Genetic variation and inference of demographic histories in non-model species Jean-Luc Tison

Genetic variation and inference of
demographic histories in
non-model species
Jean-Luc Tison
Department of Molecular Biosciences,
The Wenner-Gren Institute
Stockholm University
2014
Genetic variation and inference of demographic histories in non-model species
Doctoral Dissertation 2014
Jean-Luc Tison
Department of Molecular Biosciences, The Wenner-Gren Institute
Stockholm University
S-10691
Stockholm, Sweden
©Jean-Luc Tison, Stockholm, Sweden, 2014
ISBN 978-91-7649-056-3
Cover by Jean-Luc Tison
Printed in Sweden by US-AB, Stockholm, 2014
Distributor: Department of Molecular Biosciences, The Wenner-Gren Institute,
Stockholm University
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Abstract
Both long-term environmental changes such as those driven by the glacial cycles
and more recent anthropogenic impacts have had major effects on the past demography in wild organisms. Within species, these changes are reflected in the amount and
distribution of neutral genetic variation. In this thesis, mitochondrial and microsatellite DNA was analysed to investigate how environmental and anthropogenic factors
at different spatial and temporal scales have affected genetic diversity and structure
in four ecologically different animal species.
The glacial cycles are considered to have played an important role in the history
and distribution of species. Paper I describes the post-glacial recolonisation history
of the speckled-wood butterfly (Pararge aegeria) in Northern Europe. A decrease in
genetic diversity with latitude and a marked population structure were uncovered,
consistent with a hypothesis of repeated founder events during the postglacial recolonisation. Moreover, Approximate Bayesian Computation analyses indicate that the
univoltine populations in Scandinavia and Finland originate from recolonisations
along two routes, one on each side of the Baltic.
Paper II aimed to investigate how past sea-level rises affected the population
history of the convict surgeonfish (Acanthurus triostegus) in the Indo-Pacific. Assessment of the species’ demographic history suggested a population expansion that
occurred approximately at the end of the last glaciation. Moreover, the results
demonstrated an overall lack of phylogeographic structure, probably due to the high
dispersal rates associated with the species’ pelagic larval stage. Populations at the
species’ eastern range margin were significantly differentiated from other populations, which likely is a consequence of their geographic isolation.
In Paper III, we assessed the effect of human impact on the genetic variation of
European moose (Alces alces) in Sweden. Genetic analyses revealed a spatial structure with two genetic clusters, one in northern and one in southern Sweden, which
were separated by a narrow transition zone. Moreover, demographic inference suggested a recent population bottleneck. The inferred timing of this bottleneck coincided with a known reduction in population size in the 19th and early 20th century
due to high hunting pressure.
In Paper IV, we examined the effect of an indirect but well-described human
impact, via environmental toxic chemicals (PCBs), on the genetic variation of Eurasian otters (Lutra lutra) in Sweden. Genetic clustering assignment revealed differentiation between otters in northern and southern Sweden, but also in the Stockholm
region. ABC analyses indicated a decrease in effective population size in both northern and southern Sweden. Moreover, comparative analyses of historical and contemporary samples demonstrated a more severe decline in genetic diversity in southern Sweden compared to northern Sweden, in agreement with the levels of PCBs
found in the respective areas.
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List of papers
This thesis is based on the following papers, which are referred to in the text by their
roman numerals:
I.
Tison JL, Nyström Edmark V, Sandoval-Castellanos E, Van Dyck H,
Tammaru T, Välimäki P, Dalén L, Gotthard K. (2014) Signature of postglacial expansion and genetic structure at the northern range limit of the
speckled wood butterfly. Biological Journal of the Linnean Society.113:136-148.
II.
Tison JL, Chan Y, Dalén L, Planes S. Indo-Pacific population structure and
demographic history of a highly abundant and widespread coral reef fish,
Acanthurus triostegus. Manuscript.
III.
Wennerström L, Hasslow A, Tison JL, Dalén L, Laikre L†, Ryman N†.
Genetic landscape with sharp allele frequency shifts in Swedish moose (Alces alces) revealed by individually based. Manuscript.
IV.
Tison JL*, Blennow V*, Palkopoulou E, Gustafsson P, Roos A, Dalén L.
Population structure and recent temporal changes in genetic variation in
Eurasian otters from Sweden. Conservation genetics, in press.
* These authors contributed equally to the study.
† These authors contributed equally to the senior position.
Copyright: Paper I: The Linnean Society of London © 2014
Copyright: Paper IV: Springer Science + Business Media Dordrecht © 2014
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Acknowledgments
First, I would like to express my warmest thanks to my supervisor Love Dalén for
giving me the chance to join his research group, and allowing me a new departure in
my PhD studies. More than being a supervisor, you have been an essential support, a
true mentor, always full of encouragement and constantly in a good mood. I am
grateful to Martine Bérubé and Per Paslbøll for giving the opportunity to start a PhD
in Stockholm and for the work together. Your scientific expertise, rigor, objectivity
and sense of quality are remarkable. I also want to thank Karin Noren, my cosupervisor for the support. For their advices, guidance and practical help, I am grateful to Ann-Beth Jonsson, Dag Jenssen, Elisabeth Håggard and Eva Petterson.
Many thanks, to everybody at the Department of Genetics, Microbiology and
Toxicology (now MBW) and to everybody at my host department Bioinformatics
and Genetics at the Swedish Natural History Museum for the stimulating research
environment. Particularly, I would like to thank the former and current members of
the ancient DNA group at NRM: Elle, Vendela, Patricia, Erik, Yvonne, Edson, the
frequent visitor-PhD student Matti Heino and the former master students George
Xenikoudakis and Victor Blennow, for the nice discussions, help, social hangouts
and fun together. I am truly grateful to Martin, Bodil, Veronica, Rodrigo, Keyvan,
Pia, Jane and Fredrick for their help, practical and technical assistance in addition to
the pleasant company at NRM.
I also want to thank Vicky and the former colleagues from the Evolutionary Genetics Group at GMT: Morten Tange Olsen, Laetitia Wilkins, Mimmi Lidh, Pauline
Gauffier and Conor Ryan. A particular thanks to my roommate at GMT and friend
Morten for all the fun during these years, in the good times as well as in the less
good ones. I remember sharing a class as assistant with the best teacher ever,
kayaking in Central Sweden, the memorable moments in Québec and Boston with
you. Thank you for your permanent support and to remind me than pursuing my
dreams is the best thing to do in life. I am longing to go whale-watching with you at
some point or paddle (va’a) in the Tuamotu. Also, thanks to my former corridor
mates Bo, Hanna, Cissi, Petra, Dominik, Anne and Ivo, Miriam, Lisa, Katarina,
Nele, Sara, Jens, Niklas, Alice, Karl, Elina, Ramesh and Andrzey for the company
and nice social events throughout the years. Thanks also to Zoology department for
inviting me to Bloodbath throughout the years and to the peoples at Zoology for
including me in many other social occasions.
Many thanks, to all the co-authors for your help and support with the papers included in this thesis. I am particularly grateful to Veronica Nyström Edmark, Kalle
Gotthard, Edson Sandoval-Castellanos, Yvonne Chan, Serge Planes, Lovisa
Wennerström, Linda Laikre, Nils Ryman and of course Love Dalén. Thank you,
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Love for having explained me how to use (or not use) a semi-colon and helping me
so much with improving my English writing. Again, thank you Love, Elle and Anna
for reading and commenting on the thesis.
I am also grateful to all the collaborators and peoples involved in the interesting and
fun projects, which were not included in this thesis and the ones involved in fieldwork and other experience. Particularly I want to thank (i) Richard Sears and Christian Ramp at Mingan Island Cetacean Study, (ii) Olivier Van Canneyt, Ghislain
Doremus and Sophie Laran at Centre de Recherche sur les Mammifères Marins –
Université La Rochelle for the REMMOA project, (iii) Brian Bowen, Rob Toonen
and the ToBo lab at the Hawaii Institute of Marine Biology, and (iv) Love, Sverker,
Patricia and Erik for the fun “bear safari”.
I am thankful to the Knut and Alice Wallenberg foundation and C.F. Liljevach foundation for providing the financial support to present my work at conferences.
Also, my warmest thanks to my former colleagues at Lycée Français Saint Louis and
friends here in Stockholm than kept asking me “When will you be done with your
PhD?” So, Marcel, Ludo, Séverine, Arnaud, Samir, Florent, Carole, Mina, Grégory,
très bientôt, ce sera le cas. Merci d’avoir été là toutes ces années.
Merci aussi aux amis d’enfance, de Paris ou Montpellier, Antoine, Mica, Hadley,
Mag, Pauline, Manue, Florent, Romain ainsi qu’à Kelly, Sam, Frank, Bella de votre
soutien et de venir me rendre visite de temps en temps. Cela me touche énormément.
Vous êtes toujours les bienvenus. Un jour, certains d’entre vous finiront peut être par
emménager ici.
Egalement, un immense merci à Alexandre et Isolde, Mélanie, Marie-Françoise et
Jean-Noël de m’avoir toujours soutenu malgré les distances et les difficultés. Papa,
Maman, vous n’avez de cesse de croire en nous et de parcourir le monde pour nous,
merci donc. Cette thèse, c’est aussi et avant tout grâce à vous. Du fond du cœur, je
vous en remercie. Enfin, Anna merci de ton amour, de me soutenir, d’être toujours là
pour moi, et d’avoir rendu cela possible. Tu es un vrai trésor dans ma vie.
“Wonder is the beginning of wisdom”
Socrates 470 BC – 399 BC
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Contents
Abstract ..................................................................................................................... iii
List of papers .............................................................................................................. v
Acknowledgments .....................................................................................................vi
Contents .....................................................................................................................ix
Introduction................................................................................................................. 1
Genetic diversity and population genetics: the basis to infer population histories ................................ 1
Reconstructing past demography ......................................................................................................... 2
The coalescent theory .................................................................................................................... 2
Identification of population expansions and bottlenecks ................................................................ 2
Inferring more complex demographies: new tools, new possibilities ............................................. 3
Consequences of historical changes in the environment....................................................................... 4
Glacial-cycles - speckled wood butterfly ....................................................................................... 4
Sea-level fluctuations - convict surgeonfish................................................................................... 4
Recent anthropogenic impacts.............................................................................................................. 5
Harvesting pressure – moose in Sweden ........................................................................................ 5
Environmental toxins – Eurasian otters in Sweden ........................................................................ 6
Objectives ................................................................................................................... 7
Materials and methods ................................................................................................ 8
Laboratory methods ............................................................................................................................. 8
Samples ......................................................................................................................................... 8
Molecular ecology markers............................................................................................................ 8
Analytical methods ............................................................................................................................ 10
Genetic diversity .......................................................................................................................... 10
Comparisons of populations and estimates of genetic structure ................................................... 10
Neutrality tests and population history inference ......................................................................... 10
Summary of papers ................................................................................................... 11
Paper I ................................................................................................................................................ 11
Paper II .............................................................................................................................................. 12
Paper III ............................................................................................................................................. 14
Paper IV ............................................................................................................................................. 15
Future directions ....................................................................................................... 17
Contributions ............................................................................................................ 20
References................................................................................................................. 21
Sammanfattning på svenska ...................................................................................... 31
Résumé en français ................................................................................................... 32
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Introduction
“Nothing in biology makes sense except in the light of evolution."
Theodosius Grygorovych Dobzhansky - 1973
The amount and distribution of neutral genetic variation in extant organisms is a
consequence of their history. At a large time scale, historical climate-driven effects
such as glacial cycles (Paper I) and sea-level changes (Paper II) have played a major
role in influencing genetic diversity. At shorter time scales, human activities such as
overexploitation of resources (Paper III), pollution (Paper IV), habitat destruction
and introduction of exotic species have had major impacts on biodiversity. The influence of these processes on the history of populations and their genetic diversity
can be assessed using genetic tools.
Genetic diversity and population genetics: the basis to infer
population histories
The inference of demographic parameters from genetic data is based on the fact that
evolutionary forces change the frequency of alleles in a population through time.
The process of mutation creates new alleles and increases genetic variation. Mutations can be neutral, or have positive as well as negative effects on the fitness of an
individual. The frequency of an allele in a population can thus increase or decrease
under the effect of natural selection (Darwin 1859; Fisher 1930), depending on
whether its beneficial or deleterious to reproductive success. The frequency of an
allele may also change due to random sampling of alleles from one generation to the
next, called genetic drift. The rate of genetic drift in a population is directly dependent on the effective population size (Wright 1931). In a population with small effective population size, genetic drift is more pronounced and can lead to the fixation or
loss of alleles. However, in a large enough population without migration or selection
the effect of genetic drift can be negligible. In such situations, mutation-drift equilibrium can be maintained, where the loss of diversity through genetic drift is compensated by the introduction of diversity through mutation. In addition, migration, or in
evolutionary terms, the movement of alleles between populations (gene-flow) will
tend to homogenize allele frequencies between populations, in absence of selection.
Gene flow among populations can take place via the dispersal of animal organisms,
planktonic larvae, seeds or even gametes.
However, in natural situations, individuals within a species rarely breed randomly (under panmixia). This non random-mating can be due to species-specific lifehistory traits such as philopatry, ecological factors such as habitat preferences, or
environmental barriers such as mountains or rivers. As a consequence, within a
geographic range, individuals are typically more closely related to each other com1
pared to individuals from different geographic regions, creating genetic differentiation among groups of individuals. This type of genetic structure within species leads
to the formation of genetically distinct populations.
Knowledge on how these forces drive changes in the frequency of alleles, and
depending on the spatial and temporal scale of interest, different patterns of genetic
differentiation and population history can be identified. For example, population
genetic models can be used to reconstruct the demographic history of a population in
terms of expansions and reductions in effective population size as well as population
divergence. Since also the timing of such events can be estimated, it is also possible
to explore the interaction between past changes in demography and historical geological or climatic conditions.
Reconstructing past demography
Since the advent of DNA sequencing in the early 1990s and the development of the
fields of human evolution, phylogeography and conservation biology, the interest of
estimating demographic parameters and reconstructing the past demography of populations increased (Avise 2000; Beaumont 2004; Emerson et al. 2001). This investigation was facilitated by the development and application of the coalescence theory
(Hudson 1991; Kingman 1982a; Kingman 1982b).
The coalescent theory
The coalescent theory is a population model looking back in time to interpret genetic
data. Thus, the coalescent describes the genealogical history of a sample of individuals from a population back until their Most Recent Common Ancestor (MRCA).
Using the coalescent theory, it is possible to estimate population parameters, such as
effective population size, and to investigate possible population size changes. Population size changes can be reflected in the shape of the genealogy of the coalescent.
For example, a population under expansion produces long external branches in the
genealogy, resulting in an excess of singletons. A class of statistical tests (such as
Tajima’s D test), using the frequency of segregating sites, has been developed and
measure whether there is an excess or a deficiency of rare mutations in the observed
dataset compared to expectation under the Wright-Fisher model (Fu & Li 1993;
Tajima 1989a, b). The results are often interpreted in terms of population size
changes.
Identification of population expansions and bottlenecks
Historically, to detect population expansion, analysis of the distribution of pairwise
differences among DNA sequences, also called mismatch distributions, has been
used (Excoffier & Schneider 1999; Harpending 1994; Rogers & Harpending 1992;
Sherry et al. 1994; Slatkin & Hudson 1991). Following a sudden population size
expansion, a population displays a unimodal distribution of pairwise differences.
The timing of the start of population growth can then be estimated by the position of
the peak in the distribution (Rogers & Harpending 1992). Other statistical tests, such
as Fu’s Fs, based on haplotype distributions have also been developed (Fu 1997).
2
In conservation biology, detecting population bottlenecks is essential since declines in genetic diversity of a population may have a negative effect on its ability to
survive. Population bottlenecks can leave distinctive signatures in expected heterozygosities and in the distributions of allele sizes. Genetic bottleneck tests typically
make use of these properties to determine if a population has gone through a demographic decline. The earliest population bottleneck tests aimed at detecting departures from expectations under mutation-drift equilibrium. For example, tests such as
“heterozygosity-excess” (Cornuet & Luikart 1996; Piry et al. 1999) and the M-ratio
test (Garza & Williamson 2001) have been extensively used (Peery et al. 2012).
Nonetheless, the statistical power to detect genetic bottlenecks using these approaches appears to be limited, especially if the bottleneck occurred only a few generations before sampling (Aguilar et al. 2008; Girod et al. 2011; Hoffman et al.
2011; Peery et al. 2012). However, more advanced methods to estimate demographic parameters and characterize demographic histories are rapidly being developed
(Beaumont 2004, 2010).
Inferring more complex demographies: new tools, new possibilities
Recently, more powerful approaches based on maximum likelihood, Bayesian and
Approximate Bayesian Computations (ABC) have been developed (Bertorelle et al.
2010; Kuhner 2009). For example, Bayesian skyline plots can provide estimates of
changes in effective population size through time (Drummond & Rambaut 2007;
Drummond et al. 2005; Ho & Shapiro 2011; Pybus et al. 2000). Bayesian methods
implemented in MSvar show a higher probability of detecting population bottlenecks compared to more traditional heterozygosity-excess and M-ratio tests (Girod
et al. 2011; Storz & Beaumont 2002). In addition, packages such as BEAST
(Drummond & Rambaut 2007), LAMARC (Beerli & Felsenstein 2001; Kuhner et
al. 1998) and SPLATCHE2 (Ray et al. 2010) also allow estimation of effective
population sizes under different population histories.
The ABC-framework allows comparison of different scenarios of evolution, in
order to select the best scenario and to estimate posterior distributions of model
parameters. In brief, prior distributions of parameters describing various aspects of
the scenarios are given by the user. Following this, a high number of simulations
with parameter values drawn from the prior distributions are performed. Summary
statistics are then computed for the observed dataset, as well as for each simulated
dataset. The simulations with summary statistics that are most similar to those of the
observed data are kept. This allows for model selection to be implemented, as well
as recovery of posterior distributions of parameters from the selected model. Model
checking and cross validation can also be performed using pseudo-observed datasets
(Bertorelle et al. 2010; Csillery et al. 2010).
3
Consequences of historical changes in the environment
Describing the history of populations and the past variation in population size is
essential to understand the impact of past climate changes on the current distribution
of species, but also for the conservation of endangered species.
Glacial-cycles - speckled wood butterfly
During the Quaternary (2.6 Myr ago to today), fluctuations in the Earth’s climate
have led to several glacial episodes, and these have played an important role in the
abundance and distributions of species. For instance, during the Last Glacial Maximum (LGM, around 23,000-18,000 years ago), many temperate species in the northern hemisphere were confined to southern refugia (Hewitt 2000; Hewitt 1999;
Taberlet et al. 1998) while, in contrast, arctic species had a much larger distribution
than they do today (Stewart et al. 2010). After the LGM, during the PleistoceneHolocene transition, the ice-sheets covering much of northern Europe and North
America melted. Accordingly, some species adapted to cold conditions became
constrained to smaller geographical areas, and depending on their adaptations and
environmental tolerance, decreased in population size and genetic diversity (Campos
et al. 2010) or even went extinct (Stuart & Lister 2011). In contrast to cold-adapted
species, temperate species were able to recolonise high-latitude regions and consequently expanded in population size. Such postglacial recolonisation processes left
genetic footprints both in terms of genetic diversity (Lessa et al. 2003) and genetic
relatedness among populations (Hewitt 1999).
Insects and particularly butterflies are good models to study evolutionary processes and climate-driven range shifts (Hill et al. 2011; Hill et al. 1999; Parmesan et al.
1999). The speckled wood butterfly, Pararge aegeria, was likely confined to southern refugia during the LGM and subsequently expanded northwards. Today the
species is found in Scandinavia and Finland, which constitute its northern range
margin. However, little is known about the recolonisation history of the species, nor
its genetic diversity and structure in Northern Europe.
Sea-level fluctuations - convict surgeonfish
The Indian and Pacific oceans contain the highest concentration of tropical marine
biodiversity (Ekman 1953) and are divided into several biogeographical provinces
(Briggs & Bowen 2012; Cowman & Bellwood 2013; Kulbicki et al. 2013). During
the LGM, the sea-level was about 120 meters lower than it is at present-day, which
led to a considerable reduction in connectivity between the Indian and Pacific
oceans (Sathiamurthy & Voris 2006; Voris 2000). In addition, the distribution and
abundance of coral reefs were much lower than those of today (Kleypas 1997; Ludt
& Rocha 2014). By inferring past events in coral reef taxa, one could expect to find
patterns of ancient vicariance during the last ice age, demographic expansion at the
end of this period, and Holocene high levels of gene flow.
One of the most abundant and widespread coral reef fish in the Indian and Pacific
oceans is the convict surgeonfish, Acanthurus triostegus. Its range spans several
biogeographic regions, from East Africa through the Indo-Pacific to the eastern
4
Pacific. Compared to other widespread fish, in which little genetic structure has been
found based on mitochondrial DNA (Horne et al. 2008; Klanten et al. 2007), high
levels of differentiation have been described in Acanthurus triostegus using allozymes (Planes & Fauvelot 2002). Therefore, we were interested in studying the
population structure using mitochondrial DNA, and infer the demographic history of
the convict surgeonfish.
Recent anthropogenic impacts
From hunter-gatherer societies, through farming and pastoralist societies, to modernday societies, humans have exploited and modified their environment to meet their
needs. However, with the progress of technology, especially following the industrial
revolution, pollution as well as overexploitation of natural resources (through fishing, hunting, agriculture, animal farming and forestry) have become more intense
and today constitute major threats to biodiversity.
Harvesting pressure – moose in Sweden
Many species have become extinct due to human overharvesting, both in the terrestrial and marine environments, such as the dodo, the Tasmanian tiger, the great auk
and Steller’s sea cow. Others species, such as most whales and many shark species
have decreased dramatically in population size (Baum et al. 2003; Diamond 1989;
Jackson et al. 2001; Roberts & Solow 2003). Harvesting can reduce the effective
population size down to critical levels where genetic drift and inbreeding can become a threat to the survival of the population. The genetic diversity of a population
and its spatial structure can also be modified due to intensive harvesting. Moreover,
selective harvest can change the genetic composition of a population (Allendorf et
al. 2008).
In order to determine which populations to manage and protect, it is important to
define conservation and management units. Thus, concepts such as “Evolutionary
Significant Units” and “Management Units” have been discussed and are based
mainly on genetic parameters (Crandall et al. 2000; Moritz 1994; Palsboll et al.
2007; Waples & Gaggiotti 2006). These aspects have been well studied in many
taxa, but several studies have also underlined the need to estimate and delineate
population genetic structure and to take into consideration the demographic history
of the population (Manel et al. 2004; Taberlet et al. 1995; Tallmon et al. 2004;
Waits et al. 2000). Thus, population genetic data can provide valuable information
to monitor populations and species for management and conservation (Schwartz et
al. 2007).
The largest game animal in Sweden is the moose, Alces alces. Approximately
one third (c. 100,000 animals) of the population is currently harvested annually.
However, in the beginning of the 19th century a strong decline in population size
occurred. It is believed that this decline culminated with only a few hundred to a few
thousand animals remaining in the central part of Sweden. The population size has
subsequently increased rapidly since the 1960s (Lavsund et al. 2003). Although the
5
current demography of the population is well studied, little is known about its population structure and past demographic history, despite the importance of these parameters for the management of the Swedish moose.
Environmental toxins – Eurasian otters in Sweden
Some of the most common toxins found in the environment are polychlorinated
biphenyls (PCBs), pesticides, phthalates and heavy metals. Depending on their concentration in organisms, these compounds can be highly toxic and have tremendous
effects on a wide range of organisms. They can lead to increased mortality, reduced
fertility and/or reduced reproductive rates. Thus, these toxins can result in major
decreases in population size, and can reduce the genetic diversity of populations. For
example, DDT, an organochlorine used as insecticide in the 1940s and banned in
most countries since the 1970s, poisoned the wildlife for decades due to its hydrophobic and lipophilic properties and its high bioaccumulation potential. According
to a well-described mechanism, a metabolite of DDT, called DDE, caused eggshell
thinning that led to egg breakage and death of embryos. This resulted in severe population declines in bird species in both North America and Europe (Bignert et al.
1995; Bowerman et al. 1995; Green 1998).
Another class of contaminants with high impact on biodiversity is PCBs. In the
Baltic ecosystem and in Sweden, both PCBs and DTT have impacted the environment and the fauna (Olsson & Reutergårdh 1986). For example, studies have shown
a negative impact on the Baltic guillemot (Bignert et al. 1995; Jorundsdottir et al.
2006), the white-tailed sea eagle (Hailer et al. 2006; Helander et al. 2002), seals
(Bredhult et al. 2008; Nyman et al. 2003) and Eurasian otters (Olsson & Sandegren
1991; Roos et al. 2001). The latter species, Lutra lutra, was common in Sweden
before the 1950s but went through a drastic bottleneck between the 1950s and
1980s. After the bans of DDT and PCBs in the 1970s, the population began to recover. However, the genetic consequences of this demographic bottleneck have
remained unknown, both in terms of how much genetic variation was lost and
whether the bottleneck had an effect on present-day population structure.
6
Objectives
The aim of this thesis was to reconstruct past demography and assess population
structure by estimating genetic variation in four wild animal species living in different environments.
More specifically, the objectives were to:

Assess species demographic histories using inferences based on deviations
from mutation-drift equilibrium as well as coalescent-based approximate
Bayesian computation (Papers I – IV).

Evaluate the relationship between inferred demographic changes and past
climatic (Papers I & II) as well as anthropogenic (Papers III & IV) changes.

Examine to what extent genetic structure among contemporary populations
have been affected by past changes in climate (Papers I, II & III) and human-mediated bottlenecks (Papers III & IV).

Investigate the relative amount of genetic diversity and population differentiation at species range margins (Papers I & II).
7
Materials and methods
Several species that inhabit widely different environments were used in this research, and a range of analyses using genetic information were conducted to learn
both about the population history of each species and understand the factors influencing its distribution. The taxonomic as well as environmental diversity in these
studies comprised terrestrial invertebrates and mammals (Papers I and III), a semiaquatic mammal (Paper IV) and a marine fish (Paper II). Both recently collected
samples (Papers I – IV) and historical museum samples (Paper IV) were analysed to
examine the population structure and demographic history and each respective species.
Laboratory methods
Samples
In Paper I, speckled wood butterflies (n=209) were collected between 1984 and
2011 from locations in northern Europe, but with particular emphasis on Sweden. In
Paper II, convict surgeonfishes (n=179) were collected between 1994 and 2008 from
reef slopes or lagoons at several sites across the Indo-Pacific. In Paper III, a very
large number of fresh tissue samples (n=20,358) were obtained from moose killed
throughout Sweden during one single hunting season in 1980. A smaller number of
these moose samples were genotyped for microsatellite and mitochondrial DNA
variation (n=1207 and n=48, respectively). In Paper IV, European otters (n=139)
were sampled at three time points, before 1950 (n=17), between 1950 and 1979
(n=31), and after 2000 (n=91).
In the four studies, whole genomic DNA was extracted for further analysis of
population genetic variability, differentiation and demographic history assessment.
In Paper I, DNA was extracted using the Molestrips DNA tissue kit. In Paper III,
DNA was extracted using salt extraction method modified from Aljnabi and Martinez (1997) or the QIAGEN DNeasy Blood and Tissue Kit. The latter kit was also
used for the DNA extraction of the muscles samples in Papers II and IV. For the
museum European otter bone samples, in Paper IV, after being drilled into fine
bones powder, DNA was extracted using a modified version of protocol C in Yang
et al. (1998).
Molecular ecology markers
A broad scope of molecular markers have been developed and used for population
analyses, including allozymes, RFLPs, AFLPs, microsatellites, SNPs as well as
mitochondrial and nuclear DNA sequences. In the papers included in this PhD thesis, three types of markers were used for different applications and are described
thereafter.
Allozymes
In Paper II, three allozyme loci (Pmi, Mdh-2, and Pgi-1) were used to detect molecular heterogeneity in the full moose sample (n=20,358). Allozymes are allelic vari8
ants of enzymes and were historically the first molecular markers broadly used to
investigate diversity patterns within and among populations. The different alleles
can be differentiated according to size and charge through gel electrophoresis (Sick
1961).
Mitochondrial DNA sequences
Regions of the mitochondrial DNA were amplified and sequenced in Papers II and
III. In both these papers, a part of the control region of the mitochondrial DNA was
sequenced. The control region contains hypervariable parts, which are often used to
describe population genetic variability. In addition, in Paper II, a 365 bp fragment of
the cytochrome oxidase I gene was sequenced. More details about the amplification,
the purification of the PCR products can be found in the respective papers. The
laboratory work for the mitochondrial DNA for Paper III was conducted at the Department of Bioinformatics and Genetics, Swedish Museum of Natural History. The
laboratory work for Paper II was conducted at URS 3278, Perpignan, France. The
sequences were edited and assembled using BioEdit (Paper II) and Geneious (Papers
II, III).
Microsatellites
Microsatellite loci consist of short tandem repeats (1-6 bp long) that are found
throughout the genome. Due to single-strand slippage during in vivo DNA replication, repeats can be added or lost. This slippage can occur at comparatively high
rates leading to mutation rates ranging between 10-3 -10-5 mutations/locus/generation
(Ellegren 2004). Thus, high levels of polymorphism can be found within species and
microsatellites are thus particularly useful to describe population variability (Selkoe
& Toonen 2006). Microsatellites were employed in Papers I, III and IV. In Paper I,
nine microsatellites previously characterized for Pararge aegeria were used. In
Paper III, twelve microsatellites were genotyped for Alces alces and in Paper IV, we
genotyped twelve loci in the Lutra lutra samples. In the three papers, the amplifications were performed in multiplex PCR reactions using the QIAGEN multiplex PCR
master mix. The grouping of the loci in the multiplex PCRs, the details of the fluorescence labeled primers and the reaction settings can be found in the respective
papers. Capillary electrophoresis was conducted on an ABI 3130xl. The sizes of the
fragments were determined using the GeneScanTM 500 LIZTM (Papers I and IV) or
the GeneScanTM 600 LIZTM size markers (Paper III). For Paper I and Paper IV, the
laboratory work and genotyping were performed at the Department of Bioinformatics and Genetics, Swedish Museum of Natural History. For Paper III, the laboratory
work and the genotyping were performed at the Center of Evolutionary Application,
University of Turku, Finland. In all three papers, genotypes were scored using
GENEMAPPER v4.0 (Applied Biosystems).
9
Analytical methods
Genetic diversity
Levels of genetic diversity were investigating in all four papers. For the microsatellite datasets (Papers I, III and IV) and the allozyme dataset (Paper III), several
statistics, such as the mean number of alleles, observed and expected heterozygosities, and allelic richness were used to describe variation within and among different
sampling locations. Moreover, in Paper IV genetic diversities were also compared
across different points in time. Genetic variation was also estimated for the mitochondrial DNA sequences (Papers II, III) by evaluating, for example, the number of
haplotypes, haplotype diversity, as well as nucleotide diversity and the number of
segregating sites among sequences.
Comparisons of populations and estimates of genetic structure
We investigated if and how the samples were genetically structured in space and in
time. For several sampled areas, we assessed connectivity in terms of gene flow
between sampling locations. For each marker, we were interested in examining
differences in allele and haplotype frequencies and how these were distributed in
space. The phylogenetic relationships between samples and geographic locations
were inferred using tree-based methods. The relationships among mitochondrial
DNA haplotypes were also estimated using minimum spanning or median-joining
networks (Papers II and III). From the spatial distribution of alleles and haplotypes,
we assessed the genetic divergence between populations using for example FST or
ΦST statistics (Wright 1951). Genetic and geographical distances were also compared using Mantel tests and tested for isolation by distance (Paper II). Population
clustering was conducted using Analysis of Molecular Variance (AMOVA) or using
individual-based approaches (i.e., spatial autocorrelograms, STRUCTURE, TESS).
Neutrality tests and population history inference
Fossil remains or museum collections are valuable in population genetics since they
allow for direct estimates of changes in genetic diversity. However, when only contemporary samples are available, the assessment of past changes in population size is
more challenging. Several statistical tests have been developed for DNA sequences
and for multilocus microsatellite genotypes to detect departure from mutation-drift
equilibrium, which can be used to infer demographic histories. For DNA sequences,
Tajima’s D, Fu’s FS were computed and the results were interpreted in terms of past
changes in effective population size. For microsatellites, heterozygosity-excess tests
were performed to detect earlier population bottlenecks (Papers III, IV). Furthermore, coalescent-based simulations coupled with Approximate Bayesian Computation (ABC) were employed to infer the history of populations. The ABC-framework
allows to assess more complex scenarios of evolution, selects the best scenario and
estimates posterior distributions of model parameters by comparing summary statistics between observed and simulated datasets (Bertorelle et al. 2010; Csillery et al.
2010).
10
Summary of papers
Paper I
Postglacial recolonisation in the speckled wood butterfly
One of the most prominent features of the last ice age was the last glacial maximum
period around 20,000 years ago. At that time, most of Britain and Northern Europe
as far south as Germany and Poland were covered by the Scandinavian Ice Sheet.
The ice started melting around 17,000 years ago allowing temperate plants and animals, which had been restricted to refugia, to recolonise the previously glaciated
areas (Mangerud et al. 2011; Svendsen et al. 2004). In this study, we investigated
the post-glacial recolonisation of the speckled wood butterfly, Pararge aegeria, in
northern Europe using microsatellite genetic markers. We found an overall pattern
of latitudinal decrease in allelic richness, which is consistent with the hypothesis that
range expansions lead to successive losses in genetic variation due to repeated
founder events (Hewitt 2004). Furthermore, using a Bayesian model-based clustering method, a marked population structure was detected. In the dataset, six genetic
clusters were identified, corresponding to six geographically separate populations:
[1] Central Scandinavia, [2] Gotland, [3] Öland, [4] South Scandinavia, [5] Benelux
and [6] Eastern Baltic. Interestingly, previous studies have found very low genetic
differentiation further south in Europe and in North Africa (Habel et al. 2013;
Vandewoestijne & Van Dyck 2010). We hypothesized that the population structure
observed in our study is a consequence of repeated founder effects during the postglacial range expansion, since this type of process can lead to increased population
divergence (Klopfstein et al. 2006; Ray & Excoffier 2009).
To further examine the recolonisation of northern Europe, we compared different
postglacial range expansion models using an ABC approach, with emphasis on different scenarios for the origin of the population in Central Scandinavia (Fig. 1). We
tested three plausible scenarios where Central Scandinavia was recolonised either
from the south (South Scandinavia) or the East (Eastern Baltic). Among the three
scenarios tested, we could reject the recolonisation of Central Scandinavia from the
East. This means that the post-glacial recolonisation of northernmost Europe (Central Scandinavia and Eastern Baltic) took place along two routes, with one route on
each side of the Baltic. This is interesting because Pararge aegeria displays different local adaptations in different parts of northern Europe, where populations in both
Central Scandinavia and Eastern Baltic are univoltine (i.e. have one generation per
year), while populations further south are multivoltine. Thus, under the assumption
that the source populations in the south were multivoltine, as they are today, and that
no gene flow has occurred between Central Scandinavia and Eastern Baltic, the
ABC results suggested that univoltinism evolved independently on both side of the
Baltic Sea.
11
Fig. 1
Schematic representations of three recolonisation scenarios (A-F) tested using the
ABC approach.
Paper II
Indo-Pacific genetic structure and variation in the convict surgeon fish
The oceans cover approximately 70% of the earth’s surface, and have few obvious
geographic barriers to dispersal. This, coupled with the pelagic larval stage displayed by many coral reef species implies that one might expect high levels genetic
variation and little genetic differentiation among regions. On the other hand, declines in global sea levels during the last glaciation likely had a major effect on coral
reef species, both because their distributions were more restricted and because the
formation of land bridges may have reduced connectivity among populations. To
investigate the demographic history and genetic structure in a widespread coral reef
fish, we analysed genetic variation in the convict surgeonfish (Acanthurus triostegus) sampled across the Indo-Pacific. We recovered sequences from two mitochondrial DNA (mtDNA) markers, the left hypervariable domain of the control region
and the cytochrome oxidase I gene.
High levels of haplotype and nucleotide diversities (h > 99 and π = 8.9%) were
found. Moreover, a lack of phylogeographic structure across the species range was
revealed in the haplotype networks (Fig. 2). These results are consistent with a large
long-term effective population size in Acanthurus triostegus, and likely also reflect
the species’ capacity for long distance dispersal during its pelagic larval stage. Simi-
12
lar results have been observed for species with comparable wide geographic ranges
(Gaither et al. 2010; Horne & van Herwerden 2013; Klanten et al. 2007).
In addition, it should be noted that significant genetic differentiation was observed for populations at the species range margin (e.g. Clipperton and the Marquesas). A high degree of differentiation has been commonly reported in these isolated
regions, where the presence of cryptic species is known. This is also in accordance
with the fact that the species richness is lower than in the west-Pacific and that a
high degree of endemism have been reported for Marquesas (Lessios & Robertson
2006; Szabo et al. 2014; Williams et al. 2013)
To further explore the demographic history in Acanthurus triostegus, we used an
ABC approach. The results from these analyses indicated that a ten-fold expansion
in population size took place, roughly at the end of the last glaciation. This result is
consistent with a hypothesis that climate-driven rises in sea levels at the end of the
last glaciation may have led to re-arrangements in coral reef distributions. This may
have had cascading effects on many fish species that rely on them. Interestingly, we
also observed signatures of a more ancient, probably Middle Pleistocene, demographic expansion in the distribution of pairwise differences among the mitochondrial DNA sequences. Thus, our results revealed a complex demographic history that
may be attributed to the sea-level fluctuations. Still, these findings also indicated the
need of large sampling efforts combined with a multi-locus analysis to better address
this complex demographic history. Moreover, to better understand the coral reef
history of the Indo-Pacific, there is a need to perform comparative multi-species
studies, based on different life-history traits.
A
B
Fig.2
Minimum spanning networks for Acanthurus triostegus sampled across the IndoPacific, based on 365 bp of mitochondrial CR sequences (n= 161: A) and based on
449 bp of mitochondrial COI sequences (n=179: B). Each circle represents a single
haplotype and the circle size is proportional to the frequency of the haplotype. Each
hatch-mark represents a nucleotide change. Colours indicate haplotype location.
13
Paper III
Autosomal and mitochondrial genetic variation in the Swedish moose
In Paper III, we investigated the demographic history and genetic structure in European moose (Alces alces) in Sweden. The European moose likely survived the Pleistocene glaciations in multiple refugia south or southeast of the Scandinavian ice
sheet and recolonised Fennoscandia around 8000-9000 years ago (Haanes et al.
2011; Kangas et al. 2013; Niedziałkowska et al. 2014). These historical events have
probably influenced the present genetic structure and diversity in Sweden. However,
the moose in Scandinavia have also been strongly affected by more recent anthropogenic factors such as hunting and changes in landscape use. In particular, the Swedish moose population was severely reduced in the 19 th and early 20th Centuries due
to excessive hunting. Although the population has recovered, approximately one
third (c. 100,000 animals) of the population is currently killed annually.
To assess to what extent present-day genetic patterns have been influenced by
glacial dynamics as well as more recent human hunting, including the historical
bottleneck, we examined genetic variation using allozymes and microsatellite markers in 20,000 and 1200 moose samples, respectively. To further examine genetic
patterns potentially caused by the postglacial recolonisation of Scandinavia, we also
sequenced the mitochondrial DNA control region in 48 moose samples. The autosomal markers demonstrated the existence of two major genetic groups, one in
northern and one in southern Scandinavia, which were separated by a narrow transition zone (Fig. 3). Similar divisions into northern and southern groups have previously been observed in Finnish and Norwegian moose (Haanes et al. 2011; Kangas
et al. 2013). Genetic divergence estimates in both autosomal and mitochondrial
markers were comparatively limited among the two populations, suggesting that the
populations diverged during the Holocene and consequently are unlikely to be the
result of postglacial recolonisation from two separate glacial refugia. The ABC
analyses indicated that both the northern and southern populations went through a
bottleneck. The inferred timing of this bottleneck was consistent with the known
bottleneck that took place from the 18th to the 20th Century.
At a finer geographic scale, we also found some evidence of additional substructure within the southern subpopulation. Moreover, spatial autocorrelation analyses
suggested comparatively small “genetic patch sizes”. Thus, it appears that limited
dispersal distances, estimated as only a few kilometers in our study, have led to a
pattern of isolation by distance within the subpopulations.
From a management perspective, the two genetically distinct subpopulations
identified in this study, need to be taken into account in order to ensure preservation
of potentially unique genetic variation in the respective subpopulations. However,
the estimated “genetic patch size” generally exceeds the size of current management
areas, indicating that overharvesting in separate management areas would be unlikely to have any major genetic effects on the overall Swedish moose population.
14
Fig. 3
Color coded 3D surface plot of assignment probabilities to the northern (red) of the
two major clusters identified by the software STRUCTURE, using the 1207 moose
data set and 15 loci (12 microsatellites and 3 allozymes). The two major clusters and
the transition zone previously identified in Norway are shown in three shades of
grey (Haanes et al. 2011).
Paper IV
Recent demographic bottleneck in Eurasian otter from Sweden
Although European otters (Lutra lutra) used to be abundant across large parts of the
Palaearctic, their population sizes started to decrease severely in the 1950s’ throughout most parts of Europe (Mason & Macdonald 1986). Polychlorinated biphenyls
(PCBs) have been identified as one of the major drivers for the population decline
(Mason 1993; Olsson & Sandegren 1991). However, even though several studies
have examined the present-day genetic variation in otters (Hobbs et al. 2011; Mucci
et al. 2010; Randi et al. 2003; Stanton et al. 2014), little is known about the genetic
consequences of the bottleneck that took place in the 1950’s. In our study, using
microsatellite data from historical as well as modern samples, we were able to test
whether this bottleneck led to any loss in genetic diversity and/or changes in genetic
structure. Comparisons of allelic richness at different points in time demonstrated a
significant loss in diversity in southern Sweden (Fig. 4). In contrast, we found no
evidence of declines in genetic diversity in northern Sweden.
Bayesian assignment of individual genotypes into genetic clusters indicated a
pronounced genetic structure in both the modern and pre-bottleneck samples. Interestingly, historical and modern samples from northern Sweden were assigned to the
same clusters, indicating that allele frequencies have remained stable through the
last 60 years. However, historical and modern samples from southern Sweden were
15
assigned to different clusters, suggesting a marked change in allelic composition
likely due to genetic drift. These results suggested that the bottleneck was more
severe in southern compared to northern Sweden.
The results from ABC analyses further supported this pattern. A bottleneck scenario was supported for both northern and southern Sweden, and the inferred effective population sizes (Ne) during the height of the bottleneck were similar (~100).
However, the posteriors for the post-bottleneck effective population sizes were highly different, where otters in northern Sweden appear to have recovered more (56%
of the pre-bottleneck Ne) compared to in southern Sweden (17% of the prebottleneck Ne).
Overall, the genetic results fit well with a previous study on environmental toxin
loads in otters, which demonstrated a higher concentration of PCBs in otters from
southern Sweden compared to northern Sweden (Roos et al. 2001). Conservation
efforts should take into account the observed pattern of genetic structure and careful
consideration is required for the southern population, which may be particularly
vulnerable.
A
B
Fig. 4
Rarefaction curves of allelic richness. (A) Estimates of allelic richness for subpopulations in northern Sweden. (B) Estimates of allelic richness for subpopulations in
southern Sweden.
16
Future directions
This thesis illustrates how genetic tools can be used to reconstruct demographic
histories. The studies encompassed a broad taxonomic diversity as well as a range of
different environments, and made use of several different genetic markers. Past
demographic changes were inferred both at long time scales to assess the consequences of climate change at the end of the last ice age (Papers I & II), as well as
short time scales to examine the consequences of recent anthropogenic impacts
(Papers III & IV). However, it should be noted that the accuracy in the inferences
made in these studies sometimes are imprecise due to large confidence intervals in
the estimated parameters. Moreover, the use of a limited number of loci can lead to
incorrect inferences because gene trees do not always capture the true relationships
among populations. Thus, to reiterate a declaration that likely has been around since
the start of scientific time, more data is needed! Fortunately, recent technological
advances now make this possible, moving the challenge to the analysis of the data.
Recent developments in sequencing and computational technologies
Today, with the emergence of next-generation sequencing (NGS) technologies,
large-scale datasets and complete genomes have become more easily available. This
is revolutionizing the fields of molecular ecology, conservation biology and population genetics (Ellegren 2014; Luikart et al. 2003). Thus, the field of population genetics is moving towards population genomics (Andrews & Luikart 2014) and more
and more scientists talk about conservation genomics (Narum et al. 2013). Large
SNP datasets can, for example, be obtained using restriction site-associated DNA
sequencing (RAD-seq), and these may permit more complex demographic history to
be revealed (Emerson et al. 2010; Lemmon & Lemmon 2013; Puritz et al. 2014;
Reitzel et al. 2013).
However, to estimate complex demographic and historical effects on genetic variation (e.g. effective population size, gene flow, divergence), computer simulations
are needed and these have started to play an increasingly important role (Hoban
2014; Hoban et al. 2011). Thus, genomics is to some extent dependent of developments in the bioinformatics field, where new simulators and programs with more
sophisticated features emerge rapidly (Yuan et al. 2012). For example, the ABC
framework, which is both powerful and flexible, has become especially popular to
estimate demographic histories and other types of population genetic inference
(Beaumont 2010; Beaumont et al. 2002; Bertorelle et al. 2010; Cornuet et al. 2014;
Csillery et al. 2010; Wegmann et al. 2010). Additional recent developments for
inference-based computational methods also include the simultaneous use of genetic
data from several taxa to understand the interplay between, for example, geography,
climate fluctuations and demographic change (Hickerson et al. 2007). These methods use a coalescent-based hierarchical ABC (hABC) framework. For example,
MTML-msBayes allow testing of simultaneous divergence and migration across
multiple co-distributed taxon-pairs (Huang et al. 2011). Another statistical develop-
17
ment based on hABC explores the demographic history of multiple taxa to detect
concerted demographic expansions at the community-level (Chan et al. 2014).
Moreover, new methods continue to be developed to infer historical changes in
effective population size. A recent major development uses the pairwise sequentially
Markovian coalescent model (PSMC), which is based on the assumption that local
densities of heterozygotes allow inference of the local time to the most recent common ancestor (Li et al. 2008; MacLeod et al. 2013). This method has the advantage
that it enables inference of species’ population size histories based on single diploid
genomes. This has for example been used to reconstruct the demographic history in
several marine mammal species (Moura et al. 2014; Yim et al. 2014; Zhou et al.
2013), and with the aid of ABCs analyses can also help to identity ancient admixture
(Miller et al. 2012) or to reconstruct divergence history (Nadachowska-Brzyska et
al. 2013).
NGS and adaptive genetic variation
In addition to enabling more accurate inference population histories, large-scale
genomic data can also be used to detect regions of the genome under natural selection, which in turn can be used to identify locally adapted traits among populations
(Nielsen et al. 2005). For example, selective sweep mapping can be performed to
detect purifying selection (Boitard et al. 2012; Foll & Gaggiotti 2008; Kim &
Stephan 2002; Messer & Petrov 2013). Most of these tests are based on the genetic
hitchhiking concept, where genome scans are employed to identify regions with
local reduction in genetic diversity where purifying selection has acted. Moreover by
integrating genomic and environmental datasets, potential ecological and environmental drivers of selection can be revealed (Jones et al. 2013; Joost et al. 2007;
Schoville et al. 2012; Stapley et al. 2010).
Ancient DNA and museum collections
The recent development of the ancient DNA field can also provide new insights to
understand how the past has affected the present. For example, the use of serially
sampled ancient DNA data (Hadly et al. 2004) now permits demographic histories to
be investigated in real-time as changes occurred, thus facilitating interpretations of
the interaction between genetic and climatic changes (de Bruyn et al. 2011; Shapiro
et al. 2004). The development of ancient DNA tools also highlights the utility of
museum collections in genetic research. By allowing the comparison of historical
and present-day genetic diversities, museum collections provide the opportunity to
better understand the impacts of recent environmental change and human activities
(Bi et al. 2013; Moritz et al. 2008; Nachman 2013; Ramakrishnan et al. 2005;
Thomas et al. 1990; Wandeler et al. 2007). In Paper IV, we made use of this approach through sampling of both contemporary samples and museum specimens
from Eurasian otters in Sweden. This allowed us to compare levels of genetic diversity and differentiation before, during and after a well-documented bottleneck.
18
Palaeogenomics
Coupled with the development of more advanced extraction and next-generation
sequencing methods, the ancient DNA field has now entered the age of the palaeogenomics, pushing the limits of the DNA recovery (Millar & Lambert 2013;
Orlando et al. 2013) and enabling new ways to calibrate molecular clocks as well as
examining selection (Campbell et al. 2010; Fu et al. 2014; Shapiro & Hofreiter
2014). Another method that has recently been developed takes advantage of temporal sampling to investigate the footprint of genomic differentiation among samples
to provide information about the populations’ histories. Thus, genetic differentiation
between temporally spaced samples now make it possible to distinguish between (i)
constant population size evolution, (ii) bottleneck models and (iii) replacement models, something which was not possible without taking into account the temporal
sampling (Skoglund et al. 2014).
A new genetic era
To conclude, the fields of molecular ecology, population genetics and conservation
genetics are being revolutionized by the fact that next-generation sequencing is
resulting in a rapidly growing amount of data becoming available. More than ever,
evolutionary biology is becoming a multidisciplinary field where archeologists,
ecologists, geneticists, statisticians, and informaticians are collaborating. As a result,
we can continue to satisfy our curiosity to understand the environmental, ecological
and evolutionary processes that shape the genetic variation and biodiversity at different temporal and spatial scales.
19
Contributions
Paper I
VN performed the DNA extractions. VN and JLT conducted PCRs and genotyping.
JLT conducted all the data-analysis with input from ES on the ABCs analysis. LD,
KG and JLT wrote the manuscript.
Paper II
JLT performed all the laboratory work and analysed the data, with input from LD
and SP. JLT wrote the manuscript with input from all coauthors.
Paper III
JLT performed the laboratory as well as computational analyses on the mitochondrial DNA. LW analyzed the allozyme and microsatellite data, except for the coalescent-based ABC analyses that were done by JLT. LW wrote the paper, with input
from JLT and the other coauthors.
Paper IV
JLT collected and did the laboratory work on the museum otter samples. VB and
PG performed laboratory analyses on the modern samples, under the supervision of
JLT and EP. VB and JLT performed the computational analyses. VB wrote the
paper together with JLT and LD.
20
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Sammanfattning på svenska
Såväl långsiktiga miljöförändringar, till exempel de som drivs av istidscykler, som
mer nutida antropogent drivna förändringar har haft stor effekt på demografin hos
vilda organismer. Inom en art speglas dessa förändringar genom mängden och den
geografiska utbredningen av genetisk variation. I denna avhandling analyserades
mitokondriellt- och mikrosatellit-DNA för att undersöka hur miljöförändringar i
olika rums- och tidsskalor har påverkat genetisk variation och struktur hos fyra ekologiskt skilda djurarter.
Istidscyklerna anses ha spelat en stor roll i utvecklingen och fördelningen av arter. Artikel I undersöker den postglaciala rekoloniseringen av Kvickgräsfjärilen
(Pararge aegeria) i norra Europa. En minskning av genetisk diversitet i förhållande
till latitud och en tydlig populationsstruktur upptäcktes, vilket överensstämmer med
en hypotes om att den postglaciala koloniseringsprocessen innebar ett flertal lokala
flaskhalser (s.k. ”founder events”). Bayesianska beräkningsanalyser genom ”Approximate Bayesian Computation” (ABC) indikerade att de univoltina populationerna i Skandinavien och Finland härstammar från rekoloniseringar längs två vägar, en
på var sida om Östersjön.
Artikel II syftade till att undersöka hur tidigare höjning av havsnivån påverkat
populationen av Sebrastrimmig kirurgfisk (Acanthurus triostegus) i Indiska Oceanen
och Stilla Havet. Inferens av artens demografiska historia indikerade en populationsexpansion ungefär vid tiden för slutet på den senaste istiden. Därtill visade resultaten
en övergripande brist på fylogeografisk struktur, sannolikt på grund av den höga
spridnigsförmågan som artens pelagiska larvstadie innebär. Populationer i den
Sebrastrimmig kirurgfiskens östligaste utbredningsområde var signifikant differentierade från andra populationer vilket sannolikt är en konsekvens av deras geografiska
isolering.
I Artikel III analyserades människans effekt på den genetiska variationen hos
den svenska älgstammen (Alces alces). Genetiska analyser påvisade en tydlig spatial
struktur med två genetiska kluster, en i norra och en i södra Sverige, som var åtskilda med en transitionszon. Därtill indikerade demografisk inferens med hjälp av
ABC-analys en recent flaskhals i populationsstorlek. Den uppskattade tidpunkten för
denna flaskhals stämde väl överens med en känd minskning i älgstammen som
skedde under 1800- och 1900-talen på grund av högt jakttryck.
I Artikel IV undersöktes effekten av en indirekt men välbeskriven mänsklig påverkan, den genom miljötoxiska kemikalier (PCB), på den genetiska variationen hos
eurasisk utter (Lutra lutra) i Sverige. Genetiska klusteranalyser påvisade en differentiering mellan uttrar från olika delar av Sverige. ABC-analyser indikerade att en
minskning i populationsstorlek skett i både norra och södra Sverige. Jämförande
analyser av historiska och nutida prov påvisade en kraftigare minskning av genetisk
variation i södra jämfört med norra Sverige, vilket överensstämmer med de tidigare
nivåer av PCB som uppmätts i respektive område.
31
Résumé en français
Les changements environnementaux à long terme, tels que ceux induits par les
cycles glaciaires, et les impacts anthropiques plus récents ont eu des effets majeurs
sur la démographie passée des organismes sauvages. Au sein des espèces, ces changements se reflètent dans la quantité et la distribution de la variation génétique
neutre.
Dans cette thèse, l’ADN mitochondrial et des microsatellites ont été analysés
pour quatre espèces animales écologiquement différentes, afin de déterminer comment des facteurs environnementaux et anthropiques ont affecté la diversité génétique et la structure des populations, à différentes échelles spatiales et temporelles.
Les cycles glaciaires sont considérés comme ayant joué un rôle important dans
l'histoire et la distribution des espèces. L’article I décrit l'histoire de la recolonisation postglaciaire du papillon tircis (Pararge aegeria) en Europe du Nord. Une diminution de la diversité génétique corrélée avec la latitude ainsi qu’une forte structuration des populations ont été révélées. Ceci est compatible avec une hypothèse
d'effets fondateurs répétés durant la recolonisation postglaciaire. En outre, les analyses d’inférences bayésiennes approximatives semblent indiquer que les populations univoltines (produisant une seule génération par an) en Scandinavie et en Finlande proviennent de recolonisations le long de deux routes distinctes, une route de
chaque côté de la Baltique.
L’article II vise à étudier comment les variations du niveau des océans ont affecté l'histoire des populations du poisson chirurgien bagnard (Acanthurus triostegus)
dans l'Indo-Pacifique. L’évaluation de l'histoire démographique de l'espèce a suggéré une expansion de la population qui a eu lieu autour de la fin de la dernière glaciation. De plus, les résultats ont démontré un manque global de structure phylogéographique, probablement en raison de taux élevés de dispersion pélagique au stade
larvaire de l'espèce. Cependant, les populations à l’extrémité orientale de la zone de
distribution de l'espèce sont significativement génétiquement différenciées des
autres populations. Ceci est vraisemblablement une conséquence de leur isolement
géographique.
Dans l’article III, nous avons évalué l'effet de l'impact humain sur la variation
génétique des élans européen (Alces alces) en Suède. Les analyses génétiques ont
révélé une structure spatiale avec deux groupes génétiques: un dans le nord et un au
sud de la Suède, séparés par une étroite zone de transition. Par ailleurs, l'inférence
démographique suggère un goulot d'étranglement de population récent, coïncidant
avec une réduction de taille de la population connue au 19ème siècle et au début du
20ème siècle en raison d’une pression de chasse élevée.
Dans l’article IV, nous avons examiné l'effet d'un impact humain indirect mais
bien décrit, celui des produits chimiques toxiques environnementaux (PCBs), sur la
variation génétique des loutres eurasiennes (Lutra lutra) en Suède. Les analyses
d’affectation individuelle en groupement génétique ont révélé des populations distinctes de loutres dans le nord et le sud de la Suède, mais aussi dans la région de
32
Stockholm. Les analyses d’inférence bayésienne approximative ont indiqué une
diminution de la taille effective des populations à la fois dans le nord et le sud de la
Suède. De plus, des analyses comparatives d’échantillons historiques et contemporains ont démontré une baisse plus sévère de la diversité génétique dans le sud de la
Suède par rapport au nord de la Suède, en accord avec les différents niveaux de
PCBs trouvés dans ces régions.
33