Faculty of Biological and Environmental Sciences University of Helsinki
OF THE INTERACTIONS BETWEEN EYE FLUKE PARASITES AND SALMONID FISHES
Hanna Kuukka-Anttila
DOCTORAL DISSERTATION
To be presented for public discussion with the permission of the Faculty of Biological and Environmental Sciences of the University of Helsinki, in Auditorium
1041, Biocentre 2 Building, on the 9th of October 2020at 12 o’clock.
Helsinki 2020
Supervised by
Docent Nina Peuhkuri | Natural Resources Institute Finland (Luke) Docent Antti Kause | Natural Resources Institute Finland (Luke) Reviewed by
Professor Anti Vasemägi | Swedish University of Agricultural Sciences Professor Anssi Vainikka | University of Eastern Finland
Opponent
Docent Katja Pulkkinen | University of Jyväskylä, Finland Custos
Professor Craig Primmer | University of Helsinki, Finland
The Faculty of Biological and Environmental Sciences uses the Urkund system (plagiarism recognition) to examine all doctoral dissertations.
ISBN 978-951-51-6455-1 (pbk.) ISBN 978-951-51-6456-8 (PDF) Unigrafia
Helsinki 2020
ABSTRACT
In addition to their major biological significance, parasites interest scientists due to their importance in agriculture, aquaculture and medicine. In this thesis I look at local adaptation between salmonid fishes and Diplostomatidae parasites as well as genetic differences in rainbow trout resistance and tolerance against Diplostomum sp. parasite infection. I also study phenotypic and genetic correlations between fish resistance and tolerance and other fitness-related traits to find possible trade-offs. The results are combined with the literature on host-parasite coevolution to gain more understanding on how host-parasite dynamics work and how the health, welfare and productivity of the fish could be further enhanced in captive populations.
The results indicate local adaptation of parasites and genetic differences in fish resistance against eye flukes in salmonid fishes. The heritability of resistance was estimated to be of moderate degree (h2 = 0.25–0.35) in farmed rainbow trout. There was genetic variation also in fish tolerance against eye flukes, contradicting the hypothesis that tolerance traits should quickly become fixed.
Phenotypic and genetic correlations between parasite resistance, tolerance and other fitness-related traits were estimated to find out possible trade-offs, and also for the purposes of the rainbow trout breeding programme. There was no indication of trade-offs between fish resistance and the other studied traits.
Fish with lower resistance tended to grow fast during the first months of their life but over the time, parasite-induced cataracts blinded the fish and growth slowed down. Survival was also reduced among the families having lower resistance and more severe cataracts. Yet, a trade-off between fish performance in the absence of parasites and tolerance emerged when parasite load increased. The fish that had the highest weight and the lowest mortality in the absence of parasites tolerated the parasitism the worst. Resistance and tolerance were not genetically correlated, indicating that the two defence mechanisms are independent from each other. In the arms-race of coevolving host and parasite populations, host resistance and tolerance have different consequences. Resistance favours an increase in parasite infectivity and virulence, whereas tolerance does not cause such selection pressure on parasites. The results of my thesis give new information to improve rainbow trout breeding stock. Resistance and tolerance can both be selected for without compromising productivity.
My deepest gratitude goes to my supervisors Nina Peuhkuri and Antti Kause.
Nina, thank you for taking me into the IKP group back then and giving me the possibility for this thesis. I admire your knowledge and expertise and your encouragement has been priceless to me. Antti, thank you for the opportunity to use the valuable rainbow trout breeding program data and for sharing your brilliant knowledge of animal genetics. You have been really patient answering hundreds of questions. Thank you both for everything!
I have been privileged to do research with several great colleagues and co- authors in Natural Resources Institute Finland (Luke), University of Jyväskylä and University of Joensuu. I am grateful to you all!
Professor Ellen Bjerkås is thanked for teaching me to use slit-lamp to categorise cataracts and for all the knowledge of fish ophthalmology shared in this project. Thank you also Eva Brännäs for guiding us in northern Sweden.
This research was done in the premises of Natural Resources Institute Finland.
My warmest thanks to you all working there, who helped one way or another!
Especially Irma, Eila, Tuija, Jorma, Matti, Esa, Tane, Pasi and the others in Enonkoski and Tervo.
I am honestly grateful for the reviewers of this thesis, professors Anti Vasemägi and Anssi Vainikka for several valuable comments and suggestions.
My warmest thanks also go to my Thesis Advisory Committee, Heikki Hirvonen and Jouni Taskinen. I knew that I could trust your help. I also want to thank the staff in the former Department of Ecology and Evolutionary Biology. The late Esa Ranta is thanked for the opportunity to join IKP and the former head of the department, Veijo Kaitala, for all the help and support.
Perttu Seppä, you determinedly guided me through the last hard steps. I really appreciate it – thank you!
IKP guys, Annu, Ansku, Kata, Katja, Katriina, Nina, Tiina, Antti, Lasse and the others. Thank you for the warm welcome to IKP, your true friendship and all the encouragement during these years. Nowadays IKP means to me a couple of lifetime friends and I really appreciate that. Especially Ansku, this thesis would have never finished without your encouragement – thank you!
I also want to thank my present employer and colleagues at the Food Safety Authority; ladies in the animal diseases’ section, bosses Sirpa and Terhi , the others in the “kaksikko” and the “fishy" colleagues: Mia, Satu, Pia, Perttu,
Marjukka and Riikka. The atmosphere there in sometimes hectic office has always been good and every morning it has been nice to come to work. This thesis has been my hobby for the last 13 years. Thank you for giving me the leave of absence to finally finish this and taking care of my duties meanwhile.
I really appreciate you all!
My deepest gratitude belongs to my family and friends who have not much to do with this thesis but mean everything to me.
I am blessed to have many precious friends. You know who you are. “No good thing is pleasant without friends to share it.” I hope we can raise a toast sooner or later. You are priceless to me!
Äiti ja isä, jotka olette tämän väitöskirjatyön aikana muuttuneet mummoksi ja ukiksi; vahvat juuret antavat voimia koko elämän, niistä kaunein kiitos!
Mikko, Sanna ja lapset, Salme ja Seppo, Kirsti ja Raikka, Marika, Jaska, serkut ja te kaikki muut - kiitos että jaatte osan elämäänne, olette rakkaita.
Lopuksi kaikkein kaunein kiitokseni kotiväelle. Saku, kiitos tuestasi ja siitä, että jaksat myötä- sekä vastamäet. Olisin eksyksissä ilman sinua. Leo ja Tom, olette maailman rakkaimmat ja tärkeimmät äidille aina.
This work has mainly been funded by Nordisk Ministerråd, The Finnish Cultural Foundation / South Karelia Regional Fund, The Finnish Foundation for Nature Conservation, Employment Fund, and the University of Helsinki dissertation completion grant.
Abstract ... 3
Acknowledgements ... 4
Contents ... 6
List of original publications ... 8
1 Introduction ... 9
1.1 Natural selection and local adaptation ... 9
1.2 Trade-offs ... 10
1.3 Fish as hosts of parasites ... 11
1.4 Fish defences against parasites ... 12
1.4.1 Resistance ... 12
1.4.2 Tolerance ... 12
1.5 Resistance vs. tolerance ... 13
1.6 Aquaculture environment and host-parasite interactions ... 14
2 Aims of the thesis ... 16
3 Material and methods ... 17
3.1 Study fish ... 18
3.1.1 Atlantic salmon (I) ... 18
3.1.2 Arctic charr (I) ... 18
3.1.3 Rainbow trout (II-IV) ... 18
3.2 Study parasites ... 19
3.2.1 Diplostomum (I-IV) ... 19
3.2.2 Tylodelphys clavata (I) ... 20
3.3 Fish eye examination ... 20
3.3.1 Eye lens and vitreous body examination under microscope (I) .. 20
3.3.2 Eye lens examination of live fish (II-IV)... 20
3.4 Quantitative genetic analyses (II-IV) ... 22
4 Main results and discussion ... 24
4.1 Locally adapted parasites and salmonids ... 24
4.2 Genetic variation in rainbow trout resistance against diplostomum infections ... 25
4.3 Phenotypic and genetic correlations of different life history traits with resistance ... 26
4.4 Tolerance and its correlations with other fitness-related traits ...28
5 Conclusions ... 30
References ... 32
This thesis is based on the following publications:
I Voutilainen, A., Valdez, H., Karvonen, A., Kortet, R., Kuukka, H., Peuhkuri, N., Piironen, J., & Taskinen, J. (2009). Infectivity of trematode eye flukes in farmed salmonid fish—effects of parasite and host origins. Aquaculture, 293(1-2), 108-112.
II Kuukka-Anttila, H., Peuhkuri, N., Kolari, I., Paananen, T., &
Kause, A. (2010). Quantitative genetic architecture of parasite- induced cataract in rainbow trout, Oncorhynchus mykiss.
Heredity, 104(1), 20-27.
III Vehviläinen, H., Kause, A., Kuukka‐Anttila, H., Koskinen, H., &
Paananen, T. (2012). Untangling the positive genetic correlation between rainbow trout growth and survival. Evolutionary applications, 5(7), 732-745.
IV Kuukka-Anttila, H., Peuhkuri, N., Kolari, I., & Kause, A.
Genetically determined resistance and tolerance to Diplostomum sp. parasite in farmed rainbow trout. Aquaculture Research (in press).
The publications are referred to in the text by their roman numerals.
The original articles are reprinted with the permission of the copyright holders.
1 INTRODUCTION
Parasitism is suggested to be the most common life strategy in the world (Thompson, 1994; Windsor, 1998). It has been estimated that around 40 % of all the organisms are parasites (Dobson, Lafferty, Kuris, Hechinger, & Jetz, 2008) and probably every macroscopic species is a host of parasites (Price, 1980). An average mammalian host species appears to harbour two cestodes, two trematodes, and four nematodes, and an acanthocephalan is found in every fourth mammalian species examined (Dobson et al., 2008). Parasites evolve to maximise their own success. Host, on the other hand, coevolve with parasites. Hosts have developed resistance, tolerance and adapted to avoid behaviourally some parasites. Due to parasites’ usually better evolutionary potential, their evolutionary strategies have been seen driving the host- parasite coevolution (Ebert & Hamilton, 1996; Greischar & Koskella, 2007;
Kaltz & Shykoff, 1998; Lively & Dybdahl, 2000).
1.1 NATURAL SELECTION AND LOCAL ADAPTATION
In each population, natural selection should lead to evolution of traits that provide an advantage under local environmental conditions (Darwin, 2004).
In co-evolving host and parasite populations this is expected to lead to arms- race, ”Red Queen dynamics”, between parasite infectivity or virulence and host resistance. When the host develops its resistance, the parasite must adapt and develop its infectivity and/or virulence to keep on living in or on the host (Van Valen, 1973). Parasites commonly have better prerequisites to adapt to their local hosts than vice versa, particularly due to their shorter generation times and larger population sizes and migration potential (Ebert & Hamilton, 1996;
Greischar & Koskella, 2007; Kaltz & Shykoff, 1998; Lively & Dybdahl, 2000).
Without environmental stochasticity, this process should lead to higher fitness of parasite populations on the sympatric host population compared to other populations. The course of the host-parasite coevolution may, however, be determined by several factors depending on the species and their environment. Local adaptation of the parasites is not a rule. Kaltz & Shykoff (1998) reviewed 38 studies on local adaption and found out that in half of the studies, local adaptation of parasite had not been detected. Furthermore, in some studies, local adaptation of the host seems to override the adaption of the parasite (Kalbe & Kurtz, 2006).
In habitats with multiple host populations, a parasite with a narrow host range may have more advantage of adapting to one host species than a parasite with several hosts (Lajeunesse & Forbes, 2002). The opposite can also be assumed.
If hosts are prone to several pathogens, like they often are, using lots of
resources in resisting one parasite species may not be advantageous. In metapopulations, migration, i.e. gene flow, is one important factor influencing the host-parasite coevolution. Higher gene flow to a host or a parasite population can lead to better local adaptation of that population (Gandon, Capowiez, Dubois, Michalakis, & Olivieri, 1996). Variable parasite infectivity and virulence (reviewed in Dybdahl & Storfer, 2003) and different objectives of resistance (Gandon & Michalakis, 2000) further affect the direction of the coevolution. By different objectives of resistance Gandon & Michalakis (2000) mean, e.g. resisting the infection or minimizing parasite production. The complexity of the influencing factors on host-parasite coevolution may make it impossible to build any common hypothesis for several species or environments (reviewed in Kaltz & Shykoff, 1998). Furthermore, since coevolution exists only in sympatry, the infectivity and/or virulence of a parasite on its allopatric host is difficult to predict.
1.2 TRADE-OFFS
“Trade-offs represent the costs paid in the currency of fitness when a beneficial change in one trait is linked to a detrimental change in another” (Stearns, 1989). Trade-offs can be seen at the phenotypic level when there are limited resources to be used for example for resistance and other fitness-related traits like reproduction, e.g. sexual ornamentation or sperm quality or growth (Liljedal, Folstad, & Skarstein, 1999; reviewed in Sheldon & Verhulst, 1996;
Skarstein & Folstad, 1996). Phenotypic trade-offs may, however, be problematic to reveal if there are among-individual differences in resource acquisition and allocation. This may result in positive correlations among individuals, some individuals having high amounts of resources (e.g. due to higher feed intake) to allocate to competing body functions – the effect called
“big house, big car” (Reznick, Nunney, & Tessier, 2000). Hence, the data across individuals does not necessarily show a trade-off, even if resources were traded-off within individual level (Van Noordwijk & de Jong 1986; Simmons, Lüpold, & Fitzpatrick, 2017). Further, a third trait may also have an effect on the correlation between two traits and hide a trade-off (Remick, 1992).
Genetic trade-offs are considered appropriate to give evidence of trade-offs between life-history traits because they are free of environmental variation (Remick, 1992). Genetic trade-offs, i.e. constraints on life-history evolution, mean that a gene (antagonistic pleiotropy) or a set of linked genes (linkage disequilibrium) will have a favourable effect on one trait and an unfavourable effect on the other trait (Falconer, 1989). This involves that selection for one trait will pull along the correlated, undesired trait. Hypothetically, without genetic trade-offs, directional selection would drive any fitness-improving trait to the favour of extreme phenotypes and to a loss of trait variance in a
population (Stearns, 1989). Therefore, trade-offs have been seen as important factors maintaining genetic variation.
Trade-offs in the host-parasite relationships are involved e.g. in immunocompetence handicap hypothesis that includes a trade-off that explains the dual role of male androgens, on the one hand, in producing sexual ornaments to attract females, and on the other hand, in suppressing immunological functions (Folstad & Karter, 1992; Kortet, Vainikka, Rantala, Jokinen, & Taskinen, 2003). Another example is the high virulence of parasites that can pose a trade-off; if parasites kill their host too rapidly, before getting transmitted, they reduce their own fitness (Anderson & May, 1982).
Genetic trade-offs are important constraints influencing evolution of traits both in the wild and in captive-selected farm animal populations. In animal breeding programmes, selected traits often include high production potential and resource utilisation, but also good health, fertility, easy management and good conformation. Hence, the genetic architecture of the population has to be studied carefully to find out the possible negative or positive genetic correlations between important life-history traits. For example, selection for fast growth may lead to serious problems in the long run if the gene or genes selected for are linked with some unwanted characteristics.
1.3 FISH AS HOSTS OF PARASITES
Like in many organisms, parasites are common in fish. Ectoparasites like lice, leeches and flatworms use hooks to attach themselves on fish skin or gills, and may use fish as an attachment ground, or eat fish mucus or skin, or suck blood and body fluids through the skin (Valtonen, Hakalahti-Sirén, Karvonen, &
Pulkkinen, 2012). Endoparasites such as flukes, roundworms, and protozoan, penetrate the epidermis or gills, or are ingested along food (Valtonen et al., 2012). In global aquaculture sector, parasites cause major concern. For example, mass occurrence of sea lice in fish farms has led to reduced production but also lower fish welfare and increased environmental problems in Norway, Chile and other salmonid farming countries (Aaen, Helgesen, Bakke, Kaur, & Horsberg, 2015; Costello, 2009). Annual loss caused by sea lice was estimated to be 436 M USD in 2011 in Norway alone (Abolofia, Asche, &
Wilen, 2017).
1.4 FISH DEFENCES AGAINST PARASITES
Fish have several possibilities to defend themselves against parasites. The simplest way of avoiding infection is to escape (reviewed in Barber, Hoare, &
Krause, 2000). Fish have been shown to escape for example Diplostomum metacercaria that float in water (Karvonen, Anssi, Hudson, Seppälä, &
Valtonen, 2004; Klemme & Karvonen, 2016). Similarly, warning systems of conspecifics infected with Diplostomum have been shown to lead to avoidance reaction (Poulin, Marcogliese, & McLaughlin, 1999). In addition to such behavioural defences, there are also physiological mechanisms that aid the fish in avoiding the harmful effects of parasites.
1.4.1 RESISTANCE
Physiological resistance mechanisms can be divided into innate and acquired mechanisms. Innate resistance is fast and less specific than acquired resistance and provides the first line protection mechanism against pathogens.
Physical barriers for pathogens, such as mucus on the skin of fish (reviewed in Jones, 2001), are an important part of it. Acquired resistance, on the other hand, is characterized by highly specific reaction systems based on lymphocytes, production of antibodies and immunological memory (Playfair
& Bancroft, 2004). The acquired immune response of poikilothermic fish is slow compared to the innate immune response (reviewed in Magnadttir, 2006). However, the innate mechanisms of fish have been shown to be more active and diverse than comparable components in mammalian species (reviewed in Magnadttir, 2006). Mounting of the adaptive response takes approximately two weeks in mammals and, depending on temperature, up to several weeks in fish (Whyte, Allan, Secombes, & Chappell, 1987). This slow mounting of the acquired resistance is especially useless against sporadic infections of parasites that escape from immune responses to eye lenses or brain of fish being thus only shortly exposed to the immune system (Wegner, Kalbe, & Reusch, 2007). In fish in general, innate resistance plays a proportionally greater role compared to vertebrates mainly due to the slower metabolic rate of poikilothermic animals (Du Pasquier, 1982).
1.4.2 TOLERANCE
Whereas resistance of the host can be defined as mechanisms reducing the parasite burden, tolerance minimises the fitness impact of parasites on the host (Svensson & Råberg, 2010). Resistance is often measured as host parasite prevalence. On the other hand, tolerance can be measured as host performance despite parasites; e.g. Råberg, Sim, & Read (2007) measured tolerance “by the extent to which anaemia and weight loss increase with increasing parasite burden.” On the other hand, e.g. Soares, Teixeira & Moita (2017) defined tolerance as “tissue damage control mechanisms that prevent
the deleterious effects of pathogens”. Tolerance can be defined in numerous ways from variation in behavioural adaptation to parasite damage to regulation of immune functions against parasite attack to minimize self-harm.
In coevolutionary studies, the principal difference between resistance and tolerance is, that unlike resistance, tolerance of the host does not harm the parasite (Råberg et al., 2007).
Plant scientists have used the concept of tolerance as a plant-host defence strategy for decades (Caldwell, Schafer, Compton, & Patterson, 1958; Koskela, Puustinen, Salonen, & Mutikainen, 2002). Råberg et al. (2007) imported the concept of tolerance to animal disease ecology. They referred to a study by Wambua et al. (2006) in which significant negative associations between α+- thalassaemia blood disorder and the incidence rates of severe malaria and severe anaemia were found in Kenyan children. Since then, review and opinion articles have discussed the mechanisms and epidemiological and evolutionary impact of tolerance and referred to earlier studies where differences in animal tolerance have been found (Medzhitov, Schneider, &
Soares, 2012; Råberg, Graham, & Read, 2008; Schneider & Ayres, 2008).
However, empirical studies done with the aim to study tolerance in animas are still quite few.
1.5 RESISTANCE VS. TOLERANCE
It is not useful for the host to maintain costly resistance mechanisms if the costs are higher than the benefits. Increasing host resistance reduces fitness of the parasite and thus the infection pressure in the environment. Consequently, it reduces the benefits of the host resistance, and then also the strength of selection for the resistance. Evolution of resistance is thus expected to be governed by negative frequency-dependent selection (Van Valen, 1973). That is, when parasite prevalence is high, resistance spreads through a host population, causing the decline of parasite prevalence. Provided that resistance is costly in the absence of parasitism, a reduction in the frequency of resistant host genotypes is expected when parasites are not present (Roy &
Kirchner, 2000). If a new gene arises in the parasite population, allowing the parasite to infect previously resistant individuals, the infection pressure raises again (Penn, 2001). According to the evolutionary theory of arms race (Van Valen, 1973), host resistance will lead to a continuous competition between hosts and parasites, i.e. to the “Red Queen coevolutionary dynamics”.
Host tolerance, on the other hand, does not put such selective pressure on parasites. If tolerance is high, costly resistance is unworthy. Tolerant individuals can be assumed to increase parasite fitness also by living longer, thus increasing parasite reproduction time. Evolution of tolerance is therefore expected to result in a positive feedback where parasite infection selects for
tolerant, rather than non-tolerant hosts, which in turn increases parasite prevalence (Roy & Kirchner, 2000). Even if tolerant individuals’ probability of dying of infection decreases, overall parasite number in the population may in fact increase (Baucom & de Roode, 2011). However, little is known of the cost of tolerance in animals. If tolerance means maintaining some sort of physiological mechanisms, it potentially also has costs.
Most theoretical models predict the maintenance of genetic variation in resistance but the fixation of tolerance along the course of host–parasite coevolution (Roy & Kirchner, 2000). Empirical studies showing this on animals are scarce, but Lefvre et al. (2010) suggested fixed tolerance (low genetic variance) in their study of the monarch butterfly (Danaus plexippus).
Furthermore, plant scientists have presented a theory that natural selection towards resistance and tolerance should favour either high tolerance and low resistance, low tolerance and high resistance, or intermediate values of both (Fornoni, Nunez‐Farfán, Valverde, & Rausher, 2004) because increasing tolerance should not increase the fitness of resistant individuals and vice versa (Fornoni et al., 2004). Plant scientists are well aware of tolerance and its consequences in the coevolution of plant hosts and their herbivores and parasites. In animal science, the scientific discussion about tolerance is rather new and studies of the effects of tolerance on host-parasite interactions are limited.
1.6 AQUACULTURE ENVIRONMENT AND HOST- PARASITE INTERACTIONS
Animal protein production for the growing humankind is one of the big challenges for the future. According to FAO (2018), aquaculture is the fastest growing food-producing sector in the world, fish constituting 80 Mt of the 110.2 Mt total aquaculture production. As stated in the latest report, annual growth rate of fish consumption has surpassed that of meat consumption from all terrestrial animals combined (FAO, 2018). Growing production units and denser fish populations in aquaculture create favourable conditions for parasites like eye flukes (Diplostomum sp.) in Finnish fresh water fish farms (Figure 1) (Kuukka, Peuhkuri, & Kolari, 2006) or sea lice (like Lepeophtheirus salmonis and Caligus elongatus) in Norway, Chile and other salmonid farming countries (Aaen et al., 2015; Costello, 2009).
Figure 1 Cataract prevalence in different fish groups in 8 Finnish fish farms (F1–F8). Group abbreviations: GR = grayling, SA = salmon, TR = trout, CH = arctic charr, LT = lake trout. Lake = fresh water migrating stock, sea =sea migrating stock. a–g=different stocks. 0+–7 = fish age at the time of the measurement. N = 39–150 (from Kuukka et al., 2006).
In populations of farmed fish, humans interfere with the host-parasite interactions, e.g. by practicing artificial fertilisation, medicating fish against pathogens, transferring hosts and parasites to new environments, vaccinating, and enhancing immunity by stimulants. On the other hand, humans offer parasites, for specializing in, host populations that are dense, having often low genetic variation at commercial on-growing farms (Janhunen et al., 2013). The farmed fish populations can also be exposed to stress-invoking conditions, such as netting, and have none or limited possibilities to escape the parasites.
Host-parasite coevolution is, however, in progress in aquaculture conditions too. Even if human impact is high, fish farms are ecosystems that may maintain parasite populations. This is because the common use of natural, unfiltered water, and often close contact with wild fish, support parasite success at farms. Medication is generally used but it is often inadequate to get rid of the parasites.
2 AIMS OF THE THESIS
We have shown in an earlier survey in Finnish freshwater fish farms the commonness of the cataracts in salmonid fishes and variation in cataract occurrence in different species and stocks (Fig. 1) (Kuukka et al., 2006). The found cataracts were mostly caused by Diplostomum sp. eye flukes. In this thesis, I studied further i) whether Diplostomum sp. infectivity varies between salmonid populations depending on the origin of the hosts and parasites and possible local adaptation. I was also interested in ii) whether there is within population genetic variation in resistance against this parasite. I also wanted to study iii) possible phenotypic and genetic trade-offs of resistance.
Furthermore, I was interested in finding out iv) whether fish families might vary in their tolerance against Diplostomum sp. Given that Diplostomum sp.
parasites cause major problems in fish farming, it was also my aim to study v) whether the resistance or tolerance of the fish produced for human consumption could be improved by selective breeding.
3 MATERIAL AND METHODS
To study population differences in susceptibility to Diplostomum sp. eye flukes (Trematoda: Diplostomatidae) and thereby parasite-induced cataracts (I), three salmon (Salmo salar) stocks were used originating from three different environments: Lake Saimaa in River Vuoksi catchment, River Iijoki and River Simojoki. The fish were experimentally infected with Diplostomum sp. parasite population that was considered as local for the salmon of River Iijoki and River Simojoki, but distant for Lake Saimaa salmon (Figure 2). All these three salmon stocks were also naturally infected by Tylodelphus clavata (Trematoda: Diplostomatidae) originating from Lake Ylä-Enonvesi in Lake Saimaa area. To correspondingly study population-wide differences in the infectivity of Diplostomum sp. eye flukes (I), Arctic charr (Salvelinus alpinus) from Lake Saimaa area, that were infected with three different Diplostomum sp. populations originating from Lake Huumojärvi (distant), Lake Pieni- Hietajärvi (local 1) and Lake Ylä-Enonvesi (local 2), were used.
Figure 2 Origins of the salmon stocks (Rivers Simojoki and Iijoki and Lake Saimaa), Arctic charr (Lake Saimaa) and parasites (Lake Huumonjärvi, Lake Pieni-Hietajärvi and Lake Ylä-Enonvesi).
The other three articles (II-IV) are based on studies carried out using rainbow trout (Oncorhynchus mykiss) originating from a selective breeding programme and their natural Diplostomum sp. infections.
3.1 STUDY FISH
3.1.1 ATLANTIC SALMON (I)
Two hatchery-reared Atlantic salmon stocks from northern-Baltic Sea (Simojoki and Iijoki) and a third hatchery stock, the landlocked Lake Saimaa salmon, were used in the first article of this thesis. All three stocks are genetically related due to common history thousands of years ago (Säisä et al., 2005), but the Lake Saimaa population has been landlocked and diverged since the ice age. All stocks are in the Red List of Finnish threatened species (Urho et al., 2019), the Baltic sea salmon is considered vulnerable and the Lake Saimaa salmon critically endangered (Urho et al., 2019). All three salmon populations are bred in captivity solely for conservation purposes of the species.
3.1.2 ARCTIC CHARR (I)
Like the landlocked Lake Saimaa salmon, also the Lake Saimaa Arctic charr has been landlocked since the ice age. It is also critically endangered and belongs to the Red List of Finnish threatened species (Salmi, Auvinen, Jurvelius, & Sipponen, 2000; Urho et al., 2019). The study population is bred in captivity solely for conservation purposes of the species.
3.1.3 RAINBOW TROUT (II-IV)
Rainbow trout is a foreign species to Finland and was brought for hatchery rearing from Northern America (Gross, Lulla, & Paaver, 2007; Kause, Ritola, Paananen, Eskelinen, & Mäntysaari, 2003). Farming of the rainbow trout started in Finland in 1960’s and nowadays comprises more than 90 % of the food fish production in Finland (Official Statistics of Finland, Natural Resources Institute Finland, 2019).
Natural Resources Institute Finland (Luke) maintains a rainbow trout selective breeding programme. The fish have been selected for good production, quality, and health traits since early 90's (Kause, Ritola, Paananen, Wahlroos, & Mäntysaari, 2005). Fish individuals with the desired characteristics are selected over all the other individuals and used as a breeding stock for the next generation. Pedigree data are collected and used in a quantitative genetics evaluation to identify which individuals are the
genetically superior. Pedigree data were also used in the quantitative genetic analyses of this thesis.
3.2 STUDY PARASITES
3.2.1 DIPLOSTOMUM (I-IV)
Diplostomum spp. (class Trematoda) parasites are common parasites of several species of fishes both in fresh and brackish water environments (Valtonen & Gibson, 1997). Somewhat fewer infections are found in the Baltic Sea brackish water compared to fresh waters (Cichowlas, 1961). Infection rate in fish decreases with a distance from a shore (Styczynska-Jurewicz, 1959), reflecting the occurrence of the Lymnea spp. freshwater snail populations serving as intermediate hosts for the parasite (Valtonen, Pulkkinen, Poulin, &
Julkunen, 2001). Taxonomy of different Diplostomum species is not exactly described (Valtonen & Gibson, 1997) and therefore, in this thesis, Diplostomum sp. (I, IV) or spp. (II, III) is used as a general name for the parasites found in fish lenses. In the article III, Diplostomum sp. class is mistakenly indicated to belong to Nematoda - it belongs to Trematoda. In literature, names D. spathaceum or D. spathaceum group are also collectively used to mean lens-dwelling Diplostomum sp. or spp. (Valtonen et al., 2012).
The life cycle of Diplostomum eye fluke is well known and described in several sources (Palmieri, Heckmann, & Evans, 1976; Valtonen et al., 2012; Valtonen
& Gibson, 1997). Fishes are secondary hosts for Diplostomum parasites.
Diplostomum cercaria penetrate fish skin, gills or cornea and find their way to the eye where cercaria develop to metacercaria. Metacercaria cause cataract and destroy fish vision by eating lens structure and producing metabolic wastes. Weak-sighted fish then tend to swim in the upper water layers, where they are easily caught by predators, like seagulls (Larus sp.) (Seppälä, Karvonen, & Valtonen, 2004; Seppälä, Karvonen, & Valtonen, 2005) which are the primary hosts for Diplostomum parasites. In bird intestine, metacercaria reproduce sexually and produce eggs which are released via birds’ feaces. If the eggs end up in water, hatched mirachidia flukes seek their way to snails (e.g. Lymnaea spp, Radix balthica, Myxas glutinosa). In snails, cercaria flukes are produced asexually and released in the water where they float waiting for a fish to swim by.
Diplostomum infection and parasite-induced cataract cause severe symptoms for fishes. Despite being an easy catch for gulls, also the feeding ability of fishes gets worse (Crowden & Broom, 1980; Owen, Barber, & Hart, 1993; Palmieri et al., 1976), which potentially results in great monetary losses for aquaculture industry.
Diplostomum sp. parasite count has been found to be directly related to cataract intensity the parasites induce (Karvonen, A., Seppälä, & Valtonen, 2004; Seppänen, Kuukka, Huuskonen, & Piironen, 2008). Therefore, both traits, parasite count and cataract score, were used to express fish resistance.
3.2.2 TYLODELPHYS CLAVATA (I)
The life cycle of Tylodelphys clavata is not as well-known as that of Diplostomum, possibly because Tylodelphys cannot be observed with bare eyes and possibly also due to its minor importance in fish farming. This parasite is found in vitreous body of the eye and it does not impair vision (Valtonen et al., 2012). Like other Diplostomatidae, the species has a life cycle including three hosts, with fish-eating birds acting as definitive hosts, snails as first intermediate hosts and fishes as second intermediate hosts (Valtonen et al., 2012). However, bird and snail host species are not exactly known (but see: Kozicka & Niewiadomska, 1960; Niewiadomska, 1960). T. clavata is very common in Finland and found especially in perch (Perca fluviatilis) and ruffe (Gymnocephalus cernuus) (Valtonen et al., 2012).
3.3 FISH EYE EXAMINATION
3.3.1 EYE LENS AND VITREOUS BODY EXAMINATION UNDER MICROSCOPE (I)
In the first article of this thesis, parasites in fisheyes were counted under a light microscope. Fish were anesthetised and killed by decapitation. The eyes were then dissected and burst lens and vitreous humour were compressed between glass plates.
3.3.2 EYE LENS EXAMINATION OF LIVE FISH (II-IV)
In the articles II and IV, eye flukes and cataract coverage in fish lenses were examined using KOWA SL-15 portable slit-lamp (Kowa Ltd., Tokyo, Japan).
Slit-lamp includes a microscope and a narrow, high-intensity beam of light that can be focused to shine into the eye. Different structures of the eye can be easily examined. It was possible to count eye flukes in lenses in which parasite infection was recent and where there were not tens of flukes grouped together.
When cataract was formed, the flukes could not be reliably counted in the opaque areas of the lens. Given the relationship between Diplostomum sp.
count and cataract score (Karvonen, A. et al., 2004; Seppänen et al., 2008) cataract coverage was used in the older infections to describe the level of
parasite infection (resistance). The categorisation of cataract coverage was done following the categorisation by Wall and Bjerkås (1999) (II, IV). In addition, score 5 was added to describe totally injured eye where the normal eye anatomy could not be seen (II). Eye fluke counts and cataract coverages from both eyes were summed to obtain a single eye fluke and cataract value for each examined individual.
A simple and rapid macroscopic examination of the cataracts, using a torch by a trained person, is in continuous use in the breeding programme. There a categoritation: 0 = healthy eyes, 1 = one eye opaque, 2 = both eyes opaque is used. In the article II the term “blindness” is used for this variable. In the article III only this macroscopic examination was carried out and termed
“cataract”. According to the article II, the phenotypic correlation between slit- lamp measured “cataracts” and macroscopically measured “blindness” was moderately positive and the genetic correlation highly positive. This encouraged us to use the simple and easily recorded macroscopic measurements for the cataracts in the article III.
All the fish were anesthetised before eye-examination using neutralised tricaine methanesulphonate (MS-222).
Figure 3 Initial stage of a parasite-induced cataract. At least 4 cercaria, each surrounded by opacity, are seen in the lens. Photo by Ellen Bjerkås.
3.4 QUANTITATIVE GENETIC ANALYSES (II-IV)
In articles II-IV, animal models were used to study the genetic variation in several fitness-related traits and how these traits covary in rainbow trout study population.
Within any given population, there are multiple potential sources of phenotypic variation. Quantitative genetics is a discipline that studies how much genes and environment contribute to the trait phenotypic (co)variation and whether there is evolutionary potential in a trait in a population to respond to natural or artificial selection. The basis for the quantitative genetic studies is knowledge about the relationships among individuals in a population and data on their phenotypic traits. Quantitative genetic analyses are referred to as “animal models” when the relationships of all individuals, irrespective of their level of relatedness are used in linear mixed models for the estimation of variance components, trait heritability and genetic correlations between traits (Lynch & Walsh, 1998; Wilson et al., 2010). In an animal model, a pedigree with typically multiple generations is included as an explanatory variable for a phenotypic trait of interest, to estimate the proportion to which the relationships (i.e. genetics) explain phenotypic (co)variance.
Quantitative genetic analyses were carried out using multivariate mixed animal models with restricted maximum likelihood methodology (REML) in DMUAI software (Madsen, Sorensen, Su, Damgaard, Thomsen, & Labouriau, 2006; Madsen & Jensen, 2000). Trait measurements from individual full sibs in a fish family were combined with the pedigree data (animal effect) in a multivariate model. The analysis accounted for all the relationships between all animals in the pedigree using a relationship matrix.
Total phenotypic variance (VP) for each trait is the sum of genetic variance (VG), common environment variance (VC) and residual variance (VR) (Falconer, 1989). Heritability (h2) is a measure of the proportion of phenotypic variance attributable to genetic variance. The broad-sense heritability indicates the proportion of total genetic variance of total phenotypic variance.
It may include effects due to dominance and epistasis (gene interactions) that are not necessarily additive (Falconer, 1989). The narrow-sense heritability is the proportion of additive genetic variance of the total phenotypic variance.
Heritability was determined as a degree by which the trait covaried between relatives. Heritability for each trait was calculated as h2 = VG / VP. Environmental effect common to full sibs (c2), including the effect due to common rearing of full sibs before individual tagging, maternal genetic effects and parts of potential dominance and epistasis effect, was estimated without pedigree data as c2 = VC / VP. When family tank effect is included in the statistical model, the heritability estimate is interpreted 'narrow sense'. When
family tank effect is excluded from the statistical model, the heritability estimate is interpreted 'broad-sense'. Animal models used are described in each article (II-IV)
Genetic correlations between measured traits could be analysed using pedigree data even if the traits were not measured from the same individual.
When this was done, residual correlation was set to zero because it did not exist.
Tolerance (IV) was estimated as the regression slope of fish performance traits, weight, condition factor or mortality (on y-axis), against parasite burden, i.e. eye fluke count of fish individuals (on x-axis). A random regression model was applied in which the genetic variation in the slope of the regression quantifies the genetic variation in tolerance (Kause, 2011). Further, genetic correlation between tolerance slope and intercept was calculated to estimate genetic differences in tolerance compared to performance without parasites. The intercept of a regression quantifies the fish performance when parasites are not present (x-axis = zero).
4 MAIN RESULTS AND DISCUSSION
4.1 LOCALLY ADAPTED PARASITES AND SALMONIDS
In the first study of this thesis, between-population variation in host resistance and/or parasite infectivity was found in the three salmon populations that were infected with Diplostomum sp. parasites (I). The local River Iijoki and the River Simojoki salmon stocks were more prone to the parasite infections compared to the Lake Saimaa salmon population that was more distant to the parasite. Similarly, the local Lake Saimaa salmon population was more prone to infection of the local T. clavata compared to the two more distant salmon stocks. In the second phase of the experiment, when studying infectivity rate of three different Diplostomum sp. populations in the same Lake Saimaa Arctic charr population, geographically closer parasites were again better infectors.
These results support the hypothesis of local adaptation of the parasite.
Parasites are supposed to have better prerequisites to adapt to their hosts than vice versa (Ebert & Hamilton, 1996; Greischar & Koskella, 2007; Lively &
Dybdahl, 2000) and their fitness should decrease with distance of the host population from the origin of the parasite (Ebert, 1994; Ebert, 1998). Parasite local adaptation has been reported in several host and parasite species (Ebert
& Hamilton, 1996; reviewed in Greischar & Koskella, 2007; Kaltz & Shykoff, 1998; Lively & Dybdahl, 2000).
Local adaptation of the parasite is, however, not a rule (Kaltz & Shykoff, 1998).
One interesting example is Gyrodactylus salaris that is one of the great threats of wild stocks of Atlantic salmon in the Northern Atlantic (Johnsen & Jensen, 1986). Stocks of Atlantic salmon that originate from rivers that flow to the Atlantic or to the Arctic Ocean, are highly sensitive to this parasite. In contrast, salmon stocks that originate from rivers that flow to the Baltic Sea are resistant. G. salaris can infect also salmon stocks of Baltic Sea but the survival and fecundity of the parasite are essentially lower than in salmon stocks from rivers flowing in to the Atlantic Ocean or the Arctic Ocean (Cable, Harris, &
Bakke, 2000). In nature, G. salaris thus cause no apparent harm for Atlantic salmon in Baltic Sea, whereas the parasite has devastated wild salmon stocks in over 50 Norwegian rivers (Karlsson et al., 2020). Salmon in rivers flowing to Baltic Sea has shared more than 10 000 years of coevolution with G. Salaris (Garcia de Leaniz et al., 2007) whereas Atlantic salmon stocks in Norway encountered the parasite only in 1970’s when the parasite was accidentally imported to Norway (Bakke, Jansen, & Hansen, 1990; Johnsen & Jensen, 1986). Stocks of salmon in Baltic are better adapted to G. salaris compared to
stocks in Atlantic or Arctic sea, and salmon (host) adaptation seems to overcome parasite adaptation in the Baltic environment.
The higher infectivity of the distant Diplostomum sp. parasites in the River Iijoki and the River Simojoki salmon stocks might also be explained by the Lake Saimaa salmon stock (host) being better adapted and thus more resistant to Diplostomum sp. parasite compared to the River Iijoki and the River Simojoki salmon stocks. Diplostomum sp. parasites occur commonly in Lake Saimaa. In contrast, the River Iijoki and the River Simojoki salmon stocks are anadromous, living in rivers (until smolts and for breeding) and open sea. In these two environments, contact rate with Diplostomum sp. cercaria is probably lower than in the lake due to differences in the water current and the occurrence of intermediate snail hosts releasing Diplostomum sp. cercaria, respectively. In addition, Diplostomum sp. from Lake Huumojärvi were strictly speaking local, but not sympatric with the River Iijoki and the River Simojoki salmon stocks (Figure 2). This means that the populations have not actually coevolved with the salmon stocks from River Iijoki and River Simojoki.
Taken together, the results lend support to the hypothesis of parasites’ local adaptation to their hosts (I). Salmon populations varied in their susceptibility to Diplostomum sp. and T. clavata parasites, and Diplostomum sp.
populations varied in their infectivity to Arctic charr. Some unclarity, however, remains concerning the coevolution between Diplostomum sp. and the studied salmon stocks.
4.2 GENETIC VARIATION IN RAINBOW TROUT RESISTANCE AGAINST DIPLOSTOMUM INFECTIONS
The existence of genetic variation in a trait in question is a prerequisite for evolution of the population, and also for genetic improvement by artificial selection. In article II, genetic variation in resistance against Diplostomum sp.
infections and parasite-induced cataract formation was estimated probably for the first time in a population of rainbow trout. Moderate heritability in parasite resistance (h2 = 0.25–0.35) was found in the three articles (II-IV).
Apart from this thesis, published heritability estimates for parasite resistance in rainbow trout are more or less lacking (but see Caceres et al., 2019; and Silverstein et al., 2009).
Several studies have, however, shown that there is significant additive genetic variation in resistance against different infectious and parasitic diseases in farmed salmonids. Challenge tests measuring fish resistance (survival) against
certain pathogens have shown relatively high heritabilities (h2 = 0.43–0.69) (reviewed in Gjedrem, 2015). In accordance to the results of this thesis (II-IV), heritability of salmon resistance against salmon louse was estimated to be h2
= 0.26 (Kolstad, Heuch, Gjerde, Gjedrem, & Salte, 2005), and rainbow trout resistance against Flavobacterium psychrophilum h2 = 0.35 (Silverstein et al., 2009). The estimated heritability values indicate that variability in resistance traits has often sustained in farmed populations, and improving these traits through artificial selection is feasible (Lhorente, Araneda, Neira, & Yáñez, 2019).
Due to natural selection, essential life-history traits are expected to generally possess lower heritabilities than traits more loosely connected with fitness (Mousseau & Roff, 1987). Eye fluke infected fish experience increased predation risk and have reduced feeding ability compared to their healthy counterparts (Crowden & Broom, 1980; Owen et al., 1993; Palmieri et al., 1976). Resistance against eye flukes should thus be essential. The studied host and parasite population (II-IV) have coexisted at least for 15 years meanwhile rainbow trout have been yearly selected for good production traits, like growth, and later also for bright eyes. The artificial selection, together with reduced survival (IV), might have eliminated individuals with the lowest resistance against Diplostomum sp. from the rainbow trout population but not driven the resistance into fixation.
4.3 PHENOTYPIC AND GENETIC CORRELATIONS OF DIFFERENT LIFE HISTORY TRAITS WITH
RESISTANCE
Slightly negative phenotypic correlations between parasite infection (parasite count, cataract coverage) and fish mass and condition were found in young fish in two studies (II-III) whereas in one study, the phenotypic correlation in the young fish measurement was positive (IV). Similarly, genetic correlations between parasite infection and fish mass and condition were slightly negative (II, III) or positive (IV) in young fish after the first growing season (April- November). The results indicate that in the youngest fish, cataract does not impair weight gain much (II, III). According to the results in article IV, the fish that have somewhat lower resistance gain weight even more rapidly in the first months than their peers that have higher resistance (IV). A slight trade-off in resource allocation between resistance and weight gain in the first months may thus be seen (IV). However, later in rearing, after the second growing season, the genetic correlation between parasite count or cataracts and fish weight or condition turned strongly negative (II-IV). Cataracts thus obviously affected fish feeding when older, and the fish with better resistance and thus lower cataract intensities grew heavier and gained better condition than the fish with
higher parasite load. Genetic correlation between cataracts and survival was also negative. Families that had better resistance against Diplostomum sp.
parasites, i.e., had less severe cataracts, had also better survival (IV).
We also looked at the relationship between parasite infection and maturity, fillet colour (II, III), deformations, and entrails proportion of the body weight (III). In the article III, cataract had negative genetic correlation with age of maturity suggesting that fish that grew slower due to cataracts matured later.
No other significant correlations were found between parasite infection and these traits.
In all, trade-offs that would have important consequences in rainbow trout breeding programme were not found in this thesis. On the contrary, fish with better resistance gained more weight and had better condition and survival.
This has beneficial implications for the breeding programme because resistance can be selected for along with the productivity-related traits.
The study population of rainbow trout cannot, without doubt, be compared to a natural population. However, rainbow trout is a rather new captive species compared to many terrestrial farm animals. The Finnish breed originates from fish that were captured for cultivation in USA around the end of 19th century (Hershberger, 1992), and Northern European rainbow trout strains in general have not significantly lost their variability due to breeding practices (Gross et al., 2007). In contrast to natural populations, farmed fish are more or less protected from predation and, during early life, fed ad libitum in the way that enables also cataract-bearing fish to find feed. It can thus be hypothesised that, in the wild, the positive correlations between eye fluke resistance and growth, condition factor and survival would be more dramatic and genetic variation of resistance against this common parasite could be lower. It can also be hypothesised that the slight trade-off seen in the article IV between resistance and weight gain in the earliest months, could be more important in the wild, where small size could generally expose fish to predation (Hyvärinen &
Vehanen, 2004; Yule, Whaley, Mavrakis, Miller, & Flickinger, 2000) or lower feeding activity might lead to general weakness if feed was limited.
Life history theory predicts that if there were no trade-offs, natural selection would drive all traits closely associated with fitness to fixation (Stearns, 1989).
Despite the remaining genetic variability in fitness-related traits, like resistance, no clear genetic trade-offs with other measured, important traits like growth or survival were found. However, trade-offs cannot alone explain the existence of genetic variability in fitness-related traits. In fact, in the review by Roff (1996), 60 % of the genetic correlations between fitness-related traits were positive, and in the review by Carlson and Seamons (2008) of studies in salmonids, genetic correlations were also skewed towards positive values.
Taken together, the families that had better resistance against Diplostomum sp. parasites grew less during the first months but ended up having higher weight, condition and survival compared to the families with lower resistance.
Hypothetically, rainbow trout may implement two different life-history continuums 1.) take a risk, invest in faster juvenile growth at the cost of increased parasitism and lower survival, and 2.) invest in better resistance at the cost of slower juvenile growth but better growth later in life and better survival. This may be an oversimplification and certainly needs more research in different generations, but it could, however, be one explanation for these results.
4.4 TOLERANCE AND ITS CORRELATIONS WITH OTHER FITNESS-RELATED TRAITS
If rainbow trout juveniles express two life-history strategies like hypothesised above, it can be asked if there is also difference in their tolerance against Diplostomum sp. eye flukes. Perhaps some families find ways to feed better that the others despite lowered vision. In the article IV, genetic variance was found in fish tolerance measured as slopes (Kause, 2011; Simms, 2000) of weight and condition against Diplostomum sp. count (resistance) in fish lenses. When cataracts most probably impaired feeding of the fish, some families gained more weight and were in better condition than the others despite the same level of parasites. Differences were found in the 1.5-year-old fish but not in the early-phase juveniles. In other words, families varied in how well they were able to gain weight and good condition despite eye flukes.
The issue of animal host tolerance was raised by Råberg, Sim and Read (2007).
Since then, some empirical studies on host genetic variation in tolerance have been published. In line with the results of this thesis (IV), Vincent and Sharp (2014) found genetic variation in tolerance of fly Drosophila melanogaster against bacteria Pseudomonas aeruginosa, and studies of Blanchet, Rey and Loot (2010) and Mazé-Guilmo et al. (2014) showed genetic variation in tolerance of freshwater fish Leuciscus burdigalensis against parasite Tracheliastes polycolpus. If tolerance proves to be a common host defence mechanism in animal hosts like in plant hosts (Strauss & Agrawal, 1999), the theories of the evolution of virulence and Red queen dynamics may also need revision. Where host resistance puts selection pressure on parasite infectivity and virulence, host tolerance does not, and could therefore change the course of parasite virulence evolution (Råberg et al., 2007).
Negative genetic correlation between the tolerance slope and the intercept in three tolerance regressions for weight, condition and mortality was found in the fish of 1.5 years of age. This means that the high performance of the fish in
the absence of parasites was genetically associated with strong reduction in performance when parasitism increased. This is a clear genetic trade-off for tolerance and may, for its part, explain the maintenance of genetic variation in tolerance. This means that by selecting for high weight, condition and resistance and low mortality in the rainbow trout breeding programme, some of the fish tolerance might be lost.
The results of this thesis suggest that animals, like plants, can evolve two conceptually different types of parasite-coping mechanisms that are not mutually exclusive strategies and may concurrently exist in a single animal, also in varying degree. Both strategies may simultaneously direct the course of the evolution in one population. In this study population, is seems that the better they gain weight and survive in the absence of parasite, the worse they tolerate an increasing number of parasites. These findings support the importance of considering tolerance in parallel with resistance when studying host-parasite interactions and coevolution because, depending on the strategy, consequences in the epidemiology and the evolution of diseases may be totally different.
5 CONCLUSIONS
This thesis shows adaptation of Diplostomatidae parasites to their local salmonid hosts. This is likely to explain at least some of the variation in cataract incidences detected in Finnish fish farms.
We also found genetic variation in the studied rainbow trout population in both resistance and tolerance against Diplostomum sp. parasites. The results of this thesis thus suggest that animals, like plants, can evolve two conceptually different types of parasite defence.
We did not find trade-offs between resistance and other studied important traits. The rainbow trout families that had better resistance against Diplostomum sp. grew less during the first months of their life but ended up heavier in weight, in better condition and having higher survival compared to the families with lower resistance. A trade-off between fish performance in the absence of parasites and parasite tolerance was however found. The families that weighted the most and had the highest survival in the absence of parasites suffered the greatest reduction in weight gain and survival when the parasite load increased. This may explain at least some of the remaining variation in parasite tolerance.
Resistance and tolerance were not genetically related. Resistance and tolerance appear thus two independent strategies with uncorrelated evolution in rainbow trout. Resistance and tolerance may concurrently exist in a single animal, also in varying degree. The evolutionary consequences of these two host strategies are totally different and both may simultaneously direct the course of the evolution in the studied populations. This finding has important implications for the epidemiology and evolution of infectious diseases. If a host’s strategy is tolerance instead of resistance, natural selection should not lead to a more virulent parasite, and tolerance could thus explain some of the variation in the virulence evolution of the parasite.
The studies of animal tolerance are still few. More information is needed on the mechanisms and genetic basis of tolerance and its specificity. Does tolerance include costs like resistance includes? Does animal tolerance vary depending on the parasite, or, do tolerant individuals show general tolerance against parasitism? It would also be interesting to study how population tolerance evolves in the course of time and depending on the nature of the parasitism.
This thesis adds to our current knowledge of host-parasite interactions in salmonid fishes, and it also provides new information that can be used in
Finnish national breeding programme for rainbow trout. According to the results, tolerance and resistance can be genetically improved along with productivity traits and survival. This improves the health, welfare and productivity of rainbow trout in the Finnish aquaculture.
REFERENCES
Aaen, S. M., Helgesen, K. O., Bakke, M. J., Kaur, K., & Horsberg, T. E. (2015).
Drug resistance in sea lice: A threat to salmonid aquaculture.Trends in Parasitology, 31(2), 72-81.
Abolofia, J., Asche, F., & Wilen, J. E. (2017). The cost of lice: Quantifying the impacts of parasitic sea lice on farmed salmon.Marine Resource Economics, 32(3), 329-349.
Anderson, R. M., & May, R. M. (1982). Coevolution of hosts and parasites.
Parasitology, 85(02), 411-426.
Bakke, T. A., Jansen, P. A., & Hansen, L. P. (1990). Differences in the host resistance of Atlantic salmon, Salmo salar L., stocks to the monogenean Gyrodactylus salaris Malmberg, 1957.Journal of Fish Biology, 37(4), 577-587.
Barber, I., Hoare, D., & Krause, J. (2000). Effects of parasites on fish behaviour: A review and evolutionary perspective.Reviews in Fish Biology and Fisheries, 10(2), 131-165.
Baucom, R. S., & de Roode, J. C. (2011). Ecological immunology and tolerance in plants and animals.Functional Ecology, 25(1), 18-28.
Blanchet, S., Rey, O., & Loot, G. (2010). Evidence for host variation in parasite tolerance in a wild fish population.Evolutionary Ecology, 24(5), 1129-1139.
Cable, J., Harris, P. D., & Bakke, T. A. (2000). Population growth of Gyrodactylus salaris (Monogenea) on Norwegian and Baltic Atlantic salmon (Salmo salar) stocks.Parasitology, 121(06), 621-629.
Caceres, P., Barria, A., Christensen, K. A., Bassini, L., Correa, K., Lhorente, J. P., &
Yanez, J. M. (2019). Genome-scale comparative analysis for host resistance against sea lice between atlantic salmon and rainbow trout.bioRxiv, 624031.
Caldwell, R. M., Schafer, J. F., Compton, L. E., & Patterson, F. L. (1958). Tolerance to cereal leaf rusts.Science, 128(3326), 714-715.
Carlson, S. M., & Seamons, T. R. (2008). A review of quantitative genetic components of fitness in salmonids: Implications for adaptation to future change.Evolutionary Applications, 1(2), 222-238.
Cichowlas, Z. (1961). The life-cycle of diplostomum spathaceum (rud. 1819) in brackish waters of the baltic sea.Acta Parasitologica Polonica, 9(1/9)
Costello, M. J. (2009). The global economic cost of sea lice to the salmonid farming industry.Journal of Fish Diseases, 32(1), 115-118.
Crowden, A. E., & Broom, D. M. (1980). Effects of the eyefluke, Diplostomum spathaceum, on the behaviour of dace (Leuciscus leuciscus).Animal Behaviour, 28(1), 287-294.
Darwin, C. (1859). On the origin of species by means of natural selection, or, the preservation of favoured races in the struggle for life. London: J. Murray.
Dobson, A., Lafferty, K. D., Kuris, A. M., Hechinger, R. F., & Jetz, W. (2008).
Homage to linnaeus: How many parasites? how many hosts?Proceedings of the National Academy of Sciences, 105(Supplement 1), 11482-11489.
Du Pasquier, L. (1982). Antibody diversity in lower vertebrates—why is it so restricted?Nature, 296(5855), 311.
Dybdahl, M. F., & Storfer, A. (2003). Parasite local adaptation: Red queen versus suicide king.Trends in Ecology & Evolution, 18(10), 523-530.
Ebert, D. (1994). Virulence and local adaptation of a horizontally transmitted parasite.Science, 265(5175), 1084-1086.
Ebert, D. (1998). Experimental evolution of parasites.Science, 282(5393), 1432- 1436.
Ebert, D., & Hamilton, W. D. (1996). Sex against virulence: The coevolution of parasitic diseases.Trends in Ecology & Evolution, 11(2), 79-82.
Falconer, D., & Mackay, T. (1996). Introduction to quantitative genetics (4th ed.).
Longman.
FAO. (2018). The state of world fisheries and aquaculture. meeting the sustanable development goals.Retrieved from http://www.fao.org/3/I9540EN/i9540en.pdf Folstad, I., & Karter, A. J. (1992). Parasites, bright males, and the
immunocompetence handicap.The American Naturalist, 139(3), 603-622.
Fornoni, J., Nunez‐Farfán, J., Valverde, P. L., & Rausher, M. D. (2004). Evolution of mixed strategies of plant defense allocation against natural enemies.
Evolution, 58(8), 1685-1695.
Gandon, S., Capowiez, Y., Dubois, Y., Michalakis, Y., & Olivieri, I. (1996). Local adaptation and gene-for-gene coevolution in a metapopulation model.
Proceedings of the Royal Society of London.Series B: Biological Sciences, 263(1373), 1003-1009.
Gandon, S., & Michalakis, Y. (2000). Evolution of parasite virulence against qualitative or quantitative host resistance.Proceedings of the Royal Society of London.Series B: Biological Sciences, 267(1447), 985-990.
Garcia de Leaniz, C., Fleming, I. A., Einum, S., Verspoor, E., Jordan, W. C.,
Consuegra, S., . . . Youngson, A. F. (2007). A critical review of adaptive genetic variation in Atlantic salmon: Implications for conservation.Biological Reviews, 82(2), 173-211.
Gjedrem, T. (2015). Disease resistant fish and shellfish are within reach: A review.
Journal of Marine Science and Engineering, 3(1), 146-153.
Greischar, M. A., & Koskella, B. (2007). A synthesis of experimental work on parasite local adaptation.Ecology Letters, 10(5), 418-434.
Gross, R., Lulla, P., & Paaver, T. (2007). Genetic variability and differentiation of rainbow trout (Oncorhynchus mykiss) strains in northern and Eastern Europe.
Aquaculture, 272, S139-S146.
Hershberger, W. K. (1992). Genetic variability in rainbow trout populations.
Aquaculture, 100(1-3), 51-71.
Hyvärinen, P., & Vehanen, T. (2004). Effect of brown trout body size on post‐
stocking survival and pike predation.Ecology of Freshwater Fish, 13(2), 77-84.
Janhunen, M., Kause, A., Mäntysaari, E. A., Vehviläinen, H., Præbel, A. K., Järvisalo, O., . . . Koskinen, H. (2013). A novel breeding design to produce genetically protected homogenous fish populations for on‐growing.Aquaculture Research, 44(12), 1847-1859.
Johnsen, B. O., & Jensen, A. J. (1986). Infestations of atlantic salmon, salmo salar, by gyrodactylus salaris in norwegian rivers.Journal of Fish Biology, 29(2), 233-241.
Jones, S. R. (2001). The occurrence and mechanisms of innate immunity against parasites in fish.Developmental & Comparative Immunology, 25(8), 841-852.
Kalbe, M., & Kurtz, J. (2006). Local differences in immunocompetence reflect resistance of sticklebacks against the eye fluke Diplostomum
pseudospathaceum.Parasitology, 132(01), 105-116.
