Dissecting the molecular mechanism of developmental macular dystrophies

North Carolina macular dystrophy (NCMD) and Progressive bifocal chorioretinal atrophy (PBCRA) are a rare set of dominantly inherited disorders that affect central vision from birth. Two linked loci had been previously identified at 5p21 and 6q16. Whole-genome sequencing (WGS) analysis of our cohort of 92 affected individuals has identified 3 novel causative structural variants (SVs) on 5p21 in 13 NCMD families, and 2 novel noncoding single nucleotide variants on 6q16 upstream of the promoter of PRDM13 in three PBCRA families. Combined, the rearrangements in 5p21 have a shared duplicated region of 39kb, located in a gene desert downstream of IRX1 and upstream of ADAMTS16. DNAse-seq data publicly available for human fetal retina identified active open chromatin sites at both loci at restricted times during retinal development. To dissect the molecular mechanism of the identified variants, skin-derived fibroblasts lines from selected patients were established; CRISPR-CAS9 technology was used to recreate the patient variants in a mouse model; and candidate genes expression profile was assessed in three stages of human fetal retina tissue. Additionally, chromosome conformation capture technology was performed in patient fibroblasts and in mouse developing tissue to characterise the genomic landscape of the locus and assess the effect of structural variants. Genome-wide analysis of chromosome occupancy was also performed for the architectural protein CTCF and for histone modifications relevant for identification of cis-acting elements. Expression studies showed altered expression of IRX genes and ADAMTS16 in mutant lines. Together with evidence from human retinal tissue immunohistochemistry and in situ expression data, these genes are suggested to be miss-expressed and/or ectopically expressed during macular development, with involvement of PRDM13, FGF8 and FGF10, which were also found miss-expressed in mutant lines . This work provides novel insight into the gene regulation landscape involved in human macular development and prognostic information for affected families

Multi-model Consistency through Transitive Combination of Binary Transformations

Softwaresysteme werden häufig durch eine Vielzahl an Modellen beschrieben, von denen jedes unterschiedliche Systemeigenschaften abbildet. Diese Modelle können geteilte Informationen enthalten, was zu redundanten Beschreibungen und Abhängigkeiten zwischen den Modellen führt. Damit die Systembeschreibung korrekt ist, müssen alle geteilten Informationen zueinander konsistent beschrieben sein. Die Weiterentwicklung eines Modells kann zu Inkonsistenzen mit anderen Modellen des gleichen Systems führen. Deshalb ist es wichtig einen Mechanismus zur Konsistenzwiederherstellung anzuwenden, nachdem Änderungen erfolgt sind. Manuelle Konsistenzwiederherstellung ist fehleranfallig und zeitaufwändig, weshalb eine automatisierte Konsistenzwiederherstellung notwendig ist. Viele existierende Ansätze nutzen binäre Transformationen, um Konsistenz zwischen zwei Modellen wiederherzustellen, jedoch werden Systeme im Allgemeinen durch mehr als zwei Modelle beschrieben. Um Konsistenzerhaltung für mehrere Modelle mit binären Transformationen zu erreichen, müssen diese durch transitive Ausführung kombiniert werden. In dieser Masterarbeit untersuchen wir die transitive Kombination von binären Transformationen und welche Probleme mit ihr einhergehen. Wir entwickeln einen Katalog aus sechs Fehlerpotentialen, die zu Konsistenzfehlern führen können. Das Wissen über diese Fehlerpotentiale kann den Transformationsentwickler über mögliche Probleme beim Kombinieren von Transformationen informieren. Eines der Fehlerpotentiale entsteht als Folge der Topologie des Transformationsnetzwerks und der benutzten Modelltypen, und kann nur durch Topologieänderungen vermieden werden. Ein weiteres Fehlerpotential entsteht, wenn die kombinierten Transformationen versuchen zueinander widersprüchliche Konsistenzregeln zu erfüllen. Dies kann nur durch Anpassung der Konsistenzregeln behoben werden. Beide Fehlerpotentiale sind fallabhängig und können nicht behoben werden, ohne zu wissen, welche Transformationen kombiniert werden. Zusätzlich wurden zwei Implementierungsmuster entworfen, um zwei weitere Fehlerpotentiale zu verhindern. Sie können auf die einzelnen Transformationsdefinitionen angewendet werden, unabhängig davon welche Transformationen letztendlich kombiniert werden. Für die zwei übrigen Fehlerpotentiale wurden noch keine generellen Lösungen gefunden. Wir evaluieren die Ergebnisse mit einer Fallstudie, bestehend aus zwei voneinander unabhängig entwickelten binären Transformationen zwischen einem komponentenbasierten Softwarearchitekturmodell, einem UML Klassendiagramm und der dazugehörigen Java-Implementierung. Alle gefundenen Fehler konnten einem der Fehlerpotentiale zugewiesen werden, was auf die Vollständigkeit des Fehlerkatalogs hindeutet. Die entwickelten Implementierungsmuster konnten alle Fehler beheben, die dem Fehlerpotential zugeordnet wurden, für das sie entworfen wurden, was 70% aller gefundenen Fehler ausgemacht hat. Dies zeigt, dass die Implementierungsmuster tatsächlich anwendbar sind und Fehler verhindern können

Understanding The Complexity of Human Structural Genomic Variation Through Multiple Whole Genome Sequencing Platforms

Genomic structural variants (SVs) are major sources of genome diversity and closely related to human health, as indicated by numerous studies. In spite of the recent advances in sequencing technology and discovery methodology, there are still considerable amounts of variants in the genome that are partially or completely misinterpreted. This thesis has mainly focused on comprehensively interpreting the structural variants in human genomes by accurately defining the locations and formats of variants with the application of different sequencing platforms. To accomplish this goal, I developed a randomized iterative approach to define all types of SVs, which has shown superior performance in accurately defining complex variants. Next, I built a recurrence based validation pipeline to systematically validate SVs with long read sequences. I conclude with a systematic integration of SVs in multiple individuals discovered by various short read based detecting algorithms, with supportive evidence from orthogonal technologies, which presents to date the most comprehensive SV map in the human genome and the best current technologies allow us to do.PhDBioinformaticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/138462/1/xuefzhao_1.pd

Development of an application for the generation of robot trajectories based on learning by demonstration techniques

En col·laboració amb la Universitat de Barcelona (UB) i la Universitat Rovira i Virgili (URV).The need of designing and implementing software to prepare robots for the execution of new tasks implies an expensive cost that requires specific hardware, software and knowledge. Learning by demonstration is a paradigm for enabling robots to autonomously perform new tasks learning from previous demonstrations. This project focuses on how to facilitate the learning of new tasks by robots through demonstrations performed by humans. In order to accomplish this goal, this thesis considers two subproblems: imitation and correspondence. Three different algorithms are used in order to solve both subproblems, in addition to a reinforcement learning to improve the final solution through new demonstrations. Moreover, a methodology is proposed to perform experimentation using these algorithms, including a final discussion over their performance and future work

Mechanisms of Regulatory Adaptation in the Evolving Genome

The development from a single cell into a complex organism requires the precise control of gene expression in space and time. To achieve this, the activity of genes is governed by large regulatory chromatin landscapes that when disrupted can cause gene mis-regulation and disease. However, at the same time, the successful modification of these landscapes is thought to be a major driver of phenotypic innovation during evolution. Given the vulnerability of these landscapes in disease settings, it remains largely unknown how their integrity is maintained when novel genes are “safely” incorporated during evolution, which is addressed in this work. Specifically, here, multiple mechanisms are dissected that adapted the Fat1 regulatory landscape to maintain its integrity while simultaneously incorporating a novel gene, Zfp42, during evolution. First, comparative evolutionary genomics was used to reconstruct the history of the locus (section 1). Second, the three-dimensional chromatin configuration of the locus was examined in relationship to the gene activities using genomics-technologies (HiC, DamID) combined with super resolution microscopy and in silico modeling (section 2). Finally, the mechanisms that adapted the landscape in ESCs (section 3) and embryonic limbs (section 4) for the emergence of Zfp42 were investigated using genome engineering and genomics. Two tissue-specific mechanisms were identified that enabled the independent activities of Zfp42 and Fat1 despite sharing the same regulatory chromatin landscape: In ESCs, the landscape physically restructures and isolates the genes together with their regulatory information, from one another, thereby allowing their independent regulation. Surprisingly, this restructuring is not driven by the most recognized chromatin structuring force, loop extrusion, but rather by the underlying epigenetic state of chromatin. A different mechanism operates in embryonic mouse limbs where both genes are exposed to the same regulatory information driving Fat1 activation, but surprisingly not Zfp42. The inactivity of Zfp42 cannot be explained by nuclear envelopment attachment nor by enhancer-promoter specificity. Instead, Zfp42 is kept inactive by a highly context-dependent silencing mechanism driven by DNA methylation. As such, Zfp42 is ectopically active and responsive to the surrounding regulatory information when DNA methylation is removed or when the gene is slightly repositioned within its domain. Combined, we find that 3D-restructuring and context-dependent silencing adapted the Fat1 landscape to integrate Zfp42. More generally, this demonstrates that even single regulatory landscapes harbor an enormous regulatory complexity and, thus can accommodate multiple independently regulated genes. We believe that this has significant consequences for human genetics where similar genomic alterations do not drive disease in patients. This is possible, because additional, yet still unknown, mechanisms control how regulatory information is used in the genome

Analysis of Secure Routing Scheme for MANET

Mobile ad hoc networks pose various kinds of security problems, caused by their nature of collaborative and open systems and by limited availability of resources. In our work we look at AODV in detail, study and analyses various attacks that can be possible on it. Then we look into some existing mechanism for securing AODV protocol. Our proposed work is an extension to Adaptive-SAODV of the secure AODV protocol extension, which includes tuning strategies aimed at improving its performance. In A-SAODV an intermediate node makes an adaptive reply decision for an incoming request that helps to balance its load that is over-burdened by signing and verification task of incoming messages. Namely, we propose a modification to adaptive mechanism that tunes SAODV behavior. In our paper we have proposed an extension to Adaptive-SAODV of the secure AODV protocol extension, which includes further filtering strategies aimed at further improving its network performance. We have analyzed the how our proposed algorithm can help in further improvement of performance in adaptive SAODV and also compared its performance with existing mechanisms using simulation

Characterization of a chromosome rearrangement associated with cardiopathy and autism

Chromosomal rearrangements have been associated with multiple congenital abnormalities, including malformative syndromes and global developmental delay. The aim of this study was identification of candidate genes for a complex phenotype characterized by cardiopathy and autism, identified in an individual with a chromosome translocation t(4;7)(q21.1;p21.2). Since classical and molecular cytogenetic analyses have low resolutions, large-insert whole-genome sequencing (liWGS) was applied for identification and mapping of structural chromosomal alterations. By this approach, the 4q21.1 breakpoint was identified between genomic positions chr4:73,918,924-74,049,529 on 4q13.3, whereas the 7p21.2 breakpoint between chr7:13,184,731-14,536,001 [GRCh38/hg38]; suggesting the occurrence of deletions at both breakpoints. Additionally, a 473Kb deletion on 2p16.3 was also identified in the proband. Nucleotide-level resolution of the breakpoints and familial segregation analysis were carried out by amplification of the junction fragments and Sanger sequencing. At the 4q13.3 breakpoint, the 130Kb deletion erases four genes PF4, PPBP, CXCL5 and CXCL3, whereas at 7p21.2, the 1351Kb deletion removes the entire ETV1 and disrupts DGKB and the long non-coding intergenic (Linc) RNA AC011288.2. Furthermore, at this breakpoint region, genomic array analysis identified in the proband’s father a 742Kb deletion comprising DGKB and ETV but not the LincRNA AC011288.2. The maternally inherited 473Kb deletion on 2p16.3 removes the first 5 exons of NRXN1, a gene associated with Pitt-Hopkins like syndrome (OMIM #614325), susceptibility to schizophrenia and chromosome 2p16.3 deletion (OMIM #614332). Similar deletions have been reported with incomplete penetrance and variable expressivity. Several genes from the 7p21.2 breakpoint region and especially those affected by the deletion, DGKB, ETV1 and LincRNA AC011288.2, have been linked with cognitive, speech, language and auditory disorders. In conclusion, coinheritance of the maternally derived deletion on 2p16.3 and the deletion at the breakpoint of the der(7) on 7p21.2 appear to be the most contributively alterations for the proband’s phenotype. At the time, NRXN1, DGKB, ETV1 and LincRNA AC011288.2 are the most likely genes to be responsible for the proband’s phenotype, being those mainly characterised by cardiopathy and autism