The role of type 4 phosphodiesterases in generating microdomains of cAMP: Large scale stochastic simulations

Cyclic AMP (cAMP) and its main effector Protein Kinase A (PKA) are critical for several aspects of neuronal function including synaptic plasticity. Specificity of synaptic plasticity requires that cAMP activates PKA in a highly localized manner despite the speed with which cAMP diffuses. Two mechanisms have been proposed to produce localized elevations in cAMP, known as microdomains: impeded diffusion, and high phosphodiesterase (PDE) activity. This paper investigates the mechanism of localized cAMP signaling using a computational model of the biochemical network in the HEK293 cell, which is a subset of pathways involved in PKA-dependent synaptic plasticity. This biochemical network includes cAMP production, PKA activation, and cAMP degradation by PDE activity. The model is implemented in NeuroRD: novel, computationally efficient, stochastic reaction-diffusion software, and is constrained by intracellular cAMP dynamics that were determined experimentally by real-time imaging using an Epac-based FRET sensor (H30). The model reproduces the high concentration cAMP microdomain in the submembrane region, distinct from the lower concentration of cAMP in the cytosol. Simulations further demonstrate that generation of the cAMP microdomain requires a pool of PDE4D anchored in the cytosol and also requires PKA-mediated phosphorylation of PDE4D which increases its activity. The microdomain does not require impeded diffusion of cAMP, confirming that barriers are not required for microdomains. The simulations reported here further demonstrate the utility of the new stochastic reaction-diffusion algorithm for exploring signaling pathways in spatially complex structures such as neurons

Adaptive gene regulatory polymorphisms in natural populations of Drosophila melanogaster

It has long been recognized that changes in gene regulation, specifically mutations in cis-regulatory elements that tend to be stable and additive, are important to adaptive processes and phenotypic evolution. Since cis-regulatory elements are found in the vicinity of the genes they regulate, the direct effect of changes in these sequences is typically limited to a particular gene that allows for refined, situation-specific control of gene expression but are not exclusive of downstream or trans-acting elements. This dissertation focuses on examining mechanisms responsible for maintaining adaptive cis-regulatory polymorphisms in two Drosophila melanogaster genes: fezzik (fiz) and Metallothionein A (MtnA) and their associated effect on gene expression and organismal phenotype. Previous experiments show that the 3’ untranslated region of MtnA contains an insertion/deletion (indel) polymorphism, wherein the deletion is rare or absent in the ancestral African range but its deletion frequency appears to follow a latitudinal cline in derived populations worldwide. By genotyping biannual collections of wild caught D. melanogaster across a 5-year period, I show that the deletion is maintained at a high frequency (~90%) in a single German population with no evidence for overdominant, seasonally fluctuating or sexually antagonistic selection. Expression analysis on pairs of nearly-isogenic lines and on data from a North American population indicated significant differences in expression associated to the indel. Furthermore, the data from this North American population showed that expression variation was only partially explained by the deletion and the effect on oxidative stress tolerance was significantly associated with menadione sodium bisulfite and not paraquat. Altogether these findings suggested a scenario in which MtnA expression and consequently oxidative stress tolerance is likely a polygenic adaptation that varies with genomic background. Indeed, the effect of the deletion allele on oxidative stress tolerance was dependent on the genomic background with some indication of sign epistasis. Transcriptomic analysis revealed that MtnA expression was induced by oxidative stress independent of the indel status, indicating a general role of this gene in stress tolerance as well as suggesting additional levels of context-dependent expression regulation. The transcriptional response to oxidative stress between lines with and without the deletion was mostly similar but interestingly, there were consistently larger numbers of differentially expressed genes associated with the deletion which is possibly related to regulatory cascades resulting from aberrant microRNA epigenetic regulation due to the loss of microRNA binding sites in the deleted region. In general, the response to MSB indicated the significance of functional categories such as general stress response, oxidative stress response, metabolism, apoptosis and autophagy. In particular among the differentially expressed genes with the largest fold-change in response to MSB-induced oxidative stress were several genes related to glutathione metabolism and biosynthesis, suggesting a strong association between this pathway and oxidative stress tolerance. Another instance of expression divergence between ancestral and cosmopolitan populations being associated with a regulatory polymorphism is represented by a single nucleotide polymorphism (SNP) located 67 base pairs upstream of the start codon, in the enhancer region of the gene fezzik, referred to here as “SNP67”. SNP67 has two variants segregating in natural populations of D. melanogaster: the ancestral “C” variant, and the derived “G” variant that is found outside of the ancestral range at intermediate frequencies and is associated with increased fiz expression. Previous studies suggest that this SNP was a recent target of balancing selection; therefore to determine the forces of selection maintaining this SNP in cosmopolitan populations we genotyped biannually collected wild-caught D. melanogaster from a single European (Munich, Germany) population. A model-based approach using allele and genotype frequency data of the SNP67 variants across seasons and sexes was employed. The model indicated that sexually antagonistic and temporally fluctuating selection may help maintain variation at this site, with the derived variant likely being female-beneficial but there was some uncertainty of dominance estimates in the model. Gene expression and body-size phenotypes that were dependent on genomic background and developmental stage indicated that variable dominance may play a role in the maintenance of this polymorphism. Lastly, we identified a novel sex-dependent association between fiz expression and starvation resistance that may suggest that this trait is a potential phenotypic target of selection. Interestingly our findings for the MtnA and fiz regulatory polymorphisms both indicated that the relationship between gene expression divergence and population-level genetic mechanisms underlying phenotypic evolution is potentially complicated by context-dependent factors such as genomic background or spatial and temporal differences. By integrating extensive experimental work to identify the mechanisms of selection in natural populations along with functional characterizations, a refined understanding of these adaptive regulatory polymorphisms was achieved

Cloud-edge hybrid applications

Many modern applications are designed to provide interactions among users, including multi- user games, social networks and collaborative tools. Users expect application response time to be in the order of milliseconds, to foster interaction and interactivity. The design of these applications typically adopts a client-server model, where all interac- tions are mediated by a centralized component. This approach introduces availability and fault- tolerance issues, which can be mitigated by replicating the server component, and even relying on geo-replicated solutions in cloud computing infrastructures. Even in this case, the client-server communication model leads to unnecessary latency penalties for geographically close clients and high operational costs for the application provider. This dissertation proposes a cloud-edge hybrid model with secure and ecient propagation and consistency mechanisms. This model combines client-side replication and client-to-client propagation for providing low latency and minimizing the dependency on the server infras- tructure, fostering availability and fault tolerance. To realize this model, this works makes the following key contributions. First, the cloud-edge hybrid model is materialized by a system design where clients maintain replicas of the data and synchronize in a peer-to-peer fashion, and servers are used to assist clients’ operation. We study how to bring most of the application logic to the client-side, us- ing the centralized service primarily for durability, access control, discovery, and overcoming internetwork limitations. Second, we dene protocols for weakly consistent data replication, including a novel CRDT model (∆-CRDTs). We provide a study on partial replication, exploring the challenges and fundamental limitations in providing causal consistency, and the diculty in supporting client- side replicas due to their ephemeral nature. Third, we study how client misbehaviour can impact the guarantees of causal consistency. We propose new secure weak consistency models for insecure settings, and algorithms to enforce such consistency models. The experimental evaluation of our contributions have shown their specic benets and limitations compared with the state-of-the-art. In general, the cloud-edge hybrid model leads to faster application response times, lower client-to-client latency, higher system scalability as fewer clients need to connect to servers at the same time, the possibility to work oine or disconnected from the server, and reduced server bandwidth usage. In summary, we propose a hybrid of cloud-and-edge which provides lower user-to-user la- tency, availability under server disconnections, and improved server scalability – while being ecient, reliable, and secure.Muitas aplicações modernas são criadas para fornecer interações entre utilizadores, incluindo jogos multiutilizador, redes sociais e ferramentas colaborativas. Os utilizadores esperam que o tempo de resposta nas aplicações seja da ordem de milissegundos, promovendo a interação e interatividade. A arquitetura dessas aplicações normalmente adota um modelo cliente-servidor, onde todas as interações são mediadas por um componente centralizado. Essa abordagem apresenta problemas de disponibilidade e tolerância a falhas, que podem ser mitigadas com replicação no componente do servidor, até com a utilização de soluções replicadas geogracamente em infraestruturas de computação na nuvem. Mesmo neste caso, o modelo de comunicação cliente-servidor leva a penalidades de latência desnecessárias para clientes geogracamente próximos e altos custos operacionais para o provedor das aplicações. Esta dissertação propõe um modelo híbrido cloud-edge com mecanismos seguros e ecientes de propagação e consistência. Esse modelo combina replicação do lado do cliente e propagação de cliente para cliente para fornecer baixa latência e minimizar a dependência na infraestrutura do servidor, promovendo a disponibilidade e tolerância a falhas. Para realizar este modelo, este trabalho faz as seguintes contribuições principais. Primeiro, o modelo híbrido cloud-edge é materializado por uma arquitetura do sistema em que os clientes mantêm réplicas dos dados e sincronizam de maneira ponto a ponto e onde os servidores são usados para auxiliar na operação dos clientes. Estudamos como trazer a maior parte da lógica das aplicações para o lado do cliente, usando o serviço centralizado principalmente para durabilidade, controlo de acesso, descoberta e superação das limitações inter-rede. Em segundo lugar, denimos protocolos para replicação de dados fracamente consistentes, incluindo um novo modelo de CRDTs (∆-CRDTs). Fornecemos um estudo sobre replicação parcial, explorando os desaos e limitações fundamentais em fornecer consistência causal e a diculdade em suportar réplicas do lado do cliente devido à sua natureza efémera. Terceiro, estudamos como o mau comportamento da parte do cliente pode afetar as garantias da consistência causal. Propomos novos modelos seguros de consistência fraca para congurações inseguras e algoritmos para impor tais modelos de consistência. A avaliação experimental das nossas contribuições mostrou os benefícios e limitações em comparação com o estado da arte. Em geral, o modelo híbrido cloud-edge leva a tempos de resposta nas aplicações mais rápidos, a uma menor latência de cliente para cliente e à possibilidade de trabalhar oine ou desconectado do servidor. Adicionalmente, obtemos uma maior escalabilidade do sistema, visto que menos clientes precisam de estar conectados aos servidores ao mesmo tempo e devido à redução na utilização da largura de banda no servidor. Em resumo, propomos um modelo híbrido entre a orla (edge) e a nuvem (cloud) que fornece menor latência entre utilizadores, disponibilidade durante desconexões do servidor e uma melhor escalabilidade do servidor – ao mesmo tempo que é eciente, conável e seguro

A Study of Accomodation of Prosodic and Temporal Features in Spoken Dialogues in View of Speech Technology Applications

Inter-speaker accommodation is a well-known property of human speech and human interaction in general. Broadly it refers to the behavioural patterns of two (or more) interactants and the effect of the (verbal and non-verbal) behaviour of each to that of the other(s). Implementation of thisbehavior in spoken dialogue systems is desirable as an improvement on the naturalness of humanmachine interaction. However, traditional qualitative descriptions of accommodation phenomena do not provide sufficient information for such an implementation. Therefore, a quantitativedescription of inter-speaker accommodation is required. This thesis proposes a methodology of monitoring accommodation during a human or humancomputer dialogue, which utilizes a moving average filter over sequential frames for each speaker. These frames are time-aligned across the speakers, hence the name Time Aligned Moving Average (TAMA). Analysis of spontaneous human dialogue recordings by means of the TAMA methodology reveals ubiquitous accommodation of prosodic features (pitch, intensity and speech rate) across interlocutors, and allows for statistical (time series) modeling of the behaviour, in a way which is meaningful for implementation in spoken dialogue system (SDS) environments.In addition, a novel dialogue representation is proposed that provides an additional point of view to that of TAMA in monitoring accommodation of temporal features (inter-speaker pause length and overlap frequency). This representation is a percentage turn distribution of individual speakercontributions in a dialogue frame which circumvents strict attribution of speaker-turns, by considering both interlocutors as synchronously active. Both TAMA and turn distribution metrics indicate that correlation of average pause length and overlap frequency between speakers can be attributed to accommodation (a debated issue), and point to possible improvements in SDS “turntaking” behaviour. Although the findings of the prosodic and temporal analyses can directly inform SDS implementations, further work is required in order to describe inter-speaker accommodation sufficiently, as well as to develop an adequate testing platform for evaluating the magnitude ofperceived improvement in human-machine interaction. Therefore, this thesis constitutes a first step towards a convincingly useful implementation of accommodation in spoken dialogue systems

Bruk av Liquid Array Diagnostics (LAD) som verktøy for analyse av sammensetning og funksjon av tarmens mikrobiota

The microbial species residing in the human gut exercise vital functions for the host. They produce different metabolites that are crucial for human wellbeing. A variety of such molecules mediate signalling along the gut-brain axis, regulate host gene expression, develop and maintain intestinal and blood-brain barriers, are involved in lipogenesis and gluconeogenesis, in addition to taking part in a wide range of other functions. A deviation in the intestinal flora composition is mechanistically linked to various health disorders, including inflammatory bowel disease (IBD), irritable bowel syndrome (IBS), type 2 diabetes, Parkinson’s and Alzheimer’s disease. Such a deviation, known as dysbiosis, represents an unbalanced composition where certain microbial groups are promoted in the expense of others. These species are considered as promising biomarkers, valuable for disease diagnosis, monitoring and treatment. Of particular interest are those markers that can additionally unveil phenotypical characteristics, such as the overall level of short-chain fatty acids (SCFA) in human gut samples. The prospect of discovering additional markers is high, considering that the content of healthy human guts worldwide is not fully characterized. The field of gut microbiota is at a stage of switching focus to clinically relevant species, particularly to their rapid detection, as a means of offering simple diagnostic solutions with increased availability and accessibility. This affords putting biological findings to practical clinical use, which is often not feasible with current species identification platforms. With the intention of filling this need, the main aim of this thesis was to develop a targeted approach for rapid gut microbiota testing based on the novel Liquid Array Diagnostics (LAD) technology. LAD is adopted to target 16S rRNA gene sites unique for specific microbial groups. Requiring only commonplace qPCR instrumentation, it can detect up to 30 distinct microbial markers in a single-tube multiplex reaction within a working day. LAD’s utility in microbiome studies was validated by testing the prevalence and abundance of 15 microbial markers in 541 samples collected from mothers and their children, as reported in Paper I. Paper II, on the other hand, describes a comprehensive human gut prokaryotic genome collection, HumGut. It was built after screening thousands of human gut metagenome samples, collected from healthy people worldwide, for the presence of any high quality publicly available prokaryote genome. The main rationale for creating it was to enable functional studies through LAD-based 16S targeting. It was demonstrated that HumGut, as a reference database, aids whole genome sequencing studies by significantly increasing the number of mapped sequencing reads, thus elevating the potential for an improved taxonomic classification. However, as it is, HumGut exhibits limited practical use for 16S rRNA gene targeted approaches like LAD. This because most of the representative genomes either lack this gene, or the quality of 16S sequences is compromised (addressed in Paper III). Nonetheless, LAD was exploited to infer a segment of human gut microbiota functionality by targeting the 16S rRNA gene. This was performed based on data retrieved from 16S rDNA sequencing and short-chain fatty acid (SCFA) measurements. LAD’s value in classifying samples with disturbed SCFA ratios (namely high propionate-to-butyrate ratio) - an indication of functional dysbiosis - is presented in Paper IV. Taken together, this thesis introduces two tools, LAD and HumGut, both pointing at the direction of simplified human gut functional analysis via gut microbial composition detection.De mikrobielle artene som bor i menneskets tarm utøver vitale funksjoner for verten. De produserer forskjellige metabolitter avgjørende for menneskers helse. En rekke av disse molekylene deltar i prosesser som signaltransduksjon langs tarm-hjerne-aksen, regulering av genekspresjon, utvikling og vedlikehold av tarm- og blod-hjerne-barrieren, lipogenese og glukoneogenese, samt en rekke andre funksjoner. Avvik i tarmflorasammensetningen kan knyttes til mange ulike sykdommer og lidelser, inkludert irritabel tarm (IBS), innflammatorisk tarmsykdom (IBD), type -2 diabetes, Parkinsons og Alzheimers sykdom. Slike avvik, kjent som dysbiose, kjennetegnes av at visse mikrobielle grupper fremmes på bekostning av andre. Disse artene har potensiale som biomarkører, og kan slik være verdifulle for sykdomsdiagnose og behandling. Spesielt lovende er biomarkører i tarm som kan knyttes opp mot phenotypiske trekk, slik som kortkjedede fettsyrer (SCFA). Det antas at enda flere slike arter vil identifiseres i fremtiden, da mikrobiota-komposisjonen i sunne tarmer ikke er fullt karakterisert globalt. Mikrobiota-feltet er nå på et stadium hvor fokuset endres fra eksplorative studier til identifisering av klinisk relevante arter. Det vil da bli spesielt viktig med metoder som muliggjør rask deteksjon, da dette vil innebære enkle diagnostiske løsninger tilgjengelig for praktisk klinisk bruk, noe som ofte ikke er gjennomførbart med dagens artsidentifikasjonsplattformer. Hovedmålet med denne oppgaven var å utvikle en målrettet tilnærming for rask tarmmikrobiotatesting basert på det nye Liquid Array Diagnostics (LAD)-prinsippet. LAD er utviklet for å identifisere sekvenser i 16S rRNA-genet som er unike for spesifikke mikrobielle markører. Metoden krever kun et vanlig qPCR-instrument og kan oppdage inntil 30 forskjellige mikrobielle markører i étt enkelt test-rør i løpet av en arbeidsdag. LADs nytteverdi i mikrobiomstudier ble validert ved å teste forekomsten av 15 mikrobielle markører i 541 prøver samlet fra mødre og deres barn, som rapportert i Artikel I. Artikel II beskriver genereringen av en omfattende prokaryot genomsamling av menneskets tarm. Den ble bygget ved å screene tusenvis av metagenom fra tarmprøver samlet inn fra friske mennesker over hele verden. Metagenomene ble screenet for tilstedeværelse av alle offentlig tilgjengelige prokaryote genom. Sekvenser av dårlig kvalitet ble fjernet mens alle andre sekvenser ble samlet i én stor referansedatabase, HumGut. Hovedmålet med å lage denne referansedatabasen var å muliggjøre LAD-baserte funksjonelle studier. Det ble vist at HumGut fungerer som et nyttig verktøy for full-genoms sekvenseringsstudier ved å øke antallet artlagte sekvenseringsavlesninger betydelig, da dette gir forbedret taksonomisk klassifisering. HumGut har imidlertid begrenset nytteverdi for 16S rRNA-baserte metoder som LAD. Dette fordi de fleste genom i samlingen enten mangler dette genet fullstendig, eller har for dårlig kvalitet på 16S-sekvensene (behandlet i Artikel III). Til tross for begrensningene knyttet til 16S rRNA-genet i HumGut, ble LAD benyttet til å utvikle en 16S rDNA-basert test for måling av menneskelig tarmmikrobiotafunksjonalitet. Dette ble utført basert på data hentet fra 16S-sekvensering og målinger av kortkjedede fettsyrer (SCFA). LADs evne til å klassifisere prøver med forstyrret SCFA-forhold (nemlig høyt propionat-tilbutyrat-forhold) - en indikasjon på funksjonell dysbiose - er presentert i Artikel IV. Til sammen presenterer denne oppgaven to verktøy, LAD og HumGut, som begge peker i retning av forenklet funksjonell analyse av menneskelig tarm via deteksjon av mikrobiell sammensetning i tarmen

An investigation of the utility of monaural sound source separation via nonnegative matrix factorization applied to acoustic echo and reverberation mitigation for hands-free telephony

In this thesis we investigate the applicability and utility of Monaural Sound Source Separation (MSSS) via Nonnegative Matrix Factorization (NMF) for various problems related to audio for hands-free telephony. We first investigate MSSS via NMF as an alternative acoustic echo reduction approach to existing approaches such as Acoustic Echo Cancellation (AEC). To this end, we present the single-channel acoustic echo problem as an MSSS problem, in which the objective is to extract the users signal from a mixture also containing acoustic echo and noise. To perform separation, NMF is used to decompose the near-end microphone signal onto the union of two nonnegative bases in the magnitude Short Time Fourier Transform domain. One of these bases is for the spectral energy of the acoustic echo signal, and is formed from the in- coming far-end user’s speech, while the other basis is for the spectral energy of the near-end speaker, and is trained with speech data a priori. In comparison to AEC, the speaker extraction approach obviates Double-Talk Detection (DTD), and is demonstrated to attain its maximal echo mitigation performance immediately upon initiation and to maintain that performance during and after room changes for similar computational requirements. Speaker extraction is also shown to introduce distortion of the near-end speech signal during double-talk, which is quantified by means of a speech distortion measure and compared to that of AEC. Subsequently, we address Double-Talk Detection (DTD) for block-based AEC algorithms. We propose a novel block-based DTD algorithm that uses the available signals and the estimate of the echo signal that is produced by NMF-based speaker extraction to compute a suitably normalized correlation-based decision variable, which is compared to a fixed threshold to decide on doubletalk. Using a standard evaluation technique, the proposed algorithm is shown to have comparable detection performance to an existing conventional block-based DTD algorithm. It is also demonstrated to inherit the room change insensitivity of speaker extraction, with the proposed DTD algorithm generating minimal false doubletalk indications upon initiation and in response to room changes in comparison to the existing conventional DTD. We also show that this property allows its paired AEC to converge at a rate close to the optimum. Another focus of this thesis is the problem of inverting a single measurement of a non- minimum phase Room Impulse Response (RIR). We describe the process by which percep- tually detrimental all-pass phase distortion arises in reverberant speech filtered by the inverse of the minimum phase component of the RIR; in short, such distortion arises from inverting the magnitude response of the high-Q maximum phase zeros of the RIR. We then propose two novel partial inversion schemes that precisely mitigate this distortion. One of these schemes employs NMF-based MSSS to separate the all-pass phase distortion from the target speech in the magnitude STFT domain, while the other approach modifies the inverse minimum phase filter such that the magnitude response of the maximum phase zeros of the RIR is not fully compensated. Subjective listening tests reveal that the proposed schemes generally produce better quality output speech than a comparable inversion technique

An investigation of the utility of monaural sound source separation via nonnegative matrix factorization applied to acoustic echo and reverberation mitigation for hands-free telephony

In this thesis we investigate the applicability and utility of Monaural Sound Source Separation (MSSS) via Nonnegative Matrix Factorization (NMF) for various problems related to audio for hands-free telephony. We first investigate MSSS via NMF as an alternative acoustic echo reduction approach to existing approaches such as Acoustic Echo Cancellation (AEC). To this end, we present the single-channel acoustic echo problem as an MSSS problem, in which the objective is to extract the users signal from a mixture also containing acoustic echo and noise. To perform separation, NMF is used to decompose the near-end microphone signal onto the union of two nonnegative bases in the magnitude Short Time Fourier Transform domain. One of these bases is for the spectral energy of the acoustic echo signal, and is formed from the in- coming far-end user’s speech, while the other basis is for the spectral energy of the near-end speaker, and is trained with speech data a priori. In comparison to AEC, the speaker extraction approach obviates Double-Talk Detection (DTD), and is demonstrated to attain its maximal echo mitigation performance immediately upon initiation and to maintain that performance during and after room changes for similar computational requirements. Speaker extraction is also shown to introduce distortion of the near-end speech signal during double-talk, which is quantified by means of a speech distortion measure and compared to that of AEC. Subsequently, we address Double-Talk Detection (DTD) for block-based AEC algorithms. We propose a novel block-based DTD algorithm that uses the available signals and the estimate of the echo signal that is produced by NMF-based speaker extraction to compute a suitably normalized correlation-based decision variable, which is compared to a fixed threshold to decide on doubletalk. Using a standard evaluation technique, the proposed algorithm is shown to have comparable detection performance to an existing conventional block-based DTD algorithm. It is also demonstrated to inherit the room change insensitivity of speaker extraction, with the proposed DTD algorithm generating minimal false doubletalk indications upon initiation and in response to room changes in comparison to the existing conventional DTD. We also show that this property allows its paired AEC to converge at a rate close to the optimum. Another focus of this thesis is the problem of inverting a single measurement of a non- minimum phase Room Impulse Response (RIR). We describe the process by which percep- tually detrimental all-pass phase distortion arises in reverberant speech filtered by the inverse of the minimum phase component of the RIR; in short, such distortion arises from inverting the magnitude response of the high-Q maximum phase zeros of the RIR. We then propose two novel partial inversion schemes that precisely mitigate this distortion. One of these schemes employs NMF-based MSSS to separate the all-pass phase distortion from the target speech in the magnitude STFT domain, while the other approach modifies the inverse minimum phase filter such that the magnitude response of the maximum phase zeros of the RIR is not fully compensated. Subjective listening tests reveal that the proposed schemes generally produce better quality output speech than a comparable inversion technique

Gene Evolution and Function in Arabidopsis Telomere Biology System

Telomeres protect chromosome ends from being recognized as double-strand breaks, and respond to incomplete end-replication through telomerase-mediated extension. POT1 (Protection of Telomere 1) is a highly conserved protein required for capping chromosome ends and for regulating telomere extension by telomerase. Arabidopsis thaliana encodes three POT1 paralogues: POT1a, POT1b, and POT1c. POT1a functions to maintain telomere length homeostasis by promoting telomerase processivity, while POT1b functions in the DNA damage response. POT1c is derived from a recent duplication of the POT1a locus, but its function is unknown. In this dissertation, I examined the function and evolution of POT1c using genetic and biochemical approach. Unlike pot1a mutants which show defects in telomere maintenance, plants lacking POT1c exhibit no obvious telomere-related or developmental phenotypes. Furthermore, the POT1c gene is not expressed under standard growth conditions. Transposable elements (TE) are embedded in the POT1c promoter region; yet, active silencing is not observed. Although POT1a and the dS17 gene, which was created in the same duplication event that gave rise to POT1c, are highly conserved among A. thaliana accessions, POT1c is not. Comparison of POT1a and POT1c loci from species closely related to A. thaliana and A. lyrata indicates that POT1c initially had a functional promoter that was subsequently disrupted by TE insertion. Together, these studies provide new insights into the fate of newly duplicated genes, and the importance of proper regulation of telomere proteins. In addition to the study of the POT1c locus, I have analyzed a newly identified gene (NOP2A) that is implicated in the control of telomere length set point. NOP2A is a conserved rRNA methyltransferase protein that positively correlates with cell proliferation. Telomere length is variable across eukaryotes, but each species establishes a specific set point that allows full protection for chromosome ends. My research shows that mutation in NOP2A locus leads to shorter, but stable telomere length in the Col-0 accession of A. thaliana. These findings provide strong evidence that additional genes that regulate telomeres remain to be discovered

Topology and dynamics of an artificial genetic regulatory network model

This thesis presents some of the methods of studying models of regulatory networks using mathematical and computational formalisms. A basic review of the biology behind gene regulation is introduced along with the formalisms used for modelling networks of such regulatory interactions. Topological measures of large-scale complex networks are discussed and then applied to a specific artificial regulatory network model created through a duplication and divergence mechanism. Such networks share topological features with natural transcriptional regulatory networks. Thus, it may be the case that the topologies inherent in natural networks may be primarily due to their method of creation rather than being exclusively shaped by subsequent evolution under selection. The evolvability of the dynamics of these networks are also examined by evolving networks in simulation to obtain three simple types of output dynamics. The networks obtained from this process show a wide variety of topologies and numbers of genes indicating that it is relatively easy to evolve these classes of dynamics in this model