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La thèse vise à examiner l’applicabilité des règles du droit de la concurrence, comme une solution alternative aux solutions existantes de la propriété intellectuelle dans le cas spécifique d'un de refus du titulaire d’un tel brevet. Sont étudiés: les solutions existantes, l'étendue de la protection conférée par un tel brevet, et si un tel refus du titulaire d’un brevet sur une séquence d’ADN est donc examiné en tant que pratique potentiellement répréhensible en vertu du droit de la concurrence. / Doctorat en droit / info:eu-repo/semantics/nonPublished

Indiana University-Purdue University Indianapolis (IUPUI) / My thesis comprises of two individual projects: 1) we have developed a database for operon prediction using high-throughput sequencing datasets for bacterial genomes. 2) Genomics and mechanistic insights of convergent transcription in bacterial genomes. In the first project we developed a database for the prediction of operons for bacterial genomes using RNA-seq datasets, we predicted operons for bacterial genomes. RNA-seq datasets with different condition for each bacterial genome were taken into account and predicted operons using Rockhopper. We took RNA-seq datasets from NCBI with distinct experimental conditions for each bacterial genome into account and analyzed using tool for operon prediction. Currently our database contains 9 bacterial organisms for which we predicted operons. User interface is simple and easy to use, in terms of visualization, downloading and querying of data. In our database user can browse through reference genome, genes present in that genome and operons predicted from different RNA-seq datasets. Further in the second project, we studied the genomic and mechanistic insights of convergent transcription in bacterial genomes. We know that convergent gene pairs with overlapping head-to-head configuration are widely spread across both eukaryotic and prokaryotic genomes. They are believed to contribute to the regulation of genes at both transcriptional and post-transcriptional levels, although factors contributing to their abundance across genomes and mechanistic basis for their prevalence are poorly understood. In this study, we explore the role of various factors contributing to convergent overlapping transcription in bacterial genomes. Our analysis shows that the proportion of convergent overlapping gene pairs (COGPs) in a genome is affected due to endospore formation, bacterial habitat, oxygen requirement, GC content and the temperature range. In particular, we show that bacterial genomes thriving in specialized habitats, such as thermophiles, exhibit a high proportion of COGPs. Our results also conclude that the density distribution of COGPs across the genomes is high for shorter overlaps with increased conservation of distances for decreasing overlaps. Our study further reveals that COGPs frequently contain stop codon overlaps with the middle base position exhibiting mismatches between complementary strands. Further, for the functional analysis using cluster of orthologous groups (COGs) annotations suggested that cell motility, cell metabolism, storage and cell signaling are enriched among COGPs, suggesting their role in processes beyond regulation. Our analysis provides genomic insights into this unappreciated regulatory phenomenon, allowing a refined understanding of their contribution to bacterial phenotypes.

Indiana University-Purdue University Indianapolis (IUPUI) / LIM homeodomain 3 (LHX3) is an important regulator of pituitary and nervous system development. To date, twelve LHX3 gene mutations have been identified in patients with combined pituitary hormone deficiency disease (CPHD). Understanding the molecular mechanisms governing LHX3/Lhx3 gene regulation will provide critical insights into organ development pathways and associated diseases. DNA methylation has been implicated in gene regulation in multiple physiological systems. This dissertation examines the role of DNA methylation in regulating the murine Lhx3 gene. To determine if demethylation of the Lhx3 gene promoter would induce its expression, murine pre-somatotrope pituitary cells that do not normally express Lhx3 (Pit-1/0 cells) were treated with the demethylating reagent, 5-Aza-2’-deoxycytidine. This treatment lead to activation of the Lhx3 gene and thus suggested that methylation contributes to Lhx3 gene regulation. Proteins that modify chromatin, such as histone deacetylases (HDACs) have also been shown to affect DNA methylation patterns and subsequent gene activation. Pit-1/0 pituitary cells treated with a combination of the demethylating reagent and the HDAC inhibitor, Trichostatin A led to activation of the Lhx3 gene, suggesting crosstalk between DNA methylation and histone modification processes. To assess DNA methylation levels, treated and untreated Pit-1/0 genomic DNA were subjected to bisulfite conversion and sequencing. Treated Pit-1/0 cells had decreased methylation compared to untreated cells. Chromatin immunoprecipitation assays demonstrated interactions between the methyl-binding protein, MeCP2 and the Lhx3 promoter regions in the Pit-1/0 cell line. Overall, the study demonstrates that DNA methylation patterns of the Lhx3 gene are associated with its expression status.

Indiana University-Purdue University Indianapolis (IUPUI) / The development of new methods to carry out gene transfer has many benefits to several fields, such as gene therapy, agriculture and animal health. The newly established lentiviral vector systems further increase the efficiency of gene transfer dramatically. Some studies have shown that lentiviral vector systems enhance efficiency over 10-fold higher than traditional pronuclear injection. However, the timing for lentiviral vector integration to occur remains unclear. Integrating in different stages of embryogenesis might lead to different integration patterns between tissues. Moreover, in our previous study we found that the vector copy number in transgenic sheep varied, some having one or more copies per cells while other animals having less than one copy per cell suggesting mosaicism. Here I hypothesized that injection of a lentiviral vector into a single cell embryo can lead to integration very early in embryogenesis but can also occur after several cell divisions. In this study, we focus on investigating integration sites in tissues developing from different germ layers as well as extraembryonic tissues to determine when integration occurs. In addition, we are also interested in insertional mutagenesis caused by viral sequence integration in or near gene regions. We utilize linear amplification-mediated polymerase chain reaction (LAM-PCR) and next- generation sequencing (NGS) technology to determine possible integration sites. In this study, we found the evidence based on a series of experiments to support my hypothesis, suggesting that integration event also happens after several cell divisions. For insertional mutagenesis analysis, the closest genes can be found according to integration sites, but they are likely too far away from the integration sites to be influenced. A well-annotated sheep genome database is needed for insertional mutagenesis analysis.

Indiana University-Purdue University Indianapolis (IUPUI) / RNA-binding proteins (RBPs) are vital post-transcriptional regulatory molecules in transcriptome of mammalian species. It necessitates studying their expression dynamics to extract how post-transcriptional networks work in various mammalian tissues. RNA binding proteins (RBPs) play important roles in controlling the post-transcriptional fate of RNA molecules, yet their evolutionary dynamics remains largely unknown. As expression profiles of genes encoding for RBPs can yield insights about their evolutionary trajectories on the post-transcriptional regulatory networks across species, we performed a comparative analyses of RBP expression profiles across 8 tissues (brain, cerebellum, heart, lung, liver, lung, skeletal muscle, testis) in 11 mammals (human, chimpanzee, gorilla, orangutan, macaque, rat, mouse, platypus, opossum, cow) and chicken & frog (evolutionary outgroups). Noticeably, orthologous gene expression profiles suggest a significantly higher expression level for RBPs than their non-RBP gene counterparts, which include other protein-coding and non-coding genes, across all the mammalian tissues studied here. This trend is significant irrespective of the tissue and species being compared, though RBP gene expression distribution patterns were found to be generally diverse in nature. Our analysis also shows that RBPs are expressed at a significantly lower level in human and mouse tissues compared to their expression levels in equivalent tissues in other mammals: chimpanzee, orangutan, rat, etc., which are all likely exposed to diverse natural habitats and ecological settings compared to more stable ecological environment humans and mice might have been exposed, thus reducing the need for complex and extensive post-transcriptional control. Further analysis of the similarity of orthologous RBP expression profiles between all pairs of tissue-mammal combinations clearly showed the grouping of RBP expression profiles across tissues in a given mammal, in contrast to the clustering of expression profiles for non-RBPs, which frequently grouped equivalent tissues across diverse mammalian species together, suggesting a significant evolution of RBPs expression after speciation events. Calculation of species specificity indices (SSIs) for RBPs across various tissues, to identify those that exhibited restricted expression to few mammals, revealed that about 30% of the RBPs are species-specific in at least one tissue studied here, with lung, liver, kidney & testis exhibiting a significantly higher proportion of species specifically expressed RBPs. We conducted a differential expression analysis of RBPs in human, mouse and chicken tissues to study the evolution of expression levels in recently evolved species (i.e., humans and mice) than evolutionarily-distant species (i.e., chickens). We identified more than 50% of the orthologous RBPs to be differentially expressed in at least one tissue, compared between human and mouse, but not so between human and an outgroup chicken, in which RBP expression levels are relatively conserved. Among the studied tissues (brain, liver and kidney) showed a higher fraction of differentially expressed RBPs, which may suggest hyper- regulatory activities by RBPs in these tissues with species evolution. Overall, this study forms a foundation for understanding the evolution of expression levels of RBPs in mammals, facilitating a snapshot of the wiring patterns of post-transcriptional regulatory networks in mammalian genomes. In our second study, we focused on elucidating novel features of post-transcriptional regulatory molecules called as circRNA from LongPolyA RNA-sequence data. The debate over presence of nonlinear exon splicing such as exon-shuffling or formation of circularized forms has finally come to an end as numerous repertoires have shown of their occurrence and presence through transcriptomic analyses. It is evident from previous studies that along with consensus-site splicing non-consensus site splicing is robustly occurring in the cell. Also, in spite of applying different high-throughput approaches (both computational and experimental) to determine their abundance, the signal is consistent and strongly conforming the plausible circularization mechanisms. Earlier studies hypothesized and hence focused on the ribo-minus non-polyA RNA-sequence data to identify circular RNA structures in cell and compared their abundance levels with their linear counterparts. Thus far, the studies show their conserved nature across tissues and species also that they are not translated and preferentially are without poly (A) tail, with one to five exons long. Much of this initial work has been performed using non-polyA sequencing thus probably underestimates the abundance of circular RNAs originating from long poly (A) RNA isoforms. Our hypothesis is if the circular RNA events are not the artifact of random events, but has a structured and defined mechanism for their formation, then there would not be biases on preferential selection / leaving of polyA tails, while forming the circularized isoforms. We have applied an existing computational pipeline from earlier studies by Memczack et. al., on ENCODE cell-lines long poly (A) RNA-sequence data. With the same pipeline, we achieve a significant number of circular RNA isoforms in the data, some of which are overlapping with known circular RNA isoforms from the literature. We identified an approach and worked upon to identify the precise structure of circular RNA, which is not plausible from the existing computational approaches. We aim to study their expression profiles in normal and cancer cell-lines, and see if there exists any pattern and functional significance based on their abundance levels in the cell.

Indiana University-Purdue University Indianapolis (IUPUI) / Reliable detection of low-frequency single nucleotide variants (SNVs) carries great significance in many applications. In cancer genetics, the frequencies of somatic variants from tumor biopsies tend to be low due to contamination with normal tissue and tumor heterogeneity. Circulating tumor DNA monitoring also faces the challenge of detecting low-frequency variants due to the small percentage of tumor DNA in blood. Moreover, in population genetics, although pooled sequencing is cost-effective compared with individual sequencing, pooling dilutes the signals of variants from any individual. Detection of low frequency variants is difficult and can be cofounded by multiple sources of errors, especially next-generation sequencing artifacts. Existing methods are limited in sensitivity and mainly focus on frequencies around 5%; most fail to consider differential, context-specific sequencing artifacts. To face this challenge, we developed a computational and experimental framework, RareVar, to reliably identify low-frequency SNVs from high-throughput sequencing data. For optimized performance, RareVar utilized a supervised learning framework to model artifacts originated from different components of a specific sequencing pipeline. This is enabled by a customized, comprehensive benchmark data enriched with known low-frequency SNVs from the sequencing pipeline of interest. Genomic-context-specific sequencing error model was trained on the benchmark data to characterize the systematic sequencing artifacts, to derive the position-specific detection limit for sensitive low-frequency SNV detection. Further, a machine-learning algorithm utilized sequencing quality features to refine SNV candidates for higher specificity. RareVar outperformed existing approaches, especially at 0.5% to 5% frequency. We further explored the influence of statistical modeling on position specific error modeling and showed zero-inflated negative binomial as the best-performed statistical distribution. When replicating analyses on an Illumina MiSeq benchmark dataset, our method seamlessly adapted to technologies with different biochemistries. RareVar enables sensitive detection of low-frequency SNVs across different sequencing platforms and will facilitate research and clinical applications such as pooled sequencing, cancer early detection, prognostic assessment, metastatic monitoring, and relapses or acquired resistance identification.

Biological signal processing can help us gain knowledge about biological complexity, as well as using this knowledge to engineer better systems. Three areas are identified as critical to understanding biology: 1) understanding DNA, 2) examining the overall biological function and 3) evaluating these systems in environmental (ie: turbulent) conditions. DNA is investigated for coding structure and redundancy, and a new tandem repeat region, an indicator of a neurodegenerative disease, is discovered. The linear algebraic framework can be used for further analysis and techniques. The work illustrates how signal processing is a tool to reverse engineer biological systems, and how our better understanding of biology can improve engineering designs. Then, the way a single-cell mobilizes in response to a chemical gradient, known as chemotaxis, is examined. Inspiration from receptor clustering in chemotaxis combined with a Hebbian learning method is shown to improve a gradient-source (chemical/thermal) localization algorithm. The algorithm is implemented, and its performance is evaluated in diffusive and turbulent environments. We then show that sensor cross-correlation can be used in solving chemical localization in difficult turbulent scenarios. This leads into future techniques which can be designed for gradient source tracking. These techniques pave the way for use of biologically-inspired sensor networks in chemical localization.

Indiana University-Purdue University Indianapolis (IUPUI) / In mammalian cells DNA double strand breaks (DSBs) are highly variable with respect to sequence and structure all of which are recognized by the DNA- dependent protein kinase (DNA-PK), a critical component for the resolution of these breaks. Previously studies have shown that DNA-PK does not respond the same way to all DSBs but how DNA-PK senses differences in DNA substrate sequence and structure is unknown. Here we explore the enzymatic mechanism by which DNA-PK is activated by various DNA substrates. We provide evidence that recognition of DNA structural variations occur through distinct protein-protein interactions between the carboxy terminal (C-terminal) region of Ku80 and DNA-dependent protein kinase catalytic subunit (DNA-PKcs). Discrimination of terminal DNA sequences, on the other hand, occurs independently of Ku 80 C-terminal interactions and results exclusively from DNA-PKcs interactions with the DNA. We also show that sequence differences in DNA termini can drastically influence DNA repair through altered DNA-PK activation. Our results indicate that even subtle differences in DNA substrates influence DNA-PK activation and ultimately Non-homologous End Joining (NHEJ) efficiency.

Indiana University-Purdue University Indianapolis (IUPUI) / Phormia regina (Meigen), commonly known as the black blow fly is a dipteran that belongs to the family Calliphoridae. Calliphorids play an important role in various research fields including ecology, medical studies, veterinary and forensic sciences. P. regina, a non-model organism, is one of the most common forensically relevant insects in North America and is typically used to assist in estimating postmortem intervals (PMI). To better understand the roles P. regina plays in the numerous research fields, we re-constructed its genome using next generation sequencing technologies. The focus was on generating a reference genome through de novo assembly of high-throughput short read sequences. Following assembly, genetic markers were identified in the form of microsatellites and single nucleotide polymorphisms (SNPs) to aid in future population genetic surveys of P. regina. A total 530 million 100 bp paired-end reads were obtained from five pooled male and female P. regina flies using the Illumina HiSeq2000 sequencing platform. A 524 Mbp draft genome was assembled using both sexes with 11,037 predicted genes. The draft reference genome assembled from this study provides an important resource for investigating the genetic diversity that exists between and among blow fly species; and empowers the understanding of their genetic basis in terms of adaptations, population structure and evolution. The genomic tools will facilitate the analysis of genome-wide studies using modern genomic techniques to boost a refined understanding of the evolutionary processes underlying genomic evolution between blow flies and other insect species.