Pavlos Antoniou

Finding common motifs with gaps using finite automata

We present an algorithm that uses finite automata to find the common motifs with gaps occurring in all strings belonging to a finite set S = {S1,S2,...,Sr}. In order to find these common motifs we must first identify the factors that exist in each string. Therefore the algorithm begins by constructing a factor automaton for each string Si. To find the common factors of all the strings, the algorithm needs to gather all the factors from the strings together in one data structure and this is achieved by computing an automaton that accepts the union of the above-mentioned automata. Using this automaton we are able to create a new factor alphabet. Based on this factor alphabet a finite automaton is created for each string Si that accepts sequences of all non overlapping factors residing in each string. The intersection of the latter automata produces the finite automaton which accepts all the common subsequences with gaps over the factor alphabet that are present in all the strings of the set S = {S1,S2,...,Sr}. These common subsequences are the common motifs of the strings.

Bisulfite Conversion of DNA: Performance Comparison of Different Kits and Methylation Quantitation of Epigenetic Biomarkers that Have the Potential to Be Used in Non-Invasive Prenatal Testing.

Introduction Epigenetic alterations, including DNA methylation, play an important role in the regulation of gene expression. Several methods exist for evaluating DNA methylation, but bisulfite sequencing remains the gold standard by which base-pair resolution of CpG methylation is achieved. The challenge of the method is that the desired outcome (conversion of unmethylated cytosines) positively correlates with the undesired side effects (DNA degradation and inappropriate conversion), thus several commercial kits try to adjust a balance between the two. The aim of this study was to compare the performance of four bisulfite conversion kits [Premium Bisulfite kit (Diagenode), EpiTect Bisulfite kit (Qiagen), MethylEdge Bisulfite Conversion System (Promega) and BisulFlash DNA Modification kit (Epigentek)] regarding conversion efficiency, DNA degradation and conversion specificity. Methods Performance was tested by combining fully methylated and fully unmethylated λ-DNA controls in a series of spikes by means of Sanger sequencing (0%, 25%, 50% and 100% methylated spikes) and Next-Generation Sequencing (0%, 3%, 5%, 7%, 10%, 25%, 50% and 100% methylated spikes). We also studied the methylation status of two of our previously published differentially methylated regions (DMRs) at base resolution by using spikes of chorionic villus sample in whole blood. Results The kits studied showed different but comparable results regarding DNA degradation, conversion efficiency and conversion specificity. However, the best performance was observed with the MethylEdge Bisulfite Conversion System (Promega) followed by the Premium Bisulfite kit (Diagenode). The DMRs, EP6 and EP10, were confirmed to be hypermethylated in the CVS and hypomethylated in whole blood. Conclusion Our findings indicate that the MethylEdge Bisulfite Conversion System (Promega) was shown to have the best performance among the kits. In addition, the methylation level of two of our DMRs, EP6 and EP10, was confirmed. Finally, we showed that bisulfite amplicon sequencing is a suitable approach for methylation analysis of targeted regions.

Implementation of a Swap Matching Algorithm Using a Graph Theoretic Model

The swap matching problem consists if finding a pattern in a text, while allowing for transpositions in the pattern. A new approach using a graph-theoretic model was presented in [6] by Iliopoulos et al. In this paper we present a useful application for this algorithm and provide an analysis of its running time with a naive approach through implementation.

Automated selection of differentially methylated regions in microarray data

Differentially methylated regions (DMRs) are segments or islands of consecutive sequence positions, showing methylation enrichment or depletion compared to each other in different samples or tissues. The identification of DMRs is a crucial first step in the discovery of biomarkers for noninvasive prenatal diagnosis of aneuploidies such as Trisomy 21. In this paper we describe an algorithm to automatically identify the manifestation of DMRs on arrays. Our approach, methylation status mask AND (MS-AND), influenced by the SHIFT-AND methodology, uses bit operations and masking and can be applied to any microarray dataset in General Feature Format (GFF). We show the effectiveness and utilization of our algorithm using data from Methylated DNA Immunoprecipitation arrays for the identification of DMRs in chromosomes 13, 18 and 21. The algorithm runs on Linux and on Windows systems and an implementation is available at sourceforge (http://sourceforge.net/projects/ms-and).

Practical and Efficient Algorithms for Degenerate and Weighted Sequences Derived from High Throughput Sequencing Technologies

High throughput, (or next generation) sequencing technologies have opened new and exciting opportunities in the use of DNA sequences. The new emerging technologies mark the beginning of a new era of high throughput short read sequencing: they have the potential to assemble a bacterial genome during a single experiment and at a moderate cost. In this paper, we address the problem of efficiently mapping millions of degenerate and weighted sequences to a reference genome with respect to whether they occur exactly once in the genome or not, and by taking probability scores into consideration. In particular, we define and solve the Massive Exact and Approximate Unique Pattern Matching problem for degenerate and weighted sequences derived from high throughput sequencing technologies.