1,368 research outputs found

    Design of new algorithms for gene network reconstruction applied to in silico modeling of biomedical data

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    Programa de Doctorado en Biotecnología, Ingeniería y Tecnología QuímicaLínea de Investigación: Ingeniería, Ciencia de Datos y BioinformáticaClave Programa: DBICódigo Línea: 111The root causes of disease are still poorly understood. The success of current therapies is limited because persistent diseases are frequently treated based on their symptoms rather than the underlying cause of the disease. Therefore, biomedical research is experiencing a technology-driven shift to data-driven holistic approaches to better characterize the molecular mechanisms causing disease. Using omics data as an input, emerging disciplines like network biology attempt to model the relationships between biomolecules. To this effect, gene co- expression networks arise as a promising tool for deciphering the relationships between genes in large transcriptomic datasets. However, because of their low specificity and high false positive rate, they demonstrate a limited capacity to retrieve the disrupted mechanisms that lead to disease onset, progression, and maintenance. Within the context of statistical modeling, we dove deeper into the reconstruction of gene co-expression networks with the specific goal of discovering disease-specific features directly from expression data. Using ensemble techniques, which combine the results of various metrics, we were able to more precisely capture biologically significant relationships between genes. We were able to find de novo potential disease-specific features with the help of prior biological knowledge and the development of new network inference techniques. Through our different approaches, we analyzed large gene sets across multiple samples and used gene expression as a surrogate marker for the inherent biological processes, reconstructing robust gene co-expression networks that are simple to explore. By mining disease-specific gene co-expression networks we come up with a useful framework for identifying new omics-phenotype associations from conditional expression datasets.In this sense, understanding diseases from the perspective of biological network perturbations will improve personalized medicine, impacting rational biomarker discovery, patient stratification and drug design, and ultimately leading to more targeted therapies.Universidad Pablo de Olavide de Sevilla. Departamento de Deporte e Informátic

    The swan genome and transcriptome, its not all black and white

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    BACKGROUND: The Australian black swan (Cygnus atratus) is an iconic species with contrasting plumage to that of the closely related northern hemisphere white swans. The relative geographic isolation of the black swan may have resulted in a limited immune repertoire and increased susceptibility to infectious diseases, notably infectious diseases from which Australia has been largely shielded. Unlike mallard ducks and the mute swan (Cygnus olor), the black swan is extremely sensitive to highly pathogenic avian influenza. Understanding this susceptibility has been impaired by the absence of any available swan genome and transcriptome information. RESULTS: Here, we generate the first chromosome-length black and mute swan genomes annotated with transcriptome data, all using long-read based pipelines generated for vertebrate species. We use these genomes and transcriptomes to show that unlike other wild waterfowl, black swans lack an expanded immune gene repertoire, lack a key viral pattern-recognition receptor in endothelial cells and mount a poorly controlled inflammatory response to highly pathogenic avian influenza. We also implicate genetic differences in SLC45A2 gene in the iconic plumage of the black swan. CONCLUSION: Together, these data suggest that the immune system of the black swan is such that should any avian viral infection become established in its native habitat, the black swan would be in a significant peril. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-022-02838-0

    Human VDAC pseudogenes: an emerging role for VDAC1P8 pseudogene in acute myeloid leukemia

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    Background Voltage-dependent anion selective channels (VDACs) are the most abundant mitochondrial outer membrane proteins, encoded in mammals by three genes, VDAC1, 2 and 3, mostly ubiquitously expressed. As ’mitochondrial gatekeepers’, VDACs control organelle and cell metabolism and are involved in many diseases. Despite the presence of numerous VDAC pseudogenes in the human genome, their significance and possible role in VDAC protein expression has not yet been considered. Results We investigated the relevance of processed pseudogenes of human VDAC genes, both in physiological and in pathological contexts. Using high-throughput tools and querying many genomic and transcriptomic databases, we show that some VDAC pseudogenes are transcribed in specific tissues and pathological contexts. The obtained experimental data confirm an association of the VDAC1P8 pseudogene with acute myeloid leukemia (AML). Conclusions Our in-silico comparative analysis between the VDAC1 gene and its VDAC1P8 pseudogene, together with experimental data produced in AML cellular models, indicate a specific over-expression of the VDAC1P8 pseudogene in AML, correlated with a downregulation of the parental VDAC1 gene. Keywords Pseudogene, Voltage-dependent anion selective channels (VDAC

    Marine Toxins from Harmful Algae and Seafood Safety

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    The rapid expansion of aquaculture around the world is increasingly being impacted by toxins produced by harmful marine microalgae, which threaten the safety of seafood. In addition, ocean climate change is leading to changing patterns in the distribution of toxic dinoflagellates and diatoms which produce these toxins. New approaches are being developed to monitor for harmful species and the toxins they produce. This Special Issue covers pioneering research on harmful marine microalgae and their toxins, including the identification of species and toxins; the development of new chemical and biological techniques to identify and monitor species and toxins; the uptake of marine biotoxins in seafood and marine ecosystems; and the distribution and abundance of toxins, particularly in relation to climate change

    A stem cell zoo uncovers intracellular scaling of developmental tempo across mammals

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    Differential speeds in biochemical reactions have been proposed to be responsible for the differences in developmental tempo between mice and humans. However, the underlying mechanism controlling the species-specific kinetics remains to be determined. Using in vitro differentiation of pluripotent stem cells, we recapitulated the segmentation clocks of diverse mammalian species varying in body weight and taxa: marmoset, rabbit, cattle, and rhinoceros. Together with mousee and human, the segmentation clock periods of the six species did not scale with the animal body weight, but with the embryogenesis length. The biochemical kinetics of the core clock gene HES7 displayed clear scaling with the species-specific segmentation clock period. However, the cellular metabolic rates did not show an evident correlation. Instead, genes involving biochemical reactions showed an expression pattern that scales with the segmentation clock period. Altogether, our stem cell zoo uncovered general scaling laws governing species-specific developmental tempo
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