Statistical methods for the analysis of DNA sequences: application to dinucleotide distribution in the human genome

Questa tesi si inserisce nell'ambito delle analisi statistiche e dei metodi stocastici applicati all'analisi delle sequenze di DNA. Nello specifico il nostro lavoro è incentrato sullo studio del dinucleotide CG (CpG) all'interno del genoma umano, che si trova raggruppato in zone specifiche denominate CpG islands. Queste sono legate alla metilazione del DNA, un processo che riveste un ruolo fondamentale nella regolazione genica. La prima parte dello studio è dedicata a una caratterizzazione globale del contenuto e della distribuzione dei 16 diversi dinucleotidi all'interno del genoma umano: in particolare viene studiata la distribuzione delle distanze tra occorrenze successive dello stesso dinucleotide lungo la sequenza. I risultati vengono confrontati con diversi modelli nulli: sequenze random generate con catene di Markov di ordine zero (basate sulle frequenze relative dei nucleotidi) e uno (basate sulle probabilità di transizione tra diversi nucleotidi) e la distribuzione geometrica per le distanze. Da questa analisi le proprietà caratteristiche del dinucleotide CpG emergono chiaramente, sia dal confronto con gli altri dinucleotidi che con i modelli random. A seguito di questa prima parte abbiamo scelto di concentrare le successive analisi in zone di interesse biologico, studiando l’abbondanza e la distribuzione di CpG al loro interno (CpG islands, promotori e Lamina Associated Domains). Nei primi due casi si osserva un forte arricchimento nel contenuto di CpG, e la distribuzione delle distanze è spostata verso valori inferiori, indicando che questo dinucleotide è clusterizzato. All’interno delle LADs si trovano mediamente meno CpG e questi presentano distanze maggiori. Infine abbiamo adottato una rappresentazione a random walk del DNA, costruita in base al posizionamento dei dinucleotidi: il walk ottenuto presenta caratteristiche drasticamente diverse all’interno e all’esterno di zone annotate come CpG island. Riteniamo pertanto che metodi basati su questo approccio potrebbero essere sfruttati per migliorare l’individuazione di queste aree di interesse nel genoma umano e di altri organismi.

Electrolyte disorders in the human ventricle. A simulation study.

Ventricular cells are immersed in a bath of electrolytes and these ions are essential for a healthy heart and a regular rhythm. Maintaining physiological concentration of them is fundamental for reducing arrhythmias and risk of sudden cardiac death, especially in haemodialysis patients and in the heart diseases treatments. Models of electrically activity of the heart based on mathematical formulation are a part of the efforts to improve the understanding and prediction of heart behaviour. Modern models incorporate the extensive and ever increasing amounts of experimental data in incorporating biophysically detailed mechanisms to allow the detailed study of molecular and subcellular mechanisms of heart disease. The goal of this project was to simulate the effects of changes in potassium and calcium concentrations in the extracellular space between experimental data and and a description incorpored into two modern biophysically detailed models (Grandi et al. Model; O’Hara Rudy Model). Moreover the task was to analyze the changes in the ventricular electrical activity, in particular by studying the modifications on the simulated electrocardiographic signal. We used the cellular information obtained by the heart models in order to build a 1D tissue description. The fibre is composed by 165 cells, it is divided in four groups to differentiate the cell types that compound human ventricular tissue. The main results are the following: Grandi et al. (GBP) model is not even able to reproduce the correct action potential profile in hyperkalemia. Data from hospitalized patients indicates that the action potential duration (APD) should be shorter than physiological state but in this model we have the opposite. From the potassium point of view the results obtained by using O’Hara model (ORD) are in agreement with experimental data for the single cell action potential in hypokalemia and hyperkalemia, most of the currents follow the data from literature. In the 1D simulations we were able to reproduce ECGs signal in most the potassium concentrations we selected for this study and we collected data that can help physician in understanding what happens in ventricular cells during electrolyte disorder. However the model fails in the conduction of the stimulus under hyperkalemic conditions. The model emphasized the ECG modifications when the K+ is slightly more than physiological value. In the calcium setting using the ORD model we found an APD shortening in hypocalcaemia and an APD lengthening in hypercalcaemia, i.e. the opposite to experimental observation. This wrong behaviour is kept in one dimensional simulations bringing a longer QT interval in the ECG under higher [Ca2+]o conditions and vice versa. In conclusion it has highlighted that the actual ventricular models present in literature, even if they are useful in the original form, they need an improvement in the sensitivity of these two important electrolytes. We suggest an use of the GBP model with modifications introduced by Carro et al. who understood that the failure of this model is related to the Shannon et al. model (a rabbit model) from which the GBP model was built. The ORD model should be modified in the Ca2+ - dependent IcaL and in the influence of the Iks in the action potential for letting it him produce a correct action potential under different calcium concentrations. In the 1D tissue maybe a heterogeneity setting of intra and extracellular conductances for the different cell types should improve a reproduction of the ECG signal.