Rozprawy doktorskie na temat „Variation (biology)”

Temporal and spatial variation in the environment can influence the performance of individuals in wild ungulate populations. Of particular importance is an understanding of the mechanisms that shape variation in individual body mass, because several important life history traits are directly related to body mass. Body mass is one of the first traits that is influenced by environmental variation, and often the effect operates through variation in the components of the foraging niche of ungulates. In this thesis, I aim to demonstrate how measurements of environmental variation relate to variation in the foraging niche of ungulates. Furthermore, I aim to explore how variation in ungulate life history traits relates to these variables, and finally, how the management of ungulates could benefit from the incorporation of knowledge about the effects of environmental variation on population dynamics. I use weather observations, large-scale climate indices, and indices of environmental phenology based on satellite-derived vegetation indices (NDVI) to analyse the effect of environmental variation on plants and body mass in moose (Alces alces) and roe deer (Capreolus capreolus) populations.

The environmental variables that explained most of the variation in plant performance, measured as radial growth in common juniper (Juniper communis) also explained variation in ungulate body mass. These variables were related to conditions in spring and early summer. Plant growth was low in cold summers, and in spring where the green-up curve as measured by change in photosynthetic activity during spring was moderate. Such growing conditions are recognised to increase the quality of the plants as forage for ungulates. Consequently, moose body mass in autumn showed the opposite pattern than juniper to environmental conditions, indicating that quality of plants, rather than the quantity, is an important component in temperate ungulate foraging niche. Further, regional variation in moose body mass was associated with environmental variables related to forage quality. Roe deer body mass was associated with availability of forage during winter, and not with factors related to summer conditions. Factors related to forage quantity neither influenced temporal nor spatial variation in body mass in the two species.

Accordingly, it appears that both weather observations and satellite-derived vegetation indices are able to effectively predict variation in plant performance related to variation in foraging conditions for ungulates. The variation in forage quality in space and time created variation in body mass between populations and between cohorts within a population. Further, the variation in body mass between moose population, caused by variation in the foraging conditions, predicted how the populations differentially respond to the effects of environmental stochastisity. In populations with a high mean body mass, or a low density relative to plant biomass production, available resources buffered environmental stochastisity, and were less influenced by environmental variation than populations with relatively fewer resources available.

If wildlife managers fail to incorporate the effects of environmental variation on population performance, e.g. on the recruitment rate, the population may show unexpected and large fluctuations in size. Therefore, managers should attempt to incorporate knowledge of recent environmental conditions on the population when setting harvesting quotas.

In face of the large variation in environmental conditions experienced by the ungulate populations in Norway, and the fact that responses to environmental variation varies between populations, management should be regionally adapted, and aim to incorporate variation in vital rates caused by environmental conditions. This is likely to create more stable and predictable populations. In face of the predicted climate and landscape changes in Norwegian forests, environmental variables, e.g. from satellite-derived vegetation indices, have the potential to be a powerful tool for a sustainable management of ungulate populations. Consequently, such information should be incorporated into the management of ungulates in order to a) obtain a management of ungulate populations that is adapted to regional mechanisms of environmental variation, and b) acquire a management that is sustainable in face of future change in climate and landscape that may vary regionally. This calls for a regional differentiation in management strategies.

In this thesis the genetic variation of two grouse species, the Chinese grouse (Bonasa sewersowi) and the Black grouse (Tetrao tetrix) was examined with neutral genetic markers: microsatellites. Habitat fragmentation and isolation leads to structuring among and loss of genetic variation within populations.

The Chinese grouse in a small population in Lianhuasan nature reserve was found to have undergone a population bottleneck and as a result of isolation and possible inbreeding showed genetic impoverishment hereof.

The Black grouse populations in Europe face various different conditions from widely distributed areas of suitable habitat in the northern and eastern parts of its range to highly naturally and anthropogenically fragmented habitat landscapes in the west.

Structure among populations was found in Great Britain where Wales, Scotland and England showed characteristics of three different genetic entities, indicating very little or no geneflow between these populations.

The Dutch population showed signs of loss of genetic variation as to be expected from a population that has historically decreased in population size from several thousands to tens of individuals in a matter of decades. However the possibility to spot signs of a bottleneck was impaired due to the short time-window in which this can be observed in a population with such a low effective population size (N_E).

The sampled populations in Europe clustered into five different groups of genetic identities. The different clusters were: Great Britain-, the Netherlands-, Fenno-Scandian-, Alpine- and lowland German-Austrian populations. The level of genetic variation when compared over all these different populations decreased as a sign of isolation and small N_E. However it was not feasible to separate the impact of these two factors.

Viral infection and the subsequent immune responses such as the expression of interferon beta (ifnb1) show extreme levels of cell to cell variability. A fraction of cells get infected and a fraction of infected cells induce an ifnb1 response. These responding cells then signal to coordinate appropriate immune responses required to clear infection. The mechanism of propagation of this response at the single cell level is critical to generate an appropriate defense against the virus, yet is incompletely understood.

Interesting work on cell to cell variability has been done using transfected ifnb1 reporter constructs. However, this approach has several limitations. The reporter systems introduce multiple copies of the reporter construct in each cell, which does not reflect the conditions in the intact cells where only two of the interferon promoter and gene are present. This alters the ifnb1 enhanceosome stoichiometry from the one present in a normal physiological environment, and potentially distorts the patterns of single cell responses observed. In addition, reporter constructs integrate the response that occur over many hours, which makes it difficult to measure the expression dynamics that occur early after exposure to infection. Such measurements in the intact cells would be helpful for understanding the mechanisms underlying the propagation of this immune response.

In order to obtain sensitive and accurate measurements of changes in gene expression in infected single cells, we used single-cell single-molecule mRNA imaging to directly and simultaneously count the transcripts of ifnb1 and that of a virus (Newcastle disease virus) gene Hemagglutinin-neuraminidase hn . This experimental approach enabled us to measure the single-cell responses from the very early stages of infection, in primary immune cells. Simultaneous measurement of ifnb1 and the viral gene hn high lighted the variation in responses across cells, the temporal evolution of the expression of the two genes and their single cell correlation following infection.

We find that the single cell ifnb1 response to virus infection shows a temporally dispersed (asynchronous) pattern. A small fraction of infected cells respond very early and more ifnb1 expressing cells are recruited at later time after infection. In contrast, the single ifnb1 response to the toll like receptor stimulant LPS, follows a highly synchronous pattern, where in a large number of cells showed an ifnb1 response around the same time after treatment. These results suggest that the temporal evolution of single cell ifnb1 responses was likely dependent on the type of the inducing stimuli. Furthermore we observed that extracellular signaling plays an important role in introducing cell-to-cell variability in ifnb1gene induction in response to virus infection. Inhibition of extracellular signaling converted the response to virus infection into an early synchronous LPS-like response. Thus extracellular signaling shapes the temporally dispersed pattern of single cell ifnb1 response to viral infection.

The pattern of ifnb1 responses to virus infection involves an increase in the amplitude of the response per cell as well as an increase in the number of responding cells over time of infection. These properties may enable cells to fine tune the ifnb1 responses gradually. This strategy of mounting an antiviral cytokine response may be useful in calibrating the immune response such that an appropriate antiviral response is generated and cellular toxicity resulting from excessive cytokine expression is usually avoided.

The Baltic Sea is an evolutionary young sea that have developed a low salinity in its water from the fresh water that flows from the north and saltwater that flows from the south of the sea. The low salinity is too low for many marine organisms and too high for many freshwater organisms. Species like the blue mussel, which have adapted to the low salinity, may have developed different protein expression as a result. To study which protein that have been expressed in the organism proteome analysis is often used. 2-dimensional electrophoresis may be the only method that can do this kind of analysis.

I found that in inbred females D. melanogaster, physical condition plays a major role in the amount of polyandry. In some systems there is evidence that the ability to self assess allows inbred females to vary their reproductive behavior to increase promiscuity. I predicted that this may be true in Drosophila melanogaster females, but we found that inbred females behaved less promiscuously in three proxies than outbred females. Inbred females mated with fewer total males, fewer different males, and had longer copulation latency than their outbred conspecifics. However, male mate choice is not predicted in Drosophila melanogaster because males invest less than females, but recently the importance of male preference has been gaining support. How these males are making decisions is an important component to understanding the evolutionary impacts of the male's behaviors. I found that male mate choices are heavily influenced by previous experiences, and the lack of experience causes significant changes in courtship latency and overall preferences.

Nordihydroguaiaretic acid (NDGA) is the principal compound in the resinous leaf coating of Larrea tridentata (creosote bush), the dominant shrub of North American deserts. L. tridentata exists as three polyploid races: diploid (2X = 26), tetraploid (4X = 52), and hexaploid (6X = 78). The distributions of these ploidy levels are strongly associated with the three major deserts of the region where diploids primarily reside in the cooler, wetter Chihuahuan desert, tetraploids in the Sonoran desert, and hexaploids in the hot, dry Mojave desert. NDGA is a secondary metabolite of creosote bush that functions to protect plants from biotic and abiotic stressors such as extreme drought, harmful UV radiation, and herbivory. Here, I investigated the role of polyploidy and environmental variables on the production of NDGA by quantifying concentrations from field and greenhouse-grown polyploids. Citizen scientists were utilized to facilitate simultaneous sampling across the entire distributional range of this species, for one full year. Under natural conditions, shrubs produced significantly higher NDGA concentrations than when removed from the harsh desert environment. In field and greenhouse treatments, hexaploids exhibited higher NDGA concentrations than diploids or tetraploids. Within the diploid cytotype, I documented environmental influences on NDGA concentration based on comparisons between a field site experiencing severe drought, a watered field site, and greenhouse-grown diploids. Principal components analysis revealed that NDGA response to environmental variables successfully predicts the current ploidy distribution of this species. These observations highlight the complexity of plant-environment-genotype interactions and suggest that evolution in production of secondary metabolites may be driven by long-term changes in environmental conditions, and potentially influence species distribution regimes.

Genome sequencing technology has enabled the identification of genetic variants that are linked with cancer phenotypes, whether these are somatically acquired mutations or common inherited single nucleotide polymorphisms (SNPs). Whereas coding variants have been reported to disrupt protein function to promote cancer, most variants map to noncoding regions, with no known function. Recently, much effort has gone into annotating the human noncoding genome, enabling the characterization of the functional basis of noncoding SNPs. As an example of functional impact, breast cancer (BrCa) risk-associated SNPs can alter transcription factor binding at distal enhancers.

Identifying the targets of risk SNPs remains a challenge. One reason for this is the complex three-dimensional structure of the genome. Local chromatin openness correlates with chromatin activity, and sites of chromatin that are open concurrently across multiple cell types indicates a functional relationship between them. We mapped BrCa risk-associated SNPs to regions of open chromatin to predict the most likely functional risk SNPs. Then, we predicted their targets by identifying the gene promoters whose openness correlated with these risk regions. Further, we validated a gene which is a novel therapeutic target and relevant in breast cancer biology.

In addition to SNPs, noncoding somatic mutations are also predicted to play a role in cancer. In 2012, driver mutations were reported in the telomerase gene promoter, hinting at the relevance of mutations in regulatory elements. This is particularly true when considering oncogenes whose elevated expression in certain cancers is not attributable to coding mutations or copy number amplification. We reveal the enrichment and functional nature of somatic mutations mapping to enhancers that regulate the estrogen receptor gene, which is known to drive over two-thirds of breast cancer.

Attributing function to noncoding SNPs and mutations associated with cancer risk and progression is a growing necessity in this era of whole-genome cancer biology. This thesis demonstrates a methodology to identify the functional consequence and gene targets of significantly mutated or risk variant-bearing enhancer sets to narrow the gap between known and unknown risk factors in BrCa.