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1.
Nucleic Acids Res ; 50(D1): D129-D140, 2022 01 07.
Article in English | MEDLINE | ID: mdl-34850121

ABSTRACT

The EMBL-EBI Expression Atlas is an added value knowledge base that enables researchers to answer the question of where (tissue, organism part, developmental stage, cell type) and under which conditions (disease, treatment, gender, etc) a gene or protein of interest is expressed. Expression Atlas brings together data from >4500 expression studies from >65 different species, across different conditions and tissues. It makes these data freely available in an easy to visualise form, after expert curation to accurately represent the intended experimental design, re-analysed via standardised pipelines that rely on open-source community developed tools. Each study's metadata are annotated using ontologies. The data are re-analyzed with the aim of reproducing the original conclusions of the underlying experiments. Expression Atlas is currently divided into Bulk Expression Atlas and Single Cell Expression Atlas. Expression Atlas contains data from differential studies (microarray and bulk RNA-Seq) and baseline studies (bulk RNA-Seq and proteomics), whereas Single Cell Expression Atlas is currently dedicated to Single Cell RNA-Sequencing (scRNA-Seq) studies. The resource has been in continuous development since 2009 and it is available at https://www.ebi.ac.uk/gxa.


Subject(s)
Databases, Genetic , Proteins/genetics , Proteomics , Software , Computational Biology , Gene Expression Profiling , Humans , Proteins/chemistry , RNA-Seq , Sequence Analysis, RNA , Single-Cell Analysis
2.
Nat Commun ; 11(1): 3400, 2020 07 07.
Article in English | MEDLINE | ID: mdl-32636365

ABSTRACT

The Pan-Cancer Analysis of Whole Genomes (PCAWG) project generated a vast amount of whole-genome cancer sequencing resource data. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumor types, we provide a user's guide to the five publicly available online data exploration and visualization tools introduced in the PCAWG marker paper. These tools are ICGC Data Portal, UCSC Xena, Chromothripsis Explorer, Expression Atlas, and PCAWG-Scout. We detail use cases and analyses for each tool, show how they incorporate outside resources from the larger genomics ecosystem, and demonstrate how the tools can be used together to understand the biology of cancers more deeply. Together, the tools enable researchers to query the complex genomic PCAWG data dynamically and integrate external information, enabling and enhancing interpretation.


Subject(s)
Computational Biology/methods , Genome, Human , Neoplasms/genetics , Chromothripsis , Data Analysis , Databases, Genetic , Genomics , Humans , Internet , Mutation , Software , User-Computer Interface , Whole Genome Sequencing
3.
Nucleic Acids Res ; 48(D1): D1093-D1103, 2020 01 08.
Article in English | MEDLINE | ID: mdl-31680153

ABSTRACT

Plant Reactome (https://plantreactome.gramene.org) is an open-source, comparative plant pathway knowledgebase of the Gramene project. It uses Oryza sativa (rice) as a reference species for manual curation of pathways and extends pathway knowledge to another 82 plant species via gene-orthology projection using the Reactome data model and framework. It currently hosts 298 reference pathways, including metabolic and transport pathways, transcriptional networks, hormone signaling pathways, and plant developmental processes. In addition to browsing plant pathways, users can upload and analyze their omics data, such as the gene-expression data, and overlay curated or experimental gene-gene interaction data to extend pathway knowledge. The curation team actively engages researchers and students on gene and pathway curation by offering workshops and online tutorials. The Plant Reactome supports, implements and collaborates with the wider community to make data and tools related to genes, genomes, and pathways Findable, Accessible, Interoperable and Re-usable (FAIR).


Subject(s)
Computational Biology/methods , Databases, Genetic , Genomics , Metabolomics , Plants/genetics , Plants/metabolism , Proteomics , Gene Regulatory Networks , Genomics/methods , Humans , Metabolic Networks and Pathways , Metabolomics/methods , Proteomics/methods , Signal Transduction , Web Browser
4.
Mob Genet Elements ; 1(2): 97-102, 2011 Jul.
Article in English | MEDLINE | ID: mdl-22016855

ABSTRACT

The Gypsy Database concerning Mobile Genetic Elements (release 2.0) is a wiki-style project devoted to the phylogenetic classification of LTR retroelements and their viral and host gene relatives characterized from distinct organisms. Furthermore, GyDB 2.0 is concerned with studying mobile elements within genomes. Therefore, an in-progress repository was created for databases with annotations of mobile genetic elements from particular genomes. This repository is called Mobilomics and the first uploaded database contains 549 LTR retroelements and related transposases which have been annotated from the genome of the Pea aphid Acyrthosiphon pisum. Mobilomics is accessible from the GyDB 2.0 project using the URL: http://gydb.org/index.php/Mobilomics.

5.
Nucleic Acids Res ; 39(Database issue): D70-4, 2011 Jan.
Article in English | MEDLINE | ID: mdl-21036865

ABSTRACT

This article introduces the second release of the Gypsy Database of Mobile Genetic Elements (GyDB 2.0): a research project devoted to the evolutionary dynamics of viruses and transposable elements based on their phylogenetic classification (per lineage and protein domain). The Gypsy Database (GyDB) is a long-term project that is continuously progressing, and that owing to the high molecular diversity of mobile elements requires to be completed in several stages. GyDB 2.0 has been powered with a wiki to allow other researchers participate in the project. The current database stage and scope are long terminal repeats (LTR) retroelements and relatives. GyDB 2.0 is an update based on the analysis of Ty3/Gypsy, Retroviridae, Ty1/Copia and Bel/Pao LTR retroelements and the Caulimoviridae pararetroviruses of plants. Among other features, in terms of the aforementioned topics, this update adds: (i) a variety of descriptions and reviews distributed in multiple web pages; (ii) protein-based phylogenies, where phylogenetic levels are assigned to distinct classified elements; (iii) a collection of multiple alignments, lineage-specific hidden Markov models and consensus sequences, called GyDB collection; (iv) updated RefSeq databases and BLAST and HMM servers to facilitate sequence characterization of new LTR retroelement and caulimovirus queries; and (v) a bibliographic server. GyDB 2.0 is available at http://gydb.org.


Subject(s)
Databases, Genetic , Retroelements , Retroviridae/genetics , Terminal Repeat Sequences , Caulimoviridae/classification , Caulimoviridae/genetics , Phylogeny , Retroviridae/classification , Retroviridae Proteins/chemistry , Retroviridae Proteins/classification , Retroviridae Proteins/genetics , Software
6.
Biol Direct ; 4: 41, 2009 Nov 02.
Article in English | MEDLINE | ID: mdl-19883502

ABSTRACT

BACKGROUND: Sequencing projects have allowed diverse retroviruses and LTR retrotransposons from different eukaryotic organisms to be characterized. It is known that retroviruses and other retro-transcribing viruses evolve from LTR retrotransposons and that this whole system clusters into five families: Ty3/Gypsy, Retroviridae, Ty1/Copia, Bel/Pao and Caulimoviridae. Phylogenetic analyses usually show that these split into multiple distinct lineages but what is yet to be understood is how deep evolution occurred in this system. RESULTS: We combined phylogenetic and graph analyses to investigate the history of LTR retroelements both as a tree and as a network. We used 268 non-redundant LTR retroelements, many of them introduced for the first time in this work, to elucidate all possible LTR retroelement phylogenetic patterns. These were superimposed over the tree of eukaryotes to investigate the dynamics of the system, at distinct evolutionary times. Next, we investigated phenotypic features such as duplication and variability of amino acid motifs, and several differences in genomic ORF organization. Using this information we characterized eight reticulate evolution markers to construct phenotypic network models. CONCLUSION: The evolutionary history of LTR retroelements can be traced as a time-evolving network that depends on phylogenetic patterns, epigenetic host-factors and phenotypic plasticity. The Ty1/Copia and the Ty3/Gypsy families represent the oldest patterns in this network that we found mimics eukaryotic macroevolution. The emergence of the Bel/Pao, Retroviridae and Caulimoviridae families in this network can be related with distinct inflations of the Ty3/Gypsy family, at distinct evolutionary times. This suggests that Ty3/Gypsy ancestors diversified much more than their Ty1/Copia counterparts, at distinct geological eras. Consistent with the principle of preferential attachment, the connectivities among phenotypic markers, taken as network-represented combinations, are power-law distributed. This evidences an inflationary mode of evolution where the system diversity; 1) expands continuously alternating vertical and gradual processes of phylogenetic divergence with episodes of modular, saltatory and reticulate evolution; 2) is governed by the intrinsic capability of distinct LTR retroelement host-communities to self-organize their phenotypes according to emergent laws characteristic of complex systems. REVIEWERS: This article was reviewed by Eugene V. Koonin, Eric Bapteste, and Enmanuelle Lerat (nominated by King Jordan).


Subject(s)
Eukaryota/genetics , Gene Regulatory Networks/genetics , Phylogeny , Retroelements/genetics , Terminal Repeat Sequences/genetics , Animals , Caulimoviridae/genetics , Evolution, Molecular , Genetic Markers , Genome/genetics , Phenotype , Retroviridae/genetics
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