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Recently developed next-generation sequencing systems are capable of rapid and cost-effective DNA sequencing, thus enabling routine sequencing tasks and taking us one step closer to personalized medicine. To provide a blueprint of a target genome, next-generation sequencing systems typically employ the so called shotgun sequencing strategy and oversample the genome with a library of relatively short overlapping reads. The order of nucleotides in the short reads is determined by processing acquired noisy signals generated by the sequencing platforms, and the overlaps between the reads are exploited to assemble the target long genome. Next-generation sequencing utilizes massively parallel array-based technology to speed up the sequencing and reduce the cost. However, accuracy and lengths of the short reads are yet to surpass those provided by the conventional slower and costlier Sanger sequencing method. In this thesis, we first focus on Illumina's sequencing-by-synthesis platform which relies on reversible terminator chemistry and describe the acquired signal by a Hidden Markov Model. Relying on this model and sequential Monte Carlo methods, we develop a parameter estimation and base calling scheme called ParticleCall. ParticleCall is tested on an experimental data set obtained by sequencing phiX174 bacteriophage using Illumina's Genome Analyzer II. The results show that ParticleCall scheme is significantly more computationally efficient than the best performing unsupervised base calling method currently available, while achieving the same accuracy. Having addressed the problem of base calling of short reads, we turn our attention to genome assembly. Assembly of a genome from acquired short reads is a computationally daunting task even in the scenario where a reference genome exists. Errors and gaps in the reference, and perfect repeat regions in the target, further render the assembly challenging and cause inaccuracies. We formulate reference-guided assembly as the inference problem on a bipartite graph and solve it using a message-passing algorithm. The proposed algorithm can be interpreted as the classical belief propagation scheme under a certain prior. Unlike existing state-of-the-art methods, the proposed algorithm combines the information provided by the reads without needing to know reliability of the short reads (so-called quality scores). Relation of the message-passing algorithm to a provably convergent power iteration scheme is discussed. Results on both simulated and experimental data demonstrate that the proposed message-passing algorithm outperforms commonly used state-of-the-art tools, and it nearly achieves the performance of a genie-aided maximum a posteriori (MAP) scheme. We then consider the reference-free genome assembly problem, i.e., the de novo assembly. Various methods for de novo assembly have been proposed in literature, all of whom are very sensitive to errors in short reads. We develop a novel error-correction method that enables performance improvements of de novo assembly. The new method relies on a suffix array structure built on the short reads data. It incorporates a hypothesis testing procedure utilizing the sum of quality information as the test statistic to improve the accuracy of overlap detection. Finally, we consider an inference problem in gene regulatory networks. Gene regulatory networks are highly complex dynamical systems comprising biomolecular components which interact with each other and through those interactions determine gene expression levels, i.e., determine the rate of gene transcription. In this thesis, a particle filter with Markov Chain Monte Carlo move step is employed for the estimation of reaction rate constants in gene regulatory networks modeled by chemical Langevin equations. Simulation studies demonstrate that the proposed technique outperforms previously considered methods while being computationally more efficient. Dynamic behavior of gene regulatory networks averaged over a large number of cells can be modeled by ordinary differential equations. For this scenario, we compute an approximation to the Cramer-Rao lower bound on the mean-square error of estimating reaction rates and demonstrate that, when the number of unknown parameters is small, the proposed particle filter can be nearly optimal. In summary, this thesis presents a set of Bayesian inference methods for base-calling and sequence assembly in next-generation DNA sequencing. Experimental studies shows the advantage of proposed algorithms over traditional methods. / text

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The activation of many pro-hormones occurs through cleavage at pairs of basic residues and is mediated by two serine proteases, PC2 and PC3. Like their substrates, they are also synthesised as inactive precurors (pro-PC2 and pro-PC3). Maturation is autocatalytic and requires removal of the N-terminal pro-peptide. Pro-PC3 matures within the endoplasmic reticulum (ER), whereas maturation of pro-PC2 proceeds within the later compartments of the Golgi network (TGN)/secretory vesicle (SV) and is thought to be regulated by 7B2. In this study the molecular basis for the differences in the maturation location and the interaction with 7B2 was examined by performing domain swap and site directed mutagenesis experiments. The mutant constructs were analysed within an <I>in vitro</I> cell free system. The results suggest that the oxyanion hole residue (Asp³¹⁰) of pro-PC2 restricts maturation to a late secretory compartment and is important for the interaction with 7B2. Mutation of this residue to resemble that of PC3 (Asp310Ans), altered pro-PC2 maturation from a TGN/SV like environment to an ER like environment. Maturation of pro-PC2, but not pro-PC3, was shown to be inhibited by 7B2. Residue Asp³¹⁰ of PC2 was necessary to mediate this interaction. When a similar mutant of PC3 was created to resemble PC2 (Asn309Asp), this residue was not sufficient to alter the maturation profile of pro-PC3 nor was it able to confer 7B2 sensitivity. The pro-region of PC2 was sufficient to alter maturation of PC3 from the ER-like compartment to a TGN/SV-like compartment, but was not able to confer 7B2 sensitivity onto PC3. This study also demonstrated that a basic cluster (HHKQQ⁸⁸) of pro-PC2 was important for delaying maturation to a late compartment and that the residue Phe¹⁰⁴, was important for efficient maturation. Mutational analysis of pro-7B2 revealed that a region within residues 1-151 was important for the interaction with pro-PC2.

The aim of DNA sequencing is to obtain the order of DNA composition comprising the base pairs A (adenine) T (thymine), and C (cytosine) G (guanine). The fast development of DNA sequencing technology allows us to better understand the relationships among diseases, inheritance, and individuality. Solid state nanopores have been recommended as the next generation platform for DNA sequencing due to its low-cost and high-throughput. In particular, nanopores fabricated from graphene sheets are extremely thin and structurally robust and have been extensively used in DNA detection in recent years. In DNA sequencing, the translocation of a DNA molecule through a nanopore is known to be a very complicated issue and is affected by many factors, such as ion concentration, thickness of the nanopore, and the nanopore diameter. The technique of molecular dynamic simulations has been a complementary tool to study DNA translocation through nanopores.       In this thesis, I summarize my work of computational studies of DNA sequencing using graphene nanopores. These studies include: DNA translocation through single-layer graphene nanopores of different diameters under conditions of various ion concentrations and applied voltages; DNA translocation through multilayer graphene nanopores varied from a single to a few layers; pulling out single strand DNA molecules from small graphene nanopores of different geometries. The major contributions of this work include: 1. Effects of bias voltage on DNA translocation time were investigated leading to the insight that lower applied voltages can extend the time of DNA translocation through monolayer graphene nanopores. The effect of salt concentration on the corresponding ionic current was studied. At a low ionic concentration (&lt; 0.3M), the current increases as DNA translocates through a nanopore. However, at a high ionic concentration (&gt;0.5M), the current decreases as DNA translocates through the nanopore. A theoretical model was proposed to explore the relationship between the current and the occupied nanopore area. We demonstrated that the DNA translocation time can be prolonged by narrowing the diameter of a nanopore properly and the reduction of the blockade current depends on the ratio of the unoccupied nanopore area to the total nanopore area. 2.  DNA translocation through multilayer graphene nanopores was studied by molecular dynamics simulations with the aim to achieve single-base resolution. We show that the DNA translocation time can be extended by increasing the graphene layers up to a moderate number (7) and that the current in DNA translocation undergoes a stepwise change upon DNA going through an multi-layer graphene (MLG) nanopore. A model was built to account for the relationship between the current change and the unoccupied volume of the MLG nanopore. We demonstrate that the blockade current is closely related to the unoccupied volume. The dynamics of DNA translocation depends specifically on the interaction of nucleotides with the graphene sheet. Thus, our study indicates that the resolution of DNA detection can be improved by increasing the number of graphene layers in a certain range and by modifying the surface of graphene nanopores. 3. The effect of graphene nanopore geometry on DNA sequencing has been assessed by steered molecular dynamics simulations. DNA fragments including A, T, C, G and 5-methylcytosine (MC) were pulled through graphene nanopores of different geometries with diameters down to ~1nm by steered molecular dynamics simulations. We demonstrated that the bases (A, T, C, G, and MC) can be indentified in single-base resolution by the characteristic force peak values in a circular graphene nanopore but not in graphene nanopores of other geometries. Symmetric nanopores are thus better suited to DNA sequence detection via force curves than asymmetric nanopores. This implies that the graphene nanopore surface should be modified as symmetric as possible to sequence DNA by an atomic force microscope or optical tweezers. This helps us to understand low-cost and time-efficient DNA sequencing in narrow nanopores. 4. The translocation time for different nucleotides to pass through graphene nanopores with certain diameters was investigated. It was found that the translocation times are different for different bases under a low electric field. The results indicate that DNA can be sequenced by the translocation time to pass through a graphene nanopore. 5. Inspired by the structure of K+ channel proteins, a series of oxygen doped graphene nanopores of different size were designed to discriminate the transport of K+ and Na+ ions. The results indicate that the ion selectivity of such biomimetic graphene nanopores can be simply controlled by the size of the nanopore.  Compared to K+, the smaller radius of Na+ leads to a much higher free energy barrier in the nanopore of a certain size. / <p>QC 20141212</p>