10,389 research outputs found

    The Analysis of Partial Sequences of the Flavonone 3 Hydroxylase Gene in Lupinus mutabilis Reveals Differential Expression of Two Paralogues Potentially Related to Seed Coat Colour

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    Flavonone 3 hydroxylases (EC 1.14.11.9) are key enzymes in the synthesis of anthocyanins and other flavonoids. Such compounds are involved in seed coat colour and stem pigmentation. Lupinus mutabilis (tarwi) is a legume crop domesticated in the Andean region, valued for the high protein and oil content of its seeds. Tarwi accessions are being selected for cultivation in Europe under defined breeding criteria. Seed coat colour patterns are relevant breeding traits in tarwi, and these are conditioned by anthocyanin content. We identified and isolated part of the tarwi flavonone 3-hydroxylase gene (LmF3h) from two accessions with distinct seed coat colour patterns. Two partial LmF3h paralogues, with predicted 20% amino-acid changes but little predicted tertiary structure alterations, were identified in the coloured seed genotype, while only one was present in the white seed genotype. Upon selection and validation of appropriate reference genes, a RT-qPCR analysis showed that these paralogues have different levels of expression during seed development in both genotypes, although they follow the same expression patterns. DNA and transcription analyses enabled to highlight potential F3H paralogues relatable to seed coat pigmentation in tarwi and, upon biochemical and genetic confirmation, prompt marker-assisted breeding for relevant phenotypic traits associated with flavonoid synthesisinfo:eu-repo/semantics/publishedVersio

    Unraveling the effect of sex on human genetic architecture

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    Sex is arguably the most important differentiating characteristic in most mammalian species, separating populations into different groups, with varying behaviors, morphologies, and physiologies based on their complement of sex chromosomes, amongst other factors. In humans, despite males and females sharing nearly identical genomes, there are differences between the sexes in complex traits and in the risk of a wide array of diseases. Sex provides the genome with a distinct hormonal milieu, differential gene expression, and environmental pressures arising from gender societal roles. This thus poses the possibility of observing gene by sex (GxS) interactions between the sexes that may contribute to some of the phenotypic differences observed. In recent years, there has been growing evidence of GxS, with common genetic variation presenting different effects on males and females. These studies have however been limited in regards to the number of traits studied and/or statistical power. Understanding sex differences in genetic architecture is of great importance as this could lead to improved understanding of potential differences in underlying biological pathways and disease etiology between the sexes and in turn help inform personalised treatments and precision medicine. In this thesis we provide insights into both the scope and mechanism of GxS across the genome of circa 450,000 individuals of European ancestry and 530 complex traits in the UK Biobank. We found small yet widespread differences in genetic architecture across traits through the calculation of sex-specific heritability, genetic correlations, and sex-stratified genome-wide association studies (GWAS). We further investigated whether sex-agnostic (non-stratified) efforts could potentially be missing information of interest, including sex-specific trait-relevant loci and increased phenotype prediction accuracies. Finally, we studied the potential functional role of sex differences in genetic architecture through sex biased expression quantitative trait loci (eQTL) and gene-level analyses. Overall, this study marks a broad examination of the genetics of sex differences. Our findings parallel previous reports, suggesting the presence of sexual genetic heterogeneity across complex traits of generally modest magnitude. Furthermore, our results suggest the need to consider sex-stratified analyses in future studies in order to shed light into possible sex-specific molecular mechanisms

    Bioinformatic characterization of a triacylglycerol lipase produced by Aspergillus flavus isolated from the decaying seed of Cucumeropsis mannii

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    Lipases are enzymes of industrial importance responsible for the hydrolysis of ester bonds of triglycerides. A lipolytic fungus was isolated and subsequently identified based on the ITS sequence analysis as putative Aspergillus flavus with accession number LC424503. The gene coding for extracellular triacylglycerol lipase was isolated from Aspergillus flavus species, sequenced, and characterised using bioinformatics tools. An open reading frame of 420 amino acid sequence was obtained and designated as Aspergillus flavus lipase (AFL) sequence. Alignment of the amino acid sequence with other lipases revealed the presence GHSLG sequence which is the lipase consensus sequence Gly-X1-Ser-X2-Gly indicating that it a classical lipase. A catalytic active site lid domain composed of TYITDTIIDLS amino acids sequence was also revealed. This lid protects the active site, control the catalytic activity and substrate selectivity in lipases. The 3-Dimensional structural model shared 34.08% sequence identity with a lipase from Yarrowia lipolytica covering 272 amino acid residues of the template model. A search of the lipase engineering database using AFL sequence revealed that it belongs to the class GX-lipase, superfamily abH23 and homologous family abH23.02, molecular weight and isoelectric point values of 46.95 KDa and 5.7, respectively. N-glycosylation sites were predicted at residues 164, 236 and 333, with potentials of 0.7250, 0.7037 and 0.7048, respectively. O-glycosylation sites were predicted at residues 355, 358, 360 and 366. A signal sequence of 37 amino acids was revealed at the N-terminal of the polypeptide. This is a short peptide sequence that marks a protein for transport across the cell membrane and indicates that AFL is an extracellular lipase. The findings on the structural and molecular properties of Aspergillus flavus lipase in this work will be crucial in future studies aiming at engineering the enzyme for biotechnology applications

    Genome-wide identification of the genetic basis of amyotrophic lateral sclerosis

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    Amyotrophic lateral sclerosis (ALS) is a complex disease that leads to motor neuron death. Despite heritability estimates of 52%, genome-wide association studies (GWASs) have discovered relatively few loci. We developed a machine learning approach called RefMap, which integrates functional genomics with GWAS summary statistics for gene discovery. With transcriptomic and epigenetic profiling of motor neurons derived from induced pluripotent stem cells (iPSCs), RefMap identified 690 ALS-associated genes that represent a 5-fold increase in recovered heritability. Extensive conservation, transcriptome, network, and rare variant analyses demonstrated the functional significance of candidate genes in healthy and diseased motor neurons and brain tissues. Genetic convergence between common and rare variation highlighted KANK1 as a new ALS gene. Reproducing KANK1 patient mutations in human neurons led to neurotoxicity and demonstrated that TDP-43 mislocalization, a hallmark pathology of ALS, is downstream of axonal dysfunction. RefMap can be readily applied to other complex diseases

    Identification of new regenerative therapies in reproductive medicine and their application as a future therapeutic approach for endometrial regeneration

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    El útero es uno de los principales órganos internos del sistema reproductor femenino. Está compuesto de tres capas tisulares: perimetrio, miometrio y endometrio. Esta última capa recubre la cavidad intrauterina y es responsable directa de la implantación embrionaria (para la cual necesita un grosor endometrial mínimo). Entre las patologías que afectan al endometrio pueden distinguirse, entre otras, la atrofia endometrial (insuficiente grosor endometrial) y el síndrome de Asherman (presencia de adhesiones intrauterinas y tejido fibrótico), las cuales conforman el hilo conductor de esta tesis, compuesta de 4 artículos científicos. En ambos casos, el tejido endometrial se encuentra degenerado, lo que dificulta la implantación embrionaria, ocasionando problemas de fertilidad. A día de hoy, ninguna de estas patologías cuenta con una cura totalmente efectiva. Hasta el momento, una de las opciones terapéuticas más prometedora es la inyección de células madre. Por ello, el primer objetivo de esta tesis fue evaluar como la inyección de células madre derivadas de la médula ósea (aisladas con la detección del antígeno CD133), que había resultado ser efectiva tanto en un modelo humano como en uno animal, estaba modificando el endometrio molecularmente. Para así, intentar entender cuáles son los mecanismos paracrinos a través de los cuales llevan a cabo su acción terapéutica. Este primer estudio reveló que estas células madre parecían estar promoviendo la regeneración endometrial mediante la creación de un escenario inmunomodulador (sub-expresión del gen CXCL8), que daría paso a la sobreexpresión de genes involucrados en la regeneración tisular, como SERPINE1, IL4, y JUN. Otro tratamiento que ha ido ganando acepción con los años es el plasma rico en plaquetas, eje central del manuscrito 2. Este manuscrito evidencia como este plasma, especialmente si proviene de sangre de cordón umbilical, es capaz de promover procesos celulares, como la migración y la proliferación de las células endometriales, así como eventos regenerativos en un modelo animal con daño endometrial inducido. Sea cual sea la aproximación terapéutica de elección, se ha hipotetizado que esta regeneración tisular podría surgir de la estimulación del nicho de células madre presente en el endometrio. Es por ello que el objetivo 3 supuso el estudio de los trabajos publicados, tanto de modelos murinos como humanos, relativos a esta población de células madre endometriales. Esta búsqueda permitió concluir que aún quedan lagunas de conocimiento, bien sea en la definición de marcadores celulares específicos o en de la contribución de la médula ósea a este nicho de células madre endometriales. Finalmente, dada la mencionada falta actual de una terapia definitiva para las pacientes con atrofia endometrial o síndrome de Asherman, el cuarto y último objetivo de esta tesis supuso el estudio de todas aquellas aproximaciones que se han llevado a cabo en modelos animales que simulan este tipo de patologías humanas. Este trabajo concluyó que si bien están emergiendo nuevas terapias muy prometedoras, como son aquellas derivadas de la bioingeniería (por ejemplo, uso de hidrogeles o biomoldes), todavía falta perfeccionar y estandarizar los modelos tanto animales como in vitro que permitan una mejor traslación clínica de las mismas.The uterus is one of the main internal organs of the female reproductive system. It is composed of three different tissue layers: perimetrium, myometrium, and endometrium. This last layer covers the intrauterine cavity and is directly responsible for embryo implantation (for which it needs a certain minimum endometrial thickness). Among the pathologies affecting the endometrium, we can distinguish, among others, endometrial atrophy (characterized by an insufficient endometrial thickness) and Asherman's syndrome (a rare disease characterized by the presence of intrauterine adhesions and fibrotic tissue), which form the common thread of this thesis, composed of four original manuscripts. In both cases, the endometrial tissue is degenerated, which hinders the correct embryo implantation, causing then fertility problems. To date, none of these pathologies has a totally effective cure. So far, one of the most promising therapeutic options is the injection of stem cells. Therefore, the first objective was to evaluate how the infusion of bone marrow-derived stem cells (isolated with the antigen CD133), which had proven effective in both a human and an animal model, was modifying the endometrium at the molecular level. Then, this work aimed to understand the paracrine mechanisms through which these cells were carrying out their therapeutic and regenerative action over the endometrial tissue. This first study revealed that these stem cells appeared to be promoting endometrial regeneration by creating an immunomodulatory scenario (down-regulation of the CXCL8 gene), which would give way to the over-expression of genes (SERPINE1, IL4, and JUN) involved in tissue regeneration. Another treatment gaining acceptance over the years is a blood derivate, platelet-rich plasma, which was the focus of the second manuscript. This work shows how this plasma, mainly derived from umbilical cord blood rather than adult peripheral blood, can promote cellular processes, such as cell migration and proliferation of different types of endometrial cells (from primary culture and from stem cell lines). These plasmas also revealed how they triggered the over-expression of certain proteins involved in regenerative events in a mouse model with induced endometrial damage. Whatever the therapeutic approach of choice, it has been hypothesized that regeneration could arise from stimulation of the stem cell niche present in the endometrium. That is why objective three involved studying those works, both murine and human models, concerning this population of endometrial stem cells. This search concluded that there are still gaps in knowledge, either in the definition of specific endometrial stem cell markers or in the contribution of the bone marrow to this endogenous endometrial stem cell niche. Finally, given the aforementioned current lack of definitive therapy for patients with endometrial atrophy or Asherman's syndrome, the last objective involved studying all those approaches that have been carried out in animal models that simulate this type of human pathology. This work concluded that although new therapies are emerging, such as those derived from bioengineering (e.g. use of decellularized scaffolds or hydrogels), there is still a need to perfect and standardize both animal and in vitro models to allow a better clinical translation of these therapies

    Machine learning and large scale cancer omic data: decoding the biological mechanisms underpinning cancer

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    Many of the mechanisms underpinning cancer risk and tumorigenesis are still not fully understood. However, the next-generation sequencing revolution and the rapid advances in big data analytics allow us to study cells and complex phenotypes at unprecedented depth and breadth. While experimental and clinical data are still fundamental to validate findings and confirm hypotheses, computational biology is key for the analysis of system- and population-level data for detection of hidden patterns and the generation of testable hypotheses. In this work, I tackle two main questions regarding cancer risk and tumorigenesis that require novel computational methods for the analysis of system-level omic data. First, I focused on how frequent, low-penetrance inherited variants modulate cancer risk in the broader population. Genome-Wide Association Studies (GWAS) have shown that Single Nucleotide Polymorphisms (SNP) contribute to cancer risk with multiple subtle effects, but they are still failing to give further insight into their synergistic effects. I developed a novel hierarchical Bayesian regression model, BAGHERA, to estimate heritability at the gene-level from GWAS summary statistics. I then used BAGHERA to analyse data from 38 malignancies in the UK Biobank. I showed that genes with high heritable risk are involved in key processes associated with cancer and are often localised in genes that are somatically mutated drivers. Heritability, like many other omics analysis methods, study the effects of DNA variants on single genes in isolation. However, we know that most biological processes require the interplay of multiple genes and we often lack a broad perspective on them. For the second part of this thesis, I then worked on the integration of Protein-Protein Interaction (PPI) graphs and omics data, which bridges this gap and recapitulates these interactions at a system level. First, I developed a modular and scalable Python package, PyGNA, that enables robust statistical testing of genesets' topological properties. PyGNA complements the literature with a tool that can be routinely introduced in bioinformatics automated pipelines. With PyGNA I processed multiple genesets obtained from genomics and transcriptomics data. However, topological properties alone have proven to be insufficient to fully characterise complex phenotypes. Therefore, I focused on a model that allows to combine topological and functional data to detect multiple communities associated with a phenotype. Detecting cancer-specific submodules is still an open problem, but it has the potential to elucidate mechanisms detectable only by integrating multi-omics data. Building on the recent advances in Graph Neural Networks (GNN), I present a supervised geometric deep learning model that combines GNNs and Stochastic Block Models (SBM). The model is able to learn multiple graph-aware representations, as multiple joint SBMs, of the attributed network, accounting for nodes participating in multiple processes. The simultaneous estimation of structure and function provides an interpretable picture of how genes interact in specific conditions and it allows to detect novel putative pathways associated with cancer
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