Biology subjects

Coppens, F.

Publications and source records attributed to Coppens, F..

6 recordsLinked to original sources

bioRxiv2022

Galaxy Training: A Powerful Framework for Teaching!

There is an ongoing explosion of scientific datasets being generated, brought on by recent technological advances in many areas of the natural sciences. As a result, the life sciences have become increasingly computational in nature, and bioinformatics has taken on a central role in research studies. However, basic computational skills, data analysis and stewardship are still rarely taught in life science educational programs [1], resulting in a skills gap in many of the researchers tasked with analysing these big datasets. In order to address this skills gap and empower researchers to perform their own data analyses, the Galaxy Training Network (GTN) has previously developed the Galaxy Training Platform (https://training.galaxyproject.org); an open access, community-driven framework for the collection of FAIR training materials for data analysis utilizing the user-friendly Galaxy framework as its primary data analysis platform [2]. Since its inception, this training platform has thrived, with the number of tutorials and contributors growing rapidly, and the range of topics extending beyond life sciences to include topics such as climatology, cheminformatics and machine learning. While initially aimed at supporting researchers directly, the GTN framework has proven to be an invaluable resource for educators as well. We have focused our efforts in recent years on adding increased support for this growing community of instructors. New features have been added to facilitate the use of the materials in a classroom setting, simplifying the contribution flow for new materials, and have added a set of train-the-trainer lessons. Here, we present the latest developments in the GTN project, aimed at facilitating the use of the Galaxy Training materials by educators, and its usage in different learning environments.

bioinformatics↗

bioRxiv2021

GPI anchor remodeling by the plant PGAP1 ortholog HLD1 is essential for Papaver self-incompatibility

In eukaryotes, glycosylphosphatidylinositol anchored proteins (GPI-APs) are tethered to the outer leaflet of the plasma membrane where they function as key regulators of a plethora of biological processes. Self-incompatibility (SI) plays a pivotal role regulating fertilization in higher plants through recognition and rejection of self pollen. Here we used Arabidopsis thaliana lines engineered to be self-incompatible by expression of Papaver SI determinants for an SI suppressor screen. We identify HLD1, an ortholog of human GPI-inositol deacylase PGAP1, whose mutation completely abolishes the SI response. We show that HLD1 functions as a GPI-inositol deacylase and that this GPI-remodeling activity is essential for SI. Using GFP-SKU5 as a representative GPI-AP, we show that HLD1 mutation does not affect GPI-AP production and targeting, but alters the configuration of mature GPI-APs. This prevents GPI-AP release from the plasma membrane, suggesting that this process plays a critical role in the regulation of SI. Our data not only identify GPI anchoring as a new pathway of SI providing new directions to investigate SI mechanisms, but identifies for the first time a function for GPI-AP remodeling by inositol deacylation in plants. One sentence summaryThe Papaver self-incompatibility response requires GPI-anchor modification by HLD1, an ortholog of the mammalian PGAP1.

plant biology↗

bioRxiv2021

Freely accessible ready to use global infrastructure for SARS-CoV-2 monitoring

The COVID-19 pandemic is the first global health crisis to occur in the age of big genomic data.Although data generation capacity is well established and sufficiently standardized, analytical capacity is not. To establish analytical capacity it is necessary to pull together global computational resources and deliver the best open source tools and analysis workflows within a ready to use, universally accessible resource. Such a resource should not be controlled by a single research group, institution, or country. Instead it should be maintained by a community of users and developers who ensure that the system remains operational and populated with current tools. A community is also essential for facilitating the types of discourse needed to establish best analytical practices. Bringing together public computational research infrastructure from the USA, Europe, and Australia, we developed a distributed data analysis platform that accomplishes these goals. It is immediately accessible to anyone in the world and is designed for the analysis of rapidly growing collections of deep sequencing datasets. We demonstrate its utility by detecting allelic variants in high-quality existing SARS-CoV-2 sequencing datasets and by continuous reanalysis of COG-UK data. All workflows, data, and documentation is available at https://covid19.galaxyproject.org.

bioinformatics↗

bioRxiv2020

Expanding the Galaxy's reference data

SummaryProperly and effectively managing reference datasets is an important task for many bioinformatics analyses. Refgenie is a reference asset management system that allows to easily organize, retrieve, and share such datasets. Here, we describe the integration of refgenie into the Galaxy platform. Server administrators are able to configure Galaxy to make use of reference datasets made available on a refgenie instance. Additionally, a Galaxy Data Manager tool has been developed to provide a graphical interface to refgenies remote reference retrieval functionality. A large collection of reference datasets has also been made available using the CVMFS repository from GalaxyProject.org, with mirrors across the United States, Canada, Europe, and Australia, enabling easy use outside of Galaxy. Availability and implementationThe ability of Galaxy to use refgenie assets was added to the core Galaxy framework in version 20.05, which is available from https://github.com/galaxyproject/galaxy under the Academic Free License version 3.0. The refgenie Data Manager tool can be installed via the Galaxy ToolShed, with source code managed at https://github.com/BlankenbergLab/galaxy-tools-blankenberg/tree/main/data_managers/data_manager_refgenie_pull and released using an MIT license.

bioinformatics↗

bioRxiv2019

The Arabidopsis condensin CAP-D subunits arrange interphase chromatin

Condensins are best known for their role in shaping chromosomes. However, other functions as organizing interphase chromatin and transcriptional control have been reported in yeasts and animals. Yeasts encode one condensin complex, while higher eukaryotes have two of them (condensin I and II). Both, condensin I and II, are conserved in Arabidopsis thaliana, but so far little is known about their function. Here we show that the A. thaliana CAP-D2 (condensin I) and CAP-D3 (condensin II) subunits are highly expressed in mitotically active tissues. In silico and pull-down experiments indicate that both CAP-D proteins interact with the other condensin I and II subunits. Our data suggest that the expression, localization and composition of the condensin complexes in A. thaliana are similar as in other higher eukaryotes. Previous experiments showed that the lack of A. thaliana CAP-D3 leads to centromere association during interphase. To study the function of CAP-D3 in chromatin organization more in detail we compared the nuclear distribution of rDNA, of centromeric chromocenters and of different epigenetic marks, as well as the nuclear size between wild-type and cap-d3 mutants. In these mutants an association of heterochromatic sequences occurs, but nuclear size and the general methylation and acetylation patterns remain unchanged. In addition, transcriptome analyses revealed a moderate influence of CAP-D3 on general transcription, but a stronger one on transcription of stress-related genes. We propose a model for the CAP-D3 function during interphase, where CAP-D3 localizes in euchromatin loops to stiff them, and consequently separates centromeric regions and 45S rDNA repeats.

cell biology↗

bioRxiv2017

PhyD3: a phylogenetic tree viewer with extended phyloXML support for functional genomics data visualization

MotivationComparative and evolutionary studies utilise phylogenetic trees to analyse and visualise biological data. Recently, several web-based tools for the display, manipulation, and annotation of phylogenetic trees, such as iTOL and Evolview, have released updates to be compatible with the latest web technologies. While those web tools operate an open server access model with a multitude of registered users, a feature-rich open source solution using current web technologies is not available.\n\nResultsHere, we present an extension of the widely used PhyloXML standard with several new options to accommodate functional genomics or annotation datasets for advanced visualization. Furthermore, PhyD3 has been developed as a lightweight tool using the JavaScript library D3.js to achieve a state-of-the-art phylogenetic tree visualisation in the web browser, with support for advanced annotations. The current implementation is open source, easily adaptable and easy to implement in third parties web sites.\n\nAvailabilityMore information about PhyD3 itself, installation procedures, and implementation links are available at http://phyd3.bits.vib.be and at http://github.com/vibbits/phyd3/.\n\nContactbits@vib.be

bioinformatics↗