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Comparative chromosome-painting analysis among highly rearranged karyotypes of Sigmodontinae rodents (Rodentia, Cricetidae) detects conserved syntenic blocks, which are proposed as chromosomal signatures and can be used as phylogenetic markers. In the Akodontini tribe, the molecular topology (Cytb and/or IRBP) shows five low-supported clades (divisions: “Akodon”, “Bibimys”, “Blarinomys”, “Oxymycterus”, and “Scapteromys”) within two high-supported major clades (clade A: “Akodon”, “Bibimys”, and “Oxymycterus”; clade B: “Blarinomys” and “Scapteromys”). Here, we examine the chromosomal signatures of the Akodontini tribe by using Hylaeamys megacephalus (HME) probes to study the karyotypes of Oxymycterus amazonicus (2n = 54, FN = 64) and Blarinomys breviceps (2n = 28, FN = 50), and compare these data with those from other taxa investigated using the same set of probes. We strategically employ the chromosomal signatures to elucidate phylogenetic relationships among the Akodontini. When we follow the evolution of chromosomal signature states, we find that the cytogenetic data corroborate the current molecular relationships in clade A nodes. We discuss the distinct events that caused karyotypic variability in the Oxymycterus and Blarinomys genera. In addition, we propose that Blarinomys may constitute a species complex, and that the taxonomy should be revised to better delimit the geographical boundaries and their taxonomic status.
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The focus of this contribution is on weak productivity growth, in the UK and other advanced economies, which has been slowing down ever since around 2000, and on increasing income inequality; both of which have been caused by a number of factors, including ‘secular stagnation’. Actually recent evidence clearly suggests that labour productivity and income inequality have been closely and significantly related; this is so since there is a strong relationship between productivity, inequality, economic growth and real wages. Productivity growth is the key determinant of how demand can grow without inflation, thereby reducing inequality of income. The slowdown in productivity growth and increase in inequality have been in evidence in the UK and other advanced economies. Indeed, they have become more pronounced following the Global Financial Crisis. It is the case that although weak productivity growth and increased income inequality predate the Global Financial Crisis, and the Great Recession, they have clearly worsened following them.
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Salmonellae are Gram-negative, predominantly flagellated, facultative intracellular bacteria, and are an important cause of enteric disease in humans and in animal hosts worldwide. Their transmission is predominantly via the faeco-oral route and members of the Salmonella enterica species can be arbitrarily classified into typhoidal and non-typhoidal types based on their pathogenicity in a particular host. Salmonella enterica serovar Typhi (S. Typhi) and Salmonella enterica serovar Paratyphi A (S. Paratyphi A) cause typhoid and paratyphoid fevers respectively, which are collectively associated with ~25 million cases and 250,000 deaths per year, predominantly concentrated in regions of Asia and Africa where sanitation and clean water are difficult to access. Non-typhoidal serovars (NTS) (e.g. S. enterica serovar Typhimurium (S. Typhimurium), S. enterica serovar Enteritidis (S. Enteritidis)) are responsible for over 93 million infections and ~155,000 deaths worldwide per year, the majority of which are thought to be food-borne infections. NTS infections usually cause self-limiting gastroenteritis, but can progress to invasive disease (iNTS) with bacteraemia and a mortality rate as high as 25% in certain patients. S. Typhi and S. Paratyphi A are pathogens restricted to humans, meaning that there has been difficulty until recently in producing a valid model with which to study pathogen-mucosal interactions and learn more about the invasion mechanisms of these unique pathogens. Although S. Typhimurium is predominantly associated with a localised gastroenteritis in immunocompetent humans; it causes a typhoid-like disease in mice; therefore mouse models have previously been used as surrogates to provide concepts about the interaction between S. Typhi and the host mucosa and resultant immune response. However, in recent years, a new approach to studying pathogen-gut epithelial interactions has been developed; known as “organoids” or human intestinal organoid systems (iHO). These can be produced from human induced pluripotent stem cells (hiPSCs), or from primary intestinal tissue, and once matured, harbour differentiated enterocytes and secretory cells such as goblet, Paneth and enteroendocrine cells. They have previously proved capable of providing a complementary human model for studying S. Typhimurium infection, but their utility has been explored during this project to include the human gut epithelial interaction with other serovars of Salmonella (in particular typhoidal strains, which have never been studied in this context) and the transcriptomic/phenotypic response to these enteric pathogens. In vivo, intestinal epithelial cells (IECs) play a key role in regulating intestinal homeostasis, and can directly inhibit pathogens, although the mechanisms by which this occurs are not well understood. I have demonstrated that the cytokine IL-22 has a role in IEC defence against S. Typhimurium in the hiPSC-derived iHO system, with evidence for restriction of intracellular infection of wild type S. Typhimurium SL1344 in iHO pre-treated with recombinant human IL-22. I have demonstrated that a mechanism via which this protection occurs is increased phagolysosomal fusion. I have also modelled infections with alternative types of bacteria, including S. Enteritidis and enteropathogenic Escherichia coli (EPEC); investigating whether luminal killing of bacteria occurs within the iHO system. I have used iHO derived from stem cells with induced mutations to explore genes of interest in epithelial defence. Lastly, I have demonstrated that typhoid-causing Salmonellae (S. Typhi and S. Paratyphi A) are able to invade both the iHO epithelium and hiPSC-derived macrophages from the same cell line. I investigated these interactions using imaging and bulk RNA-Seq to identify differences in response to the bacteria in the epithelial and immune cell compartments. Strikingly, genes differentially expressed in IECs showed most similarities in response to infection with non-encapsulated serovars (S. Paratyphi A and S. Typhimurium versus S. Typhi), whereas genes differentially expressed in macrophages demonstrated most overlap in response to typhoid-causing strains (S. Typhi and S. Paratyphi A versus S. Typhimurium), raising important questions about the immunomodulatory role of the Vi capsule and the apparent ability of S. Paratyphi to behave differently in the epithelial and macrophage environments. It was also possible to demonstrate that H58 serovars of S. Typhi caused distinct transcriptional signatures in the macrophage model, versus their non-H58 counterparts. I present this novel data and discuss how this complements what is currently known about the host-pathogen interactions of typhoid-causing Salmonellae.
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Dans cet article nous explorons la distribution syntaxique et la fonction du mot sí en catalan ancien, en démontrant que déjà au XIIIe siècle, il avait été grammaticalisé en particule de polarité emphatique et présentait une syntaxe innovante, parallèle à celle de l’espagnol moderne, contrairement aux analyses de sí proposées pour l’italien ou le français ancien.
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Knowing the localisation and spatial organisation of proteins is crucial for understanding their function. The development of super-resolution imaging has improved our ability to garner this information, but counting individual molecules in densely-packed assemblies is still challenging. DNA-based point accumulation for imaging in nanoscale topography (DNA-PAINT) is one of the most recently developed imaging techniques in super-resolution microscopy. It uses fluorescently-labelled DNA to visualise the molecules of interest with nanometre precision. DNA-PAINT was initially reliant on antibody labelling of in vitro protein targets, however, there is need for an alternative labelling strategy as good antibodies do not exist for many target proteins. Moreover, it is impossible to quantify antibody labelling efficiency, which is a crucial parameter for quantitative imaging. In order to address these issues, I present here an optimised imaging pipeline for protein counting in a thick tissue sample, tens of microns away from the coverslip, for which cell polarity proteins in epithelial cells of the fruit fly (Drosophila melanogaster) egg chambers are given as an example. Firstly, I established an alternative labelling strategy to label polarity proteins for DNA-PAINT imaging using genetically-encoded Halo and SNAP self-labelling enzymes in fruit fly tissue. In this approach, the Halo and SNAP ligands conjugated to DNA react with their respective enzymes to form a covalent bond with the protein of interest in a 1:1 stoichiometry. I then optimised the labelling protocol for imaging the fixed fruit fly tissue and analysed non-specific signal to reduce background during image post-processing. A quantitative Western blot-based gel band shift assay was developed to determine the labelling efficiency of target proteins. Moreover, I used nucleoporin proteins in the nuclear pore complex to calibrate the influx rate of fluorescently-labelled DNA to quantify the number of molecules in super-resolution images. Additionally, I used nucleoporin-160 and nucleoporin-188 to benchmark two-colour super-resolution imaging using DNA-PAINT. Super-resolution imaging of three apical polarity proteins (aPKC, Crumbs, Par6) in the fruit fly egg chambers revealed that they form mesoscopic-sized clusters along the cell junctions. In order to analyse these clusters in a quantitative manner, I collaborated with Leila Muresan to develop an image analysis pipeline. My analysis demonstrated that apical polarity proteins are less concentrated in the cytosol by approximately one order of magnitude. To expand on these observations, the junctional clusters were identified by a mean-shift algorithm and classified according to size, i.e. the number of molecules. The cluster size distribution was then approximated by a mathematical function. The model selection was performed by Bayesian information criteria that was tested on simulated data beforehand. This work provides an optimised imaging pipeline for quantifying the number of protein molecules in a thick biological sample using DNA-PAINT, and proposes a post-processing approach to identify and mathematically describe molecular clustering. These data will prove useful for modelling the spatial organisation of polarity proteins, and provide a framework for greater insight into the biological function of individual proteins.
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Background: The peak width of skeletonized mean diffusivity (PSMD) has been proposed as a fully automated imaging marker of relevance to cerebral small vessel disease (SVD). We assessed PSMD in relation to conventional SVD markers, global measures of neurodegeneration, and cognition. Methods: 145 participants underwent 3T brain MRI and cognitive assessment. 112 were patients with mild cognitive impairment, Alzheimer’s disease, progressive supranuclear palsy, dementia with Lewy bodies, or frontotemporal dementia. PSMD, SVD burden [white matter hyperintensities (WMH), enlarged perivascular spaces (EPVS), microbleeds, lacunes], average mean diffusivity (MD), gray matter (GM), white matter (WM), and total intracranial volume were quantified. Robust linear regression was conducted to examine associations between variables. Dominance analysis assessed the relative importance of markers in predicting various outcomes. Regional analyses examined spatial overlap between PSMD and WMH. Results: PSMD was associated with global and regional SVD measures, especially WMH and microbleeds. Dominance analysis demonstrated that among SVD markers, WMH was the strongest predictor of PSMD. Furthermore, PSMD was more closely associated to WMH than with GM and WM volumes. PSMD was associated with WMH across all regions, and correlations were not significantly stronger in corresponding regions (e.g., frontal PSMD and frontal WMH) compared to non-corresponding regions. PSMD outperformed all four conventional SVD markers and MD in predicting cognition, but was comparable to GM and WM volumes. Discussion: PSMD was robustly associated with established SVD markers. This new measure appears to be a marker of diffuse brain injury, largely due to vascular pathology, and may be a useful and convenient metric of overall cerebrovascular burden.
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Nectar spurs (tubular outgrowths of a floral organ which contain or give the appearance of containing nectar) are hypothesized to be a ‘key innovation’ which can lead to rapid speciation within a lineage, because they are involved in pollinator specificity. However, given that there are no conventional model plant species which possess a nectar spur, much is still unknown about the development and morphogenesis of spurs. This project aimed to determine the molecular and morphological processes underpinning nectar spur development. The well-known study system Antirrhinum majus (snapdragon), which possesses only a nectar pouch, called a gibba, was compared to the common toadflax Linaria vulgaris, a related species within the Antirrhineae which possesses a spur. The comparison between a species with a gibba and a species which possesses a spur allows insights into nectar spur development. A morphological framework was produced and used to inform a comparative transcriptome based on A. majus and L. vulgaris at three key developmental stages. This experiment provides a global view of the genes involved in nectar spur and gibba development and suggests new candidate genes for nectar spur outgrowth. The control of variation in nectar spur length at both a morphological and molecular level was also investigated, focusing on Linaria becerrae and Linaria clementei, sister species which have extremely long and short spurs respectively. A morphological characterisation (recording cell number and cell length across a range of developmental stages) was performed to determine whether the difference is due to cell expansion or cell division. We found that primarily cell number and therefore cell division drives an increase in spur length. This contrasts with previous studies in Aquilegia which have found that variation of nectar spur length is due to directed cell expansion (anisotropy) over a longer timeframe. A genetic approach to understanding genetic basis of spur length was pursued, by crossing L. becerrae and L. clementei, and producing an F2 and backcrosses. This work lays a groundwork for future studies and suggests that the genetic basis of spur length in Linaria may be complex. The morphological and genetic work to investigate control of spur length was complemented by a candidate gene approach. Candidate genes from previous work and suggested by the transcriptome were isolated in L. becerrae and L. clementei and expression in the ventral and dorsal petals tested via sqPCR.
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This dissertation consists of three related essays that contribute to the literature on the behavior of institutional investors and particularly endowments - distinctive because of their long horizon. The vast majority of endowments delegate the management of their assets to external managers. My first essay provides evidence that decisions taken by endowments about their external investment manager appointments (and terminations) are influenced by the behavior of their peers. This analysis exploits a novel hand-collected dataset on U.S. university endowments and their external investment manager appointments across all the main asset classes for each year over 1978-2008. The study documents that endowments are more likely to appoint the same external manager if their peers do so, are more active in hiring and firing managers when their peers are more active and respond faster to hiring and firing decisions by their peers in respect of a given external manager. The second essay examines the network connections between endowments and PE managers. Buyout (BO) and Venture Capital (VC) investment networks are examined separately. Using data from 1988 to 2008, I identify the characteristics of the centrally located endowments and managers in the network. While VC networks were more developed than their BO counterparts at the beginning of the sample period, both networks grew denser over time in terms of number of players and connections. The identity of their key institutions (central endowments and managers) stayed the same throughout the period examined. Centrally located managers have better investment returns and win new endowment mandates in subsequent periods. Personal connections between individuals working at endowments and BO firms also play an important role in manager selection by endowments. The third essay examines the long-term evolution of the investment strategy of U.S. university endowments, using a unique long-term dataset on characteristics and asset allocations from 1900 to 2016 of twelve important endowments. The analysis documents their early adoption of equity investing in the 1930s and their more recent shift into alternative assets from the 1980s. The essay then considers whether endowments famed for their long horizon exploit this advantage to invest countercyclically during periods of market turbulence. I find that endowments do exhibit countercyclical behaviour, decreasing their allocation to risky assets during the run-up to a crisis and increasing it after the onset of a crisis.
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Based on a novel database of kinship relations among the political elites of Chile in the nineteenth century, this thesis identifies the impact of family networks on the formation of political factions in the period 1828-1894. The sociological literature theorising the cleavages that divided elites during the initial phases of state formation has focused on three domains: 1) The conflict between an expanding state and the elites; 2) the conflict between different economic elites; and 3) the conflict between cultural and ideological blocs. This thesis develops a fourth approach referred to as Florentine, which builds on a tradition of historical and sociological research focused on the Italian city-states of the Renaissance. The Florentine approximation is elitist-focused and relational: elitist-focused because it imputes overwhelming power to the oligarchy vis-à-vis other groups in society, and relational because its analytical leverage comes from identifying the effects of networks on political outcomes. The most influential tradition in Chilean historiography sees nineteenth-century politics as shaped by the state-oligarchy opposition. Other approaches highlight the importance of economic sectors and ideological cleavages. In contrast, this thesis presents data demonstrating the importance of the family. The principal political conflict in nineteenth-century Chile consisted of neither the state versus the oligarchy, nor the mining versus the landed elites, nor the Liberals versus the Conservatives, but of elite families fighting other elite families. To develop this argument, this thesis utilised an original database with information on the family relations among all 1449 Parliamentarians, Presidents, and Ministers in the period 1828-1894. These data were combined with information on the electoral performance of all Parliamentarians over six decades. The analysis sought to infer the alignment of families during the civil wars of 1829, 1851, 1859 and 1891. Using social network analysis techniques, kinship clusters were identified, and the resulting groups were then contrasted against the electoral data. If a family cluster was well represented in Congresses immediately before the onset of violent conflicts, it was inferred that the family supported the pre-conflict regimes; where a family bloc increased its representation in post-conflict Congresses, it was concluded that its allegiance was with whatever administration took power after the conflict. Once the political allegiance of families was coded this way, substantive differences in the social status, geographic origin, and political party affiliation of the inferred sides were examined. If they did not differ substantially on these accounts but were differentiated by kinship, then it was concluded that the cleavage explaining the conflict at hand was familial. The results obtained using this procedure enabled a historical description of how elite factions formed in Chile. At its oligarchic core, the civil war of 1829 involved three large family clusters: a defeated cluster around the Vicuña clan, and two victorious clusters organised around the Irarrázaval and Vial clans, respectively. Upon the formation of the so-called Pelucón regime following the civil war, members of the Vial cluster became an internal opposition that would impact the subsequent emergence of political parties. In the years 1849-1851, the Vial and Errázuriz families established an alliance with the defeated faction of 1829 led by the Vicuñas and together formed the Liberal party. At its oligarchic core, the civil war of 1851 pitted the new Liberal party against families located near the Irarrázaval clan in the kinship network. 1859 was the only civil war with no clear familial cleavage because most core families sided against the government, which in turn had a strong base of support among bureaucrats and the bourgeoisie. The Liberal party broke apart during the civil war of 1891, which mirrored the old familial cleavage of 1829. The last chapter shows that the intra-elite divisions that structured conflict in the nineteenth century were abandoned at the turn of the twentieth century, upon the emergence of middle- and working-class parties. Whereas in the first century after independence, elites fought one another, now they all joined the same side of the political spectrum.
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In this thesis, I explore variation-aware algorithms for analyzing cancer genomes. The scientific community has extensively catalogued millions of mutations present in cancer cells. This information is rarely used during read alignment and variant calling because of a lack of algorithms for doing so. Rediscovering these variants wastes significant computational time and negatively impacts the sensitivity of detection, motivating the development of new solutions. The variants in malignant cells can arise from a number of genetic and environmental sources. In the years after the Chernobyl nuclear disaster, thousands of individuals in areas where radionuclides were deposited developed thyroid cancer. The excess relative risk of thyroid cancer has been estimated to be between fifteen and thirty fold higher following $^{131}I$ exposure. In Chapter 2, I analyze more than 300 thyroid cancer cases from children and young adults exposed to ionizing radiation from increased levels of $^{131}I$ originating from Chernobyl. I characterize the mutational landscape of these tumors across the variant size spectrum and compare it to sporadic thyroid cancer cases. I investigate possible signs of radiation exposure in the genome, especially large balanced structural variants and small indels. In Chapter 3, I develop methods for working with structural variants in variation graphs. Variation graphs have been shown to reduce reference bias and improve alignment to variant sites, though previous work has primarily focused on variants less than fifty base pairs in size. I describe the tradeoffs of various representations of large variants in the graph. I then develop several methods for genotyping and calling large variants in graphs. I construct graphs of both germline and somatic variation and describe how to work with these structures. I develop a method for fast structural variant genotyping using graph mappings and show that this significantly outperforms standard structural variant callers for certain types of variation. I describe how to locate structural variant mismapping signatures on variation graphs and how variation graphs can improve calling of structural variants. Lastly in Chapter 4, I demonstrate a new application of an alignment-free algorithm for genome analysis. I describe a MinHash toolkit for viral coinfection analysis and its application to Human Papillomavirus (HPV) samples. This toolkit is able to classify individual reads from multiple sequencing technologies and accurately detect clinically- relevant HPV coinfections. Finally, I dicuss how these approaches can be applied in other genomic analyses.
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