Phylogeography and population genetics of north European Atlantic salmon (Salmo salar L.)

Although abundant in the number of individuals, the Atlantic salmon may be considered as a threatened species in many areas of its native distribution range. Human activities such as building of power plant dams, offshore overfishing, pollution, clearing of riverbeds for timber floating and badly designed stocking regimes have diminished the distribution of Atlantic salmon. As a result of this, many of the historical populations both in Europe and northern America have gone extinct or are severely depressed. In fact, only 1% of Atlantic salmon existing today are of natural origin, the rest being farmed salmon. All of this has lead to a vast amount of research and many restoration programmes aiming to bring Atlantic salmon back to rivers from where it has vanished. However, many of the restoration programmes conducted thus far have been unsuccessful due to inadequate scientific research or lack of its implementation, highlighting the fact that more research is needed to fully understand the biology of this complex species. The White and Barents Seas in northwest Russia are among the last regions in Europe where Atlantic salmon populations are still stable, thus forming an important source of biodiversity for the entire European region. Salmon stocks from this area are also of immense economic and social importance for the local people in the form of fishing tourism. The main aim of this thesis was to elucidate the post-glacial history and population genetic structure of north European and particularly northwest Russian Atlantic salmon, both of which are aspects of great importance for the management and conservation of the species. Throughout the whole thesis, these populations were studied by utilizing microsatellites as the main molecular tool. One of the most important discoveries of the thesis was the division of Atlantic salmon from the White and Barents Seas into four separate clusters, which has not been observed in previous studies employing nuclear markers although is supported by mtDNA studies. Populations from the western Barents Sea clustered together with the northeast Atlantic populations into a clearly distinguishable group while populations from the White Sea and eastern Barents Sea were separated into three additional groups. This has important conservation implications as this thesis clearly indicates that conservation of populations from all of the observed clusters is warranted in order to conserve as much of the genetic diversity as possible in this area. The thesis also demonstrates how differences in population life histories within a species, migratory behaviour in this case, and in their phylogeographic origin affect the genetic characteristics of populations, namely diversity and divergence levels. The anadromous populations from the Atlantic Ocean, White Sea and Barents Sea possessed higher levels of genetic diversity than the anadromous populations form the Baltic Sea basin. Among the non-anadromous populations the result was the opposite: the Baltic freshwater populations were more variable. This emphasises the importance of taking the life history of a population into consideration when developing conservation strategies: due to the limited possibilities for new genetic diversity to be generated via gene flow, it is expected that freshwater Atlantic salmon populations would be more vulnerable to extinction following a population crash and thus deserve a high conservation status. In the last chapter of this thesis immune relevant marker loci were developed and screened for signatures of natural selection along with loci linked to genes with other functions or no function at all. Also, a novel landscape genomics method, which combines environmental information with molecular data, was employed to investigate whether immune relevant markers displayed significant correlations to various environmental variables more frequently than other loci. Indications of stronger selection pressure among immune-relevant loci compared to non-immune relevant EST-linked loci was found but further studies are needed to evaluate whether it is a common phenomenon in Atlantic salmon.

Molecular genetics of the immotile short tail sperm defect

Hedelmättömyyttä aiheuttavan siittiöiden puolihäntävian molekyyligenetiikka Suomalaisissa Yorkshire karjuissa yleistyi 1990-luvun lopulla autosomaalisesti ja resessiivisesti periytyvä hedelmättömyyttä aiheuttava siittiöiden puolihäntävika (ISTS, immotile short tail sperm). Sairaus aiheuttaa normaalia lyhyemmän ja täysin liikkumattoman siittiön hännän muodostuksen. Muita oireita sairailla karjuilla ei ole havaittu ja emakot ovat oireettomia. Tämän tutkimuksen tarkoituksena oli kartoittaa siittiöiden puolihäntävian aiheuttava geenivirhe ja kehittää DNA-testi markkeri- ja geeniavusteiseen valintaan. Koko genomin kartoituksessa vian aiheuttava alue paikannettiin sian kromosomiin 16. Paikannuksen perusteella kahden geenimerkin haplotyyppi kehitettiin käytettäväksi markkeri-avusteisessa valinnassa. Sairauteen kytkeytyneen alueen hienokartoitusta jatkettiin geenitestin kehittämiseksi kantajadiagnostiikkaan. Vertailevalla kartoituksella oireeseen kytkeytynyt alue paikannettiin 2 cM:n alueelle ihmisen kromosomiin viisi (5p13.2). Tällä alueella sijaitsevia geenejä vastaavista sian sekvensseistä löydetyn muuntelun perusteella voitiin tarkentaa sairauteen kytkeytyneitä haplotyyppejä. Haplotyyppien perusteella puolihäntäoireeseen kytkeytynyt alue rajattiin kahdeksan geenin alueelle ihmisen geenikartalla. Alueelle paikannetun kandidaattigeenin (KPL2) sekvensointi paljasti introniin liittyneen liikkuvan DNA-sekvenssin, Line-1 retroposonin. Tämä retroposoni muuttaa geenin silmikointia siten, että sitä edeltävä eksoni jätetään pois tai myös osa introni- ja inserttisekvenssiä liitetään geenin mRNA tuotteeseen. Molemmissa tapauksissa tuloksena on lyhentynyt KPL2 proteiini. Tähän retroposoni-inserttiin perustuva geenitesti on ollut sianjalostajien käytössä vuodesta 2006. KPL2 geenin ilmenemisen tarkastelu sialla ja hiirellä paljasti useita kudosspesifisiä silmikointimuotoja. KPL2 geenin pitkä muoto ilmenee pääasiassa vain kiveksessä, mikä selittää geenivirheen aiheuttamat erityisesti siittiön kehitykseen liittyvät oireet. KPL2 proteiinin ilmeneminen hiiren siittiön hännän kehityksen aikana ja mahdollinen yhteistoiminta IFT20 proteiinin kanssa viittaavat tehtävään proteiinien kuljetuksessa siittiön häntään. Mahdollisen kuljetustehtävän lisäksi KPL2 saattaa toimia myös siittiön hännän rakenneosana, koska se paikannettiin valmiin siittiön hännän keskiosaan. Lisäksi KPL2 proteiini saattaa myös toimia Golgin laitteessa sekä Sertolin solujen ja spermatidien liitoksissa, mutta nämä havainnot kuitenkin vaativat lisätutkimuksia. Tämän tutkimuksen tulokset osoittavat, että KPL2 geeni on tärkeä siittiön hännän kehitykselle ja sen rakennemuutos aiheuttaa siittiöiden puolihäntäoireen suomalaisilla Yorkshire karjuilla. KPL2 proteiinin ilmeneminen ja paikannus siittiön kehityksen aikana antaa viitteitä proteiinin toiminnasta. Koska KPL2 geenisekvenssi on erittäin konservoitunut, nämä tulokset tuovat uutta tietoa kaikkien nisäkkäiden siittiöiden kehitykseen ja urosten hedelmättömyyteen syihin.

A Diagnostic view of the Genetics of CASADIL

Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL, OMIM #125310) is an inherited vascular disease. The main symptoms include migraineous headache, recurrent strokes and progressive cognitive impairment. CADASIL is caused by mutations in the NOTCH3 gene which result in degeneration of vascular smooth muscle cells, arteriolar stenosis and impaired cerebral blood flow. The aims of this study were assessment of the genetic background of Finnish and Swedish CADASIL patients, analysis of genetic and environmental factors that may influence the phenotype, and identification of the optimal diagnostic strategy. The majority of Finnish CADASIL patients carry the p.Arg133Cys mutation. Haplotype analysis of 18 families revealed a region of linkage disequilibrium around the NOTCH3 locus, which is evidence for a founder effect and a common ancestral mutation. Despite the same mutational background, the clinical course of CADASIL is highly variable between and even within families. The association of several genetic factors with the phenotypic variation was investigated in 120 CADASIL patients. Apolipoprotein E allele 4 was associated with earlier occurrence of strokes, especially in younger patients. Study of a pair of monozygotic twins with CADASIL revealed environmental factors which may influence the phenotype, i.e. smoking, statin medication and physical activity. Knowledge of these factors is useful, since life-style choices may influence the disease progression. The clinical CADASIL diagnosis can be confirmed by detection of either the NOTCH3 mutation or granular osmiophilic material by electron microscopy in skin biopsy, although the sensitivity estimates have been contradictory. Comparison of these two methods in a group of 131 diagnostic cases from Finland, Sweden and France demonstrated that both methods are highly sensitive and reliable.

Conservation Genetics of Exploited Finnish Salmonid Fishes

Genetic diversity is one of the levels of biodiversity that the World Conservation Union (IUCN) has recognized as being important to preserve. This is because genetic diversity is fundamental to the future evolution and to the adaptive flexibility of a species to respond to the inherently dynamic nature of the natural world. Therefore, the key to maintaining biodiversity and healthy ecosystems is to identify, monitor and maintain locally-adapted populations, along with their unique gene pools, upon which future adaptation depends. Thus, conservation genetics deals with the genetic factors that affect extinction risk and the genetic management regimes required to minimize the risk. The conservation of exploited species, such as salmonid fishes, is particularly challenging due to the conflicts between different interest groups. In this thesis, I conduct a series of conservation genetic studies on primarily Finnish populations of two salmonid fish species (European grayling, Thymallus thymallus, and lake-run brown trout, Salmo trutta) which are popular recreational game fishes in Finland. The general aim of these studies was to apply and develop population genetic approaches to assist conservation and sustainable harvest of these populations. The approaches applied included: i) the characterization of population genetic structure at national and local scales; ii) the identification of management units and the prioritization of populations for conservation based on evolutionary forces shaping indigenous gene pools; iii) the detection of population declines and the testing of the assumptions underlying these tests; and iv) the evaluation of the contribution of natural populations to a mixed stock fishery. Based on microsatellite analyses, clear genetic structuring of exploited Finnish grayling and brown trout populations was detected at both national and local scales. Finnish grayling were clustered into three genetically distinct groups, corresponding to northern, Baltic and south-eastern geographic areas of Finland. The genetic differentiation among and within population groups of grayling ranged from moderate to high levels. Such strong genetic structuring combined with low genetic diversity strongly indicates that genetic drift plays a major role in the evolution of grayling populations. Further analyses of European grayling covering the majority of the species’ distribution range indicated a strong global footprint of population decline. Using a coalescent approach the beginning of population reduction was dated back to 1 000-10 000 years ago (ca. 200-2 000 generations). Forward simulations demonstrated that the bottleneck footprints measured using the M ratio can persist within small populations much longer than previously anticipated in the face of low levels of gene flow. In contrast to the M ratio, two alternative methods for genetic bottleneck detection identified recent bottlenecks in six grayling populations that warrant future monitoring. Consistent with the predominant role of random genetic drift, the effective population size (N_e) estimates of all grayling populations were very low with the majority of N_e estimates below 50. Taken together, highly structured local populations, limited gene flow and the small N_e of grayling populations indicates that grayling populations are vulnerable to overexploitation and, hence, monitoring and careful management using the precautionary principles is required not only in Finland but throughout Europe. Population genetic analyses of lake-run brown trout populations in the Inari basin (northernmost Finland) revealed hierarchical population structure where individual populations were clustered into three population groups largely corresponding to different geographic regions of the basin. Similar to my earlier work with European grayling, the genetic differentiation among and within population groups of lake-run brown trout was relatively high. Such strong differentiation indicated that the power to determine the relative contribution of populations in mixed fisheries should be relatively high. Consistent with these expectations, high accuracy and precision in mixed stock analysis (MSA) simulations were observed. Application of MSA to indigenous fish caught in the Inari basin identified altogether twelve populations that contributed significantly to mixed stock fisheries with the Ivalojoki river system being the major contributor (70%) to the total catch. When the contribution of wild trout populations to the fisheries was evaluated regionally, geographically nearby populations were the main contributors to the local catches. MSA also revealed a clear separation between the lower and upper reaches of Ivalojoki river system – in contrast to lower reaches of the Ivalojoki river that contributed considerably to the catch, populations from the upper reaches of the Ivalojoki river system (>140 km from the river mouth) did not contribute significantly to the fishery. This could be related to the available habitat size but also associated with a resident type life history and increased cost of migration. The studies in my thesis highlight the importance of dense sampling and wide population coverage at the scale being studied and also demonstrate the importance of critical evaluation of the underlying assumptions of the population genetic models and methods used. These results have important implications for conservation and sustainable fisheries management of Finnish populations of European grayling and brown trout in the Inari basin.

MCMC Analysis Of Classical Time Series Algorithms

Identification of order of an Autoregressive Moving Average Model (ARMA) by the usual graphical method is subjective. Hence, there is a need of developing a technique to identify the order without employing the graphical investigation of series autocorrelations. To avoid subjectivity, this thesis focuses on determining the order of the Autoregressive Moving Average Model using Reversible Jump Markov Chain Monte Carlo (RJMCMC). The RJMCMC selects the model from a set of the models suggested by better fitting, standard deviation errors and the frequency of accepted data. Together with deep analysis of the classical Box-Jenkins modeling methodology the integration with MCMC algorithms has been focused through parameter estimation and model fitting of ARMA models. This helps to verify how well the MCMC algorithms can treat the ARMA models, by comparing the results with graphical method. It has been seen that the MCMC produced better results than the classical time series approach.

The genetics of behaviour and other adaptive traits in nine-spined sticklebacks (Pungitius pungitius)

One of the main goals in current evolutionary biology research is to identify genes behind adaptive phenotypic variations. The advances in genomic technologies have made it possible to identify genetic loci behind these variations, also concerning non-model species. This thesis investigates the genetics of the behaviour and other adaptive traits of the nine-spined stickleback (Pungitius pungitius) through the application of different genetic approaches. Fennoscandian nine-spined stickleback populations express large phenotypical differences especially in behaviour, life –history traits and morphology. However the underlying genetic bases for these phenotypical differences have not been studied in detail. The results of the project will lay the foundation for further genetics studies and provide valuable information for our understanding of the genetics of the adaptive divergence of the nine-spined stickleback. A candidate gene approach was used to develop microsatellite markers situating close to candidate genes for behaviour in the nine-spined stickleback. Altogether 13 markers were developed and these markers were used in the subsequent studies with the anonymous random markers and physiologically important gene markers which are already currently available for nine-spined sticklebacks. It was shown that heterozygosity correlated with behaviour in one of the marine nine-spined stickleback populations but with contrasting effects: correlations with behaviour were negative when using physiological gene markers and positive with random markers. No correlation was found between behavioural markers and behaviour. From the physiological gene markers, a strong correlation was found between osmoregulation-related gene markers and behaviour. These results indicate that both local (physiological) and general (random) effects are important in the shaping of behaviour and that heterozygosity– behaviour correlations are population dependent. In this thesis a second linkage map for nine-spined sticklebacks was constructed. Compared to the earlier nine-spined stickleback linkage map, genomic rearrangements were observed between autosomal (LG7) and sex-determing (LG12) linkage groups. This newly constructed map was used in QTL mapping studies in order to locate genomic regions associated with pelvic structures, behaviour and body size/growth. One major QTL was found for pelvic structures and Pitx1 gene was related to these traits as was predicted from three-spined stickleback studies, but this was in contrast to earlier nine-spined stickleback study. The QTL studies also revealed that behaviour and body size/growth were genetically more complex by having more QTL than pelvic traits. However, in many cases, pelvic structure, body size/growth and behaviour were linked to similar map locations indicating possible pleiotropic effects of genes locating in these QTL regions. Many of the gene related markers resided in the QTL area. In the future, studying these possible candidate genes in depth might reveal the underlying mechanism behind the measured traits.

Scalable algorithms for height field illumination

Global illumination algorithms are at the center of realistic image synthesis and account for non-trivial light transport and occlusion within scenes, such as indirect illumination, ambient occlusion, and environment lighting. Their computationally most difficult part is determining light source visibility at each visible scene point. Height fields, on the other hand, constitute an important special case of geometry and are mainly used to describe certain types of objects such as terrains and to map detailed geometry onto object surfaces. The geometry of an entire scene can also be approximated by treating the distance values of its camera projection as a screen-space height field. In order to shadow height fields from environment lights a horizon map is usually used to occlude incident light. We reduce the per-receiver time complexity of generating the horizon map on N N height fields from O(N) of the previous work to O(1) by using an algorithm that incrementally traverses the height field and reuses the information already gathered along the path of traversal. We also propose an accurate method to integrate the incident light within the limits given by the horizon map. Indirect illumination in height fields requires information about which other points are visible to each height field point. We present an algorithm to determine this intervisibility in a time complexity that matches the space complexity of the produced visibility information, which is in contrast to previous methods which scale in the height field size. As a result the amount of computation is reduced by two orders of magnitude in common use cases. Screen-space ambient obscurance methods approximate ambient obscurance from the depth bu er geometry and have been widely adopted by contemporary real-time applications. They work by sampling the screen-space geometry around each receiver point but have been previously limited to near- field effects because sampling a large radius quickly exceeds the render time budget. We present an algorithm that reduces the quadratic per-pixel complexity of previous methods to a linear complexity by line sweeping over the depth bu er and maintaining an internal representation of the processed geometry from which occluders can be efficiently queried. Another algorithm is presented to determine ambient obscurance from the entire depth bu er at each screen pixel. The algorithm scans the depth bu er in a quick pre-pass and locates important features in it, which are then used to evaluate the ambient obscurance integral accurately. We also propose an evaluation of the integral such that results within a few percent of the ray traced screen-space reference are obtained at real-time render times.

Efficient Optimization Algorithms for Nonlinear Data Analysis

Identification of low-dimensional structures and main sources of variation from multivariate data are fundamental tasks in data analysis. Many methods aimed at these tasks involve solution of an optimization problem. Thus, the objective of this thesis is to develop computationally efficient and theoretically justified methods for solving such problems. Most of the thesis is based on a statistical model, where ridges of the density estimated from the data are considered as relevant features. Finding ridges, that are generalized maxima, necessitates development of advanced optimization methods. An efficient and convergent trust region Newton method for projecting a point onto a ridge of the underlying density is developed for this purpose. The method is utilized in a differential equation-based approach for tracing ridges and computing projection coordinates along them. The density estimation is done nonparametrically by using Gaussian kernels. This allows application of ridge-based methods with only mild assumptions on the underlying structure of the data. The statistical model and the ridge finding methods are adapted to two different applications. The first one is extraction of curvilinear structures from noisy data mixed with background clutter. The second one is a novel nonlinear generalization of principal component analysis (PCA) and its extension to time series data. The methods have a wide range of potential applications, where most of the earlier approaches are inadequate. Examples include identification of faults from seismic data and identification of filaments from cosmological data. Applicability of the nonlinear PCA to climate analysis and reconstruction of periodic patterns from noisy time series data are also demonstrated. Other contributions of the thesis include development of an efficient semidefinite optimization method for embedding graphs into the Euclidean space. The method produces structure-preserving embeddings that maximize interpoint distances. It is primarily developed for dimensionality reduction, but has also potential applications in graph theory and various areas of physics, chemistry and engineering. Asymptotic behaviour of ridges and maxima of Gaussian kernel densities is also investigated when the kernel bandwidth approaches infinity. The results are applied to the nonlinear PCA and to finding significant maxima of such densities, which is a typical problem in visual object tracking.

Differential evolution based classification with pool of distances and aggregation operators

The objective of this thesis is to develop and generalize further the differential evolution based data classification method. For many years, evolutionary algorithms have been successfully applied to many classification tasks. Evolution algorithms are population based, stochastic search algorithms that mimic natural selection and genetics. Differential evolution is an evolutionary algorithm that has gained popularity because of its simplicity and good observed performance. In this thesis a differential evolution classifier with pool of distances is proposed, demonstrated and initially evaluated. The differential evolution classifier is a nearest prototype vector based classifier that applies a global optimization algorithm, differential evolution, to determine the optimal values for all free parameters of the classifier model during the training phase of the classifier. The differential evolution classifier applies the individually optimized distance measure for each new data set to be classified is generalized to cover a pool of distances. Instead of optimizing a single distance measure for the given data set, the selection of the optimal distance measure from a predefined pool of alternative measures is attempted systematically and automatically. Furthermore, instead of only selecting the optimal distance measure from a set of alternatives, an attempt is made to optimize the values of the possible control parameters related with the selected distance measure. Specifically, a pool of alternative distance measures is first created and then the differential evolution algorithm is applied to select the optimal distance measure that yields the highest classification accuracy with the current data. After determining the optimal distance measures for the given data set together with their optimal parameters, all determined distance measures are aggregated to form a single total distance measure. The total distance measure is applied to the final classification decisions. The actual classification process is still based on the nearest prototype vector principle; a sample belongs to the class represented by the nearest prototype vector when measured with the optimized total distance measure. During the training process the differential evolution algorithm determines the optimal class vectors, selects optimal distance metrics, and determines the optimal values for the free parameters of each selected distance measure. The results obtained with the above method confirm that the choice of distance measure is one of the most crucial factors for obtaining higher classification accuracy. The results also demonstrate that it is possible to build a classifier that is able to select the optimal distance measure for the given data set automatically and systematically. After finding optimal distance measures together with optimal parameters from the particular distance measure results are then aggregated to form a total distance, which will be used to form the deviation between the class vectors and samples and thus classify the samples. This thesis also discusses two types of aggregation operators, namely, ordered weighted averaging (OWA) based multi-distances and generalized ordered weighted averaging (GOWA). These aggregation operators were applied in this work to the aggregation of the normalized distance values. The results demonstrate that a proper combination of aggregation operator and weight generation scheme play an important role in obtaining good classification accuracy. The main outcomes of the work are the six new generalized versions of previous method called differential evolution classifier. All these DE classifier demonstrated good results in the classification tasks.

Hardware Accelarated Visual Tracking Algorithms. A Systematic Literature Review

Many industrial applications need object recognition and tracking capabilities. The algorithms developed for those purposes are computationally expensive. Yet ,real time performance, high accuracy and small power consumption are essential measures of the system. When all these requirements are combined, hardware acceleration of these algorithms becomes a feasible solution. The purpose of this study is to analyze the current state of these hardware acceleration solutions, which algorithms have been implemented in hardware and what modifications have been done in order to adapt these algorithms to hardware.

3D Mesh Simplification. A survey of algorithms and CAD model simplification tests

Simplification of highly detailed CAD models is an important step when CAD models are visualized or by other means utilized in augmented reality applications. Without simplification, CAD models may cause severe processing and storage is- sues especially in mobile devices. In addition, simplified models may have other advantages like better visual clarity or improved reliability when used for visual pose tracking. The geometry of CAD models is invariably presented in form of a 3D mesh. In this paper, we survey mesh simplification algorithms in general and focus especially to algorithms that can be used to simplify CAD models. We test some commonly known algorithms with real world CAD data and characterize some new CAD related simplification algorithms that have not been surveyed in previous mesh simplification reviews.