Ekologisten ja evolutiivisten prosessien mallinnus tilarakenteisissa populaatioissa

Many species inhabit fragmented landscapes, resulting either from anthropogenic or from natural processes. The ecological and evolutionary dynamics of spatially structured populations are affected by a complex interplay between endogenous and exogenous factors. The metapopulation approach, simplifying the landscape to a discrete set of patches of breeding habitat surrounded by unsuitable matrix, has become a widely applied paradigm for the study of species inhabiting highly fragmented landscapes. In this thesis, I focus on the construction of biologically realistic models and their parameterization with empirical data, with the general objective of understanding how the interactions between individuals and their spatially structured environment affect ecological and evolutionary processes in fragmented landscapes. I study two hierarchically structured model systems, which are the Glanville fritillary butterfly in the Åland Islands, and a system of two interacting aphid species in the Tvärminne archipelago, both being located in South-Western Finland. The interesting and challenging feature of both study systems is that the population dynamics occur over multiple spatial scales that are linked by various processes. My main emphasis is in the development of mathematical and statistical methodologies. For the Glanville fritillary case study, I first build a Bayesian framework for the estimation of death rates and capture probabilities from mark-recapture data, with the novelty of accounting for variation among individuals in capture probabilities and survival. I then characterize the dispersal phase of the butterflies by deriving a mathematical approximation of a diffusion-based movement model applied to a network of patches. I use the movement model as a building block to construct an individual-based evolutionary model for the Glanville fritillary butterfly metapopulation. I parameterize the evolutionary model using a pattern-oriented approach, and use it to study how the landscape structure affects the evolution of dispersal. For the aphid case study, I develop a Bayesian model of hierarchical multi-scale metapopulation dynamics, where the observed extinction and colonization rates are decomposed into intrinsic rates operating specifically at each spatial scale. In summary, I show how analytical approaches, hierarchical Bayesian methods and individual-based simulations can be used individually or in combination to tackle complex problems from many different viewpoints. In particular, hierarchical Bayesian methods provide a useful tool for decomposing ecological complexity into more tractable components.Ekologisten ja evolutiivisten prosessien mallinnus tilarakenteisissa populaatioissa Monet lajit asuttavat maisemia joiden rakenne on pirstoutunut joko luonnostaan tai ihmisen toimesta. Tällaisia maisemia asuttavien populaatioden ekologiseen ja evolutiiviseen dynamiikkaan vaikuttaa hyvin monenlaisten tekijöiden vuorovaikutus, ja niiden tutkimus on siten haastavaa. Väitöskirjassani olen kehittänyt matemaattisia ja tilastotieteellisiä menetelmiä tilassa pirstoutuneiden populaatioiden ekologian ja evoluutiobiologian tarkasteluun. Olen testannut ja soveltanut kehittämiäni menetelmiä käyttäen empiirisiä aineistoja kahdesta mallisysteemistä, jotka ovat Ahvenanmaan täpläverkkoperhonen ja Tvärminnen saarten kirvapopulaatiot. Molemmat systeemit ovat rakenteeltaan hierarkisia, eli lajeille sopiva elinympäristö esiintyy pienten laikkujen muodostamina verkostoina, ja yksittäiset osaverkostot ovat osa laajempaa kokonaisuutta. Tällaisista systeemeistä kerättyjä aineistoja on luontevaa analysoida käyttäen hierarkisia Bayesilaisia malleja, ja väitöskirjatyöni keskeinen osa on näiden mallien kehittämisessä ja parametrisoinnissa. Pirstouneiden maisemien populaatiodynamiikka riippuu yksilöiden kyvystä liikkua elinympäristölaikulta toiselle, ja väitöskirjatyöni toinen painopistealue on yksilöiden liikkumisen matemaattisessa mallintamisessa

Accurate genotype imputation in multiparental populations from low-coverage sequence

Many different types of multiparental populations have recently been produced to increase genetic diversity and resolution in QTL mapping. Low-coverage, genotyping-by-sequencing (GBS) technology has become a cost-effective tool in these populations, despite large amounts of missing data in offspring and founders. In this work, we present a general statistical framework for genotype imputation in such experimental crosses from low-coverage GBS data. Generalizing a previously developed hidden Markov model for calculating ancestral origins of offspring DNA, we present an imputation algorithm that does not require parental data and that is applicable to bi-and multiparental populations. Our imputation algorithm allows heterozygosity of parents and offspring as well as error correction in observed genotypes. Further, our approach can combine imputation and genotype calling from sequencing reads, and it also applies to called genotypes from SNP array data. We evaluate our imputation algorithm by simulated and real data sets in four different types of populations: the F2, the advanced intercross recombinant inbred lines, the multiparent advanced generation intercross, and the cross-pollinated population. Because our approach uses marker data and population design information efficiently, the comparisons with previous approaches show that our imputation is accurate at even very low (< 1 ×) sequencing depth, in addition to having accurate genotype phasing and error detection.</p

Modelling single nucleotide effects in phosphoglucose isomerase on dispersal in the Glanville fritillary butterfly: coupling of ecological and evolutionary dynamics

Dispersal comprises a complex life-history syndrome that influences the demographic dynamics of especially those species that live in fragmented landscapes, the structure of which may in turn be expected to impose selection on dispersal. We have constructed an individual-based evolutionary sexual model of dispersal for species occurring as metapopulations in habitat patch networks. The model assumes correlated random walk dispersal with edge-mediated behaviour (habitat selection) and spatially correlated stochastic local dynamics. The model is parametrized with extensive data for the Glanville fritillary butterfly. Based on empirical results for a single nucleotide polymorphism (SNP) in the phosphoglucose isomerase (Pgi) gene, we assume that dispersal rate in the landscape matrix, fecundity and survival are affected by a locus with two alleles, A and C, individuals with the C allele being more mobile. The model was successfully tested with two independent empirical datasets on spatial variation in Pgi allele frequency. First, at the level of local populations, the frequency of the C allele is the highest in newly established isolated populations and the lowest in old isolated populations. Second, at the level of sub-networks with dissimilar numbers and connectivities of patches, the frequency of C increases with decreasing network size and hence with decreasing average metapopulation size. The frequency of C is the highest in landscapes where local extinction risk is high and where there are abundant opportunities to establish new populations. Our results indicate that the strength of the coupling of the ecological and evolutionary dynamics depends on the spatial scale and is asymmetric, demographic dynamics having a greater immediate impact on genetic dynamics than vice versa

Whole genome resequencing and phenotyping of MAGIC population for high resolution mapping of drought tolerance in chickpea

Terminal drought is one of the major constraints to crop production in chickpea (Cicer arietinum L.). In order to map drought tolerance related traits at high resolution, we sequenced multi-parent advanced generation intercross (MAGIC) population using whole genome resequencing approach and phenotyped it under drought stress environments for two consecutive years (2013-14 and 2014-15). A total of 52.02 billion clean reads containing 4.67 TB clean data were generated on the 1136 MAGIC lines and eight parental lines. Alignment of clean data on to the reference genome enabled identification of a total, 932,172 of SNPs, 35,973 insertions, and 35,726 deletions among the parental lines. A high-density genetic map was constructed using 57,180 SNPs spanning a map distance of 1606.69 cM. Using compressed mixed linear model, genome-wide association study (GWAS) enabled us to identify 737 markers significantly associated with days to 50% flowering, days to maturity, plant height, 100 seed weight, biomass, and harvest index. In addition to the GWAS approach, an identity-by-descent (IBD)-based mixed model approach was used to map quantitative trait loci (QTLs). The IBD-based mixed model approach detected major QTLs that were comparable to those from the GWAS analysis as well as some exclusive QTLs with smaller effects. The candidate genes like FRIGIDA and CaTIFY4b can be used for enhancing drought tolerance in chickpea. The genomic resources, genetic map, marker-trait associations, and QTLs identified in the study are valuable resources for the chickpea community for developing climate resilient chickpeas

Modeling X-linked ancestral origins in multiparental populations

The models for the mosaic structure of an individual's genome from multiparental populations have been developed primarily for autosomes, whereas X chromosomes receive very little attention. In this paper, we extend our previous approach to model ancestral origin processes along two X chromosomes in a mapping population, which is necessary for developing hidden Markov models in the reconstruction of ancestry blocks for X-linked quantitative trait locus mapping. The model accounts for the joint recombination pattern, the asymmetry between maternally and paternally derived X chromosomes, and the finiteness of population size. The model can be applied to various mapping populations such as the advanced intercross lines (AIL), the Collaborative Cross (CC), the heterogeneous stock (HS), the Diversity Outcross (DO), and the Drosophila synthetic population resource (DSPR). We further derive the map expansion, density (per Morgan) of recom-bination breakpoints, in advanced intercross populations with L inbred founders under the limit of an infinitely large population size. The analytic results show that for X chromosomes the genetic map expands linearly at a rate (per generation) of two-thirds times 1 - 10/(9L) for the AIL, and at a rate of two-thirds times 1 - 1/L for the DO and the HS, whereas for autosomes the map expands at a rate of 1 - 1/L for the AIL, the DO, and the HS

Coverage, step and quantum effects on surface diffusion of H on Pt(111) surfaces

Surface diffusion of H on Pt(111) surface has been studied systematically by a linear optical diffraction technique. The coverage-dependent diffusion coefficients on flat Pt(111) surface were measured over a wide H coverage range from 0.1 to 0.8ML. These results were analyzed within the framework of the lattice gas model using the quasi-chemical approximation, indicating that H-H repulsive interaction can significantly affect the energy of saddle points as well as that at the adsorption sites. Step effects on surface diffusion of hydrogen on stepped Pt(111) have been studied over a temperature range from 90K to 150K. Diffusion anisotropy on stepped Pt(111) surfaces has been observed: the unexpected enhanced diffusion perpendicular to steps cannot be explained within the lattice gas model on stepped substrates, manifesting a non-local and directional step effect. A nearly temperature independent diffusion coefficient of H on flat Pt(111) surfaces at low temperature regime was observed, marking diffusion of H atoms by quantum tunnelling. The almost constant quantum diffusion coefficient below the temperature of 95K is ~2x10-11 cm2/s, consistent with the theoretical prediction of 6x10-10 cm2/s. The strong isotope effects on quantum diffusion at low temperature were explained within the theoretical prediction and the simple WKB approximation

Heritage and Tourism Conflict Within World Heritage Sites in China: A Longitudinal Study

Although the conflicting relationship between heritage and tourism has been debated at length in the Western academic literature, interest in the relationship is now becoming increasingly pronounced across the developing world with particular interest noted in China. To examine this phenomenon further, this study explores the cause and temporal variation of conflicts between heritage and tourism over the past decade in China. Content analysis was adopted as the most appropriate methodology for the study with data from online media reports serving as the primary data for the analysis of the occurrence of heritage and tourism conflicts in China. The findings highlight antiquated management structures, inappropriate tourism operations, and the ineffective use or deficiency of legislation as the primary causes of heritage and tourism conflicts in China with the categories of conflicts varying from clashes relating to resource use to clashes over values. The findings also shed light on the significant role played by the media in the resolution of conflicts. Finally, implications and limitations of the study\u27s findings are discussed

Reconstruction of genome ancestry blocks in multiparental populations

We present a general hidden Markov model framework called reconstructing ancestry blocks bit by bit (RABBIT) for reconstructing genome ancestry blocks from single-nucleotide polymorphism (SNP) array data, a required step for quantitative trait locus (QTL) mapping. The framework can be applied to a wide range of mapping populations such as the Arabidopsis multiparent advanced generation intercross (MAGIC), the mouse Collaborative Cross (CC), and the diversity outcross (DO) for both autosomes and X chromosomes if they exist. The model underlying RABBIT accounts for the joint pattern of recombination breakpoints between two homologous chromosomes and missing data and allelic typing errors in the genotype data of both sampled individuals and founders. Studies on simulated data of the MAGIC and the CC and real data of the MAGIC, the DO, and the CC demonstrate that RABBIT is more robust and accurate in reconstructing recombination bin maps than some commonly used methods.</p

Reconstruction of genome ancestry blocks in multiparental populations

We present a general hidden Markov model framework called reconstructing ancestry blocks bit by bit (RABBIT) for reconstructing genome ancestry blocks from single-nucleotide polymorphism (SNP) array data, a required step for quantitative trait locus (QTL) mapping. The framework can be applied to a wide range of mapping populations such as the Arabidopsis multiparent advanced generation intercross (MAGIC), the mouse Collaborative Cross (CC), and the diversity outcross (DO) for both autosomes and X chromosomes if they exist. The model underlying RABBIT accounts for the joint pattern of recombination breakpoints between two homologous chromosomes and missing data and allelic typing errors in the genotype data of both sampled individuals and founders. Studies on simulated data of the MAGIC and the CC and real data of the MAGIC, the DO, and the CC demonstrate that RABBIT is more robust and accurate in reconstructing recombination bin maps than some commonly used methods

Joint inference of identity by descent along multiple chromosomes from population samples

There has been much interest in detecting genomic identity by descent (IBD) segments from modern dense genetic marker data and in using them to identify human disease susceptibility loci. Here we present a novel Bayesian framework using Markov chain Monte Carlo (MCMC) realizations to jointly infer IBD states among multiple individuals not known to be related, together with the allelic typing error rate and the IBD process parameters. The data are phased single nucleotide polymorphism (SNP) haplotypes. We model changes in latent IBD state along homologous chromosomes by a continuous time Markov model having the Ewens sampling formula as its stationary distribution. We show by simulation that this model for the IBD process fits quite well with the coalescent predictions. Using simulation data sets of 40 haplotypes over regions of 1 and 10 million base pairs (Mbp), we show that the jointly estimated IBD states are very close to the true values, although the presence of linkage disequilibrium decreases the accuracy. We also present comparisons with the ibd-haplo program, which estimates IBD among sets of four haplotypes. Our new IBD detection method focuses on the scale between genome-wide methods using simple IBD models and complex coalescent-based methods that are limited to short genome segments. At the scale of a few Mbp, our approach offers potentially more power for fine-scale IBD association mapping.</p