Unsupervised and semi-supervised training methods for eukaryotic gene prediction

This thesis describes new gene finding methods for eukaryotic gene prediction. The current methods for deriving model parameters for gene prediction algorithms are based on curated or experimentally validated set of genes or gene elements. These training sets often require time and additional expert efforts especially for the species that are in the initial stages of genome sequencing. Unsupervised training allows determination of model parameters from anonymous genomic sequence with. The importance and the practical applicability of the unsupervised training is critical for ever growing rate of eukaryotic genome sequencing. Three distinct training procedures are developed for diverse group of eukaryotic species. GeneMark-ES is developed for species with strong donor and acceptor site signals such as Arabidopsis thaliana, Caenorhabditis elegans and Drosophila melanogaster. The second version of the algorithm, GeneMark-ES-2, introduces enhanced intron model to better describe the gene structure of fungal species with posses with relatively weak donor and acceptor splice sites and well conserved branch point signal. GeneMark-LE, semi-supervised training approach is designed for eukaryotic species with small number of introns. The results indicate that the developed unsupervised training methods perform well as compared to other training methods and as estimated from the set of genes supported by EST-to-genome alignments. Analysis of novel genomes reveals interesting biological findings and show that several candidates of under-annotated and over-annotated fungal species are present in the current set of annotated of fungal genomes.Ph.D.Committee Chair: Mark Borodovky; Committee Member: Jung H. Choi; Committee Member: King Jordan; Committee Member: Leonid Bunimovich; Committee Member: Yury Chernof

Coherence as ultrashort pulse train generator

Intense, well-controlled regular light pulse trains start to play a crucial role in many fields of physics. We theoretically demonstrate a very simple and robust technique for generating such periodic ultrashort pulses from a continuous probe wave which propagates in a dispersive thermal gas media

Knowledge, attitude, and practice of physicians regarding vaccinations in Yerevan, Armenia: a case study of HPV

This paper highlights the low levels of vaccine coverage and high levels of reported vaccination hesitancy in Yerevan, Armenia that present profound challenges to the control of disease through routine vaccination programmes. We draw on investigations of hesitancy towards the introduction of new vaccines, using the Human Papillomavirus (HPV) vaccine Gardasil as a case study, to interrogate underlying challenges to vaccine acceptance. We analyse primary data from the introduction of Gardasil, first used in Armenia in 2017, to investigate how levels of medical knowledge amongst physicians in 20 health facilities in Yerevan, Armenia regarding vaccine science, influence attitudes towards the introduction a newly developed vaccine. A questionnaire- based cross-sectional study was completed by 348 physicians between December 2017 and September 2018. The responding physicians displayed a respectable level of knowledge and awareness regarding vaccination with respect to some characteristics (e.g. more than 81% knew that HPV infection was commonly asymptomatic, 73% knew that HPV infection was implicated in most cervical cancers and 87% knew that cervical cancer is the most prevalent cancer amongst women) but low knowledge and poor understanding of other key issues such as the age at which women were most likely to develop cervical cancer (only 15% answered correctly); whether or not the vaccine should be administered to people who had already been infected (27% answered correctly) and whether sexually-active young people should be treated for infection before vaccination (26% answered correctly). The study suggests that drivers of vaccine hesitancy are complex and may not be consistent from vaccine to vaccine. The Armenian healthcare sector may need to provide additional training, awareness-raising and educational activities alongside the introduction of new vaccines to improve understanding of, and trust in, vaccination programmes

Exploiting mid-range DNA patterns for sequence classification: binary abstraction Markov models

Messenger RNA sequences possess specific nucleotide patterns distinguishing them from non-coding genomic sequences. In this study, we explore the utilization of modified Markov models to analyze sequences up to 44 bp, far beyond the 8-bp limit of conventional Markov models, for exon/intron discrimination. In order to analyze nucleotide sequences of this length, their information content is first reduced by conversion into shorter binary patterns via the application of numerous abstraction schemes. After the conversion of genomic sequences to binary strings, homogenous Markov models trained on the binary sequences are used to discriminate between exons and introns. We term this approach the Binary Abstraction Markov Model (BAMM). High-quality abstraction schemes for exon/intron discrimination are selected using optimization algorithms on supercomputers. The best MM classifiers are then combined using support vector machines into a single classifier. With this approach, over 95% classification accuracy is achieved without taking reading frame into account. With further development, the BAMM approach can be applied to sequences lacking the genetic code such as ncRNAs and 5′-untranslated regions

Resequencing and comparative genomics of stagonospora nodorum: Sectional gene absence and effector discovery

Stagonospora nodorum is an important wheat (Triticum aestivum) pathogen in many parts of the world, causing major yield losses. It was the first species in the large fungal Dothideomycete class to be genome sequenced. The reference genome sequence (SN15) has been instrumental in the discovery of genes encoding necrotrophic effectors that induce disease symptoms in specific host genotypes. Here we present the genome sequence of two further S. nodorum strains (Sn4 and Sn79) that differ in their effector repertoire from the reference. Sn79 is avirulent on wheat and produces no apparent effectors when infiltrated onto many cultivars and mapping population parents. Sn4 is pathogenic on wheat and has virulences not found in SN15. The new strains, sequenced with short-read Illumina chemistry, are compared with SN15 by a combination of mapping and de novo assembly approaches.Each of the genomes contains a large number of strain-specific genes, many of which have no meaningful similarity to any known gene. Large contiguous sections of the reference genome are absent in the two newly sequenced strains. We refer to these differences as “sectional gene absences.” The presence of genes in pathogenic strains and absence in Sn79 is added to computationally predicted properties of known proteins to produce a list of likely effector candidates. Transposon insertion was observed in the mitochondrial genomes of virulent strains where the avirulent strain retained the likely ancestral sequence. The study suggests that short-read enabled comparative genomics is an effective way to both identify new S. nodorum effector candidates and to illuminate evolutionary processes in this species

A review of bioinformatics tools for bio-prospecting from metagenomic sequence data

The microbiome can be defined as the community of microorganisms that live in a particular environment. Metagenomics is the practice of sequencing DNA from the genomes of all organisms present in a particular sample, and has become a common method for the study of microbiome population structure and function. Increasingly, researchers are finding novel genes encoded within metagenomes, many of which may be of interest to the biotechnology and pharmaceutical industries. However, such “bioprospecting” requires a suite of sophisticated bioinformatics tools to make sense of the data. This review summarizes the most commonly used bioinformatics tools for the assembly and annotation of metagenomic sequence data with the aim of discovering novel genes

Exploring Repetitive DNA Landscapes Using REPCLASS, a Tool That Automates the Classification of Transposable Elements in Eukaryotic Genomes

Eukaryotic genomes contain large amount of repetitive DNA, most of which is derived from transposable elements (TEs). Progress has been made to develop computational tools for ab initio identification of repeat families, but there is an urgent need to develop tools to automate the annotation of TEs in genome sequences. Here we introduce REPCLASS, a tool that automates the classification of TE sequences. Using control repeat libraries, we show that the program can classify accurately virtually any known TE types. Combining REPCLASS to ab initio repeat finding in the genomes of Caenorhabditis elegans and Drosophila melanogaster allowed us to recover the contrasting TE landscape characteristic of these species. Unexpectedly, REPCLASS also uncovered several novel TE families in both genomes, augmenting the TE repertoire of these model species. When applied to the genomes of distant Caenorhabditis and Drosophila species, the approach revealed a remarkable conservation of TE composition profile within each genus, despite substantial interspecific covariations in genome size and in the number of TEs and TE families. Lastly, we applied REPCLASS to analyze 10 fungal genomes from a wide taxonomic range, most of which have not been analyzed for TE content previously. The results showed that TE diversity varies widely across the fungi “kingdom” and appears to positively correlate with genome size, in particular for DNA transposons. Together, these data validate REPCLASS as a powerful tool to explore the repetitive DNA landscapes of eukaryotes and to shed light onto the evolutionary forces shaping TE diversity and genome architecture

Genomic Transition to Pathogenicity in Chytrid Fungi

Understanding the molecular mechanisms of pathogen emergence is central to mitigating the impacts of novel infectious disease agents. The chytrid fungus Batrachochytrium dendrobatidis (Bd) is an emerging pathogen of amphibians that has been implicated in amphibian declines worldwide. Bd is the only member of its clade known to attack vertebrates. However, little is known about the molecular determinants of - or evolutionary transition to - pathogenicity in Bd. Here we sequence the genome of Bd's closest known relative - a non-pathogenic chytrid Homolaphlyctis polyrhiza (Hp). We first describe the genome of Hp, which is comparable to other chytrid genomes in size and number of predicted proteins. We then compare the genomes of Hp, Bd, and 19 additional fungal genomes to identify unique or recent evolutionary elements in the Bd genome. We identified 1,974 Bd-specific genes, a gene set that is enriched for protease, lipase, and microbial effector Gene Ontology terms. We describe significant lineage-specific expansions in three Bd protease families (metallo-, serine-type, and aspartyl proteases). We show that these protease gene family expansions occurred after the divergence of Bd and Hp from their common ancestor and thus are localized to the Bd branch. Finally, we demonstrate that the timing of the protease gene family expansions predates the emergence of Bd as a globally important amphibian pathogen

Metagenome sequence of Elaphomyces granulatus from sporocarp tissue reveals Ascomycota ectomycorrhizal fingerprints of genome expansion and a Proteobacteria‐rich microbiome

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/113145/1/emi12840.pd

Comparative Genomics Suggests that the Fungal Pathogen Pneumocystis Is an Obligate Parasite Scavenging Amino Acids from Its Host's Lungs

Pneumocystis jirovecii is a fungus causing severe pneumonia in immuno-compromised patients. Progress in understanding its pathogenicity and epidemiology has been hampered by the lack of a long-term in vitro culture method. Obligate parasitism of this pathogen has been suggested on the basis of various features but remains controversial. We analysed the 7.0 Mb draft genome sequence of the closely related species Pneumocystis carinii infecting rats, which is a well established experimental model of the disease. We predicted 8’085 (redundant) peptides and 14.9% of them were mapped onto the KEGG biochemical pathways. The proteome of the closely related yeast Schizosaccharomyces pombe was used as a control for the annotation procedure (4’974 genes, 14.1% mapped). About two thirds of the mapped peptides of each organism (65.7% and 73.2%, respectively) corresponded to crucial enzymes for the basal metabolism and standard cellular processes. However, the proportion of P. carinii genes relative to those of S. pombe was significantly smaller for the “amino acid metabolism” category of pathways than for all other categories taken together (40 versus 114 against 278 versus 427, P<0.002). Importantly, we identified in P. carinii only 2 enzymes specifically dedicated to the synthesis of the 20 standard amino acids. By contrast all the 54 enzymes dedicated to this synthesis reported in the KEGG atlas for S. pombe were detected upon reannotation of S. pombe proteome (2 versus 54 against 278 versus 427, P<0.0001). This finding strongly suggests that species of the genus Pneumocystis are scavenging amino acids from their host's lung environment. Consequently, they would have no form able to live independently from another organism, and these parasites would be obligate in addition to being opportunistic. These findings have implications for the management of patients susceptible to P. jirovecii infection given that the only source of infection would be other humans