Philosophiae Doctor - PhD / 2018, the International Agency for Research on Cancer (IARC) estimated that prostate cancer (PCa) was the second leading cause of death in males worldwide. The number of deaths are expected to raise by 50 % in the next decade. This rise is attributed to the shortcomings of the current diagnostic, prognostic, and therapeutic biomarkers used in the management of the disease. Therefore, research into more sensitive, specific and effective biomarkers is a requirement. The use of biomarkers in PCa diagnosis and management takes advantage of the genetic alterations and abnormalities that characterise the disease. In this regard, a microRNA, hsa-miR-5698 was identified in a previous study as a differentiating biomarker between prostate adenocarcinoma and bone metastasis. Six putative translational targets (CDKN1A, CTNND1, FOXC1, LRP8, ELK1 and BIRC2) of this microRNA were discovered using in silico approaches. The aim of this study was to analyse via expression profiling and characterization, the target genes of hsa-miR-5698 in order to determine their ability to act as putative dynamic network biomarkers for PCa. The study was conducted using a combined in silico and molecular approach. The in silico part of the study investigated the putative transcriptional effects of hsa-miR-5698 on the promotors of its translational targets, the correlation between hsa-miR-5698 and mRNA expression profiles as well as the co-expression analysis, pathway analysis and prognostic ability of the target genes. A number of computational software were employed for these purposes, including, R Studio, Trident algorithm, STRING, KEGG, MEME Suite, SurvExpress and ProGgene. The molecular part of the study involved expression profiling of the genes in two PCa cell line LNCaP and PC3 via qPCR.

DNA sequence assembly is one of the fundamental areas of bioinformatics. It involves the correct formation of a genome sequence from its DNA fragments ("reads") by aligning and merging the fragments. There are different sequencing technologies -- some support long DNA reads and the others, shorter DNA reads. There are sequence assembly programs specifically designed for these different types of raw sequencing data.<p> This work explores and experiments with these different types of assembly software in order to compare their performance on the type of data for which they were designed, as well as their performance on data for which they were not designed, and on mixed data. Such results are useful for establishing good procedures and tools for sequence assembly in the current genomic environment where read data of different lengths are available. This work also investigates the effect of the presence or absence of quality information on the results produced by sequence assemblers.<p> Five strategies were used in this research for assembling mixed data sets and the testing was done using a collection of real and artificial data sets for six bacterial organisms. The results show that there is a broad range in the ability of some DNA sequence assemblers to handle data from various sequencing technologies, especially data other than the kind they were designed for. For example, the long-read assemblers PHRAP and MIRA produced good results from assembling 454 data. The results also show the importance of having an effective methodology for assembling mixed data sets. It was found that combining contiguous sequences obtained from short-read assemblers with long DNA reads, and then assembling this combination using long-read assemblers was the most appropriate approach for assembling mixed short and long reads. It was found that the results from assembling the mixed data sets were better than the results obtained from separately assembling individual data from the different sequencing technologies. DNA sequence assemblers which do not depend on the availability of quality information were used to test the effect of the presence of quality values when assembling data. The results show that regardless of the availability of quality information, good results were produced in most of the assemblies.<p> In more general terms, this work shows that the approach or methodology used to assemble DNA sequences from mixed data sources makes a lot of difference in the type of results obtained, and that a good choice of methodology can help reduce the amount of effort spent on a DNA sequence assembly project.

DNA sequence assembly is one of the fundamental areas of bioinformatics. It involves the correct formation of a genome sequence from its DNA fragments ("reads") by aligning and merging the fragments. There are different sequencing technologies -- some support long DNA reads and the others, shorter DNA reads. There are sequence assembly programs specifically designed for these different types of raw sequencing data.<p> This work explores and experiments with these different types of assembly software in order to compare their performance on the type of data for which they were designed, as well as their performance on data for which they were not designed, and on mixed data. Such results are useful for establishing good procedures and tools for sequence assembly in the current genomic environment where read data of different lengths are available. This work also investigates the effect of the presence or absence of quality information on the results produced by sequence assemblers.<p> Five strategies were used in this research for assembling mixed data sets and the testing was done using a collection of real and artificial data sets for six bacterial organisms. The results show that there is a broad range in the ability of some DNA sequence assemblers to handle data from various sequencing technologies, especially data other than the kind they were designed for. For example, the long-read assemblers PHRAP and MIRA produced good results from assembling 454 data. The results also show the importance of having an effective methodology for assembling mixed data sets. It was found that combining contiguous sequences obtained from short-read assemblers with long DNA reads, and then assembling this combination using long-read assemblers was the most appropriate approach for assembling mixed short and long reads. It was found that the results from assembling the mixed data sets were better than the results obtained from separately assembling individual data from the different sequencing technologies. DNA sequence assemblers which do not depend on the availability of quality information were used to test the effect of the presence of quality values when assembling data. The results show that regardless of the availability of quality information, good results were produced in most of the assemblies.<p> In more general terms, this work shows that the approach or methodology used to assemble DNA sequences from mixed data sources makes a lot of difference in the type of results obtained, and that a good choice of methodology can help reduce the amount of effort spent on a DNA sequence assembly project.

Genomic sequence databases, like GenBank, EMBL, are widely used by molecular biologists for homology searching. Because of the increase of the size of genomic sequence databases, the importance of indexing the sequences for fast queries grows. The DNA sequences are composed of 4 base pairs, and these genomic sequences can be regarded as the text strings. Similar to conventional databases, there are some approaches use indexes to provide efficient access to the data. The inverted-list indexing approach uses hashing to store the database sequences. However, the perfect hashing function is difficult to construct, and the collision in a hash table may occur frequently. Different from the inverted-list approach, there are other data structures, such as the suffix tree, the suffix array, and the suffix binary search tree, to index the genomic sequences. One characteristic of those suffix-tree-like data structures is that they store all suffixes of the sequences. They do not break the sequences into words. The advantage of the suffix tree is simple. However, the storage space of the suffix tree is too large. The suffix array and the suffix binary search tree reduce more storage space than the suffix tree. But since they use the binary searching technique to find the query sequence, they waste too much time to do the search. Another data structure, the word suffix tree, uses the concept of words and stores partial suffixes to index the DNA sequence. Although the word suffix tree reduces the storage space, it will lose information in the search process. In this thesis, we propose a new index structure, ACGT-Words tree, for efficiently support query processing in genomic databases. We define the concept of words which is different from the word definition given in the word suffix tree, and separate the DNA sequences stored in the database and in the query sequence into distinct words. Our approach does not store all of the suffixes in the database sequences. Therefore, we need less space than the suffix tree approach. We also propose an efficient search algorithm to do the sequence match based on the ACGT-Words tree index structure; therefore, we can take less time to finish the search than the suffix array approach. Our approach also avoids the missing cases in the word suffix tree. Then, based on the ACGT-Words tree, we propose one improved operation for data insertion and two improved operations for the searching process. In the improved operation for insertion, we sort the ACGT-Words generated and then preprocess them before constructing the tree structure. In the two improved operations, we can provide better performance when the query sequence satisfies some conditions. The simulation results show that the ACGT-Words tree outperforms the suffix tree and the suffix array in terms of storage and processing time, respectively. Moreover, we show that the improved operations in the ACGT-Words tree also require shorter time to construct or search than the original processes or the suffix array.

Die Arten der Familie der Dipterocarpaceaen (Flügelfruchtgewächse) sind in der Region Malesien die Hauptbaumarten in Bezug auf Holzgewinnung. Die geografische Verbreitung der Pflanzenfamilie erstreckt sich bis Südamerika und Afrika. Die Familie umfasst etwa 500 Arten in 17 verschiedenen Gattungen und ist unterteilt in drei Unterfamilien: Dipterocarpoideae, Monotoideae und Pakaraimoideae (Ashton, 1982). Dipterocarpoideae ist mit 470 Arten in 13 Gattungen die artenreichste Unterfamilie (Ashton, 1982). Sie ist noch einmal unterteilt in zwei Triben: Dipterocarpeae und Shoreae. Dipterocarpeae umfasst die Gattungen Anisoptera, Cotylelobium, Dipterocarpus, Stemonoporus, Upuna, Vateria und Vateriopsis, Shoreae die Gattungen Dryobalanops, Hopea, Neobalanocarpus, Parashorea und Shorea. Shorea und Hopea sind mit 169, bzw. 100 Arten die artenreichsten Gattungen. Studien zur molekularen Phylogenie der Unterfamilie Dipterocarpoideae werden bereits seit 1998 durchgeführt, besonders an der Gattung Shorea und ihren Schwestergattungen im Tribus Shoreae, da diese Gattung die höchste Artenzahl aufweist und von allen Dipterocarpaceaen das wertvollste Holz liefert. Viele dieser Arten sind vom Aussterben bedroht. Ziel von Untersuchungen zur molekularen Phylogenie ist die Vervollständigung von Phylogenien, die auf morphologischen Merkmalen beruhen, da die Einordnung von einigen Gattungen im Tribus Dipterocarpoideae noch immer zur Diskussion steht. Die Klassifizierung von Shorea in dieser Untersuchung bezieht sich auf Ashton (1982) und Symington (1943). Symington (1943) unterteilt Shorea basierend auf der Farbe des Holzes (White Meranti, Yellow Meranti, Balau und Red Meranti). Ashton (1982) hat die Klassifizierung von Symington (1943) grundsätzlich beibehalten, aber einige der Gruppen wurden in niedrigere taxonomische Ränge neu klassifiziert. Die Nachfrage nach Identifikationsmöglichkeiten für Dipterocapaceaen zur Vermeidung von Betrug bei der Zertifizierung von Holz hat zu einer Verbesserung moderner Identifikationssysteme geführt, die auch molekulare Daten nutzen. Traditionell werden Dipterocarpaceaen anhand von morphologischen Merkmalen identifiziert. Allerdings ist diese Art der Bestimmung ist oft nur eingeschränkt nutzbar, vor allem wenn keine Blüte vorhanden ist, da dies das eindeutigste taxonomische Bestimmungsmerkmal bei Dipterocarpaceaen ist. Die große Menge molekularer Daten und die fortschrittlichen Technologien im Bereich der DNA-Sequenzierung ermöglichten es dem DNA-Barcoding zu einer weitverbreiteten Technik für verschiedene taxonomische Studien zu werden. Dabei will es die traditionelle Taxonomie nicht ersetzen, sondern ergänzen und den Identifikationsvorgang beschleunigen. Zusätzlich ermöglicht die große Anzahl an verfügbaren Sequenzen in öffentlichen Datenbanken, wie z.B. die NCBI-Datenbank, die Entwicklung eines molekularen taxonomischen Schlüssels, einem neuen Konzept der Artidentifikation. Allerdings sind die Methoden des DNA-Barcoding noch immer in ihren Anfängen, so wird z.B. die Datenbank für das Projekt DNA Barcoding zurzeit noch eingerichtet. Diese Studie hat zum Ziel, mithilfe von vier Chloroplastenregionen (trnL intron, psbC-trnS IGS, matK und rbcL) die phylogenetischen Beziehungen in der Unterfamilie Dipterocarpoideae zu erschließen, sowie die Einordnung der verschiedenen Gattungen. Zusätzlich prüft diese Untersuchung auch die Eignung der beiden Barcoding-Regionen matK und rbcL, die vom Konsortium Barcode of Life (CBOL) im Jahr 2009 vorgeschlagen wurden. Ein weiteres Ziel ist die Entwicklung eines taxonomischen Identifizierungsschlüssels für die Identifizierung von Arten basierend auf der phylogenetischen Analyse. Alle Sequenzen von Dipterocarpaceaen, die in der NCBI-Datenbank hinterlegt sind, wurden für vier Chloroplastenregionen (trnL intron, psbC-trnS IGS, matK und rbcL) abgerufen. Zusätzlich zu den Sequenzen aus der NCBI-Datenbank wurden für die Untersuchung auch Proben sequenziert, die in der Abteilung Forstgenetik und Forstpflanzenzüchtung der Universität Göttingen zur Verfügung standen, um eine höchstmögliche Zahl von unterschiedlichen Arten untersuchen zu können. Für die phylogenetischen Analysen wurde die Software MEGA 5 verwendet und die statistischen Methoden maximum parsimony (MP), maximum likelihood (ML) und neighbor joining (NJ). Für die DNA-basierte Identifizierung wurde die Eignung von zwei Barcoding-Regionen mithilfe von nBLAST getestet. Die phylogenetische Analyse wurde unter Verwendung der neighbor joining-Methode durchgeführt. Es war für eine große Anzahl von Arten möglich, Sequenzen von den oben genannten  Chloroplastenregionen zu erhalten: 145 Arten für trnL intron, 117 Arten für psbC-trnS IGS, 116 Arten für matK und 69 Arten für rbcL. Die Länge der Sequenzen für die verschiedenen Regionen variierte, 537 bp, 1136 bp, 653 bp und 647 bp für die Regionen trnL intron, psbC-trnS IGS, matK bzw. rbcL. Die verschiedenen Methoden MP, ML und NJ für die phylogenetischen Analysen erzeugten sehr ähnliche Baumtopologien. Daher basiert die Diskussion vor allem auf den Ergebnisse der MP-Methode. Grundsätzlich war es nicht möglich, die evolutionären Beziehungen der Unterfamilie der Dipterocarpoideae anhand der vier Chloroplastenregionen eindeutig zu entschlüsseln. Die Regionen ermöglichten nur eine Aufklärung der Triben Dipterocarpeae und Shoreae, waren aber innerhalb der Triben deutlich weniger erfolgreich, vor allem in Bezug auf Shoreae. Für die Gattung Dipterocarpus stehen bisher nur Sequenzdaten der Regionen trnL intron und matK zur Verfügung. In dieser Studie wurden für beide Regionen eindeutig abgrenzbare Gruppen von Arten entdeckt. Es wird vermutet, dass Dipterocarpus die basale Gruppe der Dipterocarpoideae repräsentiert (Meijer, 1979). Diese Gattung hat der Familie auch ihren Namen gegeben, möglicherweise weil sie als eine sehr ursprüngliche Gruppe innerhalb der Dipterocarpaceaen gilt (Maury – Lechon, 1979). Auch ist diese Gattung innerhalb der Familie der Dipterocarpaceaen eindeutig definiert, basierend auf morphologischen Merkmalen und molekularen Analysen. Die Analysen der Region psbC-trnS IGS bestätigten die Ergebnisse von Symington (1943) basierend auf der Farbe des Holzes dahingehend, dass die Gattung Shorea eine monophyletische Gruppe bildet. Durch die Analyse der Region matK war es am ehesten möglich, die Beziehungen innerhalb des Tribus Dipterocarpeae zu beschreiben und die Sektion Doona innerhalb der Gattung Shorea als monophyletische Gruppe abzugrenzen. Allerdings war diese Region nicht geeignet für die weitere Klassifizierung innerhalb des Tribus Shoreae. Obwohl die Region rbcL die erste Chloroplastenregion ist, die sequenziert wurde, sind in der NCBI-Datenbank nur wenige Sequenzen verfügbar. Die Ergebnisse basierend auf den eigenen Labordaten führten zu dem Schluss, dass diese Region nicht geeignet ist, um die evolutionären Beziehungen der Dipterocarpoideae unterhalb der Gattungsebene aufzuzeigen. Die Region matK zeigte in dieser Untersuchung eine nahe Verwandtschaft zwischen den Gattungen Dryobalanops und Dipterocarpus, während die Region trnL intron eher darauf hindeutete, dass Dryobalanops eine Verwandtschaft zur Sektion Balau aus der Shorea-Gruppe aufweist. Diese gegensätzlichen Ergebnisse unterstützen die Annahme von Indrioko (2005), dass diese Gattung eine basale Gruppe des Tribus Shoreae ist. Die Artidentifizierung basierend auf DNA-Daten wurde anhand von zwei Vorgehensweisen untersucht, DNA-Barcoding und ein molekularer taxonomischer Identifizierungsschlüssel. Die zwei Barcode-Regionen matK und rbcL, übernommen vom Consortium for the Barcode of Life für Landpflanzen (Hollingsworth et al., 2009), wurden auf ihre Eignung als Barcoding-Regionen für die Unterscheidung der Dipterocarpaceae geprüft. Die meisten benötigten Informationen für die Region matK waren in der NCBI-Datenbank vorhanden, aber es wurden auch einige zusätzliche Proben in dieser Studie verwendet. Insgesamt wurden 119 bzw. 67 Proben für die Untersuchung der Region matK bzw. rbcL, verwendet. Für die Beurteilung der Effektivität der Barcoding-Analyse in dieser Untersuchung wurden zunächst mithilfe von neighbor joining-Bäumen monophyletische Gruppen einmal für die Eingabesequenzen und einmal für die Referenzsequenzen, die in der NCBI-Datenbank hinterlegt sind, identifiziert. Unter Verwendung von nBLAST wurde dann nach Ähnlichkeiten zwischen den Eingabesequenzen aus dem Labor und den Sequenzen aus der NCBI-Datenbank gesucht. Obwohl der neighbor joining-Baum einige der Sequenzen in die korrekte Gattung eingeordnet hat, konnte diese Region keine drei klar abgetrennten Gruppen für die Gattungen Shorea, Hopea und Parashorea erstellen. Die nBLAST-Analyse ergab für die meisten Eingabesequenzen auf der Artebene eine falsche Identifizierung. Aufgrund der fehlenden Unterscheidung zwischen Arten durch die Region matK, was nicht nur durch die Ergebnisse des nBLAST, sondern auch durch die phylogenetische Analyse deutlich wurde, und der Probleme bei der Amplifizierung ist diese Region ungeeignet als Barcoding-Region für die Familie der Dipterocarpaceaen. Über die Region rbcL kann keine weitere Aussage gemacht werden, da nur wenige Sequenzen für diese Region in der Datenbank verfügbar waren. Allerdings konnte die neighbor joining-Analyse zeigen, dass diese Region erfolgreich auf der Gattungsebene unterscheidet, aber nicht auf der Artebene.  Das DNA-basierte Identifizierungsverfahren unter der Verwendung eines taxonomischen Identifizierungsschlüssels kann noch nicht ausreichend zwischen Arten unterscheiden. Viele verschiedene Arten mit dem gleichen Haplotypen wurden bei der Erstellung des Schlüssels gefunden. Ein möglicher Grund ist die Verwendung der Region trnL intron für die Erstellung des Schlüssels. Taberlet (2007) berichtet, dass diese Region nicht effektiv ist bei der Unterscheidung zwischen nah verwandten Arten.

Abstract The pattern and the genetic basis of variation in courtship song of D. virilis were studied using three different approaches: a candidate gene, a biometrical and a quantitative trait locus (QTL) method. Nucleotide variation in a candidate song gene, no-on-transientA, was analysed both within the species (D. virilis and D. littoralis) and between the species of the D. virilis group. Nucleotide variation showed no signs of selection and there was no association between the nucleotide or repeat length variation in nonA gene region and the song characters of the D. virilis group species. Molecular markers (microsatellites) were isolated for D. virilis and their cross-species amplification was tested in all members of the D. virilis group. Intraspecific variation in D. virilis was studied at the phenotypic level in male song characters and at the genetic level in microsatellites. Significant geographic variation was detected in both levels, grouping the strains according to the main continents of the species' distribution range: America, Asia, Europe and Japan. The strains with most extreme song phenotypes were chosen for further analysis. The inheritance of two courtship song characters, the number of pulses in a pulse train (PN) and the length of a pulse train (PTL) was studied by analysing the means and variances of these characters between parental and reciprocal F1, F2 and backcross males. This biometrical analysis showed the genetic basis of these song characters to be polygenic with significant dominance, epistatic and Y-chromosomal effects on both characters. A subset of these data (F2 generation males) were used to conduct a QTL study with the aid of a recombination linkage map constructed for the microsatellites. Composite interval mapping (CIM) revealed significant QTLs, which were shared in both characters. Altogether, significant QTLs, located on the X, 2nd, 3rd and 4th chromosome, were found to affect PN, whereas only QTLs on the 3rd chromsome was found to affect PTL. The effect of the same QTL on the 3rd chromosome on both characters accounted for 31.8% and 49.1% of the mean difference between the parental strains in PN and PTL, respectively. These results suggest the genetic basis for these song characters is caused mainly by autosomal QTLs with a relatively large effect.

Much research has been published on Mycosphaerella spp. causing Mycosphaerella Leaf Disease (MLD) on Eucalyptus spp. The first chapter of this thesis presents a review of the literature on this topic and focuses on the taxonomy, phylogeny and population biology of Mycosphaerella spp. occurring on Eucalyptus. From the published literature, it is clear that the majority of research conducted on MLD has focussed on the epidemiology and taxonomy of Mycosphaerella spp and the susceptibility of Eucalyptus hosts to species of Mycosphaerella. Advances in DNA-based technologies have, however, lead to extensive DNA sequence datasets of Mycosphaerella spp occurring on Eucalyptus. These datasets have provided substantial insight into species concepts for Mycosphaerella and have led to the realisation that many morphological species are complexes of several cryptic phylogenetic taxa. Furthermore, a recent application to the study of Mycosphaerella spp. occurring on Eucalyptus is that concerning their population dynamics. Such studies will aid in our understanding of the genetic structure of Mycosphaerella populations and their movement between countries. These population-based studies will aid forestry companies in establishing Eucalyptus breeding programmes to produce tolerant Eucalyptus genotypes that may be deployed in commercial forestry operations. Mycosphaerella spp. are difficult to identify, due to their conserved teleomorph morphology and the lack of natural occurrences of anamorph structures. DNA sequence data have, therefore, become the definitive technique used to identify Mycosphaerella spp. The Internal Transcribed Spacer (ITS) region of the ribosomal RNA operon has traditionally been targeted for DNA sequence comparisons. However, this gene region does not offer sufficient resolution to discriminate cryptic taxa or resolve deeper nodes within Mycosphaerella. Results presented in chapter two of this thesis present a multi-gene phylogeny for the identification of Mycosphaerella spp. occurring on Eucalyptus. This is based on DNA sequence data from four nuclear gene regions. The generation of these sequence datasets has allowed for competent elucidation of cryptic taxa, species complexes and the greater resolution of deeper nodes within Mycosphaerella. Furthermore, these results have also led to recognising that Mycosphaerella ambipyhlla and M. vespa is a synonym of Mycosphaerella molleriana and Pseudocercospora epispermogonia is recognised as the asexual state of Mycosphaerella marksii. A serious foliar disease of Eucalyptus camaldulensis and hybrids of this species has been known from Thailand and Vietnam for many years. This disease has been known to be caused by a species of Pseudocercospora and was attributed to the cosmopolitan Pseudocercospora eucalyptorum. Results of a study presented in chapter three of this thesis have, however, clearly shown that P. eucalyptorum is not the causal agent of the disease observed on E. camaldulensis in Thailand. By employing classical morphological techniques and DNA sequence data from four nuclear gene regions, I have shown that an undescribed species of Pseudocercospora is responsible for epidemics of this leaf disease. This species is formally described as Pseudocercospora flavomarginata. P. flavomarginata is only known from Thailand and Vietnam. However, considering that E. camaldulensis is planted in other south-east Asian countries and that E. camaldulensis is the most commonly found Eucalyptus sp. in Australia, further surveys in these areas will most likely lead to the discovery of the pathogen from these countries. Techniques that have been used to identify Mycosphaerella spp. include classical morphological comparisons and analyses of DNA sequence data. These techniques have, however, allowed only for the study of the evolutionary history within Mycosphaerella and for species identification. Recent advances in the field of population biology have led to the study of many fungal pathogens at a population level. One of the main tools used to study population biology involves applying DNA-based microsatellite markers. Chapter four of this thesis focuses on the development of DNA-based microsatellite markers for the Eucalyptus leaf pathogen Mycosphaerella nubilosa. By employing specific enrichment protocols, I was able to develop ten polymorphic microsatellite markers for M. nubilosa. These microsatellite markers exhibit high specificity for M. nubilosa and did not cross amplify with other Mycosphaerella spp. that are closely related to M. nubilosa. Mycosphaerella nubilosa has been extensively studied with respect to its taxonomy and epidemiology. However, nothing is known regarding the population biology of this important Eucalyptus leaf pathogen. Therefore, DNA-based microsatellite markers developed in chapter four of this thesis were used to study the population biology of M. nubilosa from several different geographic locations. Results presented in chapter five of this thesis show that populations of M. nubilosa from eastern Australia are genetically more diverse than those populations from western Australia, Africa and Europe. This indicates that eastern Australia is the likely centre of origin for M. nubilosa. Furthermore, based on shared haplotypes between M. nubilosa populations used in this study, I have proposed a pathway of gene flow of M. nubilosa. This suggests that the pathogen moved from eastern Australia to both western Australia and South Africa and then from South Africa into other countries in Africa and finally into Europe. An interesting result emerging from the population biology study presented in chapter five, is the finding that M. nubilosa appears to employ a homothallic mating strategy. Thus, opportunities exist, in countries with limited genetic diversity of M. nubilosa, to breed for Eucalyptus resistance. From the high number of M. nubilosa haplotypes observed in Australia and South Africa, it is also important that this pathogen be added to quarantine action lists to prevent the movement of contaminated Eucalyptus germplasm. This is necessary to prevent novel M. nubilosa haplotypes from moving into new environments where susceptible Eucalyptus spp. are propagated. Mycosphaerella nubilosa is one of the most pathogenic Mycosphaerella spp. causing MLD on Eucalyptus. Surveys of diseased Eucalyptus plantations from several countries where this pathogen occurs, have resulted in an extensive collection of M. nubilosa isolates. Recently, DNA-based studies have led to the hypothesis that M. nubilosa may represent two distinct taxa. Results of studies presented in chapter six of this thesis indicate that two distinct ITS phylogenetic lineages are represented by M. nubilosa sensu lato. These are characterized by defined geographic distributions and Eucalyptus host associations. M. nubilosa ITS lineage 1 is found exclusively in New Zealand, Tasmania and Victoria, eastern Australia occurring on E. globulus. M. nubilosa ITS lineage 2 has a broader geographic distribution and can be found in Spain, Portugal, Tanzania, Kenya, Ethiopia, South Africa, western Australia, Victoria and New South Wales, eastern Australia, where it occurs on E. globulus and several other Eucalyptus spp. that are used in commercial forestry including E. nitens. It is envisaged that results presented in chapter six will lead to more extensive studies into M. nubilosa sensu lato that may result in the description of a new Mycosphaerella sp. represented by M. nubilosa ITS lineage 1. / Thesis (PhD)--University of Pretoria, 2011. / Microbiology and Plant Pathology / Unrestricted

We have previously reported a high prevalence of H. pylori DNA in saliva. In this study, the cytotoxin genotypes of H. pylori strains from both stomach and saliva were compared in 31 patients with gastritis and peptic ulcer. The cagA, vacA m1, vacA m2, and vacA s1 genotypes were analyzed by PCR. The 417 bp PCR products from three patients were also subjected to DNA sequencing analysis. There was 95% agreement between stomach H. pylori isolates and their corresponding saliva DNA in at least one cytotoxin genotype; 86% agreement with two cytotoxin genotypes; 59% agreement with three cytotoxin genotypes; and 27% agreement with all four cytotoxin genotypes studied. DNA sequencing from three patients showed 78.0%, 64.0%, and 66.9% homology of H. pylori from both sources, respectively. The data suggest that more than one H. pylori strain may exist in the stomach and saliva in the same patient.

DNA detection technology has developed rapidly due to its extensive application in clinical diagnostics, bioengineering, environmental monitoring, and food science areas. Currently developed methods such as surface Plasmon resonance (SPR) methods, fluorescent dye labeled methods and electrochemical methods, usually have the problems of bulky size, high equipment cost and time-consuming algorithms, so limiting their application for in vivo detection. In this work, an intrinsic Fabry-Perot interferometric (IFPI) based DNA sensor is presented with the intrinsic advantages of small size, low cost and corrosion-tolerance. This sensor has experimentally demonstrated its high sensitivity and selectivity. In theory, DNA detection is realized by interrogating the sensor's optical cavity length variation resulting from hybridization event. First, a microgap structure based IFPI sensor is fabricated with simple etching and splicing technology. Subsequently, considering the sugar phosphate backbone of DNA, layer-by-layer electrostatic self-assembly technique is adopted to attach the single strand capture DNA to the sensor endface. When the target DNA strand binds to the single-stranded DNA successfully, the optical cavity length of sensor will be increased. Finally, by demodulating the sensor spectrum, DNA hybridization event can be judged qualitatively. This sensor can realize DNA detection without attached label, which save the experiment expense and time. Also the hybridization detection is finished within a few minutes. This quick response feature makes it more attractive in diagnose application. Since the sensitivity and specificity are the most widely used statistics to describe a diagnostic test, so these characteristics are used to evaluate this biosensor. Experimental results demonstrate that this sensor has a sensitivity of 6nmol/ml and can identify a 2 bp mismatch. Since this sensor is optical fiber based, it has robust structure and small size ( 125μm ). If extra etching process is applied to the sensor, the size can be further reduced. This promises the sensor potential application of in-cell detection. Further investigation can be focused on the nanofabrication of this DNA sensor, and this is very meaningful topic not only for diagnostic test but also in many other applications such as food industry, environment monitoring. / Master of Science

Phylogenetics is the study of evolution of organisms. Evolution occurs due to mutations of DNA sequences. The reasons behind these seemingly random mutations are largely unknown. There are many algorithms that build phylogenetic trees from DNA sequences. However, there are certain uncertainties associated with these phylogenetic trees. Fine level analysis of these phylogenetic trees is both important and interesting for evolutionary biologists. In this thesis, we try to model evolutions of DNA sequences using Cellular Automata and resolve the uncertainties associated with the phylogenetic trees. In particular, we determine the effect of neighboring DNA base-pairs on the mutation of a base-pair. Cellular Automata can be viewed as an array of cells which modifies itself in discrete time-steps according to a governing rule. The state of the cell at the next time-step depends on its current state and state of its neighbors. We have used cellular automata rules for analysis and predictions of DNA sequence transformations on Computational grids. In the first part of the thesis, DNA sequence evolution is modeled as a cellular automaton with each cell having one of the four possible states, corresponding to four bases. Phylogenetic trees are explored in order to find out the cellular automata rules that may have guided the evolutions. Master-client paradigm is used to exploit the parallelism in the sequence transformation analysis. Load balancing and fault-tolerance techniques are developed to enable the execution of the explorations on grid resources. The analysis of the sequence transformations is used to resolve uncertainties associated with the phylogenetic trees namely, intermediate sequences in the phylogenetic tree and the exact number of time-steps required for the evolution of a branch. The model is further used to find out various statistics such as most popular rules at a particular time-step in the evolution history of a branch in a phylogenetic tree. We have observed some interesting statistics regarding the unknown base pairs in the intermediate sequences of the phylogenetic tree and the most popular rules used for sequence transformations. Next part of the thesis deals with predictions of future sequences using the previous sequences. First, we try to find out the preserved sequences so that cellular automata rules can be applied selectively. Then, random strategies are developed as base benchmarks. Roulette Wheel strategy is used for predicting future DNA sequences. Though the prediction strategies are able to better the random benchmarks in most of the cases, average performance improvement over the random strategies is not significant. The possible reasons are discussed.