33 research outputs found

    The role of class I TCP genes in determining leaf shape and size

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    Leaf shape is an important feature of plant development and is known to be controlled by genetic, hormonal and environmental factors. Leaves are the plants photosynthetic organs and provide the plant with the energy to grow. Leaf size and shape, and especially the alteration of leaf size and shape, in mutants can provide us with valuable insight into the genetic basis of leaf development. Alterations in the regulatory control of early leaf development can be visualised by analysing the mature leaf. However, the human eye is not made to identify subtle differences between shapes and we have therefore used automated quantitative imaging technology to quantify differences in shape. In this thesis we employ landmark-based geometric morphometrics to analyse Arabidopsis leaf size and shape. We have quantified the natural leaf size and shape variation in Arabidopsis and built a Leaf Size and Shape Library using Arabidopsis accessions. The Arabidopsis leaf shape library has been applied to the leaf size and shape characterization of a sub-clade of plant specific class I TCP transcription factors (TCP8, TCP14, TCP15, TCP22 and TCP23) in an attempt to better understand their role in leaf development. Functional characterization of class I TCP genes has been hampered by a high degree of redundancy between its family members. We have discovered that TCP14 and TCP15 repress cell proliferation in leaves and thereby modulate leaf shape, combined with work from Kieffer et al., 2011 it constitutes proof that class I TCP genes can activate or repress transcription in a tissue dependent manner. TCP8, TCP22 and TCP23 have a yet to be determined role in modulating leaf shape that may work separately from TCP14/TCP15. TCP8 and TCP23 appear to have a regulatory role that is not limited to leaves

    diXa: a data infrastructure for chemical safety assessment

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    Motivation: The field of toxicogenomics (the application of ‘-omics' technologies to risk assessment of compound toxicities) has expanded in the last decade, partly driven by new legislation, aimed at reducing animal testing in chemical risk assessment but mainly as a result of a paradigm change in toxicology towards the use and integration of genome wide data. Many research groups worldwide have generated large amounts of such toxicogenomics data. However, there is no centralized repository for archiving and making these data and associated tools for their analysis easily available. Results: The Data Infrastructure for Chemical Safety Assessment (diXa) is a robust and sustainable infrastructure storing toxicogenomics data. A central data warehouse is connected to a portal with links to chemical information and molecular and phenotype data. diXa is publicly available through a user-friendly web interface. New data can be readily deposited into diXa using guidelines and templates available online. Analysis descriptions and tools for interrogating the data are available via the diXa portal. Availability and implementation: http://www.dixa-fp7.eu Contact: [email protected]; [email protected] Supplementary information: Supplementary data are available at Bioinformatics onlin

    Building biomolecular modelling communities through BioExcel Interest Groups

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    BioExcel is an EU-funded Centre of Excellence for computational biomolecular research. Despite the importance and increasing adoption of biomolecular simulation techniques, the user communities in Europe are fragmented, possibly excepting communities built around specific codes (e.g. HADDOCK, GROMACS). Support and maintenance of codes is done by small to mid-sized groups, and there is a noticeable lack of overall interactions to ensure coordinated approaches, knowledge transfer and structured initiatives. The BioExcel vision is to become a focal point for advances in software development, knowledge exchange and support, as well as a networking facilitator for the wider community of computational biomolecular researchers. BioExcel addressed this by creating user-led Interest Groups (IGs), the current IGs are: Entry Level Users, Integrative Modelling, Free energy, Hybrid Methods, Workflows, Industry IG, Training IG. The aim of the IGs are (1) to share BioExcel expertise with members of the groups through workshops, forums and training, (2) to learn from IG members, this could be informal feedback on training needs, software improvement but also more formalised, where IG members join the BioExcel Scientific Advisory Board, (3) enhance the interactions between IG members, including between industry and academia or training professionals. In this poster we present the different Interest Groups, the approaches that each IG has taken to facilitate community building (e.g. newsletter, webinar, online discussions) and what metrics will be used to measure success (e.g. number of active members, workshop attendance). To increase interconnections all IGs are involved in a BioExcel community forum event

    Building biomolecular modelling communities through BioExcel Interest Groups

    Get PDF
    BioExcel is an EU-funded Centre of Excellence for computational biomolecular research. Despite the importance and increasing adoption of biomolecular simulation techniques, the user communities in Europe are fragmented, possibly excepting communities built around specific codes (e.g. HADDOCK, GROMACS). Support and maintenance of codes is done by small to mid-sized groups, and there is a noticeable lack of overall interactions to ensure coordinated approaches, knowledge transfer and structured initiatives. The BioExcel vision is to become a focal point for advances in software development, knowledge exchange and support, as well as a networking facilitator for the wider community of computational biomolecular researchers. BioExcel addressed this by creating user-led Interest Groups (IGs), the current IGs are: Entry Level Users, Integrative Modelling, Free energy, Hybrid Methods, Workflows, Industry IG, Training IG. The aim of the IGs are (1) to share BioExcel expertise with members of the groups through workshops, forums and training, (2) to learn from IG members, this could be informal feedback on training needs, software improvement but also more formalised, where IG members join the BioExcel Scientific Advisory Board, (3) enhance the interactions between IG members, including between industry and academia or training professionals. In this poster we present the different Interest Groups, the approaches that each IG has taken to facilitate community building (e.g. newsletter, webinar, online discussions) and what metrics will be used to measure success (e.g. number of active members, workshop attendance). To increase interconnections all IGs are involved in a BioExcel community forum event

    Phenotypic Characterization of EIF2AK4 Mutation Carriers in a Large Cohort of Patients Diagnosed Clinically With Pulmonary Arterial Hypertension.

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    BACKGROUND: Pulmonary arterial hypertension (PAH) is a rare disease with an emerging genetic basis. Heterozygous mutations in the gene encoding the bone morphogenetic protein receptor type 2 (BMPR2) are the commonest genetic cause of PAH, whereas biallelic mutations in the eukaryotic translation initiation factor 2 alpha kinase 4 gene (EIF2AK4) are described in pulmonary veno-occlusive disease/pulmonary capillary hemangiomatosis. Here, we determine the frequency of these mutations and define the genotype-phenotype characteristics in a large cohort of patients diagnosed clinically with PAH. METHODS: Whole-genome sequencing was performed on DNA from patients with idiopathic and heritable PAH and with pulmonary veno-occlusive disease/pulmonary capillary hemangiomatosis recruited to the National Institute of Health Research BioResource-Rare Diseases study. Heterozygous variants in BMPR2 and biallelic EIF2AK4 variants with a minor allele frequency of <1:10 000 in control data sets and predicted to be deleterious (by combined annotation-dependent depletion, PolyPhen-2, and sorting intolerant from tolerant predictions) were identified as potentially causal. Phenotype data from the time of diagnosis were also captured. RESULTS: Eight hundred sixty-four patients with idiopathic or heritable PAH and 16 with pulmonary veno-occlusive disease/pulmonary capillary hemangiomatosis were recruited. Mutations in BMPR2 were identified in 130 patients (14.8%). Biallelic mutations in EIF2AK4 were identified in 5 patients with a clinical diagnosis of pulmonary veno-occlusive disease/pulmonary capillary hemangiomatosis. Furthermore, 9 patients with a clinical diagnosis of PAH carried biallelic EIF2AK4 mutations. These patients had a reduced transfer coefficient for carbon monoxide (Kco; 33% [interquartile range, 30%-35%] predicted) and younger age at diagnosis (29 years; interquartile range, 23-38 years) and more interlobular septal thickening and mediastinal lymphadenopathy on computed tomography of the chest compared with patients with PAH without EIF2AK4 mutations. However, radiological assessment alone could not accurately identify biallelic EIF2AK4 mutation carriers. Patients with PAH with biallelic EIF2AK4 mutations had a shorter survival. CONCLUSIONS: Biallelic EIF2AK4 mutations are found in patients classified clinically as having idiopathic and heritable PAH. These patients cannot be identified reliably by computed tomography, but a low Kco and a young age at diagnosis suggests the underlying molecular diagnosis. Genetic testing can identify these misclassified patients, allowing appropriate management and early referral for lung transplantation

    Comprehensive Rare Variant Analysis via Whole-Genome Sequencing to Determine the Molecular Pathology of Inherited Retinal Disease

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    Inherited retinal disease is a common cause of visual impairment and represents a highly heterogeneous group of conditions. Here, we present findings from a cohort of 722 individuals with inherited retinal disease, who have had whole-genome sequencing (n = 605), whole-exome sequencing (n = 72), or both (n = 45) performed, as part of the NIHR-BioResource Rare Diseases research study. We identified pathogenic variants (single-nucleotide variants, indels, or structural variants) for 404/722 (56%) individuals. Whole-genome sequencing gives unprecedented power to detect three categories of pathogenic variants in particular: structural variants, variants in GC-rich regions, which have significantly improved coverage compared to whole-exome sequencing, and variants in non-coding regulatory regions. In addition to previously reported pathogenic regulatory variants, we have identified a previously unreported pathogenic intronic variant in CHM\textit{CHM} in two males with choroideremia. We have also identified 19 genes not previously known to be associated with inherited retinal disease, which harbor biallelic predicted protein-truncating variants in unsolved cases. Whole-genome sequencing is an increasingly important comprehensive method with which to investigate the genetic causes of inherited retinal disease.This work was supported by The National Institute for Health Research England (NIHR) for the NIHR BioResource – Rare Diseases project (grant number RG65966). The Moorfields Eye Hospital cohort of patients and clinical and imaging data were ascertained and collected with the support of grants from the National Institute for Health Research Biomedical Research Centre at Moorfields Eye Hospital, National Health Service Foundation Trust, and UCL Institute of Ophthalmology, Moorfields Eye Hospital Special Trustees, Moorfields Eye Charity, the Foundation Fighting Blindness (USA), and Retinitis Pigmentosa Fighting Blindness. M.M. is a recipient of an FFB Career Development Award. E.M. is supported by UCLH/UCL NIHR Biomedical Research Centre. F.L.R. and D.G. are supported by Cambridge NIHR Biomedical Research Centre

    “Be Sustainable”: EOSC-Life Recommendations for Implementation of FAIR Principles in Life Science Data Handling

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    The main goals and challenges for the life science communities in the Open Science framework are to increase reuse and sustainability of data resources, software tools, and workflows, especially in large-scale data-driven research and computational analyses. Here, we present key findings, procedures, effective measures and recommendations for generating and establishing sustainable life science resources based on the collaborative, cross-disciplinary work done within the EOSC-Life (European Open Science Cloud for Life Sciences) consortium. Bringing together 13 European life science research infrastructures, it has laid the foundation for an open, digital space to support biological and medical research. Using lessons learned from 27 selected projects, we describe the organisational, technical, financial and legal/ethical challenges that represent the main barriers to sustainability in the life sciences. We show how EOSC-Life provides a model for sustainable data management according to FAIR (findability, accessibility, interoperability, and reusability) principles, including solutions for sensitive- and industry-related resources, by means of cross-disciplinary training and best practices sharing. Finally, we illustrate how data harmonisation and collaborative work facilitate interoperability of tools, data, solutions and lead to a better understanding of concepts, semantics and functionalities in the life sciences

    Telomerecat: A ploidy-agnostic method for estimating telomere length from whole genome sequencing data.

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    Telomere length is a risk factor in disease and the dynamics of telomere length are crucial to our understanding of cell replication and vitality. The proliferation of whole genome sequencing represents an unprecedented opportunity to glean new insights into telomere biology on a previously unimaginable scale. To this end, a number of approaches for estimating telomere length from whole-genome sequencing data have been proposed. Here we present Telomerecat, a novel approach to the estimation of telomere length. Previous methods have been dependent on the number of telomeres present in a cell being known, which may be problematic when analysing aneuploid cancer data and non-human samples. Telomerecat is designed to be agnostic to the number of telomeres present, making it suited for the purpose of estimating telomere length in cancer studies. Telomerecat also accounts for interstitial telomeric reads and presents a novel approach to dealing with sequencing errors. We show that Telomerecat performs well at telomere length estimation when compared to leading experimental and computational methods. Furthermore, we show that it detects expected patterns in longitudinal data, repeated measurements, and cross-species comparisons. We also apply the method to a cancer cell data, uncovering an interesting relationship with the underlying telomerase genotype

    Bi-allelic loss-of-function CACNA1B mutations in progressive epilepsy-dyskinesia

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    The occurrence of non-epileptic hyperkinetic movements in the context of developmental epileptic encephalopathies is an increasingly recognized phenomenon. Identification of causative mutations provides an important insight into common pathogenic mechanisms that cause both seizures and abnormal motor control. We report bi-allelic loss-of-function CACNA1B variants in six children from three unrelated families whose affected members present with a complex and progressive neurological syndrome. All affected individuals presented with epileptic encephalopathy, severe neurodevelopmental delay (often with regression), and a hyperkinetic movement disorder. Additional neurological features included postnatal microcephaly and hypotonia. Five children died in childhood or adolescence (mean age of death: 9 years), mainly as a result of secondary respiratory complications. CACNA1B encodes the pore-forming subunit of the pre-synaptic neuronal voltage-gated calcium channel Cav2.2/N-type, crucial for SNARE-mediated neurotransmission, particularly in the early postnatal period. Bi-allelic loss-of-function variants in CACNA1B are predicted to cause disruption of Ca2+ influx, leading to impaired synaptic neurotransmission. The resultant effect on neuronal function is likely to be important in the development of involuntary movements and epilepsy. Overall, our findings provide further evidence for the key role of Cav2.2 in normal human neurodevelopment
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