reasonable question to ask was to what degree differences in intensity and 235 selectivity of harvesting of grayling could select for different maturation schedules? For 236 example, we observed that in the lake with the most intensive fishing activity, and thus 237 highest adult mortality, all fish seemed to mature at the same young age. This was in the 238 time period when then first major studies on the evolutionary effects of selective harvesting 239 were being published (Rijnsdorp, 1993; Law, 2000; Grift et al., 2003; Olsen et al., 2004). It
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240 was clearly timely to ask questions about how important harvesting selection could be for 241 explaining differences in maturation schedules. We asked if harvesting intensity differed 242 among the various lakes. Harvesting intensity was estimated as the total number of gill net 243 nights used annually. Large differences in fishing effort clearly led to differences in adult 244 mortality among the populations (Haugen and Vøllestad, 2001; Haugen and Vøllestad, 2002).
245 These large differences in adult mortality were also correlated with the observed pattern of 246 age at first maturation among these populations (Haugen and Vøllestad, 2002). Various 247 reproductive traits also differed among populations, however there was no clear differences 248 in growth rate among populations.
249 A second highly relevant question was to what degree early development could drive 250 these differences? Grayling spawn in tributaries experiencing highly divergent
251 environmental conditions during spring and early summer. Based on temperature 252 measurements during spring in these locations we knew that temperature profiles were 253 different. Using field experiments, Haugen (2000a) investigated how egg mortality, survival 254 probability from hatching to swim up, and early growth rate varied in eight populations. He 255 observed large differences in most of these traits, but it was difficult to pin-point if these 256 differences were plastic or evolutionary in origin. The phenotypic divergence rates were, 257 however, large. It is important to keep in mind that the various populations have had a very 258 short time period in order to evolve genetically based phenotypic differences (8-28
259 generations as estimated by Haugen, 2000a). The evolution - we have often used the term 260 contemporary evolution - has been fast. Genetically-based studies were clearly needed to 261 better understand if divergence was due to drift, plasticity or adaptive evolution.
262 The first such endeavour used classical quantitative genetics approaches by
263 performing common garden experiments (Falconer and Mackay, 1996; Roff, 1997). Using a 264 classical full-sib half-sib design, we investigated a number of early life history traits in 265 embryos from three different populations. Gametes were collected in the field, and 266 transported to the aquaculture facility at the University of Oslo for controlled fertilization 267 and experimentation under three different temperatures (Haugen and Vøllestad, 2000).
268 These temperatures were chosen to mimic temperatures under early development in the 269 three different populations. Using this approach, we could analyse norms of reaction
270 (Stearns, 1992; Hutchings, 2011), and ask if there were significant genotype-by-environment 271 interactions? In general, we found significantly different reaction norms for most of the
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272 studied traits, indicating genetically based differences in the traits (Haugen and Vøllestad, 273 2000). Further, for some traits we found significant levels of additive genetic variance. These 274 traits were thus heritable and potentially able to respond to selection. For some traits we 275 also observed that the populations seemed to "do better" at the temperature experienced in 276 nature. This prompted us to suggest that differentiation was due to local adaptation.
277 However, as mentioned earlier, while such observations show that the populations have 278 evolved different phenotypes, it is not sufficient evidence to conclude there has been 279 adaptation as a response to directional selection. The results only indicate adaptation.
280 Clearly, different genetic approaches were needed.
281 At that time, a number of microsatellite markers for grayling had been developed 282 (Koskinen and Primmer, 2001). Using these new tools, and based on the results from the 283 common garden experiments, it was possible to investigate to what degree the phenotypic 284 differences observed among the populations were due to genetic drift or selection. This was 285 done using the classical Fst – Qst comparison (Whitlock, 2008; Whitlock and Guillaume, 286 2009; Leinonen et al., 2013). The logic behind this comparison is that population divergence 287 in assumedly neutral molecular markers such as microsatellites (as estimated by Fst), can be 288 used as a proxy for the level of neutral divergence, which can be compared to genetic 289 divergence in functional, quantitative traits (as estimated by Qst). If Qst is greater than Fst, 290 non-neutral evolution can be inferred, potentially indicating positive selection (reviewed by 291 Whitlock 2008). Pairwise estimates of (assumedly neutral) genetic differentiation were 292 measured as the fixation index Fst based on microsatellite data, whereas the pairwise 293 estimates of Qst were extracted from phenotypic traits measured during the common 294 garden experiment (Haugen and Vøllestad, 2000). These analyses indicated that natural 295 selection was likely the dominant diversifying agent in the evolution of these early life- 296 history quantitative traits. This was surprising, given the short time scale (around 20 grayling 297 generations) and the low level of genetic diversity in the populations due to repeated
298 founder effects (Koskinen et al., 2002a). The use of microsatellite markers for estimating the 299 neutral baseline in Fst – Qst comparisons has been questioned recently (e.g. Edelaar et al.
300 2011), however, the unique setup of the study system, whereby migration and mutation 301 could be excluded as potential causes of diversity, enabled the use of other approaches that 302 also supported natural selection as being a key driver in population divergence (Koskinen et 303 al., 2002a).
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304 Next-generation sequencing (NGS) technologies (Hoban et al., 2016; Flanagan et al., 305 2018) have dramatically broadened the scope for investigating the genetic basis for
306 evolutionary change and adaptation also in non-model organisms. These technologies can 307 improve the reliability of population genetic estimates as well as provide the means to 308 identify specific genes that have contributed to adaptation (Shafer et al., 2015). An initial 309 hurdle in applying NGS approaches in grayling was the lack of an annotated genome for 310 grayling itself or for a closely related species. We therefore first used proteomics approaches 311 prior to the availability of the Atlantic salmon Salmo salar genome sequence (Lien et al., 312 2016) as proteomics is not as reliant on having genome sequence information available (Diz 313 et al., 2012). Our first proteomics study aimed to describe the proteomic profiles of different 314 early life history stage grayling embryos (Papakostas et al., 2010). We constructed an all- 315 salmonid protein database for protein identification and used zebrafish Danio rerio gene 316 annotations for functional enrichment analyses. The main functions of the proteins 317 identified were as expected for the respective early life history stages indicating that
318 proteomic profiling at the population level was a viable approach in grayling. More advanced 319 proteomic experiments were then conducted to more directly investigate adaptive
320 processes. These are described in more detail later.
321 More recently, decreasing sequencing costs, combined with other factors such as the 322 publication of a high-quality assembly of the Atlantic salmon genome (Lien et al., 2016) and 323 other fishes, as well as improvements in de novo assembly procedures opened up new 324 possibilities for ‘omics approaches in grayling. Using grayling larvae reared in a common 325 garden experiment we employed an RNAseq/transcriptomics approach to compare over 326 16,000 annotated mRNA transcripts from grayling larvae originating from four populations 327 developing at two different temperatures (Mäkinen et al., 2018). We sampled and compared 328 embryos at a fixed physiological age; using degree-days as the metric for physiological
329 development (Neuheimer and Taggart, 2007). One of the main results from this analysis was 330 that the functions of a number of the identified transcripts could be grouped into ‘modules’
331 with similar expression patterns. Response to temperature (plastic effects) and population 332 differences in expression patterns were highly variable among the six identified modules, 333 and the plastic effects explained a larger proportion of the expression patterns than 334 population effects did (Mäkinen et al., 2018). Overall, the results indicated that plasticity 335 was a main driver of gene expression variance. We could not document strong signals of
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336 natural selection acting on specific transcripts using an Fst – Qst comparison in which
337 transcript expression levels were the phenotype, and the neutral Fst baseline was estimated 338 using SNPs. However, the plastic responses were population specific, consistent with what is 339 called Baldwin effects and genetic assimilation (Crispo, 2007). Plastic responses to new 340 environmental condition are expected to be prevalent during the early stages of adaptation 341 (Chevin and Lande, 2010; Chevin et al., 2010). Phenotypic plasticity itself can also evolve (Via 342 and Lande, 1985; Lande, 2009). The lack of support for a response to natural selection is in 343 contrast to some of our earlier research (Koskinen et al. 2002; Kavanagh et al. 2010;
344 Papakostas et al. 2014). It may be that selection on the transcript level is not as strong, or 345 that the low sample sizes used here make these analyses conservative, and thus it is 346 premature to conclude if these differences in gene expression are due solely to neutral 347 processes.
348
349 Investigating local adaptation with gene flow
350 The studies presented this far have included grayling from different lake systems where 351 there was no opportunity for present-day gene flow among the different populations. Thus, 352 gene flow could not hinder adaptation to local conditions. However, we also had the
353 opportunity to study a system where gene flow clearly is possible and also expected. In 354 Lesjaskogsvatnet, one of the lakes included in the abovementioned studies, grayling spawn 355 in numerous tributaries with divergent environmental conditions, potentially presenting 356 very different selection pressures.
357 As already noted, the tributaries to Lesjaskogsvatnet (Figure 1) differ in size and in 358 how they heat up during spring. Based on measurements of temperature and stream width 359 (and thus water flow) they can be classified into two distinct categories: small and warm 360 (SW) or large and cold (LC) (Gregersen et al., 2008). The LC tributaries tend to be facing to 361 the north, and are fed by large high-elevation snow packs. This leads to intense snow melt 362 and increasing water flow with increasing air temperatures during spring and early summer.
363 The SW tributaries are mainly south-facing, and drain landscapes where snow-melt are 364 earlier leading to a more rapid warming of the stream water. These smaller tributaries 365 respond rapidly to rainfall, and tend to be unstable.
366 Grayling are exposed to these different environmental conditions solely during the 367 early life history stages as eggs, embryos and larvae, and later as they are spawning during
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368 short periods each spring. Otherwise the grayling from all the tributaries utilize the lake 369 itself, and experience more or less the same biotic and abiotic conditions throughout most 370 of their lifetime. Grayling mature for the first time at an age of 3-5 years (Haugen and 371 Vøllestad, 2001). Even if fish tend to have limited home ranges in the lake, they may make 372 long excursions (Bass et al., 2014). Thus, there is little opportunity for differential selection 373 for the various populations during the lake-dwelling phase. Therefore, temporal variation in 374 selection pressures while in the lake will affect the different spawning populations in the 375 same way. One such selection process is harvesting by gill nets. The fishing activity and the 376 mesh sizes of the gill nets that are used has changed over time and seems to have impacted 377 on the grayling life history.
378 We were able to acquire historic as well as recent samples of grayling scales and 379 otoliths with associated information on fish size, and time of capture (Haugen and Vøllestad, 380 2001). In addition, we summarized all available information on harvest regulations and 381 practices such that it was possible to quantify what kind of mesh sizes of gill nets were used 382 in the local fishery. Gill nets are highly selective (Hamley, 1975), and are expected to have 383 evolutionary effects when fishing effort is high. We found that grayling length at age
384 decreased from 1923-1981, and increased sharply thereafter (Haugen and Vøllestad, 2002).
385 This could be linked to changes in mesh size, and thus changes in selectivity. During the time 386 with decreasing growth rates, also age and length at maturation decreased. Based on this 387 we also found a general shift in the maturation reaction norm (estimated following Heino et 388 al., 2002). In addition, we observed that grayling spawning in SW tributaries on average 389 produced larger eggs than grayling spawning in LC streams, after adjusting for fish size 390 (Gregersen et al., 2008). This divergence can both be evolutionary and plastic in origin.
391 The juvenile grayling individuals drift with the water current from the various 392 tributaries into the lake during their first summer of life. Since timing of spawning and early 393 egg and embryo development is temperature dependent, the larvae originating from 394 different tributaries will enter the lake at different times. Spawning timing may differ by 395 more than a month. When the larvae enter the lake, they have to efficiently feed and grow 396 in order to survive the long period of ice cover. This could potentially lead to strong selection 397 for fast growth, in particular for larvae originating from the LC tributaries where
398 development is slower. We thus expected that potential signals of local adaptation would be 399 strong during this stage.
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400 In a common-garden experiment, we exposed eggs and developing embryos from 401 two SW and two LC tributaries to one common temperature (Kavanagh et al., 2010). Here, 402 we investigated the growth patterns from fertilization until the yolk sac was completely 403 converted into body tissue. Embryos from the LC tributaries grew faster than those from the 404 SW tributaries, and they also had higher yolk conversion efficiency (how yolk mass is
405 transformed to body mass). By doing histological analyses of the embryos we also found that 406 the LC embryos had larger muscles (muscle fibre area) at a given age and size than the SW 407 embryos. In contrast, the skeletal development was delayed in the LC relative to the SW 408 embryos, indicating a trade-off between muscle growth and structural development (bone).
409 All these results, and the fact that embryo from the two LC and the two SW tributaries 410 exhibited the same (parallel) development, indicates that the trait differences are due to 411 directional selection. Qst – Fst comparisons also suggested this.
412 We followed up this study with a new common garden experiment, but now at three 413 different temperatures (Thomassen et al., 2011). This reaction norm approach allows for 414 testing for genotype-environment (G*E) interactions. We found significant G*E interactions 415 for early development, with larval growth being faster in LC populations under cold
416 treatment. Clearly, the variation of some of the traits has a genetic component.
417 The strong signal of local adaptation observed in these studies indicates that grayling 418 in the different tributaries exhibit natal homing. Natal homing is commonly observed in 419 salmonid fishes in general (Hendry et al., 2004), and is also suggested to be common in 420 grayling (Kristiansen and Døving, 1996). We have not investigated the level of natal homing 421 directly. However, by sampling mature grayling during the spawning period in the different 422 tributaries it is possible to estimate the level of potential gene flow among populations using 423 neutral genetic markers. We here emphasize that such a sampling protocol, where mature 424 fish are sampled during the spawning period, does not necessarily estimate gene flow.
425 Individual fish may make temporary forays into non-natal tributaries during their search for 426 the appropriate spawning location (Keefer and Caudill, 2014). Further, dispersers may have 427 lower reproductive success than locals (Mobley et al., 2019). Using a set of eight
428 microsatellites we estimated genetic differentiation among 12 sub-populations sampled 429 during one particular spawning season (2005) (Barson et al., 2006). Overall, genetic diversity 430 was very low, and there were signals of recent bottlenecks in most sub-populations. By 431 comparing pairwise estimates of genetic differentiation (Fst) we investigated to what degree
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432 genetic differentiation, and thus gene flow, was related to geographic distance (isolation by 433 distance – IBD; Wright, 1943) or isolation by time (IBT; Hendry and Day, 2005). Geographic 434 distance was measured as the shortest waterway distance between tributaries/spawning 435 locations whereas temporal or time distance was measured as the estimated pairwise 436 differences in spawning time (day of spawning onset) in the different tributaries. We 437 detected a weak but significant signal of IBD, but no signal of IBT.
438 The set of microsatellites used in this analysis was limited (Barson et al., 2006). We 439 therefore developed additional markers for more detailed investigations of genetic structure 440 (Junge et al., 2010). Using 19 microsatellite markers, and samples collected over several 441 years and locations, we investigated fine-scale population structuring in time and space in 442 more detail (Junge et al., 2011). The main result in this study confirmed that overall, there 443 was a significant IBD structure; however, the structuring was not stable among years. In 444 many of the populations that we sampled it seemed like migration outweighed genetic drift, 445 and population bottlenecks were also identified in the majority of the populations. Overall, 446 this indicates that the potential for gene flow differs among years and populations. This 447 leads to the questions of whether the probability for a grayling individual to home or stray is 448 influenced by environmental factors. A highly relevant factor that might constrain or
449 facilitate gene flow in this way is timing of spawning as timing of spawning in a given
450 tributary depend on the temperature profile during spring. Spawning on average happened 451 10 days earlier in small and warm tributaries relative to the large and cold tributaries, with 452 large variation among tributaries and among years within tributaries (C. Junge, personal 453 communication). Such large among-year variation in timing of spawning in the various 454 tributaries lead to among-year variation in opportunity for gene flow between populations.
455 What is fascinating is that the populations seem to have adapted to the overall temperature 456 conditions even under these potentially constraining conditions. This supports the view 457 presented by Tigano and Friesen (2016) that local adaptation can both be promoted and 458 maintained by gene flow, but also that the genetic architecture plays a fundamental role.
459 Various genomics approaches may be needed in order to understand the underlying process 460 of adaptation in this (and other) systems.
461 Taking advantage of the samples collected in an earlier common garden experiment 462 (Thomassen et al., 2011), we examined the protein expression profiles of larvae sampled at a 463 particular developmental stage. Larvae were from two large and cold and two small and
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464 warm tributaries, and had developed at two temperatures (Papakostas et al., 2014). Due to 465 cost constraints, sample sizes were low and thus the variation in expression of the 790 466 proteins characterised for each individual was simplified to a single principle component, 467 which we term its “protein expression profile”. Both plastic (protein expression changes in 468 different temperature treatments by the same populations) and evolutionary (expression 469 differences between different populations in the same temperature) responses were 470 observed. Of particular interest was the observation that the level of gene expression 471 change was constrained by the level of molecular pleiotropy (number of protein-protein 472 interactions or Gene Ontology biological processes). Genes with low molecular pleiotropy 473 levels were the main drivers of both plastic and evolutionary expression changes. This 474 highlights the importance of understanding the genetic architecture when investigating 475 adaptation at the proteome scale. In a detailed follow-up investigation of the protein 476 expression data we found that expression reaction norms at the plastic and evolutionary 477 level were positively correlated (Mäkinen et al., 2016). Overall this indicates that, contrary to 478 studies in some other fish species (Ghalambor et al., 2015), the plastic responses that we 479 observed in grayling are adaptive, and that the plastic responses are moving the populations 480 closer to the various thermal gene expression optima. Further, we found that differentially 481 expressed genes were mostly related to muscle activity/development. This fits well with our 482 observations at the phenotypic scale (Kavanagh et al., 2010; Thomassen et al., 2011).
483
484 Merging “top-down” and “bottom-up” approaches
485 Approaches in ecological and evolutionary genomics aimed at linking genotype and
486 phenotype can be classified as those that either start by identifying phenotypic differences 487 and attempting to understand their genetic basis (“top-down”, or “forward genetics”), or 488 starting with genetic differences (e.g. identified by genome scans), and attempting to link 489 these with different phenotypes (“bottom-up” or “reverse genetics”) (Barrett and Hoekstra, 490 2011). However, such approaches often lack an understanding of the environmental factors 491 maintaining the phenotypic diversity i.e. the relative fitness of the respective phenotypes in 492 the wild. Linking bottom-up and top-down approaches can provide this missing information 493 about whether selection acts on the traits under investigation (Barrett and Hoekstra, 2011) 494 especially when the critical environmental factors are known.
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495 To date, our ‘omics studies have been able to provide information on population- 496 level processes, but have lacked the power to identify specific candidate genes, but the 497 characterisation of the grayling genome sequence (Varadharajan et al., 2018; Sävilammi et 498 al., in press) will enable more comprehensive population genomic approaches to possibly 499 identify specific genome regions that may contain genes important in the rapid adaptation 500 process. This resource will provide information that can help understand the rediploidization 501 process following the salmonid whole-genome duplication event. It will also facilitate
502 identification of potentially more subtle genomic modifications such as methylation
503 (epigenetic) modifications that may be important for phenotypic adaptation (e.g., Baerwald 504 et al., 2016).
505
506 Some concluding thoughts
507 This set of studies started as a relatively traditional study of fish ecology, with an applied 508 focus (interaction among species, effects of hydropower development), but it quickly 509 changed into a curiosity-driven long-term program. Curiosity driven research is at times 510 difficult to fund, in particular when the study object is not a model species or a species of 511 great economic interest. In spite of this, we have at times been lucky – other times not – in 512 acquiring funding to follow up ideas and questions. This has, however, led to a research 513 program that has not followed a paved highway, but has followed a long and winding road 514 with lots of bumps and barriers. This should be a familiar tale for many ecologist and 515 evolutionary biologists.
516 Long term mark-recapture methods would have been very useful in this study 517 system. However, this requires long term installations and infrastructure, as well as funding 518 for human resources. We have not been successful in financing this, and have had to focus 519 on more short-term and ad hoc types of projects. Some have also failed. For example, we 520 have tried to use reciprocal transplant experiments to investigate local adaptation during 521 egg and embryo development. This was logistically challenging, particularly in small streams 522 that respond very rapidly to changes in rainfall and temperature. Further, attempts to 523 produce large and cold x small and warm tributary hybrids have usually failed, probably for 524 technical reasons.
525 Based on the experiences from the transplant experiment we focused our effort on 526 common garden experiments. Success depends on good quality gametes being collected at
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527 the right time, handled properly, and luck during the experimental period (stable
528 experimental facilities, no diseases, good sampling protocols). This was not always the case.
529 Further, we lost large number of samples due to a major freezer (and subsequent alarm 530 system) failure. That happens, but it also made us focus on proteomics first, and then 531 transcriptomics. Our initial plan was the other way around.
532 Where to from here? More recently we have had the good fortune to have funding 533 for both genomic and ecological studies. In the near future, we hope to scale up the
534 genomics approaches to learn more about the potential significance of epigenetics in rapid 535 adaptation. The improved grayling genome (Sävilammi et al., in press) that allowed to
536 construct a chromosome level assembly, will enable population genomics studies of material 537 thus far only investigated with 19 microsatellite loci and possibly, eventually, allow us to 538 connect genotype, phenotype, and fitness. Achieving this aim will require us to continue our 539 strategy of merging ecological and evolutionary approaches with genomics.
540 Studies like ours may have important implications for management and
541 conservation. For proper management it is important to properly delineate the relevant 542 evolutionary units. However, it is still unclear what is the best approach to do so (Palsbøll et 543 al., 2007). Merging of population genetic methods with demographic studies seems to be 544 the most common approach. However, basing population genetic studies on only neutral 545 genetic markers many lead to loss of important information. Our studies have shown that 546 functionally relevant differences may evolve even if the genetic differentiation detected 547 using neutral genetic markers is low. This seems to be the case in a number of fish species.
548 For example, significant differentiation at linked loci (chromosomal inversions) is important 549 for migration propensity in Atlantic cod Gadus morhua (Kirubakaran et al., 2016; Sodeland et 550 al., 2016) and in rainbow/steelhead trout Oncorhynchus mykiss and Chinook salmon O.
551 tshawytscha (Prince et al., 2017). In Atlantic salmon variation at the vestigial-like family 552 member 3 gene (VGLL3) explain 39% of the phenotypical variation in age at maturity (Barson 553 et al., 2015). Clearly, classical population genetic studies based on a narrow sample of
554 neutral genetic markers is not sufficient to properly delineate and understand what are the 555 relevant evolutionary units. More comprehensive and holistic approaches are needed.
556
557 Acknowledgements
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558 The different studies presented here were financed by various sources; the Norwegian 559 Resource Council, University of Oslo, Academy of Finland, University of Helsinki, University 560 of Turku, and the Marie Curie EST program. The authors also acknowledge the EU-FAIR 561 network TROUTCONCERT (1998-1999), and in particular Michael Hansen and Kjetil Hindar, 562 who invited CRP to attend one meeting as an external guest which lead to him making the 563 first contact with LAV about grayling population genetics collaboration. Further, Thrond 564 Haugen was instrumental in initiating and getting the various projects running. His local 565 contacts were of great help. A very large number of people (local helpers, national and 566 international master students, PhD-students, post docs, researchers) have over the years 567 been involved in the study. They are all mentioned either as authors of the various papers, 568 or acknowledged there. We are indebted to them all.
569 570 571
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572 573
574 References
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