Molecular markers for the assessment of genetic variability in threatened plant species

La variabilità genetica è un importante strumento per lo studio e la conservazione della biodiversità in specie rare e minacciate di estinzione. Durante il mio dottorato mi sono quindi occupata di mettere a punto diverse metodologie molecolari al fine di valutare la diversità genetica in due specie rare della flora italiana che presentano problematiche diverse e specifiche. I marcatori arbitrari RAPD e i marcatori semi-arbitrari ISSR sono stati utilizzati per valutare la diversità genetica in Quercus crenata Lam. e per confermare l’ipotesi della sua origine ibridogena dalle due specie presunte parentali Quercus cerris L. e Quercus suber L., essendo Q. crenata presente in Italia settentrionale dove Q. suber è attualmente assente. I marcatori SSR o microsatelliti sono invece stati messi a punto su una specie a rischio di estinzione, endemica dell’Appennino Tosco-Emiliano, Primula apennina Widmer, applicando una metodologia specifica, basata sulla costruzione di una libreria genomica arricchita per l’isolamento di primer specifici. I marcatori RAPD e ISSR, utilizzati su un totale di 85 campioni, hanno mostrato alti livelli di diversità molecolare entro le specie studiate, eccetto per Q. suber le cui popolazioni rappresentano il margine orientale di distribuzione della specie, per questo più sottoposte ad impoverimento genetico. Oltre alla cluster analysis (UPGMA) e alla Analisi delle Componenti Principali effettuate per entrambi i marcatori, che confermano l’ipotesi dell’origine ibrida degli individui di Q. crenata diffusi in Italia Settentrionale, sono stati calcolati l’indice di ibridità basato sul maximum likelihood, che dimostra una introgressione asimmetrica di Q. crenata verso il parentale caratterizzato da superiorità demografica (Q. cerris) e il test di Mantel. Quest’ultimo ha permesso di confrontare i due marcatori RAPD e ISSR utilizzati ottenendo una bassa correlazione, a conferma del fatto che, amplificando tratti differenti del DNA nucleare, i dati non sono sovrapponibili, sebbene forniscano risultati analoghi. Per l’isolamento di loci microsatelliti ipervariabili ho utilizzato il protocolllo FIASCO (Fast isolation by AFLP of sequences containing repeats- Zane et al. 2002) che permette di costruire una libreria genomica arricchita partendo dal DNA estratto da P. apennina. Tale procedura ha previsto la digestione del DNA genomico per la produzione di una miscela di frammenti di DNA. Tramite ibridazione con opportune sonde sono stati isolati i frammenti contenenti i microsatelliti. Sequenziando i cloni ricombinanti, ho ottenuto sequenze contenenti repeats sulle cui regioni fiancheggianti sono stati costruiti 15 coppie di primer che potranno, in seguito, essere utilizzate per definire la quota di riproduzione clonale in P. apennina e per valutare la diversità genetica delle popolazioni che coprono l’areale di distribuzione della specie. Data la loro natura altamente variabile e la loro abbondanza nel DNA, gli SSR saranno, come i marcatori RAPD e gli ISSR, ugualmente validi per lo studio della variabilità genetica e per l’analisi di problematiche specifiche legate alle specie rare.

Metodi molecolari nello studio della variabilità genetica di Tuber borchii

Tuber borchii (Ascomycota, order Pezizales) is highly valued truffle sold in local markets in Italy. Despite its economic importance, knowledge on its distribution and population variation is scarce. The objective of this work was to investigate the evolutionary forces shaping the genetic structure of this fungus using coalescent and phylogenetic methods to reconstruct the evolutionary history of populations in Italy. To assess population structure, 61 specimens were collected from 11 different Provinces of Italy. Sampling was stratified across hosts and habitats to maximize coverage in native oak and pine stands and both mychorrizae and fruiting bodies were collected. Samples were identified considering anatomo-morphological characters. DNA was extracted and both multilocus (AFLP) and single-locus (18 loci from rDNA, nDNA, and mtDNA) approaches were used to look for polymorphisms. Screening AFLP profiles, both Jaccard and Dice coefficients of similarity were utilized to transform binary matrix into a distance matrix and then to desume Neighbour-Joining trees. Though these are only preliminary examinations, phylogenetic trees were totally concordant with those deriving from single locus analyses. Phylogenetic analyses of the nuclear loci were performed using maximum likelihood with PAUP and a combined phylogenetic inference, using Bayesian estimation with all nuclear gene regions, was carried out. To reconstruct the evolutionary history, we estimated recurrent migration, migration across the history of the sample, and estimated the mutation and approximate age of mutations in each tree using SNAP Workbench. The combined phylogenetic tree using Bayesian estimation suggests that there are two main haplotypes that are difficult to be differentiated on the basis of morphology, of ecological parameters and symbiontic tree. Between these two lineages, that occur in sympatry within T. borchii populations, there is no evidence of recurrent migration. However, migration over the history of the sample was asymmetrical suggesting that isolation was a result of interrupted gene flow followed by range expansion. Low levels of divergence between the haplotypes indicate that there are likely to be two cryptic species within the T. borchii population sampled. Our results suggest that isolation between populations of T. borchii could have led to reproductive isolation between two lineages. This isolation is likely due to sympatric speciation caused by a multiple colonization from different refugia or a recent isolation. In attempting to determinate whether these haplotypes represent separate species or a partition of the same species we applied Biological and Mechanistic species Concepts. Notwithstanding, further analyses are necessary to evaluate if selection favoured premating or post-mating isolation.

Essays in Applied Health Economics: Evidence on Health and Health Care in Italy and UK

This thesis is the result of my experience as a PhD student taking part in the Joint Doctoral Programme at the University of York and the University of Bologna. In my thesis I deal with topics that are of particular interest in Italy and in Great Britain. Chapter 2 focuses on the empirical test of the existence of the relationship between technological profiles and market structure claimed by Sutton’s theory (1991, 1998) in the specific economic framework of hospital care services provided by the Italian National Health Service (NHS). In order to test the empirical predictions by Sutton, we identify the relevant markets for hospital care services in Italy in terms of both product and geographic dimensions. In particular, the Elzinga and Hogarty (1978) approach has been applied to data on patients’ flows across Italian Provinces in order to derive the geographic dimension of each market. Our results provide evidence in favour of the empirical predictions of Sutton. Chapter 3 deals with the patient mobility in the Italian NHS. To analyse the determinants of patient mobility across Local Health Authorities, we estimate gravity equations in multiplicative form using a Poisson pseudo maximum likelihood method, as proposed by Santos-Silva and Tenreyro (2006). In particular, we focus on the scale effect played by the size of the pool of enrolees. In most of the cases our results are consistent with the predictions of the gravity model. Chapter 4 considers the effects of contractual and working conditions on selfassessed health and psychological well-being (derived from the General Health Questionnaire) using the British Household Panel Survey (BHPS). We consider two branches of the literature. One suggests that “atypical” contractual conditions have a significant impact on health while the other suggests that health is damaged by adverse working conditions. The main objective of our paper is to combine the two branches of the literature to assess the distinct effects of contractual and working conditions on health. The results suggest that both sets of conditions have some influence on health and psychological well-being of employees.

Analysis and modeling techniques for ultrasonic tissue characterization

This thesis introduces new processing techniques for computer-aided interpretation of ultrasound images with the purpose of supporting medical diagnostic. In terms of practical application, the goal of this work is the improvement of current prostate biopsy protocols by providing physicians with a visual map overlaid over ultrasound images marking regions potentially affected by disease. As far as analysis techniques are concerned, the main contributions of this work to the state-of-the-art is the introduction of deconvolution as a pre-processing step in the standard ultrasonic tissue characterization procedure to improve the diagnostic significance of ultrasonic features. This thesis also includes some innovations in ultrasound modeling, in particular the employment of a continuous-time autoregressive moving-average (CARMA) model for ultrasound signals, a new maximum-likelihood CARMA estimator based on exponential splines and the definition of CARMA parameters as new ultrasonic features able to capture scatterers concentration. Finally, concerning the clinical usefulness of the developed techniques, the main contribution of this research is showing, through a study based on medical ground truth, that a reduction in the number of sampled cores in standard prostate biopsy is possible, preserving the same diagnostic power of the current clinical protocol.

A novel map-matching procedure for low-sampling GPS data with applications to traffic flow analysis

An extensive sample (2%) of private vehicles in Italy are equipped with a GPS device that periodically measures their position and dynamical state for insurance purposes. Having access to this type of data allows to develop theoretical and practical applications of great interest: the real-time reconstruction of traffic state in a certain region, the development of accurate models of vehicle dynamics, the study of the cognitive dynamics of drivers. In order for these applications to be possible, we first need to develop the ability to reconstruct the paths taken by vehicles on the road network from the raw GPS data. In fact, these data are affected by positioning errors and they are often very distanced from each other (~2 Km). For these reasons, the task of path identification is not straightforward. This thesis describes the approach we followed to reliably identify vehicle paths from this kind of low-sampling data. The problem of matching data with roads is solved with a bayesian approach of maximum likelihood. While the identification of the path taken between two consecutive GPS measures is performed with a specifically developed optimal routing algorithm, based on A* algorithm. The procedure was applied on an off-line urban data sample and proved to be robust and accurate. Future developments will extend the procedure to real-time execution and nation-wide coverage.

A Multilevel Model with Time Series Components for the Analysis of Tribal Art Prices

In the present work we perform an econometric analysis of the Tribal art market. To this aim, we use a unique and original database that includes information on Tribal art market auctions worldwide from 1998 to 2011. In Literature, art prices are modelled through the hedonic regression model, a classic fixed-effect model. The main drawback of the hedonic approach is the large number of parameters, since, in general, art data include many categorical variables. In this work, we propose a multilevel model for the analysis of Tribal art prices that takes into account the influence of time on artwork prices. In fact, it is natural to assume that time exerts an influence over the price dynamics in various ways. Nevertheless, since the set of objects change at every auction date, we do not have repeated measurements of the same items over time. Hence, the dataset does not constitute a proper panel; rather, it has a two-level structure in that items, level-1 units, are grouped in time points, level-2 units. The main theoretical contribution is the extension of classical multilevel models to cope with the case described above. In particular, we introduce a model with time dependent random effects at the second level. We propose a novel specification of the model, derive the maximum likelihood estimators and implement them through the E-M algorithm. We test the finite sample properties of the estimators and the validity of the own-written R-code by means of a simulation study. Finally, we show that the new model improves considerably the fit of the Tribal art data with respect to both the hedonic regression model and the classic multilevel model.

An optimal estimator for the correlation of CMB anisotropies with Large Scale Structures and its application to WMAP-7year and NVSS

In the thesis we present the implementation of the quadratic maximum likelihood (QML) method, ideal to estimate the angular power spectrum of the cross-correlation between cosmic microwave background (CMB) and large scale structure (LSS) maps as well as their individual auto-spectra. Such a tool is an optimal method (unbiased and with minimum variance) in pixel space and goes beyond all the previous harmonic analysis present in the literature. We describe the implementation of the QML method in the {\it BolISW} code and demonstrate its accuracy on simulated maps throughout a Monte Carlo. We apply this optimal estimator to WMAP 7-year and NRAO VLA Sky Survey (NVSS) data and explore the robustness of the angular power spectrum estimates obtained by the QML method. Taking into account the shot noise and one of the systematics (declination correction) in NVSS, we can safely use most of the information contained in this survey. On the contrary we neglect the noise in temperature since WMAP is already cosmic variance dominated on the large scales. Because of a discrepancy in the galaxy auto spectrum between the estimates and the theoretical model, we use two different galaxy distributions: the first one with a constant bias $b$ and the second one with a redshift dependent bias $b(z)$. Finally, we make use of the angular power spectrum estimates obtained by the QML method to derive constraints on the dark energy critical density in a flat $\Lambda$CDM model by different likelihood prescriptions. When using just the cross-correlation between WMAP7 and NVSS maps with 1.8° resolution, we show that $\Omega_\Lambda$ is about the 70\% of the total energy density, disfavouring an Einstein-de Sitter Universe at more than 2 $\sigma$ CL (confidence level).

Un modello multicriteriale di supporto alla pianificazione territoriale finalizzato alla classificazione del territorio rurale e alla caratterizzazione dell’Impronta Agro ambientale delle aree agricole periurbane.

La ricerca proposta si pone l’obiettivo di definire e sperimentare un metodo per un’articolata e sistematica lettura del territorio rurale, che, oltre ad ampliare la conoscenza del territorio, sia di supporto ai processi di pianificazione paesaggistici ed urbanistici e all’attuazione delle politiche agricole e di sviluppo rurale. Un’approfondita disamina dello stato dell’arte riguardante l’evoluzione del processo di urbanizzazione e le conseguenze dello stesso in Italia e in Europa, oltre che del quadro delle politiche territoriali locali nell’ambito del tema specifico dello spazio rurale e periurbano, hanno reso possibile, insieme a una dettagliata analisi delle principali metodologie di analisi territoriale presenti in letteratura, la determinazione del concept alla base della ricerca condotta. E’ stata sviluppata e testata una metodologia multicriteriale e multilivello per la lettura del territorio rurale sviluppata in ambiente GIS, che si avvale di algoritmi di clustering (quale l’algoritmo IsoCluster) e classificazione a massima verosimiglianza, focalizzando l’attenzione sugli spazi agricoli periurbani. Tale metodo si incentra sulla descrizione del territorio attraverso la lettura di diverse componenti dello stesso, quali quelle agro-ambientali e socio-economiche, ed opera una sintesi avvalendosi di una chiave interpretativa messa a punto allo scopo, l’Impronta Agroambientale (Agro-environmental Footprint - AEF), che si propone di quantificare il potenziale impatto degli spazi rurali sul sistema urbano. In particolare obiettivo di tale strumento è l’identificazione nel territorio extra-urbano di ambiti omogenei per caratteristiche attraverso una lettura del territorio a differenti scale (da quella territoriale a quella aziendale) al fine di giungere ad una sua classificazione e quindi alla definizione delle aree classificabili come “agricole periurbane”. La tesi propone la presentazione dell’architettura complessiva della metodologia e la descrizione dei livelli di analisi che la compongono oltre che la successiva sperimentazione e validazione della stessa attraverso un caso studio rappresentativo posto nella Pianura Padana (Italia).